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a/data/.DS_Store b/data/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..6e0065fc26a8a4b5aeef6df83c1bf87e3b0b5489 Binary files /dev/null and b/data/.DS_Store differ diff --git a/data/Run 1/.DS_Store b/data/Run 1/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..022cc005cb68888f7b0dadf7ea4545a99d70ea8c Binary files /dev/null and b/data/Run 1/.DS_Store differ diff --git a/data/Run 1/RESULT Run 1/.DS_Store b/data/Run 1/RESULT Run 1/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..23d69a60bcc82831b85deaef293ddf91d2e0f010 Binary files /dev/null and b/data/Run 1/RESULT Run 1/.DS_Store differ diff --git a/data/Run 1/RESULT Run 1/.claude/launch.json b/data/Run 1/RESULT Run 1/.claude/launch.json new file mode 100644 index 0000000000000000000000000000000000000000..040a45112e8a96614bb158901a5b4b575a2b4a8b --- /dev/null +++ b/data/Run 1/RESULT Run 1/.claude/launch.json @@ -0,0 +1,11 @@ +{ + "version": "0.0.1", + "configurations": [ + { + "name": "app", + "runtimeExecutable": "python3", + "runtimeArgs": ["-m", "http.server", "8765", "--bind", "127.0.0.1", "--directory", "app"], + "port": 8765 + } + ] +} diff --git a/data/Run 1/RESULT Run 1/README.md b/data/Run 1/RESULT Run 1/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e4fbc48e114dabbdef2a65be29a6633bcfb7359d --- /dev/null +++ b/data/Run 1/RESULT Run 1/README.md @@ -0,0 +1,58 @@ +# Hierarchical Fracture Lab — deliverables + +Browser-based generative design and fracture-discovery platform for hierarchical cellular networks derived from the +five supplied reference images, with a validated beam-network fracture solver, a complete computational study +(345 logged runs + 68 archived preliminary runs), publication figures, movies, printable STL geometry, and a compiled +LaTeX report. + +## Start here +* **Application**: open `app/HierarchicalFractureLab.html` in a modern browser (Chrome/Edge/Firefox/Safari; no server or + internet needed — everything is inlined). Generate → Run. Panel 7 runs the validation suite; panel 9 exports data, + STL, SVG, PNG and movies; the "Study presets" menu in panel 2 loads the designs of the study and the print set. + URL options: `?preset=&autorun=1&replay=1&color=util|level|interface|N|disp|state|failOrder|thickness&view=iso&extrude=1`. +* **Report**: `report/report.pdf` (source `report/report.tex`, tables in `report/tables/`, figures in `report/figures/`). +* **Printable designs**: `stl/` — 12 designs × 4 thickening variants (`STL_README.md` explains each design and variant). +* **Manifest**: `manifest.json` — versions, configuration, dates, parameter ranges, seeds and SHA-256 checksums of every file. + +## Layout +``` +app/HierarchicalFractureLab.html single-file application (core + Three.js r128 + OrbitControls + reference thumbnails) +app/src/core/*.js solver core modules (RNG/geometry, generator, beam solver, fracture driver, metrics, validation, STL/SVG) +app/src/hfx_core.js built core (used by the app and by the Node study driver) +app/src/ui/*.html|js application UI (CSS/HTML skeleton, Three.js viewer, application logic) +app/src/build.js build script (node build.js --app) +app/SOLVER_DESCRIPTION.md description of the numerical solver +reference_images/ the five reference images (originals + 512 px thumbnails used in the app) +validation/ run_validation.js, validation_results.json, validation_report.md (44 tests, all pass) +study/hfx_batch.js parallel study driver (worker threads); plans/ stage 1–5 plan files; study_base.js +study/experiment_log.jsonl machine-readable log: one JSON line per run (params, seed, reason, hypothesis, metrics, files, checksums) +study/runs// results.json, steps.csv, events.csv, members.csv, member_history.csv, geometry.json, snapshots.json, snapshot.png +study/hypotheses.md competing hypotheses recorded after stages 1–2 and their outcomes +study/predictions.json|.md holdout predictions recorded before stage 5 was run +study/prelim/ archived preliminary family (frame side walls) with its own log and runs +analysis/*.py analysis and figure scripts (hfx_analysis, load_sharing, make_figures, make_tables, render_*) +analysis/figures/ all figures as PDF, SVG and PNG +analysis/processed/ flat experiment table, design summary, load-sharing statistics, holdout comparison, key numbers +analysis/gallery/ generator gallery (contact sheet) +movies/ MP4 movies of complete runs (README.md) +stl/ STL set + stl_manifest.json + STL_README.md +screenshots/ application screenshots (take_screenshots.py: Playwright script that reproduces them) +task_prompt.md the original task statement +``` + +## Reproducing +```bash +node app/src/build.js --app # rebuild hfx_core.js and the single-file app +node validation/run_validation.js # validation suite (Node) +node study/hfx_batch.js study/plans/stage1_baseline.js # ... stage2_recon.js, stage3_hypotheses.js, stage4_refine.js, stage5_holdout.js +python3 analysis/load_sharing.py && python3 analysis/make_figures.py && python3 analysis/make_tables.py +python3 analysis/render_run_images.py; bash analysis/render_all_movies.sh +node stl/make_stl_set.js +cd report && pdflatex report.tex (×3) +``` +Requirements: Node ≥ 18 (study driver), Python 3 with numpy/pandas/scipy/matplotlib/Pillow (analysis), ffmpeg (movies), +pdflatex (report). 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+ + + + + + + + + + + + + + + + + + + + + diff --git a/data/Run 1/RESULT Run 1/analysis/gallery.js b/data/Run 1/RESULT Run 1/analysis/gallery.js new file mode 100644 index 0000000000000000000000000000000000000000..47a7fb0c5eb19790f06cbc445a7a2299ea619301 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/gallery.js @@ -0,0 +1,33 @@ +const fs=require('fs'), path=require('path'); +const HFX=require(path.join(__dirname,'..','app','src','hfx_core.js')); +const out=path.join(__dirname,'gallery'); fs.mkdirSync(out,{recursive:true}); +const cases=[ + ['ordered_D3b4', {depth:3,branching:4,disorder:0}], + ['ordered_D4b4_rt05', {depth:4,branching:4,disorder:0,thicknessRatio:0.5}], + ['ordered_D8b2', {depth:8,branching:2,disorder:0}], + ['ordered_D10b2', {depth:10,branching:2,disorder:0,thicknessRatio:0.7}], + ['dis035_D3b4', {depth:3,branching:4,disorder:0.35,seed:7}], + ['dis07_D3b4', {depth:3,branching:4,disorder:0.7,seed:7}], + ['dis10_D3b4', {depth:3,branching:4,disorder:1.0,seed:7}], + ['dis10_D4b4', {depth:4,branching:4,disorder:1.0,seed:3}], + ['dis10_D6b3', {depth:6,branching:3,disorder:1.0,seed:3,thicknessRatio:0.7}], + ['flat_D0_8x8', {n0x:8,n0y:8,depth:0,disorder:0}], + ['flat_D0_8x8_dis1', {n0x:8,n0y:8,depth:0,disorder:1,seed:2}], + ['stag_D3b4_dis0', {depth:3,branching:4,layout:'staggered',disorder:0}], + ['stag_D3b6_dis03', {depth:3,branching:6,layout:'staggered',disorder:0.3,seed:5}], + ['radial_D3b5_dis0', {depth:3,branching:5,layout:'radial',disorder:0}], + ['radial_D4b5_dis03', {depth:4,branching:5,layout:'radial',disorder:0.3,seed:4}], + ['red1_D3b4_dis0', {depth:3,branching:4,disorder:0,redundancy:1}], + ['red05_D3b4_dis05', {depth:3,branching:4,disorder:0.5,redundancy:0.5,seed:9}], + ['con07_D3b4_dis05', {depth:3,branching:4,disorder:0.5,connectivity:0.7,seed:9}], + ['notch_D3b4_dis035', {depth:3,branching:4,disorder:0.35,defectType:'notch',defectX:0.0,defectY:0.5,defectSize:0.12,seed:7}], + ['missing_D3b4', {depth:3,branching:4,disorder:0.35,missingFraction:0.08,seed:7}], + ['n0_2x3_D2b4_dis02', {n0x:2,n0y:3,depth:2,branching:4,disorder:0.2,seed:11}], + ['fullframe_D3b4', {depth:3,branching:4,disorder:0.3,frameMode:'full',seed:12}], +]; +const lines=[]; +for (const [name,pp] of cases){ const st=HFX.generateStructure(Object.assign({relDensity:0.2},pp)); + fs.writeFileSync(path.join(out,name+'.json'),JSON.stringify(HFX.geometryJSON(st))); + lines.push(name.padEnd(22)+' nodes='+String(st.stats.nodes).padStart(5)+' el='+String(st.stats.elements).padStart(5)+' if='+String(st.stats.interfaces).padStart(4)+' rho='+st.stats.relDensityDesign.toFixed(4)+' grip='+st.stats.gripLineMaterial.toFixed(4)+' t0='+st.t0.toFixed(4)+' tmin='+st.stats.tMin.toExponential(2)+' wallSl='+st.stats.minSlendernessLevel.toFixed(1)+' elSl='+st.stats.minElementSlenderness.toFixed(1)+' levels='+st.levelStats.map(l=>l.materialFraction.toFixed(2)).join('/')); +} +console.log(lines.join('\n')); diff --git a/data/Run 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+#!/usr/bin/env python3 +"""Shared analysis utilities for the HFX study: load the experiment log, aggregate over seeds, plotting style.""" +import json, os, math +import numpy as np +import pandas as pd +import matplotlib +matplotlib.use('Agg') +import matplotlib.pyplot as plt + +ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) +STUDY = os.path.join(ROOT, 'study') +LOG = os.path.join(STUDY, 'experiment_log.jsonl') +FIG = os.path.join(ROOT, 'analysis', 'figures') +PROC = os.path.join(ROOT, 'analysis', 'processed') +os.makedirs(FIG, exist_ok=True); os.makedirs(PROC, exist_ok=True) + +plt.rcParams.update({'font.size': 9, 'axes.labelsize': 9.5, 'axes.titlesize': 10, 'legend.fontsize': 8, 'xtick.labelsize': 8.5, 'ytick.labelsize': 8.5, + 'figure.dpi': 120, 'savefig.dpi': 300, 'axes.spines.top': False, 'axes.spines.right': False, 'lines.linewidth': 1.4, 'pdf.fonttype': 42}) +PAL = {'ord': '#1f77b4', 'dis': '#d62728', 'hier': '#2ca02c', 'grey': '#7f7f7f', 'a': '#1f77b4', 'b': '#ff7f0e', 'c': '#2ca02c', 'd': '#d62728', 'e': '#9467bd', 'f': '#8c564b'} +MODE_COL = {'abrupt-brittle': '#d62728', 'intermediate': '#ff7f0e', 'progressive': '#2ca02c', 'no-failure': '#7f7f7f'} + +PARAM_KEYS = ['n0x', 'n0y', 'depth', 'branching', 'layout', 'disorder', 'disorderMinLevel', 'seed', 'thicknessRatio', 'relDensity', 'redundancy', 'connectivity', + 'interfaceMode', 'interfaceStrengthRatio', 'interfaceStiffnessRatio', 'strengthCV', 'strengthLevelRatio', 'failStrain', 'E', 'includeFrame', 'frameMode', + 'defectType', 'defectSize', 'defectX', 'defectY', 'missingFraction', 'H', 'gripType', 'dispIncrement', 'maxDisp', 'exactEvents', 'bendingFactor'] +METRIC_KEYS = ['K0', 'EeffRel', 'Fpeak', 'sigmaPeakRel', 'strengthRel', 'dFirst', 'dPeak', 'dFinal', 'finalFailureReached', 'Wf', 'WfPerArea', 'WfRel', 'Wtotal', 'nFailed', 'nDamaged', + 'fractionFailed', 'nEvents', 'nCascades', 'maxCascade', 'prePeakFailures', 'prePeakFraction', 'abruptness', 'postPeakWorkFraction', 'localizationIndex', 'participationRatio', + 'damageBandStd', 'damageBandCentre', 'interfaceFailures', 'interfaceFailureFraction', 'interfaceFailureShare', 'meanFailLevel', 'firstFailLevel', 'firstFailInterface', + 'fractureMode', 'damagePattern', 'fractureLabel', 'maxResidual', 'maxResidualAbs', 'residualExceeded', 'iterationCapHits', 'nonPositivePivots', 'energyBalanceError', + 'steps', 'rebuilds', 'solves', 'elapsedMs'] + +def load_log(path=LOG): + rows = [] + with open(path) as f: + for line in f: + line = line.strip() + if not line: continue + r = json.loads(line) + row = {'runId': r['runId'], 'batch': r['batch'], 'stage': r['stage'], 'designId': r['designId'], 'seed': r['seed'], 'status': r['status'], 'reason': r.get('reason', ''), 'hypothesis': r.get('hypothesis', ''), 'dir': r.get('dir', ''), 'hash': r.get('hash', '')} + for k in PARAM_KEYS: row['p_' + k] = r['params'].get(k) + if r['status'] == 'ok': + for k in METRIC_KEYS: row[k] = r['metrics'].get(k) + row['converged'] = r['converged']; row['simStatus'] = r['simStatus'] + ss = r['structureStats'] + for k in ['nodes', 'activeElements', 'leafCells', 'relDensityDesign', 'relDensityActual', 't0', 'tMin', 'meanCoordination', 'interfaces', 'braces', 'minSlendernessLevel']: row['s_' + k] = ss.get(k) + row['levelMaterial'] = [l['materialFraction'] for l in r['levelStats']] + row['totalMs'] = r['timing']['totalMs'] + rows.append(row) + df = pd.DataFrame(rows) + return df + +def agg(df, by='designId'): + """Mean / std / n over seeds for the numeric metrics.""" + num = ['K0', 'Fpeak', 'Wf', 'WfRel', 'dFirst', 'dPeak', 'dFinal', 'nFailed', 'prePeakFailures', 'abruptness', 'localizationIndex', 'interfaceFailures', 'fractionFailed', 'postPeakWorkFraction', 'EeffRel', 'strengthRel'] + g = df[df.status == 'ok'].groupby(by) + out = g[num].agg(['mean', 'std', 'count']) + out.columns = ['_'.join(c) for c in out.columns] + first = g.first() + for k in ['p_depth', 'p_branching', 'p_disorder', 'p_thicknessRatio', 'p_interfaceStrengthRatio', 'p_redundancy', 'p_relDensity', 'p_strengthCV', 'p_layout', 'reason', 'hypothesis', 'stage', 'batch']: + if k in first: out[k] = first[k] + out['modes'] = g['fractureMode'].agg(lambda s: '/'.join(sorted(set(s)))) + return out + +def load_run(dir_rel): + d = os.path.join(ROOT, dir_rel) + res = json.load(open(os.path.join(d, 'results.json'))) + geom = json.load(open(os.path.join(d, 'geometry.json'))) + snaps = json.load(open(os.path.join(d, 'snapshots.json'))) + return res, geom, snaps + +def savefig(fig, name, formats=('pdf', 'png', 'svg')): + for ext in formats: + fig.savefig(os.path.join(FIG, name + '.' + ext), bbox_inches='tight') + print('saved', name) + +if __name__ == '__main__': + df = load_log() + print(df.shape, 'runs;', (df.status == 'ok').sum(), 'ok;', df.converged.sum() if 'converged' in df else 0, 'converged') + a = agg(df) + pd.set_option('display.width', 250); pd.set_option('display.max_columns', 40) + print(a[['K0_mean', 'Fpeak_mean', 'Wf_mean', 'abruptness_mean', 'localizationIndex_mean', 'prePeakFailures_mean', 'modes']].round(5)) + df.to_csv(os.path.join(PROC, 'experiment_log_flat.csv'), index=False) + a.to_csv(os.path.join(PROC, 'design_summary.csv')) diff --git a/data/Run 1/RESULT Run 1/analysis/load_sharing.py b/data/Run 1/RESULT Run 1/analysis/load_sharing.py new file mode 100644 index 0000000000000000000000000000000000000000..4317477261635a08fb2f5063f778ecd2dca4f972 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/load_sharing.py @@ -0,0 +1,60 @@ +#!/usr/bin/env python3 +"""Mechanistic load-sharing statistics at the first failure event, computed from the exported per-member data +(utilisation per unit displacement of the intact structure x displacement at first failure).""" +import os, json, sys +import numpy as np, pandas as pd +from hfx_analysis import load_log, ROOT, PROC + +def stats_for_run(dir_rel, dFirst, **kwargs): + m = pd.read_csv(os.path.join(ROOT, dir_rel, 'members.csv')) + m = m[m.absent == 0] + w = m['utilInitial_perUnitDisp'].values * dFirst # utilisation of every member at the first failure event + w = np.clip(w, 0, None) + N = len(w); wmax = w.max() if N else np.nan + out = {} + out['ls_mean_over_max'] = w.mean() / wmax if wmax > 0 else np.nan + out['ls_participation'] = (w.sum() ** 2) / (N * (w ** 2).sum()) if (w ** 2).sum() > 0 else np.nan + out['ls_frac_ge0.5'] = float((w >= 0.5 * wmax).mean()) + out['ls_frac_ge0.8'] = float((w >= 0.8 * wmax).mean()) + out['ls_cv'] = w.std() / w.mean() if w.mean() > 0 else np.nan + out['ls_gini'] = gini(w) + # dominant load path: largest single-member share of the reaction force (axial force per unit displacement / K0) + Nax = m['NInitial_perUnitDisp'].values + K0 = kwargs.get('K0', np.nan) + out['lp_max_share'] = float(np.abs(Nax).max() / K0) if K0 > 0 else np.nan + # share of the reaction carried by level-0 members crossing the mid-height line y = H/2 + y1, y2 = m['y1'].values, m['y2'].values + yc = 15.0 / 32.0 # cut line between grid lines of the 16x16-equivalent ordered designs + cross = ((y1 - yc) * (y2 - yc) < 0) + lvl = m['level'].values + tot = np.abs(Nax[cross]).sum() + out['lp_level0_share'] = float(np.abs(Nax[cross & (lvl == 0)]).sum() / tot) if tot > 0 else np.nan + out['lp_top3_share'] = float(np.sort(np.abs(Nax[cross]))[-3:].sum() / tot) if tot > 0 else np.nan + out['ls_frac_tension'] = float((Nax > 1e-3 * np.abs(Nax).max()).mean()) if np.abs(Nax).max() > 0 else np.nan + # bending share of the fibre strain at the most utilised member: util - axial strain / eps_c + return out + +def gini(x): + x = np.sort(np.asarray(x, dtype=float)); n = len(x) + if n == 0 or x.sum() == 0: return np.nan + return (2 * np.sum(np.arange(1, n + 1) * x) / (n * x.sum())) - (n + 1) / n + +if __name__ == '__main__': + df = load_log() + rows = [] + for _, r in df[df.status == 'ok'].iterrows(): + try: + s = stats_for_run(r['dir'], r['dFirst'], K0=r['K0']); s['runId'] = r['runId']; rows.append(s) + except Exception as e: + print('skip', r['runId'], e) + ls = pd.DataFrame(rows).set_index('runId') + ls.to_csv(os.path.join(PROC, 'load_sharing.csv')) + d = df.set_index('runId').join(ls) + from scipy.stats import spearmanr, pearsonr + print('n =', len(d)) + for k in ['ls_mean_over_max', 'ls_participation', 'ls_frac_ge0.5', 'ls_frac_ge0.8', 'ls_cv', 'ls_gini', 'ls_frac_tension', 'lp_max_share', 'lp_level0_share', 'lp_top3_share']: + ok = d[[k, 'abruptness']].dropna() + print('%-20s Spearman rho vs abruptness = %+.3f (p=%.1e), vs prePeakFailures = %+.3f, vs Wf = %+.3f' % (k, spearmanr(ok[k], ok['abruptness'])[0], spearmanr(ok[k], ok['abruptness'])[1], spearmanr(d[[k,'prePeakFailures']].dropna()[k], d[[k,'prePeakFailures']].dropna()['prePeakFailures'])[0], spearmanr(d[[k,'Wf']].dropna()[k], d[[k,'Wf']].dropna()['Wf'])[0])) + g = d.groupby('designId')[['ls_frac_ge0.8', 'lp_max_share', 'lp_top3_share', 'abruptness', 'prePeakFailures', 'Wf']].mean().sort_values('abruptness') + pd.set_option('display.width', 200); pd.set_option('display.max_rows', 200) + print(g.round(3).to_string()) diff --git a/data/Run 1/RESULT Run 1/analysis/make_figures.py b/data/Run 1/RESULT Run 1/analysis/make_figures.py new file mode 100644 index 0000000000000000000000000000000000000000..4570fb3bf814e6b9ed5c562e94aa78041bb13471 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/make_figures.py @@ -0,0 +1,272 @@ +#!/usr/bin/env python3 +"""Publication figures for the HFX hierarchical fracture study. Run after the study stages; re-run after the holdouts.""" +import os, json, sys, math +import numpy as np, pandas as pd +import matplotlib; matplotlib.use('Agg') +import matplotlib.pyplot as plt +from matplotlib import cm, colors, gridspec +from matplotlib.lines import Line2D +from hfx_analysis import load_log, agg, load_run, savefig, ROOT, FIG, PROC, MODE_COL +from render_structure import render +import matplotlib.image as mpimg + +df = load_log(); df = df[df.status == 'ok'].copy() +LS = os.path.join(PROC, 'load_sharing.csv') +if os.path.exists(LS): df = df.set_index('runId').join(pd.read_csv(LS).set_index('runId')).reset_index() +df['f0'] = df['levelMaterial'].apply(lambda l: l[0] if isinstance(l, list) and len(l) else np.nan) +df['Wf_uJ'] = df['Wf'] * 1e6; df['Fpeak_m'] = df['Fpeak'] * 1e3 +A = agg(df) +A['f0'] = df.groupby('designId')['f0'].mean() +A['dml'] = df.groupby('designId')['p_disorderMinLevel'].first() +A['fmode'] = df.groupby('designId')['fractureMode'].agg(lambda s: s.mode().iloc[0]) +main = df[df.stage != 'holdout'] +print('runs', len(df), 'designs', df.designId.nunique(), 'seeds per design: min', df.groupby('designId').size().min(), 'median', df.groupby('designId').size().median()) + +def errbar(ax, x, y, ystd, **kw): + ax.errorbar(x, y, yerr=ystd, capsize=2, **kw) + +def design_rows(ids): + return A.loc[[i for i in ids if i in A.index]] + +# ------------------------------------------------------------------ Fig 1: references, hierarchy, generated specimens +def fig1(): + fig = plt.figure(figsize=(12, 6.4)) + gs = gridspec.GridSpec(2, 5, height_ratios=[1, 1.15], hspace=0.05, wspace=0.12) + refs = ['ref1_nested_rings_wire_mesh', 'ref2_organic_thread_net', 'ref3_polygonal_cells_inner_venation', 'ref4_triangulated_lattice_defects', 'ref5_leaf_venation_hierarchy'] + caps = ['(1) nested rings:\nclosed loops, slender wires', '(2) thread net:\norganic disorder, redundancy', '(3) cells with inner veins:\nnested subdivision', '(4) triangulated lattice:\norder, braces, defects', '(5) leaf venation:\nthickness hierarchy, T-junctions'] + for i, (r, c) in enumerate(zip(refs, caps)): + ax = fig.add_subplot(gs[0, i]); ax.imshow(mpimg.imread(os.path.join(ROOT, 'reference_images', r + '_512.jpg'))); ax.set_xticks([]); ax.set_yticks([]); ax.set_title(c, fontsize=8.5) + specs = [('B2_ref_ord', 'ordered nested (δ = 0)'), ('E4_L3_dis0.35_rt0.6', 'level-selective (finest level organic)'), ('B2_ref', 'disordered (δ = 0.35)'), ('R_dis1', 'organic (δ = 1)'), ('E5_ord_red1', 'ordered + full bracing')] + for i, (d, t) in enumerate(specs): + ax = fig.add_subplot(gs[1, i]) + row = df[df.designId == d].iloc[0]; res, geom, snaps = load_run(row['dir']) + render(geom, ax, color_by='level', title=t, frame=True) + ax.set_xlabel('D=%d b=%d r_t=%.2g ρ=%.2f' % (row.p_depth, row.p_branching, row.p_thicknessRatio, row.s_relDensityDesign), fontsize=8) + handles = [Line2D([0], [0], color=c, lw=3, label='level %d' % k) for k, c in enumerate(['#d62728', '#ff7f0e', '#bcbd22', '#2ca02c'])] + fig.legend(handles=handles, loc='lower center', ncol=4, frameon=False, bbox_to_anchor=(0.5, 0.01)) + fig.suptitle('Reference images (top) and members of the generated hierarchical cellular-network family coloured by hierarchy level (bottom; line width ∝ member thickness)', fontsize=10, y=0.99) + savefig(fig, 'fig1_references_and_family') + +# ------------------------------------------------------------------ Fig 2: design-space coverage +def fig2(): + fig, axes = plt.subplots(2, 4, figsize=(12, 5.6)); axes = axes.ravel() + pars = [('p_depth', 'hierarchy depth D'), ('p_branching', 'branching ratio b'), ('p_disorder', 'geometric disorder δ'), ('p_thicknessRatio', 'thickness ratio r_t'), + ('p_interfaceStrengthRatio', 'interface strength s_int'), ('p_redundancy', 'redundancy (braces)'), ('p_strengthCV', 'strength CV'), ('f0', 'level-0 material fraction f0')] + stage_col = {'baseline': '#7f7f7f', 'reconnaissance': '#1f77b4', 'hypothesis-tests': '#2ca02c', 'refinement': '#ff7f0e', 'holdout': '#d62728'} + for ax, (k, lab) in zip(axes, pars): + for st, col in stage_col.items(): + sub = df[df.stage == st] + if len(sub): ax.scatter(sub[k], sub['Wf_uJ'], s=12, alpha=0.7, color=col, label=st, edgecolor='none') + ax.set_xlabel(lab); ax.set_ylabel('work to failure W_f [10⁻⁶ E_s W² b_z]'); ax.set_yscale('log') + axes[0].legend(frameon=False, fontsize=7) + fig.suptitle('Coverage of the design space: every simulated run (n = %d runs, %d designs) by study stage; vertical axis = work to failure' % (len(df), df.designId.nunique()), fontsize=10) + fig.tight_layout(); savefig(fig, 'fig2_design_space_coverage') + +# ------------------------------------------------------------------ Fig 3: stiffness vs work to failure, Pareto fronts +def pareto_front(x, y): + idx = np.argsort(-x); front = []; best = -np.inf + for i in idx: + if y[i] > best: front.append(i); best = y[i] + return np.array(front) + +def fig3(): + fig, axes = plt.subplots(1, 3, figsize=(13, 4.3)) + B = A[A.stage != 'holdout'] if 'stage' in A else A + # (a) K0 vs Wf + ax = axes[0] + sc = ax.scatter(main['K0'], main['Wf_uJ'], c=main['abruptness'], cmap='coolwarm', vmin=0.15, vmax=1.0, s=10, alpha=0.5, edgecolor='none') + ax.scatter(B['K0_mean'], B['Wf_mean'] * 1e6, c=B['abruptness_mean'], cmap='coolwarm', vmin=0.15, vmax=1.0, s=34, edgecolor='k', linewidth=0.4) + fr = pareto_front(B['K0_mean'].values, B['Wf_mean'].values * 1e6) + o = np.argsort(B['K0_mean'].values[fr]); ax.plot(B['K0_mean'].values[fr][o], B['Wf_mean'].values[fr][o] * 1e6, 'k--', lw=1, label='Pareto front (max K0, max W_f)') + for i in fr: ax.annotate(B.index[i].replace('_', ' '), (B['K0_mean'].values[i], B['Wf_mean'].values[i] * 1e6), fontsize=6, xytext=(3, 3), textcoords='offset points') + ax.set_xlabel('initial stiffness K_0 [E_s b_z]'); ax.set_ylabel('work to failure W_f [10⁻⁶ E_s W² b_z]'); ax.set_yscale('log'); ax.legend(frameon=False, fontsize=7) + cb = fig.colorbar(sc, ax=ax, fraction=0.05, pad=0.02); cb.set_label('abruptness (max drop / F_peak)') + ax.set_title('(a) stiffness – work to failure', fontsize=9) + # (b) Wf vs abruptness (damage tolerance trade-off) + ax = axes[1] + ax.scatter(main['abruptness'], main['Wf_uJ'], c=main['K0'], cmap='viridis', s=10, alpha=0.5, edgecolor='none') + sc2 = ax.scatter(B['abruptness_mean'], B['Wf_mean'] * 1e6, c=B['K0_mean'], cmap='viridis', s=34, edgecolor='k', linewidth=0.4) + fr = pareto_front(-B['abruptness_mean'].values, B['Wf_mean'].values * 1e6) + o = np.argsort(B['abruptness_mean'].values[fr]); ax.plot(B['abruptness_mean'].values[fr][o], B['Wf_mean'].values[fr][o] * 1e6, 'k--', lw=1, label='Pareto front (min abruptness, max W_f)') + for i in fr: ax.annotate(B.index[i].replace('_', ' '), (B['abruptness_mean'].values[i], B['Wf_mean'].values[i] * 1e6), fontsize=6, xytext=(3, 3), textcoords='offset points') + ax.set_xlabel('abruptness A (largest force drop / F_peak)'); ax.set_ylabel('work to failure W_f [10⁻⁶ E_s W² b_z]'); ax.set_yscale('log'); ax.legend(frameon=False, fontsize=7) + cb = fig.colorbar(sc2, ax=ax, fraction=0.05, pad=0.02); cb.set_label('K_0 [E_s b_z]') + ax.set_title('(b) damage tolerance – work to failure', fontsize=9) + # (c) Wf vs elastic energy at peak + ax = axes[2] + Ue = 0.5 * main['Fpeak'] * main['dPeak'] * 1e6 + ax.scatter(Ue, main['Wf_uJ'], c=[MODE_COL.get(m, '#333') for m in main['fractureMode']], s=12, alpha=0.7, edgecolor='none') + lim = [min(Ue.min(), main['Wf_uJ'].min()) * 0.8, max(Ue.max(), main['Wf_uJ'].max()) * 1.3] + ax.plot(lim, lim, 'k-', lw=0.8, label='W_f = ½ F_peak d_peak'); ax.plot(lim, [3 * l for l in lim], 'k:', lw=0.8, label='3 × ') + ax.set_xscale('log'); ax.set_yscale('log'); ax.set_xlabel('elastic energy at peak ½ F_peak d_peak [10⁻⁶ E_s W² b_z]'); ax.set_ylabel('work to failure W_f [10⁻⁶ E_s W² b_z]') + ax.legend(handles=[Line2D([0], [0], marker='o', color='w', markerfacecolor=c, label=m, markersize=6) for m, c in MODE_COL.items() if m != 'no-failure'] + [Line2D([0], [0], color='k', lw=0.8, label='W_f = ½F_peak d_peak'), Line2D([0], [0], color='k', ls=':', lw=0.8, label='3×')], frameon=False, fontsize=7) + ax.set_title('(c) energy budget: post-peak contribution', fontsize=9) + fig.tight_layout(); savefig(fig, 'fig3_stiffness_toughness_pareto') + +# ------------------------------------------------------------------ Fig 4: representative load-displacement curves +def fig4(): + sel = [('B0_flat16_ord', 'flat ordered grid (D=0)', '#1f77b4'), ('B2_ref_ord', 'ordered nested hierarchy', '#9467bd'), ('E4_L3_dis0.35_rt0.6', 'level-selective (finest level organic)', '#2ca02c'), ('B2_ref', 'disordered hierarchy (δ=0.35)', '#d62728'), ('E5_ord_red1', 'ordered + full bracing', '#ff7f0e'), ('R_frame', 'disordered + side stringers', '#8c564b'), ('R_rt0.3', 'disordered, strong thickness hierarchy r_t=0.3', '#17becf')] + fig, axes = plt.subplots(1, 2, figsize=(12, 4.4)) + for d, lab, col in sel: + rows = df[df.designId == d] + for k, (_, r) in enumerate(rows.iterrows()): + res = json.load(open(os.path.join(ROOT, r['dir'], 'results.json'))) + dd = [s['d'] for s in res['steps']]; FF = [s['F'] * 1e3 for s in res['steps']] + for ax in axes: ax.plot(dd, FF, color=col, lw=1.3 if k == 0 else 0.6, alpha=1 if k == 0 else 0.45, label=lab + ' (n=%d seeds)' % len(rows) if k == 0 else None) + axes[0].set_xlim(0, 0.03); axes[0].set_ylim(0, None); axes[1].set_xlim(0, 0.03); axes[1].set_ylim(1e-3, 3); axes[1].set_yscale('log') + for ax in axes: ax.set_xlabel('applied displacement d [W]'); ax.set_ylabel('reaction force F [10⁻³ E_s W b_z]') + axes[0].legend(frameon=False, fontsize=7); axes[0].set_title('(a) linear scale', fontsize=9); axes[1].set_title('(b) logarithmic force scale (post-peak tails)', fontsize=9) + fig.tight_layout(); savefig(fig, 'fig4_load_displacement_curves') + +# ------------------------------------------------------------------ Fig 5: snapshots localized vs distributed +def fig5(): + sel = [('B2_ref_ord', 'ordered nested hierarchy: abrupt, localised'), ('B2_ref', 'disordered hierarchy: progressive, distributed'), ('E4_L3_dis0.35_rt0.6', 'level-selective: intermediate')] + keys = [('peak', 'at peak force (before the drop)'), ('f1', 'at 50 % of the final-failure displacement'), ('final', 'at final failure')] + fig, axes = plt.subplots(3, 3, figsize=(11, 11.2)) + for i, (d, lab) in enumerate(sel): + row = df[(df.designId == d) & (df.seed == 1)].iloc[0]; res, geom, snaps = load_run(row['dir']); m = res['metrics'] + for j, (k, kl) in enumerate(keys): + s = snaps[k]; ax = axes[i, j] + render(geom, ax, u=np.array(s['u']), scale=1.0, color_by='util', state=np.array(s['state']), util=np.array(s['util']), show_failed='ghost', frame=True) + nf = int((np.array(s['state']) == 2).sum()) + ax.set_title('%s\nd = %.4f, F = %.2e, failed %d' % (kl, s['d'], s['F'], nf), fontsize=7.5) + axes[i, 0].set_ylabel('%s\nA = %.2f, LI = %.2f, pre-peak failures %d' % (lab, m['abruptness'], m['localizationIndex'], m['prePeakFailures']), fontsize=8) + sm = plt.cm.ScalarMappable(cmap='viridis', norm=plt.Normalize(0, 1)); sm.set_array([]) + cb = fig.colorbar(sm, ax=axes, fraction=0.02, pad=0.02); cb.set_label('member utilisation ε_max/ε_c (failed members: dashed grey; deformation × 1)') + savefig(fig, 'fig5_fracture_snapshots') + +# ------------------------------------------------------------------ Fig 6: factor effects +def sweep(ax, ids, xs, ykey, yscale=1, label=None, color=None, marker='o', ls='-'): + rows = design_rows(ids) + x = [xs[i] for i in rows.index]; y = rows[ykey + '_mean'].values * yscale; e = rows[ykey + '_std'].fillna(0).values * yscale + errbar(ax, x, y, e, fmt=marker + ls, color=color, label=label, ms=4, lw=1.1) + # individual seeds + for i in rows.index: + sub = df[df.designId == i]; ax.scatter([xs[i]] * len(sub), sub[ykey] * yscale, s=6, color=color, alpha=0.35, edgecolor='none') + +def fig6(): + fig, axes = plt.subplots(4, 5, figsize=(15, 11.5)) + metrics = [('K0', 1, 'K_0 [E_s b_z]'), ('Fpeak', 1e3, 'F_peak [10⁻³ E_s W b_z]'), ('Wf', 1e6, 'W_f [10⁻⁶ E_s W² b_z]'), ('abruptness', 1, 'abruptness A')] + # column 1: disorder + dis_ids = {'R_dis0': 0, 'E1_dis0.05': 0.05, 'E1_dis0.1': 0.1, 'R_dis0.15': 0.15, 'E1_dis0.2': 0.2, 'B2_ref': 0.35, 'E1_dis0.5': 0.5, 'R_dis0.7': 0.7, 'R_dis1': 1.0} + cv_ids = {'R_cv0': 0, 'B2_ref': 0.05, 'R_cv0.2': 0.2, 'F6_dis_cv0.4': 0.4} + ocv_ids = {'B2_ref_ord': 0.05, 'E7_ord_cv0.1': 0.1, 'E7_ord_cv0.2': 0.2, 'E7_ord_cv0.4': 0.4} + for r, (mk, sc, lab) in enumerate(metrics): + ax = axes[r, 0]; sweep(ax, list(dis_ids), dis_ids, mk, sc, 'geometric disorder δ (r_t=0.6)', '#d62728') + ax.set_xlabel('geometric disorder δ'); ax.set_ylabel(lab) + if r == 0: ax.set_title('(a) geometric disorder', fontsize=9) + ax2 = ax.twiny(); sweep(ax2, list(ocv_ids), ocv_ids, mk, sc, 'strength CV, ordered geometry', '#1f77b4', 's', '--'); ax2.set_xlabel('strength CV (ordered geometry, δ=0)', color='#1f77b4', fontsize=8); ax2.tick_params(axis='x', colors='#1f77b4', labelsize=7) + if r == 0: ax.legend(frameon=False, fontsize=6.5, loc='center right'); ax2.legend(frameon=False, fontsize=6.5, loc='upper right') + # column 2: thickness ratio / f0 collapse + for r, (mk, sc, lab) in enumerate(metrics): + ax = axes[r, 1] + sub = A[(A.p_disorder == 0.35) & (A.dml == 0) & (A.p_redundancy == 0) & (A.p_interfaceStrengthRatio == 0.8) & (A.p_strengthCV == 0.05) & (A.p_relDensity == 0.2) & (A.p_layout == 'grid') & (~A.index.str.contains('notch|con|frame|H2|flat|noif|movie|_s3|movie|n0'))] + for D, col, mkr in [(0, '#7f7f7f', 'x'), (1, '#9467bd', 'v'), (2, '#17becf', '^'), (3, '#d62728', 'o'), (6, '#2ca02c', 's')]: + s2 = sub[sub.p_depth == D] + if not len(s2): continue + ax.errorbar(s2['f0'], s2[mk + '_mean'] * sc, yerr=s2[mk + '_std'].fillna(0) * sc, fmt=mkr, color=col, ms=4, capsize=2, lw=0.8, ls='none', label='D = %d' % D) + ax.set_xlabel('level-0 (coarsest) material fraction f_0'); ax.set_ylabel(lab) + if r == 0: ax.set_title('(b) thickness hierarchy (δ=0.35): collapse on f_0', fontsize=9); ax.legend(frameon=False, fontsize=6.5) + # column 3: interface strength + sint_d = {'R_sint0.3': 0.3, 'R_sint0.5': 0.5, 'B2_ref': 0.8, 'R_sint1': 1.0, 'R_sint1.5': 1.5} + sint_o = {'E3_ord_sint0.3': 0.3, 'E3_ord_sint0.5': 0.5, 'B2_ref_ord': 0.8, 'E3_ord_sint1': 1.0, 'E3_ord_sint1.5': 1.5} + sint_l = {'F4_L3_sint0.5': 0.5, 'E4_L3_dis0.35_rt0.6': 0.8, 'F4_L3_sint1.5': 1.5} + for r, (mk, sc, lab) in enumerate(metrics): + ax = axes[r, 2]; sweep(ax, list(sint_o), sint_o, mk, sc, 'ordered (δ=0)', '#1f77b4', 's'); sweep(ax, list(sint_d), sint_d, mk, sc, 'disordered (δ=0.35)', '#d62728'); sweep(ax, list(sint_l), sint_l, mk, sc, 'level-selective L3', '#2ca02c', '^') + ax.set_xlabel('inter-level (interface) strength ratio s_int'); ax.set_ylabel(lab) + if r == 0: ax.set_title('(c) inter-level strength', fontsize=9); ax.legend(frameon=False, fontsize=6.5) + if mk in ('K0', 'Fpeak', 'Wf'): ax.set_yscale('log') + # column 4: redundancy + red_o = {'B2_ref_ord': 0, 'E5_ord_red0.5': 0.5, 'E5_ord_red1': 1.0} + red_d = {'B2_ref': 0, 'E5_dis035_red0.25': 0.25, 'R_red0.5': 0.5, 'E5_dis035_red0.75': 0.75, 'R_red1': 1.0} + red_1 = {'R_dis1': 0, 'E5_dis1_red0.5': 0.5, 'E5_dis1_red1': 1.0} + red_l = {'E4_L3_dis0.35_rt0.6': 0, 'F3_L3_red0.5': 0.5, 'F3_L3_red1': 1.0} + for r, (mk, sc, lab) in enumerate(metrics): + ax = axes[r, 3]; sweep(ax, list(red_o), red_o, mk, sc, 'ordered (δ=0)', '#1f77b4', 's'); sweep(ax, list(red_d), red_d, mk, sc, 'δ=0.35', '#d62728'); sweep(ax, list(red_1), red_1, mk, sc, 'δ=1', '#8c564b', 'v'); sweep(ax, list(red_l), red_l, mk, sc, 'level-selective L3', '#2ca02c', '^') + ax.set_xlabel('redundancy (fraction of leaf-cell braces)'); ax.set_ylabel(lab) + if r == 0: ax.set_title('(d) redundancy (bracing)', fontsize=9); ax.legend(frameon=False, fontsize=6.5) + if mk in ('K0', 'Fpeak', 'Wf'): ax.set_yscale('log') + # column 5: depth at fixed contrast and level-selective disorder + depC = {'R_depthC1': 1, 'R_depthC2': 2, 'B2_ref': 3, 'R_depthC6': 6} + lsel = {'B2_ref': 0, 'E4_L1_dis0.35_rt0.6': 1, 'E4_L2_dis0.35_rt0.6': 2, 'E4_L3_dis0.35_rt0.6': 3, 'B2_ref_ord': 4} + lsel1 = {'E4_L1_dis0.35_rt1': 1, 'E4_L2_dis0.35_rt1': 2, 'E4_L3_dis0.35_rt1': 3} + lselD6 = {'F7_D6_L2': 2, 'F7_D6_L4': 4, 'F7_D6_L5': 5, 'F7_D6_L6': 6} + for r, (mk, sc, lab) in enumerate(metrics): + ax = axes[r, 4]; sweep(ax, list(lsel), lsel, mk, sc, 'levels ≥ k disordered (D=3, r_t=0.6); k=4 ≡ ordered', '#2ca02c', '^'); sweep(ax, list(lsel1), lsel1, mk, sc, 'same, r_t=1', '#bcbd22', 'v'); sweep(ax, list(lselD6), lselD6, mk, sc, 'D=6 (fixed contrast), levels ≥ k', '#17becf', 'd') + ax.set_xlabel('first disordered level k'); ax.set_ylabel(lab) + if r == 0: ax.set_title('(e) level-selective disorder', fontsize=9); ax.legend(frameon=False, fontsize=6.5) + if mk in ('K0', 'Fpeak', 'Wf'): ax.set_yscale('log') + fig.suptitle('Factor effects at fixed material (ρ = 0.2, 256-cell family). Markers: design means ± s.d. over seeds; small dots: individual seeds.', fontsize=10, y=0.995) + fig.tight_layout(); savefig(fig, 'fig6_factor_effects') + # supplementary: depth at fixed contrast + fig, axes = plt.subplots(1, 4, figsize=(12, 3)) + for ax, (mk, sc, lab) in zip(axes, metrics): + sweep(ax, list(depC), depC, mk, sc, 'fixed contrast t_D/t_0 = 0.216', '#d62728'); dep = {'R_depth0': 0, 'R_depth1': 1, 'R_depth2': 2, 'B2_ref': 3, 'R_depth6': 6}; sweep(ax, list(dep), dep, mk, sc, 'fixed per-level ratio r_t = 0.6', '#1f77b4', 's') + ax.set_xlabel('hierarchy depth D (256 leaf cells)'); ax.set_ylabel(lab) + axes[0].legend(frameon=False, fontsize=7); fig.suptitle('Hierarchy depth at fixed finest resolution and fixed material (δ = 0.35)', fontsize=10) + fig.tight_layout(); savefig(fig, 'fig6b_depth_effect') + +# ------------------------------------------------------------------ Fig 8: mechanism: two routes to abrupt failure +def fig8(): + if 'ls_frac_ge0.8' not in df: print('no load-sharing data'); return + fig, axes = plt.subplots(1, 3, figsize=(13, 4.2)) + B = A.join(df.groupby('designId')[['ls_frac_ge0.8', 'lp_max_share', 'lp_top3_share', 'ls_frac_ge0.5']].mean()) + B = B[B.stage != 'holdout'] + ax = axes[0] + sc = ax.scatter(B['ls_frac_ge0.8'] + 1e-3, B['lp_max_share'], c=B['abruptness_mean'], cmap='coolwarm', vmin=0.15, vmax=1, s=30, edgecolor='k', linewidth=0.4) + ax.set_xscale('log'); ax.set_xlabel('fraction of members within 20 % of failure at the first event, φ_0.8 (+10⁻³)'); ax.set_ylabel('largest single-member share of the reaction force, s_max') + ax.axvline(0.05 + 1e-3, color='k', ls=':', lw=0.8); ax.axhline(0.30, color='k', ls=':', lw=0.8) + ax.text(0.06, 0.9, 'route (i): uniform\nload sharing', transform=ax.transAxes, fontsize=7.5); ax.text(0.06, 0.55, 'route (ii): dominant\ncoarse load path', transform=ax.transAxes, fontsize=7.5); ax.text(0.06, 0.08, 'progressive region', transform=ax.transAxes, fontsize=7.5) + cb = fig.colorbar(sc, ax=ax, fraction=0.05, pad=0.02); cb.set_label('abruptness A (design mean)'); ax.set_title('(a) two routes to abrupt failure', fontsize=9) + ax = axes[1] + for lab, mask, col, mk in [('ordered (φ_0.8 ≥ 0.05)', B['ls_frac_ge0.8'] >= 0.05, '#1f77b4', 's'), ('disordered / hierarchical', B['ls_frac_ge0.8'] < 0.05, '#d62728', 'o')]: + s2 = B[mask]; ax.errorbar(s2['lp_max_share'], s2['abruptness_mean'], yerr=s2['abruptness_std'].fillna(0), fmt=mk, color=col, ms=4, capsize=2, lw=0.7, ls='none', label=lab) + ax.set_xlabel('largest single-member force share s_max (initial state)'); ax.set_ylabel('abruptness A'); ax.legend(frameon=False, fontsize=7); ax.set_title('(b) abruptness vs dominant load path', fontsize=9) + ax = axes[2] + ax.errorbar(B['ls_frac_ge0.8'] + 1e-3, B['abruptness_mean'], yerr=B['abruptness_std'].fillna(0), fmt='o', color='#7f7f7f', ms=3, capsize=1.5, lw=0.6, ls='none') + ax.set_xscale('log'); ax.set_xlabel('φ_0.8 (+10⁻³)'); ax.set_ylabel('abruptness A'); ax.set_title('(c) abruptness vs load-sharing uniformity', fontsize=9) + fig.tight_layout(); savefig(fig, 'fig8_mechanism_two_routes') + +# ------------------------------------------------------------------ Fig 7: holdout predictions vs observations +def fig7(): + P = json.load(open(os.path.join(ROOT, 'study', 'predictions.json')))['predictions'] + hold = df[df.stage == 'holdout'] + fig, axes = plt.subplots(1, 4, figsize=(14, 3.7)) + for ax, (mk, sc, lab, log) in zip(axes, [('K0', 1, 'K_0 [E_s b_z]', True), ('Fpeak', 1e3, 'F_peak [10⁻³ E_s W b_z]', True), ('Wf', 1e6, 'W_f [10⁻⁶ E_s W² b_z]', True), ('abruptness', 1, 'abruptness A', False)]): + xs, ys, xe, ye, ok = [], [], [], [], [] + for i, (k, v) in enumerate(P.items()): + pt, lo, hi = [q * sc for q in v[mk]] + obs = hold[hold.designId == k][mk] * sc + xs.append(pt); ys.append(obs.mean()); xe.append([pt - lo, hi - pt]); ye.append(obs.std() if len(obs) > 1 else 0); ok.append(lo <= obs.mean() <= hi) + ax.annotate(k.split('_')[0], (pt, obs.mean()), fontsize=6, xytext=(3, 2), textcoords='offset points') + ax.scatter([pt] * len(obs), obs, s=6, color='#7f7f7f', alpha=0.5, zorder=1) + xe = np.array(xe).T + ax.errorbar(xs, ys, xerr=xe, yerr=ye, fmt='o', ms=4, capsize=2, lw=0.8, color='#1f77b4', ecolor='#9ecae1', zorder=2) + for x, y, o in zip(xs, ys, ok): + if not o: ax.scatter([x], [y], s=60, facecolor='none', edgecolor='#d62728', linewidth=1.2, zorder=3) + lim = [min(min(xs), min(ys)) * 0.8, max(max(xs), max(ys)) * 1.2] + ax.plot(lim, lim, 'k--', lw=0.8) + if log: ax.set_xscale('log'); ax.set_yscale('log') + ax.set_xlabel('predicted (bar = stated range)'); ax.set_ylabel('observed (mean of 3 seeds ± s.d.)') + ax.set_title('%s: %d/%d within range' % (lab, sum(ok), len(ok)), fontsize=9) + fig.suptitle('Holdout designs (12 × 3 unseen seeds): predictions recorded before the runs vs observations; red circles = misses; grey dots = seeds', fontsize=9.5, y=1.02) + fig.tight_layout(); savefig(fig, 'fig7_holdout_predictions') + +# ------------------------------------------------------------------ Fig 9: density scaling +def fig9(): + ids = {'R_rho0.1': 0.1, 'B2_ref': 0.2, 'R_rho0.3': 0.3} + rows = design_rows(list(ids)); rho = np.array([ids[i] for i in rows.index]) + fig, axes = plt.subplots(1, 3, figsize=(10, 3.2)) + for ax, (mk, sc, lab) in zip(axes, [('K0', 1, 'K_0 [E_s b_z]'), ('Fpeak', 1e3, 'F_peak [10⁻³ E_s W b_z]'), ('Wf', 1e6, 'W_f [10⁻⁶ E_s W² b_z]')]): + y = rows[mk + '_mean'].values * sc; e = rows[mk + '_std'].fillna(0).values * sc + ax.errorbar(rho, y, yerr=e, fmt='o', color='#d62728', capsize=2, ms=4) + p = np.polyfit(np.log(rho), np.log(y), 1); xx = np.linspace(0.08, 0.35, 20); ax.plot(xx, np.exp(p[1]) * xx ** p[0], 'k--', lw=0.8, label='∝ ρ^%.2f' % p[0]) + ax.set_xscale('log'); ax.set_yscale('log'); ax.set_xlabel('relative density ρ'); ax.set_ylabel(lab); ax.legend(frameon=False, fontsize=8) + fig.suptitle('Density scaling of the disordered reference (δ = 0.35): bending-dominated cellular-solid exponents', fontsize=9.5) + fig.tight_layout(); savefig(fig, 'fig9_density_scaling') + +if __name__ == '__main__': + which = sys.argv[1:] or ['1', '2', '3', '4', '5', '6', '7', '8', '9'] + for w in which: + globals()['fig' + w]() + A.to_csv(os.path.join(PROC, 'design_summary.csv')) diff --git a/data/Run 1/RESULT Run 1/analysis/make_tables.py b/data/Run 1/RESULT Run 1/analysis/make_tables.py new file mode 100644 index 0000000000000000000000000000000000000000..a654a554d527554b1355763ebfcb6b319187d614 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/make_tables.py @@ -0,0 +1,53 @@ +#!/usr/bin/env python3 +"""LaTeX tables for the report: validation, design summary, holdout comparison, complete experiment appendix.""" +import os, json +import numpy as np, pandas as pd +from hfx_analysis import load_log, agg, ROOT, PROC +OUT = os.path.join(ROOT, 'report', 'tables'); os.makedirs(OUT, exist_ok=True) +def esc(s): return str(s).replace('\\', '/').replace('_', '\\_').replace('%', '\\%').replace('&', '\\&').replace('#', '\\#').replace('^', '\\textasciicircum{}').replace('~', '\\textasciitilde{}').replace('<', '$<$').replace('>', '$>$').replace('|', '$|$') +def sci(x, d=2): + if x is None or (isinstance(x, float) and np.isnan(x)): return '--' + return ('%.' + str(d) + 'e') % x +def f3(x): return '--' if x is None or (isinstance(x, float) and np.isnan(x)) else '%.3g' % x +# ---- validation +v = json.load(open(os.path.join(ROOT, 'validation', 'validation_results.json'))) +rows = [] +for t in v['tests']: + rows.append('%s & %s & %s & %s & %s & %s & %s \\\\' % (esc(t['id']), esc(t['name']), f3(t['expected']) if isinstance(t['expected'], (int, float)) else esc(t['expected']), f3(t['observed']) if isinstance(t['observed'], (int, float)) else esc(str(t['observed'])[:20]), (sci(t['error'], 1) if isinstance(t['error'], (int, float)) and not np.isnan(t['error']) else '--') + (' (abs)' if t['absolute'] else ''), sci(t['tolerance'], 0) if t['tolerance'] else '0', '\\textbf{PASS}' if t['pass'] else '\\textbf{FAIL}')) +open(os.path.join(OUT, 'validation.tex'), 'w').write('\\begin{longtable}{@{}l p{6.3cm} r r l l l@{}}\n\\caption{Validation suite of the simulator core (%s, build %s): analytical references, invariances, conservation checks, step-size and export consistency. All %d tests pass.}\\label{tab:validation}\\\\\n\\toprule ID & test & expected & observed & error & tol. & status \\\\ \\midrule\\endfirsthead\n\\toprule ID & test & expected & observed & error & tol. & status \\\\ \\midrule\\endhead\n\\bottomrule\\endfoot\n' % (esc(v['coreVersion']), esc(v['build'][:19]), len(v['tests'])) + '\n'.join(rows) + '\n\\end{longtable}\n') +# ---- design summary (means ± sd over seeds) +df = load_log(); df = df[df.status == 'ok'] +A = agg(df) +A['f0'] = df.groupby('designId')['levelMaterial'].apply(lambda s: np.mean([l[0] for l in s])) +A['dml'] = df.groupby('designId')['p_disorderMinLevel'].first(); A['n0'] = df.groupby('designId').apply(lambda g: '%dx%d' % (g.p_n0x.iloc[0], g.p_n0y.iloc[0])) +A['extra'] = df.groupby('designId')['reason'].first() +def pm(m, s, fmt): + return (fmt % m) + ('$\\pm$' + (fmt % s) if not np.isnan(s) else '') +rows = [] +for did, r in A.sort_values(['stage', 'K0_mean']).iterrows(): + rows.append('%s & %s & %s & %d & %d & %s & %s & %s & %s & %d & %s & %s & %s & %s & %s \\\\' % (esc(did), esc(r['stage'][:5]), r['n0'], r['p_depth'], r['p_branching'], f3(r['p_disorder']), f3(r['p_thicknessRatio']), f3(r['p_interfaceStrengthRatio']), f3(r['p_redundancy']), int(r['Wf_count']), pm(r['K0_mean'], r['K0_std'], '%.3f'), pm(r['Fpeak_mean'] * 1e3, r['Fpeak_std'] * 1e3, '%.2f'), pm(r['Wf_mean'] * 1e6, r['Wf_std'] * 1e6, '%.2f'), pm(r['abruptness_mean'], r['abruptness_std'], '%.2f'), esc(r['modes'].replace('abrupt-brittle', 'abrupt').replace('intermediate', 'interm.').replace('progressive', 'progr.')))) +open(os.path.join(OUT, 'design_summary.tex'), 'w').write('{\\scriptsize\n\\begin{longtable}{@{}l l l r r r r r r r l l l l l@{}}\n\\caption{All %d designs of the study: parameters, number of seeds $n$, and design means $\\pm$ s.d. of the initial stiffness $K_0$ [$E_sb_z$], peak force $F_\\mathrm{peak}$ [$10^{-3}E_sWb_z$], work to failure $W_f$ [$10^{-6}E_sW^2b_z$] and abruptness $A$; last column: fracture modes observed over the seeds. Parameters not listed are at the study base values (Table~\\ref{tab:base}).}\\label{tab:designs}\\\\\n\\toprule design & stage & $n_0$ & $D$ & $b$ & $\\delta$ & $r_t$ & $s_\\mathrm{int}$ & red. & $n$ & $K_0$ & $F_\\mathrm{peak}$ & $W_f$ & $A$ & modes \\\\ \\midrule\\endfirsthead\n\\toprule design & stage & $n_0$ & $D$ & $b$ & $\\delta$ & $r_t$ & $s_\\mathrm{int}$ & red. & $n$ & $K_0$ & $F_\\mathrm{peak}$ & $W_f$ & $A$ & modes \\\\ \\midrule\\endhead\n\\bottomrule\\endfoot\n' % len(A) + '\n'.join(rows) + '\n\\end{longtable}}\n') +# ---- holdout table +P = json.load(open(os.path.join(ROOT, 'study', 'predictions.json')))['predictions'] +H = pd.read_csv(os.path.join(PROC, 'holdout_comparison.csv')).set_index('design') +rows = [] +for k, v in P.items(): + h = H.loc[k] + cell = lambda m, fmt: (('%s [%s, %s] / \\textbf{%s}' if not h[m + '_in'] else '%s [%s, %s] / %s') % (fmt % v[m][0], fmt % v[m][1], fmt % v[m][2], fmt % h[m + '_obs'])).replace('e-0', 'e-') + rows.append('%s & %s & %s & %s & %s & %s & %s \\\\' % (esc(k), cell('K0', '%.3f'), cell('Fpeak', '%.2e'), cell('Wf', '%.2e'), cell('abruptness', '%.2f'), esc(v['mode'].replace('intermediate', 'interm.').replace('abrupt-brittle', 'abrupt').replace('(seed-dependent)', '')[:20]), esc(str(h['mode_obs']).replace('intermediate', 'interm.').replace('abrupt-brittle', 'abrupt')))) +open(os.path.join(OUT, 'holdout.tex'), 'w').write('{\\scriptsize\n\\begin{longtable}{@{}l l l l l l l@{}}\n\\caption{Holdout designs: predictions recorded before the runs (point [low--high]) versus observed means over three unseen seeds (bold = outside the stated range). Modes: predicted / observed majority (letters: individual seeds).}\\label{tab:holdout}\\\\\n\\toprule design & $K_0$ pred / obs & $F_\\mathrm{peak}$ pred / obs & $W_f$ pred / obs & $A$ pred / obs & mode pred & mode obs \\\\ \\midrule\\endfirsthead\n\\toprule design & $K_0$ & $F_\\mathrm{peak}$ & $W_f$ & $A$ & mode pred & mode obs \\\\ \\midrule\\endhead\n\\bottomrule\\endfoot\n' + '\n'.join(rows) + '\n\\end{longtable}}\n') +# ---- complete experiment appendix +rows = [] +for _, r in df.sort_values(['batch', 'designId', 'seed']).iterrows(): + rows.append('%s & %d & %d & %d & %s & %s & %s & %s & %s & %.3f & %.2f & %.2f & %d & %d & %.2f & %s & %s \\\\' % (esc(r['designId']), r['seed'], r.p_depth, r.p_branching, f3(r.p_disorder), f3(r.p_disorderMinLevel), f3(r.p_thicknessRatio), f3(r.p_interfaceStrengthRatio), f3(r.p_redundancy), r.K0, r.Fpeak * 1e3, r.Wf * 1e6, r.nFailed, r.prePeakFailures, r.abruptness, f3(r.localizationIndex), esc(str(r['fractureLabel']).replace('abrupt-brittle', 'abr').replace('intermediate', 'int').replace('progressive', 'pro').replace('distributed', 'dis').replace('localized', 'loc').replace('few-failures', 'few')))) +open(os.path.join(OUT, 'experiments.tex'), 'w').write('{\\tiny\n\\begin{longtable}{@{}l r r r r r r r r r r r r r r r l@{}}\n\\caption{Complete experiment table: every simulated run (%d runs; all converged). Columns: design, seed, depth $D$, branching $b$, disorder $\\delta$, first disordered level $k_\\delta$, thickness ratio $r_t$, interface strength $s_\\mathrm{int}$, redundancy, $K_0$ [$E_sb_z$], $F_\\mathrm{peak}$ [$10^{-3}E_sWb_z$], $W_f$ [$10^{-6}E_sW^2b_z$], failed members $n_f$, pre-peak failures, abruptness $A$, localisation index LI, fracture label (abr = abrupt-brittle, int = intermediate, pro = progressive; loc = localised, dis = distributed, few = fewer than 10 failures). Root grids and all other parameters are in Table~\\ref{tab:designs}; full parameter sets, reasons, hypotheses, file paths and checksums are in \\texttt{study/experiment\\_log.jsonl}.}\\label{tab:experiments}\\\\\n\\toprule design & seed & $D$ & $b$ & $\\delta$ & $k_\\delta$ & $r_t$ & $s_\\mathrm{int}$ & red. & $K_0$ & $F_\\mathrm{pk}$ & $W_f$ & $n_f$ & pre & $A$ & LI & mode \\\\ \\midrule\\endfirsthead\n\\toprule design & seed & $D$ & $b$ & $\\delta$ & $k_\\delta$ & $r_t$ & $s_\\mathrm{int}$ & red. & $K_0$ & $F_\\mathrm{pk}$ & $W_f$ & $n_f$ & pre & $A$ & LI & mode \\\\ \\midrule\\endhead\n\\bottomrule\\endfoot\n' % len(df) + '\n'.join(rows) + '\n\\end{longtable}}\n') +# ---- base parameter table +base = json.load(open(os.path.join(ROOT, 'study', 'plans', 'study_base.json'))) if os.path.exists(os.path.join(ROOT, 'study', 'plans', 'study_base.json')) else None +print('tables written:', os.listdir(OUT)) +# key numbers for the text +key = {} +for did in ['B0_flat16_ord', 'B2_ref_ord', 'B2_ref', 'E4_L3_dis0.35_rt0.6', 'E5_ord_red1', 'R_red1', 'R_dis1', 'E1_dis0.05', 'R_frame', 'H11_4x1_L1_rt0.45', 'E2_D6_rt0.5', 'R_rt0.3', 'E3_ord_sint0.3', 'E7_ord_cv0.4', 'R_sint0.3', 'R_sint1.5', 'F2_L3_dis0.35_rt0.3', 'R_radial', 'R_depthC1', 'R_depthC6', 'R_rho0.1', 'R_rho0.3', 'E8_ord_notch', 'R_notch', 'E8_dis_notch20', 'F5_ord_red1_notch']: + if did in A.index: + r = A.loc[did]; key[did] = {k: (None if isinstance(r[k], float) and np.isnan(r[k]) else float(r[k]) if isinstance(r[k], (int, float, np.floating, np.integer)) else str(r[k])) for k in ['K0_mean', 'K0_std', 'Fpeak_mean', 'Fpeak_std', 'Wf_mean', 'Wf_std', 'abruptness_mean', 'abruptness_std', 'localizationIndex_mean', 'prePeakFailures_mean', 'Wf_count', 'f0', 'modes']} +json.dump(key, open(os.path.join(PROC, 'key_numbers.json'), 'w'), indent=1) +print(json.dumps({k: {'K0': round(v['K0_mean'], 4), 'Fpk': '%.2e' % v['Fpeak_mean'], 'Wf': '%.2e' % v['Wf_mean'], 'A': round(v['abruptness_mean'], 2), 'n': v['Wf_count'], 'f0': round(v['f0'], 3)} for k, v in key.items()}, indent=0)) diff --git a/data/Run 1/RESULT Run 1/analysis/processed/design_summary.csv b/data/Run 1/RESULT Run 1/analysis/processed/design_summary.csv new file mode 100644 index 0000000000000000000000000000000000000000..3b4f50d9a90ab7cbe4e12a20ff9376947ca643f0 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/processed/design_summary.csv @@ -0,0 +1,138 @@ +designId,K0_mean,K0_std,K0_count,Fpeak_mean,Fpeak_std,Fpeak_count,Wf_mean,Wf_std,Wf_count,WfRel_mean,WfRel_std,WfRel_count,dFirst_mean,dFirst_std,dFirst_count,dPeak_mean,dPeak_std,dPeak_count,dFinal_mean,dFinal_std,dFinal_count,nFailed_mean,nFailed_std,nFailed_count,prePeakFailures_mean,prePeakFailures_std,prePeakFailures_count,abruptness_mean,abruptness_std,abruptness_count,localizationIndex_mean,localizationIndex_std,localizationIndex_count,interfaceFailures_mean,interfaceFailures_std,interfaceFailures_count,fractionFailed_mean,fractionFailed_std,fractionFailed_count,postPeakWorkFraction_mean,postPeakWorkFraction_std,postPeakWorkFraction_count,EeffRel_mean,EeffRel_std,EeffRel_count,strengthRel_mean,strengthRel_std,strengthRel_count,p_depth,p_branching,p_disorder,p_thicknessRatio,p_interfaceStrengthRatio,p_redundancy,p_relDensity,p_strengthCV,p_layout,reason,hypothesis,stage,batch,modes +B0_flat16_dis035,0.04767113247375851,0.0018393332644546297,3,0.00024171001247117341,1.464557255142501e-05,3,1.0957716267929407e-06,1.280884900926718e-07,3,0.027394290669823504,0.0032022122523167732,3,0.00493947941938613,8.395723585918213e-05,3,0.005409787249498688,0.00030487153698078337,3,0.014616609095002423,0.0029330925605272748,3,37.0,6.557438524302,3,1.3333333333333333,0.5773502691896257,3,0.3960361589898322,0.12635151605110276,3,0.3944254856371409,0.059532516302158923,3,0.0,0.0,3,0.05541434343017922,0.009988590956956993,3,0.364519266496757,0.08657036561040564,3,0.04767113247375851,0.0018393332644546297,3,0.012085500623558669,0.000732278627571249,3,0,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,Non-hierarchical baseline with the reference geometric disorder (0.35).,baseline,baseline,S1,intermediate +B0_flat16_dis1,0.01329953474501634,0.001227915382012733,3,0.00011210295719250427,5.662827022985192e-06,3,8.517104136993253e-07,2.113738532221636e-07,3,0.02129276034248313,0.005284346330554078,3,0.008171890833634631,0.0005306128203663902,3,0.008700218511557483,0.0002998803079638045,3,0.02056892882204841,0.001885177171581348,3,27.333333333333332,8.144527815247079,3,0.6666666666666666,0.5773502691896258,3,0.44367804203636857,0.15008191459414408,3,0.5648276363172556,0.2094454413271745,3,0.0,0.0,3,0.03958839462734914,0.011846865147515965,3,0.38494322636898176,0.17512322157717208,3,0.01329953474501634,0.001227915382012733,3,0.0056051478596252135,0.0002831413511492598,3,0,4,1.0,1.0,0.8,0.0,0.2,0.05,grid,Non-hierarchical fully organic (Voronoi) baseline.,baseline,baseline,S1,intermediate +B0_flat16_ord,0.10000000000878409,0.0,5,0.0017295547069986323,3.18218298671701e-05,5,1.496084793661582e-05,5.499896844210961e-07,5,0.37402119841539316,0.013749742110527333,5,0.017295547068467053,0.000318218298643758,5,0.017295547068467053,0.000318218298643758,5,0.017295547068467053,0.000318218298643758,5,26.4,2.4083189157584592,5,0.0,0.0,5,0.9999999998658076,1.8636714559406657e-11,5,0.6649925824381147,0.08803176781850915,5,0.0,0.0,5,0.05500000000000001,0.005017331074496789,5,0.0,0.0,5,0.10000000000878409,0.0,5,0.08647773534993161,0.0015910914933585064,5,0,4,0.0,1.0,0.8,0.0,0.2,0.05,grid,"Non-hierarchical ordered baseline: uniform 16x16 grid, single thickness, no interfaces.",baseline,baseline,S1,abrupt-brittle +B1_D3_rt1_if08,0.03345340484600245,0.0016788553797218613,3,0.0001483697716670484,1.2153569579083743e-05,3,7.13993152373865e-07,5.943064036139471e-08,3,0.0178498288093466,0.0014857660090348537,3,0.004172832853302405,0.00040691694796358616,3,0.004843663287146526,0.0007527878722240686,3,0.017426082028621493,0.0020233374051397556,3,32.666666666666664,5.033222956847167,3,1.0,1.0,3,0.23601135904618095,0.09264761360085837,3,0.6272073987724346,0.12267714396572652,3,14.0,2.6457513110645907,3,0.034440126943431834,0.005340471585210781,3,0.45661542195897736,0.15881589976022628,3,0.03345340484600245,0.0016788553797218613,3,0.007418488583352419,0.0006076784789541871,3,3,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,Nested topology with interfaces (s_int=0.8) but uniform thickness: isolates the interface effect.,baseline,baseline,S1,intermediate/progressive +B1_D3_rt1_noif,0.03346716738080082,0.0016663044607233763,3,0.00015921345045867525,9.3251568096459e-06,3,8.669971725552783e-07,3.442555257542363e-08,3,0.021674929313881954,0.0008606388143855786,3,0.004421123515059817,0.000493748709163316,3,0.005363934100244002,0.0005298223492733906,3,0.021996990565194607,0.003883664364221579,3,33.666666666666664,0.5773502691896247,3,1.3333333333333333,1.1547005383792517,3,0.2849527299544123,0.11648032287508055,3,0.5913607734112399,0.11869370899125971,3,0.0,0.0,3,0.05037190155733819,0.0005841524095221918,3,0.4668288559354865,0.07243569558265915,3,0.03346716738080082,0.0016663044607233763,3,0.007960672522933762,0.000466257840482295,3,3,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,"Nested topology (2x2 root, b=4, D=3) with uniform thickness and no interfaces: isolates the purely topological effect of nesting.",baseline,baseline,S1,intermediate/progressive +B2_ref,0.040155672540777426,0.0046765824188202245,5,0.00017401211975011442,3.2843874132277396e-05,5,1.1842869842705222e-06,3.9230441176478944e-07,5,0.029607174606763043,0.009807610294119732,5,0.004048715984915539,0.0007291787678340056,5,0.004669656855797931,0.0006784437141716691,5,0.02917407335447153,0.011119914050731908,5,51.4,16.742162345408076,5,2.0,1.8708286933869707,5,0.340956906771417,0.09752054994137307,5,0.43004837046140343,0.09124083350723755,5,35.2,14.324803663575986,5,0.054244800332897025,0.017705415644333217,5,0.6133862576178842,0.1423954823891155,5,0.040155672540777426,0.0046765824188202245,5,0.00870060598750572,0.0016421937066138698,5,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,"Reference hierarchical design (centre of the design space): 2x2 root, b=4, D=3, r_t=0.6, s_int=0.8, disorder 0.35.",reference,baseline,S1,intermediate +B2_ref_ord,0.10000000002582585,0.0,5,0.0014222192793255188,2.2503501993691076e-05,5,1.0145864484814637e-05,3.4247428991114584e-07,5,0.25364661212036527,0.008561857247778616,5,0.01422219278958218,0.00022503501987878254,5,0.01422219278958218,0.00022503501987878254,5,0.014564027031337115,0.0007234846527588493,5,33.2,3.033150177620619,5,0.0,0.0,5,0.9551197573328537,0.08575270069647041,5,0.7140273727804978,0.07118876654847577,5,29.8,2.0493901531919194,5,0.04368421052631579,0.003990987075816609,5,0.002913427723970286,0.005560547615849392,5,0.10000000002582585,0.0,5,0.07111096396627595,0.0011251750996845512,5,3,4,0.0,0.6,0.8,0.0,0.2,0.05,grid,Ordered version of the reference hierarchical design.,reference,baseline,S1,abrupt-brittle +E1_dis0.05,0.09605547427518428,0.0007095432633675732,3,0.0005717689985589551,3.38292916816534e-05,3,3.0721061935745e-06,4.7555379407231337e-07,3,0.07680265483936248,0.011888844851807774,3,0.005732052147752068,0.00019185328939434483,3,0.006136369632735782,0.00035499948088070184,3,0.035902079403341815,0.021368115333874088,3,46.666666666666664,8.736894948054106,3,1.3333333333333333,0.5773502691896258,3,0.3504301572471853,0.03182555932062025,3,0.5077929861089592,0.08601211641088925,3,35.333333333333336,6.429100507328636,3,0.05722863742357448,0.011211096934297737,3,0.39756354898833063,0.1481681790112245,3,0.09605547427518428,0.0007095432633675732,3,0.028588449927947752,0.0016914645840826708,3,3,4,0.05,0.6,0.8,0.0,0.2,0.05,grid,disorder fine sweep delta=0.05 (transition location),H1,hypothesis-tests,S3,intermediate +E1_dis0.1,0.08518864448170223,0.0026226464565102478,3,0.00039228771315531936,4.611230449992546e-05,3,1.932637790303124e-06,8.456279069394627e-07,3,0.04831594475757806,0.02114069767348649,3,0.004440542461200596,0.00036100801041586957,3,0.004676681735682864,0.00047467977326681266,3,0.028214520071591448,0.027980712063751002,3,47.333333333333336,23.96525262402492,3,0.6666666666666666,0.5773502691896258,3,0.38367435807324535,0.19972392424547336,3,0.41474326132287803,0.08613328376828946,3,31.0,22.538855339169288,3,0.05408421220216112,0.02782077212524004,3,0.4738457146601058,0.18529596250210323,3,0.08518864448170223,0.0026226464565102478,3,0.019614385657765968,0.002305615224996274,3,3,4,0.1,0.6,0.8,0.0,0.2,0.05,grid,disorder fine sweep delta=0.1 (transition location),H1,hypothesis-tests,S3,abrupt-brittle/intermediate/progressive +E1_dis0.15_s3,0.06944532661588425,,1,0.00024199865829405685,,1,1.6386573644146053e-06,,1,0.040966434110365144,,1,0.0033178266508055035,,1,0.0038481386619993035,,1,0.02131041757776173,,1,48.0,,1,2.0,,1,0.3201383250206348,,1,0.3739130434782608,,1,25.0,,1,0.052805280528052806,,1,0.6923672262402571,,1,0.06944532661588425,,1,0.012099932914702842,,1,3,4,0.15,0.6,0.8,0.0,0.2,0.05,grid,third seed for delta=0.15,H1,hypothesis-tests,S3,intermediate +E1_dis0.2,0.062415927030585266,0.004880787237670802,3,0.00026658024567786546,6.225945408524769e-05,3,1.614501663329005e-06,5.429031167665955e-07,3,0.04036254158322509,0.013572577919164896,3,0.003920236938544315,0.0005102150510563528,3,0.004607169833214931,0.001172271732034951,3,0.03057362928226238,0.00837778103806958,3,56.666666666666664,14.46835627614047,3,2.0,2.6457513110645907,3,0.4088811798823028,0.18018124156429371,3,0.44442086816168674,0.054654366032155996,3,34.0,11.532562594670797,3,0.061441716437310244,0.015495806054822214,3,0.5952427950254652,0.08398575913684353,3,0.062415927030585266,0.004880787237670802,3,0.013329012283893271,0.0031129727042623835,3,3,4,0.2,0.6,0.8,0.0,0.2,0.05,grid,disorder fine sweep delta=0.2 (transition location),H1,hypothesis-tests,S3,abrupt-brittle/intermediate +E1_dis0.35_s3,0.03553704822361948,,1,0.00014393926359677266,,1,9.393173546849099e-07,,1,0.02348293386712273,,1,0.0032557994863044747,,1,0.004559290847304084,,1,0.02303255874439029,,1,39.0,,1,3.0,,1,0.2590329308487851,,1,0.5451555023923444,,1,24.0,,1,0.040880503144654086,,1,0.6229764947055321,,1,0.03553704822361948,,1,0.0071969631798386325,,1,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,third seed for delta=0.35,H1,hypothesis-tests,S3,intermediate +E1_dis0.5,0.027753580377633747,0.005675546645171012,3,0.00012769863961442274,3.995767787995306e-05,3,1.0135492128280549e-06,2.255466744216963e-07,3,0.025338730320701375,0.005638666860542425,3,0.0034716433200011865,0.0006780270187448175,3,0.005617753421029801,0.0005137825315052084,3,0.03754231161303812,0.020828197467629518,3,50.666666666666664,12.055427546683415,3,3.3333333333333335,2.5166114784235836,3,0.3279628226131676,0.12136127720264407,3,0.4257506235516619,0.16349260813626315,3,35.666666666666664,8.736894948054104,3,0.05301311457259731,0.01299312849748286,3,0.5861795311281449,0.14936271299218348,3,0.027753580377633747,0.005675546645171012,3,0.006384931980721137,0.001997883893997653,3,3,4,0.5,0.6,0.8,0.0,0.2,0.05,grid,disorder fine sweep delta=0.5 (transition location),H1,hypothesis-tests,S3,intermediate/progressive +E1_dis0_s3,0.10000000002582585,,1,0.0014466707466690395,,1,1.0483208765976692e-05,,1,0.2620802191494166,,1,0.014466707462954169,,1,0.014466707462954169,,1,0.015716245303340294,,1,32.0,,1,0.0,,1,0.9899627988825641,,1,0.7793103448275862,,1,30.0,,1,0.042105263157894736,,1,0.0018055084814242956,,1,0.10000000002582585,,1,0.07233353733345198,,1,3,4,0.0,0.6,0.8,0.0,0.2,0.05,grid,third seed for delta=0,H1,hypothesis-tests,S3,abrupt-brittle +E2_D1_rt0.3,0.03996140419213681,0.005172391612917993,2,0.00019433792556416575,4.516153904538279e-05,2,1.002542807447673e-06,1.3490752852320102e-07,2,0.0250635701861918,0.003372688213080044,2,0.004363842393017016,0.00012631467405687296,2,0.005243569828310887,3.701668443245415e-05,2,0.016038082146956418,0.0011342572852082221,2,35.5,6.363961030678928,2,1.5,0.7071067811865476,2,0.34446846206512566,0.14965390344263288,2,0.4452537593984962,0.14587400232184888,2,6.0,7.0710678118654755,2,0.04852623474094174,0.008652970336333778,2,0.4630079227130951,0.016532165093241662,2,0.03996140419213681,0.005172391612917993,2,0.009716896278208287,0.0022580769522691385,2,1,64,0.35,0.3,0.8,0.0,0.2,0.05,grid,"(D,r_t) collapse: D=1 r_t=0.3",H2,hypothesis-tests,S3,intermediate/progressive +E2_D1_rt0.5,0.04040410158555041,0.002166767832304399,2,0.00019912218933184386,2.7014519991711095e-06,2,1.0015538672765284e-06,5.6249552521304694e-08,2,0.025038846681913206,0.0014062388130326145,2,0.0049335681616962425,0.0001977137092173138,2,0.0049335681616962425,0.0001977137092173138,2,0.015864669038503462,0.0010418355995017972,2,35.0,5.656854249492381,2,0.0,0.0,2,0.24961236357443295,0.03311920643790356,2,0.41876293995859215,0.013029503835528537,2,7.0,2.8284271247461903,2,0.04784317463165212,0.007686977465860346,2,0.5092951142517876,0.014558613556756755,2,0.04040410158555041,0.002166767832304399,2,0.009956109466592193,0.00013507259995855655,2,1,64,0.35,0.5,0.8,0.0,0.2,0.05,grid,"(D,r_t) collapse: D=1 r_t=0.5",H2,hypothesis-tests,S3,intermediate/progressive +E2_D2_rt0.4,0.03455532079410827,0.010485659210245284,2,0.00016145438047901993,5.819291821371412e-05,2,1.1338209453513667e-06,1.4168560266246283e-08,2,0.028345523633784144,0.00035421400665616455,2,0.004453891602119463,3.0043877245597602e-05,2,0.005410143321175301,0.00138238802737695,2,0.03875212080807858,0.02920086129394818,2,44.5,7.7781745930520225,2,4.0,5.656854249492381,2,0.42189514104443077,0.23040021095968105,2,0.4959747495399714,0.04395020680447977,2,26.0,8.48528137423857,2,0.04844916493496498,0.008761963501195576,2,0.5396132815170941,0.3155447907499197,2,0.03455532079410827,0.010485659210245284,2,0.008072719023950996,0.0029096459106857054,2,2,8,0.35,0.4,0.8,0.0,0.2,0.05,grid,"(D,r_t) collapse: D=2 r_t=0.4",H2,hypothesis-tests,S3,intermediate +E2_D2_rt0.7,0.03172325318432905,0.00350794886174711,2,0.00014897428313977664,1.7965995366466738e-06,2,8.715436074547702e-07,1.4714329878223684e-07,2,0.021788590186369243,0.003678582469555878,2,0.004423287358624904,4.334517898716386e-05,2,0.005125282290225309,0.0010361159319736304,2,0.02403529494737524,0.005259815077450125,2,34.5,4.949747468305833,2,1.0,1.4142135623730951,2,0.3068309597326624,0.08926918536872679,2,0.530930371783424,0.0054637329924664595,2,17.5,0.7071067811865476,2,0.03752493946444535,0.005155031942366096,2,0.5206423735842468,0.19956790293366106,2,0.03172325318432905,0.00350794886174711,2,0.007448714156988832,8.982997683233331e-05,2,2,8,0.35,0.7,0.8,0.0,0.2,0.05,grid,"(D,r_t) collapse: D=2 r_t=0.7",H2,hypothesis-tests,S3,intermediate/progressive +E2_D3_rt0.2,0.04816775057509697,0.020998166563753827,2,0.0002776957695221938,0.00014524006555087447,2,1.6265552887953851e-06,6.219787862906382e-07,2,0.0406638822198846,0.0155494696572659,2,0.0042107356776598555,0.0001993183851879448,2,0.00821076429779821,0.0028443751859384874,2,0.023647315229864223,0.011237995442911486,2,29.0,0.0,2,6.0,4.242640687119285,2,0.9382924015902371,0.017898237137064885,2,0.47617244748412313,0.09441619978886813,2,9.5,3.5355339059327378,2,0.03065593921108504,0.0001833152008439839,2,0.25281348942338194,0.23670674570297112,2,0.04816775057509697,0.020998166563753827,2,0.013884788476109688,0.007262003277543724,2,3,4,0.35,0.2,0.8,0.0,0.2,0.05,grid,"(D,r_t) collapse: D=3 r_t=0.2 (extreme contrast)",H2,hypothesis-tests,S3,abrupt-brittle +E2_D3_rt0.3_s3,0.04035352650984795,,1,0.00018777390795191896,,1,1.0402260209283002e-06,,1,0.026005650523207482,,1,0.0031532863639839818,,1,0.004885266595009698,,1,0.03116740847456369,,1,27.0,,1,1.0,,1,0.6667572631923846,,1,0.4232594936708861,,1,9.0,,1,0.02830188679245283,,1,0.5499130849103097,,1,0.04035352650984795,,1,0.009388695397595948,,1,3,4,0.35,0.3,0.8,0.0,0.2,0.05,grid,third seed r_t=0.3,H2,hypothesis-tests,S3,abrupt-brittle +E2_D3_rt0.45_s3,0.035358739204304664,,1,0.00016468949208522167,,1,9.15273196175238e-07,,1,0.02288182990438097,,1,0.00370922998657649,,1,0.005970191531282962,,1,0.02351556552173331,,1,36.0,,1,8.0,,1,0.35493761928051265,,1,0.474025974025974,,1,15.0,,1,0.03773584905660377,,1,0.38117953399339466,,1,0.035358739204304664,,1,0.008234474604261084,,1,3,4,0.35,0.45,0.8,0.0,0.2,0.05,grid,third seed r_t=0.45,H2,hypothesis-tests,S3,intermediate +E2_D3_rt1_s3,0.03166203898862586,,1,0.00014913695402214673,,1,6.560345766670141e-07,,1,0.01640086441667534,,1,0.0046318423356829395,,1,0.005515900542342208,,1,0.016427106089977248,,1,28.0,,1,2.0,,1,0.3379310846999795,,1,0.7621359223300971,,1,11.0,,1,0.029350104821802937,,1,0.297417968585545,,1,0.03166203898862586,,1,0.007456847701107336,,1,3,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,third seed r_t=1,H2,hypothesis-tests,S3,intermediate +E2_D6_rt0.5,0.053420036503430905,0.012209435295732065,3,0.00034378848118747575,0.00011249474920379565,3,2.419647463532931e-06,4.5782154492745454e-07,3,0.060491186588323365,0.011445538623186315,3,0.0018682111346533137,0.0002757971293213314,3,0.007458629045383625,0.0007342520647203859,3,0.02558159669358803,0.010919854917116181,3,51.666666666666664,14.011899704655804,3,10.666666666666666,2.081665999466133,3,0.6852486480915606,0.1994047564637436,3,0.35703113962189875,0.04936369105395214,3,36.333333333333336,11.015141094572202,3,0.046553476734690534,0.012913205210601216,3,0.4082788173305503,0.275576037949321,3,0.053420036503430905,0.012209435295732065,3,0.01718942405937379,0.005624737460189783,3,6,2,0.35,0.5,0.8,0.0,0.2,0.05,grid,"(D,r_t) collapse: D=6 r_t=0.5",H2,hypothesis-tests,S3,abrupt-brittle/intermediate +E2_D6_rt0.8,0.0418493260747229,0.006687291740777806,2,0.00019678893487285,3.885972827270406e-05,2,1.1288939898155445e-06,2.2816874960009463e-07,2,0.02822234974538864,0.005704218740002367,2,0.004250837293919424,0.0007976661053559063,2,0.005112255827745989,0.00042056366806116936,2,0.034128304583337335,0.021052494659116204,2,49.0,19.79898987322333,2,2.0,2.8284271247461903,2,0.4162178521153322,0.19761682760243526,2,0.4852326968973747,0.10927246797572543,2,40.0,24.041630560342615,2,0.043909693346984496,0.017665480365259445,2,0.5218499157219358,0.11294379602459273,2,0.0418493260747229,0.006687291740777806,2,0.0098394467436425,0.0019429864136352028,2,6,2,0.35,0.8,0.8,0.0,0.2,0.05,grid,"(D,r_t) collapse: D=6 r_t=0.8",H2,hypothesis-tests,S3,intermediate +E3_dis_sint0.3_s3,0.03553704822361948,,1,8.183509819907464e-05,,1,3.4063117123027524e-07,,1,0.008515779280756874,,1,0.001648920282404834,,1,0.0032699943412368556,,1,0.012410115695575177,,1,63.0,,1,15.0,,1,0.5959826881578065,,1,0.4885309278350516,,1,62.0,,1,0.0660377358490566,,1,0.5121219275390827,,1,0.03553704822361948,,1,0.004091754909953732,,1,3,4,0.35,0.6,0.3,0.0,0.2,0.05,grid,third seed disordered s_int=0.3,H3,hypothesis-tests,S3,intermediate +E3_dis_sint0.5_s3,0.03553704822361948,,1,0.00012649891062174666,,1,5.668088707467331e-07,,1,0.014170221768668318,,1,0.0027482004706747233,,1,0.0054996018056830236,,1,0.020263720597488984,,1,44.0,,1,15.0,,1,0.4061066358693368,,1,0.7299107142857143,,1,40.0,,1,0.04612159329140461,,1,0.20803298677427748,,1,0.03553704822361948,,1,0.006324945531087333,,1,3,4,0.35,0.6,0.5,0.0,0.2,0.05,grid,third seed disordered s_int=0.5,H3,hypothesis-tests,S3,intermediate +E3_dis_sint1.5_s3,0.03553704822361948,,1,0.0001481665245199011,,1,1.099458802239222e-06,,1,0.02748647005598053,,1,0.0032557994863044747,,1,0.004627317938986763,,1,0.030401382769711424,,1,36.0,,1,2.0,,1,0.2277851187588862,,1,0.5060975609756098,,1,1.0,,1,0.03773584905660377,,1,0.6684389490500828,,1,0.03553704822361948,,1,0.007408326225995055,,1,3,4,0.35,0.6,1.5,0.0,0.2,0.05,grid,third seed disordered s_int=1.5,H3,hypothesis-tests,S3,progressive +E3_dis_sint1_s3,0.03553704822361948,,1,0.0001481665245199011,,1,9.737181721764517e-07,,1,0.024342954304411274,,1,0.0032557994863044747,,1,0.004627317938986763,,1,0.02321074429345393,,1,37.0,,1,2.0,,1,0.22778511862293774,,1,0.5743159203980099,,1,16.0,,1,0.03878406708595388,,1,0.6256229714479292,,1,0.03553704822361948,,1,0.007408326225995055,,1,3,4,0.35,0.6,1.0,0.0,0.2,0.05,grid,third seed disordered s_int=1,H3,hypothesis-tests,S3,progressive +E3_ord_sint0.3,0.10000000002582583,0.0,3,0.0005314693608264382,1.1336426610124959e-05,3,4.053167836310992e-06,6.382214698561123e-07,3,0.10132919590777452,0.015955536746402772,3,0.005314693606891818,0.0001133642660719786,3,0.005314693606891818,0.0001133642660719786,3,0.018708963194059725,0.0036860154994623725,3,62.666666666666664,3.214550253664317,3,0.0,0.0,3,0.7822964205552267,0.0068620495891868125,3,0.5071794886076743,0.03583261847638262,3,61.666666666666664,3.214550253664317,3,0.08245614035087719,0.0042296713864004186,3,0.6468111069619965,0.04456778995685329,3,0.10000000002582583,0.0,3,0.026573468041321907,0.0005668213305062476,3,3,4,0.0,0.6,0.3,0.0,0.2,0.05,grid,ordered hierarchy with s_int=0.3,H3,hypothesis-tests,S3,abrupt-brittle +E3_ord_sint0.5,0.10000000002582583,0.0,3,0.0008857822680440643,1.8894044350208235e-05,3,6.457975235825288e-06,2.829128168613474e-07,3,0.16144938089563177,0.007072820421533677,3,0.00885782267815303,0.00018894044345329748,3,0.00885782267815303,0.00018894044345329748,3,0.02604399299025413,0.009477821760712974,3,52.666666666666664,4.932882862316248,3,0.0,0.0,3,0.7822964205552262,0.006862049589186232,3,0.5856946494272824,0.03600475519906789,3,51.333333333333336,4.618802153517006,3,0.06929824561403508,0.006490635345152957,3,0.3919035288223706,0.027652704771005815,3,0.10000000002582583,0.0,3,0.044289113402203206,0.000944702217510414,3,3,4,0.0,0.6,0.5,0.0,0.2,0.05,grid,ordered hierarchy with s_int=0.5,H3,hypothesis-tests,S3,abrupt-brittle +E3_ord_sint1,0.10000000002582583,0.0,3,0.001745285314389919,1.9787355675943364e-05,3,1.523140927067407e-05,3.4646213143588664e-07,3,0.38078523176685075,0.008661553285897145,3,0.017452853139391825,0.00019787355670833193,3,0.017452853139391825,0.00019787355670833193,3,0.017452853139391825,0.00019787355670833193,3,26.333333333333332,3.214550253664319,3,0.0,0.0,3,0.9987216135609889,0.0022142294512070984,3,0.7283075776687955,0.0686233291762614,3,19.333333333333332,4.041451884327381,3,0.03464912280701754,0.004229671386400415,3,0.0,0.0,3,0.10000000002582583,0.0,3,0.08726426571949593,0.000989367783797172,3,3,4,0.0,0.6,1.0,0.0,0.2,0.05,grid,ordered hierarchy with s_int=1,H3,hypothesis-tests,S3,abrupt-brittle +E3_ord_sint1.5,0.10000000002582583,0.0,3,0.0017496198173848284,1.6912836790018885e-05,3,1.5306801003136417e-05,2.963664934513251e-07,3,0.3826700250784094,0.007409162336283121,3,0.017496198169329732,0.0001691283678564979,3,0.017496198169329732,0.0001691283678564979,3,0.017496198169329732,0.0001691283678564979,3,22.333333333333332,6.658328118479393,3,0.0,0.0,3,0.9999999995020946,1.8483322735205055e-10,3,0.8129221190375686,0.10849907572482681,3,0.3333333333333333,0.5773502691896258,3,0.0293859649122807,0.00876095805063078,3,0.0,0.0,3,0.10000000002582583,0.0,3,0.08748099086924144,0.0008456418395009428,3,3,4,0.0,0.6,1.5,0.0,0.2,0.05,grid,ordered hierarchy with s_int=1.5,H3,hypothesis-tests,S3,abrupt-brittle +E4_L1_dis0.35_rt0.6,0.05273715834085126,0.002761738989246459,3,0.0002757749100385326,1.1630177229567926e-05,3,2.537685738850397e-06,3.603646044476299e-07,3,0.06344214347125987,0.009009115111190619,3,0.004627643942307069,0.00033163739244599743,3,0.010210527998313648,0.004475093842409348,3,0.03671842721214161,0.01107543549426135,3,44.0,17.349351572897472,3,17.666666666666668,14.468356276140469,3,0.9277836709984696,0.07524731498933054,3,0.6377600931494615,0.18849868282962215,3,24.666666666666668,13.613718571108091,3,0.04621279775544748,0.01792032937116013,3,0.2748082261042175,0.4144218550915366,3,0.05273715834085126,0.002761738989246459,3,0.01378874550192663,0.0005815088614783964,3,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=0.6",H4,hypothesis-tests,S3,abrupt-brittle +E4_L1_dis0.35_rt1,0.04030235831937038,0.001233012546400227,3,0.0001937238159468314,5.600203007219758e-06,3,1.066774241159885e-06,5.818661706966384e-08,3,0.026669356028997115,0.0014546654267415925,3,0.0045859272997317395,0.0005140275320904901,3,0.005085797326085954,0.0004133064227867111,3,0.014734195413209644,0.0027877336834316487,3,36.333333333333336,1.5275252316519456,3,1.0,1.0,3,0.37582091261428724,0.06644556143697423,3,0.6024887398164746,0.07831966453354343,3,17.0,2.0,3,0.03821492079205328,0.0014364012980435604,3,0.5126444188873825,0.09816393834681011,3,0.04030235831937038,0.001233012546400227,3,0.009686190797341569,0.000280010150360988,3,3,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=1",H4,hypothesis-tests,S3,intermediate +E4_L1_dis0.7_rt0.6,0.03342151487028129,0.003898707386595287,3,0.00026015422624222864,3.325654737999084e-05,3,2.140633352931242e-06,5.178043076748522e-07,3,0.05351583382328103,0.012945107691871315,3,0.005795314718550538,9.938267812279176e-05,3,0.011357413447587145,0.003485792474570952,3,0.02726514496489187,0.00606055972437025,3,43.333333333333336,8.386497083606084,3,21.0,13.076696830622021,3,0.8589686444521579,0.11983104462952927,3,0.6033139069515417,0.1068947747706148,3,28.0,5.196152422706632,3,0.04519160522185465,0.009045999285441305,3,0.18192206474284675,0.18711008751860425,3,0.03342151487028129,0.003898707386595287,3,0.013007711312111432,0.0016628273689995414,3,3,4,0.7,0.6,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=0.6",H4,hypothesis-tests,S3,abrupt-brittle +E4_L1_dis0.7_rt1,0.02168010950481476,0.0017685227688877066,3,0.00014650926799911313,1.0532918898356692e-05,3,7.628110318497031e-07,9.378819954589853e-08,3,0.01907027579624258,0.0023447049886474503,3,0.0066762803059378095,0.0008260195620697479,3,0.007052362894463041,0.00030817473087221044,3,0.018968413911577362,0.003194263819483528,3,24.333333333333332,5.033222956847167,3,0.3333333333333333,0.5773502691896258,3,0.569243744503968,0.1317838130765621,3,0.6741762271526056,0.1471299159841527,3,8.666666666666666,1.5275252316519468,3,0.025334474184356984,0.005091566731849305,3,0.30011352169814437,0.02031340446507787,3,0.02168010950481476,0.0017685227688877066,3,0.007325463399955656,0.0005266459449178345,3,3,4,0.7,1.0,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=1",H4,hypothesis-tests,S3,abrupt-brittle/intermediate +E4_L2_dis0.35_rt0.6,0.0643319206993192,0.0013562410283407965,5,0.00037204908752097127,2.483701155857612e-05,5,3.693993396470878e-06,3.167923391483338e-07,5,0.09234983491177202,0.007919808478708318,5,0.00508461914775204,0.0006576557159572475,5,0.008139763992364895,0.0013959091658835253,5,0.02526157617890363,0.00990498471780224,5,55.6,6.767569726275452,5,15.0,4.0,5,0.7681684111918377,0.11971549405617854,5,0.4916243525913881,0.054769913766797684,5,33.8,5.403702434442518,5,0.059332507535071674,0.0074233945533842,5,0.48761983984228763,0.17348490941571518,5,0.0643319206993192,0.0013562410283407965,5,0.018602454376048565,0.0012418505779288064,5,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=0.6",H4,hypothesis-tests,S3,abrupt-brittle/intermediate +E4_L2_dis0.35_rt1,0.049169776701978085,0.001684671062653741,3,0.00028073198197937677,1.1742436207137804e-05,3,1.4495730447207697e-06,3.607460710781961e-08,3,0.03623932611801927,0.0009018651776955428,3,0.005621244126213648,0.00021859952563196724,3,0.00598691363719451,0.0005638062905279997,3,0.011413684857354618,0.0008006893902346605,3,34.0,7.54983443527075,3,1.3333333333333333,1.5275252316519468,3,0.31819657126843587,0.04438393749566272,3,0.6701127169828794,0.08463304073374207,3,14.333333333333334,5.686240703077327,3,0.036353160187573307,0.008161938582184312,3,0.3930677219308502,0.1123842486183057,3,0.049169776701978085,0.001684671062653741,3,0.014036599098968839,0.0005871218103568899,3,3,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=1",H4,hypothesis-tests,S3,intermediate +E4_L2_dis0.7_rt0.6,0.05138180927655467,0.0014455168462939648,3,0.00048042238681334355,8.018848680107096e-05,3,3.9681212896693625e-06,3.0293484647129673e-07,3,0.0992030322417341,0.007573371161782377,3,0.005690587901843215,0.0011722716015746663,3,0.011752961934936627,0.0004353940500421984,3,0.0300611124402102,0.004754533509751956,3,52.0,8.888194417315589,3,14.666666666666666,5.033222956847166,3,0.5521470459999784,0.09267964844800684,3,0.4609058991362575,0.027953432748435203,3,35.0,6.557438524302,3,0.05463799988214632,0.00917386676665997,3,0.20659415705581705,0.05421729491370209,3,0.05138180927655467,0.0014455168462939648,3,0.02402111934066718,0.00400942434005355,3,3,4,0.7,0.6,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=0.6",H4,hypothesis-tests,S3,abrupt-brittle/intermediate +E4_L2_dis0.7_rt1,0.0323108524152809,0.0005341821100204001,3,0.0002550422838303175,1.7113215639098243e-05,3,1.5001362046099095e-06,1.6752534224272985e-07,3,0.03750340511524775,0.00418813355606819,3,0.006887450323337182,0.0010342558372056331,3,0.008545532018317937,0.0005069979245411142,3,0.01906865335802616,0.0054151427454621716,3,30.666666666666668,6.429100507328637,3,2.6666666666666665,0.5773502691896258,3,0.48996111137110726,0.12909161441994588,3,0.6142786281179139,0.041418419234740086,3,12.0,3.605551275463989,3,0.032237233724829006,0.0067790322295486665,3,0.22698656147710072,0.08474137328236593,3,0.0323108524152809,0.0005341821100204001,3,0.012752114191515874,0.0008556607819549121,3,3,4,0.7,1.0,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=1",H4,hypothesis-tests,S3,intermediate +E4_L3_dis0.35_rt0.6,0.08030561101339338,0.0007217978429066968,5,0.0006116334646659999,4.372797174575331e-05,5,4.675506446019606e-06,7.276462511292299e-07,5,0.11688766115049018,0.018191156278230845,5,0.006456342748654552,0.0003663106703122358,5,0.008462370272957875,0.0008549948842301841,5,0.024031958301368082,0.009819372884503992,5,42.4,5.128352561983234,5,6.4,4.159326868617084,5,0.4950724783023627,0.11233673171714655,5,0.525878943231501,0.06865376187675147,5,26.2,4.764451699828639,5,0.047525882401409106,0.005692548825796943,5,0.3997631280494177,0.06960304707335471,5,0.08030561101339338,0.0007217978429066968,5,0.0305816732333,0.002186398587287667,5,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=0.6",H4,hypothesis-tests,S3,abrupt-brittle/intermediate +E4_L3_dis0.35_rt1,0.06801409701458377,0.0017131899628018425,3,0.00047969283454653446,5.963696964474604e-06,3,2.389827544945668e-06,2.9370533102944075e-07,3,0.05974568862364177,0.00734263327573606,3,0.006125733749659222,0.00040787069652483554,3,0.0077137676608803685,0.0002310181534926927,3,0.01358110543408731,0.005432295517155635,3,40.333333333333336,4.932882862316248,3,4.0,1.0,3,0.5223558546331495,0.10566554423336641,3,0.5228243146649506,0.18802091686674982,3,22.666666666666668,4.041451884327381,3,0.04518390473446653,0.005310947203835305,3,0.16036106231499914,0.12537618717264373,3,0.06801409701458377,0.0017131899628018425,3,0.023984641727326724,0.00029818484822373035,3,3,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=1",H4,hypothesis-tests,S3,intermediate +E4_L3_dis0.7_rt0.6,0.07361396827563896,0.0002600420155356786,3,0.0006391162104176754,4.982678140320154e-05,3,4.458350121842722e-06,5.561810094884932e-07,3,0.11145875304606812,0.013904525237212513,3,0.00844935719146162,0.0005764075487195893,3,0.009375567961986969,0.0006766652422034166,3,0.01918526102779174,0.0019830440255853223,3,45.333333333333336,6.027713773341707,3,5.0,7.0,3,0.4964147518923414,0.10759297821141484,3,0.5602525718810577,0.1244730257866298,3,33.0,7.211102550927978,3,0.04962620342705381,0.006495066272164419,3,0.2862097218590521,0.0918104416417187,3,0.07361396827563896,0.0002600420155356786,3,0.03195581052088376,0.0024913390701600743,3,3,4,0.7,0.6,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=0.6",H4,hypothesis-tests,S3,intermediate +E4_L3_dis0.7_rt1,0.054654026013368155,0.000707221086126521,3,0.00046068942071154293,4.295291891347058e-05,3,2.418108312183207e-06,1.514343030852001e-07,3,0.06045270780458025,0.003785857577130008,3,0.0081995720103185,0.0005865408389989655,3,0.008470646652613193,0.0008529697568750548,3,0.013456103109985915,0.001735896355630011,3,33.0,1.7320508075688772,3,0.3333333333333333,0.5773502691896258,3,0.36876120460201195,0.05439477937423051,3,0.5756384986143668,0.1564987540905005,3,18.0,1.7320508075688772,3,0.036133136699098546,0.0019449191905494235,3,0.1891620838216932,0.1108126447700374,3,0.054654026013368155,0.000707221086126521,3,0.02303447103557715,0.0021476459456735287,3,3,4,0.7,1.0,0.8,0.0,0.2,0.05,grid,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=1",H4,hypothesis-tests,S3,intermediate +E5_dis035_red0.25,0.04239620054413052,0.006045553463967511,2,0.00017057276729883137,2.7260271370431907e-05,2,1.2671563942805245e-06,3.109191828552614e-08,2,0.03167890985701311,0.0007772979571381674,2,0.003660027689677134,0.00021015165055121224,2,0.005139401948894639,0.00021085956218862032,2,0.020492833984906034,0.00017961694811515774,2,53.5,0.7071067811865476,2,5.0,0.0,2,0.35782226983734056,0.13338512634148442,2,0.40362536087053075,0.027766856891696994,2,29.0,2.8284271247461903,2,0.051000545256270444,0.0006053204179186923,2,0.5946273011281726,0.03034822511719826,2,0.04239620054413052,0.006045553463967511,2,0.008528638364941568,0.0013630135685215948,2,3,4,0.35,0.6,0.8,0.25,0.2,0.05,grid,redundancy r=0.25 at delta=0.35,H5,hypothesis-tests,S3,intermediate +E5_dis035_red0.5_s3,0.039617708901162715,,1,0.0002234354145047582,,1,1.4736760866050552e-06,,1,0.036841902165126325,,1,0.003702108283017342,,1,0.006405624229389848,,1,0.027512450375024106,,1,53.0,,1,5.0,,1,0.22561789106158825,,1,0.5686425061425062,,1,20.0,,1,0.04514480408858603,,1,0.47943440418803146,,1,0.039617708901162715,,1,0.011171770725237909,,1,3,4,0.35,0.6,0.8,0.5,0.2,0.05,grid,third seed r=0.5 delta=0.35,H5,hypothesis-tests,S3,progressive +E5_dis035_red0.75,0.04540307566682274,0.0012698051451350422,2,0.00024143505015332363,2.835910699610706e-05,2,1.7675325941597535e-06,2.1692935370560675e-07,2,0.044188314853993854,0.005423233842640212,2,0.0045431187262481455,0.0014466050896373053,2,0.005601197310119873,0.0004904140955536182,2,0.03003710596789235,0.0008314953538798965,2,59.5,16.263455967290593,2,2.0,1.4142135623730951,2,0.43519137517414463,0.13336647563184215,2,0.5745116487455197,0.026807964078855585,2,24.0,4.242640687119285,2,0.047082953853585394,0.012105214662050504,2,0.6032590336079211,0.038617793619934,2,0.04540307566682274,0.0012698051451350422,2,0.012071752507666181,0.0014179553498053533,2,3,4,0.35,0.6,0.8,0.75,0.2,0.05,grid,redundancy r=0.75 at delta=0.35,H5,hypothesis-tests,S3,intermediate +E5_dis035_red1_s3,0.04255679386837564,,1,0.00025704457476935565,,1,3.260079788349644e-06,,1,0.08150199470874092,,1,0.004024687371880427,,1,0.0062734697786490995,,1,0.06923526078211063,,1,70.0,,1,2.0,,1,0.3857823953095849,,1,0.568661971830986,,1,22.0,,1,0.05124450951683748,,1,0.7486638520602352,,1,0.04255679386837564,,1,0.012852228738467782,,1,3,4,0.35,0.6,0.8,1.0,0.2,0.05,grid,third seed r=1 delta=0.35,H5,hypothesis-tests,S3,intermediate +E5_dis1_red0.5,0.024699811740448913,0.004325030660014668,2,0.00013428096459729562,6.228763648652924e-06,2,1.3320512104861446e-06,1.0683361554097942e-07,2,0.03330128026215359,0.0026708403885244325,2,0.004971151015292111,0.0014567925177419046,2,0.005695980658249148,0.0004317286062620158,2,0.03515090071609768,0.001313170752705458,2,56.0,5.656854249492381,2,1.5,2.1213203435596424,2,0.6020387079363646,0.3779704320033504,2,0.6022964262015358,0.12630258341556094,2,21.5,2.1213203435596424,2,0.04822232574881699,0.00539640641414865,2,0.7042297327816232,0.02673816307117155,2,0.024699811740448913,0.004325030660014668,2,0.006714048229864782,0.0003114381824326452,2,3,4,1.0,0.6,0.8,0.5,0.2,0.05,grid,fully organic braced r=0.5,H5,hypothesis-tests,S3,abrupt-brittle/intermediate +E5_dis1_red1,0.029312890308538026,0.0016232818452958672,3,0.00023097229636716255,1.6668383907469942e-05,3,2.533038980710408e-06,5.605202657171464e-07,3,0.06332597451776018,0.01401300664292864,3,0.0057910812797368994,0.0013778609997174025,3,0.008585436525773848,0.0006127522282792845,3,0.05155344729153355,0.020049905527608016,3,72.66666666666667,9.451631252505216,3,6.333333333333333,2.0816659994661326,3,0.2725916162867137,0.021876801526954943,3,0.5791121786714092,0.16938483302168295,3,20.333333333333332,3.214550253664318,3,0.053628112337392675,0.006513473694335441,3,0.5642948658313103,0.13670810640842956,3,0.029312890308538026,0.0016232818452958672,3,0.011548614818358128,0.0008334191953734965,3,3,4,1.0,0.6,0.8,1.0,0.2,0.05,grid,fully organic braced r=1,H5,hypothesis-tests,S3,intermediate +E5_ord_red0.5,0.08527001949125226,0.00011331413376256128,2,0.0009595070258293501,5.0005642598821634e-05,2,5.4061708634453935e-06,5.698762737825842e-07,2,0.13515427158613413,0.01424690684456475,2,0.011252971498049177,0.0006013926538581067,2,0.011252971498049177,0.0006013926538581067,2,0.011252971498049177,0.0006013926538581067,2,26.5,3.5355339059327378,2,0.0,0.0,2,0.9977044376094231,0.0022616402312349054,2,0.8612583056478404,0.05074841940392819,2,20.0,2.8284271247461903,2,0.029885860999542428,0.004128893884756469,2,0.0,0.0,2,0.08527001949125226,0.00011331413376256128,2,0.0479753512914675,0.0025002821299410817,2,3,4,0.0,0.6,0.8,0.5,0.2,0.05,grid,ordered braced lattice r=0.5,H5,hypothesis-tests,S3,abrupt-brittle +E5_ord_red1,0.0762985419654385,0.0,5,0.0007534825568444138,1.952916923616703e-05,5,5.598246105656549e-06,9.665562762346777e-07,5,0.13995615264141234,0.024163906905866714,5,0.009644603405758356,0.0001877388983457396,5,0.010061065670329265,0.0003083139550210883,5,0.03475429343897515,0.030409426279317506,5,43.4,13.538833036861043,5,0.8,0.4472135954999579,5,0.5470082742588713,0.15505152642897202,5,0.8101887981139452,0.08968956166761988,5,22.4,8.203657720797473,5,0.04271653543307087,0.013325623067776618,5,0.29631161239079196,0.11302346876394664,5,0.0762985419654385,0.0,5,0.037674127842220684,0.0009764584618083514,5,3,4,0.0,0.6,0.8,1.0,0.2,0.05,grid,ordered braced lattice r=1,H5,hypothesis-tests,S3,abrupt-brittle/intermediate +E6_dis015_rt0.3,0.07496344417543022,0.0062719514177254,3,0.0003786132710342603,0.00011259978530188102,3,2.176089088843397e-06,1.3739502270137364e-06,3,0.054402227221085,0.0343487556753435,3,0.0032173234563939897,0.0008185007494515308,3,0.006019872395591483,0.0019563885156617922,3,0.028565082379183638,0.010589492082897275,3,40.333333333333336,9.073771725877467,3,11.333333333333334,6.8068592855540455,3,0.7666378492818563,0.18175919282834993,3,0.477295799236847,0.017621610583915842,3,16.0,6.082762530298219,3,0.04444183764935711,0.009895751328307306,3,0.38103360801025093,0.130881826234759,3,0.07496344417543022,0.0062719514177254,3,0.018930663551713012,0.005629989265094049,3,3,4,0.15,0.3,0.8,0.0,0.2,0.05,grid,delta=0.15 with strong thickness hierarchy,H2,hypothesis-tests,S3,abrupt-brittle/intermediate +E6_dis015_rt1,0.06711161016534196,0.0020366881810596205,2,0.0002919192385351734,1.0100865900068227e-05,2,1.302899229162515e-06,2.3779420321714999e-07,2,0.032572480729062894,0.005944855080428776,2,0.0043494767405711145,1.851152171274975e-05,2,0.0043494767405711145,1.851152171274975e-05,2,0.014958095093857773,0.0028516512831010653,2,49.0,1.4142135623730951,2,0.0,0.0,2,0.39596659171754894,0.21479964871048557,2,0.6003696759586812,0.032055940996553095,2,24.5,6.363961030678928,2,0.054049909823516956,0.0011806310452780182,2,0.5062098154867185,0.07118875051845784,2,0.06711161016534196,0.0020366881810596205,2,0.01459596192675867,0.0005050432950034098,2,3,4,0.15,1.0,0.8,0.0,0.2,0.05,grid,delta=0.15 with uniform thickness,H2,hypothesis-tests,S3,intermediate/progressive +E6_ord_rt0.3,0.10000000002167131,0.0,2,0.0014025420694722631,2.3011648875545004e-05,2,1.1464702203832673e-05,1.5269991194635608e-06,2,0.286617555095822,0.03817497798658973,2,0.014025420691683138,0.00023011648870560988,2,0.014025420691683138,0.00023011648870560988,2,0.02001757848586349,0.003440085124354659,2,30.5,6.363961030678928,2,0.0,0.0,2,0.8005838938813041,0.2395727023849736,2,0.6805132681564245,0.15306985412012422,2,27.0,7.0710678118654755,2,0.04013157894736842,0.00837363293510385,2,0.13240961998323533,0.14370698630782835,2,0.10000000002167131,0.0,2,0.07012710347361314,0.0011505824437772593,2,3,4,0.0,0.3,0.8,0.0,0.2,0.05,grid,"ordered, strong thickness hierarchy",H2,hypothesis-tests,S3,abrupt-brittle +E6_ord_rt1,0.10000000000878381,0.0,2,0.0017191261400964805,2.8371815196807485e-05,2,1.4778985826260878e-05,4.877472914254046e-07,2,0.36947464565651966,0.012193682285635022,2,0.017191261399454753,0.0002837181519431924,2,0.017191261399454753,0.0002837181519431924,2,0.017191261399454753,0.0002837181519431924,2,24.5,2.1213203435596424,2,0.0,0.0,2,0.9999999998885389,9.802715256546281e-12,2,0.6929048742138365,0.14022616788860587,2,0.0,0.0,2,0.051041666666666666,0.004419417382415924,2,0.0,0.0,2,0.10000000000878381,0.0,2,0.08595630700482403,0.0014185907598403833,2,3,4,0.0,1.0,0.8,0.0,0.2,0.05,grid,"ordered, uniform thickness, no interfaces (= flat grid with 2x2 nesting labels)",H2,hypothesis-tests,S3,abrupt-brittle +E7_ord_cv0.1,0.10000000002582583,0.0,3,0.0012532072972899582,5.330412773125532e-05,3,8.168089477042704e-06,5.936452231443798e-07,3,0.20420223692606707,0.014841130578609462,3,0.012532072969663036,0.0005330412771748929,3,0.012532072969663036,0.0005330412771748929,3,0.018966759409266263,0.00610204271374264,3,36.666666666666664,3.0550504633038926,3,0.0,0.0,3,0.8532672579566567,0.11631742878529476,3,0.7341306977336388,0.025259615791317414,3,31.333333333333332,2.5166114784235827,3,0.048245614035087724,0.004019803241189335,3,0.037845131396956395,0.02410418101470679,3,0.10000000002582583,0.0,3,0.0626603648644979,0.0026652063865627716,3,3,4,0.0,0.6,0.8,0.0,0.2,0.1,grid,ordered geometry with strength disorder CV=0.1: can statistics alone make failure progressive?,H1,hypothesis-tests,S3,abrupt-brittle +E7_ord_cv0.2,0.10000000002582583,0.0,3,0.0009767071758083948,8.227160398714114e-05,3,5.318073232201629e-06,4.1791466570827185e-07,3,0.13295183080504036,0.01044786664270678,3,0.00976707175556153,0.000822716039658935,3,0.00976707175556153,0.000822716039658935,3,0.01859383416158684,0.0058516949554801015,3,39.0,0.0,3,0.0,0.0,3,0.7684624826816252,0.34209540030862917,3,0.6860811899746978,0.0423013984948674,3,31.0,2.6457513110645907,3,0.05131578947368421,0.0,3,0.10193576037587652,0.09684886040392512,3,0.10000000002582583,0.0,3,0.04883535879041973,0.004113580199357062,3,3,4,0.0,0.6,0.8,0.0,0.2,0.2,grid,ordered geometry with strength disorder CV=0.2: can statistics alone make failure progressive?,H1,hypothesis-tests,S3,abrupt-brittle/intermediate +E7_ord_cv0.4,0.10000000002582583,0.0,3,0.0005856340735817077,7.736977051114422e-05,3,2.968235154137457e-06,6.374205316764164e-07,3,0.07420587885343623,0.015935513291910373,3,0.005722727660096375,0.0006757739783540703,3,0.006280181769328748,0.0012444366839895029,3,0.017234333370191354,0.0018073842469283322,3,47.666666666666664,10.016652800877814,3,2.6666666666666665,3.785938897200183,3,0.3829482101613603,0.018140360301346373,3,0.6385067315417542,0.032424653653587175,3,27.333333333333332,8.504900548115383,3,0.06271929824561404,0.01317980631694449,3,0.34153961460724647,0.14757197293156982,3,0.10000000002582583,0.0,3,0.02928170367908538,0.003868488525557211,3,3,4,0.0,0.6,0.8,0.0,0.2,0.4,grid,ordered geometry with strength disorder CV=0.4: can statistics alone make failure progressive?,H1,hypothesis-tests,S3,intermediate +E8_dis_notch06,0.041326622909094696,0.0064355266579495555,2,0.00016868634495530047,4.481527177879006e-05,2,1.1057352912887972e-06,1.139729176655915e-07,2,0.027809011242417823,0.002676927249660853,2,0.003839141913649055,0.0001611713186842682,2,0.0045242833024489535,0.0011301075628682225,2,0.03377555588478273,0.01897044978016121,2,50.5,4.949747468305833,2,2.0,2.8284271247461903,2,0.27750640173540786,0.04204287773689953,2,0.40169664396196963,0.04263135445180497,2,35.0,7.0710678118654755,2,0.05357827652092356,0.0057310437116995004,2,0.6227149097186147,0.1815488961335785,2,0.041326622909094696,0.0064355266579495555,2,0.008434317247765024,0.0022407635889395033,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,disordered reference with small edge notch r=0.06W,H7,hypothesis-tests,S3,intermediate/progressive +E8_dis_notch12_s3,0.034595619084901254,,1,0.00013951451519987466,,1,9.278786859482115e-07,,1,0.023793892885846046,,1,0.0032762397514228304,,1,0.0045541918721779436,,1,0.0230460866684341,,1,37.0,,1,3.0,,1,0.3306375122767737,,1,0.527279005524862,,1,21.0,,1,0.03948772678762007,,1,0.6296016955024389,,1,0.034595619084901254,,1,0.006975725759993732,,1,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,third seed disordered notch 0.12W,H7,hypothesis-tests,S3,intermediate +E8_dis_notch20,0.036237722299170834,0.007532665671604316,2,0.00014294964579230046,4.746716433275728e-05,2,8.469317082608685e-07,1.94684051832555e-07,2,0.0226598017234031,0.005094685760542837,2,0.0037790173719278682,0.00033988789536960916,2,0.004413520828855834,0.001237211289529752,2,0.018935125852582117,0.0004017732211480365,2,38.0,2.8284271247461903,2,2.0,2.8284271247461903,2,0.33086592755862626,0.029278435987861885,2,0.41396076441738544,0.044186699754511956,2,24.5,3.5355339059327378,2,0.04275840752357451,0.0028771123078584937,2,0.59212787425317,0.19091888935149331,2,0.036237722299170834,0.007532665671604316,2,0.007147482289615023,0.002373358216637864,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,disordered reference with large edge notch r=0.20W,H7,hypothesis-tests,S3,intermediate +E8_ord_notch,0.09625071283471154,0.0,3,0.00118822246504033,2.896223646919e-05,3,7.61400946042756e-06,2.0342524377451104e-07,3,0.19442305174327632,0.005194445436641141,3,0.012345077039385996,0.0003009041244081577,3,0.012345077039385996,0.0003009041244081577,3,0.01542746958775118,0.0016163757061757654,3,32.0,2.6457513110645907,3,0.0,0.0,3,0.7522977813413411,0.20079820107045793,3,0.7280722280722282,0.04958914188708171,3,30.333333333333332,2.081665999466133,3,0.04278074866310161,0.0035371006832414314,3,0.03647863572953804,0.03385292391678489,3,0.09625071283471154,0.0,3,0.0594111232520165,0.0014481118234595009,3,3,4,0.0,0.6,0.8,0.0,0.2,0.05,grid,ordered design with edge notch r=0.12W,H7,hypothesis-tests,S3,abrupt-brittle +E8_ord_notch06,0.10000000002578839,0.0,2,0.0014025420699640427,2.3011649450704753e-05,2,9.836945127584426e-06,3.227480644556084e-07,2,0.24736366442531998,0.00811594889210523,2,0.014025420696023513,0.00023011649444774652,2,0.014025420696023513,0.00023011649444774652,2,0.014025420696023513,0.00023011649444774652,2,33.0,1.4142135623730951,2,0.0,0.0,2,0.9942341203663467,0.0028739440036830194,2,0.736583138515488,0.06042539464888262,2,29.0,1.4142135623730951,2,0.043478260869565216,0.0018632589754586214,2,0.0,0.0,2,0.10000000002578839,0.0,2,0.07012710349820214,0.0011505824725352395,2,3,4,0.0,0.6,0.8,0.0,0.2,0.05,grid,ordered design with small edge notch r=0.06W,H7,hypothesis-tests,S3,abrupt-brittle +E9_ref_dis_movie,0.03697465880742474,,1,0.000132751224964839,,1,1.0271719676124389e-06,,1,0.025679299190310978,,1,0.0035903299515554045,,1,0.0035903299515554045,,1,0.04717960352653455,,1,54.0,,1,0.0,,1,0.2556227571243103,,1,0.371551724137931,,1,40.0,,1,0.05732484076433121,,1,0.7679937176416575,,1,0.03697465880742474,,1,0.006637561248241951,,1,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,"disordered reference, full state history for movie/snapshots",representative,hypothesis-tests,S3,intermediate +E9_ref_ord_movie,0.10000000002582585,,1,0.0013862703765912987,,1,9.608727782591333e-06,,1,0.24021819456478272,,1,0.013862703762332798,,1,0.013862703762332798,,1,0.013862703762332798,,1,34.0,,1,0.0,,1,0.9962663056601007,,1,0.6938559322033898,,1,30.0,,1,0.04473684210526316,,1,0.0,,1,0.10000000002582585,,1,0.06931351882956494,,1,3,4,0.0,0.6,0.8,0.0,0.2,0.05,grid,"ordered reference, full state history for movie/snapshots",representative,hypothesis-tests,S3,abrupt-brittle +F10_L3_movie,0.08084348685872705,,1,0.0006380202818826803,,1,5.674481595693485e-06,,1,0.14186203989233725,,1,0.006932243754662316,,1,0.009230002727628568,,1,0.021803420030638388,,1,47.0,,1,9.0,,1,0.4825730487894214,,1,0.5878731343283582,,1,28.0,,1,0.052808988764044947,,1,0.41686795307830965,,1,0.08084348685872705,,1,0.03190101409413401,,1,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,L3 design full state history (movie),representative,refinement,S4,intermediate +F10_flat_ord_movie,0.10000000000878408,,1,0.0017328379703385511,,1,1.5013637155916313e-05,,1,0.3753409288979055,,1,0.01732837970186335,,1,0.01732837970186335,,1,0.01732837970186335,,1,27.0,,1,0.0,,1,0.9999999998613223,,1,0.6521946564885497,,1,0.0,,1,0.05625,,1,0.0,,1,0.10000000000878408,,1,0.08664189851692755,,1,0,4,0.0,1.0,0.8,0.0,0.2,0.05,grid,flat ordered grid full state history (movie),representative,refinement,S4,abrupt-brittle +F10_ord_red1_movie,0.0762985419654385,,1,0.0007570805791326593,,1,4.714956727313153e-06,,1,0.11787391818282768,,1,0.009673627659670852,,1,0.010154925514853847,,1,0.012327011518398783,,1,34.0,,1,1.0,,1,0.3899601032000122,,1,0.8327546296296297,,1,15.0,,1,0.03346456692913386,,1,0.16739010593564047,,1,0.0762985419654385,,1,0.037854028956632965,,1,3,4,0.0,0.6,0.8,1.0,0.2,0.05,grid,ordered braced lattice full state history (movie),representative,refinement,S4,intermediate +F1_L3_dis0.15_rt0.6,0.09080146280106212,0.0009135618184017154,3,0.0006100265463766539,7.51954274611338e-06,3,4.806060001585467e-06,7.122243961465997e-07,3,0.12015150003963689,0.017805609903665063,3,0.004892187028296856,0.00025741715143420455,3,0.00883514914917857,0.00048087975555423135,3,0.023161257051682694,0.0057344795294975975,3,59.666666666666664,13.051181300301263,3,15.0,1.0,3,0.40424239927326294,0.051341208758346114,3,0.410432893698359,0.20883277455735122,3,38.0,7.0,3,0.07089385157041085,0.015353805906211571,3,0.3235113545424098,0.17481166073798865,3,0.09080146280106212,0.0009135618184017154,3,0.030501327318832695,0.00037597713730567166,3,3,4,0.15,0.6,0.8,0.0,0.2,0.05,grid,L3 design: disorder of the finest level delta=0.15,H4,refinement,S4,intermediate +F1_L3_dis0.5_rt0.6,0.07664787548400166,0.0006516596533962957,3,0.0006321893985048371,2.7705403332403026e-05,3,4.233616173825487e-06,4.2762998164631796e-07,3,0.10584040434563702,0.010690749541157877,3,0.007392987798899822,0.0008703308222343409,3,0.008687693887857449,0.0010166743770408091,3,0.02133884130324956,0.005981741776657597,3,47.0,11.0,3,3.3333333333333335,4.932882862316247,3,0.5670495547844321,0.10963170690978703,3,0.4988525060812868,0.09893683842507656,3,33.666666666666664,8.504900548115383,3,0.05194984564217103,0.012017938273768803,3,0.3176794758737827,0.16264138615402104,3,0.07664787548400166,0.0006516596533962957,3,0.031609469925241857,0.0013852701666201518,3,3,4,0.5,0.6,0.8,0.0,0.2,0.05,grid,L3 design: disorder of the finest level delta=0.5,H4,refinement,S4,abrupt-brittle/intermediate 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+F2_L3_dis0.35_rt0.3,0.09264025712123514,0.00017718091032751157,3,0.0008946404031145035,2.6515335318573407e-05,3,1.0213595092765821e-05,3.3394432763238147e-07,3,0.2553398773191455,0.008348608190809551,3,0.004184686223838812,0.0009414972547821264,3,0.012807247256796994,0.004397255276266963,3,0.02250687197168902,0.008289687253733458,3,49.666666666666664,18.556220879622373,3,19.0,19.078784028338912,3,0.9501672401905848,0.048478486459586294,3,0.5044693512387936,0.1886978582594472,3,28.333333333333332,14.047538337136986,3,0.05571171487146084,0.02098345405630958,3,0.352583830436723,0.3055376123267821,3,0.09264025712123514,0.00017718091032751157,3,0.04473202015572517,0.0013257667659286726,3,3,4,0.35,0.3,0.8,0.0,0.2,0.05,grid,L3 design: thickness ratio r_t=0.3,H4/H2,refinement,S4,abrupt-brittle +F2_L3_dis0.35_rt0.45,0.08601411703645133,0.00040719829702370413,3,0.0007560109488278856,8.620048219930972e-06,3,6.602366024366315e-06,8.228791844048293e-07,3,0.16505915060915807,0.020571979610120927,3,0.0061572596191205925,0.0005264796124093783,3,0.009271143370992553,0.0006134661637697466,3,0.020907245609678285,0.00651204087418398,3,44.333333333333336,5.131601439446883,3,7.333333333333333,5.131601439446884,3,0.6381301397775329,0.08150263673304507,3,0.567019545724955,0.02566078268179277,3,25.666666666666668,3.785938897200182,3,0.04966659568515944,0.005524275731611686,3,0.4417409552069698,0.10223488265784314,3,0.08601411703645133,0.00040719829702370413,3,0.03780054744139428,0.0004310024109965491,3,3,4,0.35,0.45,0.8,0.0,0.2,0.05,grid,L3 design: thickness ratio r_t=0.45,H4/H2,refinement,S4,abrupt-brittle/intermediate +F2_L3_dis0.35_rt0.8,0.07388148881371127,0.0014579801418101374,3,0.0005630967635777106,4.555247227211105e-05,3,3.7845057770232697e-06,2.6187851638530356e-07,3,0.09461264442558193,0.006546962909632848,3,0.0065889560067115245,0.0004325266033861825,3,0.008576190470400225,0.0014422076975482297,3,0.014326098860515288,0.0028777522006719018,3,42.666666666666664,1.5275252316519468,3,6.0,3.4641016151377544,3,0.44129337040367017,0.13253904407933123,3,0.5118874493851883,0.051714335109150786,3,28.666666666666668,1.5275252316519463,3,0.04781147311679798,0.0015547944227396577,3,0.3061405214516875,0.1633253425336764,3,0.07388148881371127,0.0014579801418101374,3,0.028154838178885533,0.002277623613605552,3,3,4,0.35,0.8,0.8,0.0,0.2,0.05,grid,L3 design: thickness ratio r_t=0.8,H4/H2,refinement,S4,intermediate +F3_L3_red0.5,0.0678174081224009,0.001254404695283701,3,0.0005705704032307606,2.20866963586008e-05,3,3.6268673051594877e-06,5.613538763787803e-07,3,0.09067168262898728,0.014033846909469488,3,0.0057027492633450125,0.000246229425324216,3,0.009018478043788964,0.0006572057534333499,3,0.019875554936505103,0.009127706670519192,3,53.666666666666664,18.903262505010435,3,9.333333333333334,4.725815626252608,3,0.5401131223651637,0.18132137717387078,3,0.5371971900589969,0.16671472710592852,3,22.666666666666668,11.015141094572204,3,0.04932469507249566,0.0173072407831158,3,0.24907575792224676,0.09256202846147726,3,0.0678174081224009,0.001254404695283701,3,0.02852852016153803,0.0011043348179300427,3,3,4,0.35,0.6,0.8,0.5,0.2,0.05,grid,L3 design with braces r=0.5 (does bracing help a mixed design?),H5,refinement,S4,abrupt-brittle/intermediate +F3_L3_red1,0.060555248024228014,0.0007319477900451309,3,0.0005543536008448957,1.1245687439104219e-05,3,3.864452348669545e-06,9.702200935466617e-07,3,0.09661130871673872,0.02425550233866672,3,0.0053316573421972316,0.00048654362698872757,3,0.00998936870644421,0.00029926018815613,3,0.017930533667837558,0.004918959775928962,3,62.666666666666664,19.42506971244462,3,13.0,2.6457513110645907,3,0.5609041624702896,0.3201150118376376,3,0.6018962576330346,0.15266254967124923,3,19.666666666666668,4.04145188432738,3,0.04939048861116113,0.015155814266373607,3,0.2177581364707739,0.15873112834629965,3,0.060555248024228014,0.0007319477900451309,3,0.027717680042244786,0.0005622843719552145,3,3,4,0.35,0.6,0.8,1.0,0.2,0.05,grid,L3 design with braces r=1 (does bracing help a mixed design?),H5,refinement,S4,abrupt-brittle/intermediate +F4_L3_sint0.5,0.08030245364852781,0.0009547356363205961,3,0.00041097975765858275,3.433805236678244e-05,3,3.6001665719066728e-06,9.01611510885356e-07,3,0.0900041642976669,0.02254028777213392,3,0.004660650300064635,0.0005592679401146408,3,0.005377844137775804,0.0005875119870395726,3,0.02157838475658851,0.006295238378278269,3,57.0,5.196152422706632,3,2.6666666666666665,3.7859388972001824,3,0.7230501860320978,0.1122626268711788,3,0.5565513239359293,0.05492244597918093,3,54.0,4.358898943540674,3,0.0638958826550424,0.006096555020190332,3,0.6676173621743181,0.11418671850180646,3,0.08030245364852781,0.0009547356363205961,3,0.020548987882929137,0.0017169026183391227,3,3,4,0.35,0.6,0.5,0.0,0.2,0.05,grid,L3 design with s_int=0.5,H3,refinement,S4,abrupt-brittle/intermediate +F4_L3_sint1.5,0.08030245364852781,0.0009547356363205961,3,0.0008640513674926254,5.742638379273286e-05,3,6.173843259798385e-06,5.338283254788324e-07,3,0.15434608149495976,0.013345708136970813,3,0.006640091603685848,0.00027924910245678445,3,0.011829803409465545,0.00085394231401167,3,0.017048368239292167,0.0009232226351708932,3,45.333333333333336,6.110100926607787,3,13.333333333333334,1.5275252316519468,3,0.5328489797150618,0.13106526595259085,3,0.3891212032804952,0.11877451078613033,3,0.0,0.0,3,0.05078434565488791,0.00661710088935043,3,0.12970694833326837,0.04892021314904668,3,0.08030245364852781,0.0009547356363205961,3,0.04320256837463127,0.0028713191896366417,3,3,4,0.35,0.6,1.5,0.0,0.2,0.05,grid,L3 design with s_int=1.5,H3,refinement,S4,abrupt-brittle/intermediate +F5_L3_notch,0.0794208448370396,0.0008378285089016366,3,0.0006613417592756767,4.872557459821556e-05,3,5.037944533724122e-06,2.4009100197063e-07,3,0.12864683701459192,0.006135683309711909,3,0.006645122219100209,0.0002588970107385857,3,0.008833667785718305,0.0008383718592949827,3,0.014852266676665308,0.0014694924997495657,3,42.0,5.291502622129181,3,6.666666666666667,4.041451884327381,3,0.48647334997981445,0.10650825788509896,3,0.5557994864612512,0.12923865644968313,3,24.666666666666668,5.507570547286102,3,0.04783248118589964,0.005992906502820182,3,0.39275118321653335,0.09123402087875179,3,0.0794208448370396,0.0008378285089016366,3,0.03306708796378383,0.0024362787299107773,3,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,L3 design with edge notch r=0.12W,H7,refinement,S4,abrupt-brittle/intermediate +F5_ord_red1_notch,0.07494103601849122,0.0,3,0.0007707018670926044,2.1094583698037412e-05,3,5.198437561385562e-06,2.05458089384356e-07,3,0.13301345610046447,0.005257097008495614,3,0.010115748473491318,0.0005087229782915144,3,0.010365828616833224,0.000231049160703563,3,0.016779040203514953,0.007451321799891698,3,37.333333333333336,5.507570547286102,3,0.3333333333333333,0.5773502691896258,3,0.5788334276718795,0.1739348361854912,3,0.8355592637227939,0.0773376821440984,3,19.0,4.358898943540674,3,0.03744567034436643,0.005524142976214744,3,0.22548102786155713,0.041187441213712005,3,0.07494103601849122,0.0,3,0.03853509335463022,0.0010547291849018687,3,3,4,0.0,0.6,0.8,1.0,0.2,0.05,grid,ordered fully braced lattice with edge notch r=0.12W,H7,refinement,S4,abrupt-brittle/intermediate +F6_L3_cv0.2,0.08030245364852781,0.0009547356363205961,3,0.000536346257762747,4.8779589739757844e-05,3,3.5008791991656177e-06,3.4774997886832e-07,3,0.08752197997914052,0.008693749471707998,3,0.0050705347160861156,0.0006503220299435244,3,0.0073919739080191465,0.00028670508257031376,3,0.026878980697686555,0.016112773762442956,3,61.0,7.211102550927978,3,7.333333333333333,2.081665999466133,3,0.42572594436503736,0.03774861941439646,3,0.428512849252965,0.1373252313690366,3,40.666666666666664,6.658328118479393,3,0.06834350039039828,0.00786147599312336,3,0.3894592484995993,0.04906902094667397,3,0.08030245364852781,0.0009547356363205961,3,0.026817312888137348,0.0024389794869878927,3,3,4,0.35,0.6,0.8,0.0,0.2,0.2,grid,L3 design with strength CV 0.2,H1,refinement,S4,intermediate +F6_dis_cv0.4,0.0394629781602585,0.005601216520390347,3,9.752889134707626e-05,1.6165603073645162e-05,3,5.497359521770156e-07,3.9191930301919026e-08,3,0.013743398804425391,0.0009797982575479747,3,0.0022325651438673704,0.0008141946106639532,3,0.0030562461220371897,0.00074824111610707,3,0.023226237693135393,0.011973010034647852,3,45.666666666666664,3.7859388972001833,3,1.6666666666666667,2.8867513459481287,3,0.3494767145037925,0.07025454059726813,3,0.3801854411343209,0.14793117523864982,3,23.0,7.0,3,0.04815590699966946,0.004308161452131581,3,0.7013497422181308,0.09030765999728751,3,0.0394629781602585,0.005601216520390347,3,0.004876444567353813,0.0008082801536822579,3,3,4,0.35,0.6,0.8,0.0,0.2,0.4,grid,disordered reference with strength CV 0.4,H1,refinement,S4,intermediate +F7_D6_L2,0.062241932821646064,0.0008387287049023789,3,0.0004437071689722142,5.192446501256398e-05,3,3.806245748749562e-06,1.0511476959833696e-06,3,0.09515614371873911,0.026278692399584285,3,0.005161309862928088,0.0010301101870282634,3,0.008658653224605463,0.0018749458018893534,3,0.029986249978215085,0.010263003507711472,3,54.666666666666664,14.502873278538063,3,11.666666666666666,8.386497083606082,3,0.6465321747101355,0.16753438995108064,3,0.40214858972260553,0.24185801431753737,3,41.666666666666664,11.239810200058244,3,0.04944859424915852,0.013307126904057928,3,0.4314323771332457,0.0665401935921691,3,0.062241932821646064,0.0008387287049023789,3,0.022185358448610706,0.0025962232506282004,3,6,2,0.35,0.7745966692414834,0.8,0.0,0.2,0.05,grid,D=6 (fixed contrast) with levels >= 2 disordered,H4,refinement,S4,abrupt-brittle/intermediate +F7_D6_L4,0.08138363460963222,0.0004961429317785331,3,0.000747225679462829,0.0001040451091265156,3,5.180466405727081e-06,7.794956466351299e-07,3,0.12951166014317692,0.01948739116587801,3,0.007813099697557268,0.0005608300075960406,3,0.009418021753830089,0.0015904303204420597,3,0.01597396312583659,0.0023453654173438547,3,47.333333333333336,2.0816659994661335,3,4.0,4.58257569495584,3,0.49028970445120096,0.23900665257581896,3,0.5739470780333983,0.07804835963395171,3,38.0,1.7320508075688772,3,0.04350682232469815,0.001964823375120576,3,0.3040204066091724,0.1459062996579743,3,0.08138363460963222,0.0004961429317785331,3,0.037361283973141445,0.0052022554563257795,3,6,2,0.35,0.7745966692414834,0.8,0.0,0.2,0.05,grid,D=6 (fixed contrast) with levels >= 4 disordered,H4,refinement,S4,abrupt-brittle/intermediate +F7_D6_L5,0.08124174076346359,0.0004917794811224579,3,0.0007307516670662179,3.719481084541723e-05,3,5.016590314878381e-06,4.263371292989682e-07,3,0.12541475787195958,0.010658428232474046,3,0.00704735098980704,0.0007846855962426875,3,0.009209213906065753,0.0005664585800545873,3,0.02353437488828707,0.010544859712023872,3,58.0,9.539392014169456,3,3.6666666666666665,1.5275252316519465,3,0.5340592976465665,0.15587121893361322,3,0.5232402457163118,0.041987179659492564,3,48.333333333333336,10.115993936995677,3,0.05440287514011214,0.009054042150910864,3,0.3157103593622086,0.06292597463522863,3,0.08124174076346359,0.0004917794811224579,3,0.0365375833533109,0.0018597405422708583,3,6,2,0.35,0.7745966692414834,0.8,0.0,0.2,0.05,grid,D=6 (fixed contrast) with levels >= 5 disordered,H4,refinement,S4,abrupt-brittle/intermediate +F7_D6_L6,0.11042006987188942,1.740812791335271e-05,3,0.0015379798609813824,3.923080488153742e-05,3,1.0719157774857981e-05,5.473509643228843e-07,3,0.26797894437144887,0.013683774108071402,3,0.01392848192124585,0.0003574173465273256,3,0.01392848192124585,0.0003574173465273256,3,0.014095847957763136,0.0005660475903868859,3,29.0,1.0,3,0.0,0.0,3,0.9935246794860113,0.00683083310122548,3,0.7699206731873077,0.06052375268983154,3,26.666666666666668,1.1547005383792517,3,0.02856890712201748,0.0008586184707394261,3,0.00032755056477828384,0.0005673342202438683,3,0.11042006987188942,1.740812791335271e-05,3,0.07689899304906911,0.0019615402440768706,3,6,2,0.35,0.7745966692414834,0.8,0.0,0.2,0.05,grid,D=6 (fixed contrast) with levels >= 6 disordered,H4,refinement,S4,abrupt-brittle +F8_ord_rt0.6_noif,0.1000000000087841,0.0,3,0.001724634712274321,2.221515367165684e-05,3,1.487346949611003e-05,3.8174625368636223e-07,3,0.37183673740274975,0.009543656342159031,3,0.01724634712122827,0.00022215153669705124,3,0.01724634712122827,0.00022215153669705124,3,0.01724634712122827,0.00022215153669705124,3,30.666666666666668,4.618802153517006,3,0.0,0.0,3,0.995168022707685,0.004422084485442086,3,0.6874483570001915,0.08096726371906539,3,0.0,0.0,3,0.06388888888888888,0.009622504486493762,3,0.0,0.0,3,0.1000000000087841,0.0,3,0.08623173561371604,0.0011107576835828507,3,3,4,0.0,0.6,0.8,0.0,0.2,0.05,grid,ordered hierarchical (r_t=0.6) without interface elements,H3,refinement,S4,abrupt-brittle +F9_n0_1x4,0.01838565432766081,0.004529115619408747,2,8.540903575128146e-05,1.2956179343050995e-05,2,5.402252056515905e-07,5.555980236982218e-08,2,0.013505630141289773,0.0013889950592455803,2,0.0034519799461033736,0.0002020362556543948,2,0.005679473755425301,0.0009444701790317276,2,0.029852045462899567,0.019524371056986446,2,26.5,0.7071067811865476,2,4.0,2.8284271247461903,2,0.2898953024926169,0.03322516353318081,2,0.6529415905393567,0.0010563242648497333,2,21.0,4.242640687119285,2,0.027647645315993306,0.0007581185380003412,2,0.5057057059740884,0.07787376068900834,2,0.01838565432766081,0.004529115619408747,2,0.004270451787564073,0.0006478089671525495,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,anisotropic level-0: 1x4 (horizontal level-0 walls only),H2,refinement,S4,intermediate +F9_n0_4x1,0.03700720164556122,0.0023435182180711837,2,0.00020910541156695804,5.894855181491719e-06,2,1.3177767920680786e-06,1.8535569459714196e-07,2,0.032944419801702,0.004633892364928548,2,0.004003525837155414,0.0005370442415071444,2,0.007882615372249371,0.001152918005097368,2,0.03243709717638794,0.004830313392136429,2,59.5,13.435028842544403,2,17.0,14.142135623730951,2,0.7296224298448164,0.10390039733311682,2,0.33206990387333896,0.1261851742861702,2,38.5,10.606601717798213,2,0.06172655033926437,0.014246303451335847,2,0.2508172329515783,0.07703701694940214,2,0.03700720164556122,0.0023435182180711837,2,0.010455270578347903,0.00029474275907458516,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,"anisotropic level-0: 4x1 (vertical level-0 walls only, aligned with the load)",H2,refinement,S4,abrupt-brittle +F9_n0_4x1_L1,0.07532137486074196,0.0007968025756350756,3,0.0007799153766564373,4.5103815132560386e-05,3,6.578116159611836e-06,3.3390058062081817e-07,3,0.16445290399029575,0.008347514515520495,3,0.004899025476212013,0.00027421841113697484,3,0.013731023062249659,0.0008837078417701195,3,0.015575829165743571,0.0002992279607675853,3,46.666666666666664,11.015141094572206,3,30.666666666666668,9.60902353693305,3,0.37278489470864157,0.029597820687093955,3,0.4267893679258612,0.08643984335996548,3,28.666666666666668,11.060440015358038,3,0.0487277468426995,0.011427767473088206,3,0.11459174870456947,0.0744139421271342,3,0.07532137486074196,0.0007968025756350756,3,0.03899576883282186,0.00225519075662802,3,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,aligned straight level-0 stringers + disordered finer levels,H4,refinement,S4,intermediate +H01_dis0.08,0.09036723322114787,0.0019293655301748217,3,0.0004977292061689285,2.5557073164870114e-05,3,3.172637197411266e-06,7.884943641902596e-07,3,0.0793159299352816,0.019712359104756525,3,0.00477629360040966,3.357670990739882e-05,3,0.0056935825765768375,0.0003344195588319845,3,0.02904139569081123,0.00802963991340648,3,50.333333333333336,5.686240703077327,3,1.6666666666666667,1.1547005383792517,3,0.3888153909248935,0.17127367303311425,3,0.5589250346603287,0.12584559180603316,3,34.666666666666664,7.505553499465136,3,0.05867339036874449,0.006468723575301076,3,0.5238869165581735,0.11562711405272744,3,0.09036723322114787,0.0019293655301748217,3,0.02488646030844643,0.0012778536582435049,3,3,4,0.08,0.6,0.8,0.0,0.2,0.05,grid,disorder between 0.05 and 0.1 (transition region),holdout,holdout,S5,intermediate/progressive +H02_L3_dis0.5_rt0.5,0.0814694423126114,0.0006651432525243349,3,0.0007087096015390952,3.5313037856190234e-05,3,6.047836990346879e-06,8.741633473968928e-07,3,0.15119592475867202,0.021854083684922344,3,0.007997119451142459,0.0004793815937588317,3,0.00883050889287248,0.0004947851876052541,3,0.027038263984510317,0.00896028383280523,3,47.333333333333336,12.013880860626733,3,3.0,2.0,3,0.5597080835282185,0.12590288038677816,3,0.4862322562787697,0.17511231793062693,3,28.666666666666668,10.066445913694333,3,0.05213522987948693,0.013032980828028048,3,0.46084462641759494,0.14785682511016265,3,0.0814694423126114,0.0006651432525243349,3,0.03543548007695476,0.0017656518928095104,3,3,4,0.5,0.5,0.8,0.0,0.2,0.05,grid,level-selective design with new disorder and thickness-ratio values,holdout,holdout,S5,abrupt-brittle/intermediate +H03_L2_dis0.7_rt0.8,0.04104405681200087,0.001622850582094148,3,0.00031536906138285444,1.7993780966850273e-05,3,2.2487411335140065e-06,1.7471656612500917e-07,3,0.05621852833785012,0.0043679141531252,3,0.006106988757248362,0.0010956642031449218,3,0.008389159748987535,0.0007978348511092962,3,0.02736640538936387,0.009750770688354334,3,46.333333333333336,6.027713773341707,3,4.666666666666667,1.1547005383792517,3,0.5744610008802807,0.13470482372190024,3,0.47153063552199054,0.033717096646275854,3,30.666666666666668,5.033222956847167,3,0.04884280299654838,0.006362043077369202,3,0.3755488150791033,0.06907349043004803,3,0.04104405681200087,0.001622850582094148,3,0.01576845306914272,0.0008996890483425133,3,3,4,0.7,0.8,0.8,0.0,0.2,0.05,grid,"level-selective (levels >= 2) organic fine levels, weak thickness hierarchy",holdout,holdout,S5,abrupt-brittle/intermediate +H04_ord_sint0.7,0.10000000002582583,0.0,3,0.0012231451456871352,1.1280628793656939e-05,3,7.564301468301997e-06,2.1438404655725356e-07,3,0.18910753670754943,0.005359601163931326,3,0.012231451453712468,0.00011280628790743649,3,0.012231451453712468,0.00011280628790743649,3,0.01578105491989949,0.0032418235412162992,3,35.666666666666664,3.214550253664319,3,0.0,0.0,3,0.9848307809425562,0.006054942765553853,3,0.6412403406269734,0.06677809942147932,3,33.333333333333336,2.5166114784235836,3,0.04692982456140351,0.004229671386400421,3,0.010846134378100664,0.010212728516512391,3,0.10000000002582583,0.0,3,0.06115725728435676,0.0005640314396828509,3,3,4,0.0,0.6,0.7,0.0,0.2,0.05,grid,ordered hierarchy with s_int = 0.7 (interpolation of the s_int law),holdout,holdout,S5,abrupt-brittle +H05_D6_rt0.65,0.0519635620925764,0.0026251227791698885,3,0.00029581687390672836,7.880000967083139e-05,3,2.2049618847031194e-06,5.964126293185513e-07,3,0.055124047117577964,0.01491031573296374,3,0.003349406527520919,0.0009965664618601427,3,0.007234655073208683,0.0009934287482004783,3,0.022209835345251297,0.004749428756890515,3,69.0,5.291502622129181,3,12.333333333333334,3.7859388972001824,3,0.6309742715208954,0.1628041134864,3,0.38744146342401836,0.14273965717804024,3,56.0,4.58257569495584,3,0.06197612275088732,0.0047555298754129996,3,0.4435045641584825,0.04557781781403834,3,0.0519635620925764,0.0026251227791698885,3,0.014790843695336417,0.00394000048354157,3,6,2,0.35,0.65,0.8,0.0,0.2,0.05,grid,deep hierarchy D=6 with r_t=0.65 (f0 ~ 0.25),holdout,holdout,S5,abrupt-brittle/intermediate +H06_ord_cv0.3,0.10000000002582583,0.0,3,0.0007021670042473425,4.377387428956763e-05,3,3.21248986610982e-06,3.1209310666804427e-07,3,0.08031224665274529,0.0078023276667010906,3,0.006988510960924528,0.0003819143401912555,3,0.007072084384498929,0.0005232805280428248,3,0.02069498341726291,0.011340030986046003,3,45.0,10.14889156509222,3,0.3333333333333333,0.5773502691896258,3,0.45970859493349714,0.14334730748852537,3,0.42332178271324744,0.1747714845103258,3,32.0,7.211102550927978,3,0.05921052631578947,0.013353804690910812,3,0.21720231860840897,0.10475155326788406,3,0.10000000002582583,0.0,3,0.03510835021236712,0.0021886937144783808,3,3,4,0.0,0.6,0.8,0.0,0.2,0.3,grid,ordered geometry with strength CV 0.3 (between 0.2 and 0.4),holdout,holdout,S5,intermediate +H07_dis0.35_red1_rt0.45,0.05582017805308132,0.005887072553358978,3,0.00039523754457580583,5.689517006424409e-05,3,2.6431433773741767e-06,6.879887827876134e-07,3,0.0660785844343544,0.017199719569690297,3,0.0038564584928647808,0.000244405284461372,3,0.008445642937234786,0.0020236381624629454,3,0.02478927409842718,0.008108170276238424,3,64.66666666666667,3.7859388972001833,3,12.666666666666666,12.42309676905615,3,0.4893269908255599,0.2760133579740402,3,0.5957282405203745,0.10960775341224069,3,21.666666666666668,1.5275252316519463,3,0.04726436055635811,0.0028782341706783824,3,0.2916744195181195,0.16479623673535035,3,0.05582017805308132,0.005887072553358978,3,0.01976187722879029,0.002844758503212204,3,3,4,0.35,0.45,0.8,1.0,0.2,0.05,grid,fully braced disordered design with stronger thickness hierarchy,holdout,holdout,S5,abrupt-brittle/intermediate/progressive +H08_L3_red1_dis0.7,0.05520372904337046,0.001642543188150446,3,0.0005117242095913377,2.0995665960244752e-05,3,3.1365161931818416e-06,3.192388226527372e-07,3,0.07841290482954615,0.007980970566318597,3,0.006872643583631492,0.00010020100744753734,3,0.00952960874926511,0.0005826754440416027,3,0.02200073404755763,0.003335448926513539,3,55.0,10.535653752852738,3,4.666666666666667,1.5275252316519465,3,0.561093694140108,0.15606452636952425,3,0.5946340274806255,0.10018776676494685,3,17.333333333333332,4.725815626252609,3,0.04244818055983581,0.008036642536879591,3,0.20450716053304988,0.08251536804034137,3,0.05520372904337046,0.001642543188150446,3,0.025586210479566884,0.001049783298012239,3,3,4,0.7,0.6,0.8,1.0,0.2,0.05,grid,level-selective + braces + organic finest level,holdout,holdout,S5,abrupt-brittle/intermediate +H09_ord_red1_sint0.5,0.0762985419654385,0.0,3,0.0004686360846860635,1.9955945555093412e-05,3,4.745698168827727e-06,5.505604296684104e-07,3,0.11864245422069201,0.013764010741710124,3,0.005804007699618564,0.00016357940962488811,3,0.006470922739916084,0.0005099702470624667,3,0.039070432820376505,0.0048746109980731854,3,72.0,6.557438524302,3,2.0,1.7320508075688772,3,0.42510635626372917,0.07990784035967902,3,0.6056294419447926,0.05815537174893664,3,46.0,5.5677643628300215,3,0.07086614173228346,0.006454171775887798,3,0.6643030105439592,0.045472558114850986,3,0.0762985419654385,0.0,3,0.023431804234303175,0.0009977972777546716,3,3,4,0.0,0.6,0.5,1.0,0.2,0.05,grid,ordered braced lattice with weak interfaces,holdout,holdout,S5,intermediate +H10_dis1_rt0.3,0.027648292088316703,0.0063172886592729035,3,0.00014906845506334747,6.568886322044047e-05,3,1.6960677175139434e-06,5.866423071602029e-07,3,0.042401692937848595,0.014666057679005159,3,0.002639872339198607,0.0007410689528359268,3,0.006087880052683444,0.0018632915078017802,3,0.03909815925461578,0.013301842057449784,3,61.333333333333336,19.139836293274122,3,7.333333333333333,5.507570547286102,3,0.6727195257141586,0.13112514026883715,3,0.26357384986269555,0.08139831785570602,3,29.333333333333332,11.718930554164631,3,0.06406910314121735,0.019859908491947274,3,0.6649231254218454,0.27448530112945413,3,0.027648292088316703,0.0063172886592729035,3,0.007453422753167373,0.0032844431610220236,3,3,4,1.0,0.3,0.8,0.0,0.2,0.05,grid,fully organic with strong thickness hierarchy (f0 ~ 0.45),holdout,holdout,S5,abrupt-brittle/intermediate +H11_4x1_L1_rt0.45,0.09312784548262909,0.0009713108956753645,3,0.0013059851489641593,3.3955327790118795e-05,3,1.1328889710810714e-05,7.585292608256593e-07,3,0.2832222427702676,0.018963231520641242,3,0.004914053759805849,0.0006134609849057092,3,0.015790390690820114,0.0004625788149664668,3,0.017300165662065266,0.00024224102420406977,3,59.333333333333336,5.859465277082315,3,27.0,4.58257569495584,3,0.46588581945603197,0.17830034081878673,3,0.33149756485837917,0.06227529320982658,3,30.666666666666668,3.214550253664318,3,0.06211176831339407,0.0061904515037675715,3,0.05721849300520085,0.036386192828490156,3,0.09312784548262909,0.0009713108956753645,3,0.06529925744820797,0.001697766389505941,3,3,4,0.35,0.45,0.8,0.0,0.2,0.05,grid,aligned straight stringers (4x1) with disordered finer levels and strong hierarchy,holdout,holdout,S5,abrupt-brittle/intermediate +H12_dis0.2_D6_rt0.8,0.05774792468265664,0.004114004711751326,3,0.00029888224755013576,4.675777332366316e-05,3,1.8550043303185175e-06,6.015794667119649e-07,3,0.046375108257963,0.015039486667799177,3,0.0047497225435863995,0.00047237285845537193,3,0.00565431194193492,0.00022534672459782921,3,0.032729472011150194,0.004810418113592153,3,56.333333333333336,10.066445913694333,3,2.6666666666666665,2.0816659994661326,3,0.45035547869371245,0.12997656546886144,3,0.4602506208693047,0.05076318160832306,3,43.0,8.54400374531753,3,0.050910505471265355,0.008756296264861114,3,0.49546508045004223,0.07986579512849697,3,0.05774792468265664,0.004114004711751326,3,0.01494411237750679,0.002337888666183159,3,6,2,0.2,0.8,0.8,0.0,0.2,0.05,grid,"moderate disorder, deep hierarchy, weak thickness contrast",holdout,holdout,S5,intermediate +R_H2,0.015761050449001085,0.002216867402182293,2,0.0001262962823128673,5.659377197118449e-06,2,1.7596154686867223e-06,6.526245667631902e-07,2,0.021995193358584,0.008157807084539863,2,0.007098757167536101,0.0008436072724784298,2,0.009011209471344279,4.147236025639961e-05,2,0.05857715483588341,0.018381055684184792,2,45.0,18.384776310850235,2,2.5,0.7071067811865476,2,0.35651637274954306,0.0816842108756481,2,0.4825112653757155,0.28210210617597026,2,34.5,13.435028842544403,2,0.04708617564963555,0.018497629781106858,2,0.6302609335985077,0.09456804074489113,2,0.03152210089800217,0.004433734804364586,2,0.006314814115643365,0.0002829688598559228,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,aspect ratio control: H = 2W (512 leaf cells),reconnaissance,reconnaissance,S2,intermediate +R_b2D3,0.04918264609040145,0.005852916647723181,2,0.0003689103301825679,9.203651208820947e-05,2,2.0183956170214847e-06,2.821696987602628e-07,2,0.05045989042553711,0.007054242469006532,2,0.007442173680194605,0.0009856746985724158,2,0.007442173680194605,0.0009856746985724158,2,0.015567542350474682,0.005774904022496038,2,6.5,3.5355339059327378,2,0.0,0.0,2,0.6589254497174772,0.3500874299174699,2,0.5732323232323232,0.02499872458740312,2,4.5,3.5355339059327378,2,0.06007409278437316,0.033994945866592456,2,0.32015893055963096,0.16471403852586997,2,0.04918264609040145,0.005852916647723181,2,0.018445516509128394,0.004601825604410472,2,3,2,0.35,0.6,0.8,0.0,0.2,0.05,grid,"branching control: b=2, D=3 (32 leaf cells, coarse)",reconnaissance,reconnaissance,S2,abrupt-brittle/intermediate +R_b9D3,0.033800707021038726,0.001854075020236936,2,0.00013265867619358823,1.2182187167488977e-05,2,6.133749241229509e-07,9.177031166647328e-09,2,0.01533437310307377,0.00022942577916614678,2,0.002901545239943782,0.0004311145018396657,2,0.004239921269465683,0.00013448316258877238,2,0.0232208798338929,0.005411273825772746,2,278.0,45.254833995939045,2,13.5,9.192388155425117,2,0.18216208583717652,0.07708520896273952,2,0.5654068297701837,0.08852554077495643,2,177.0,39.59797974644666,2,0.025665422354950625,0.004229235982443744,2,0.5158424062051445,0.013774962238256042,2,0.033800707021038726,0.001854075020236936,2,0.006632933809679411,0.0006091093583744488,2,3,9,0.35,0.6,0.8,0.0,0.2,0.05,grid,"branching control: b=9, D=3 (2916 leaf cells, fine)",reconnaissance,reconnaissance,S2,progressive +R_con0.7,0.03351168731712467,0.008167656634186431,2,0.00016219007657128663,5.424711596974695e-05,2,1.1586892768259745e-06,1.9985056116997561e-07,2,0.028967231920649362,0.004996264029249396,2,0.004598677958382671,0.0007156145221022334,2,0.005087691585334352,2.4044818681908438e-05,2,0.034060976348894066,0.01657930224178634,2,38.5,2.1213203435596424,2,1.0,1.4142135623730951,2,0.3709425478176268,0.082589432226559,2,0.43023162182644936,0.02873374893804184,2,28.5,6.363961030678928,2,0.05248526477003759,0.003800202592537344,2,0.6346567695245353,0.040165184552589425,2,0.03351168731712467,0.008167656634186431,2,0.008109503828564332,0.0027123557984873475,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,connectivity sweep: 30% of finest walls removed,reconnaissance,reconnaissance,S2,intermediate +R_cv0,0.041425943128578,0.006295066656953668,2,0.00017641514917507949,5.000788633522541e-05,2,1.0537084510651284e-06,2.952694579255812e-07,2,0.02634271127662821,0.007381736448139534,2,0.003968771588396612,0.00021762229001741576,2,0.00516200869687454,0.0019051143919537573,2,0.0185985672053915,0.0035216940850513294,2,43.5,2.1213203435596424,2,4.5,6.363961030678928,2,0.41718269926707086,0.17129922025717845,2,0.3887856837378381,0.035041590193517054,2,27.5,6.363961030678928,2,0.04597720415688904,0.001967477802161701,2,0.5053082693934773,0.24926365639246778,2,0.041425943128578,0.006295066656953668,2,0.008820757458753974,0.002500394316761271,2,3,4,0.35,0.6,0.8,0.0,0.2,0.0,grid,strength disorder control: CV=0,reconnaissance,reconnaissance,S2,intermediate +R_cv0.2,0.041425943128578,0.0062950666569536635,2,0.00013032756636304496,3.429978273317496e-05,2,8.324468623597382e-07,2.441886993464195e-07,2,0.02081117155899346,0.006104717483660489,2,0.002845664329203985,0.000562267607359894,2,0.003331044470484142,0.00020217283077132077,2,0.020773915156448556,0.0026169182615231345,2,44.5,2.1213203435596424,2,1.5,0.7071067811865476,2,0.3190635943174579,0.07469524890421635,2,0.37283721078057463,0.09742494937458056,2,27.0,7.0710678118654755,2,0.04704771482847246,0.002523744618515846,2,0.7245717849032094,0.001502458587982908,2,0.041425943128578,0.0062950666569536635,2,0.006516378318152249,0.0017149891366587489,2,3,4,0.35,0.6,0.8,0.0,0.2,0.2,grid,strength disorder control: CV=0.2,reconnaissance,reconnaissance,S2,intermediate +R_depth0,0.048298858319096714,0.0020981075506334907,2,0.0002427332494779215,2.0559754543433496e-05,2,1.0236538544302406e-06,4.009344142240215e-08,2,0.025591346360756013,0.001002336035560036,2,0.004906209585708262,8.635012396349412e-05,2,0.005266157945088629,0.00024923291437959434,2,0.013031573075594865,0.001460146855739078,2,34.0,5.656854249492381,2,1.0,0.0,2,0.46056775570149067,0.08332736268409857,2,0.38199626865671643,0.07849412962798427,2,0.0,0.0,2,0.05093588640275387,0.008899687327756672,2,0.3456652594767743,0.11338436805654144,2,0.048298858319096714,0.0020981075506334907,2,0.012136662473896075,0.0010279877271716742,2,0,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,depth sweep (fixed r_t): D=0 flat 16x16,reconnaissance,reconnaissance,S2,intermediate +R_depth1,0.04014379760153808,0.0013140117188842778,2,0.00019632481827739978,1.9102361384626442e-05,2,1.0682707680234326e-06,1.6320180692128708e-07,2,0.02670676920058579,0.00408004517303214,2,0.00490095264438381,0.0006362694144328659,2,0.00490095264438381,0.0006362694144328659,2,0.01620385486449543,0.0016269704417972064,2,38.0,0.0,2,0.0,0.0,2,0.26516409514244954,0.05455576043777217,2,0.5182030820033021,0.12643863137452357,2,10.0,1.4142135623730951,2,0.05194807621866894,5.021577165251532e-05,2,0.5493660101091138,0.03344034350835437,2,0.04014379760153808,0.0013140117188842778,2,0.009816240913869989,0.000955118069231323,2,1,64,0.35,0.6,0.8,0.0,0.2,0.05,grid,"depth sweep (fixed r_t): D=1 (2x2 root, 64 sub-cells each)",reconnaissance,reconnaissance,S2,intermediate/progressive +R_depth2,0.03291747643713969,0.0049137205257325685,2,0.00015713219780865762,1.649449462577019e-05,2,8.684857572396183e-07,8.116571028494504e-08,2,0.02171214393099044,0.002029142757123625,2,0.004510591796717407,0.00018055017217532047,2,0.0050973621397145214,0.0006492684048895109,2,0.018588034680776477,0.0027335217191890725,2,38.0,5.656854249492381,2,0.5,0.7071067811865476,2,0.3821537295187547,0.0362372026909741,2,0.4694626266891892,0.04796411601692958,2,21.0,1.4142135623730951,2,0.041331130964010206,0.005901033803767458,2,0.5201452223324966,0.08069160759004808,2,0.03291747643713969,0.0049137205257325685,2,0.00785660989043288,0.0008247247312885091,2,2,8,0.35,0.6,0.8,0.0,0.2,0.05,grid,depth sweep (fixed r_t): D=2 (b=8),reconnaissance,reconnaissance,S2,intermediate +R_depth3,0.041425943128578,0.0062950666569536635,2,0.00016656337624810046,4.7817602917799196e-05,2,1.1067491409287198e-06,1.1253911775919893e-07,2,0.027668728523218004,0.002813477943979975,2,0.0037717185987591584,0.00025652228493605736,2,0.004456859987581788,0.0012254585291521574,2,0.03377051286472913,0.01896331787301565,2,50.5,4.949747468305833,2,2.0,2.8284271247461903,2,0.28142898140313677,0.03649551236875819,2,0.40169664396196963,0.04263135445180497,2,35.0,7.0710678118654755,2,0.05339926248742877,0.005551606039352645,2,0.631167085894653,0.19350207831044283,2,0.041425943128578,0.0062950666569536635,2,0.008328168812405024,0.0023908801458899604,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,depth sweep (fixed r_t): D=3 (b=4) reference,reconnaissance,reconnaissance,S2,intermediate +R_depth6,0.050949774328963034,0.010039728102196777,3,0.00027765779560959747,7.320624057968462e-05,3,1.9645599771354577e-06,1.7005878213340986e-07,3,0.04911399942838638,0.004251469553335298,3,0.0026279234567713077,0.0009101542797494865,3,0.006395896726273738,0.00040111455967165705,3,0.031363092580460626,0.014961286142728753,3,67.66666666666667,21.501937897160182,3,9.0,5.196152422706632,3,0.5181872250610792,0.17579834218252535,3,0.2649992903647456,0.07451109250140947,3,56.0,21.0,3,0.060892112131923415,0.019205472592488657,3,0.5107086027860973,0.11047601830583148,3,0.050949774328963034,0.010039728102196777,3,0.013882889780479872,0.003660312028984232,3,6,2,0.35,0.6,0.8,0.0,0.2,0.05,grid,depth sweep (fixed r_t): D=6 (b=2),reconnaissance,reconnaissance,S2,abrupt-brittle/intermediate +R_depthC1,0.03658800345326409,0.006538548348790746,3,0.0001699664808688695,4.8526470689943e-05,3,9.565130177579524e-07,2.1525571363133166e-07,3,0.02391282544394881,0.005381392840783298,3,0.003803661721272449,0.0004461486227698847,3,0.0052482188677611995,0.0004396563642488659,3,0.02428809168776865,0.005927708959390619,3,34.333333333333336,4.932882862316248,3,2.3333333333333335,1.1547005383792515,3,0.46046283891296086,0.1639227941812029,3,0.5368611134147095,0.10260337519419079,3,7.0,5.291502622129181,3,0.04702299189056822,0.006649523668830231,3,0.4952879998543705,0.0557003042880039,3,0.03658800345326409,0.006538548348790746,3,0.008498324043443474,0.0024263235344971494,3,1,64,0.35,0.21599999999999997,0.8,0.0,0.2,0.05,grid,depth sweep (fixed contrast t_D/t_0=0.216): D=1,reconnaissance,reconnaissance,S2,abrupt-brittle/intermediate +R_depthC2,0.03407997280650846,0.008242880126748502,2,0.00016656914313279705,4.7316290897652225e-05,2,1.0561539772142127e-06,1.0618302354406134e-08,2,0.026403849430355304,0.0002654575588601004,2,0.004704554822585262,0.00043497259817009846,2,0.005259112003544137,0.0003492896882533333,2,0.035361565006806386,0.022420379862677295,2,46.5,2.1213203435596424,2,1.0,1.4142135623730951,2,0.4236180388157336,0.06544504486220531,2,0.478406652360515,0.030537605088796754,2,26.5,4.949747468305833,2,0.05060653961600625,0.0026197977826317212,2,0.5695789312831976,0.06732350482534857,2,0.03407997280650846,0.008242880126748502,2,0.008328457156639853,0.0023658145448826103,2,2,8,0.35,0.46475800154489,0.8,0.0,0.2,0.05,grid,depth sweep (fixed contrast): D=2,reconnaissance,reconnaissance,S2,intermediate +R_depthC6,0.04242209692181655,0.005445248224882403,3,0.0001913577710955837,4.7560458974962066e-05,3,1.0989635542256347e-06,2.0673486157814425e-07,3,0.02747408885564089,0.005168371539453639,3,0.00359210031855269,0.0012292758531130394,3,0.005409383221871976,0.0002575560193334574,3,0.020437606096536397,0.008249468914680763,3,45.0,13.74772708486752,3,4.666666666666667,4.041451884327381,3,0.3633194123414607,0.1953627659443863,3,0.4348670061171604,0.17394393059676155,3,36.333333333333336,16.041612554021285,3,0.04048360393346596,0.012219926112491857,3,0.4635727654759095,0.12287936532172938,3,0.04242209692181655,0.005445248224882403,3,0.009567888554779184,0.002378022948748103,3,6,2,0.35,0.7745966692414834,0.8,0.0,0.2,0.05,grid,depth sweep (fixed contrast): D=6,reconnaissance,reconnaissance,S2,intermediate/progressive +R_dis0,0.10000000002582585,0.0,2,0.0014025420699712364,2.3011649460684346e-05,2,9.836945127682792e-06,3.227480645971218e-07,2,0.24592362819206917,0.008068701614928026,2,0.014025420696090187,0.00023011649454746455,2,0.014025420696090187,0.00023011649454746455,2,0.014025420696090187,0.00023011649454746455,2,33.0,1.4142135623730951,2,0.0,0.0,2,0.9942341203655545,0.0028739440048024954,2,0.736583138515488,0.06042539464888262,2,29.0,1.4142135623730951,2,0.043421052631578944,0.0018608073189119655,2,0.0,0.0,2,0.10000000002582585,0.0,2,0.07012710349856183,0.001150582473034215,2,3,4,0.0,0.6,0.8,0.0,0.2,0.05,grid,disorder sweep delta=0,reconnaissance,reconnaissance,S2,abrupt-brittle +R_dis0.15,0.07315152952074631,0.003997368260567277,3,0.0002970563136101431,7.103895419012712e-05,3,1.7799222243513823e-06,4.989741653192196e-07,3,0.04449805560878458,0.012474354132980524,3,0.0037833183327071634,0.0004861216825323863,3,0.004219294885980221,0.0007345370575469188,3,0.023229811377332016,0.0018123196487622938,3,51.0,7.0,3,1.3333333333333333,1.1547005383792517,3,0.3283993998850793,0.08975342785307586,3,0.4063018967889316,0.033446061983351906,3,30.0,7.810249675906654,3,0.056189019614124404,0.007480937246251464,3,0.6327308625528495,0.05721255022662879,3,0.07315152952074631,0.003997368260567277,3,0.014852815680507154,0.0035519477095063566,3,3,4,0.15,0.6,0.8,0.0,0.2,0.05,grid,disorder sweep delta=0.15,reconnaissance,reconnaissance,S2,intermediate/progressive +R_dis0.7,0.020750640918395177,0.007559795188848702,3,0.00011226896146062673,3.752326971246507e-05,3,1.2656576628031985e-06,9.092659958431522e-08,3,0.03164144157007996,0.002273164989607923,3,0.004245016930502999,0.0010642084751028922,3,0.006325303633164465,0.00029434408811931126,3,0.048427536080030274,0.020924392145101566,3,64.33333333333333,5.859465277082315,3,5.0,3.605551275463989,3,0.35264980195841167,0.138116064454857,3,0.40192155174595356,0.1387683461510014,3,43.333333333333336,5.773502691896258,3,0.06710312278158115,0.006034661767845529,3,0.6795339473480403,0.14598409954429079,3,0.020750640918395177,0.007559795188848702,3,0.005613448073031337,0.0018761634856232531,3,3,4,0.7,0.6,0.8,0.0,0.2,0.05,grid,disorder sweep delta=0.7,reconnaissance,reconnaissance,S2,intermediate/progressive +R_dis1,0.01919007584627001,0.00478088515169333,3,9.108842162239095e-05,2.4449894296769873e-05,3,1.2391892151060344e-06,2.473832180508279e-07,3,0.030979730377650883,0.00618458045127073,3,0.003244815498033775,0.00019375215250497935,3,0.005326785402585421,0.0011292054558843009,3,0.09389127737780195,0.04083513146467856,3,59.666666666666664,12.423096769056151,3,1.3333333333333333,0.5773502691896257,3,0.3660479206830523,0.15568354837081314,3,0.4807760525153384,0.1431227200127535,3,43.333333333333336,6.110100926607786,3,0.06276179121006707,0.012663839834179536,3,0.7857725709532418,0.09406007513737184,3,0.01919007584627001,0.00478088515169333,3,0.004554421081119547,0.0012224947148384937,3,3,4,1.0,0.6,0.8,0.0,0.2,0.05,grid,disorder sweep delta=1,reconnaissance,reconnaissance,S2,intermediate/progressive +R_frame,0.062059611069321584,0.004357578116657207,3,0.0004326739385816342,5.7570629449386e-05,3,3.862431724024974e-06,7.112263582893165e-07,3,0.09656079310062433,0.017780658957232843,3,0.003787275436788182,0.00041073776357817963,3,0.012709190664356171,0.002386910051224392,3,0.03544169336452319,0.022788255176904255,3,53.0,16.09347693943108,3,30.333333333333332,7.637626158259733,3,0.6869694603196916,0.22809917941213886,3,0.5014347543293808,0.10190977319179434,3,30.666666666666668,12.741009902410928,3,0.05273542118896966,0.01620171523487203,3,0.1464180103708908,0.11370407030549723,3,0.062059611069321584,0.004357578116657207,3,0.02163369692908171,0.002878531472469301,3,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,frame control: add straight side walls (level 0) as in the preliminary family,reconnaissance,reconnaissance,S2,abrupt-brittle/intermediate +R_notch,0.04022614667944534,0.0075647896303922095,2,0.00016481179794275078,4.638908082115989e-05,2,9.467542588630702e-07,2.0546823718028253e-07,2,0.024259163315986952,0.005058308410323754,2,0.0038612936348825034,0.00010788755363797815,2,0.004541717862984101,0.0010701527251865005,2,0.01842897214361338,0.0007790533287567789,2,43.0,4.242640687119285,2,2.0,2.8284271247461903,2,0.28744833528100183,0.03777250319926345,2,0.4065094189016603,0.02655601377301011,2,28.5,3.5355339059327378,2,0.0462411219453473,0.004107126783706623,2,0.5739004813381077,0.16176450885142207,2,0.04022614667944534,0.0075647896303922095,2,0.00824058989713754,0.002319454041057994,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,grid,edge notch of radius 0.12 W at mid-height,reconnaissance,reconnaissance,S2,intermediate +R_radial,0.02019632909724437,0.0039499117815542635,2,0.00010789467300848779,1.6475251354605573e-05,2,8.088974055017565e-07,8.419468668098882e-08,2,0.020222435137543904,0.0021048671670247897,2,0.005365128088832192,0.00023353408781923832,2,0.005365128088832192,0.00023353408781923832,2,0.04374374251986182,0.016846282603407165,2,65.5,4.949747468305833,2,0.0,0.0,2,0.38425293658732407,0.194276227993848,2,0.6833592098833965,0.009674155798731734,2,34.0,0.0,2,0.03629552603115152,0.002671888836458314,2,0.6434773380137974,0.001953351629553396,2,0.02019632909724437,0.0039499117815542635,2,0.005394733650424389,0.0008237625677302786,2,3,5,0.35,0.6,0.8,0.0,0.2,0.05,radial,"design language: radial (nested rings), b=5 D=3 (500 leaf cells)",reconnaissance,reconnaissance,S2,intermediate/progressive +R_red0.5,0.04561852837256789,0.00010178489449257788,2,0.00023982746149052507,8.580127514800556e-07,2,1.4533151093285507e-06,1.2408304367521343e-08,2,0.03633287773321376,0.0003102076091880604,2,0.003913191692406205,0.000457523033087097,2,0.006641730561499792,0.0010614871775131217,2,0.022721491579629285,0.005149041418128162,2,48.5,10.606601717798213,2,5.0,4.242640687119285,2,0.538209762682673,0.028976611414419946,2,0.5042007367468876,0.03804197956760266,2,18.5,6.363961030678928,2,0.041563198776038604,0.008794104872530118,2,0.3717134051967148,0.14737380549905205,2,0.04561852837256789,0.00010178489449257788,2,0.011991373074526253,4.290063757400226e-05,2,3,4,0.35,0.6,0.8,0.5,0.2,0.05,grid,redundancy sweep (braces) r=0.5,reconnaissance,reconnaissance,S2,intermediate +R_red1,0.04572729370575821,0.0027688743362074943,3,0.0002945218784169866,3.297079915675898e-05,3,2.6398166946215438e-06,5.890834037300189e-07,3,0.06599541736553854,0.014727085093250365,3,0.005205775396385782,0.0010229423661226255,3,0.007211651080057052,0.001046273788798347,3,0.04003526788075049,0.0258195267634255,3,67.33333333333333,2.516611478423585,3,5.333333333333333,4.163331998932265,3,0.3103432379725331,0.07210209210252264,3,0.6779294637684105,0.09469833307420254,3,19.0,4.358898943540674,3,0.04945640119187383,0.0015860279443013472,3,0.5351375081333746,0.18669191766523122,3,0.04572729370575821,0.0027688743362074943,3,0.014726093920849332,0.0016485399578379512,3,3,4,0.35,0.6,0.8,1.0,0.2,0.05,grid,redundancy sweep (braces) r=1,reconnaissance,reconnaissance,S2,intermediate/progressive +R_rho0.1,0.009296969169306578,0.0024510983107392044,2,4.1294698291331904e-05,1.2642700771907149e-05,2,4.88271793584657e-07,6.627464544679565e-08,2,0.024413589679232857,0.003313732272339781,2,0.004415949127451502,0.00019563099459399646,2,0.004415949127451502,0.00019563099459399646,2,0.05880975672098877,0.008325428181069378,2,50.5,0.7071067811865476,2,0.0,0.0,2,0.34246446108646156,0.09483507862811459,2,0.38170822263351145,0.07953737561374183,2,33.5,3.5355339059327378,2,0.053385853167951726,0.0010667048324973095,2,0.8147329803365493,0.04029623948710289,2,0.009296969169306578,0.0024510983107392044,2,0.002064734914566595,0.0006321350385953575,2,3,4,0.35,0.6,0.8,0.0,0.1,0.05,grid,density control: rho=0.1,reconnaissance,reconnaissance,S2,intermediate +R_rho0.3,0.0854182927555858,0.00878173169513073,2,0.0003568594391981626,8.457588603820365e-05,2,1.8078955132986037e-06,4.845590328527525e-07,2,0.03013159188831009,0.008075983880879234,2,0.003657993295845964,0.0001305231608697689,2,0.004903679048455116,0.0016311425249250298,2,0.025207923472107437,0.017935731967337568,2,46.5,2.1213203435596424,2,4.5,6.363961030678928,2,0.4172472166758893,0.21978544088420915,2,0.42702712896240813,0.09825442124102499,2,33.0,4.242640687119285,2,0.04914850821320818,0.0019485141606950759,2,0.4596443569825782,0.22656262151701365,2,0.0854182927555858,0.00878173169513073,2,0.01784297195990813,0.004228794301910182,2,3,4,0.35,0.6,0.8,0.0,0.3,0.05,grid,density control: rho=0.3,reconnaissance,reconnaissance,S2,intermediate +R_rt0.3,0.042842873780554146,0.01190876991794155,3,0.00021367763695385382,9.720471551508574e-05,3,1.2964960969657199e-06,4.750158726120269e-07,3,0.03241240242414297,0.011875396815300669,3,0.0034600066990916525,0.00028967228404236964,3,0.005172948449367458,0.0010444796411927752,3,0.045823195332287174,0.026352732722892343,3,44.333333333333336,19.2180470738661,3,2.6666666666666665,2.886751345948129,3,0.7186274186128147,0.06972702268019854,3,0.349552480173503,0.06439258053227258,3,22.0,12.12435565298214,3,0.04674911851997096,0.020253046585792772,3,0.5586616748629237,0.14415641922645842,3,0.042842873780554146,0.01190876991794155,3,0.010683881847692691,0.004860235775754286,3,3,4,0.35,0.3,0.8,0.0,0.2,0.05,grid,thickness-ratio sweep r_t=0.3,reconnaissance,reconnaissance,S2,abrupt-brittle +R_rt0.45,0.03954362573955456,0.008118878589024875,3,0.0001865837691662531,8.115291915827666e-05,3,1.1715945273583732e-06,5.024882869686342e-07,3,0.029289863183959347,0.012562207174215814,3,0.0035829767819297305,0.00026980830390669247,3,0.005794448161892494,0.001784646473788129,3,0.026615522370672984,0.00790719939428562,3,50.0,14.52583904633395,3,8.666666666666666,7.023769168568493,3,0.427207483483749,0.09196950361483736,3,0.3790185115965887,0.11156997443068371,3,31.333333333333332,14.364307617610164,3,0.05272462894206232,0.0153548363529047,3,0.4657831424533085,0.20325123892082714,3,0.03954362573955456,0.008118878589024875,3,0.009329188458312656,0.004057645957913832,3,3,4,0.35,0.45,0.8,0.0,0.2,0.05,grid,thickness-ratio sweep r_t=0.45,reconnaissance,reconnaissance,S2,intermediate +R_rt0.8,0.03957371657258693,0.002939962103636804,2,0.00015668054154968622,3.6150879325357196e-05,2,1.0834566211044586e-06,1.4022845737920587e-07,2,0.02708641552761147,0.0035057114344801154,2,0.0039109656291190726,0.0006566857542141103,2,0.004019210277708813,0.0005036047041241892,2,0.02736684877748568,0.0009672102120571431,2,50.0,4.242640687119285,2,0.5,0.7071067811865476,2,0.33071618007626635,0.20901832969104467,2,0.43559797857208105,0.06691210960705414,2,34.0,11.313708498984761,2,0.05286847692479607,0.004800961897965656,2,0.7043176378016127,0.05860486563075044,2,0.03957371657258693,0.002939962103636804,2,0.007834027077484311,0.0018075439662678604,2,3,4,0.35,0.8,0.8,0.0,0.2,0.05,grid,thickness-ratio sweep r_t=0.8,reconnaissance,reconnaissance,S2,intermediate/progressive +R_rt1,0.03434908777469074,0.00090753695218444,2,0.00014798618048949923,1.716204107553348e-05,2,7.429724402272904e-07,4.500230305862952e-08,2,0.01857431100568223,0.0011250575764657242,2,0.003943328112112138,0.00012299694186088548,2,0.004507544659548685,0.0006749257516392034,2,0.017925569997943612,0.0025866695036455894,2,35.0,4.242640687119285,2,0.5,0.7071067811865476,2,0.18505149621928166,0.039821035846014395,2,0.5597431369936035,0.05282805692999843,2,15.5,0.7071067811865476,2,0.036985138004246285,0.004263658723078122,2,0.5362141486456936,0.1114864847971322,2,0.03434908777469074,0.00090753695218444,2,0.007399309024474962,0.0008581020537766742,2,3,4,0.35,1.0,0.8,0.0,0.2,0.05,grid,thickness-ratio sweep r_t=1,reconnaissance,reconnaissance,S2,progressive +R_sint0.3,0.041425943128578,0.006295066656953668,2,9.173392904506703e-05,2.7472075570866463e-05,2,5.862704290856844e-07,2.5628729888669523e-07,2,0.014656760727142112,0.006407182472167385,2,0.0014385552091480292,0.00013036429541811093,2,0.0025710657737749777,0.0005626004135131006,2,0.03520877796048497,0.019897008318205782,2,120.5,41.71930009000631,2,8.5,9.192388155425117,2,0.47882817089455443,0.24195246709146814,2,0.30052203214932083,0.07542357968223772,2,118.5,40.30508652763321,2,0.12724885462062802,0.04333982226850164,2,0.7759358344146201,0.030524834516099154,2,0.041425943128578,0.006295066656953668,2,0.0045866964522533514,0.0013736037785433228,2,3,4,0.35,0.6,0.3,0.0,0.2,0.05,grid,inter-level strength sweep s_int=0.3,reconnaissance,reconnaissance,S2,abrupt-brittle/intermediate +R_sint0.5,0.041425943128578,0.006295066656953668,2,0.00015288988174177727,4.578679261810984e-05,2,7.913431390236156e-07,2.9458191982135007e-07,2,0.019783578475590397,0.007364547995533752,2,0.0023975920152467154,0.00021727382569685093,2,0.0042851096229582965,0.0009376673558551676,2,0.03805209969670804,0.02995274847792841,2,70.5,14.849242404917497,2,8.5,9.192388155425117,2,0.29195169461265297,0.052835461817046875,2,0.4183279072050259,0.07625598987118686,2,64.0,12.727922061357855,2,0.07447871270533021,0.015251508649528147,2,0.5426856867456404,0.09415306455394035,2,0.041425943128578,0.006295066656953668,2,0.007644494087088864,0.002289339630905492,2,3,4,0.35,0.6,0.5,0.0,0.2,0.05,grid,inter-level strength sweep s_int=0.5,reconnaissance,reconnaissance,S2,intermediate +R_sint1,0.041425943128578,0.006295066656953668,2,0.00017299166630575238,3.8726627605909315e-05,2,1.2889772591773137e-06,2.6288075908279904e-07,2,0.03222443147943285,0.006572018977069973,2,0.003945575244945531,1.0651857990589442e-05,2,0.0046307166326722835,0.0009795881006568875,2,0.04563189499839909,0.02555978723262902,2,47.0,1.4142135623730951,2,2.0,2.8284271247461903,2,0.28864407887122817,0.026291823976462313,2,0.3709533863222388,0.054988412338919095,2,23.5,2.1213203435596424,2,0.04967929377584088,0.0011978700193080829,2,0.6653362407181228,0.10571759117981663,2,0.041425943128578,0.006295066656953668,2,0.00864958331528762,0.0019363313802954654,2,3,4,0.35,0.6,1.0,0.0,0.2,0.05,grid,inter-level strength sweep s_int=1,reconnaissance,reconnaissance,S2,intermediate +R_sint1.5,0.041425943128578,0.006295066656953668,2,0.00017299166630575238,3.8726627605909315e-05,2,1.524398129420328e-06,4.5606661849728086e-07,2,0.03810995323550821,0.011401665462432023,2,0.003945575244945531,1.0651857990589442e-05,2,0.0046307166326722835,0.0009795881006568875,2,0.04258057994069025,0.01901423822739356,2,45.5,9.192388155425117,2,2.0,2.8284271247461903,2,0.2901715133182979,0.024131705465780483,2,0.3782472366477679,0.08789353461059979,2,1.5,0.7071067811865476,2,0.04806905799530674,0.009429670719276188,2,0.7172558975180734,0.06251259788711938,2,0.041425943128578,0.006295066656953668,2,0.00864958331528762,0.0019363313802954654,2,3,4,0.35,0.6,1.5,0.0,0.2,0.05,grid,inter-level strength sweep s_int=1.5,reconnaissance,reconnaissance,S2,intermediate +R_stag,0.01839129567642596,0.009134989589217294,2,9.855358868560196e-05,4.9934625892314884e-05,2,8.396219759177153e-07,7.19078698098931e-08,2,0.0209905493979429,0.001797696745247312,2,0.004928288122998025,0.00015151524070603818,2,0.007410540674876809,0.001785330136164647,2,0.027847635638732063,0.009970107580301752,2,34.5,0.7071067811865476,2,6.0,2.8284271247461903,2,0.3576359195408134,0.09604263434661969,2,0.5557272711054022,0.0024252707964588656,2,21.0,4.242640687119285,2,0.03627708978328173,0.0006895933005379694,2,0.5166603822063431,0.03937671918201162,2,0.01839129567642596,0.009134989589217294,2,0.004927679434280098,0.002496731294615744,2,3,4,0.35,0.6,0.8,0.0,0.2,0.05,staggered,design language: staggered (hexagonal-like),reconnaissance,reconnaissance,S2,intermediate diff --git a/data/Run 1/RESULT Run 1/analysis/processed/experiment_log_flat.csv b/data/Run 1/RESULT Run 1/analysis/processed/experiment_log_flat.csv new file mode 100644 index 0000000000000000000000000000000000000000..464b72e3cf2b828bde94b2daf1a1d29fcf09fdb4 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/processed/experiment_log_flat.csv @@ -0,0 +1,346 @@ +runId,batch,stage,designId,seed,status,reason,hypothesis,dir,hash,p_n0x,p_n0y,p_depth,p_branching,p_layout,p_disorder,p_disorderMinLevel,p_seed,p_thicknessRatio,p_relDensity,p_redundancy,p_connectivity,p_interfaceMode,p_interfaceStrengthRatio,p_interfaceStiffnessRatio,p_strengthCV,p_strengthLevelRatio,p_failStrain,p_E,p_includeFrame,p_frameMode,p_defectType,p_defectSize,p_defectX,p_defectY,p_missingFraction,p_H,p_gripType,p_dispIncrement,p_maxDisp,p_exactEvents,p_bendingFactor,K0,EeffRel,Fpeak,sigmaPeakRel,strengthRel,dFirst,dPeak,dFinal,finalFailureReached,Wf,WfPerArea,WfRel,Wtotal,nFailed,nDamaged,fractionFailed,nEvents,nCascades,maxCascade,prePeakFailures,prePeakFraction,abruptness,postPeakWorkFraction,localizationIndex,participationRatio,damageBandStd,damageBandCentre,interfaceFailures,interfaceFailureFraction,interfaceFailureShare,meanFailLevel,firstFailLevel,firstFailInterface,fractureMode,damagePattern,fractureLabel,maxResidual,maxResidualAbs,residualExceeded,iterationCapHits,nonPositivePivots,energyBalanceError,steps,rebuilds,solves,elapsedMs,converged,simStatus,s_nodes,s_activeElements,s_leafCells,s_relDensityDesign,s_relDensityActual,s_t0,s_tMin,s_meanCoordination,s_interfaces,s_braces,s_minSlendernessLevel,levelMaterial,totalMs +S1_B0_flat16_ord_s3,S1,baseline,B0_flat16_ord,3,ok,"Non-hierarchical ordered baseline: uniform 16x16 grid, single thickness, no interfaces.",baseline,study/runs/S1_B0_flat16_ord_s3,fa1c4c4a,16,16,0,4,grid,0.0,0,3,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000000878408,0.10000000000878408,0.0017624116213210324,0.0017624116213210324,0.08812058106605161,0.01762411621166218,0.01762411621166218,0.01762411621166218,True,1.553047361347291e-05,1.553047361347291e-05,0.3882618403368203,1.553047361347291e-05,23,0,0.04791666666666667,23,1,23,0,0.0,0.9999999998506568,0.0,0.6591494845360825,0.34085051546391754,0.1261174063681771,0.44157608695652173,0,0.0,0.0,0.0,0,False,abrupt-brittle,localized,abrupt-brittle/localized,5.835085995802823e-12,1.3862606486101437e-17,0,0,0,4.3632047203994453e-16,20,24,42,59.844999999999985,True,completed,285,480,256,0.20000000000000123,0.20000000000000123,0.006666666666666667,0.006666666666666667,3.3684210526315788,0,0,9.375,[1],115 +S1_B0_flat16_ord_s2,S1,baseline,B0_flat16_ord,2,ok,"Non-hierarchical ordered baseline: uniform 16x16 grid, single thickness, no interfaces.",baseline,study/runs/S1_B0_flat16_ord_s2,e74c1c74,16,16,0,4,grid,0.0,0,2,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000000878408,0.10000000000878408,0.001699064237309607,0.001699064237309607,0.08495321186548034,0.01699064237160356,0.01699064237160356,0.01699064237160356,True,1.4434096411254432e-05,1.4434096411254432e-05,0.36085241028135856,1.4434096411254432e-05,25,0,0.052083333333333336,25,1,25,0,0.0,0.999999999878399,0.0,0.7543238993710693,0.2456761006289308,0.06724488828156389,0.55125,0,0.0,0.0,0.0,0,False,abrupt-brittle,localized,abrupt-brittle/localized,4.942853319670599e-12,1.1339036609987766e-17,0,0,0,1.1736556596557841e-15,19,26,43,62.766084000000006,True,completed,285,480,256,0.20000000000000123,0.20000000000000123,0.006666666666666667,0.006666666666666667,3.3684210526315788,0,0,9.375,[1],109 +S1_B0_flat16_ord_s1,S1,baseline,B0_flat16_ord,1,ok,"Non-hierarchical ordered baseline: uniform 16x16 grid, single thickness, no interfaces.",baseline,study/runs/S1_B0_flat16_ord_s1,0be8f29c,16,16,0,4,grid,0.0,0,1,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000000878408,0.10000000000878408,0.0017328379703385511,0.0017328379703385511,0.08664189851692755,0.01732837970186335,0.01732837970186335,0.01732837970186335,True,1.5013637155916313e-05,1.5013637155916313e-05,0.3753409288979055,1.5013637155916313e-05,27,0,0.05625,27,1,27,0,0.0,0.9999999998613223,0.0,0.6521946564885497,0.34780534351145037,0.09894310311649292,0.5243055555555556,0,0.0,0.0,0.0,0,False,abrupt-brittle,localized,abrupt-brittle/localized,5.257286110923982e-12,1.3259956178767854e-17,0,0,0,3.3850542881430285e-16,20,28,46,52.49683399999999,True,completed,285,480,256,0.20000000000000123,0.20000000000000123,0.006666666666666667,0.006666666666666667,3.3684210526315788,0,0,9.375,[1],99 +S1_B0_flat16_dis1_s3,S1,baseline,B0_flat16_dis1,3,ok,Non-hierarchical fully organic (Voronoi) baseline.,baseline,study/runs/S1_B0_flat16_dis1_s3,28aca550,16,16,0,4,grid,1.0,0,3,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.012253838290141872,0.012253838290141872,0.00010640607851602725,0.00010640607851602725,0.005320303925801363,0.008290509353322683,0.009027952525440721,0.02205201784107865,True,6.099480850436259e-07,6.099480850436259e-07,0.01524870212609066,6.099480850436259e-07,18,0,0.02601156069364162,18,6,8,1,0.05555555555555555,0.49310036076075736,0.1861891669853027,0.7530487804878049,0.24695121951219512,0.07922646640527575,0.11677979691670973,0,0.0,0.0,0.0,0,False,intermediate,localized,intermediate/localized,1.444285427154433e-10,1.6187731564772417e-16,0,0,0,2.5690890599457768e-14,35,19,47,98.093834,True,completed,491,692,256,0.19999999999999984,0.19999999999999984,0.0066887211323303905,0.0066887211323303905,2.8187372708757636,0,0,6.4600774077898375,[1],281 +S1_B0_flat16_dis035_s2,S1,baseline,B0_flat16_dis035,2,ok,Non-hierarchical baseline with the reference geometric disorder (0.35).,baseline,study/runs/S1_B0_flat16_dis035_s2,84164d4d,16,16,0,4,grid,0.35,0,2,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.046815272242385075,0.046815272242385075,0.00022819530762072874,0.00022819530762072874,0.011409765381036437,0.0048451508274973765,0.005089923661235932,0.014064052818816182,True,1.0520041987411268e-06,1.0520041987411268e-06,0.026300104968528155,1.0520041987411268e-06,38,0,0.0572289156626506,38,25,7,1,0.02631578947368421,0.4016464124891737,0.4258401150101061,0.32649253731343286,0.6735074626865671,0.28190520267238345,0.5419095637033838,0,0.0,0.0,0.0,0,False,intermediate,distributed,intermediate/distributed,1.1687092644467646e-10,9.685220768809414e-17,0,0,0,7.24645066475121e-15,65,39,78,212.33249999999998,True,completed,469,664,256,0.2000000000000001,0.2000000000000001,0.006790726748004542,0.006790726748004542,2.831556503198294,0,0,6.531747771990075,[1],273 +S1_B0_flat16_dis035_s3,S1,baseline,B0_flat16_dis035,3,ok,Non-hierarchical baseline with the reference geometric disorder (0.35).,baseline,study/runs/S1_B0_flat16_dis035_s3,7f51889a,16,16,0,4,grid,0.35,0,3,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0464156807830821,0.0464156807830821,0.0002396635384576772,0.0002396635384576772,0.01198317692288386,0.005006019086741866,0.005697045858318805,0.017786681133817542,True,1.2400071715183408e-06,1.2400071715183408e-06,0.031000179287958486,1.2400071715183408e-06,43,0,0.06437125748502993,43,28,6,2,0.046511627906976744,0.266972965566515,0.4022272805367225,0.41928391959798994,0.5807160804020101,0.19667929021159838,0.45929703521835397,0,0.0,0.0,0.0,0,False,intermediate,distributed,intermediate/distributed,1.8689967275938702e-10,1.5430080260650408e-16,0,0,0,5.0036132702688804e-14,74,44,89,313.51433399999996,True,completed,473,668,256,0.2000000000000002,0.2000000000000002,0.006801544392552052,0.006801544392552052,2.824524312896406,0,0,6.471999264417051,[1],391 +S1_B1_D3_rt1_noif_s3,S1,baseline,B1_D3_rt1_noif,3,ok,"Nested topology (2x2 root, b=4, D=3) with uniform thickness and no interfaces: isolates the purely topological effect of nesting.",baseline,study/runs/S1_B1_D3_rt1_noif_s3,a7455c8e,2,2,3,4,grid,0.35,0,3,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03168978813942055,0.03168978813942055,0.00014910933888889088,0.00014910933888889088,0.007455466944444543,0.00462988822867202,0.005510708239938893,0.02646616066721049,True,8.589463147071639e-07,8.589463147071639e-07,0.021473657867679092,8.589463147071639e-07,34,0,0.05067064083457526,34,24,6,2,0.058823529411764705,0.34555297047533984,0.4638884198869881,0.7242366412213741,0.27576335877862596,0.10340570155645169,0.464891469835353,0,0.0,0.0,1.6470588235294117,0,False,intermediate,localized,intermediate/localized,8.169872898928324e-11,9.300418448565854e-17,0,0,0,1.0859759419094909e-13,75,35,85,80.659291,True,completed,474,671,256,0.20000000000000004,0.20000000000000004,0.006658649756890711,0.006658649756890711,2.831223628691983,0,0,7.900034468266361,"[0.06535550834255384, 0.13377454033367886, 0.2684615284458149, 0.5324084228779513]",122 +S1_B0_flat16_dis1_s1,S1,baseline,B0_flat16_dis1,1,ok,Non-hierarchical fully organic (Voronoi) baseline.,baseline,study/runs/S1_B0_flat16_dis1_s1,4ba964f1,16,16,0,4,grid,1.0,0,1,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.014651638891082258,0.014651638891082258,0.00011773110692957526,0.00011773110692957526,0.005886555346478763,0.007592007659511916,0.008439547521162433,0.02120732206093913,True,9.435719612444716e-07,9.435719612444716e-07,0.023589299031111777,9.435719612444716e-07,31,0,0.04492753623188406,31,18,4,1,0.03225806451612903,0.2751174582847361,0.4520594339316649,0.6022350993377483,0.3977649006622517,0.13211945630025368,0.5905448333439803,0,0.0,0.0,0.0,0,False,intermediate,localized,intermediate/localized,1.8300698092080974e-10,8.13249736987238e-17,0,0,0,2.73794749657283e-13,58,32,71,176.837541,True,completed,490,690,256,0.2000000000000001,0.2000000000000001,0.006660477768163022,0.006660477768163022,2.816326530612245,0,0,6.53386472720448,[1],319 +S1_B1_D3_rt1_noif_s2,S1,baseline,B1_D3_rt1_noif,2,ok,"Nested topology (2x2 root, b=4, D=3) with uniform thickness and no interfaces: isolates the purely topological effect of nesting.",baseline,study/runs/S1_B1_D3_rt1_noif_s2,ddc7a754,2,2,3,4,grid,0.35,0,2,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03499402847535946,0.03499402847535946,0.00016748866409938175,0.00016748866409938175,0.008374433204969087,0.003857284132446892,0.0058048958767325754,0.02008293295975115,True,9.047347125976762e-07,9.047347125976762e-07,0.022618367814941885,9.047347125976762e-07,34,0,0.050746268656716415,34,22,7,2,0.058823529411764705,0.35863998274321496,0.3959081534556616,0.5540123456790124,0.44598765432098764,0.17242079029268256,0.5561995287197097,0,0.0,0.0,1.4705882352941178,0,False,intermediate,distributed,intermediate/distributed,9.948399119365304e-11,9.250123569188959e-17,0,0,0,4.0374593062160266e-14,65,35,77,77.41875000000002,True,completed,473,670,256,0.20000000000000018,0.20000000000000018,0.006669889011819013,0.006669889011819013,2.8329809725158563,0,0,7.817005837299642,"[0.06662788651561867, 0.13285028835862372, 0.26671265446191433, 0.5338091706638431]",113 +S1_B0_flat16_dis035_s1,S1,baseline,B0_flat16_dis035,1,ok,Non-hierarchical baseline with the reference geometric disorder (0.35).,baseline,study/runs/S1_B0_flat16_dis035_s1,ad0bd5a5,16,16,0,4,grid,0.35,0,1,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04978244439580835,0.04978244439580835,0.00025727119133511425,0.00025727119133511425,0.012863559566755712,0.004967268343919148,0.005442392228941327,0.011999093332373546,True,9.953035101193544e-07,9.953035101193544e-07,0.02488258775298387,9.953035101193544e-07,30,0,0.044642857142857144,30,18,8,1,0.03333333333333333,0.5194890989138077,0.2654904039434425,0.4375,0.5625,0.2767640455822123,0.5916365831710191,0,0.0,0.0,0.0,0,False,intermediate,distributed,intermediate/distributed,1.1839866132799505e-10,9.04955179228509e-17,0,0,0,2.89350132033521e-14,48,31,60,231.81908399999998,True,completed,477,672,256,0.1999999999999999,0.1999999999999999,0.006797564307387961,0.006797564307387961,2.8176100628930816,0,0,6.441011475224623,[1],310 +S1_B1_D3_rt1_noif_s1,S1,baseline,B1_D3_rt1_noif,1,ok,"Nested topology (2x2 root, b=4, D=3) with uniform thickness and no interfaces: isolates the purely topological effect of nesting.",baseline,study/runs/S1_B1_D3_rt1_noif_s1,301f5788,2,2,3,4,grid,0.35,0,1,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03371768552762246,0.03371768552762246,0.00016104234838775313,0.00016104234838775313,0.008052117419387656,0.004776198184060538,0.004776198184060538,0.019441878068622177,True,8.373104903609949e-07,8.373104903609949e-07,0.02093276225902488,8.373104903609949e-07,33,0,0.04969879518072289,33,24,3,0,0.0,0.15066523664468204,0.5406899944638099,0.49583333333333335,0.5041666666666667,0.23392904044396265,0.45490518304210553,0,0.0,0.0,1.9393939393939394,1,False,progressive,distributed,progressive/distributed,2.7811865140690947e-10,1.8231654652354886e-16,0,0,0,3.616511224084367e-14,68,34,77,156.77425,True,completed,468,664,256,0.19999999999999996,0.19999999999999996,0.006690948248616675,0.006690948248616675,2.8376068376068377,0,0,7.84399192086285,"[0.06521551261054966, 0.13414357897688597, 0.26862439563983137, 0.5320165127727327]",233 +S1_B0_flat16_dis1_s2,S1,baseline,B0_flat16_dis1,2,ok,Non-hierarchical fully organic (Voronoi) baseline.,baseline,study/runs/S1_B0_flat16_dis1_s2,3b6c241e,16,16,0,4,grid,1.0,0,2,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.01299312705382489,0.01299312705382489,0.00011217168613191029,0.00011217168613191029,0.005608584306595514,0.008633155488069295,0.008633155488069295,0.018447446564127445,True,1.0016111948098785e-06,1.0016111948098785e-06,0.02504027987024695,1.0016111948098785e-06,33,0,0.04782608695652174,33,16,14,0,0.0,0.5628163070636122,0.5165810781899776,0.3391990291262136,0.6608009708737864,0.2397783479503266,0.5282953355964005,0,0.0,0.0,0.0,0,False,intermediate,distributed,intermediate/distributed,4.579305076780488e-10,1.640090814731163e-16,0,0,0,3.1924057882479326e-14,51,34,68,199.916375,True,completed,491,690,256,0.2000000000000001,0.2000000000000001,0.0067165069468119966,0.0067165069468119966,2.8105906313645623,0,0,6.425308263062544,[1],318 +S1_B1_D3_rt1_if08_s1,S1,baseline,B1_D3_rt1_if08,1,ok,Nested topology with interfaces (s_int=0.8) but uniform thickness: isolates the interface effect.,baseline,study/runs/S1_B1_D3_rt1_if08_s1,5caf6d5c,2,2,3,4,grid,0.35,0,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03370736224162375,0.03370736224162375,0.00013585078486598744,0.00013585078486598744,0.006792539243299371,0.004030300083767177,0.004030300083767177,0.019754621544659852,True,7.111510065655213e-07,7.111510065655213e-07,0.017778775164138012,7.111510065655213e-07,32,0,0.03397027600849257,32,19,4,0,0.0,0.21320922069987103,0.6150469980563967,0.5223880597014925,0.47761194029850745,0.2358599028392497,0.46569162698423,15,0.46875,0.053763440860215055,2.03125,3,True,progressive,distributed,progressive/distributed,1.8472083143405985e-10,2.0924184286678708e-16,0,0,0,1.3950445549713133e-13,58,33,71,174.69641599999997,True,completed,746,942,256,0.2000000000000002,0.2000000000000002,0.0066908080302243746,0.0066908080302243746,2.525469168900804,279,0,7.844303756847165,"[0.06521730193512827, 0.1341414312524813, 0.26862590284005705, 0.5320153639723333]",255 +S1_B2_ref_ord_s1,S1,baseline,B2_ref_ord,1,ok,Ordered version of the reference hierarchical design.,reference,study/runs/S1_B2_ref_ord_s1,6767c994,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0013862703765912987,0.0013862703765912987,0.06931351882956494,0.013862703762332798,0.013862703762332798,0.013862703762332798,True,9.608727782591333e-06,9.608727782591333e-06,0.24021819456478272,9.609441934596302e-06,34,0,0.04473684210526316,34,1,34,0,0.0,0.9962663056601007,0.0,0.6938559322033898,0.3061440677966102,0.09100556253036025,0.4597886029411765,30,0.8823529411764706,0.10714285714285714,2.323529411764706,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.5550107648744588e-12,2.378806536501951e-17,0,0,0,5.817629670825665e-15,17,35,50,123.09999999999997,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",166 +S1_B1_D3_rt1_if08_s3,S1,baseline,B1_D3_rt1_if08,3,ok,Nested topology with interfaces (s_int=0.8) but uniform thickness: isolates the interface effect.,baseline,study/runs/S1_B1_D3_rt1_if08_s3,d9349054,2,2,3,4,grid,0.35,0,3,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03166203898862586,0.03166203898862586,0.00014913695402214673,0.00014913695402214673,0.007456847701107336,0.0046318423356829395,0.005515900542342208,0.016427106089977248,True,6.560345766670141e-07,6.560345766670141e-07,0.01640086441667534,6.560345766670141e-07,28,0,0.029350104821802937,28,16,6,2,0.07142857142857142,0.3379310846999795,0.297417968585545,0.7621359223300971,0.23786407766990292,0.07926863087353045,0.535228463263505,11,0.39285714285714285,0.03859649122807018,1.8571428571428572,0,False,intermediate,localized,intermediate/localized,2.0894985764243665e-10,1.2420218711636277e-16,0,0,0,9.667416045032162e-14,49,29,61,93.73629199999999,True,completed,757,954,256,0.20000000000000015,0.20000000000000015,0.006658544259701006,0.006658544259701006,2.5204755614266845,285,0,7.900260967027888,"[0.06535447287399583, 0.13377242085922447, 0.26846628983288157, 0.5324068164338973]",151 +S1_B2_ref_ord_s2,S1,baseline,B2_ref_ord,2,ok,Ordered version of the reference hierarchical design.,reference,study/runs/S1_B2_ref_ord_s2,d25ea1b6,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.001418813763351174,0.001418813763351174,0.0709406881675587,0.014188137629847577,0.014188137629847577,0.014188137629847577,True,1.006516247277425e-05,1.006516247277425e-05,0.2516290618193556,1.0074401912764517e-05,32,0,0.042105263157894736,32,1,32,0,0.0,0.9922019350710082,0.0,0.7793103448275862,0.2206896551724138,0.09810735653232977,0.4009765625,28,0.875,0.1,2.40625,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.1595892460631707e-12,2.6834668691891227e-17,0,0,0,5.8854418179084356e-15,18,33,49,112.55570799999998,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",159 +S1_B1_D3_rt1_if08_s2,S1,baseline,B1_D3_rt1_if08,2,ok,Nested topology with interfaces (s_int=0.8) but uniform thickness: isolates the interface effect.,baseline,study/runs/S1_B1_D3_rt1_if08_s2,de34ea9c,2,2,3,4,grid,0.35,0,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03499081330775773,0.03499081330775773,0.00016012157611301102,0.00016012157611301102,0.008006078805650551,0.003856356140457098,0.004984789235330194,0.016096518451227376,True,7.747938738890594e-07,7.747938738890594e-07,0.019369846847226445,7.747938738890594e-07,38,0,0.04,38,23,4,1,0.02631578947368421,0.1568937717386923,0.4573812992349905,0.5970982142857143,0.4029017857142857,0.17466038845136816,0.4963593342152775,16,0.42105263157894735,0.05673758865248227,1.894736842105263,0,False,progressive,distributed,progressive/distributed,1.53427174916483e-10,8.64148294652774e-17,0,0,0,3.635011381135183e-14,63,39,78,154.98987500000004,True,completed,753,950,256,0.20000000000000043,0.20000000000000043,0.006669558406737532,0.006669558406737532,2.5232403718459495,282,0,7.81809198203799,"[0.06662458398422541, 0.1328437033944165, 0.2667012955707675, 0.53383041705059]",215 +S1_B2_ref_ord_s3,S1,baseline,B2_ref_ord,3,ok,Ordered version of the reference hierarchical design.,reference,study/runs/S1_B2_ref_ord_s3,8b75cc06,2,2,3,4,grid,0.0,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0014466707466690395,0.0014466707466690395,0.07233353733345198,0.014466707462954169,0.014466707462954169,0.015716245303340294,True,1.0483208765976692e-05,1.0483208765976692e-05,0.2620802191494166,1.0483208765976692e-05,32,0,0.042105263157894736,32,2,31,0,0.0,0.9899627988825641,0.0018055084814242956,0.7793103448275862,0.2206896551724138,0.06483784844073309,0.49614257812500007,30,0.9375,0.10714285714285714,2.46875,3,True,abrupt-brittle,localized,abrupt-brittle/localized,2.0494150522187835e-12,2.5834951588775374e-17,0,0,0,3.070362587848799e-15,20,33,50,105.58250000000004,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",152 +S1_B2_ref_s2,S1,baseline,B2_ref,2,ok,"Reference hierarchical design (centre of the design space): 2x2 root, b=4, D=3, r_t=0.6, s_int=0.8, disorder 0.35.",reference,study/runs/S1_B2_ref_s2,9e28f288,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.00020037552753136191,0.00020037552753136191,0.010018776376568096,0.003953107245962912,0.00532339002360817,0.020361422202923706,True,1.1863263142450008e-06,1.1863263142450008e-06,0.02965815785612503,1.1863263142450008e-06,47,0,0.049473684210526316,47,27,5,4,0.0851063829787234,0.30723520568196316,0.4943404541476485,0.43184156378600824,0.5681584362139918,0.16690989344698717,0.6166960537752404,30,0.6382978723404256,0.10638297872340426,2.5531914893617023,2,False,intermediate,distributed,intermediate/distributed,5.842594929803456e-10,1.1006493296582747e-15,0,0,0,2.017040376885058e-14,75,48,95,181.06729200000007,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",237 +S1_B2_ref_s3,S1,baseline,B2_ref,3,ok,"Reference hierarchical design (centre of the design space): 2x2 root, b=4, D=3, r_t=0.6, s_int=0.8, disorder 0.35.",reference,study/runs/S1_B2_ref_s3,e8e9f0fb,2,2,3,4,grid,0.35,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03553704822361948,0.03553704822361948,0.00014393926359677266,0.00014393926359677266,0.0071969631798386325,0.0032557994863044747,0.004559290847304084,0.02303255874439029,True,9.393173546849099e-07,9.393173546849099e-07,0.02348293386712273,9.393173546849099e-07,39,0,0.040880503144654086,39,29,3,3,0.07692307692307693,0.2590329308487851,0.6229764947055321,0.5451555023923444,0.4548444976076555,0.14578762275804155,0.4624852087777296,24,0.6153846153846154,0.08421052631578947,2.4871794871794872,3,False,intermediate,distributed,intermediate/distributed,3.8755559597366094e-10,5.677896842334763e-16,0,0,0,1.3650297394284859e-13,82,40,92,147.08754199999998,True,completed,757,954,256,0.20000000000000015,0.20000000000000015,0.01863751534628866,0.00402570331479835,2.5204755614266845,285,0,13.06709243047595,"[0.18292962299726434, 0.22466041670068604, 0.2705210004717499, 0.32188895983030114]",211 +S1_B2_ref_s1,S1,baseline,B2_ref,1,ok,"Reference hierarchical design (centre of the design space): 2x2 root, b=4, D=3, r_t=0.6, s_int=0.8, disorder 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0.2706385482576284, 0.32160085286031964]",292 +S2_R_depth0_s1,S2,reconnaissance,R_depth0,1,ok,depth sweep (fixed r_t): D=0 flat 16x16,reconnaissance,study/runs/S2_R_depth0_s1,ad0bd5a5,16,16,0,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04978244439580835,0.04978244439580835,0.00025727119133511425,0.00025727119133511425,0.012863559566755712,0.004967268343919148,0.005442392228941327,0.011999093332373546,True,9.953035101193544e-07,9.953035101193544e-07,0.02488258775298387,9.953035101193544e-07,30,0,0.044642857142857144,30,18,8,1,0.03333333333333333,0.5194890989138077,0.2654904039434425,0.4375,0.5625,0.2767640455822123,0.5916365831710191,0,0.0,0.0,0.0,0,False,intermediate,distributed,intermediate/distributed,1.1839866132799505e-10,9.04955179228509e-17,0,0,0,2.89350132033521e-14,48,31,60,139.963709,True,completed,477,672,256,0.1999999999999999,0.1999999999999999,0.006797564307387961,0.006797564307387961,2.8176100628930816,0,0,6.441011475224623,[1],201 +S2_R_depth0_s2,S2,reconnaissance,R_depth0,2,ok,depth sweep (fixed r_t): D=0 flat 16x16,reconnaissance,study/runs/S2_R_depth0_s2,84164d4d,16,16,0,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.046815272242385075,0.046815272242385075,0.00022819530762072874,0.00022819530762072874,0.011409765381036437,0.0048451508274973765,0.005089923661235932,0.014064052818816182,True,1.0520041987411268e-06,1.0520041987411268e-06,0.026300104968528155,1.0520041987411268e-06,38,0,0.0572289156626506,38,25,7,1,0.02631578947368421,0.4016464124891737,0.4258401150101061,0.32649253731343286,0.6735074626865671,0.28190520267238345,0.5419095637033838,0,0.0,0.0,0.0,0,False,intermediate,distributed,intermediate/distributed,1.1687092644467646e-10,9.685220768809414e-17,0,0,0,7.24645066475121e-15,65,39,78,133.998583,True,completed,469,664,256,0.2000000000000001,0.2000000000000001,0.006790726748004542,0.006790726748004542,2.831556503198294,0,0,6.531747771990075,[1],196 +S2_R_depth1_s1,S2,reconnaissance,R_depth1,1,ok,"depth sweep 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each)",reconnaissance,study/runs/S2_R_depth1_s1,8afc8467,2,2,1,64,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.039214651004556414,0.039214651004556414,0.00020983222754914518,0.00020983222754914518,0.01049161137745726,0.005350863061990883,0.005350863061990883,0.017354296696680305,True,1.1836718723993725e-06,1.1836718723993725e-06,0.029591796809984253,1.1836718723993725e-06,38,0,0.05198358413132695,38,16,6,0,0.0,0.303740843300787,0.525720116449149,0.6076086956521739,0.3923913043478261,0.17459771037821056,0.43249359548312943,11,0.2894736842105263,0.19298245614035087,0.9473684210526315,1,False,intermediate,localized,intermediate/localized,5.606582470637544e-10,3.81551870724705e-16,0,0,0,7.621116205095253e-14,50,39,72,191.75904200000002,True,completed,532,731,256,0.20000000000000037,0.20000000000000037,0.01077390682858333,0.006464344097149998,2.7481203007518795,57,0,6.964833742373107,"[0.10503756702000218, 0.8949624329799977]",259 +S2_R_depth1_s2,S2,reconnaissance,R_depth1,2,ok,"depth sweep (fixed r_t): D=1 (2x2 root, 64 sub-cells each)",reconnaissance,study/runs/S2_R_depth1_s2,8a0fe9da,2,2,1,64,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04107294419851974,0.04107294419851974,0.00018281740900565437,0.00018281740900565437,0.009140870450282718,0.004451042226776737,0.004451042226776737,0.015053413032310552,True,9.528696636474929e-07,9.528696636474929e-07,0.023821741591187322,9.528696636474929e-07,38,0,0.05191256830601093,38,26,4,0,0.0,0.22658734698411206,0.5730119037690787,0.42879746835443033,0.5712025316455697,0.23866835972628406,0.4323994355838255,9,0.23684210526315788,0.14754098360655737,0.9736842105263158,0,False,progressive,distributed,progressive/distributed,1.8368780642333612e-10,1.872757098867952e-16,0,0,0,2.2112095039626943e-14,68,39,80,159.664208,True,completed,534,732,256,0.2,0.2,0.010736886111086936,0.006442131666652162,2.741573033707865,61,0,7.0761146669308,"[0.1072545627180572, 0.8927454372819429]",236 +S2_R_depth2_s2,S2,reconnaissance,R_depth2,2,ok,depth sweep (fixed r_t): D=2 (b=8),reconnaissance,study/runs/S2_R_depth2_s2,00deb8a3,2,2,2,8,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03639200154174071,0.03639200154174071,0.0001687955668107848,0.0001687955668107848,0.00843977834053924,0.004638260047806975,0.004638260047806975,0.016655142936617174,True,9.258785813819257e-07,9.258785813819257e-07,0.023146964534548124,9.258785813819257e-07,42,0,0.04550379198266522,42,22,5,0,0.0,0.3565301577647355,0.5772028052442635,0.5033783783783784,0.4966216216216216,0.14732034138272002,0.4283398539452925,20,0.47619047619047616,0.08547008547008547,1.7619047619047619,0,False,intermediate,distributed,intermediate/distributed,8.657223763040799e-11,2.9244897947232087e-16,0,0,0,6.975673001501102e-15,61,43,81,242.203709,True,completed,722,923,256,0.20000000000000015,0.20000000000000015,0.014217838838751672,0.005118421981950602,2.556786703601108,234,0,9.755323209627244,"[0.14202703387823729, 0.3340496820382124, 0.5239232840835492]",310 +S2_R_depth2_s1,S2,reconnaissance,R_depth2,1,ok,depth sweep (fixed r_t): D=2 (b=8),reconnaissance,study/runs/S2_R_depth2_s1,15e21522,2,2,2,8,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.029442951332538658,0.029442951332538658,0.00014546882880653046,0.00014546882880653046,0.007273441440326523,0.004382923545627839,0.0055564642316220676,0.02052092642493578,True,8.11092933097311e-07,8.11092933097311e-07,0.020277323327432758,8.11092933097311e-07,34,0,0.03715846994535519,34,20,6,1,0.029411764705882353,0.4077773012727739,0.4630876394207297,0.435546875,0.564453125,0.20464036462842417,0.5248682955955721,22,0.6470588235294118,0.0944206008583691,1.7352941176470589,1,False,intermediate,distributed,intermediate/distributed,1.434167744438674e-09,3.0199580783365983e-15,0,0,0,1.868010584946561e-13,61,35,75,235.528959,True,completed,714,915,256,0.20000000000000018,0.20000000000000018,0.014298970043914946,0.005147629215809381,2.563025210084034,233,0,9.639309489560148,"[0.13938088204159985, 0.3433870223845527, 0.5172320955738485]",324 +S2_R_depthC1_s1,S2,reconnaissance,R_depthC1,1,ok,depth sweep (fixed contrast t_D/t_0=0.216): D=1,reconnaissance,study/runs/S2_R_depthC1_s1,6c38c150,2,2,1,64,grid,0.35,0,1,0.21599999999999997,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03374848248803913,0.03374848248803913,0.0001470264419131939,0.0001470264419131939,0.007351322095659694,0.004124807859404493,0.005711143986204566,0.0201179093103996,True,8.846582427863146e-07,8.846582427863146e-07,0.02211645606965783,8.846582427863146e-07,31,0,0.04240766073871409,31,19,5,3,0.0967741935483871,0.3580727783051547,0.43487819004899625,0.6022350993377483,0.3977649006622517,0.17188362143011304,0.40241763706374956,3,0.0967741935483871,0.05263157894736842,0.967741935483871,1,False,intermediate,localized,intermediate/localized,3.436950517980886e-09,3.566751663635917e-15,0,0,0,1.2877959634093604e-13,59,32,71,88.57054099999999,True,completed,532,731,256,0.20000000000000026,0.20000000000000026,0.025218400059209008,0.005447174412789145,2.7481203007518795,57,0,8.26540119303566,"[0.24586061755508037, 0.7541393824449206]",145 +S2_R_depth3_s2,S2,reconnaissance,R_depth3,2,ok,depth sweep (fixed r_t): D=3 (b=4) reference,reconnaissance,study/runs/S2_R_depth3_s2,9e28f288,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.00020037552753136191,0.00020037552753136191,0.010018776376568096,0.003953107245962912,0.00532339002360817,0.020361422202923706,True,1.1863263142450008e-06,1.1863263142450008e-06,0.02965815785612503,1.1863263142450008e-06,47,0,0.049473684210526316,47,27,5,4,0.0851063829787234,0.30723520568196316,0.4943404541476485,0.43184156378600824,0.5681584362139918,0.16690989344698717,0.6166960537752404,30,0.6382978723404256,0.10638297872340426,2.5531914893617023,2,False,intermediate,distributed,intermediate/distributed,5.842594929803456e-10,1.1006493296582747e-15,0,0,0,2.017040376885058e-14,75,48,95,293.467166,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",358 +S2_R_depthC1_s2,S2,reconnaissance,R_depthC1,2,ok,depth sweep (fixed contrast t_D/t_0=0.216): 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0.7497810935891875]",143 +S2_R_depth3_s1,S2,reconnaissance,R_depth3,1,ok,depth sweep (fixed r_t): D=3 (b=4) 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0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",348 +S2_R_depth6_s2,S2,reconnaissance,R_depth6,2,ok,depth sweep (fixed r_t): D=6 (b=2),reconnaissance,study/runs/S2_R_depth6_s2,7cc663ec,2,2,6,2,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06253121119390634,0.06253121119390634,0.0003621024495215181,0.0003621024495215181,0.018105122476075906,0.0032364358603390988,0.006108696826450694,0.014892629126763072,True,1.942878000585591e-06,1.942878000585591e-06,0.04857195001463971,1.942878000585591e-06,46,0,0.04129263913824058,46,21,10,3,0.06521739130434782,0.6215257121036355,0.411904165243686,0.33875,0.66125,0.19291542008327237,0.43495172058606973,35,0.7608695652173914,0.078125,4.1521739130434785,6,True,abrupt-brittle,distributed,abrupt-brittle/distributed,8.960342316727724e-11,2.5437854564144322e-15,0,0,0,3.008180304832886e-14,57,47,82,320.578375,True,completed,917,1114,256,0.2000000000000003,0.2000000000000003,0.031711789453179436,0.0014795452487275393,2.4296619411123226,448,0,12.600177760177775,"[0.31678031000959705, 0.1846079345613821, 0.12063969410872638, 0.1273594307259436, 0.09212835005333285, 0.09012059904536819, 0.06836368149564845]",428 +S2_R_depthC2_s1,S2,reconnaissance,R_depthC2,1,ok,depth sweep (fixed contrast): D=2,reconnaissance,study/runs/S2_R_depthC2_s1,189f1e6b,2,2,2,8,grid,0.35,0,1,0.46475800154489,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.028251376372376763,0.028251376372376763,0.00013311147297847187,0.00013311147297847187,0.006655573648923593,0.0043969827487888545,0.005506097110706604,0.05121516764448382,True,1.0636622508137024e-06,1.0636622508137024e-06,0.026591556270342508,1.0636622508137024e-06,48,0,0.05245901639344262,48,29,5,2,0.041666666666666664,0.3773414037986104,0.6171838380784469,0.5,0.5,0.1733735237104028,0.5261688086523119,30,0.625,0.12875536480686695,1.8125,1,False,intermediate,distributed,intermediate/distributed,4.644297631731998e-09,6.875416080832662e-15,0,0,0,5.349389638325466e-13,110,49,129,172.027583,True,completed,714,915,256,0.20000000000000037,0.20000000000000037,0.019978815872096302,0.004315424228372801,2.563025210084034,233,0,11.498195431738187,"[0.19474584322138175, 0.3716417454424872, 0.43361241133613]",229 +S2_R_rt1_s1,S2,reconnaissance,R_rt1,1,ok,thickness-ratio sweep r_t=1,reconnaissance,study/runs/S2_R_rt1_s1,5caf6d5c,2,2,3,4,grid,0.35,0,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03370736224162375,0.03370736224162375,0.00013585078486598744,0.00013585078486598744,0.006792539243299371,0.004030300083767177,0.004030300083767177,0.019754621544659852,True,7.111510065655213e-07,7.111510065655213e-07,0.017778775164138012,7.111510065655213e-07,32,0,0.03397027600849257,32,19,4,0,0.0,0.21320922069987103,0.6150469980563967,0.5223880597014925,0.47761194029850745,0.2358599028392497,0.46569162698423,15,0.46875,0.053763440860215055,2.03125,3,True,progressive,distributed,progressive/distributed,1.8472083143405985e-10,2.0924184286678708e-16,0,0,0,1.3950445549713133e-13,58,33,71,130.50183299999998,True,completed,746,942,256,0.2000000000000002,0.2000000000000002,0.0066908080302243746,0.0066908080302243746,2.525469168900804,279,0,7.844303756847165,"[0.06521730193512827, 0.1341414312524813, 0.26862590284005705, 0.5320153639723333]",177 +S2_R_depthC2_s2,S2,reconnaissance,R_depthC2,2,ok,depth sweep (fixed contrast): D=2,reconnaissance,study/runs/S2_R_depthC2_s2,ea312d7b,2,2,2,8,grid,0.35,0,2,0.46475800154489,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03990856924064015,0.03990856924064015,0.00020002681328712226,0.00020002681328712226,0.010001340664356113,0.00501212689638167,0.00501212689638167,0.019507962369128957,True,1.048645703614723e-06,1.048645703614723e-06,0.0262161425903681,1.048645703614723e-06,45,0,0.04875406283856988,45,25,4,0,0.0,0.4698946738328568,0.5219740244879484,0.45681330472103,0.54318669527897,0.1748255281943659,0.44854419314493743,23,0.5111111111111111,0.09829059829059829,1.7777777777777777,2,False,intermediate,distributed,intermediate/distributed,2.611153181582592e-10,1.348998564590367e-15,0,0,0,1.001597442277058e-13,70,46,90,168.917416,True,completed,722,923,256,0.19999999999999982,0.19999999999999982,0.019881341710549342,0.004294369809478657,2.556786703601108,234,0,11.62728478739254,"[0.19860177237154059, 0.3618251831265919, 0.43957304450186707]",220 +S2_R_depthC6_s2,S2,reconnaissance,R_depthC6,2,ok,depth sweep (fixed contrast): D=6,reconnaissance,study/runs/S2_R_depthC6_s2,c60195f1,2,2,6,2,grid,0.35,0,2,0.7745966692414834,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.048656506563275255,0.048656506563275255,0.0002446267106774035,0.0002446267106774035,0.012231335533870175,0.004836123704798676,0.005154385929820455,0.013642553493686536,True,1.0190553188910363e-06,1.0190553188910363e-06,0.02547638297227595,1.0190553188910363e-06,33,0,0.0296229802513465,33,18,7,1,0.030303030303030304,0.5879973119166619,0.36760719484867777,0.5492549668874172,0.4507450331125828,0.126262327565303,0.5390376232991753,21,0.6363636363636364,0.046875,4.0606060606060606,5,False,intermediate,distributed,intermediate/distributed,2.504856927822245e-11,2.4012758281071965e-16,0,0,0,4.0520720919825185e-14,50,34,65,193.32929199999995,True,completed,917,1114,256,0.19999999999999968,0.19999999999999968,0.016466814791779142,0.0035568319950242955,2.4296619411123226,448,0,20.298028804950306,"[0.16449285217133766, 0.12375523797679229, 0.10440657001072727, 0.14229612877985723, 0.13288612703138927, 0.16781655265446258, 0.16434653137543306]",269 +S2_R_rt1_s2,S2,reconnaissance,R_rt1,2,ok,thickness-ratio sweep r_t=1,reconnaissance,study/runs/S2_R_rt1_s2,de34ea9c,2,2,3,4,grid,0.35,0,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03499081330775773,0.03499081330775773,0.00016012157611301102,0.00016012157611301102,0.008006078805650551,0.003856356140457098,0.004984789235330194,0.016096518451227376,True,7.747938738890594e-07,7.747938738890594e-07,0.019369846847226445,7.747938738890594e-07,38,0,0.04,38,23,4,1,0.02631578947368421,0.1568937717386923,0.4573812992349905,0.5970982142857143,0.4029017857142857,0.17466038845136816,0.4963593342152775,16,0.42105263157894735,0.05673758865248227,1.894736842105263,0,False,progressive,distributed,progressive/distributed,1.53427174916483e-10,8.64148294652774e-17,0,0,0,3.635011381135183e-14,63,39,78,138.09337499999998,True,completed,753,950,256,0.20000000000000043,0.20000000000000043,0.006669558406737532,0.006669558406737532,2.5232403718459495,282,0,7.81809198203799,"[0.06662458398422541, 0.1328437033944165, 0.2667012955707675, 0.53383041705059]",198 +S2_R_depth6_s1,S2,reconnaissance,R_depth6,1,ok,depth sweep (fixed r_t): D=6 (b=2),reconnaissance,study/runs/S2_R_depth6_s1,95b554c6,2,2,6,2,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.045605016066841655,0.045605016066841655,0.0002321220144012561,0.0002321220144012561,0.011606100720062804,0.00306573551598125,0.00622480626778867,0.03508357533755291,True,2.1444199238155556e-06,2.1444199238155556e-06,0.053610498095388884,2.1444199238155556e-06,89,0,0.07967770814682185,89,53,20,12,0.1348314606741573,0.6178319760543233,0.629990811269353,0.18975040916530284,0.8102495908346972,0.2446390572678651,0.5184937345839241,77,0.8651685393258427,0.1714922048997773,4.49438202247191,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,1.4731740674461451e-09,9.462192230463874e-15,0,0,0,3.8334165159575515e-13,142,90,178,552.4915,True,completed,920,1117,256,0.2,0.2,0.03147156267303781,0.0014683372280732516,2.4282608695652175,449,0,12.38810635161128,"[0.3067478653420361, 0.19672966055002464, 0.11752793388130436, 0.13142793633227373, 0.09006243518929274, 0.09010338441441101, 0.06740078429065745]",666 +S2_R_rt0.8_s1,S2,reconnaissance,R_rt0.8,1,ok,thickness-ratio sweep r_t=0.8,reconnaissance,study/runs/S2_R_rt0.8_s1,f69d34ca,2,2,3,4,grid,0.35,0,1,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03749484943267388,0.03749484943267388,0.0001311180096328696,0.0001311180096328696,0.006555900481643479,0.0034466186792056724,0.0036631079763851542,0.026682927877707197,True,9.843001279762935e-07,9.843001279762935e-07,0.024607503199407365,9.843001279762935e-07,53,0,0.05626326963906582,53,34,5,1,0.018867924528301886,0.18291790175944314,0.7457575356996429,0.38828397212543553,0.6117160278745645,0.21415717293376652,0.4966869013558594,42,0.7924528301886793,0.15053763440860216,2.4716981132075473,3,True,progressive,distributed,progressive/distributed,2.6991248942887406e-10,4.665253622535046e-16,0,0,0,3.6788228982119424e-14,95,54,114,203.366083,True,completed,746,942,256,0.19999999999999976,0.19999999999999976,0.01084685926784325,0.005553591945135745,2.525469168900804,279,0,9.450591812710032,"[0.1057275732203389, 0.17397160046559507, 0.27871047927400583, 0.4415903470400626]",271 +S2_R_rt0.8_s2,S2,reconnaissance,R_rt0.8,2,ok,thickness-ratio sweep r_t=0.8,reconnaissance,study/runs/S2_R_rt0.8_s2,378efcdd,2,2,3,4,grid,0.35,0,2,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04165258371249998,0.04165258371249998,0.00018224307346650286,0.00018224307346650286,0.009112153673325143,0.004375312579032472,0.004375312579032472,0.028050769677264165,True,1.1826131142326239e-06,1.1826131142326239e-06,0.02956532785581558,1.1826131142326239e-06,47,0,0.049473684210526316,47,24,9,0,0.0,0.47851445839308954,0.6628777399035827,0.48291198501872656,0.5170880149812734,0.1659661779724498,0.6446505404688677,26,0.5531914893617021,0.09219858156028368,2.3617021276595747,2,False,intermediate,distributed,intermediate/distributed,5.5965304506345124e-11,1.8746565494144866e-16,0,0,0,7.71746896497701e-14,77,48,100,176.489375,True,completed,753,950,256,0.2000000000000001,0.2000000000000001,0.010811241961287263,0.005535355884179079,2.5232403718459495,282,0,9.420030472201855,"[0.10799732967267084, 0.17226992647425346, 0.2766837202191118, 0.44304902363396403]",230 +S2_R_dis0_s1,S2,reconnaissance,R_dis0,1,ok,disorder sweep delta=0,reconnaissance,study/runs/S2_R_dis0_s1,6767c994,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0013862703765912987,0.0013862703765912987,0.06931351882956494,0.013862703762332798,0.013862703762332798,0.013862703762332798,True,9.608727782591333e-06,9.608727782591333e-06,0.24021819456478272,9.609441934596302e-06,34,0,0.04473684210526316,34,1,34,0,0.0,0.9962663056601007,0.0,0.6938559322033898,0.3061440677966102,0.09100556253036025,0.4597886029411765,30,0.8823529411764706,0.10714285714285714,2.323529411764706,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.5550107648744588e-12,2.378806536501951e-17,0,0,0,5.817629670825665e-15,17,35,50,89.79962499999999,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",127 +S2_R_rt0.45_s1,S2,reconnaissance,R_rt0.45,1,ok,thickness-ratio sweep r_t=0.45,reconnaissance,study/runs/S2_R_rt0.45_s1,98701e17,2,2,3,4,grid,0.35,0,1,0.45,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03437099962976545,0.03437099962976545,0.00011862414778574524,0.00011862414778574524,0.005931207389287262,0.0032731892441213743,0.003928431731263773,0.020727994296858277,True,8.489570009326573e-07,8.489570009326573e-07,0.02122392502331649,8.489570009326573e-07,49,0,0.05201698513800425,49,30,9,2,0.04081632653061224,0.39595406613834544,0.6976706481470687,0.4068675889328063,0.5931324110671937,0.2266265448569185,0.511054299370311,37,0.7551020408163265,0.13261648745519714,2.489795918367347,2,True,intermediate,distributed,intermediate/distributed,3.7208148660080335e-09,6.3147243374883475e-15,0,0,0,8.929715956871341e-14,81,50,100,185.80891599999995,True,completed,746,942,256,0.19999999999999946,0.19999999999999946,0.02928687110033561,0.002668766129018083,2.525469168900804,279,0,13.312857213014253,"[0.28546786974871924, 0.2642225355819093, 0.23810434575581568, 0.21220524891355808]",254 +S2_R_depthC6_s1,S2,reconnaissance,R_depthC6,1,ok,depth sweep (fixed contrast): D=6,reconnaissance,study/runs/S2_R_depthC6_s1,b683a66e,2,2,6,2,grid,0.35,0,1,0.7745966692414834,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03859790515110154,0.03859790515110154,0.00017629102860005784,0.00017629102860005784,0.008814551430002891,0.0035620544047629222,0.005404339841054588,0.029616497502126752,True,1.3337260609217878e-06,1.3337260609217878e-06,0.03334315152304475,1.3337260609217878e-06,60,0,0.05371530886302596,60,35,7,4,0.06666666666666667,0.2684873583180413,0.6020668504294785,0.23469387755102045,0.7653061224489796,0.22717913500999437,0.4955645358214692,53,0.8833333333333333,0.11804008908685969,4.25,3,False,intermediate,distributed,intermediate/distributed,2.1606452321397186e-10,9.539534760478378e-16,0,0,0,1.5067454451418067e-13,100,61,125,310.23470799999996,True,completed,920,1117,256,0.19999999999999968,0.19999999999999968,0.016351191064019204,0.0035318572698281488,2.4282608695652175,449,0,20.307479415208412,"[0.15937222459514858, 0.1319548334960184, 0.10177027232582658, 0.1469237142225485, 0.12997872438845307, 0.16787810709079956, 0.1621221238812056]",391 +S2_R_dis0_s2,S2,reconnaissance,R_dis0,2,ok,disorder sweep delta=0,reconnaissance,study/runs/S2_R_dis0_s2,d25ea1b6,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.001418813763351174,0.001418813763351174,0.0709406881675587,0.014188137629847577,0.014188137629847577,0.014188137629847577,True,1.006516247277425e-05,1.006516247277425e-05,0.2516290618193556,1.0074401912764517e-05,32,0,0.042105263157894736,32,1,32,0,0.0,0.9922019350710082,0.0,0.7793103448275862,0.2206896551724138,0.09810735653232977,0.4009765625,28,0.875,0.1,2.40625,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.1595892460631707e-12,2.6834668691891227e-17,0,0,0,5.8854418179084356e-15,18,33,49,87.027333,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",134 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0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",244 +S2_R_sint0.5_s2,S2,reconnaissance,R_sint0.5,2,ok,inter-level strength sweep s_int=0.5,reconnaissance,study/runs/S2_R_sint0.5_s2,42fa6e89,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.0001852660332908249,0.0001852660332908249,0.009263301664541245,0.0025512278107713026,0.004948140568780745,0.05923189126062626,True,9.996440121442441e-07,9.996440121442441e-07,0.024991100303606108,9.996440121442441e-07,81,0,0.08526315789473685,81,43,9,15,0.18518518518518517,0.3293120079506097,0.47610941633005444,0.4722490347490348,0.5277509652509652,0.2111850980467038,0.34454488018726953,73,0.9012345679012346,0.25886524822695034,2.5925925925925926,3,True,intermediate,distributed,intermediate/distributed,9.11055397575872e-10,3.1233844897944487e-15,0,0,0,4.91877728378941e-13,146,82,184,243.7382080000001,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",305 +S2_R_sint1_s2,S2,reconnaissance,R_sint1,2,ok,inter-level strength sweep s_int=1,reconnaissance,study/runs/S2_R_sint1_s2,1a39a237,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,1.0,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.000200375527298377,0.000200375527298377,0.01001877636491885,0.003953107245962912,0.005323390021416419,0.06370539387627641,True,1.474862026568228e-06,1.474862026568228e-06,0.03687155066420571,1.474862026568228e-06,48,0,0.05052631578947368,48,33,3,4,0.08333333333333333,0.30723520589474773,0.5905826151041673,0.4098360655737705,0.5901639344262295,0.16743518004450825,0.6095611657262444,22,0.4583333333333333,0.07801418439716312,2.5,2,False,intermediate,distributed,intermediate/distributed,5.869902270931911e-10,3.4317914959872593e-15,0,0,0,2.986429405855073e-14,130,49,145,160.095959,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",220 +S2_R_sint1.5_s1,S2,reconnaissance,R_sint1.5,1,ok,inter-level strength sweep s_int=1.5,reconnaissance,study/runs/S2_R_sint1.5_s1,f29885e0,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,1.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03697465880742474,0.03697465880742474,0.00014560780531312775,0.00014560780531312775,0.007280390265656388,0.003938043243928148,0.003938043243928148,0.029135483151003783,True,1.2019103308080826e-06,1.2019103308080826e-06,0.030047758270202073,1.2019103308080826e-06,39,0,0.041401273885350316,39,32,3,0,0.0,0.27310782074184803,0.7614589793936433,0.31609712230215825,0.6839028776978417,0.2135357931931161,0.4704516422644076,1,0.02564102564102564,0.0035842293906810036,2.358974358974359,3,False,intermediate,distributed,intermediate/distributed,1.3434845788364513e-09,3.112256763727128e-15,0,0,0,6.307413027084205e-14,94,40,101,147.65925000000004,True,completed,746,942,256,0.19999999999999993,0.19999999999999993,0.018724827940452965,0.00404456283513784,2.525469168900804,279,0,12.976613964768223,"[0.18251648410168128, 0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",210 +S2_R_sint1.5_s2,S2,reconnaissance,R_sint1.5,2,ok,inter-level strength sweep s_int=1.5,reconnaissance,study/runs/S2_R_sint1.5_s2,e2f14a23,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,1.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.000200375527298377,0.000200375527298377,0.01001877636491885,0.003953107245962912,0.005323390021416419,0.056025676730376714,True,1.8468859280325735e-06,1.8468859280325735e-06,0.04617214820081435,1.8468859280325735e-06,52,0,0.05473684210526316,52,41,3,4,0.07692307692307693,0.30723520589474773,0.6730528156425034,0.4403973509933775,0.5596026490066225,0.16325473065868884,0.5935427688374056,2,0.038461538461538464,0.0070921985815602835,2.4423076923076925,2,False,intermediate,distributed,intermediate/distributed,7.121376295622835e-10,2.2216714649540995e-15,0,0,0,6.94820885043655e-14,139,53,150,180.56158399999993,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",233 +S2_R_sint0.3_s2,S2,reconnaissance,R_sint0.3,2,ok,inter-level strength sweep s_int=0.3,reconnaissance,study/runs/S2_R_sint0.3_s2,490a58ea,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.3,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.000111159619974496,0.000111159619974496,0.0055579809987248,0.0015307366864627818,0.002968884341268447,0.049278087467613425,True,7.674929160604501e-07,7.674929160604501e-07,0.019187322901511258,7.674929160604501e-07,150,0,0.15789473684210525,150,63,14,15,0.1,0.6499144010997465,0.7543515169336892,0.24718950749464663,0.7528104925053534,0.28214190930929683,0.4451192419367505,147,0.98,0.5212765957446809,2.6733333333333333,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,4.610743173349548e-10,2.6581353879574923e-15,0,0,0,1.8734224093488914e-13,176,151,263,400.6478339999999,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",458 +S2_R_con0.7_s1,S2,reconnaissance,R_con0.7,1,ok,connectivity sweep: 30% of finest walls removed,reconnaissance,study/runs/S2_R_con0.7_s1,18896d58,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,0.7,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.027736281924688154,0.027736281924688154,0.0001238315730092655,0.0001238315730092655,0.006191578650463275,0.004092662077088611,0.005070689330991973,0.045784313391402515,True,1.0173735897987478e-06,1.0173735897987478e-06,0.02543433974496869,1.0173735897987478e-06,40,0,0.05517241379310345,40,28,4,2,0.05,0.31254300023588016,0.6630578438892805,0.4505494505494505,0.5494505494505495,0.20713027948392676,0.46894296037426264,33,0.825,0.1542056074766355,2.375,2,False,intermediate,distributed,intermediate/distributed,2.103085785705265e-09,4.012614329527817e-15,0,0,0,6.494032334661332e-14,102,41,114,106.74212499999999,True,completed,608,725,256,0.20000000000000004,0.20000000000000004,0.020699659454729714,0.004471126442221618,2.3848684210526314,214,0,11.968909829637036,"[0.2017657560215743, 0.24899788779010884, 0.29919906277952085, 0.2500372934087956]",151 +S2_R_con0.7_s2,S2,reconnaissance,R_con0.7,2,ok,connectivity sweep: 30% of finest walls removed,reconnaissance,study/runs/S2_R_con0.7_s2,ecc3576f,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,0.7,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03928709270956119,0.03928709270956119,0.00020054858013330776,0.00020054858013330776,0.010027429006665388,0.0051046938396767305,0.0051046938396767305,0.022337639306385614,True,1.3000049638532012e-06,1.3000049638532012e-06,0.03250012409633003,1.3000049638532012e-06,37,0,0.04979811574697174,37,20,5,0,0.0,0.42934209539937346,0.6062556951597902,0.4099137931034482,0.5900862068965518,0.1953396836824458,0.5796474060162654,24,0.6486486486486487,0.11009174311926606,2.324324324324324,2,False,intermediate,distributed,intermediate/distributed,2.767128825060674e-10,9.511889199646894e-16,0,0,0,3.111205291979181e-14,63,38,80,99.56395799999996,True,completed,621,743,256,0.19999999999999998,0.19999999999999998,0.02065113208110975,0.004460644529519706,2.392914653784219,218,0,11.558240210444286,"[0.20629148135464795, 0.24689608257862725, 0.2972859301744194, 0.24952650589230446]",142 +S2_R_red0.5_s1,S2,reconnaissance,R_red0.5,1,ok,redundancy sweep (braces) r=0.5,reconnaissance,study/runs/S2_R_red0.5_s1,7a813d26,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.5,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04569050116168595,0.04569050116168595,0.000239220754855609,0.000239220754855609,0.01196103774278045,0.003589674053161281,0.005891145780137695,0.026362413682998104,True,1.4445411131672499e-06,1.4445411131672499e-06,0.036113527829181216,1.4445411131672499e-06,41,0,0.0353448275862069,41,19,8,2,0.04878048780487805,0.5586993211096167,0.4759224224343618,0.47730099502487566,0.5226990049751243,0.16739944668210585,0.42336520562148444,14,0.34146341463414637,0.05017921146953405,2.1707317073170733,2,True,intermediate,distributed,intermediate/distributed,2.595182263827292e-10,9.330759751295159e-16,0,0,0,3.5182090957471986e-15,65,42,87,245.88745800000015,True,completed,748,1160,256,0.20000000000000018,0.20000000000000018,0.0138166212338543,0.0029843901865125285,3.1016042780748663,279,224,20.965452308787857,"[0.1346747290702589, 0.16620246813332837, 0.1996979798397757, 0.49942482295663565]",324 +S2_R_cv0_s1,S2,reconnaissance,R_cv0,1,ok,strength disorder control: CV=0,reconnaissance,study/runs/S2_R_cv0_s1,2f35a17e,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.0,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03697465880742474,0.03697465880742474,0.00014105423363463553,0.00014105423363463553,0.007052711681731777,0.0038148893913879526,0.0038148893913879526,0.016108353436587147,True,8.449214150886738e-07,8.449214150886738e-07,0.02112303537721685,8.449214150886738e-07,42,0,0.044585987261146494,42,29,3,0,0.0,0.296055859011252,0.6815642911319447,0.41356382978723405,0.586436170212766,0.21265382320199175,0.4839128201527784,32,0.7619047619047619,0.11469534050179211,2.4047619047619047,3,False,intermediate,distributed,intermediate/distributed,5.010601622342313e-10,1.1690841732464035e-15,0,0,0,1.0526240414011464e-13,75,43,88,165.26466699999992,True,completed,746,942,256,0.19999999999999993,0.19999999999999993,0.018724827940452965,0.00404456283513784,2.525469168900804,279,0,12.976613964768223,"[0.18251648410168128, 0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",228 +S2_R_cv0_s2,S2,reconnaissance,R_cv0,2,ok,strength disorder control: CV=0,reconnaissance,study/runs/S2_R_cv0_s2,ceca9a2e,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.0,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.00021177606471552347,0.00021177606471552347,0.010588803235776174,0.0041226537854052725,0.006509128002361128,0.021088780974195847,True,1.2624954870415828e-06,1.2624954870415828e-06,0.031562387176039576,1.2624954870415828e-06,45,0,0.04736842105263158,45,25,6,9,0.2,0.5383095395228897,0.3290522476550098,0.3640075376884422,0.6359924623115578,0.18178732210967283,0.5618114418397295,23,0.5111111111111111,0.08156028368794327,2.511111111111111,2,False,intermediate,distributed,intermediate/distributed,5.201406013776848e-10,1.0590049854699291e-15,0,0,0,5.031896881701893e-15,72,46,92,160.4665,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",215 +S2_R_red0.5_s2,S2,reconnaissance,R_red0.5,2,ok,redundancy sweep (braces) r=0.5,reconnaissance,study/runs/S2_R_red0.5_s2,9246bbe4,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.5,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04554655558344983,0.04554655558344983,0.00024043416812544115,0.00024043416812544115,0.012021708406272057,0.004236709331651128,0.007392315342861889,0.019080569476260464,True,1.4620891054898518e-06,1.4620891054898518e-06,0.036552227637246304,1.4620891054898518e-06,56,0,0.04778156996587031,56,24,15,8,0.14285714285714285,0.5177202042557291,0.2675043879590678,0.5311004784688995,0.4688995215311005,0.22944851455299298,0.5115159784046279,23,0.4107142857142857,0.08156028368794327,2.25,2,False,intermediate,distributed,intermediate/distributed,3.4109367065532236e-11,5.324960118804967e-16,0,0,0,5.445707566176573e-14,68,57,100,335.32574999999997,True,completed,755,1172,256,0.19999999999999993,0.19999999999999993,0.013657735829022773,0.0029500709390689185,3.104635761589404,282,225,20.58968681161148,"[0.13643196629868024, 0.1632201801256135, 0.19661165289957497, 0.5037362006761319]",420 +S2_R_cv0.2_s2,S2,reconnaissance,R_cv0.2,2,ok,strength disorder control: CV=0.2,reconnaissance,study/runs/S2_R_cv0.2_s2,33bdfe05,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.2,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04587722744973127,0.04587722744973127,0.00015458117532689825,0.00015458117532689825,0.0077290587663449125,0.0032432475672097014,0.003474002250094223,0.022624355804982475,True,1.0051143475567145e-06,1.0051143475567145e-06,0.02512785868891787,1.0051143475567145e-06,43,0,0.045263157894736845,43,29,6,1,0.023255813953488372,0.3718811113400463,0.7256341835592242,0.44172705314009664,0.5582729468599034,0.1746909610961932,0.599161871684397,22,0.5116279069767442,0.07801418439716312,2.395348837209302,3,True,intermediate,distributed,intermediate/distributed,5.040901515567015e-10,8.802228412530071e-16,0,0,0,2.4649646846067225e-14,81,44,95,141.16845799999987,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018648249475923903,0.004028021886799562,2.5232403718459495,282,0,12.945118613761757,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",192 +S2_R_cv0.2_s1,S2,reconnaissance,R_cv0.2,1,ok,strength disorder control: CV=0.2,reconnaissance,study/runs/S2_R_cv0.2_s1,8a0fe0b1,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.2,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03697465880742474,0.03697465880742474,0.0001060739573991917,0.0001060739573991917,0.005303697869959585,0.002448081091198269,0.0031880866908740608,0.018923474507914637,True,6.597793771627619e-07,6.597793771627619e-07,0.01649448442906905,6.597793771627619e-07,46,0,0.04883227176220807,46,30,6,2,0.043478260869565216,0.2662460772948695,0.7235093862471947,0.30394736842105263,0.6960526315789474,0.22777234780308012,0.5132556330942885,32,0.6956521739130435,0.11469534050179211,2.4782608695652173,3,True,intermediate,distributed,intermediate/distributed,6.732676867483547e-10,1.4814460091648095e-15,0,0,0,9.339735227515125e-14,79,47,95,179.10691699999984,True,completed,746,942,256,0.19999999999999993,0.19999999999999993,0.018724827940452965,0.00404456283513784,2.525469168900804,279,0,12.976613964768223,"[0.18251648410168128, 0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",238 +S2_R_rho0.1_s1,S2,reconnaissance,R_rho0.1,1,ok,density control: rho=0.1,reconnaissance,study/runs/S2_R_rho0.1_s1,91f0cf58,2,2,3,4,grid,0.35,0,1,0.6,0.1,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.007563780932427995,0.007563780932427995,3.235495884300396e-05,3.235495884300396e-05,0.001617747942150198,0.0042776171245638185,0.0042776171245638185,0.05292278999787303,True,4.414085423684937e-07,4.414085423684937e-07,0.02207042711842469,4.414085423684937e-07,51,0,0.054140127388535034,51,34,3,0,0.0,0.27540593389416235,0.8432267245341968,0.32546680497925307,0.6745331950207469,0.19909597738678844,0.4821252932738624,36,0.7058823529411765,0.12903225806451613,2.5294117647058822,3,True,intermediate,distributed,intermediate/distributed,6.843468712911795e-10,5.83276770609339e-16,0,0,0,4.796130498934416e-13,121,52,138,180.28583400000002,True,completed,746,942,256,0.09999999999999996,0.09999999999999996,0.009362413970226482,0.00202228141756892,2.525469168900804,279,0,25.953227929536446,"[0.18251648410168128, 0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",240 +S2_R_rho0.1_s2,S2,reconnaissance,R_rho0.1,2,ok,density control: rho=0.1,reconnaissance,study/runs/S2_R_rho0.1_s2,7d944e76,2,2,3,4,grid,0.35,0,2,0.6,0.1,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.01103015740618516,0.01103015740618516,5.023443773965985e-05,5.023443773965985e-05,0.0025117218869829924,0.004554281130339186,0.004554281130339186,0.06469672344410451,True,5.351350448008203e-07,5.351350448008203e-07,0.026756752240041023,5.351350448008203e-07,50,0,0.05263157894736842,50,38,5,0,0.0,0.4095229882787608,0.7862392361389017,0.43794964028776984,0.5620503597122302,0.17069581202708806,0.6166251608166007,31,0.62,0.1099290780141844,2.54,2,False,intermediate,distributed,intermediate/distributed,4.2179889150920204e-10,7.547623156803967e-16,0,0,0,4.900867151977087e-13,141,51,153,169.2823330000001,True,completed,753,950,256,0.09999999999999996,0.09999999999999996,0.009324124737961952,0.002014010943399781,2.5232403718459495,282,0,25.890237227523514,"[0.18628397677909056, 0.22286055877722039, 0.26845321940945543, 0.3224022450342325]",217 +S2_R_rho0.3_s1,S2,reconnaissance,R_rho0.3,1,ok,density control: rho=0.3,reconnaissance,study/runs/S2_R_rho0.3_s1,e1c5df0a,2,2,3,4,grid,0.35,0,1,0.6,0.3,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07920867072339803,0.07920867072339803,0.0002970552566556882,0.0002970552566556882,0.01485276283278441,0.00375028710799888,0.00375028710799888,0.012525445772458708,True,1.4652605352832273e-06,1.4652605352832273e-06,0.02442100892138713,1.4652605352832273e-06,45,0,0.04777070063694268,45,27,7,0,0.0,0.26183544102059,0.6198483230206597,0.3575507614213198,0.6424492385786802,0.2100106401984626,0.505437540479397,36,0.8,0.12903225806451613,2.466666666666667,2,True,intermediate,distributed,intermediate/distributed,2.2139901403573043e-09,3.676208286461874e-15,0,0,0,1.4307397858423647e-14,67,46,85,152.36441600000012,True,completed,746,942,256,0.2999999999999999,0.2999999999999999,0.028087241910679444,0.006066844252706759,2.525469168900804,279,0,8.65107597651215,"[0.18251648410168134, 0.22524411478037126, 0.2706385482576287, 0.32160085286031964]",211 +S2_R_b2D3_s1,S2,reconnaissance,R_b2D3,1,ok,"branching control: b=2, D=3 (32 leaf cells, coarse)",reconnaissance,study/runs/S2_R_b2D3_s1,1831abc9,2,2,3,2,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.045044009039076745,0.045044009039076745,0.00030383068836823735,0.00030383068836823735,0.015191534418411867,0.0067451964167900445,0.0067451964167900445,0.0196510161454831,True,1.8188715095827377e-06,1.8188715095827377e-06,0.045471787739568455,1.8188715095827377e-06,9,0,0.08411214953271028,9,8,2,0,0.0,0.41137625401466416,0.4366293441578959,0.5909090909090908,0.4090909090909091,0.2171263567142901,0.4105306544847118,7,0.7777777777777778,0.18421052631578946,1.4444444444444444,2,True,intermediate,few-failures,intermediate/few-failures,8.701873953174382e-12,2.092855349163786e-17,0,0,0,2.328457350592665e-16,36,10,37,1.747624999999971,True,completed,97,107,32,0.19999999999999993,0.19999999999999993,0.0415826166821991,0.008981845203355003,2.2061855670103094,38,0,9.37646758736014,"[0.4053245367728967, 0.2585268081625524, 0.15085633204882162, 0.18529232301572932]",13 +S2_R_b2D3_s2,S2,reconnaissance,R_b2D3,2,ok,"branching control: b=2, D=3 (32 leaf cells, coarse)",reconnaissance,study/runs/S2_R_b2D3_s2,a5e972cc,2,2,3,2,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05332128314172614,0.05332128314172614,0.00043398997199689846,0.00043398997199689846,0.02169949859984492,0.008139150943599167,0.008139150943599167,0.011484068555466263,True,2.217919724460232e-06,2.217919724460232e-06,0.055447993111505764,2.217919724460232e-06,4,0,0.036036036036036036,4,3,2,0,0.0,0.9064746454202904,0.20368851696136608,0.5555555555555556,0.4444444444444444,0.17058542024571013,0.46279286555806154,2,0.5,0.05,1.25,1,True,abrupt-brittle,few-failures,abrupt-brittle/few-failures,1.713550418892974e-10,1.0718818307099641e-16,0,0,0,4.200946642496198e-15,18,5,19,1.3869579999998223,True,completed,100,111,32,0.2000000000000001,0.2000000000000001,0.0420779416640826,0.00908883539944184,2.22,40,0,9.496048722945615,"[0.4203314803345926, 0.242136895140459, 0.16076219182101037, 0.1767694327039374]",17 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(hexagonal-like),reconnaissance,study/runs/S2_R_stag_s1,c8db6275,2,2,3,4,staggered,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.02485070876103002,0.02485070876103002,0.00013386270127007117,0.00013386270127007117,0.0066931350635035585,0.004821150668841674,0.006148121628938085,0.02079770495954129,True,8.904685182809702e-07,8.904685182809702e-07,0.02226171295702426,8.904685182809702e-07,34,0,0.035789473684210524,34,21,5,4,0.11764705882352941,0.4255483175703282,0.4888168370518644,0.5540123456790124,0.44598765432098764,0.14142041768536232,0.45159207029926607,18,0.5294117647058824,0.06498194945848375,2.4705882352941178,3,True,intermediate,distributed,intermediate/distributed,8.17227214095967e-10,7.77544045215829e-16,0,0,0,4.985590555595363e-13,63,35,76,102.20358299999998,True,completed,753,950,256,0.19999999999999993,0.19999999999999993,0.018466828671963025,0.0039888349931440125,2.5232403718459495,277,0,12.999213945270705,"[0.18894322405285352, 0.22318268870851746, 0.2662566202152634, 0.32161746702336474]",149 +S2_R_red1_s2,S2,reconnaissance,R_red1,2,ok,redundancy sweep (braces) r=1,reconnaissance,study/runs/S2_R_red1_s2,c2a01d89,2,2,3,4,grid,0.35,0,2,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04695531376066951,0.04695531376066951,0.00030745860120704203,0.00030745860120704203,0.015372930060352102,0.005782740263375097,0.007021537115036283,0.03064759079937558,True,2.0878700790184284e-06,2.0878700790184284e-06,0.05219675197546073,2.0878700790184284e-06,67,0,0.04890510948905109,67,27,10,4,0.05970149253731343,0.3031263123159555,0.45404041219341307,0.7289251207729468,0.27107487922705314,0.11044845910775938,0.30711808928360057,14,0.208955223880597,0.04964539007092199,2.1940298507462686,1,False,intermediate,localized,intermediate/localized,1.5459862055154575e-10,5.158787483779258e-16,0,0,0,7.60673181756821e-14,85,68,125,439.49137500000006,True,completed,754,1370,256,0.1999999999999999,0.1999999999999999,0.011030558792052968,0.002382600699083441,3.6339522546419096,282,426,25.493586370066957,"[0.11018816326605291, 0.1318234453692664, 0.15879179562859125, 0.5991965957360906]",535 +S2_R_rho0.3_s2,S2,reconnaissance,R_rho0.3,2,ok,density control: rho=0.3,reconnaissance,study/runs/S2_R_rho0.3_s2,75a57cd9,2,2,3,4,grid,0.35,0,2,0.6,0.3,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09162791478777357,0.09162791478777357,0.00041666362174063706,0.00041666362174063706,0.020833181087031853,0.0035656994836930477,0.006057070988911352,0.03789040117175617,True,2.15053049131398e-06,2.15053049131398e-06,0.03584217485523305,2.15053049131398e-06,48,0,0.05052631578947368,48,26,10,9,0.1875,0.5726589923311887,0.29944039094449665,0.49650349650349646,0.5034965034965035,0.14980143978248614,0.5986243677061519,30,0.625,0.10638297872340426,2.5416666666666665,3,True,intermediate,distributed,intermediate/distributed,7.03744957635982e-10,5.8352025137622735e-15,0,0,0,2.4616976795826574e-14,90,49,112,156.955375,True,completed,753,950,256,0.2999999999999996,0.2999999999999996,0.027972374213885855,0.006042032830199343,2.5232403718459495,282,0,8.630079075841172,"[0.18628397677909073, 0.22286055877722052, 0.2684532194094559, 0.3224022450342332]",209 +S2_R_stag_s2,S2,reconnaissance,R_stag,2,ok,design language: staggered (hexagonal-like),reconnaissance,study/runs/S2_R_stag_s2,de3fb7e9,2,2,3,4,staggered,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.011931882591821895,0.011931882591821895,6.324447610113275e-05,6.324447610113275e-05,0.0031622238050566377,0.005035425577154377,0.008672959720815533,0.03489756631792283,True,7.887754335544605e-07,7.887754335544605e-07,0.01971938583886154,7.887754335544605e-07,35,0,0.03676470588235294,35,23,6,8,0.22857142857142856,0.2897235215112986,0.544503927360822,0.557442196531792,0.4425578034682081,0.16407572101181456,0.5421467559700566,24,0.6857142857142857,0.08633093525179857,2.6,2,True,intermediate,distributed,intermediate/distributed,1.0704221510612349e-09,7.447489949099531e-16,0,0,0,2.3759112113254556e-13,81,36,93,121.95570900000007,True,completed,757,952,256,0.19999999999999968,0.19999999999999968,0.018610687426332755,0.004019908484087875,2.5151915455746368,278,0,12.755578482511646,"[0.18334090994814442, 0.2307852567462397, 0.2674093715486275, 0.3184644617569886]",189 +S2_R_red1_s1,S2,reconnaissance,R_red1,1,ok,redundancy sweep (braces) r=1,reconnaissance,study/runs/S2_R_red1_s1,f880260d,2,2,3,4,grid,0.35,0,1,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0476697734882295,0.0476697734882295,0.00031906245927456223,0.00031906245927456223,0.01595312296372811,0.005809898553901824,0.008339946346485773,0.020222952060765267,True,2.5715002164965585e-06,2.5715002164965585e-06,0.06428750541241397,2.5715002164965585e-06,65,0,0.04821958456973294,65,30,8,10,0.15384615384615385,0.242121006292059,0.4027082601464753,0.7362012987012987,0.2637987012987013,0.20772465366397053,0.6354505496497522,21,0.3230769230769231,0.07526881720430108,2.276923076923077,1,False,progressive,localized,progressive/localized,2.14168893674845e-11,2.8194237002220256e-16,0,0,0,7.9054205804421e-15,81,66,116,447.18174999999997,True,completed,748,1348,256,0.19999999999999996,0.19999999999999996,0.011215740997759816,0.00242260005551612,3.6042780748663104,279,426,25.82724704545297,"[0.10932317349008887, 0.13491604092065235, 0.1621062618529918, 0.5936545237362678]",538 +S2_R_frame_s1,S2,reconnaissance,R_frame,1,ok,frame control: add straight side walls (level 0) as in the preliminary family,reconnaissance,study/runs/S2_R_frame_s1,d552ec65,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,True,sides,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06050198449207982,0.06050198449207982,0.00036630734422292085,0.00036630734422292085,0.01831536721114604,0.004072894753534602,0.009991596350286677,0.030233603603954183,True,3.04225599237235e-06,3.04225599237235e-06,0.07605639980930881,3.04225599237235e-06,58,0,0.05788423153692615,58,42,5,22,0.3793103448275862,0.571986872620925,0.27722125689033295,0.44082446808510634,0.5591755319148937,0.17545307565446383,0.505979999484342,37,0.6379310344827587,0.12052117263843648,2.396551724137931,1,False,intermediate,distributed,intermediate/distributed,2.6847050933436647e-10,1.0362719857950014e-15,0,0,0,1.1888646760312435e-13,115,59,131,222.41916700000002,True,completed,778,1002,256,0.19999999999999982,0.19999999999999982,0.01577161829605057,0.003406669551946923,2.575835475578406,307,0,15.406467446924939,"[0.31144685162903013, 0.1897194576657821, 0.22795445132476494, 0.270879239380423]",300 +S2_R_frame_s2,S2,reconnaissance,R_frame,2,ok,frame control: add straight side walls (level 0) as in the preliminary family,reconnaissance,study/runs/S2_R_frame_s2,e2e0e6d3,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,True,sides,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06698195384705827,0.06698195384705827,0.00046254306314659564,0.00046254306314659564,0.023127153157329782,0.003972370817801661,0.013670055100018463,0.06038318270007374,True,4.236094878026128e-06,4.236094878026128e-06,0.10590237195065322,4.236094878026128e-06,66,0,0.06573705179282868,66,47,4,37,0.5606060606060606,0.9496764676099874,0.09083975868196933,0.44438775510204087,0.5556122448979591,0.16145672356261187,0.6149827588377407,39,0.5909090909090909,0.1270358306188925,2.393939393939394,2,False,abrupt-brittle,distributed,abrupt-brittle/distributed,5.3892824515766514e-11,5.40830785325443e-16,0,0,0,7.43836635985414e-14,155,67,174,221.2556669999999,True,completed,781,1004,256,0.19999999999999996,0.19999999999999996,0.015717211084206643,0.0033949175941886344,2.5710627400768247,307,0,15.359202109698058,"[0.31417976036336165, 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cells),reconnaissance,study/runs/S2_R_H2_s2,0174602e,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,2,clamped,0.001,0.25,True,1,0.01419348847592658,0.02838697695185316,0.00012229449831949234,0.00012229449831949234,0.006114724915974617,0.007695277590563886,0.008981884084175166,0.0455797857162288,True,1.2981402119595377e-06,6.490701059797689e-07,0.016226752649494205,1.2981402119595377e-06,32,0,0.03400637619553666,32,21,4,2,0.0625,0.4142758321755858,0.5633912307042693,0.6819875776397515,0.31801242236024846,0.19220352669911794,0.46843715799041896,25,0.78125,0.09025270758122744,2.5625,3,True,intermediate,localized,intermediate/localized,4.123306484464747e-09,7.959707364094692e-15,0,0,0,3.91987736282282e-13,88,33,99,106.98424999999997,True,completed,749,941,256,0.20000000000000018,0.20000000000000018,0.02545988791097719,0.005499335788771072,2.512683578104139,277,0,13.716441676374135,"[0.1902376363798962, 0.22421193720102733, 0.2692485370430977, 0.3163018893759782]",161 +S2_R_notch_s1,S2,reconnaissance,R_notch,1,ok,edge notch of radius 0.12 W at mid-height,reconnaissance,study/runs/S2_R_notch_s1,f85a6a75,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.12,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.03487703263354533,0.03487703263354533,0.0001320097643210978,0.0001320097643210978,0.00660048821605489,0.003785005614099462,0.003785005614099462,0.017878098251943506,True,8.014662750344465e-07,8.014662750344465e-07,0.02068239913771408,8.014662750344465e-07,40,0,0.04333694474539545,40,24,4,0,0.0,0.2607391421264121,0.6882852625022595,0.4252873563218391,0.5747126436781609,0.21130215134807814,0.492354941970708,31,0.775,0.1111111111111111,2.375,3,False,intermediate,distributed,intermediate/distributed,4.07448439391927e-10,9.621282572938226e-16,0,0,0,1.9340430680115e-13,66,41,82,149.0513330000001,True,completed,746,923,256,0.19999999999999993,0.1937556348511289,0.018724827940452965,0.00404456283513784,2.521857923497268,279,0,12.976613964768223,"[0.18251648410168128, 0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",203 +S2_R_H2_s1,S2,reconnaissance,R_H2,1,ok,aspect ratio control: H = 2W (512 leaf cells),reconnaissance,study/runs/S2_R_H2_s1,09d59451,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,2,clamped,0.001,0.25,True,1,0.01732861242207559,0.03465722484415118,0.00013029806630624228,0.00013029806630624228,0.006514903315312114,0.006502236744508316,0.00904053485851339,0.07157452395553801,True,2.221090725413907e-06,1.1105453627069534e-06,0.027763634067673796,2.221090725413907e-06,58,0,0.06016597510373444,58,38,4,3,0.05172413793103448,0.29875691332350035,0.6971306364927459,0.2830349531116795,0.7169650468883205,0.23906348365214797,0.5138668241278028,44,0.7586206896551724,0.15331010452961671,2.5344827586206895,3,True,intermediate,distributed,intermediate/distributed,1.344468162826539e-09,2.695457713636615e-15,0,0,0,3.199602045134488e-13,148,59,168,210.24370799999997,True,completed,762,964,256,0.20000000000000026,0.20000000000000026,0.02583544408399373,0.005580455922142645,2.5301837270341205,287,0,13.141927878623797,"[0.19299297667450965, 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mid-height,reconnaissance,study/runs/S2_R_notch_s2,0d5f449f,2,2,3,4,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.12,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.045575260725345346,0.045575260725345346,0.00019761383156440376,0.00019761383156440376,0.009880691578220187,0.003937581655665545,0.005298430111868739,0.01897984603528325,True,1.0920422426916939e-06,1.0920422426916939e-06,0.027835927494259824,1.0920422426916939e-06,46,0,0.049145299145299144,46,28,4,4,0.08695652173913043,0.3141575284355916,0.4595157001739558,0.3877314814814815,0.6122685185185185,0.17439608611210697,0.6102889745637359,26,0.5652173913043478,0.09219858156028368,2.5217391304347827,2,False,intermediate,distributed,intermediate/distributed,5.034421561912741e-10,1.0545595410796143e-15,0,0,0,8.764745473931101e-14,75,47,93,159.59199999999987,True,completed,753,936,256,0.19999999999999993,0.19615697068417945,0.018648249475923903,0.004028021886799562,2.519515477792732,282,0,12.945118613761757,"[0.18628397677909056, 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fine)",reconnaissance,study/runs/S2_R_b9D3_s2,4883c3a8,2,2,3,9,grid,0.35,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03511173604067685,0.03511173604067685,0.00014127278334940342,0.00014127278334940342,0.007063639167470171,0.0032063892276624696,0.00414482731324375,0.02704722825095408,True,6.068857831538542e-07,6.068857831538542e-07,0.015172144578846379,6.068857831538542e-07,246,0,0.0226749009125265,246,76,30,7,0.028455284552845527,0.23666955982391166,0.5061020369958851,0.5028098195800059,0.4971901804199941,0.2320680798796155,0.4305907708056383,149,0.6056910569105691,0.055308092056421676,2.7642276422764227,3,True,progressive,distributed,progressive/distributed,2.1292972675088787e-09,5.601331522988085e-15,0,0,0,1.0247957009132985e-12,180,247,350,78870.62762500001,True,completed,8128,10849,2916,0.19999999999999968,0.19999999999999968,0.0065084351665564595,0.001405821995976195,2.6695374015748032,2694,0,10.127318403807207,"[0.06501884048700998, 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progressive?,H1,study/runs/S3_E7_ord_cv0.1_s2,2cf0cf74,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.1,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0012555875809685244,0.0012555875809685244,0.06277937904842622,0.012555875806442532,0.012555875806442532,0.025335206029350896,True,8.384542658929177e-06,8.384542658929177e-06,0.20961356647322887,8.384542658929177e-06,36,0,0.04736842105263158,36,6,28,0,0.0,0.7870410901195742,0.059877063541248374,0.7545454545454545,0.24545454545454545,0.09918068457556206,0.4143663194444444,31,0.8611111111111112,0.11071428571428571,2.4166666666666665,3,True,abrupt-brittle,localized,abrupt-brittle/localized,3.6512137398395785e-12,3.934142982551129e-17,0,0,0,1.1516639596812848e-14,38,37,68,130.64212500000002,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 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delta=0.15,H1,study/runs/S3_E1_dis0.15_s3_s3,3fb9276a,2,2,3,4,grid,0.15,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06944532661588425,0.06944532661588425,0.00024199865829405685,0.00024199865829405685,0.012099932914702842,0.0033178266508055035,0.0038481386619993035,0.02131041757776173,True,1.6386573644146053e-06,1.6386573644146053e-06,0.040966434110365144,1.6386573644146053e-06,48,0,0.052805280528052806,48,31,4,2,0.041666666666666664,0.3201383250206348,0.6923672262402571,0.3739130434782608,0.6260869565217392,0.20842039152034517,0.5450488933503562,25,0.5208333333333334,0.08928571428571429,2.4791666666666665,3,False,intermediate,distributed,intermediate/distributed,1.6908254037031722e-10,9.925145579587108e-16,0,0,0,9.485237682783685e-14,84,49,101,186.57208399999996,True,completed,714,909,256,0.19999999999999996,0.19999999999999996,0.018708055402146075,0.004040939966863551,2.546218487394958,280,0,13.482992709665725,"[0.18499401013680897, 0.22423699197749403, 0.26822518066195883, 0.3225438172237383]",238 +S3_E7_ord_cv0.1_s3,S3,hypothesis-tests,E7_ord_cv0.1,3,ok,ordered geometry with strength disorder CV=0.1: can statistics alone make failure progressive?,H1,study/runs/S3_E7_ord_cv0.1_s3,c5e9f7d0,2,2,3,4,grid,0.0,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.1,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0013052814091335826,0.0013052814091335826,0.06526407045667913,0.01305281408796481,0.01305281408796481,0.018393492057429513,True,8.623135170168687e-06,8.623135170168687e-06,0.2155783792542166,8.623135170168687e-06,34,0,0.04473684210526316,34,2,33,0,0.0,0.9875747847040068,0.012099704476505857,0.7419642857142856,0.2580357142857143,0.0640807775481323,0.5254136029411764,29,0.8529411764705882,0.10357142857142858,2.3529411764705883,3,True,abrupt-brittle,localized,abrupt-brittle/localized,2.3974203027975974e-12,2.958737244078794e-17,0,0,0,1.9645591320070438e-16,23,35,55,115.07166700000005,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",167 +S3_E7_ord_cv0.2_s1,S3,hypothesis-tests,E7_ord_cv0.2,1,ok,ordered geometry with strength disorder CV=0.2: can statistics alone make failure progressive?,H1,study/runs/S3_E7_ord_cv0.2_s1,41d6affd,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.2,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0008931991614893525,0.0008931991614893525,0.044659958074467626,0.008931991612586777,0.008931991612586777,0.01264991444951499,True,5.069210634769659e-06,5.069210634769659e-06,0.12673026586924113,5.069210634769659e-06,39,0,0.05131578947368421,39,6,14,0,0.0,0.37357845277677754,0.21308779673987996,0.7001182965299684,0.29988170347003157,0.09008311674801057,0.4512820512820514,28,0.717948717948718,0.1,2.3333333333333335,3,True,intermediate,localized,intermediate/localized,6.58693570624001e-12,1.9548253967702636e-17,0,0,0,6.015371681737269e-15,25,40,58,135.67008300000003,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",186 +S3_E1_dis0.35_s3_s3,S3,hypothesis-tests,E1_dis0.35_s3,3,ok,third seed for delta=0.35,H1,study/runs/S3_E1_dis0.35_s3_s3,e8e9f0fb,2,2,3,4,grid,0.35,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03553704822361948,0.03553704822361948,0.00014393926359677266,0.00014393926359677266,0.0071969631798386325,0.0032557994863044747,0.004559290847304084,0.02303255874439029,True,9.393173546849099e-07,9.393173546849099e-07,0.02348293386712273,9.393173546849099e-07,39,0,0.040880503144654086,39,29,3,3,0.07692307692307693,0.2590329308487851,0.6229764947055321,0.5451555023923444,0.4548444976076555,0.14578762275804155,0.4624852087777296,24,0.6153846153846154,0.08421052631578947,2.4871794871794872,3,False,intermediate,distributed,intermediate/distributed,3.8755559597366094e-10,5.677896842334763e-16,0,0,0,1.3650297394284859e-13,82,40,92,185.94099999999997,True,completed,757,954,256,0.20000000000000015,0.20000000000000015,0.01863751534628866,0.00402570331479835,2.5204755614266845,285,0,13.06709243047595,"[0.18292962299726434, 0.22466041670068604, 0.2705210004717499, 0.32188895983030114]",265 +S3_E7_ord_cv0.4_s2,S3,hypothesis-tests,E7_ord_cv0.4,2,ok,ordered geometry with strength disorder CV=0.4: can statistics alone make failure progressive?,H1,study/runs/S3_E7_ord_cv0.4_s2,179db7a4,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.4,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0006243562867728402,0.0006243562867728402,0.03121781433864201,0.005938235487987156,0.006435237485586661,0.01709166432363755,True,2.6924255853386385e-06,2.6924255853386385e-06,0.06731063963346579,2.6924255853386385e-06,38,0,0.05,38,15,8,1,0.02631578947368421,0.40341478043963735,0.23434999175391483,0.6632462686567164,0.33675373134328357,0.11423908802656561,0.50390625,19,0.5,0.06785714285714285,2.3421052631578947,3,True,intermediate,localized,intermediate/localized,1.618966530492009e-11,2.814418043240561e-17,0,0,0,2.1235396161366574e-14,48,39,71,107.33283300000005,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",153 +S3_E7_ord_cv0.2_s2,S3,hypothesis-tests,E7_ord_cv0.2,2,ok,ordered geometry with strength disorder CV=0.2: can statistics alone make failure progressive?,H1,study/runs/S3_E7_ord_cv0.2_s2,d8fb539e,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.2,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0009792384155874138,0.0009792384155874138,0.048961920779370685,0.009792384153345188,0.009792384153345188,0.024348723713882452,True,5.084449753664722e-06,5.084449753664722e-06,0.12711124384161773,5.084449753664722e-06,39,0,0.05131578947368421,39,10,25,0,0.0,0.9570042107340745,0.05701902784725784,0.6385456273764258,0.36145437262357416,0.12693043697094572,0.4347355769230768,32,0.8205128205128205,0.11428571428571428,2.358974358974359,3,True,abrupt-brittle,localized,abrupt-brittle/localized,3.0509706986217453e-12,4.3702375786308396e-17,0,0,0,9.6623849818438e-15,45,40,74,128.28558299999997,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",174 +S3_E7_ord_cv0.2_s3,S3,hypothesis-tests,E7_ord_cv0.2,3,ok,ordered geometry with strength disorder CV=0.2: can statistics alone make failure progressive?,H1,study/runs/S3_E7_ord_cv0.2_s3,df9b0d62,2,2,3,4,grid,0.0,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.2,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0010576839503484178,0.0010576839503484178,0.05288419751742089,0.010576839500752626,0.010576839500752626,0.018782864321363082,True,5.800559308170503e-06,5.800559308170503e-06,0.1450139827042622,5.800559308170503e-06,39,0,0.05131578947368421,39,5,34,0,0.0,0.9748047845340234,0.03570045654049173,0.7195796460176991,0.28042035398230086,0.0993680045265814,0.5009615384615385,33,0.8461538461538461,0.11785714285714285,2.41025641025641,3,True,abrupt-brittle,localized,abrupt-brittle/localized,2.5123222136763736e-12,3.046295017756668e-17,0,0,0,1.2558243023437873e-14,29,40,63,140.874417,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",186 +S3_E7_ord_cv0.4_s1,S3,hypothesis-tests,E7_ord_cv0.4,1,ok,ordered geometry with strength disorder CV=0.4: can statistics alone make failure progressive?,H1,study/runs/S3_E7_ord_cv0.4_s1,54e554d1,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.4,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0004965483368821926,0.0004965483368821926,0.024827416844109627,0.004965483367539541,0.004965483367539541,0.01550251177892596,True,2.515164689036599e-06,2.515164689036599e-06,0.0628791172259148,2.515164689036599e-06,47,0,0.06184210526315789,47,22,6,0,0.0,0.37657656944473444,0.5098526711361469,0.6504746835443038,0.3495253164556962,0.09923180278871739,0.4366356382978724,27,0.574468085106383,0.09642857142857143,2.382978723404255,3,True,intermediate,localized,intermediate/localized,4.6084514989614395e-12,2.163968121224206e-17,0,0,0,4.209629646452422e-15,60,48,85,150.87225,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",198 +S3_E2_D1_rt0.5_s2,S3,hypothesis-tests,E2_D1_rt0.5,2,ok,"(D,r_t) collapse: D=1 r_t=0.5",H2,study/runs/S3_E2_D1_rt0.5_s2,25893f24,2,2,1,64,grid,0.35,0,2,0.5,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04193623781302973,0.04193623781302973,0.0002010324043595077,0.0002010324043595077,0.010051620217975385,0.004793763457175134,0.004793763457175134,0.01512798002121419,True,9.61779427250005e-07,9.61779427250005e-07,0.024044485681250123,9.61779427250005e-07,39,0,0.05327868852459016,39,27,4,0,0.0,0.22619354811467418,0.49900061988113054,0.4095496894409938,0.5904503105590062,0.235107349866236,0.4333819677674163,9,0.23076923076923078,0.14754098360655737,0.9743589743589743,0,False,progressive,distributed,progressive/distributed,3.193311913105242e-10,2.213887880316117e-16,0,0,0,1.2770056612985523e-14,70,40,82,72.44020799999998,True,completed,534,732,256,0.2,0.2,0.012613688210645391,0.006306844105322696,2.741573033707865,61,0,7.227903783799697,"[0.12600260441411432, 0.8739973955858861]",126 +S3_E2_D1_rt0.5_s1,S3,hypothesis-tests,E2_D1_rt0.5,1,ok,"(D,r_t) collapse: D=1 r_t=0.5",H2,study/runs/S3_E2_D1_rt0.5_s1,78d9e575,2,2,1,64,grid,0.35,0,1,0.5,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.038871965358071095,0.038871965358071095,0.00019721197430418,0.00019721197430418,0.009860598715209,0.00507337286621735,0.00507337286621735,0.016601358055792735,True,1.0413283073030518e-06,1.0413283073030518e-06,0.02603320768257629,1.0413283073030518e-06,31,0,0.04240766073871409,31,17,4,0,0.0,0.2730311790341917,0.5195896086224447,0.4279761904761905,0.5720238095238095,0.1719979435456684,0.501607732149724,5,0.16129032258064516,0.08771929824561403,0.967741935483871,1,False,intermediate,distributed,intermediate/distributed,4.926678853563733e-10,5.338431753644157e-16,0,0,0,4.290768593757347e-14,51,32,65,98.24129200000004,True,completed,532,731,256,0.20000000000000004,0.20000000000000004,0.01266267684083561,0.006331338420417805,2.7481203007518795,57,0,7.111147580572647,"[0.12345166785675575, 0.8765483321432451]",151 +S3_E2_D1_rt0.3_s1,S3,hypothesis-tests,E2_D1_rt0.3,1,ok,"(D,r_t) collapse: D=1 r_t=0.3",H2,study/runs/S3_E2_D1_rt0.3_s1,d12d1fc7,2,2,1,64,grid,0.35,0,1,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.036303971007690075,0.036303971007690075,0.00016240389505635454,0.00016240389505635454,0.008120194752817727,0.004453160355605999,0.005217395079731657,0.01523604112897544,True,9.071487791957998e-07,9.071487791957998e-07,0.022678719479894957,9.071487791957998e-07,31,0,0.04240766073871409,31,20,5,2,0.06451612903225806,0.23864717210980316,0.4746979287582218,0.5484022556390977,0.4515977443609023,0.19903271553451618,0.42811542070641895,1,0.03225806451612903,0.017543859649122806,0.967741935483871,1,False,progressive,distributed,progressive/distributed,3.107867923065671e-09,1.826297868034071e-15,0,0,0,2.451043905403994e-14,56,32,67,95.60312499999998,True,completed,532,731,256,0.20000000000000032,0.20000000000000032,0.01949962091811546,0.005849886275434638,2.7481203007518795,57,0,7.6964029333707975,"[0.19010678035727063, 0.8098932196427286]",142 +S3_E7_ord_cv0.4_s3,S3,hypothesis-tests,E7_ord_cv0.4,3,ok,ordered geometry with strength disorder CV=0.4: can statistics alone make failure progressive?,H1,study/runs/S3_E7_ord_cv0.4_s3,7d092e4e,2,2,3,4,grid,0.0,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.4,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0006359975970900902,0.0006359975970900902,0.031799879854504505,0.006264464124762427,0.007439824454860041,0.01910882400801055,True,3.697115188037133e-06,3.697115188037133e-06,0.09242787970092808,3.697115188037133e-06,58,0,0.07631578947368421,58,18,14,7,0.1206896551724138,0.3688532805997091,0.28041618093167764,0.6017992424242424,0.39820075757575757,0.1202927520825704,0.4433459051724138,36,0.6206896551724138,0.12857142857142856,2.206896551724138,2,False,intermediate,localized,intermediate/localized,1.7333899445869613e-11,3.312304339692171e-17,0,0,0,1.9359495282858228e-14,56,59,96,188.563042,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",250 +S3_E2_D1_rt0.3_s2,S3,hypothesis-tests,E2_D1_rt0.3,2,ok,"(D,r_t) collapse: D=1 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r_t=0.7",H2,study/runs/S3_E2_D2_rt0.7_s1,89860aec,2,2,2,8,grid,0.35,0,1,0.7,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.02924275875613204,0.02924275875613204,0.00014770389542433717,0.00014770389542433717,0.007385194771216858,0.004453937028618472,0.005857926891819283,0.027754545856427466,True,7.674975830796922e-07,7.674975830796922e-07,0.019187439576992323,7.674975830796922e-07,31,0,0.033879781420765025,31,21,6,2,0.06451612903225806,0.369953806057888,0.3795265561126764,0.5270669291338583,0.4729330708661417,0.19706020136862387,0.4944013254349983,18,0.5806451612903226,0.07725321888412018,1.6129032258064515,1,False,intermediate,distributed,intermediate/distributed,2.602257337462264e-10,7.628644670597679e-16,0,0,0,8.001313623623535e-14,70,32,80,109.81183299999998,True,completed,714,915,256,0.19999999999999982,0.19999999999999982,0.011494261805455581,0.005632188284673234,2.563025210084034,233,0,8.810002194656253,"[0.11204166061899357, 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contrast)",H2,study/runs/S3_E2_D3_rt0.2_s1,c94bf96b,2,2,3,4,grid,0.35,0,1,0.2,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03331980460538202,0.03331980460538202,0.00017499553427119177,0.00017499553427119177,0.008749776713559589,0.004069796295878307,0.010222041280014062,0.03159377801449045,True,1.1867498712550964e-06,1.1867498712550964e-06,0.029668746781377424,1.1867498712550964e-06,29,0,0.03078556263269639,29,26,3,9,0.3103448275862069,0.9509483664411406,0.0854365443842114,0.4094101123595506,0.5905898876404494,0.25824606552196366,0.5055487492345836,12,0.41379310344827586,0.043010752688172046,2.2413793103448274,1,False,abrupt-brittle,distributed,abrupt-brittle/distributed,5.197793325690513e-08,1.093933577075573e-13,0,0,0,1.56844752771936e-13,84,30,87,110.92616599999997,True,completed,746,942,256,0.1999999999999999,0.1999999999999999,0.06250360897968965,0.0005000288718375173,2.525469168900804,279,0,6.237910730905407,"[0.6092413233872026, 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r_t=0.4",H2,study/runs/S3_E2_D2_rt0.4_s2,d166eb9c,2,2,2,8,grid,0.35,0,2,0.4,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04196980152688389,0.04196980152688389,0.00020260298756497134,0.00020260298756497134,0.010130149378248566,0.004475135831452961,0.006387639269564637,0.018103993770640033,True,1.14383963039528e-06,1.14383963039528e-06,0.028595990759881975,1.14383963039528e-06,39,0,0.04225352112676056,39,22,6,8,0.20512820512820512,0.5848126926008324,0.31648942020973564,0.5270522388059702,0.47294776119402987,0.206378315929305,0.39610820639451805,20,0.5128205128205128,0.08547008547008547,1.7435897435897436,2,False,intermediate,distributed,intermediate/distributed,5.43417185645243e-10,1.9539041005877555e-15,0,0,0,3.813663701136305e-14,63,40,80,126.67537500000003,True,completed,722,923,256,0.20000000000000015,0.20000000000000015,0.023792296292118494,0.0038067674067389598,2.556786703601108,234,0,13.116604042788829,"[0.23766968453121542, 0.3726684062877799, 0.3896619091810047]",187 +S3_E2_D3_rt0.2_s2,S3,hypothesis-tests,E2_D3_rt0.2,2,ok,"(D,r_t) collapse: D=3 r_t=0.2 (extreme contrast)",H2,study/runs/S3_E2_D3_rt0.2_s2,60892081,2,2,3,4,grid,0.35,0,2,0.2,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06301569654481193,0.06301569654481193,0.0003803960047731958,0.0003803960047731958,0.01901980023865979,0.004351675059441403,0.006199487315582359,0.015700852445237994,True,2.066360706335674e-06,2.066360706335674e-06,0.05165901765839178,2.066360706335674e-06,29,0,0.030526315789473683,29,16,6,3,0.10344827586206896,0.9256364367393336,0.4201904344625525,0.5429347826086957,0.45706521739130435,0.21810307284200464,0.4206174672222676,7,0.2413793103448276,0.024822695035460994,2.206896551724138,2,False,abrupt-brittle,distributed,abrupt-brittle/distributed,1.0908995868582842e-08,3.982608877655826e-14,0,0,0,9.428052772739939e-15,48,30,61,113.61300000000006,True,completed,753,950,256,0.20000000000000023,0.20000000000000023,0.06167977272315166,0.0004934381817852134,2.5232403718459495,282,0,6.478204548464727,"[0.6161411216925979, 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r_t=0.4",H2,study/runs/S3_E2_D2_rt0.4_s1,aac191eb,2,2,2,8,grid,0.35,0,1,0.4,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.027140840061332654,0.027140840061332654,0.00012030577339306852,0.00012030577339306852,0.006015288669653426,0.004432647372785965,0.004432647372785965,0.05940024784551712,True,1.1238022603074538e-06,1.1238022603074538e-06,0.028095056507686313,1.1238022603074538e-06,50,0,0.0546448087431694,50,32,6,0,0.0,0.2589775894880292,0.7627371428244525,0.4648972602739726,0.5351027397260274,0.18582864397528923,0.5455063678772748,32,0.64,0.13733905579399142,1.78,1,False,intermediate,distributed,intermediate/distributed,4.306342207827697e-09,1.9119546309879698e-14,0,0,0,2.8251333501298827e-12,124,51,142,203.81037500000002,True,completed,714,915,256,0.2000000000000002,0.2000000000000002,0.023903866375277732,0.003824618620044438,2.563025210084034,233,0,12.973735704950341,"[0.23300573183651102, 0.3826978434052995, 0.3842964247581889]",276 +S3_E2_D6_rt0.5_s1,S3,hypothesis-tests,E2_D6_rt0.5,1,ok,"(D,r_t) collapse: D=6 r_t=0.5",H2,study/runs/S3_E2_D6_rt0.5_s1,1d6a1ddb,2,2,6,2,grid,0.35,0,1,0.5,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04629750820741481,0.04629750820741481,0.0002665271849886879,0.0002665271849886879,0.013326359249434394,0.002151788328230545,0.006646201428194531,0.022442064671821534,True,2.0915221484815777e-06,2.0915221484815777e-06,0.052288053712039616,2.0915221484815777e-06,51,0,0.045658012533572066,51,21,9,10,0.19607843137254902,0.5228386205965488,0.5492321349471581,0.3310185185185185,0.6689814814814815,0.22690284544955147,0.4307746339802033,37,0.7254901960784313,0.08240534521158129,4.019607843137255,5,True,intermediate,distributed,intermediate/distributed,2.920377719444845e-09,1.9661238623488806e-14,0,0,0,1.302023470035733e-13,65,52,95,310.638916,True,completed,920,1117,256,0.19999999999999934,0.19999999999999934,0.04307753283187349,0.0006730864504980233,2.4282608695652175,449,0,9.050496623532748,"[0.41986924442424683, 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r_t=0.3,H2,study/runs/S3_E2_D3_rt0.3_s3_s3,5eab4ed5,2,2,3,4,grid,0.35,0,3,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04035352650984795,0.04035352650984795,0.00018777390795191896,0.00018777390795191896,0.009388695397595948,0.0031532863639839818,0.004885266595009698,0.03116740847456369,True,1.0402260209283002e-06,1.0402260209283002e-06,0.026005650523207482,1.0402260209283002e-06,27,0,0.02830188679245283,27,18,4,1,0.037037037037037035,0.6667572631923846,0.5499130849103097,0.4232594936708861,0.5767405063291139,0.21889875005436202,0.49107855042520354,9,0.3333333333333333,0.031578947368421054,2.2962962962962963,2,False,abrupt-brittle,distributed,abrupt-brittle/distributed,3.400477387614805e-09,1.2848494797724617e-14,0,0,0,3.7416064531438813e-13,68,28,77,97.91154200000005,True,completed,757,954,256,0.20000000000000018,0.20000000000000018,0.04623245842000247,0.0012482763773400665,2.5204755614266845,285,0,8.491981294289065,"[0.45377755735513675, 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s_int=0.5,H3,study/runs/S3_E3_ord_sint0.5_s3,a6db9332,2,2,3,4,grid,0.0,0,3,0.6,0.2,0.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0009041692166681451,0.0009041692166681451,0.04520846083340726,0.009041692164346355,0.009041692164346355,0.018747921609215668,True,6.741882419370871e-06,6.741882419370871e-06,0.16854706048427134,6.741882419370871e-06,47,0,0.06184210526315789,47,12,27,0,0.0,0.783476951972209,0.3936990284714554,0.5617063492063492,0.4382936507936508,0.1337602780882887,0.544747340425532,46,0.9787234042553191,0.16428571428571428,2.425531914893617,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,9.208718465632492e-12,2.234548750412739e-17,0,0,0,2.8896614587750223e-15,43,48,78,119.72299999999996,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 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s_int=1.5,H3,study/runs/S3_E3_ord_sint1.5_s3,18724a79,2,2,3,4,grid,0.0,0,3,0.6,0.2,0.0,1.0,segment,1.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0017349156992692175,0.0017349156992692175,0.08674578496346087,0.017349156988211625,0.017349156988211625,0.017349156988211625,True,1.5049662413967309e-05,1.5049662413967309e-05,0.3762415603491817,1.5049662413967309e-05,24,0,0.031578947368421054,24,1,24,0,0.0,0.9999999994524772,0.0,0.7391304347826086,0.2608695652173913,0.09765104152777052,0.34531249999999997,1,0.041666666666666664,0.0035714285714285713,2.2916666666666665,2,False,abrupt-brittle,localized,abrupt-brittle/localized,1.8608701117965087e-11,4.272560922380672e-17,0,0,0,5.628252142507761e-16,20,25,43,57.09195799999998,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",113 +S3_E3_ord_sint0.5_s2,S3,hypothesis-tests,E3_ord_sint0.5,2,ok,ordered hierarchy with s_int=0.5,H3,study/runs/S3_E3_ord_sint0.5_s2,6240ba6c,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0008867586020944851,0.0008867586020944851,0.044337930104724255,0.008867586018654734,0.008867586018654734,0.03675634833166247,True,6.176067382621009e-06,6.176067382621009e-06,0.1544016845655248,6.176067382621009e-06,56,0,0.07368421052631578,56,19,30,0,0.0,0.7884916160502631,0.36339682724463757,0.5682819383259912,0.43171806167400884,0.13502319597997495,0.4339285714285714,54,0.9642857142857143,0.19285714285714287,2.4107142857142856,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,4.733176118631187e-12,7.67391114803842e-17,0,0,0,1.7829190700365803e-14,75,57,112,154.72120800000005,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",224 +S3_E3_dis_sint1_s3_s3,S3,hypothesis-tests,E3_dis_sint1_s3,3,ok,third seed disordered s_int=1,H3,study/runs/S3_E3_dis_sint1_s3_s3,11f37762,2,2,3,4,grid,0.35,0,3,0.6,0.2,0.0,1.0,segment,1.0,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03553704822361948,0.03553704822361948,0.0001481665245199011,0.0001481665245199011,0.007408326225995055,0.0032557994863044747,0.004627317938986763,0.02321074429345393,True,9.737181721764517e-07,9.737181721764517e-07,0.024342954304411274,9.737181721764517e-07,37,0,0.03878406708595388,37,24,3,2,0.05405405405405406,0.22778511862293774,0.6256229714479292,0.5743159203980099,0.42568407960199006,0.13625479694346054,0.4879231628347727,16,0.43243243243243246,0.056140350877192984,2.5135135135135136,3,False,progressive,distributed,progressive/distributed,3.5464121177247413e-10,3.7656938567444263e-16,0,0,0,9.481859729941225e-14,72,38,85,128.46395900000016,True,completed,757,954,256,0.20000000000000015,0.20000000000000015,0.01863751534628866,0.00402570331479835,2.5204755614266845,285,0,13.06709243047595,"[0.18292962299726434, 0.22466041670068604, 0.2705210004717499, 0.32188895983030114]",179 +S3_E3_dis_sint1.5_s3_s3,S3,hypothesis-tests,E3_dis_sint1.5_s3,3,ok,third seed disordered s_int=1.5,H3,study/runs/S3_E3_dis_sint1.5_s3_s3,0729a532,2,2,3,4,grid,0.35,0,3,0.6,0.2,0.0,1.0,segment,1.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03553704822361948,0.03553704822361948,0.0001481665245199011,0.0001481665245199011,0.007408326225995055,0.0032557994863044747,0.004627317938986763,0.030401382769711424,True,1.099458802239222e-06,1.099458802239222e-06,0.02748647005598053,1.099458802239222e-06,36,0,0.03773584905660377,36,28,3,2,0.05555555555555555,0.2277851187588862,0.6684389490500828,0.5060975609756098,0.49390243902439024,0.16042106674447182,0.4595864586189605,1,0.027777777777777776,0.0035087719298245615,2.4722222222222223,3,False,progressive,distributed,progressive/distributed,1.9414906521382693e-10,7.224508814848404e-16,0,0,0,1.7526804561288632e-13,87,37,95,128.0340000000001,True,completed,757,954,256,0.20000000000000015,0.20000000000000015,0.01863751534628866,0.00402570331479835,2.5204755614266845,285,0,13.06709243047595,"[0.18292962299726434, 0.22466041670068604, 0.2705210004717499, 0.32188895983030114]",186 +S3_E3_dis_sint0.5_s3_s3,S3,hypothesis-tests,E3_dis_sint0.5_s3,3,ok,third seed disordered s_int=0.5,H3,study/runs/S3_E3_dis_sint0.5_s3_s3,5c54a3c2,2,2,3,4,grid,0.35,0,3,0.6,0.2,0.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03553704822361948,0.03553704822361948,0.00012649891062174666,0.00012649891062174666,0.006324945531087333,0.0027482004706747233,0.0054996018056830236,0.020263720597488984,True,5.668088707467331e-07,5.668088707467331e-07,0.014170221768668318,5.668088707467331e-07,44,0,0.04612159329140461,44,24,8,15,0.3409090909090909,0.4061066358693368,0.20803298677427748,0.7299107142857143,0.2700892857142857,0.11223120832829873,0.49080347376911265,40,0.9090909090909091,0.14035087719298245,2.590909090909091,3,True,intermediate,localized,intermediate/localized,1.4836828529509975e-10,2.1516624114772092e-16,0,0,0,4.4458073049592745e-14,69,45,89,145.629958,True,completed,757,954,256,0.20000000000000015,0.20000000000000015,0.01863751534628866,0.00402570331479835,2.5204755614266845,285,0,13.06709243047595,"[0.18292962299726434, 0.22466041670068604, 0.2705210004717499, 0.32188895983030114]",202 +S3_E4_L1_dis0.35_rt0.6_s3,S3,hypothesis-tests,E4_L1_dis0.35_rt0.6,3,ok,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L1_dis0.35_rt0.6_s3,4e0d0aa8,2,2,3,4,grid,0.35,1,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05082180779470383,0.05082180779470383,0.0002623506009989168,0.0002623506009989168,0.013117530049945841,0.0042472177730507425,0.012273883533249945,0.030260409909224007,True,2.2013856375330367e-06,2.2013856375330367e-06,0.05503464093832602,2.2013856375330367e-06,33,0,0.03492063492063492,33,22,3,25,0.7575757575757576,0.97455026557582,0.04006435695455161,0.7309782608695652,0.26902173913043476,0.08288594381313981,0.28724410086983165,14,0.42424242424242425,0.05,2.4242424242424243,3,False,abrupt-brittle,localized,abrupt-brittle/localized,1.5777384893230878e-09,5.915232896299994e-15,0,0,0,1.5775677939074924e-14,75,34,86,125.85129200000006,True,completed,750,945,256,0.19999999999999962,0.19999999999999962,0.018646124348255435,0.004027562859223174,2.52,280,0,12.909591875335474,"[0.18646124348255466, 0.22162332475386876, 0.26942421706419817, 0.3224912146993795]",190 +S3_E4_L1_dis0.35_rt1_s1,S3,hypothesis-tests,E4_L1_dis0.35_rt1,1,ok,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L1_dis0.35_rt1_s1,eb64fa65,2,2,3,4,grid,0.35,1,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03928320423328137,0.03928320423328137,0.00019638359302812022,0.00019638359302812022,0.00981917965140601,0.004999174503737138,0.004999174503737138,0.01359271424807959,True,1.0969247368605516e-06,1.0969247368605516e-06,0.027423118421513744,1.0969247368605516e-06,35,0,0.03684210526315789,35,21,5,0,0.0,0.44315471390398914,0.5524962569317693,0.6849279835390947,0.3150720164609053,0.10101415747441773,0.39241461912717024,17,0.4857142857142857,0.060498220640569395,1.6285714285714286,1,False,intermediate,localized,intermediate/localized,1.956079715060351e-10,1.166739693973556e-16,0,0,0,5.40532128735635e-15,56,36,70,130.94679199999996,True,completed,754,950,256,0.20000000000000032,0.20000000000000032,0.006681993635227929,0.006681993635227929,2.519893899204244,281,0,7.833777013424932,"[0.06681993635227917, 0.13148809351151214, 0.2665429292943879, 0.5351490408418206]",184 +S3_E4_L1_dis0.35_rt0.6_s1,S3,hypothesis-tests,E4_L1_dis0.35_rt0.6,1,ok,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L1_dis0.35_rt0.6_s1,5c14fd3f,2,2,3,4,grid,0.35,1,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05148671757106092,0.05148671757106092,0.00028280638805861533,0.00028280638805861533,0.014140319402930765,0.004779905645180441,0.013281701416387801,0.03038784482768486,True,2.4936110748099014e-06,2.4936110748099014e-06,0.062340276870247444,2.4936110748099014e-06,35,0,0.03684210526315789,35,18,4,27,0.7714285714285715,0.9678182153384074,0.031047275303052176,0.76148753894081,0.23851246105919002,0.08015952840080098,0.2389165853248262,20,0.5714285714285714,0.0711743772241993,2.4,3,False,abrupt-brittle,localized,abrupt-brittle/localized,1.1614635226056262e-09,1.8171914298394554e-15,0,0,0,4.585696985166297e-14,67,36,84,151.1410420000002,True,completed,754,950,256,0.2000000000000003,0.2000000000000003,0.018703424421868918,0.0040399396751236855,2.519893899204244,281,0,12.956938061679761,"[0.18703424421868892, 0.22082729379471905, 0.2685868454745377, 0.3235516165120544]",222 +S3_E4_L1_dis0.35_rt1_s3,S3,hypothesis-tests,E4_L1_dis0.35_rt1,3,ok,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L1_dis0.35_rt1_s3,2fd4f6fc,2,2,3,4,grid,0.35,1,3,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03995093963002916,0.03995093963002916,0.00019749848058256403,0.00019749848058256403,0.009874924029128202,0.0047482811564353005,0.005535550078788253,0.012698362641353314,True,9.99700021081586e-07,9.99700021081586e-07,0.024992500527039642,9.99700021081586e-07,36,0,0.0380952380952381,36,20,4,2,0.05555555555555555,0.31030072269526676,0.40082164439603124,0.5290697674418605,0.47093023255813954,0.20182659489142235,0.42946414247264253,15,0.4166666666666667,0.05357142857142857,1.9444444444444444,1,False,intermediate,distributed,intermediate/distributed,1.8795468036361657e-10,9.790874109806395e-17,0,0,0,7.837405818622921e-15,53,37,69,145.09691700000008,True,completed,750,945,256,0.20000000000000004,0.20000000000000004,0.006665879500422583,0.006665879500422583,2.52,280,0,7.800049905122681,"[0.06665879500422582, 0.13204838618653097, 0.26754880232340383, 0.5337440164858391]",199 +S3_E4_L1_dis0.35_rt1_s2,S3,hypothesis-tests,E4_L1_dis0.35_rt1,2,ok,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L1_dis0.35_rt1_s2,42611d11,2,2,3,4,grid,0.35,1,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04167293109480061,0.04167293109480061,0.0001872893742298099,0.0001872893742298099,0.009364468711490494,0.0040103262390227806,0.004722667395732471,0.017911509350196024,True,1.1036979655375176e-06,1.1036979655375176e-06,0.027592449138437954,1.1036979655375176e-06,38,0,0.03970741901776385,38,22,4,1,0.02631578947368421,0.3740073012436058,0.5846153553343473,0.5934684684684685,0.40653153153153154,0.12495618734031548,0.6816864039879932,19,0.5,0.06785714285714285,1.9473684210526316,1,False,intermediate,distributed,intermediate/distributed,9.425465436607476e-11,9.742041613205744e-17,0,0,0,9.017536899590953e-14,62,39,78,151.7980419999999,True,completed,762,957,256,0.1999999999999999,0.1999999999999999,0.006668368171804191,0.006668368171804191,2.5118110236220472,280,0,7.821925842570615,"[0.06668368171804194, 0.13300820324428544, 0.26640652541063686, 0.5339015896270352]",211 +S3_E3_dis_sint0.3_s3_s3,S3,hypothesis-tests,E3_dis_sint0.3_s3,3,ok,third seed disordered s_int=0.3,H3,study/runs/S3_E3_dis_sint0.3_s3_s3,140fdc79,2,2,3,4,grid,0.35,0,3,0.6,0.2,0.0,1.0,segment,0.3,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03553704822361948,0.03553704822361948,8.183509819907464e-05,8.183509819907464e-05,0.004091754909953732,0.001648920282404834,0.0032699943412368556,0.012410115695575177,True,3.4063117123027524e-07,3.4063117123027524e-07,0.008515779280756874,3.4063117123027524e-07,63,0,0.0660377358490566,63,31,11,15,0.23809523809523808,0.5959826881578065,0.5121219275390827,0.4885309278350516,0.5114690721649484,0.18632391011956476,0.5711342166983807,62,0.9841269841269841,0.21754385964912282,2.6031746031746033,3,True,intermediate,distributed,intermediate/distributed,1.6764281009246239e-10,1.3985229991738627e-16,0,0,0,1.589906433679266e-13,75,64,107,207.17150000000015,True,completed,757,954,256,0.20000000000000015,0.20000000000000015,0.01863751534628866,0.00402570331479835,2.5204755614266845,285,0,13.06709243047595,"[0.18292962299726434, 0.22466041670068604, 0.2705210004717499, 0.32188895983030114]",262 +S3_E4_L1_dis0.7_rt0.6_s2,S3,hypothesis-tests,E4_L1_dis0.7_rt0.6,2,ok,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L1_dis0.7_rt0.6_s2,6ad74260,2,2,3,4,grid,0.7,1,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03787960201590967,0.03787960201590967,0.00022214166874627103,0.00022214166874627103,0.011107083437313552,0.005694042163943394,0.0073666392934927,0.03180651639329117,True,1.542740310044321e-06,1.542740310044321e-06,0.03856850775110799,1.542740310044321e-06,39,0,0.04058272632674298,39,21,6,6,0.15384615384615385,0.7338080208535552,0.38623745624269845,0.6022489539748954,0.3977510460251046,0.11895164973708848,0.41763928207829903,25,0.6410256410256411,0.08992805755395683,2.5384615384615383,1,False,abrupt-brittle,localized,abrupt-brittle/localized,7.484415120117821e-10,3.027827877868428e-15,0,0,0,1.847534448249969e-13,74,40,92,179.93641599999978,True,completed,761,961,256,0.20000000000000018,0.20000000000000018,0.018239119159845104,0.003939649738526542,2.5256241787122207,278,0,13.216297303327709,"[0.18241038294311088, 0.2236052715541786, 0.271933327945899, 0.3220510175568109]",227 +S3_E4_L1_dis0.35_rt0.6_s2,S3,hypothesis-tests,E4_L1_dis0.35_rt0.6,2,ok,"level-selective disorder: levels >= 1 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L1_dis0.35_rt0.6_s2,3ccc098a,2,2,3,4,grid,0.35,1,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.055902949656789026,0.055902949656789026,0.00028216774105806566,0.00028216774105806566,0.014108387052903282,0.004855808408690024,0.005075999045303196,0.04950702689951595,True,2.918060504208253e-06,2.918060504208253e-06,0.07295151260520616,2.918060504208253e-06,64,0,0.06687565308254964,64,36,9,1,0.015625,0.8409825320811815,0.7533130460550488,0.420814479638009,0.579185520361991,0.19222419325508,0.5261937866195424,40,0.625,0.14285714285714285,2.53125,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,7.404444513048299e-10,4.100499099517498e-15,0,0,0,2.438289660778172e-14,122,65,150,235.99037499999986,True,completed,762,957,256,0.20000000000000046,0.20000000000000046,0.01864142658628795,0.004026548142638197,2.5118110236220472,280,0,12.953894870516969,"[0.18641426586287904, 0.223094699537104, 0.2681062473961211, 0.32238478720389413]",316 +S3_E4_L1_dis0.7_rt1_s1,S3,hypothesis-tests,E4_L1_dis0.7_rt1,1,ok,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L1_dis0.7_rt1_s1,ef6bff04,2,2,3,4,grid,0.7,1,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.020100856839444212,0.020100856839444212,0.0001375498119384157,0.0001375498119384157,0.0068774905969207845,0.00684298251746664,0.00684298251746664,0.016289691833291094,True,6.558888744898759e-07,6.558888744898759e-07,0.016397221862246916,6.558888744898759e-07,19,0,0.01993704092339979,19,11,5,0,0.0,0.41950953214965025,0.282461560956121,0.7406609195402298,0.2593390804597701,0.1471208474505799,0.6819730589724187,7,0.3684210526315789,0.02527075812274368,1.7894736842105263,0,False,intermediate,localized,intermediate/localized,2.523820541358882e-10,8.263916297164815e-17,0,0,0,2.0985697315856577e-14,39,20,47,77.0094160000001,True,completed,754,953,256,0.19999999999999976,0.19999999999999976,0.006517477964847756,0.006517477964847756,2.5278514588859418,277,0,8.032225331271196,"[0.06517671784388285, 0.13298346552278711, 0.2644671348603897, 0.5373726817729416]",143 +S3_E4_L1_dis0.7_rt0.6_s1,S3,hypothesis-tests,E4_L1_dis0.7_rt0.6,1,ok,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L1_dis0.7_rt0.6_s1,4e8ca9fb,2,2,3,4,grid,0.7,1,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.030650241145428404,0.030650241145428404,0.0002838808914256556,0.0002838808914256556,0.01419404457128278,0.005799208948687071,0.012898883776723127,0.029605570107595104,True,2.435807209905556e-06,2.435807209905556e-06,0.06089518024763888,2.435807209905556e-06,53,0,0.055613850996852045,53,41,5,27,0.5094339622641509,0.8704549939632309,0.14060514847852978,0.4969555873925502,0.5030444126074498,0.1734447823152773,0.3483153271092898,34,0.6415094339622641,0.12274368231046931,2.6226415094339623,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,2.947663702334793e-10,1.4983866665368561e-15,0,0,0,2.1212273932186815e-14,112,54,124,211.4881660000001,True,completed,754,953,256,0.20000000000000004,0.20000000000000004,0.018294805172556192,0.003951677917272137,2.5278514588859418,277,0,13.247499594144388,"[0.18295349231278213, 0.22397374622816033, 0.26725290117556605, 0.32581986028349263]",292 +S3_E4_L1_dis0.7_rt1_s2,S3,hypothesis-tests,E4_L1_dis0.7_rt1,2,ok,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L1_dis0.7_rt1_s2,95cc6130,2,2,3,4,grid,0.7,1,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.023590959966862335,0.023590959966862335,0.0001438659004354323,0.0001438659004354323,0.007193295021771615,0.005779623540273351,0.006907871305849044,0.022503602213721337,True,8.013736014363704e-07,8.013736014363704e-07,0.020034340035909263,8.013736014363704e-07,25,0,0.026014568158168574,25,18,6,1,0.04,0.6206220740639349,0.32231637062773116,0.5055379746835442,0.4944620253164557,0.1564240709154085,0.44284634739186357,10,0.4,0.03597122302158273,1.72,1,False,abrupt-brittle,distributed,abrupt-brittle/distributed,7.838994236210248e-11,1.6643270031932614e-16,0,0,0,9.380665139714867e-15,59,26,66,103.51175000000012,True,completed,761,961,256,0.19999999999999998,0.19999999999999998,0.006510638788097616,0.006510638788097616,2.5256241787122207,278,0,7.99730777731535,"[0.06511323842632563, 0.1330302870298718, 0.269637118557124, 0.5322193559866786]",162 +S3_E4_L1_dis0.7_rt1_s3,S3,hypothesis-tests,E4_L1_dis0.7_rt1,3,ok,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L1_dis0.7_rt1_s3,47599197,2,2,3,4,grid,0.7,1,3,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.021348511708137723,0.021348511708137723,0.00015811209162349142,0.00015811209162349142,0.00790560458117457,0.007406234860073439,0.007406234860073439,0.018111947687719652,True,8.31170619622863e-07,8.31170619622863e-07,0.020779265490571564,8.31170619622863e-07,29,0,0.03005181347150259,29,14,11,0,0.0,0.6675996272983187,0.295562633510581,0.7763297872340426,0.22367021276595744,0.06316221967768636,0.140692627304096,9,0.3103448275862069,0.031914893617021274,2.2758620689655173,3,False,abrupt-brittle,localized,abrupt-brittle/localized,5.738740228092796e-10,2.560167998805677e-16,0,0,0,1.6216179271711714e-13,47,30,62,136.368334,True,completed,764,965,256,0.2000000000000001,0.2000000000000001,0.006488072028573591,0.006488072028573591,2.526178010471204,282,0,8.14545616569452,"[0.06489119519125636, 0.13052844228607804, 0.2662530823907557, 0.5383272801319084]",190 +S3_E4_L1_dis0.7_rt0.6_s3,S3,hypothesis-tests,E4_L1_dis0.7_rt0.6,3,ok,"level-selective disorder: levels >= 1 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L1_dis0.7_rt0.6_s3,c80a36ae,2,2,3,4,grid,0.7,1,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0317347014495058,0.0317347014495058,0.0002744401185547593,0.0002744401185547593,0.013722005927737965,0.005892693043021149,0.013806717272545604,0.020383348393789334,True,2.4433525388438487e-06,2.4433525388438487e-06,0.06108381347109621,2.4433525388438487e-06,38,0,0.039378238341968914,38,19,9,30,0.7894736842105263,0.9726429185396877,0.018923589507312003,0.7107371794871795,0.28926282051282054,0.1266361568226809,0.2716502385059916,25,0.6578947368421053,0.08865248226950355,2.526315789473684,3,True,abrupt-brittle,localized,abrupt-brittle/localized,4.671278920317361e-10,2.6329974117598967e-15,0,0,0,4.090686308546452e-14,59,39,78,183.6389999999999,True,completed,764,965,256,0.2,0.2,0.018258871505881204,0.003943916245270339,2.526178010471204,282,0,13.399956546235524,"[0.18261819376266927, 0.22040156567943994, 0.26974624931454555, 0.32723399124334396]",249 +S3_E4_L2_dis0.35_rt1_s2,S3,hypothesis-tests,E4_L2_dis0.35_rt1,2,ok,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L2_dis0.35_rt1_s2,413ace5c,2,2,3,4,grid,0.35,2,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05048928430320293,0.05048928430320293,0.0002718821706279545,0.0002718821706279545,0.013594108531397725,0.005384948001940866,0.005384948001940866,0.010779361404856717,True,1.4383107876076383e-06,1.4383107876076383e-06,0.03595776969019096,1.4383107876076383e-06,26,0,0.027689030883919063,26,15,5,0,0.0,0.2672949497092043,0.49104485480444526,0.7359375,0.2640625,0.08848425493486378,0.6693355269345731,8,0.3076923076923077,0.02857142857142857,1.6538461538461537,1,False,intermediate,localized,intermediate/localized,1.130838468741166e-11,5.4156558439201344e-17,0,0,0,1.3250433409403532e-14,41,27,52,123.11420899999985,True,completed,744,939,256,0.19999999999999998,0.19999999999999998,0.006668083228545706,0.006668083228545706,2.524193548387097,280,0,7.765064748771497,"[0.06668083228545707, 0.1333616645709142, 0.2665297726097971, 0.533427730533832]",185 +S3_E4_L2_dis0.35_rt1_s1,S3,hypothesis-tests,E4_L2_dis0.35_rt1,1,ok,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L2_dis0.35_rt1_s1,6a7add54,2,2,3,4,grid,0.35,2,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.049747880468727634,0.049747880468727634,0.0002940532598011865,0.0002940532598011865,0.014702662990059324,0.005816261290379187,0.0065026185163781286,0.012313365954820278,True,1.4204730855960976e-06,1.4204730855960976e-06,0.035511827139902426,1.4204730855960976e-06,41,0,0.043897216274089934,41,16,7,3,0.07317073170731707,0.3488148378630028,0.27038668360646045,0.5746457489878543,0.42535425101214575,0.17028346633232772,0.5071162123694558,19,0.4634146341463415,0.06785714285714285,1.8780487804878048,2,False,intermediate,distributed,intermediate/distributed,9.714953275524956e-11,9.912561427371122e-17,0,0,0,1.6547419676341812e-14,45,42,70,166.847125,True,completed,739,934,256,0.20000000000000007,0.20000000000000007,0.006689844797749186,0.006689844797749186,2.527740189445196,280,0,7.817363059280735,"[0.06689844797749184, 0.13379689595498367, 0.2657705206992216, 0.5335341353683029]",220 +S3_E4_L2_dis0.35_rt0.6_s2,S3,hypothesis-tests,E4_L2_dis0.35_rt0.6,2,ok,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L2_dis0.35_rt0.6_s2,c71dd026,2,2,3,4,grid,0.35,2,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06574133746355701,0.06574133746355701,0.00041338400052396025,0.00041338400052396025,0.02066920002619801,0.0048524751195881425,0.00782538400305713,0.017712728987343204,True,3.952261093157375e-06,3.952261093157375e-06,0.09880652732893451,3.952261093157375e-06,50,0,0.05324813631522897,50,27,8,14,0.28,0.7413134166773844,0.5315696856335631,0.42974452554744524,0.5702554744525548,0.18298714611164327,0.5958192245305355,28,0.56,0.1,2.4,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,1.594286143592708e-10,1.337767665506465e-15,0,0,0,4.286320803657353e-16,72,51,95,209.54829100000006,True,completed,744,939,256,0.1999999999999997,0.1999999999999997,0.01863275211274507,0.004024674456352934,2.524193548387097,280,0,12.865164271391727,"[0.18632752112745096, 0.2235930253529413, 0.26811692128857845, 0.3219625322310289]",264 +S3_E4_L2_dis0.35_rt1_s3,S3,hypothesis-tests,E4_L2_dis0.35_rt1,3,ok,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L2_dis0.35_rt1_s3,72fe2e61,2,2,3,4,grid,0.35,2,3,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.047272165334003705,0.047272165334003705,0.0002762605155089893,0.0002762605155089893,0.013813025775449465,0.0056625230863208914,0.006073174393264535,0.011148327212386861,True,1.4899352609585736e-06,1.4899352609585736e-06,0.03724838152396442,1.4899352609585736e-06,35,0,0.03747323340471092,35,17,8,1,0.02857142857142857,0.3384799262331006,0.4177716273816449,0.6997549019607843,0.3002450980392157,0.08465309504941375,0.2322069820254214,16,0.45714285714285713,0.05714285714285714,2.0,1,False,intermediate,localized,intermediate/localized,2.4604093877882737e-11,1.188443082935121e-16,0,0,0,4.178498439129301e-14,46,36,64,136.10866699999997,True,completed,739,934,256,0.19999999999999957,0.19999999999999957,0.006684372223068427,0.006684372223068427,2.527740189445196,280,0,7.8566914501012866,"[0.06684372223068442, 0.1336874444613688, 0.2658826967586835, 0.5335861365492651]",195 +S3_E4_L2_dis0.35_rt0.6_s1,S3,hypothesis-tests,E4_L2_dis0.35_rt0.6,1,ok,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L2_dis0.35_rt0.6_s1,9412fb67,2,2,3,4,grid,0.35,2,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06289579711897657,0.06289579711897657,0.0003681068068080949,0.0003681068068080949,0.018405340340404742,0.005485310551427198,0.007704919882391011,0.024854938875147625,True,3.905966758240315e-06,3.905966758240315e-06,0.09764916895600805,3.905966758240315e-06,63,0,0.06745182012847965,63,32,13,13,0.20634920634920634,0.8220739475715934,0.5581909023539618,0.46653225806451615,0.5334677419354839,0.1706112835451527,0.3528659665376513,40,0.6349206349206349,0.14285714285714285,2.5396825396825395,2,False,abrupt-brittle,distributed,abrupt-brittle/distributed,1.3892082193393597e-10,1.4294876733162473e-15,0,0,0,1.236080104666488e-14,89,64,120,252.92275000000018,True,completed,739,934,256,0.19999999999999968,0.19999999999999968,0.018681637459644258,0.004035233691283159,2.527740189445196,280,0,12.96007854692947,"[0.18681637459644296, 0.2241796495157315, 0.2671826207478427, 0.3218213551399832]",312 +S3_E4_L2_dis0.7_rt0.6_s2,S3,hypothesis-tests,E4_L2_dis0.7_rt0.6,2,ok,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L2_dis0.7_rt0.6_s2,0965f2ec,2,2,3,4,grid,0.7,2,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.053022932569236125,0.053022932569236125,0.00038941651046797644,0.00038941651046797644,0.01947082552339882,0.00451797075576394,0.012182684043340528,0.03156239639051622,True,3.6246681186191e-06,3.6246681186191e-06,0.09061670296547758,3.6246681186191e-06,42,0,0.04439746300211417,42,21,10,20,0.47619047619047616,0.6538663594615884,0.17269581697651332,0.44318181818181823,0.5568181818181818,0.16402796846530923,0.5068944898569465,29,0.6904761904761905,0.10507246376811594,2.5,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,1.2704797562010156e-09,2.126187022519406e-15,0,0,0,2.3835936916854523e-14,74,43,95,185.97529200000008,True,completed,750,946,256,0.19999999999999984,0.19999999999999984,0.01829497167382628,0.0039517138815464755,2.522666666666667,276,0,13.29800231907125,"[0.18296391738933035, 0.21954521893225468, 0.2704229447772675, 0.3270679189011469]",245 +S3_E4_L2_dis0.35_rt0.6_s3,S3,hypothesis-tests,E4_L2_dis0.35_rt0.6,3,ok,"level-selective disorder: levels >= 2 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L2_dis0.35_rt0.6_s3,1fe7e4f8,2,2,3,4,grid,0.35,2,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06304519381260049,0.06304519381260049,0.00037301172443315986,0.00037301172443315986,0.018650586221657994,0.005776739071522157,0.010598444776092321,0.042328317527252024,True,3.1947507418990126e-06,3.1947507418990126e-06,0.07986876854747546,3.1947507418990126e-06,63,0,0.06745182012847965,63,37,7,22,0.3492063492063492,0.5706642848632076,0.17991352514804843,0.48427754677754675,0.5157224532224532,0.1802549168878005,0.4149314252392413,39,0.6190476190476191,0.1392857142857143,2.492063492063492,2,False,intermediate,distributed,intermediate/distributed,1.2221854671106676e-10,6.719853241595069e-16,0,0,0,5.2761410864689616e-14,117,64,143,286.63808300000005,True,completed,739,934,256,0.19999999999999962,0.19999999999999962,0.018669941094437273,0.00403270727639845,2.527740189445196,280,0,13.02277762674072,"[0.18669941094437312, 0.22403929313324766, 0.2673467430461217, 0.3219145528762589]",344 +S3_E4_L2_dis0.7_rt1_s1,S3,hypothesis-tests,E4_L2_dis0.7_rt1,1,ok,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L2_dis0.7_rt1_s1,42636c19,2,2,3,4,grid,0.7,2,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03208817504077094,0.03208817504077094,0.0002717491323567597,0.0002717491323567597,0.013587456617837985,0.00707805035309766,0.008874763366465054,0.025190651487528293,True,1.6932309876260912e-06,1.6932309876260912e-06,0.042330774690652224,1.6932309876260912e-06,38,0,0.04,38,19,9,2,0.05263157894736842,0.5445534603462702,0.2661245943883856,0.6239583333333334,0.37604166666666666,0.1333353718015062,0.46632085090970393,16,0.42105263157894735,0.05734767025089606,1.9473684210526316,2,False,intermediate,localized,intermediate/localized,1.5245113250110814e-10,1.2615303443270422e-16,0,0,0,3.051503909395861e-14,64,39,83,165.48679199999992,True,completed,754,950,256,0.20000000000000023,0.20000000000000023,0.0065598459625072466,0.0065598459625072466,2.519893899204244,279,0,7.914115663046827,"[0.06559845962507237, 0.13119691925014476, 0.26512472895290734, 0.5380798921718745]",225 +S3_E4_L2_dis0.7_rt1_s2,S3,hypothesis-tests,E4_L2_dis0.7_rt1,2,ok,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L2_dis0.7_rt1_s2,203aa224,2,2,3,4,grid,0.7,2,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.032920349327226456,0.032920349327226456,0.00023754976449448864,0.00023754976449448864,0.011877488224724432,0.005771151357289312,0.007961688560054303,0.017109754620155928,True,1.4136159698520714e-06,1.4136159698520714e-06,0.03534039924630182,1.4136159698520714e-06,26,0,0.02748414376321353,26,16,4,3,0.11538461538461539,0.3425424931497318,0.28508517747319245,0.5688775510204082,0.43112244897959184,0.15753478305873156,0.47528537163969303,11,0.4230769230769231,0.03985507246376811,1.9615384615384615,1,False,intermediate,distributed,intermediate/distributed,4.988131843502334e-11,1.3174616056314117e-16,0,0,0,2.995979690802936e-16,50,27,60,128.1346669999998,True,completed,750,946,256,0.19999999999999982,0.19999999999999982,0.006500832028136437,0.006500832028136437,2.522666666666667,276,0,8.083565324202864,"[0.06501336626060535, 0.13001993264456105, 0.2669182324297824, 0.5380484686650515]",183 +S3_E4_L2_dis0.7_rt1_s3,S3,hypothesis-tests,E4_L2_dis0.7_rt1,3,ok,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L2_dis0.7_rt1_s3,96a780cf,2,2,3,4,grid,0.7,2,3,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03192403287784532,0.03192403287784532,0.0002558279546397041,0.0002558279546397041,0.012791397731985206,0.007813149259624575,0.008800144128434457,0.014905553966394253,True,1.3935616563515664e-06,1.3935616563515664e-06,0.034839041408789226,1.3935616563515664e-06,28,0,0.029227557411273485,28,10,9,3,0.10714285714285714,0.5827873806173197,0.12974991256972412,0.65,0.35,0.1019641170501365,0.5587006071815946,9,0.32142857142857145,0.03225806451612903,1.6428571428571428,0,False,intermediate,localized,intermediate/localized,5.3938218323856276e-11,1.3770960339601651e-16,0,0,0,1.686697117359332e-14,35,29,53,129.8812499999999,True,completed,761,958,256,0.1999999999999996,0.1999999999999996,0.006551464276481091,0.006551464276481091,2.5177398160315376,279,0,7.919794392550929,"[0.06551512314725422, 0.1310292855296221, 0.26466509330390897, 0.5387904980192154]",187 +S3_E4_L2_dis0.7_rt0.6_s1,S3,hypothesis-tests,E4_L2_dis0.7_rt0.6,1,ok,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L2_dis0.7_rt0.6_s1,122cd1af,2,2,3,4,grid,0.7,2,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05029751536714506,0.05029751536714506,0.000540711848188063,0.000540711848188063,0.02703559240940315,0.006862513653079586,0.011764092387154338,0.033883784227611576,True,4.082406943114422e-06,4.082406943114422e-06,0.10206017357786062,4.082406943114422e-06,59,0,0.06210526315789474,59,29,17,10,0.1694915254237288,0.5300867501669464,0.17796162053833953,0.4464058524173028,0.5535941475826972,0.23421611156530217,0.409480256382344,42,0.711864406779661,0.15053763440860216,2.559322033898305,3,False,intermediate,distributed,intermediate/distributed,1.297247708722804e-10,5.839163637918388e-16,0,0,0,2.821778485872914e-14,92,60,122,240.2852499999999,True,completed,754,950,256,0.19999999999999984,0.19999999999999984,0.018427218395908315,0.003980279173516196,2.519893899204244,279,0,13.043150345956969,"[0.18427218395908337, 0.22112662075089998, 0.2681136221456971, 0.3264875731443198]",299 +S3_E4_L2_dis0.7_rt0.6_s3,S3,hypothesis-tests,E4_L2_dis0.7_rt0.6,3,ok,"level-selective disorder: levels >= 2 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L2_dis0.7_rt0.6_s3,9ddbfcea,2,2,3,4,grid,0.7,2,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.050824979893282815,0.050824979893282815,0.0005111388017839912,0.0005111388017839912,0.025556940089199558,0.0056912792966861215,0.011312109374315014,0.024737156702502792,True,4.197288807274567e-06,4.197288807274567e-06,0.10493222018186411,4.197288807274567e-06,55,0,0.05741127348643006,55,27,8,14,0.2545454545454545,0.47248802837140047,0.26912503365259827,0.49313002680965146,0.5068699731903485,0.16989725052170826,0.43583563905631995,34,0.6181818181818182,0.12186379928315412,2.6,3,False,intermediate,distributed,intermediate/distributed,2.3601903883273875e-10,2.752698782689329e-15,0,0,0,1.4328139429153485e-14,79,56,107,243.1736249999999,True,completed,761,958,256,0.20000000000000012,0.20000000000000012,0.01841380632638002,0.003977382166498084,2.5177398160315376,279,0,13.04532676716764,"[0.1841394134458202, 0.22096567591656, 0.2677961693694647, 0.32709874126815397]",308 +S3_E4_L3_dis0.35_rt0.6_s2,S3,hypothesis-tests,E4_L3_dis0.35_rt0.6,2,ok,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L3_dis0.35_rt0.6_s2,f5364439,2,2,3,4,grid,0.35,3,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08086379185910014,0.08086379185910014,0.0006340940977965464,0.0006340940977965464,0.03170470488982732,0.006375840227340003,0.009472809862231256,0.013195080570983838,True,4.772121664762944e-06,4.772121664762944e-06,0.11930304161907375,4.772121664762944e-06,42,0,0.046822742474916385,42,16,11,12,0.2857142857142857,0.422253344481503,0.2917817754708197,0.43170103092783507,0.5682989690721649,0.20609260347916317,0.5189948052431127,24,0.5714285714285714,0.08571428571428572,2.4047619047619047,3,False,intermediate,distributed,intermediate/distributed,3.7901951951147e-10,1.8237769519548565e-15,0,0,0,9.229796797188657e-15,46,43,72,167.93975,True,completed,702,897,256,0.19999999999999973,0.19999999999999973,0.018647654686616066,0.00402789341230907,2.5555555555555554,280,0,12.81520076607376,"[0.18647654686616094, 0.22377185623939305, 0.2685262274872715, 0.3212253694071736]",215 +S3_E4_L3_dis0.35_rt1_s1,S3,hypothesis-tests,E4_L3_dis0.35_rt1,1,ok,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L3_dis0.35_rt1_s1,320b254a,2,2,3,4,grid,0.35,3,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0692634071495845,0.0692634071495845,0.00048492619294467575,0.00048492619294467575,0.024246309647233788,0.006205791257553186,0.007871119345068322,0.010210785978425263,True,2.3198247743496e-06,2.3198247743496e-06,0.05799561935874001,2.3198247743496e-06,37,0,0.04157303370786517,37,12,12,5,0.13513513513513514,0.5688174573436608,0.1012413052962474,0.5866545893719807,0.4133454106280193,0.1983815849134296,0.620430388859781,19,0.5135135135135135,0.06785714285714285,2.2972972972972974,1,False,intermediate,distributed,intermediate/distributed,1.0514603270305643e-11,6.928638796042751e-17,0,0,0,1.2049223531216374e-14,35,38,60,140.72566699999993,True,completed,695,890,256,0.19999999999999993,0.19999999999999993,0.006683545230795672,0.006683545230795672,2.5611510791366907,280,0,7.889415570093022,"[0.06683545230795673, 0.13367090461591352, 0.26734180923182665, 0.5321518338443039]",188 +S3_E4_L3_dis0.35_rt0.6_s1,S3,hypothesis-tests,E4_L3_dis0.35_rt0.6,1,ok,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L3_dis0.35_rt0.6_s1,d1e0ff69,2,2,3,4,grid,0.35,3,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08084348685872705,0.08084348685872705,0.0006380202818826803,0.0006380202818826803,0.03190101409413401,0.006932243754662316,0.009230002727628568,0.021803420030638388,True,5.674481595693485e-06,5.674481595693485e-06,0.14186203989233725,5.674481595693485e-06,47,0,0.052808988764044947,47,19,11,9,0.19148936170212766,0.4825730487894214,0.41686795307830965,0.5878731343283582,0.4121268656716418,0.1657551069854661,0.6789485733178156,28,0.5957446808510638,0.1,2.5531914893617023,3,False,intermediate,distributed,intermediate/distributed,3.186996298071534e-11,9.414725277138543e-16,0,0,0,1.2538725585674546e-14,60,48,88,189.64474999999993,True,completed,695,890,256,0.19999999999999982,0.19999999999999982,0.01865735085983989,0.004029987785725416,2.5611510791366907,280,0,13.084224719993495,"[0.18657350859839908, 0.2238882103180789, 0.2686658523816949, 0.32087242870182814]",246 +S3_E4_L3_dis0.35_rt0.6_s3,S3,hypothesis-tests,E4_L3_dis0.35_rt0.6,3,ok,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=0.6",H4,study/runs/S3_E4_L3_dis0.35_rt0.6_s3,308c3bfb,2,2,3,4,grid,0.35,3,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07920008222775624,0.07920008222775624,0.0006457464049739743,0.0006457464049739743,0.032287320248698716,0.006612190829055222,0.00828427229914786,0.01873573947883871,True,4.9439489208278746e-06,4.9439489208278746e-06,0.12359872302069694,4.9439489208278746e-06,46,0,0.051685393258426963,46,17,13,2,0.043478260869565216,0.4825042133259362,0.45282020837969683,0.4874031007751938,0.5125968992248062,0.16159818721873945,0.3523400831639175,29,0.6304347826086957,0.10357142857142858,2.4782608695652173,3,False,intermediate,distributed,intermediate/distributed,4.879754496155148e-10,3.978335852102118e-15,0,0,0,9.080341832690401e-15,53,47,82,179.90954199999987,True,completed,695,890,256,0.19999999999999987,0.19999999999999987,0.018659960703477564,0.004030551511951154,2.5611510791366907,280,0,12.905755150620747,"[0.1865996070347758, 0.22391952844173094, 0.26870343413007725, 0.3207774303934173]",240 +S3_E4_L3_dis0.35_rt1_s2,S3,hypothesis-tests,E4_L3_dis0.35_rt1,2,ok,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L3_dis0.35_rt1_s2,af5de1ea,2,2,3,4,grid,0.35,3,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06871776344001473,0.06871776344001473,0.0004809523198681643,0.0004809523198681643,0.024047615993408215,0.006487639818358911,0.0074485449805511,0.019847809078634468,True,2.71220939331795e-06,2.71220939331795e-06,0.06780523483294887,2.71220939331795e-06,46,0,0.05128205128205128,46,20,17,3,0.06521739130434782,0.5968296941262766,0.3043666880476013,0.31119791666666663,0.6888020833333334,0.24769633783387293,0.5204687336174972,27,0.5869565217391305,0.09642857142857143,2.3260869565217392,3,False,intermediate,distributed,intermediate/distributed,1.643461467194406e-11,1.4996017996683911e-16,0,0,0,1.1711387623792005e-14,60,47,86,156.9085829999999,True,completed,702,897,256,0.19999999999999962,0.19999999999999962,0.0066777866979074105,0.0066777866979074105,2.5555555555555554,280,0,7.729845992125211,"[0.06677786697907424, 0.13355573395814854, 0.26711146791629675, 0.5325549311464813]",202 +S3_E4_L3_dis0.35_rt1_s3,S3,hypothesis-tests,E4_L3_dis0.35_rt1,3,ok,"level-selective disorder: levels >= 3 disordered (delta=0.35), r_t=1",H4,study/runs/S3_E4_L3_dis0.35_rt1_s3,0a333ab2,2,2,3,4,grid,0.35,3,3,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06606112045415208,0.06606112045415208,0.0004731999908267634,0.0004731999908267634,0.02365999954133817,0.00568377017306557,0.007821638657021684,0.010684721245202198,True,2.1374484671694547e-06,2.1374484671694547e-06,0.053436211679236414,2.1374484671694547e-06,38,0,0.04269662921348315,38,13,9,4,0.10526315789473684,0.40142041242951104,0.07547519360114868,0.6706204379562044,0.3293795620437956,0.13021026244106998,0.5330278426587673,22,0.5789473684210527,0.07857142857142857,1.9210526315789473,1,False,intermediate,localized,intermediate/localized,9.645363300032114e-11,1.04293577687039e-16,0,0,0,5.349810750326971e-15,37,39,62,125.577583,True,completed,695,890,256,0.19999999999999982,0.19999999999999982,0.006685095883589325,0.006685095883589325,2.5611510791366907,280,0,7.781086739967145,"[0.0668509588358933, 0.13370191767178666, 0.2674038353435731, 0.5320432881487461]",172 +S3_E4_L3_dis0.7_rt0.6_s2,S3,hypothesis-tests,E4_L3_dis0.7_rt0.6,2,ok,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L3_dis0.7_rt0.6_s2,1637ada5,2,2,3,4,grid,0.7,3,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07360934826426549,0.07360934826426549,0.00069128043235604,0.00069128043235604,0.034564021617802,0.008903625772980504,0.009505095497272279,0.019045146735733733,True,4.057466704943258e-06,4.057466704943258e-06,0.10143666762358147,4.057466704943258e-06,39,0,0.04276315789473684,39,13,17,2,0.05128205128205128,0.5948165504857742,0.18119905674195166,0.6710640138408305,0.3289359861591695,0.1348417591761985,0.5673947827565288,25,0.6410256410256411,0.08928571428571429,2.4615384615384617,3,False,intermediate,localized,intermediate/localized,7.966476510553993e-10,1.616363974041423e-15,0,0,0,4.175181258899059e-14,46,40,72,151.70170800000005,True,completed,717,912,256,0.19999999999999996,0.19999999999999996,0.018503018581806554,0.003996652013670215,2.5439330543933054,280,0,13.019002898293826,"[0.18503018581806552, 0.2220362229816787, 0.2664434675780148, 0.3264901236222409]",204 +S3_E4_L3_dis0.7_rt0.6_s3,S3,hypothesis-tests,E4_L3_dis0.7_rt0.6,3,ok,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L3_dis0.7_rt0.6_s3,67749d7b,2,2,3,4,grid,0.7,3,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07335626704798175,0.07335626704798175,0.0006340550082579665,0.0006340550082579665,0.03170275041289832,0.008643501554451144,0.008643501554451144,0.021234646240685974,True,4.224272924079045e-06,4.224272924079045e-06,0.10560682310197603,4.224272924079045e-06,46,0,0.05043859649122807,46,16,9,0,0.0,0.3815323218157695,0.35131375884288285,0.5841194968553459,0.4158805031446541,0.13169455122543527,0.6631710316449214,35,0.7608695652173914,0.125,2.5,2,True,intermediate,distributed,intermediate/distributed,2.1213861463705774e-11,4.0221976199038456e-16,0,0,0,2.0051567748524824e-16,54,47,84,172.03250000000003,True,completed,717,912,256,0.20000000000000018,0.20000000000000018,0.01853207879076983,0.004002929018806283,2.5439330543933054,280,0,12.89508953501945,"[0.18532078790769813, 0.22238494548923773, 0.2668619345870855, 0.3254323320159778]",229 +S3_E4_L3_dis0.7_rt1_s2,S3,hypothesis-tests,E4_L3_dis0.7_rt1,2,ok,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L3_dis0.7_rt1_s2,97e13cd2,2,2,3,4,grid,0.7,3,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.055045534141758515,0.055045534141758515,0.0005006156300976745,0.0005006156300976745,0.025030781504883724,0.008400110705569584,0.009213334632453659,0.0150227563177361,True,2.5423598446470362e-06,2.5423598446470362e-06,0.0635589961161759,2.5423598446470362e-06,35,0,0.03837719298245614,35,9,12,1,0.02857142857142857,0.4307096495716035,0.08305539366762343,0.39714566929133854,0.6028543307086615,0.18198172501250418,0.5334864809611936,20,0.5714285714285714,0.07142857142857142,2.1714285714285713,2,False,intermediate,distributed,intermediate/distributed,1.5688232605406295e-11,1.014928322242922e-16,0,0,0,1.632523204881838e-14,34,36,60,135.98358299999995,True,completed,717,912,256,0.2,0.2,0.006592353008708408,0.006592353008708408,2.5439330543933054,280,0,7.892845556163371,"[0.06592353008708407, 0.1318470601741681, 0.263694120348336, 0.5385352893904111]",201 +S3_E4_L3_dis0.7_rt1_s1,S3,hypothesis-tests,E4_L3_dis0.7_rt1,1,ok,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L3_dis0.7_rt1_s1,002d8a3f,2,2,3,4,grid,0.7,3,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.055078918953286565,0.055078918953286565,0.00041524344733717943,0.00041524344733717943,0.020762172366858973,0.007539063133925258,0.007539063133925258,0.011589940206167893,True,2.24942966864996e-06,2.24942966864996e-06,0.05623574171624904,2.24942966864996e-06,32,0,0.034934497816593885,32,8,10,0,0.0,0.3467638773242645,0.30414660012406236,0.6404494382022472,0.3595505617977528,0.1651924869612519,0.4180295277393707,17,0.53125,0.060714285714285714,2.0625,2,False,intermediate,localized,intermediate/localized,1.461247961057549e-11,8.520619315652604e-17,0,0,0,6.213149859485918e-15,28,33,52,166.1423749999999,True,completed,721,916,256,0.19999999999999987,0.19999999999999987,0.006613715227881033,0.006613715227881033,2.5409153952843275,280,0,7.89560121245818,"[0.06613715227881038, 0.13227430455762074, 0.2645486091152417, 0.5370399340483277]",220 +S3_E4_L3_dis0.7_rt1_s3,S3,hypothesis-tests,E4_L3_dis0.7_rt1,3,ok,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=1",H4,study/runs/S3_E4_L3_dis0.7_rt1_s3,ef9b6890,2,2,3,4,grid,0.7,3,3,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05383762494505937,0.05383762494505937,0.00046620918469977504,0.00046620918469977504,0.023310459234988753,0.008659542191460659,0.008659542191460659,0.013755612806053757,True,2.4625354232526246e-06,2.4625354232526246e-06,0.0615633855813158,2.4625354232526246e-06,32,0,0.03508771929824561,32,10,8,0,0.0,0.32881008691016783,0.1802842576733938,0.6893203883495146,0.3106796116504854,0.14059726617763954,0.6747147602646075,17,0.53125,0.060714285714285714,2.125,2,True,intermediate,localized,intermediate/localized,1.100288440132631e-11,6.852498024359091e-17,0,0,0,1.9262198057475298e-14,34,33,56,109.68529199999989,True,completed,717,912,256,0.1999999999999994,0.1999999999999994,0.006609448592769823,0.006609448592769823,2.5439330543933054,280,0,7.809748025924648,"[0.06609448592769843, 0.13218897185539677, 0.26437794371079376, 0.5373385985061122]",172 +S3_E4_L3_dis0.7_rt0.6_s1,S3,hypothesis-tests,E4_L3_dis0.7_rt0.6,1,ok,"level-selective disorder: levels >= 3 disordered (delta=0.7), r_t=0.6",H4,study/runs/S3_E4_L3_dis0.7_rt0.6_s1,fdfed5a6,2,2,3,4,grid,0.7,3,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07387628951466964,0.07387628951466964,0.0005920131906390195,0.0005920131906390195,0.029600659531950974,0.00780094424695321,0.009978106834237483,0.017275990106955512,True,5.0933107365058625e-06,5.0933107365058625e-06,0.12733276841264687,5.0933107365058625e-06,51,0,0.055676855895196505,51,17,9,13,0.2549019607843137,0.5128953833754805,0.32611634999232164,0.4255742049469965,0.5744257950530035,0.18949885212374734,0.41960396603419003,39,0.7647058823529411,0.1392857142857143,2.549019607843137,2,True,intermediate,distributed,intermediate/distributed,5.21602100706092e-11,4.638680014811779e-16,0,0,0,3.7251876039105844e-14,52,52,86,222.27637499999992,True,completed,721,916,256,0.1999999999999995,0.1999999999999995,0.018539322258429122,0.00400449360782069,2.5409153952843275,280,0,13.040165146006856,"[0.18539322258429164, 0.2224718671011499, 0.2669662405213802, 0.32516866979318065]",280 +S3_E5_ord_red0.5_s2,S3,hypothesis-tests,E5_ord_red0.5,2,ok,ordered braced lattice r=0.5,H5,study/runs/S3_E5_ord_red0.5_s2,265e29ad,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.5,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08535014468364005,0.08535014468364005,0.0009241476968501324,0.0009241476968501324,0.046207384842506624,0.010827722674350336,0.010827722674350336,0.010827722674350336,True,5.003207485816407e-06,5.003207485816407e-06,0.12508018714540936,5.003319232060578e-06,24,0,0.02696629213483146,24,1,24,0,0.0,0.9993036587535337,0.0,0.8971428571428571,0.10285714285714286,0.04043403802746617,0.20638020833333334,18,0.75,0.06428571428571428,2.4583333333333335,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.8832254277780798e-11,2.4301577405739415e-17,0,0,0,2.878001469714888e-15,14,25,37,89.4100420000002,True,completed,566,890,256,0.2000000000000013,0.2000000000000013,0.015130945316874938,0.003268284188444986,3.1448763250883394,280,130,21.79090600875804,"[0.15130945316874836, 0.1815713438024981, 0.21788561256299818, 0.4492335904657525]",133 +S3_E5_ord_red0.5_s1,S3,hypothesis-tests,E5_ord_red0.5,1,ok,ordered braced lattice r=0.5,H5,study/runs/S3_E5_ord_red0.5_s1,8db0410c,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.5,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08518989429886448,0.08518989429886448,0.0009948663548085678,0.0009948663548085678,0.04974331774042839,0.011678220321748018,0.011678220321748018,0.011678220321748018,True,5.8091342410743805e-06,5.8091342410743805e-06,0.1452283560268589,5.810398246911318e-06,29,0,0.032805429864253395,29,1,29,0,0.0,0.9961052164653126,0.0,0.8253737541528239,0.1746262458471761,0.09010483071392153,0.4011853448275863,22,0.7586206896551724,0.07857142857142857,2.4482758620689653,2,True,abrupt-brittle,localized,abrupt-brittle/localized,2.8564019661363734e-12,2.1316230921849642e-17,0,0,0,3.2071338396641616e-15,15,30,43,111.37650000000008,True,completed,566,884,256,0.20000000000000082,0.20000000000000082,0.015263221695045159,0.003296855886129754,3.1236749116607774,280,124,21.519829513784877,"[0.15263221695045107, 0.18315866034054118, 0.2197903924086492, 0.44441873030035417]",159 +S3_E5_ord_red1_s1,S3,hypothesis-tests,E5_ord_red1,1,ok,ordered braced lattice r=1,H5,study/runs/S3_E5_ord_red1_s1,564323f6,2,2,3,4,grid,0.0,0,1,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0762985419654385,0.0762985419654385,0.0007570805791326593,0.0007570805791326593,0.037854028956632965,0.009673627659670852,0.010154925514853847,0.012327011518398783,True,4.714956727313153e-06,4.714956727313153e-06,0.11787391818282768,4.714956727313153e-06,34,0,0.03346456692913386,34,8,12,1,0.029411764705882353,0.3899601032000122,0.16739010593564047,0.8327546296296297,0.16724537037037038,0.06544803399401605,0.17192095588235293,15,0.4411764705882353,0.05357142857142857,2.588235294117647,3,True,intermediate,localized,intermediate/localized,2.421416243949863e-11,2.6796952531410274e-17,0,0,0,1.095853318932923e-14,29,35,55,112.15158300000007,True,completed,567,1016,256,0.20000000000000195,0.20000000000000195,0.012801210833506573,0.0027650615400374194,3.583774250440917,280,256,27.12417026312732,"[0.1280121083350644, 0.15361453000207723, 0.1843374360024928, 0.5340359256603604]",175 +S3_E6_ord_rt1_s1,S3,hypothesis-tests,E6_ord_rt1,1,ok,"ordered, uniform thickness, no interfaces (= flat grid with 2x2 nesting labels)",H2,study/runs/S3_E6_ord_rt1_s1,c448c878,2,2,3,4,grid,0.0,0,1,1.0,0.2,0.0,1.0,none,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000000878381,0.10000000000878381,0.0017391880430167148,0.0017391880430167148,0.08695940215083574,0.017391880428639497,0.017391880428639497,0.017391880428639497,True,1.5123875243533154e-05,1.5123875243533154e-05,0.3780968810883265,1.5123875243533154e-05,23,0,0.04791666666666667,23,1,23,0,0.0,0.9999999998816074,0.0,0.792059748427673,0.20794025157232704,0.07189541606153801,0.5475543478260869,0,0.0,0.0,2.1739130434782608,2,False,abrupt-brittle,localized,abrupt-brittle/localized,5.255669470570333e-12,1.0610132619015125e-17,0,0,0,2.576291786746806e-15,20,24,42,17.65104199999996,True,completed,285,480,256,0.20000000000000123,0.20000000000000123,0.006666666666666667,0.006666666666666667,3.3684210526315788,0,0,9.375,"[0.06666666666666621, 0.13333333333333236, 0.26666666666666555, 0.5333333333333286]",36 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delta=0.35,H5,study/runs/S3_E5_dis035_red0.5_s3_s3,59cc1f41,2,2,3,4,grid,0.35,0,3,0.6,0.2,0.5,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.039617708901162715,0.039617708901162715,0.0002234354145047582,0.0002234354145047582,0.011171770725237909,0.003702108283017342,0.006405624229389848,0.027512450375024106,True,1.4736760866050552e-06,1.4736760866050552e-06,0.036841902165126325,1.4736760866050552e-06,53,0,0.04514480408858603,53,28,8,5,0.09433962264150944,0.22561789106158825,0.47943440418803146,0.5686425061425062,0.43135749385749383,0.16556514488743018,0.5129713716144685,20,0.37735849056603776,0.07017543859649122,2.2452830188679247,2,False,progressive,distributed,progressive/distributed,7.535427534580398e-11,1.0722606018276365e-16,0,0,0,2.22725516173084e-14,84,54,109,305.811917,True,completed,758,1174,256,0.20000000000000026,0.20000000000000026,0.013686687285829816,0.00295632445373924,3.0976253298153034,285,221,20.457362149871358,"[0.13433660543044787, 0.1649821240522177, 0.19866040450740416, 0.5020208660099311]",391 +S3_E6_dis015_rt1_s1,S3,hypothesis-tests,E6_dis015_rt1,1,ok,delta=0.15 with uniform thickness,H2,study/runs/S3_E6_dis015_rt1_s1,fe76e6e1,2,2,3,4,grid,0.15,0,1,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06567145414135221,0.06567145414135221,0.0002847768477613792,0.0002847768477613792,0.01423884238806896,0.004336387118037947,0.004336387118037947,0.016974517053717855,True,1.1347533355408165e-06,1.1347533355408165e-06,0.028368833388520413,1.1347533355408165e-06,48,0,0.05321507760532151,48,21,6,0,0.0,0.24408030351787635,0.45587176725091966,0.6230366492146597,0.3769633507853403,0.14411080015978864,0.432329931738861,29,0.6041666666666666,0.10357142857142858,1.9375,1,False,progressive,localized,progressive/localized,8.172132148750945e-11,2.179461307305336e-16,0,0,0,3.769556122604899e-14,59,49,86,156.83358399999997,True,completed,707,902,256,0.19999999999999998,0.19999999999999998,0.006690240942421369,0.006690240942421369,2.551626591230552,280,0,8.146660199160266,"[0.06584743994832845, 0.1331772706996709, 0.2667791509914121, 0.53419613836059]",199 +S3_E8_ord_notch_s1,S3,hypothesis-tests,E8_ord_notch,1,ok,ordered design with edge notch r=0.12W,H7,study/runs/S3_E8_ord_notch_s1,491b8407,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.12,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.09625071283471154,0.09625071283471154,0.0012205594006828534,0.0012205594006828534,0.06102797003414267,0.01268104271371876,0.01268104271371876,0.016184933779709226,True,7.8171120684115e-06,7.8171120684115e-06,0.19960925870381224,7.8171120684115e-06,33,0,0.04411764705882353,33,3,31,0,0.0,0.9833504747684005,0.009994627220723685,0.7372104247104247,0.2627895752895753,0.09216304431574399,0.46600378787878793,31,0.9393939393939394,0.11071428571428571,2.515151515151515,2,True,abrupt-brittle,localized,abrupt-brittle/localized,1.5779297483769327e-12,2.5668138252856553e-17,0,0,0,5.201099985824863e-15,23,34,53,90.3080829999999,True,completed,565,748,256,0.2000000000000005,0.19581035767511232,0.018628912071534977,0.004023845007451555,2.6858168761220824,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",129 +S3_E5_dis1_red1_s1,S3,hypothesis-tests,E5_dis1_red1,1,ok,fully organic braced r=1,H5,study/runs/S3_E5_dis1_red1_s1,5a1d86dc,2,2,3,4,grid,1.0,0,1,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.028331194109874194,0.028331194109874194,0.00023476061942134482,0.00023476061942134482,0.01173803097106724,0.006733794520396038,0.00919467719464097,0.054657858497703105,True,2.1567100853267003e-06,2.1567100853267003e-06,0.053917752133167504,2.1567100853267003e-06,62,0,0.04626865671641791,62,31,6,7,0.11290322580645161,0.2549684939966044,0.4644115181215213,0.6653899721448469,0.3346100278551532,0.1428036592657878,0.600225465342154,19,0.3064516129032258,0.06934306569343066,2.225806451612903,3,False,intermediate,localized,intermediate/localized,7.646557815624732e-11,1.4237194072655557e-16,0,0,0,2.544975115362537e-13,117,63,148,424.0546250000002,True,completed,735,1340,256,0.2,0.2,0.010493480661838136,0.0022665918229570372,3.6462585034013606,274,418,28.432061142907006,"[0.11118738892696407, 0.14107389025690098, 0.15621157402224586, 0.5915271467938886]",512 +S3_E8_ord_notch_s3,S3,hypothesis-tests,E8_ord_notch,3,ok,ordered design with edge notch r=0.12W,H7,study/runs/S3_E8_ord_notch_s3,e62cca2f,2,2,3,4,grid,0.0,0,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.12,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.09625071283471154,0.09625071283471154,0.0011646679911105037,0.0011646679911105037,0.05823339955552518,0.012100357044737478,0.012100357044737478,0.01357145741611243,True,7.614653204149806e-06,7.614653204149806e-06,0.19443948968174618,7.614653204149806e-06,29,0,0.03877005347593583,29,4,14,0,0.0,0.6535317209680855,0.0746198051846987,0.7724567099567099,0.22754329004329005,0.0861415768158256,0.46379310344827596,28,0.9655172413793104,0.1,2.5517241379310347,2,True,abrupt-brittle,localized,abrupt-brittle/localized,1.4003053946393188e-12,1.9762515420583564e-17,0,0,0,1.4460840197298725e-14,22,30,47,71.62612499999977,True,completed,565,748,256,0.2000000000000005,0.19581035767511232,0.018628912071534977,0.004023845007451555,2.6858168761220824,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",118 +S3_E6_dis015_rt1_s2,S3,hypothesis-tests,E6_dis015_rt1,2,ok,delta=0.15 with uniform thickness,H2,study/runs/S3_E6_dis015_rt1_s2,9201f45c,2,2,3,4,grid,0.15,0,2,1.0,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06855176618933172,0.06855176618933172,0.0002990616293089676,0.0002990616293089676,0.01495308146544838,0.004362566363104282,0.004362566363104282,0.01294167313399769,True,1.4710451227842138e-06,1.4710451227842138e-06,0.03677612806960538,1.4710451227842138e-06,50,0,0.054884742041712405,50,27,9,0,0.0,0.5478528799172215,0.5565478637225174,0.5777027027027026,0.4222972972972973,0.1557423978653273,0.37735933555152124,20,0.4,0.07142857142857142,2.02,2,False,intermediate,distributed,intermediate/distributed,1.4397518760052663e-10,1.5747191986812272e-16,0,0,0,5.340577569037669e-14,67,51,90,157.16087500000003,True,completed,716,911,256,0.19999999999999976,0.19999999999999976,0.006687545531497561,0.006687545531497561,2.5446927374301676,280,0,8.138968438045671,"[0.06676938616128743, 0.1332309790093552, 0.26673781207496183, 0.5332618227543963]",206 +S3_E8_ord_notch_s2,S3,hypothesis-tests,E8_ord_notch,2,ok,ordered design with edge notch r=0.12W,H7,study/runs/S3_E8_ord_notch_s2,a8678fdf,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.12,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.09625071283471154,0.09625071283471154,0.001179440003327633,0.001179440003327633,0.05897200016638165,0.012253831359701744,0.012253831359701744,0.016526017567431887,True,7.410263108721374e-06,7.410263108721374e-06,0.18922040684427047,7.410263108721374e-06,34,0,0.045454545454545456,34,4,16,0,0.0,0.620011148287537,0.024821474783191737,0.6745495495495495,0.32545045045045046,0.09103037876339524,0.5345588235294116,32,0.9411764705882353,0.11428571428571428,2.5294117647058822,2,True,abrupt-brittle,localized,abrupt-brittle/localized,1.6369616979526885e-12,2.6379260710325997e-17,0,0,0,0.0,25,35,55,112.09975000000031,True,completed,565,748,256,0.2000000000000005,0.19581035767511232,0.018628912071534977,0.004023845007451555,2.6858168761220824,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",158 +S3_E8_ord_notch06_s1,S3,hypothesis-tests,E8_ord_notch06,1,ok,ordered design with small edge notch r=0.06W,H7,study/runs/S3_E8_ord_notch06_s1,e11c718d,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.06,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002578839,0.10000000002578839,0.0013862703765911617,0.0013862703765911617,0.06931351882955808,0.013862703762336635,0.013862703762336635,0.013862703762336635,True,9.608727782593033e-06,9.608727782593033e-06,0.24162482192794893,9.60944193459798e-06,34,0,0.04479578392621871,34,1,34,0,0.0,0.9962663056601013,0.0,0.6938559322033898,0.3061440677966102,0.09100556253036025,0.4597886029411765,30,0.8823529411764706,0.10714285714285714,2.323529411764706,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.5518537918597177e-12,2.3092997982487642e-17,0,0,0,5.993921479031456e-15,17,35,50,118.66383399999995,True,completed,565,759,256,0.2000000000000005,0.19883569299552958,0.018628912071534977,0.004023845007451555,2.6914893617021276,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",160 +S3_E8_ord_notch06_s2,S3,hypothesis-tests,E8_ord_notch06,2,ok,ordered design with small edge notch r=0.06W,H7,study/runs/S3_E8_ord_notch06_s2,9c51784c,2,2,3,4,grid,0.0,0,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.06,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002578839,0.10000000002578839,0.0014188137633369237,0.0014188137633369237,0.07094068816684619,0.014188137629710391,0.014188137629710391,0.014188137629710391,True,1.006516247257582e-05,1.006516247257582e-05,0.25310250692269104,1.0074401912565725e-05,32,0,0.04216073781291173,32,1,32,0,0.0,0.992201935072592,0.0,0.7793103448275862,0.2206896551724138,0.09810735653232977,0.4009765625,28,0.875,0.1,2.40625,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.1156266370758604e-12,2.5817631182481002e-17,0,0,0,3.0267986492697787e-15,18,33,49,123.55745799999977,True,completed,565,759,256,0.2000000000000005,0.19883569299552958,0.018628912071534977,0.004023845007451555,2.6914893617021276,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",163 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r=0.20W,H7,study/runs/S3_E8_dis_notch20_s1,b453cd44,2,2,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.2,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.030911323322368303,0.030911323322368303,0.00010938529200891158,0.00010938529200891158,0.005469264600445579,0.003538680336268794,0.003538680336268794,0.018651029283409178,True,7.092692950211956e-07,7.092692950211956e-07,0.019057314874108718,7.092692950211956e-07,36,0,0.04072398190045249,36,25,3,0,0.0,0.31016294692907287,0.727127915570215,0.4452054794520548,0.5547945205479452,0.22706685502591045,0.4881985349929512,27,0.75,0.0967741935483871,2.4166666666666665,3,False,intermediate,distributed,intermediate/distributed,1.3913500388632809e-09,2.4389321107786116e-15,0,0,0,4.015609170079006e-14,69,37,80,123.55487500000027,True,completed,746,884,256,0.19999999999999993,0.18608846516589,0.018724827940452965,0.00404456283513784,2.514935988620199,279,0,12.976613964768223,"[0.18251648410168128, 0.22524411478037132, 0.2706385482576284, 0.32160085286031964]",169 +S3_E5_dis035_red1_s3_s3,S3,hypothesis-tests,E5_dis035_red1_s3,3,ok,third seed r=1 delta=0.35,H5,study/runs/S3_E5_dis035_red1_s3_s3,d6a98cb1,2,2,3,4,grid,0.35,0,3,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04255679386837564,0.04255679386837564,0.00025704457476935565,0.00025704457476935565,0.012852228738467782,0.004024687371880427,0.0062734697786490995,0.06923526078211063,True,3.260079788349644e-06,3.260079788349644e-06,0.08150199470874092,3.260079788349644e-06,70,0,0.05124450951683748,70,36,8,2,0.02857142857142857,0.3857823953095849,0.7486638520602352,0.568661971830986,0.43133802816901406,0.1596776119586282,0.3394319994996778,22,0.3142857142857143,0.07719298245614035,2.3,2,False,intermediate,distributed,intermediate/distributed,1.1129326017592038e-10,3.9876877463776655e-16,0,0,0,1.0158950206065057e-13,142,71,176,507.6424579999998,True,completed,758,1366,256,0.20000000000000046,0.20000000000000046,0.011100313325335016,0.002397667678272363,3.604221635883905,285,422,25.223929292086897,"[0.10895101058411172, 0.13380544406497494, 0.1611195382284414, 0.5961240071224715]",589 +S3_E9_ref_ord_movie_s1,S3,hypothesis-tests,E9_ref_ord_movie,1,ok,"ordered reference, full state history for movie/snapshots",representative,study/runs/S3_E9_ref_ord_movie_s1,6767c994,2,2,3,4,grid,0.0,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0013862703765912987,0.0013862703765912987,0.06931351882956494,0.013862703762332798,0.013862703762332798,0.013862703762332798,True,9.608727782591333e-06,9.608727782591333e-06,0.24021819456478272,9.609441934596302e-06,34,0,0.04473684210526316,34,1,34,0,0.0,0.9962663056601007,0.0,0.6938559322033898,0.3061440677966102,0.09100556253036025,0.4597886029411765,30,0.8823529411764706,0.10714285714285714,2.323529411764706,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.5550107648744588e-12,2.378806536501951e-17,0,0,0,5.817629670825665e-15,17,35,50,90.34745899999962,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 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braced,H5,study/runs/S4_E5_ord_red1_s5,5a04e6f0,2,2,3,4,grid,0.0,0,5,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0762985419654385,0.0762985419654385,0.0007425289534782945,0.0007425289534782945,0.03712644767391472,0.009599671399657627,0.009959740644559862,0.01201694181071158,True,5.000061201506815e-06,5.000061201506815e-06,0.12500153003766917,5.000061201506815e-06,32,0,0.031496062992125984,32,6,16,1,0.03125,0.7356047918347721,0.24438423432613465,0.9072463768115941,0.0927536231884058,0.034618142010015264,0.22880859374999998,17,0.53125,0.060714285714285714,2.53125,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.9186502255264574e-11,2.214000948951451e-17,0,0,0,8.1314167626496e-15,25,33,51,121.82400000000007,True,completed,567,1016,256,0.20000000000000195,0.20000000000000195,0.012801210833506573,0.0027650615400374194,3.583774250440917,280,256,27.12417026312732,"[0.1280121083350644, 0.15361453000207723, 0.1843374360024928, 0.5340359256603604]",171 +S4_E4_L3_dis0.35_rt0.6_s4,S4,refinement,E4_L3_dis0.35_rt0.6,4,ok,seeds 4-5 level-selective design,H4,study/runs/S4_E4_L3_dis0.35_rt0.6_s4,94902aa3,2,2,3,4,grid,0.35,3,4,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0799492006454864,0.0799492006454864,0.0006005085982218993,0.0006005085982218993,0.030025429911094966,0.0059281857125688805,0.007695093009966834,0.038985612238581505,True,3.7608569915086672e-06,3.7608569915086672e-06,0.09402142478771655,3.7608569915086672e-06,43,0,0.04793756967670011,43,22,12,3,0.06976744186046512,0.40247009364988945,0.37453907753746324,0.5283163265306122,0.4716836734693878,0.1582262773027413,0.5528646824808593,31,0.7209302325581395,0.11071428571428571,2.488372093023256,3,True,intermediate,distributed,intermediate/distributed,1.5993737594830837e-10,1.5368152101751672e-15,0,0,0,3.153127409081084e-15,83,44,104,221.74254100000007,True,completed,702,897,256,0.20000000000000026,0.20000000000000026,0.01866618046604001,0.004031894980664642,2.5555555555555554,280,0,12.762926595119293,"[0.18666180466039986, 0.2239941655924797, 0.2687929987109756, 0.32055103103614285]",284 +S4_R_red1_s3,S4,refinement,R_red1,3,ok,third seed,H5,study/runs/S4_R_red1_s3,d6a98cb1,2,2,3,4,grid,0.35,0,3,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04255679386837564,0.04255679386837564,0.00025704457476935565,0.00025704457476935565,0.012852228738467782,0.004024687371880427,0.0062734697786490995,0.06923526078211063,True,3.260079788349644e-06,3.260079788349644e-06,0.08150199470874092,3.260079788349644e-06,70,0,0.05124450951683748,70,36,8,2,0.02857142857142857,0.3857823953095849,0.7486638520602352,0.568661971830986,0.43133802816901406,0.1596776119586282,0.3394319994996778,22,0.3142857142857143,0.07719298245614035,2.3,2,False,intermediate,distributed,intermediate/distributed,1.1129326017592038e-10,3.9876877463776655e-16,0,0,0,1.0158950206065057e-13,142,71,176,644.623917,True,completed,758,1366,256,0.20000000000000046,0.20000000000000046,0.011100313325335016,0.002397667678272363,3.604221635883905,285,422,25.223929292086897,"[0.10895101058411172, 0.13380544406497494, 0.1611195382284414, 0.5961240071224715]",772 +S4_E5_ord_red1_s4,S4,refinement,E5_ord_red1,4,ok,seeds 4-5 ordered braced,H5,study/runs/S4_E5_ord_red1_s4,33c1a5be,2,2,3,4,grid,0.0,0,4,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0762985419654385,0.0762985419654385,0.0007387077782377331,0.0007387077782377331,0.03693538891188665,0.00935448137138651,0.009908486192898226,0.013497893099980637,True,4.977210742980909e-06,4.977210742980909e-06,0.12443026857452151,4.977210742980909e-06,35,0,0.0344488188976378,35,9,16,1,0.02857142857142857,0.6774697125305388,0.24935686183895692,0.856892523364486,0.143107476635514,0.039983753875537674,0.23285714285714287,18,0.5142857142857142,0.06428571428571428,2.4571428571428573,3,True,abrupt-brittle,localized,abrupt-brittle/localized,5.526686035589671e-12,2.2088975312443863e-17,0,0,0,6.637107940326654e-15,32,36,58,137.43254100000001,True,completed,567,1016,256,0.20000000000000195,0.20000000000000195,0.012801210833506573,0.0027650615400374194,3.583774250440917,280,256,27.12417026312732,"[0.1280121083350644, 0.15361453000207723, 0.1843374360024928, 0.5340359256603604]",204 +S4_B2_ref_s4,S4,refinement,B2_ref,4,ok,seeds 4-5 for the disordered reference,reference,study/runs/S4_B2_ref_s4,982b5989,2,2,3,4,grid,0.35,0,4,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.044445540789300075,0.044445540789300075,0.0001974582816201751,0.0001974582816201751,0.009872914081008754,0.004291041503327231,0.004721971719094322,0.03266707637539884,True,1.8591219588420962e-06,1.8591219588420962e-06,0.04647804897105238,1.8591219588420962e-06,79,0,0.08333333333333333,79,43,11,3,0.0379746835443038,0.47828414648444256,0.735584625168573,0.31447715289982425,0.6855228471001757,0.2444850878203834,0.4643067184149817,58,0.7341772151898734,0.20714285714285716,2.5443037974683542,3,False,intermediate,distributed,intermediate/distributed,2.039614328968951e-10,1.842613620148466e-15,0,0,0,2.152753162180522e-14,119,80,155,366.146708,True,completed,753,948,256,0.20000000000000012,0.20000000000000012,0.018673614194656962,0.004033500666045903,2.5179282868525896,280,0,12.892867775426492,"[0.18744615366184178, 0.22223398661394694, 0.2683448429327666, 0.3219750167914437]",441 +S4_E4_L2_dis0.35_rt0.6_s4,S4,refinement,E4_L2_dis0.35_rt0.6,4,ok,seeds 4-5,H4,study/runs/S4_E4_L2_dis0.35_rt0.6_s4,97daf0db,2,2,3,4,grid,0.35,2,4,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06435997538882374,0.06435997538882374,0.0003510137722631426,0.0003510137722631426,0.01755068861315713,0.00407713923275571,0.007278211221018112,0.019587180518137792,True,3.566841695630822e-06,3.566841695630822e-06,0.08917104239077062,3.566841695630822e-06,51,0,0.054313099041533544,51,28,6,12,0.23529411764705882,0.8624811359751274,0.5760665425831683,0.5777597402597403,0.42224025974025975,0.14568513012103537,0.3499096025574239,32,0.6274509803921569,0.11428571428571428,2.5686274509803924,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,6.969872603959147e-10,2.959953615954104e-15,0,0,0,1.4129716051981257e-14,76,52,99,213.52483300000006,True,completed,744,939,256,0.19999999999999984,0.19999999999999984,0.018674688665766086,0.004033732751805474,2.524193548387097,280,0,12.712904613246675,"[0.18674688665766104, 0.2240962639891932, 0.26750250272712145, 0.3216543466260233]",283 +S4_E4_L2_dis0.35_rt0.6_s5,S4,refinement,E4_L2_dis0.35_rt0.6,5,ok,seeds 4-5,H4,study/runs/S4_E4_L2_dis0.35_rt0.6_s5,a95f7490,2,2,3,4,grid,0.35,2,5,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06561729971263819,0.06561729971263819,0.00035472913357649885,0.00035472913357649885,0.017736456678824942,0.005231431763466994,0.007291860079265896,0.02182471498663749,True,3.850146693426865e-06,3.850146693426865e-06,0.09625366733567149,3.850146693426865e-06,51,0,0.05419766206163656,51,29,5,14,0.27450980392156865,0.8443092708718754,0.5923585434926967,0.4998076923076923,0.5001923076923077,0.15921633972270224,0.28863619791246053,30,0.5882352941176471,0.10714285714285714,2.5098039215686274,2,False,abrupt-brittle,distributed,abrupt-brittle/distributed,6.092676371936994e-10,3.5384060740784856e-15,0,0,0,8.030006396266479e-14,80,52,102,207.80875000000003,True,completed,746,941,256,0.20000000000000026,0.20000000000000026,0.018674847855806566,0.004033767136854218,2.5227882037533513,280,0,12.978492713137932,"[0.18674847855806542, 0.22409817426967843, 0.2671089497339071, 0.3220443974383486]",275 +S4_F1_L3_dis0.15_rt0.6_s2,S4,refinement,F1_L3_dis0.15_rt0.6,2,ok,L3 design: disorder of the finest level delta=0.15,H4,study/runs/S4_F1_L3_dis0.15_rt0.6_s2,9c235c8b,2,2,3,4,grid,0.15,3,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09153421977561897,0.09153421977561897,0.000615152306333237,0.000615152306333237,0.030757615316661848,0.004776751401769711,0.009388613812544858,0.022263161421527858,True,3.985097570343114e-06,3.985097570343114e-06,0.09962743925857796,3.985097570343114e-06,45,0,0.05363528009535161,45,24,8,16,0.35555555555555557,0.3456347597404001,0.12191207106862233,0.6266592920353982,0.3733407079646018,0.14814954632331653,0.5472251980956448,31,0.6888888888888889,0.11071428571428571,2.511111111111111,3,False,intermediate,localized,intermediate/localized,1.4253839819400433e-10,2.2131324684245336e-15,0,0,0,1.4240857711584682e-14,71,46,92,184.291917,True,completed,644,839,256,0.19999999999999976,0.19999999999999976,0.01864560195392388,0.0040274500220475575,2.6055900621118013,280,0,13.900667705983519,"[0.18645601953923893, 0.22374722344708692, 0.2684966681365043, 0.32130008887717004]",244 +S4_E5_dis1_red1_s3,S4,refinement,E5_dis1_red1,3,ok,third seed,H5,study/runs/S4_E5_dis1_red1_s3,59530e79,2,2,3,4,grid,1.0,0,3,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.02842089771588338,0.02842089771588338,0.00021273581314409852,0.00021273581314409852,0.010636790657204926,0.006429665983963135,0.00796923209545286,0.06987007871941923,True,3.1772356533097556e-06,3.1772356533097556e-06,0.07943089133274385,3.1772356533097556e-06,76,0,0.055964653902798235,76,42,7,4,0.05263157894736842,0.2970768373620676,0.7200977412450976,0.38395904436860073,0.6160409556313993,0.2227854761537987,0.32983531145321016,18,0.23684210526315788,0.06521739130434782,2.1710526315789473,3,True,intermediate,distributed,intermediate/distributed,2.079978273519644e-10,6.925863977928921e-16,0,0,0,2.6166231543576486e-13,154,77,188,733.064875,True,completed,750,1358,256,0.2000000000000001,0.2000000000000001,0.010802915456558676,0.0023334297386166736,3.6213333333333333,276,410,27.288469894664345,"[0.10809057800932956, 0.13668822879307244, 0.1547737868904337, 0.6004474063071638]",873 +S4_F1_L3_dis0.15_rt0.6_s1,S4,refinement,F1_L3_dis0.15_rt0.6,1,ok,L3 design: disorder of the finest level delta=0.15,H4,study/runs/S4_F1_L3_dis0.15_rt0.6_s1,6676ab6e,2,2,3,4,grid,0.15,3,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09109227196447423,0.09109227196447423,0.0006135331360425113,0.0006135331360425113,0.030676656802125567,0.004712692801501932,0.008597185220938526,0.029291794429678417,True,5.258720659271133e-06,5.258720659271133e-06,0.1314680164817787,5.258720659271133e-06,70,0,0.0830367734282325,70,44,8,14,0.2,0.4412778526353572,0.4155125073684022,0.39476284584980237,0.6052371541501976,0.22643355085475456,0.5057838448935543,45,0.6428571428571429,0.16071428571428573,2.557142857142857,3,False,intermediate,distributed,intermediate/distributed,1.9000245641323913e-10,2.2923432111621044e-15,0,0,0,4.123444627445857e-14,118,71,144,279.65808300000003,True,completed,648,843,256,0.19999999999999946,0.19999999999999946,0.018653853529269855,0.004029232362322288,2.6018518518518516,280,0,13.405037149409672,"[0.18653853529269912, 0.2238462423512389, 0.2686154908214867, 0.32099973153457606]",335 +S4_F1_L3_dis0.15_rt0.6_s3,S4,refinement,F1_L3_dis0.15_rt0.6,3,ok,L3 design: disorder of the finest level delta=0.15,H4,study/runs/S4_F1_L3_dis0.15_rt0.6_s3,bcfb2caf,2,2,3,4,grid,0.15,3,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08977789666309315,0.08977789666309315,0.0006013941967542136,0.0006013941967542136,0.03006970983771068,0.005187116881618927,0.008519648414052323,0.017928815303841817,True,5.174361775142155e-06,5.174361775142155e-06,0.12935904437855397,5.174361775142155e-06,64,0,0.07600950118764846,64,31,10,15,0.234375,0.42581458544403167,0.43310948519020487,0.2098765432098766,0.7901234567901234,0.2425208945967927,0.4614208670685993,38,0.59375,0.1357142857142857,2.453125,3,False,intermediate,distributed,intermediate/distributed,6.521946562598075e-10,1.845932150599475e-15,0,0,0,1.1949957856950422e-14,80,65,113,216.116125,True,completed,647,842,256,0.19999999999999984,0.19999999999999984,0.01865356083067831,0.004029169139426515,2.6027820710973724,280,0,13.590176352741466,"[0.18653560830678328, 0.22384272996813986, 0.2686112759617679, 0.32101038576330965]",281 +S4_F1_L3_dis0.5_rt0.6_s3,S4,refinement,F1_L3_dis0.5_rt0.6,3,ok,L3 design: disorder of the finest level delta=0.5,H4,study/runs/S4_F1_L3_dis0.5_rt0.6_s3,d769c3dc,2,2,3,4,grid,0.5,3,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07591087730819038,0.07591087730819038,0.000607965874680112,0.000607965874680112,0.0303982937340056,0.008008942805545923,0.008008942805545923,0.01807807888333591,True,3.847383162370588e-06,3.847383162370588e-06,0.09618457905926478,3.847383162370588e-06,36,0,0.03991130820399113,36,12,18,0,0.0,0.6132747720691121,0.36721094409575783,0.6105769230769231,0.3894230769230769,0.127868629685213,0.6128553676992091,25,0.6944444444444444,0.08928571428571429,2.5,2,True,abrupt-brittle,localized,abrupt-brittle/localized,3.409564393317881e-11,2.6651671994632826e-16,0,0,0,2.1355345286961854e-14,43,37,67,148.41308300000003,True,completed,707,902,256,0.19999999999999984,0.19999999999999984,0.018630699583566904,0.004024231110050451,2.551626591230552,280,0,12.739518502766352,"[0.18630699583566918, 0.22356839500280307, 0.26828207400336357, 0.32184253515816413]",206 +S4_F1_L3_dis1_rt0.6_s2,S4,refinement,F1_L3_dis1_rt0.6,2,ok,L3 design: disorder of the finest level delta=1,H4,study/runs/S4_F1_L3_dis1_rt0.6_s2,a1b028d5,2,2,3,4,grid,1.0,3,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0704254986886968,0.0704254986886968,0.0005897872429493555,0.0005897872429493555,0.029489362147467776,0.00721772294854972,0.009192072023710224,0.018334116195646413,True,4.4701708270982534e-06,4.4701708270982534e-06,0.11175427067745658,4.4701708270982534e-06,34,0,0.03837471783295711,34,14,9,6,0.17647058823529413,0.49333269914765543,0.35675057248310366,0.7014462809917356,0.29855371900826444,0.1346633978228388,0.6507486750812718,26,0.7647058823529411,0.1015625,2.3529411764705883,2,True,intermediate,localized,intermediate/localized,5.203655800858507e-11,8.072124433106677e-16,0,0,0,4.263425728093067e-14,47,35,67,141.248333,True,completed,692,886,256,0.19999999999999957,0.19999999999999957,0.018137051209198358,0.003917603061186845,2.560693641618497,256,0,13.79327906482276,"[0.18137348237313852, 0.2176636742489136, 0.2611941027984419, 0.33976874057950585]",204 +S4_F1_L3_dis0.5_rt0.6_s1,S4,refinement,F1_L3_dis0.5_rt0.6,1,ok,L3 design: disorder of the finest level delta=0.5,H4,study/runs/S4_F1_L3_dis0.5_rt0.6_s1,9f46a782,2,2,3,4,grid,0.5,3,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07714784917212616,0.07714784917212616,0.0006262040599879634,0.0006262040599879634,0.03131020299939817,0.0063973146416194384,0.00819755178897955,0.017696006605122407,True,4.693163621542958e-06,4.693163621542958e-06,0.11732909053857381,4.693163621542958e-06,47,0,0.051991150442477874,47,19,10,1,0.02127659574468085,0.44187552774517025,0.44979648693234203,0.42233263598326365,0.5776673640167364,0.17205491777140366,0.5783040813194441,34,0.723404255319149,0.12142857142857143,2.5106382978723403,3,False,intermediate,distributed,intermediate/distributed,5.658841830995086e-11,1.0872229061912963e-15,0,0,0,5.071552525590541e-14,56,48,84,191.47845800000005,True,completed,709,904,256,0.2000000000000002,0.2000000000000002,0.018630735764541072,0.004024238925140871,2.550070521861777,280,0,12.946899251999339,"[0.18630735764541057, 0.22356882917449258, 0.2682825950093909, 0.32184121817070466]",254 +S4_F1_L3_dis1_rt0.6_s1,S4,refinement,F1_L3_dis1_rt0.6,1,ok,L3 design: disorder of the finest level delta=1,H4,study/runs/S4_F1_L3_dis1_rt0.6_s1,6b3ecc58,2,2,3,4,grid,1.0,3,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07043673623591085,0.07043673623591085,0.0006465848029685103,0.0006465848029685103,0.03232924014842552,0.00917965308334179,0.00917965308334179,0.014628073221544557,True,4.733514776319332e-06,4.733514776319332e-06,0.11833786940798358,4.733514776319332e-06,37,0,0.04092920353982301,37,9,13,0,0.0,0.5616462074522887,0.3730426056864347,0.5324453551912569,0.46755464480874315,0.14611299440570144,0.4228263765871701,31,0.8378378378378378,0.11397058823529412,2.4324324324324325,2,True,intermediate,distributed,intermediate/distributed,2.89845782466203e-11,3.8507627448574223e-16,0,0,0,0.0,33,38,61,196.69275000000016,True,completed,708,904,256,0.19999999999999954,0.19999999999999954,0.018271791142679662,0.003946706886818806,2.553672316384181,272,0,13.694065710789955,"[0.182717911426797, 0.21926930174115722, 0.26312307411131824, 0.33488971272072804]",266 +S4_F1_L3_dis1_rt0.6_s3,S4,refinement,F1_L3_dis1_rt0.6,3,ok,L3 design: disorder of the finest level delta=1,H4,study/runs/S4_F1_L3_dis1_rt0.6_s3,9ae36043,2,2,3,4,grid,1.0,3,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0711601990279998,0.0711601990279998,0.0006006014626752449,0.0006006014626752449,0.030030073133762245,0.007657868884930214,0.008492169640443165,0.01640750969786091,True,4.213734963612081e-06,4.213734963612081e-06,0.10534337409030206,4.213734963612081e-06,41,0,0.044857768052516414,41,13,14,2,0.04878048780487805,0.45277015812885296,0.39175329351245786,0.5158410138248848,0.4841589861751152,0.14354418509815325,0.47662171256409097,32,0.7804878048780488,0.11678832116788321,2.5609756097560976,3,False,intermediate,distributed,intermediate/distributed,3.16407656657707e-10,2.455406061728043e-15,0,0,0,1.7689508239617067e-14,43,42,71,176.22220900000013,True,completed,719,914,256,0.19999999999999993,0.19999999999999993,0.018217690730093695,0.003935021197700238,2.5424200278164117,274,0,13.72474356883145,"[0.18217690730093702, 0.21864048910630843, 0.2623395017822473, 0.33684310181050625]",244 +S4_F2_L3_dis0.35_rt0.8_s1,S4,refinement,F2_L3_dis0.35_rt0.8,1,ok,L3 design: thickness ratio r_t=0.8,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.8_s1,acbb16d0,2,2,3,4,grid,0.35,3,1,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0747177435568008,0.0747177435568008,0.0006151995564148833,0.0006151995564148833,0.030759977820744164,0.006762219341480464,0.010225011597868079,0.012240285009810949,True,4.086428664048121e-06,4.086428664048121e-06,0.10216071660120352,4.086428664048121e-06,41,0,0.046067415730337076,41,17,11,10,0.24390243902439024,0.3060142125078659,0.11969877690670225,0.5451839826839826,0.45481601731601734,0.1997078405088191,0.36847864278763826,27,0.6585365853658537,0.09642857142857143,2.3658536585365852,3,False,intermediate,distributed,intermediate/distributed,4.391926332062983e-11,5.548144661706409e-16,0,0,0,6.425664932291132e-15,47,42,71,160.14654200000007,True,completed,695,890,256,0.19999999999999904,0.19999999999999904,0.010826488739170782,0.005543162234455442,2.5611510791366907,280,0,9.512488283222769,"[0.10826488739170831, 0.17322381982673335, 0.2771581117227735, 0.44135318105878835]",216 +S4_F1_L3_dis0.5_rt0.6_s2,S4,refinement,F1_L3_dis0.5_rt0.6,2,ok,L3 design: disorder of the finest level delta=0.5,H4,study/runs/S4_F1_L3_dis0.5_rt0.6_s2,35baceb1,2,2,3,4,grid,0.5,3,2,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07688489997168844,0.07688489997168844,0.0006623982608464358,0.0006623982608464358,0.03311991304232179,0.007772705949534107,0.009856587069046874,0.028242438421290362,True,4.160301737562913e-06,4.160301737562913e-06,0.10400754343907245,4.160301737562913e-06,58,0,0.0639470782800441,58,24,19,9,0.15517241379310345,0.6459983645390139,0.13603099659324827,0.4636479591836735,0.5363520408163265,0.17686935425764,0.45988117359818476,42,0.7241379310344828,0.15,2.586206896551724,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,1.6427107249911596e-10,4.590797648917125e-15,0,0,0,2.3413875982780562e-14,77,59,111,237.37424999999996,True,completed,712,907,256,0.20000000000000073,0.20000000000000073,0.018611107102733827,0.004019999134190506,2.547752808988764,280,0,12.794643966738368,"[0.18611107102733754, 0.22333328523280513, 0.26799994227936597, 0.322555701460488]",297 +S4_F2_L3_dis0.35_rt0.8_s2,S4,refinement,F2_L3_dis0.35_rt0.8,2,ok,L3 design: thickness ratio r_t=0.8,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.8_s2,ffa71414,2,2,3,4,grid,0.35,3,2,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07472875252693355,0.07472875252693355,0.0005308002119147406,0.0005308002119147406,0.026540010595737032,0.006096659298615697,0.007549283708975841,0.013128806427857232,True,3.6481143390737028e-06,3.6481143390737028e-06,0.0912028584768427,3.6481143390737028e-06,44,0,0.04905239687848383,44,14,15,4,0.09090909090909091,0.44695504776790757,0.42395355572774446,0.5381679389312977,0.4618320610687023,0.18539376144574346,0.4426460941417055,29,0.6590909090909091,0.10357142857142858,2.340909090909091,3,True,intermediate,distributed,intermediate/distributed,1.5558518185937577e-11,2.6501711325630446e-16,0,0,0,1.0680453503436816e-14,42,45,72,190.974333,True,completed,702,897,256,0.1999999999999997,0.1999999999999997,0.010818751123806945,0.0055392005753891575,2.5555555555555554,280,0,9.318720642185843,"[0.10818751123806963, 0.1731000179809114, 0.27696002876945824, 0.44175244201156094]",247 +S4_F2_L3_dis0.35_rt0.8_s3,S4,refinement,F2_L3_dis0.35_rt0.8,3,ok,L3 design: thickness ratio r_t=0.8,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.8_s3,f03af356,2,2,3,4,grid,0.35,3,3,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07219797035739946,0.07219797035739946,0.0005432905224035081,0.0005432905224035081,0.027164526120175406,0.006907989380038414,0.007954276104356757,0.017609205143877683,True,3.618974327947985e-06,3.618974327947985e-06,0.09047435819869958,3.618974327947985e-06,43,0,0.048314606741573035,43,17,15,4,0.09302325581395349,0.5709108509352372,0.37476923172061594,0.4523104265402843,0.5476895734597157,0.16239117452638244,0.4721263634568394,30,0.6976744186046512,0.10714285714285714,2.441860465116279,3,False,intermediate,distributed,intermediate/distributed,2.563577150849127e-10,6.18516365125753e-16,0,0,0,1.0064292650726537e-14,52,44,78,169.34245899999996,True,completed,695,890,256,0.20000000000000012,0.20000000000000012,0.010828571928819619,0.005544228827555646,2.5611510791366907,280,0,9.382244592191437,"[0.10828571928819614, 0.1732571508611138, 0.2772114413777819, 0.44124568847290735]",213 +S4_F2_L3_dis0.35_rt0.45_s1,S4,refinement,F2_L3_dis0.35_rt0.45,1,ok,L3 design: thickness ratio r_t=0.45,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.45_s1,cc17fc44,2,2,3,4,grid,0.35,3,1,0.45,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08635891994252076,0.08635891994252076,0.0007466372045958204,0.0007466372045958204,0.03733186022979102,0.0067101714606167895,0.008868626266452543,0.017241195507192518,True,7.5230785418412215e-06,7.5230785418412215e-06,0.18807696354603096,7.5230785418412215e-06,43,0,0.048314606741573035,43,20,6,6,0.13953488372093023,0.7217411646751802,0.5519342443965229,0.5916519434628975,0.4083480565371025,0.17337381811773978,0.41611844454773855,23,0.5348837209302325,0.08214285714285714,2.604651162790698,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,6.573742369625372e-09,1.4738038922088025e-14,0,0,0,1.8014602772912057e-15,58,44,81,192.94970899999987,True,completed,695,890,256,0.19999999999999954,0.19999999999999954,0.029107436980776693,0.0026524151948732764,2.5611510791366907,280,0,17.1777405317484,"[0.2910743698077675, 0.2619669328269907, 0.23577023954429185, 0.21118845782095125]",265 +S4_F2_L3_dis0.35_rt0.45_s3,S4,refinement,F2_L3_dis0.35_rt0.45,3,ok,L3 design: thickness ratio r_t=0.45,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.45_s3,15258578,2,2,3,4,grid,0.35,3,3,0.45,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08556486965140106,0.08556486965140106,0.0007577986968317418,0.0007577986968317418,0.03788993484158709,0.0056619495141934095,0.008967599269243271,0.017054610291923483,True,5.938671384474389e-06,5.938671384474389e-06,0.14846678461185975,5.938671384474389e-06,40,0,0.0449438202247191,40,15,10,3,0.075,0.6337355506147289,0.42331924067693366,0.5689655172413793,0.43103448275862066,0.1790466887269571,0.6403124928380418,24,0.6,0.08571428571428572,2.6,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,3.5311386377844805e-11,1.6168842772475292e-15,0,0,0,1.4263004170742953e-14,48,41,73,150.27824999999984,True,completed,695,890,256,0.19999999999999998,0.19999999999999998,0.02911011667652437,0.0026526593821482834,2.5611510791366907,280,0,17.176159256112538,"[0.2911011667652437, 0.26199105008871926, 0.23579194507984788, 0.2111158380661894]",205 +S4_F2_L3_dis0.35_rt0.3_s2,S4,refinement,F2_L3_dis0.35_rt0.3,2,ok,L3 design: thickness ratio r_t=0.3,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.3_s2,f58afda7,2,2,3,4,grid,0.35,3,2,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09249343442303941,0.09249343442303941,0.0009004774021561025,0.0009004774021561025,0.04502387010780512,0.003520762001299809,0.010235661037121426,0.01755886724142688,True,9.940047402330712e-06,9.940047402330712e-06,0.2485011850582673,9.940047402330712e-06,32,0,0.03567447045707915,32,18,5,7,0.21875,0.9546980909496658,0.5180723002658977,0.7192982456140351,0.2807017543859649,0.13493272524981312,0.44699746328935175,15,0.46875,0.05357142857142857,2.53125,3,True,abrupt-brittle,localized,abrupt-brittle/localized,5.133484691538827e-09,4.065763917881633e-14,0,0,0,1.1759556266671857e-14,54,33,68,149.20375000000013,True,completed,702,897,256,0.20000000000000043,0.20000000000000043,0.04597013007155577,0.0012411935119320057,2.5555555555555554,280,0,10.876627915163922,"[0.45970130071555676, 0.27582078042933394, 0.1654924682576006, 0.09898545059750727]",214 +S4_F2_L3_dis0.35_rt0.45_s2,S4,refinement,F2_L3_dis0.35_rt0.45,2,ok,L3 design: thickness ratio r_t=0.45,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.45_s2,c0d447bf,2,2,3,4,grid,0.35,3,2,0.45,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08611856151543217,0.08611856151543217,0.0007635969450560946,0.0007635969450560946,0.03817984725280473,0.0060996578825515775,0.009977204577281844,0.028425931029918857,True,6.3453481467833335e-06,6.3453481467833335e-06,0.15863370366958346,6.3453481467833335e-06,50,0,0.055741360089186176,50,20,8,13,0.26,0.5589137040426894,0.34996938054745297,0.5404411764705883,0.45955882352941174,0.1615348782203697,0.510292682591257,30,0.6,0.10714285714285714,2.6,3,True,intermediate,distributed,intermediate/distributed,1.68569696560837e-09,9.024139081096159e-15,0,0,0,4.258292908815364e-14,69,51,99,210.26212499999997,True,completed,702,897,256,0.19999999999999984,0.19999999999999984,0.029097479045741236,0.0026515077780431707,2.5555555555555554,280,0,17.18361921367827,"[0.2909747904574126, 0.2618773114116713, 0.23568958027050416, 0.21145831786041236]",262 +S4_F2_L3_dis0.35_rt0.3_s1,S4,refinement,F2_L3_dis0.35_rt0.3,1,ok,L3 design: thickness ratio r_t=0.3,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.3_s1,5b9e8b9f,2,2,3,4,grid,0.35,3,1,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09283705970363335,0.09283705970363335,0.0008656928796262622,0.0008656928796262622,0.043284643981313105,0.0037711145995827067,0.01788461816495815,0.01788461816495815,True,1.0115002075933816e-05,1.0115002075933816e-05,0.252875051898346,1.0115380735428337e-05,48,0,0.05393258426966292,48,22,7,41,0.8541666666666666,0.9962212435427823,0.0,0.4285714285714286,0.5714285714285714,0.20419788223050495,0.42278140592328034,27,0.5625,0.09642857142857143,2.5625,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,1.136244214793817e-08,5.439416293424602e-14,0,0,0,2.679588146119331e-15,63,49,89,199.79424999999992,True,completed,695,890,256,0.19999999999999948,0.19999999999999948,0.045977493112272824,0.001241392314031366,2.5611510791366907,280,0,10.874886083481018,"[0.45977493112272927, 0.27586495867363764, 0.16551897520418268, 0.09884113499945164]",263 +S4_F2_L3_dis0.35_rt0.3_s3,S4,refinement,F2_L3_dis0.35_rt0.3,3,ok,L3 design: thickness ratio r_t=0.3,H4/H2,study/runs/S4_F2_L3_dis0.35_rt0.3_s3,53802dcd,2,2,3,4,grid,0.35,3,3,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09259027723703267,0.09259027723703267,0.000917750927561146,0.000917750927561146,0.0458875463780573,0.00526218207063392,0.010301462568311413,0.03207713050868202,True,1.0585735800032936e-05,1.0585735800032936e-05,0.2646433950008232,1.0585735800032936e-05,69,0,0.07752808988764046,69,28,15,9,0.13043478260869565,0.8995823860793066,0.5396791910442712,0.36553837953091683,0.6344616204690832,0.22161208079759048,0.48020680643373914,43,0.6231884057971014,0.15357142857142858,2.5217391304347827,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,9.220869813456176e-09,9.577118340454626e-14,0,0,0,1.6323354795926387e-14,89,70,130,233.79424999999992,True,completed,695,890,256,0.20000000000000015,0.20000000000000015,0.045979474060317306,0.001241445799628567,2.5611510791366907,280,0,10.874417557366673,"[0.4597947406031726, 0.2758768443619036, 0.1655261066171424, 0.0988023084177812]",285 +S4_F3_L3_red0.5_s2,S4,refinement,F3_L3_red0.5,2,ok,L3 design with braces r=0.5 (does bracing help a mixed design?),H5,study/runs/S4_F3_L3_red0.5_s2,2d35112f,2,2,3,4,grid,0.35,3,2,0.6,0.2,0.5,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06651121606321977,0.06651121606321977,0.0005862425502234186,0.0005862425502234186,0.029312127511170932,0.0054298133237324735,0.009522778347723096,0.01232556148906092,True,3.4203665014964776e-06,3.4203665014964776e-06,0.08550916253741224,3.4203665014964776e-06,39,0,0.035944700460829496,39,12,15,11,0.28205128205128205,0.7194383387281913,0.1457702851408641,0.6466078066914498,0.3533921933085502,0.2634279259285375,0.3303495967547428,12,0.3076923076923077,0.04285714285714286,2.5641025641025643,3,False,abrupt-brittle,localized,abrupt-brittle/localized,1.1484594931819077e-10,6.2544172043102e-16,0,0,0,4.086124578632483e-15,37,40,64,230.30229200000008,True,completed,702,1085,256,0.1999999999999993,0.1999999999999993,0.014201100029365166,0.0030674376063428753,3.091168091168091,280,191,20.66051544907828,"[0.14201100029365218, 0.17041320035238264, 0.20449584042285904, 0.4830799589311077]",303 +S4_F3_L3_red0.5_s3,S4,refinement,F3_L3_red0.5,3,ok,L3 design with braces r=0.5 (does bracing help a mixed design?),H5,study/runs/S4_F3_L3_red0.5_s3,46dd7ef5,2,2,3,4,grid,0.35,3,3,0.6,0.2,0.5,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06792835300337244,0.06792835300337244,0.0005453099212073848,0.0005453099212073848,0.027265496060369238,0.005770236007108549,0.008275226777045263,0.017281624884803958,True,3.198012230520038e-06,3.198012230520038e-06,0.0799503057630009,3.198012230520038e-06,47,0,0.04315886134067952,47,17,7,4,0.0851063829787234,0.356859425385121,0.2769858410710492,0.6196625344352618,0.3803374655647383,0.16931703658442693,0.5787939363969918,22,0.46808510638297873,0.07857142857142857,2.4468085106382977,3,False,intermediate,localized,intermediate/localized,1.1022065949362934e-10,2.8380415844940957e-16,0,0,0,9.270181292921343e-15,52,48,82,243.6104580000001,True,completed,698,1089,256,0.20000000000000012,0.20000000000000012,0.014067798823115374,0.0030386445457929205,3.1203438395415475,280,199,20.92850604196558,"[0.14067798823115363, 0.16881358587738435, 0.20257630305286123, 0.4879321228386001]",309 +S4_F4_L3_sint0.5_s2,S4,refinement,F4_L3_sint0.5,2,ok,L3 design with s_int=0.5,H3,study/runs/S4_F4_L3_sint0.5_s2,a5bbf324,2,2,3,4,grid,0.35,3,2,0.6,0.2,0.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08086379185910014,0.08086379185910014,0.0004150089545700774,0.0004150089545700774,0.02075044772850387,0.0040689782658621535,0.0058814134910041135,0.028845178922892338,True,2.858084158906866e-06,2.858084158906866e-06,0.07145210397267174,2.858084158906866e-06,51,0,0.056856187290969896,51,20,13,7,0.13725490196078433,0.5934440037453728,0.5357694618316998,0.6192915690866511,0.38070843091334894,0.1381556722479142,0.5077282274135559,49,0.9607843137254902,0.175,2.549019607843137,3,True,intermediate,localized,intermediate/localized,1.5029833071309536e-10,2.1265289879163194e-15,0,0,0,2.1634564173650298e-14,69,52,100,196.96970799999986,True,completed,702,897,256,0.19999999999999973,0.19999999999999973,0.018647654686616066,0.00402789341230907,2.5555555555555554,280,0,12.81520076607376,"[0.18647654686616094, 0.22377185623939305, 0.2685262274872715, 0.3212253694071736]",253 +S4_F4_L3_sint0.5_s1,S4,refinement,F4_L3_sint0.5,1,ok,L3 design with s_int=0.5,H3,study/runs/S4_F4_L3_sint0.5_s1,b07be1a2,2,2,3,4,grid,0.35,3,1,0.6,0.2,0.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08084348685872705,0.08084348685872705,0.0004431254580822392,0.0004431254580822392,0.02215627290411196,0.005180592947583399,0.005519739235574947,0.018104057305287226,True,4.603575223645705e-06,4.603575223645705e-06,0.11508938059114274,4.603575223645705e-06,60,0,0.06741573033707865,60,28,14,1,0.016666666666666666,0.7857142290664431,0.7327016316664232,0.5171673819742489,0.48283261802575106,0.16976408270164686,0.6236912662852736,56,0.9333333333333333,0.2,2.5166666666666666,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,1.2620430240746531e-11,8.366534687706876e-16,0,0,0,3.8822859014590117e-14,75,61,107,234.41487499999994,True,completed,695,890,256,0.19999999999999982,0.19999999999999982,0.01865735085983989,0.004029987785725416,2.5611510791366907,280,0,13.084224719993495,"[0.18657350859839908, 0.2238882103180789, 0.2686658523816949, 0.32087242870182814]",302 +S4_F4_L3_sint1.5_s1,S4,refinement,F4_L3_sint1.5,1,ok,L3 design with s_int=1.5,H3,study/runs/S4_F4_L3_sint1.5_s1,2ad1d8ba,2,2,3,4,grid,0.35,3,1,0.6,0.2,0.0,1.0,segment,1.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08084348685872705,0.08084348685872705,0.00092880378679418,0.00092880378679418,0.046440189339709,0.006932243754662316,0.012774058556280757,0.017386148464586332,True,6.786459311631234e-06,6.786459311631234e-06,0.169661482790781,6.786459311631234e-06,44,0,0.04943820224719101,44,19,15,15,0.3409090909090909,0.6562346527412041,0.08260953141890016,0.46460176991150437,0.5353982300884956,0.204609673628998,0.5355220468555525,0,0.0,0.0,2.5,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,1.4676186556807153e-09,2.062821476577664e-15,0,0,0,3.2451173163105964e-15,56,45,81,162.09516700000017,True,completed,695,890,256,0.19999999999999982,0.19999999999999982,0.01865735085983989,0.004029987785725416,2.5611510791366907,280,0,13.084224719993495,"[0.18657350859839908, 0.2238882103180789, 0.2686658523816949, 0.32087242870182814]",235 +S4_F4_L3_sint0.5_s3,S4,refinement,F4_L3_sint0.5,3,ok,L3 design with s_int=0.5,H3,study/runs/S4_F4_L3_sint0.5_s3,ae369f19,2,2,3,4,grid,0.35,3,3,0.6,0.2,0.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07920008222775624,0.07920008222775624,0.00037480486032343165,0.00037480486032343165,0.01874024301617158,0.004732379686748354,0.004732379686748354,0.017785918041585965,True,3.3388403331674476e-06,3.3388403331674476e-06,0.08347100832918623,3.3388403331674476e-06,60,0,0.06741573033707865,60,29,10,0,0.0,0.7899923252844774,0.7343809930248313,0.533195020746888,0.46680497925311204,0.15935225588736313,0.6444247584575853,57,0.95,0.20357142857142857,2.5166666666666666,2,True,abrupt-brittle,distributed,abrupt-brittle/distributed,8.981906359847933e-11,3.958891187222064e-16,0,0,0,2.448115850226872e-14,76,61,107,198.16212499999983,True,completed,695,890,256,0.19999999999999987,0.19999999999999987,0.018659960703477564,0.004030551511951154,2.5611510791366907,280,0,12.905755150620747,"[0.1865996070347758, 0.22391952844173094, 0.26870343413007725, 0.3207774303934173]",262 +S4_F3_L3_red1_s1,S4,refinement,F3_L3_red1,1,ok,L3 design with braces r=1 (does bracing help a mixed design?),H5,study/runs/S4_F3_L3_red1_s1,e8309f12,2,2,3,4,grid,0.35,3,1,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0610661247978237,0.0610661247978237,0.0005425666358670305,0.0005425666358670305,0.027128331793351525,0.004970420453747439,0.009655288738156693,0.017407367445308436,True,3.4712651692124946e-06,3.4712651692124946e-06,0.0867816292303122,3.4712651692124946e-06,58,0,0.04574132492113565,58,29,11,14,0.2413793103448276,0.5089781528539684,0.20321031502386874,0.6472315436241611,0.3527684563758389,0.16715465522315176,0.7129301860457588,19,0.3275862068965517,0.06785714285714285,2.4827586206896552,3,True,intermediate,localized,intermediate/localized,5.502571294509084e-12,4.137656056858142e-16,0,0,0,2.830547857678921e-14,76,59,105,329.68545900000004,True,completed,697,1268,256,0.20000000000000037,0.20000000000000037,0.011501308693950565,0.0024842826778933218,3.6384505021520805,280,384,27.70502223687673,"[0.11501308693950545, 0.13801570432740654, 0.16561884519288786, 0.5813523635401983]",424 +S4_F4_L3_sint1.5_s2,S4,refinement,F4_L3_sint1.5,2,ok,L3 design with s_int=1.5,H3,study/runs/S4_F4_L3_sint1.5_s2,8db247dc,2,2,3,4,grid,0.35,3,2,0.6,0.2,0.0,1.0,segment,1.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08086379185910014,0.08086379185910014,0.0008440498376945549,0.0008440498376945549,0.042202491884727744,0.006375840227340003,0.011603651727039841,0.01775513126781575,True,5.926686403448446e-06,5.926686403448446e-06,0.14816716008621134,5.926686403448446e-06,52,0,0.057971014492753624,52,25,14,13,0.25,0.5470513716958679,0.12624524686124566,0.2522123893805309,0.7477876106194691,0.24449054071311785,0.513117528679809,0,0.0,0.0,2.423076923076923,3,False,intermediate,distributed,intermediate/distributed,3.574498836088625e-11,9.32351607503202e-16,0,0,0,1.200515139926454e-14,68,53,95,229.1295419999999,True,completed,702,897,256,0.19999999999999973,0.19999999999999973,0.018647654686616066,0.00402789341230907,2.5555555555555554,280,0,12.81520076607376,"[0.18647654686616094, 0.22377185623939305, 0.2685262274872715, 0.3212253694071736]",282 +S4_F4_L3_sint1.5_s3,S4,refinement,F4_L3_sint1.5,3,ok,L3 design with s_int=1.5,H3,study/runs/S4_F4_L3_sint1.5_s3,6452f5e6,2,2,3,4,grid,0.35,3,3,0.6,0.2,0.0,1.0,segment,1.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07920008222775624,0.07920008222775624,0.0008193004779891412,0.0008193004779891412,0.04096502389945706,0.006612190829055222,0.011111699945076036,0.016003824985474417,True,5.808384064315475e-06,5.808384064315475e-06,0.14520960160788696,5.808384064315475e-06,40,0,0.0449438202247191,40,18,8,12,0.3,0.39526091470811364,0.18026606671965933,0.4505494505494505,0.5494505494505495,0.21625248771868757,0.40641946341371255,0,0.0,0.0,2.575,3,False,intermediate,distributed,intermediate/distributed,4.185365234806116e-10,3.111522289982652e-15,0,0,0,1.779118226700857e-14,53,41,75,160.52762499999994,True,completed,695,890,256,0.19999999999999987,0.19999999999999987,0.018659960703477564,0.004030551511951154,2.5611510791366907,280,0,12.905755150620747,"[0.1865996070347758, 0.22391952844173094, 0.26870343413007725, 0.3207774303934173]",229 +S4_F5_ord_red1_notch_s2,S4,refinement,F5_ord_red1_notch,2,ok,ordered fully braced lattice with edge notch r=0.12W,H7,study/runs/S4_F5_ord_red1_notch_s2,64da9261,2,2,3,4,grid,0.0,0,2,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,notch,0.12,0.0,0.5,0,1,clamped,0.001,0.25,True,1,0.07494103601849122,0.07494103601849122,0.0007604682097182007,0.0007604682097182007,0.038023410485910035,0.010147553998727207,0.010147553998727207,0.012245478378358545,True,5.0198830016983436e-06,5.0198830016983436e-06,0.12844474505872536,5.0198830016983436e-06,32,0,0.0320962888665998,32,5,17,0,0.0,0.731592086695498,0.23136732272245544,0.9072463768115941,0.0927536231884058,0.034618142010015264,0.22880859374999998,17,0.53125,0.060714285714285714,2.53125,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.949835156068561e-11,2.1287538221411344e-17,0,0,0,1.3498847633982375e-15,23,33,50,114.95279200000004,True,completed,567,997,256,0.20000000000000195,0.19541021313885737,0.012801210833506573,0.0027650615400374194,3.5670840787119857,280,256,27.12417026312732,"[0.1280121083350644, 0.15361453000207723, 0.1843374360024928, 0.5340359256603604]",175 +S4_F3_L3_red1_s3,S4,refinement,F3_L3_red1,3,ok,L3 design with braces r=1 (does bracing help a mixed design?),H5,study/runs/S4_F3_L3_red1_s3,e6360122,2,2,3,4,grid,0.35,3,3,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05971671336836108,0.05971671336836108,0.0005649657779028762,0.0005649657779028762,0.02824828889514381,0.005139642409252717,0.010079926069640454,0.013294067360720294,True,3.1525417219220825e-06,3.1525417219220825e-06,0.07881354304805213,3.1525417219220825e-06,46,0,0.03639240506329114,46,15,25,10,0.21739130434782608,0.9038078367227567,0.06680170315601372,0.7267561983471074,0.2732438016528926,0.18340089787554062,0.7619046359022942,16,0.34782608695652173,0.05714285714285714,2.347826086956522,3,True,abrupt-brittle,localized,abrupt-brittle/localized,4.881560709096733e-12,2.9206878375043866e-16,0,0,0,3.0898493192615095e-15,44,47,75,350.41108399999985,True,completed,697,1264,256,0.1999999999999998,0.1999999999999998,0.011501907953361626,0.002484412117926111,3.6269727403156384,280,384,27.701095982992303,"[0.11501907953361634, 0.13802289544033966, 0.1656274745284077, 0.5813305504976375]",459 +S4_F3_L3_red0.5_s1,S4,refinement,F3_L3_red0.5,1,ok,L3 design with braces r=0.5 (does bracing help a mixed 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(movie),representative,study/runs/S4_F10_L3_movie_s1,d1e0ff69,2,2,3,4,grid,0.35,3,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08084348685872705,0.08084348685872705,0.0006380202818826803,0.0006380202818826803,0.03190101409413401,0.006932243754662316,0.009230002727628568,0.021803420030638388,True,5.674481595693485e-06,5.674481595693485e-06,0.14186203989233725,5.674481595693485e-06,47,0,0.052808988764044947,47,19,11,9,0.19148936170212766,0.4825730487894214,0.41686795307830965,0.5878731343283582,0.4121268656716418,0.1657551069854661,0.6789485733178156,28,0.5957446808510638,0.1,2.5531914893617023,3,False,intermediate,distributed,intermediate/distributed,3.186996298071534e-11,9.414725277138543e-16,0,0,0,1.2538725585674546e-14,60,48,88,169.914667,True,completed,695,890,256,0.19999999999999982,0.19999999999999982,0.01865735085983989,0.004029987785725416,2.5611510791366907,280,0,13.084224719993495,"[0.18657350859839908, 0.2238882103180789, 0.2686658523816949, 0.32087242870182814]",235 +S4_F9_n0_4x1_s1,S4,refinement,F9_n0_4x1,1,ok,"anisotropic level-0: 4x1 (vertical level-0 walls only, aligned with the load)",H2,study/runs/S4_F9_n0_4x1_s1,3c3a6c46,4,1,3,4,grid,0.35,0,1,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03535008402172887,0.03535008402172887,0.0002132737036399035,0.0002132737036399035,0.010663685181995175,0.004383273462122302,0.008697851511805786,0.029021549821552074,True,1.4488430606492604e-06,1.4488430606492604e-06,0.03622107651623154,1.4488430606492604e-06,69,0,0.07180020811654526,69,35,10,27,0.391304347826087,0.80309110536704,0.19634383586427306,0.24284351145038163,0.7571564885496184,0.24585004814398476,0.491297381635237,46,0.6666666666666666,0.16370106761565836,2.5652173913043477,2,True,abrupt-brittle,distributed,abrupt-brittle/distributed,4.429482069880553e-11,1.090959768114403e-15,0,0,0,2.3531241618196856e-14,100,70,134,236.435833,True,completed,758,961,256,0.19999999999999982,0.19999999999999982,0.017804956823174862,0.00384587067380577,2.5356200527704487,281,0,13.240210566018728,"[0.2337929159553259, 0.19868924056080683, 0.26006118957517665, 0.307456653908692]",289 +S4_F9_n0_4x1_L1_s3,S4,refinement,F9_n0_4x1_L1,3,ok,aligned straight level-0 stringers + disordered finer levels,H4,study/runs/S4_F9_n0_4x1_L1_s3,6396d860,4,1,3,4,grid,0.35,1,3,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.07549847875564489,0.07549847875564489,0.0008246678072763176,0.0008246678072763176,0.041233390363815875,0.005195920078143333,0.014573649269496482,0.015238934971433943,True,6.963447968496787e-06,6.963447968496787e-06,0.17408619921241958,6.963447968496787e-06,58,0,0.060669456066945605,58,27,9,41,0.7068965517241379,0.3454640440908891,0.05085969371033102,0.3346518987341772,0.6653481012658228,0.25927927123110445,0.6469844836471016,39,0.6724137931034483,0.13448275862068965,2.396551724137931,3,False,intermediate,distributed,intermediate/distributed,3.305766678566856e-11,5.965123233770725e-16,0,0,0,9.001350822234861e-15,70,59,101,218.01999999999998,True,completed,761,956,256,0.20000000000000012,0.20000000000000012,0.017966291082642784,0.0038807188738508407,2.512483574244415,290,0,13.304940009532002,"[0.26949436623964157, 0.16253165052869753, 0.2583990627057202, 0.30957492052594054]",267 +S5_H04_ord_sint0.7_s13,S5,holdout,H04_ord_sint0.7,13,ok,ordered hierarchy with s_int = 0.7 (interpolation of the s_int law),holdout,study/runs/S5_H04_ord_sint0.7_s13,e89242da,2,2,3,4,grid,0.0,0,13,0.6,0.2,0.0,1.0,segment,0.7,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0012357214468022527,0.0012357214468022527,0.06178607234011264,0.012357214464831163,0.012357214464831163,0.0183516864910416,True,7.793065628133898e-06,7.793065628133898e-06,0.19482664070334696,7.793065628133898e-06,38,0,0.05,38,3,35,0,0.0,0.9785898551140289,0.020278048102143648,0.6657407407407407,0.33425925925925926,0.10348849839585726,0.48754111842105263,36,0.9473684210526315,0.12857142857142856,2.4210526315789473,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.828120333141599e-12,3.014629548506561e-17,0,0,0,4.1302426453927945e-15,25,39,60,188.91749999999996,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",249 +S5_H04_ord_sint0.7_s11,S5,holdout,H04_ord_sint0.7,11,ok,ordered hierarchy with s_int = 0.7 (interpolation of the s_int law),holdout,study/runs/S5_H04_ord_sint0.7_s11,85bcf046,2,2,3,4,grid,0.0,0,11,0.6,0.2,0.0,1.0,segment,0.7,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.001213919296425369,0.001213919296425369,0.06069596482126845,0.012139192961118631,0.012139192961118631,0.012139192961118631,True,7.368000289266452e-06,7.368000289266452e-06,0.18420000723166083,7.378083663219338e-06,32,0,0.042105263157894736,32,1,32,0,0.0,0.9906807979405939,0.0,0.6923076923076923,0.3076923076923077,0.12572604087266695,0.4515625000000001,31,0.96875,0.11071428571428571,2.5,3,True,abrupt-brittle,localized,abrupt-brittle/localized,1.3714383729640237e-12,2.2477371901027152e-17,0,0,0,7.577058904532767e-15,16,33,47,169.81291700000003,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",274 +S5_H01_dis0.08_s12,S5,holdout,H01_dis0.08,12,ok,disorder between 0.05 and 0.1 (transition region),holdout,study/runs/S5_H01_dis0.08_s12,9ca685de,2,2,3,4,grid,0.08,0,12,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0884498588923547,0.0884498588923547,0.0004896852478052424,0.0004896852478052424,0.024484262390262117,0.004770957662551697,0.0056417830439173255,0.03426799810010108,True,2.30622297987572e-06,2.30622297987572e-06,0.057655574496892945,2.30622297987572e-06,52,0,0.06018518518518518,52,31,6,1,0.019230769230769232,0.2150819118397544,0.3928733416873225,0.615909090909091,0.3840909090909091,0.15672361639081855,0.6695394168812128,35,0.6730769230769231,0.125,2.4615384615384617,3,False,progressive,localized,progressive/localized,4.777678941845155e-11,6.339540068711197e-16,0,0,0,8.429109547999458e-14,97,53,118,265.667667,True,completed,669,864,256,0.20000000000000018,0.20000000000000018,0.018673103694941982,0.0040333903981074675,2.5829596412556053,280,0,14.361225249096925,"[0.18531865713937715, 0.22347697793889476, 0.26879243702260536, 0.3224119278991225]",331 +S5_H02_L3_dis0.5_rt0.5_s11,S5,holdout,H02_L3_dis0.5_rt0.5,11,ok,level-selective design with new disorder and thickness-ratio values,holdout,study/runs/S5_H02_L3_dis0.5_rt0.5_s11,4729c5dd,2,2,3,4,grid,0.5,3,11,0.5,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.081566495418604,0.081566495418604,0.0007492305991308515,0.0007492305991308515,0.037461529956542575,0.0077496367385472345,0.009397986200509594,0.0292777182241891,True,5.051505030319805e-06,5.051505030319805e-06,0.12628762575799518,5.051505030319805e-06,35,0,0.03867403314917127,35,12,9,5,0.14285714285714285,0.421969953296797,0.29073061678106893,0.6849279835390947,0.3150720164609053,0.12455839569910558,0.5376280096066063,18,0.5142857142857142,0.06428571428571428,2.5142857142857142,3,False,intermediate,localized,intermediate/localized,2.3098571786802625e-10,1.0007002727548985e-15,0,0,0,1.6264894400880272e-14,54,36,77,248.662625,True,completed,710,905,256,0.1999999999999999,0.1999999999999999,0.025025467377023863,0.003128183422127983,2.5492957746478875,280,0,16.37932204084186,"[0.25025467377023874, 0.2502546737702386, 0.2502546737702388, 0.24923597868928402]",352 +S5_H01_dis0.08_s13,S5,holdout,H01_dis0.08,13,ok,disorder between 0.05 and 0.1 (transition region),holdout,study/runs/S5_H01_dis0.08_s13,c79d9713,2,2,3,4,grid,0.08,0,13,0.6,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09230837044101317,0.09230837044101317,0.000526340513099553,0.000526340513099553,0.02631702565497765,0.004745704370515115,0.0060508794576218106,0.01979581828712464,True,3.848162619764707e-06,3.848162619764707e-06,0.09620406549411772,3.848162619764707e-06,44,0,0.05158264947245018,44,23,7,3,0.06818181818181818,0.557518429002919,0.5671178896688124,0.6461988304093567,0.3538011695906433,0.16873763758412563,0.6646492594858265,27,0.6136363636363636,0.09642857142857143,2.522727272727273,3,False,intermediate,localized,intermediate/localized,2.2622649454929132e-11,6.260341909078958e-16,0,0,0,2.2671701325482816e-14,66,45,87,273.359667,True,completed,658,853,256,0.1999999999999999,0.1999999999999999,0.018663908792342008,0.004031404299145873,2.592705167173252,280,0,14.411279890387872,"[0.18664409449925162, 0.2230041102029425, 0.2683057574666205, 0.3220460378311869]",354 +S5_H04_ord_sint0.7_s12,S5,holdout,H04_ord_sint0.7,12,ok,ordered hierarchy with s_int = 0.7 (interpolation of the s_int law),holdout,study/runs/S5_H04_ord_sint0.7_s12,2057849e,2,2,3,4,grid,0.0,0,12,0.6,0.2,0.0,1.0,segment,0.7,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.10000000002582585,0.10000000002582585,0.0012197946938337838,0.0012197946938337838,0.06098973469168919,0.012197946935187607,0.012197946935187607,0.01685228530753824,True,7.531838487505641e-06,7.531838487505641e-06,0.18829596218764055,7.531838487505641e-06,37,0,0.04868421052631579,37,4,34,0,0.0,0.985221689773046,0.012260355032158346,0.5656725888324874,0.43432741116751267,0.1649195900117671,0.5012246621621621,33,0.8918918918918919,0.11785714285714285,2.4054054054054053,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,2.074866002968302e-12,2.6756145450227685e-17,0,0,0,5.735476189728499e-15,25,38,58,294.048041,True,completed,565,760,256,0.2000000000000005,0.2000000000000005,0.018628912071534977,0.004023845007451555,2.690265486725664,280,0,15.532407407407446,"[0.18628912071534928, 0.22354694485841892, 0.26825633383010317, 0.32190760059612405]",363 +S5_H02_L3_dis0.5_rt0.5_s13,S5,holdout,H02_L3_dis0.5_rt0.5,13,ok,level-selective design with new disorder and thickness-ratio values,holdout,study/runs/S5_H02_L3_dis0.5_rt0.5_s13,89eb54d1,2,2,3,4,grid,0.5,3,13,0.5,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08208072714731732,0.08208072714731732,0.0006845061079094161,0.0006845061079094161,0.034225305395470806,0.007692059055275226,0.008489415981485149,0.017170661700054133,True,6.686194007889917e-06,6.686194007889917e-06,0.16715485019724807,6.686194007889917e-06,48,0,0.05303867403314917,48,20,9,3,0.0625,0.6688597863424631,0.5584538631368059,0.4193548387096774,0.5806451612903226,0.17500364447099592,0.6219553942754852,30,0.625,0.10714285714285714,2.4583333333333335,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,1.1516300609106593e-10,7.603889644445363e-16,0,0,0,1.5328748537183903e-14,58,49,86,294.016833,True,completed,710,905,256,0.19999999999999982,0.19999999999999982,0.02501134207845088,0.00312641775980636,2.5492957746478875,280,0,16.373061506495898,"[0.2501134207845091, 0.2501134207845089, 0.2501134207845088, 0.24965973764647212]",386 +S5_H03_L2_dis0.7_rt0.8_s12,S5,holdout,H03_L2_dis0.7_rt0.8,12,ok,"level-selective (levels >= 2) organic fine levels, weak thickness hierarchy",holdout,study/runs/S5_H03_L2_dis0.7_rt0.8_s12,4a94accc,2,2,3,4,grid,0.7,2,12,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04003231158890344,0.04003231158890344,0.00033601614521024754,0.00033601614521024754,0.016800807260512376,0.005973936431414184,0.00929480044549884,0.02893526307942031,True,2.3916894436114043e-06,2.3916894436114043e-06,0.059792236090285084,2.3916894436114043e-06,52,0,0.054679284963196635,52,25,12,6,0.11538461538461539,0.4788250211062786,0.2991876727599679,0.43288590604026844,0.5671140939597316,0.17844826607146855,0.3880271418907378,36,0.6923076923076923,0.127208480565371,2.3846153846153846,3,True,intermediate,distributed,intermediate/distributed,1.6117222893049466e-10,5.779104892326109e-16,0,0,0,6.357113564149276e-14,79,53,106,330.67229199999997,True,completed,750,951,256,0.20000000000000007,0.20000000000000007,0.01053374274182248,0.005393276283813112,2.536,283,0,9.755841660858469,"[0.10534149381335194, 0.16854197175817287, 0.279175079456883, 0.44694145497159304]",401 +S5_H02_L3_dis0.5_rt0.5_s12,S5,holdout,H02_L3_dis0.5_rt0.5,12,ok,level-selective design with new disorder and thickness-ratio values,holdout,study/runs/S5_H02_L3_dis0.5_rt0.5_s12,d6c5d675,2,2,3,4,grid,0.5,3,12,0.5,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.08076110437191286,0.08076110437191286,0.0006923920975770179,0.0006923920975770179,0.03461960487885089,0.008549662559604914,0.008604124496622696,0.034666412029287726,True,6.405811932830915e-06,6.405811932830915e-06,0.16014529832077284,6.405811932830915e-06,59,0,0.06469298245614036,59,20,11,1,0.01694915254237288,0.5882945109453954,0.5333493993349101,0.3544139465875371,0.6455860534124629,0.22757934427180085,0.41518061194647926,38,0.6440677966101694,0.1357142857142857,2.5084745762711864,3,False,intermediate,distributed,intermediate/distributed,4.659777005150303e-10,4.285663016307153e-15,0,0,0,1.613191593018819e-14,75,60,114,342.416917,True,completed,717,912,256,0.20000000000000004,0.20000000000000004,0.024976551311095146,0.0031220689138868932,2.5439330543933054,280,0,16.278645731349396,"[0.2497655131109515, 0.24976551311095152, 0.2497655131109513, 0.2507034606671444]",423 +S5_H03_L2_dis0.7_rt0.8_s11,S5,holdout,H03_L2_dis0.7_rt0.8,11,ok,"level-selective (levels >= 2) organic fine levels, weak thickness hierarchy",holdout,study/runs/S5_H03_L2_dis0.7_rt0.8_s11,c8ebab7d,2,2,3,4,grid,0.7,2,11,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.040183941607184456,0.040183941607184456,0.0003070578814026666,0.0003070578814026666,0.015352894070133329,0.007263103308042168,0.008082632415812863,0.016926328291725516,True,2.300556126238898e-06,2.300556126238898e-06,0.057513903155972344,2.300556126238898e-06,40,0,0.04206098843322818,40,18,8,4,0.1,0.5160447728172814,0.43367629171239036,0.4949494949494949,0.5050505050505051,0.16647768118449943,0.4627496941831083,26,0.65,0.09352517985611511,2.425,3,False,intermediate,distributed,intermediate/distributed,5.027758120684014e-11,1.761865221470774e-16,0,0,0,1.748884303916401e-14,53,41,75,333.262041,True,completed,756,951,256,0.20000000000000034,0.20000000000000034,0.010649457998078664,0.0054525224950162775,2.515873015873016,278,0,9.672176182934868,"[0.10649457998078647, 0.1703963030096701, 0.2730873996735049, 0.45002171733603724]",424 +S5_H01_dis0.08_s11,S5,holdout,H01_dis0.08,11,ok,disorder between 0.05 and 0.1 (transition 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interfaces,holdout,study/runs/S5_H09_ord_red1_sint0.5_s13,73cc54bc,2,2,3,4,grid,0.0,0,13,0.6,0.2,1.0,1.0,segment,0.5,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.0762985419654385,0.0762985419654385,0.00048015706243873245,0.00048015706243873245,0.024007853121936623,0.005661059319217088,0.006440475873892372,0.04332638582512601,True,5.2985210757553565e-06,5.2985210757553565e-06,0.13246302689388262,5.2985210757553565e-06,79,0,0.07775590551181102,79,40,6,1,0.012658227848101266,0.4252571986751387,0.7029002024903521,0.5727683461117197,0.4272316538882804,0.14607460051644547,0.38797468354430376,52,0.6582278481012658,0.18571428571428572,2.569620253164557,3,True,intermediate,distributed,intermediate/distributed,1.6270028130510155e-11,5.419428411222109e-17,0,0,0,4.2043744271815124e-14,124,80,163,258.584208,True,completed,567,1016,256,0.20000000000000195,0.20000000000000195,0.012801210833506573,0.0027650615400374194,3.583774250440917,280,256,27.12417026312732,"[0.1280121083350644, 0.15361453000207723, 0.1843374360024928, 0.5340359256603604]",357 +S5_H08_L3_red1_dis0.7_s11,S5,holdout,H08_L3_red1_dis0.7,11,ok,level-selective + braces + organic finest level,holdout,study/runs/S5_H08_L3_red1_dis0.7_s11,fc081819,2,2,3,4,grid,0.7,3,11,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.05682258755258686,0.05682258755258686,0.000488163260896725,0.000488163260896725,0.02440816304483625,0.006930578655418641,0.008923178426767257,0.02357798383707783,True,3.09085010206803e-06,3.09085010206803e-06,0.07727125255170086,3.09085010206803e-06,56,0,0.04327666151468315,56,21,14,6,0.10714285714285714,0.42440541775558877,0.2773198760424855,0.6585365853658536,0.34146341463414637,0.17857672488922027,0.6641971803755327,19,0.3392857142857143,0.06785714285714285,2.25,2,False,intermediate,localized,intermediate/localized,1.8136239474049217e-11,4.619095970785994e-17,0,0,0,9.728608193392688e-15,66,57,101,440.225458,True,completed,722,1294,256,0.1999999999999997,0.1999999999999997,0.011388948581409774,0.0024600128935845108,3.5844875346260388,280,384,27.79905716651903,"[0.11388948581409793, 0.13666738297691744, 0.164000859572301, 0.5854422716366842]",575 +S5_H07_dis0.35_red1_rt0.45_s13,S5,holdout,H07_dis0.35_red1_rt0.45,13,ok,fully braced disordered design with stronger thickness hierarchy,holdout,study/runs/S5_H07_dis0.35_red1_rt0.45_s13,1be4958f,2,2,3,4,grid,0.35,0,13,0.45,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06011891378887705,0.06011891378887705,0.0004597089095090901,0.0004597089095090901,0.022985445475454502,0.003669861769170105,0.010767528953510267,0.01990285719423803,True,3.425734658089202e-06,3.425734658089202e-06,0.08564336645223,3.425734658089202e-06,62,0,0.04552129221732746,62,28,14,27,0.43548387096774194,0.7818226945817086,0.10322162552917076,0.703395061728395,0.29660493827160495,0.13913474154752606,0.34394376479988037,20,0.3225806451612903,0.07142857142857142,2.403225806451613,3,True,abrupt-brittle,localized,abrupt-brittle/localized,2.986604540515701e-09,6.276901426496366e-15,0,0,0,1.0817443597060605e-13,76,63,110,501.2306659999999,True,completed,760,1362,256,0.20000000000000012,0.20000000000000012,0.02021992474750104,0.0018425406426160326,3.5842105263157893,280,426,19.76744995167196,"[0.2020457532102703, 0.17962406416100393, 0.16364473198678312, 0.45468545064194177]",612 +S5_H07_dis0.35_red1_rt0.45_s11,S5,holdout,H07_dis0.35_red1_rt0.45,11,ok,fully braced disordered design with stronger thickness hierarchy,holdout,study/runs/S5_H07_dis0.35_red1_rt0.45_s11,53ccb021,2,2,3,4,grid,0.35,0,11,0.45,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.058231322936383396,0.058231322936383396,0.0003739399928621179,0.0003739399928621179,0.018696999643105894,0.003766398762165174,0.007057223758598496,0.020316224703440192,True,2.3701343835715222e-06,2.3701343835715222e-06,0.059253359589288,2.3701343835715222e-06,69,0,0.050586510263929615,69,35,9,6,0.08695652173913043,0.2334521749137584,0.40874721602001673,0.5995121130551817,0.4004878869448183,0.17229480886699716,0.44983030166305055,22,0.3188405797101449,0.07885304659498207,2.4927536231884058,3,True,progressive,distributed,progressive/distributed,6.87134999726781e-11,7.224115676848546e-16,0,0,0,8.237553773128685e-14,91,70,125,621.92725,True,completed,760,1364,256,0.20000000000000018,0.20000000000000018,0.020064815337979918,0.0018284062976734203,3.5894736842105264,279,426,20.05013324790248,"[0.20180299442132804, 0.1797838751327586, 0.16180066704234736, 0.4566124634035634]",758 +S5_H07_dis0.35_red1_rt0.45_s12,S5,holdout,H07_dis0.35_red1_rt0.45,12,ok,fully braced disordered design with stronger thickness hierarchy,holdout,study/runs/S5_H07_dis0.35_red1_rt0.45_s12,c6b58ec2,2,2,3,4,grid,0.35,0,12,0.45,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.04911029743398353,0.04911029743398353,0.0003520637313562095,0.0003520637313562095,0.017603186567810476,0.004133114947259063,0.007512176099595593,0.03414874039760331,True,2.1335610904618056e-06,2.1335610904618056e-06,0.05333902726154517,2.1335610904618056e-06,63,0,0.04568527918781726,63,25,12,5,0.07936507936507936,0.45270610298121267,0.36305441700517105,0.48427754677754675,0.5157224532224532,0.19236871181924087,0.5338684160194488,23,0.36507936507936506,0.08156028368794327,2.5238095238095237,3,True,intermediate,distributed,intermediate/distributed,5.11177621404682e-10,3.701574573400071e-15,0,0,0,2.0247219778749827e-14,85,64,123,611.4566670000002,True,completed,763,1379,256,0.19999999999999987,0.19999999999999987,0.019961150585155112,0.0018189598470722598,3.614678899082569,282,426,19.78606521966827,"[0.19709272170716163, 0.1804243575480295, 0.1638685685989838, 0.45861435214582535]",750 +S5_H10_dis1_rt0.3_s13,S5,holdout,H10_dis1_rt0.3,13,ok,fully organic with strong thickness hierarchy (f0 ~ 0.45),holdout,study/runs/S5_H10_dis1_rt0.3_s13,8c48e0cf,2,2,3,4,grid,1.0,0,13,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.03473037846782297,0.03473037846782297,0.0002180508924449819,0.0002180508924449819,0.010902544622249094,0.002782015416894043,0.0072394524045160495,0.02424821695509302,True,1.3222084638212737e-06,1.3222084638212737e-06,0.03305521159553174,1.3222084638212737e-06,40,0,0.04201680672268908,40,19,11,13,0.325,0.8098790057999095,0.3545581439566536,0.295774647887324,0.704225352112676,0.27882211167740256,0.5664542943299977,16,0.4,0.05860805860805861,2.475,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,1.3798546473618352e-09,3.230337474741793e-14,0,0,0,2.2581848632569377e-14,63,41,84,235.22337500000003,True,completed,753,952,256,0.20000000000000057,0.20000000000000057,0.04518451483039914,0.0012199819004207765,2.5285524568393094,273,0,8.845429910966727,"[0.4514796722186396, 0.2711956480016987, 0.17728117890597123, 0.10004350087369007]",296 +S5_H10_dis1_rt0.3_s11,S5,holdout,H10_dis1_rt0.3,11,ok,fully organic with strong thickness hierarchy (f0 ~ 0.45),holdout,study/runs/S5_H10_dis1_rt0.3_s11,5531dc41,2,2,3,4,grid,1.0,0,11,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.022593585993724154,0.022593585993724154,8.726251047494159e-05,8.726251047494159e-05,0.004363125523747079,0.0018380274415351824,0.00393816056117932,0.04992142591786233,True,1.3937927446563138e-06,1.3937927446563138e-06,0.034844818616407876,1.3937927446563138e-06,67,0,0.06964656964656965,67,32,11,2,0.029850746268656716,0.5486036696972875,0.875759584981565,0.3239457831325301,0.6760542168674699,0.24949715027229347,0.6229321585105172,34,0.5074626865671642,0.11683848797250859,2.5223880597014925,3,False,intermediate,distributed,intermediate/distributed,1.5004497586735652e-08,8.002464801717596e-14,0,0,0,1.4615618039028542e-13,114,68,149,305.67125,True,completed,755,962,256,0.19999999999999982,0.19999999999999982,0.04271816993300497,0.001153390588191134,2.548344370860927,291,0,10.369939959486327,"[0.4730875603873648, 0.27087911614053556, 0.16122903653161028, 0.09480428694049085]",372 +S5_H08_L3_red1_dis0.7_s12,S5,holdout,H08_L3_red1_dis0.7,12,ok,level-selective + braces + organic finest level,holdout,study/runs/S5_H08_L3_red1_dis0.7_s12,722d1679,2,2,3,4,grid,0.7,3,12,0.6,0.2,1.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.053538483821224454,0.053538483821224454,0.0005284523360658204,0.0005284523360658204,0.026422616803291017,0.00693041062842097,0.010085197385854536,0.02425504061234015,True,3.4761289444973303e-06,3.4761289444973303e-06,0.08690322361243354,3.4761289444973303e-06,65,0,0.05003849114703618,65,30,14,5,0.07692307692307693,0.5277354591289074,0.22132220174472048,0.47916666666666663,0.5208333333333334,0.19028339520370366,0.6174089672779636,21,0.3230769230769231,0.075,2.4615384615384617,3,True,intermediate,distributed,intermediate/distributed,5.008714569741497e-11,1.3691597206674016e-16,0,0,0,6.579125786478336e-14,85,66,120,590.9482079999999,True,completed,727,1299,256,0.19999999999999937,0.19999999999999937,0.011323926372210639,0.002445968096397498,3.5735900962861074,280,384,28.192392418604722,"[0.11323926372210673, 0.13588711646652804, 0.1630645397598337, 0.5878090800515323]",699 +S5_H11_4x1_L1_rt0.45_s11,S5,holdout,H11_4x1_L1_rt0.45,11,ok,aligned straight stringers (4x1) with disordered finer levels and strong hierarchy,holdout,study/runs/S5_H11_4x1_L1_rt0.45_s11,3ecea493,4,1,3,4,grid,0.35,1,11,0.45,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09364143165385079,0.09364143165385079,0.0013426908511846914,0.0013426908511846914,0.06713454255923457,0.005021238733859561,0.01630557005238913,0.017065066191378552,True,1.1858816019694845e-05,1.1858816019694845e-05,0.29647040049237083,1.1858816019694845e-05,57,0,0.059873949579831935,57,30,17,32,0.5614035087719298,0.34864710211071936,0.04159078107069814,0.3751923076923077,0.6248076923076923,0.24619362552028864,0.40543062846918027,32,0.5614035087719298,0.1103448275862069,2.4210526315789473,3,False,intermediate,distributed,intermediate/distributed,2.6034820933317747e-10,1.1101158916844436e-15,0,0,0,2.1427930389869473e-15,78,58,105,245.244375,True,completed,757,952,256,0.20000000000000018,0.20000000000000018,0.026917825922198185,0.00245288688716031,2.5151915455746368,290,0,19.262112257284052,"[0.40376738883297214, 0.18364088914910334, 0.21747909730194423, 0.19511262471597923]",313 +S5_H11_4x1_L1_rt0.45_s13,S5,holdout,H11_4x1_L1_rt0.45,13,ok,aligned straight stringers (4x1) with disordered finer levels and strong hierarchy,holdout,study/runs/S5_H11_4x1_L1_rt0.45_s13,2544290a,4,1,3,4,grid,0.35,1,13,0.45,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09373454344480336,0.09373454344480336,0.0012995689160394447,0.0012995689160394447,0.06497844580197223,0.004254063782675092,0.01565495594900979,0.01754896665633423,True,1.1667872100182865e-05,1.1667872100182865e-05,0.2916968025045712,1.1667872100182865e-05,55,0,0.05735140771637122,55,22,13,26,0.4727272727272727,0.37793668252845725,0.09880787255568063,0.3591101694915254,0.6408898305084746,0.2700235411806886,0.5105447337116923,27,0.4909090909090909,0.09310344827586207,2.5454545454545454,3,False,intermediate,distributed,intermediate/distributed,2.7268568429073716e-10,1.256073535788269e-15,0,0,0,1.0889298493951933e-14,62,56,95,236.511167,True,completed,764,959,256,0.2000000000000003,0.2000000000000003,0.026990607429160433,0.0024595191019822446,2.5104712041884816,290,0,18.57422755607397,"[0.4048591114374057, 0.18281435236991736, 0.21639675356488916, 0.1959297826277869]",303 +S5_H10_dis1_rt0.3_s12,S5,holdout,H10_dis1_rt0.3,12,ok,fully organic with strong thickness hierarchy (f0 ~ 0.45),holdout,study/runs/S5_H10_dis1_rt0.3_s12,2b0cbdef,2,2,3,4,grid,1.0,0,12,0.3,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.025620911803402983,0.025620911803402983,0.00014189196227011895,0.00014189196227011895,0.007094598113505947,0.003299574159166595,0.007086027192354963,0.043124834890891986,True,2.3722019440642426e-06,2.3722019440642426e-06,0.05930504860160617,2.3722019440642426e-06,77,0,0.08054393305439331,77,50,8,7,0.09090909090909091,0.6596759016452786,0.7644516473273174,0.17100111856823264,0.8289988814317674,0.30649689901756044,0.45904039332728136,38,0.4935064935064935,0.1347517730496454,2.4675324675324677,3,True,abrupt-brittle,distributed,abrupt-brittle/distributed,3.747794106378839e-10,4.704042152139419e-14,0,0,0,4.070553783526248e-13,144,78,171,332.283583,True,completed,751,956,256,0.19999999999999962,0.19999999999999962,0.04323242938351526,0.0011672755933549118,2.5459387483355527,282,0,10.607391216275367,"[0.4956417443730277, 0.24116369269947616, 0.16698809972560918, 0.09620646320188701]",407 +S5_H11_4x1_L1_rt0.45_s12,S5,holdout,H11_4x1_L1_rt0.45,12,ok,aligned straight stringers (4x1) with disordered finer levels and strong hierarchy,holdout,study/runs/S5_H11_4x1_L1_rt0.45_s12,9f129a5d,4,1,3,4,grid,0.35,1,12,0.45,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.09200756134923312,0.09200756134923312,0.0012756956796683419,0.0012756956796683419,0.0637847839834171,0.0054668587628828955,0.015410646071061422,0.017286464138483015,True,1.045998101255443e-05,1.045998101255443e-05,0.26149952531386084,1.045998101255443e-05,66,0,0.06910994764397906,66,25,27,23,0.3484848484848485,0.6710736737289192,0.03125682538922377,0.2601902173913043,0.7398097826086957,0.2726536173131345,0.5619480936980862,33,0.5,0.11379310344827587,2.5,3,False,abrupt-brittle,distributed,abrupt-brittle/distributed,2.7769940698357597e-11,5.846993561285164e-16,0,0,0,5.506533935784494e-15,68,67,109,306.04595800000004,True,completed,760,955,256,0.19999999999999993,0.19999999999999993,0.026840407037956125,0.002445832091333752,2.513157894736842,290,0,18.54378364359535,"[0.402606105569342, 0.18481309941016294, 0.21638327900412438, 0.1961975160163717]",380 +S5_H12_dis0.2_D6_rt0.8_s13,S5,holdout,H12_dis0.2_D6_rt0.8,13,ok,"moderate disorder, deep hierarchy, weak thickness contrast",holdout,study/runs/S5_H12_dis0.2_D6_rt0.8_s13,c59f63f0,2,2,6,2,grid,0.2,0,13,0.8,0.2,0.0,1.0,segment,0.8,1,0.05,1,0.02,1,False,none,none,0.05,0.5,0.5,0,1,clamped,0.001,0.25,True,1,0.06189156320835685,0.06189156320835685,0.00035277856838430104,0.00035277856838430104,0.017638928419215053,0.005290120781513296,0.005817368415908618,0.02720696636707806,True,2.5265212280417556e-06,2.5265212280417556e-06,0.063163030701044,2.5265212280417556e-06,47,0,0.042805100182149364,47,26,7,1,0.02127659574468085,0.5161065700932713,0.5869410997370551,0.5015794223826715,0.4984205776173285,0.19970751966754496,0.4962102661868287,34,0.723404255319149,0.07589285714285714,4.1063829787234045,5,False,intermediate,distributed,intermediate/distributed,2.8376010155301443e-10,7.661225507112008e-16,0,0,0,2.5479502517864027e-14,80,48,101,212.11154199999987,True,completed,903,1098,256,0.19999999999999968,0.19999999999999968,0.015006829145892525,0.003933950219620851,2.431893687707641,448,0,16.811385092482347,"[0.14999124593138524, 0.11873045328467259, 0.09765576480441177, 0.15085914318261068, 0.12748886139929227, 0.18876419793407656, 0.16651033346355157]",277 +S5_H12_dis0.2_D6_rt0.8_s12,S5,holdout,H12_dis0.2_D6_rt0.8,12,ok,"moderate disorder, deep hierarchy, weak thickness 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+S4_F9_n0_4x1_L1_s1,0.22404005405886815,0.6936091047655455,0.05052631578947368,0.005263157894736842,0.6646309099525833,0.3586225178464568,0.25153110968562886,0.6877271762432753,0.6877271762432754,0.7652631578947369 +S4_F9_n0_4x1_L1_s2,0.2274228829877177,0.7098141148086831,0.040372670807453416,0.004140786749482402,0.6393899807255871,0.34526086220568963,0.24686647051706795,0.687637659702738,0.6876376597027382,0.7660455486542443 +S4_F9_n0_4x1_s2,0.14140801838527317,0.5829785345640919,0.014462809917355372,0.0010330578512396695,0.8457712591402297,0.43850429241060773,0.5555033228142716,0.5974912219182198,0.7018178484268226,0.7262396694214877 +S4_F10_ord_red1_movie_s1,0.2447450087536171,0.4845332056872794,0.2372047244094488,0.010826771653543307,1.0314271863171456,0.5649093036904944,0.2521776207350808,0.16048123275949966,0.36568740424054835,0.6496062992125984 +S4_F10_L3_movie_s1,0.32053919244975443,0.7193259973495982,0.18314606741573033,0.017977528089887642,0.6246521164307571,0.3542341149366115,0.23670148737571792,0.22546835826775163,0.5166250753857918,0.7370786516853932 +S4_F9_n0_4x1_s1,0.178914173845502,0.6077295064678656,0.037460978147762745,0.004162330905306972,0.8034107889975936,0.41967745339729645,0.6510278614572429,0.6055535660152357,0.6656203730398529,0.6711758584807492 +S4_F9_n0_4x1_L1_s3,0.24213301814705757,0.6956420619935797,0.0700836820083682,0.005230125523012552,0.6614536231946392,0.3631184041773805,0.24999312025328477,0.7031585226460279,0.7031585226460279,0.7374476987447699 diff --git a/data/Run 1/RESULT Run 1/analysis/render_all_movies.sh b/data/Run 1/RESULT Run 1/analysis/render_all_movies.sh new file mode 100644 index 0000000000000000000000000000000000000000..926bcd7775f14a95a968458207ec013a592b5012 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/render_all_movies.sh @@ -0,0 +1,11 @@ +#!/bin/bash +# Renders MP4 movies for every run that stored its full state history (state_records.json) +cd "$(dirname "$0")" +for d in ../study/runs/*/; do + if [ -f "$d/state_records.json" ]; then + id=$(basename "$d"); out="../movies/${id}.mp4" + [ -f "$out" ] && continue + python3 render_movie.py "$d" "$out" 240 "$id" >> ../movies/render_log.txt 2>&1 + fi +done +echo "movies done" >> ../movies/render_log.txt diff --git a/data/Run 1/RESULT Run 1/analysis/render_movie.py b/data/Run 1/RESULT Run 1/analysis/render_movie.py new file mode 100644 index 0000000000000000000000000000000000000000..466236e98107dcbbdfbb2fe7b1d0d74c2b606074 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/render_movie.py @@ -0,0 +1,53 @@ +#!/usr/bin/env python3 +"""Render an MP4 movie of a complete simulation run from the stored topology-state history (state_records.json). +Usage: python3 render_movie.py [n_frames] [title] +The frame at applied displacement d is reconstructed exactly: u = d * u1(state), utilisation = d * util1(state).""" +import json, os, sys, subprocess, shutil, tempfile +import numpy as np +import matplotlib; matplotlib.use('Agg') +import matplotlib.pyplot as plt +from matplotlib import cm +from render_structure import render + +def main(run_dir, out, n_frames=240, title=None, fps=30, scale=1.0): + geom = json.load(open(os.path.join(run_dir, 'geometry.json'))) + res = json.load(open(os.path.join(run_dir, 'results.json'))) + sr = json.load(open(os.path.join(run_dir, 'state_records.json'))) + recs = sr['records']; dEnd = sr['dEnd'] + steps = res['steps']; d_curve = np.array([s['d'] for s in steps]); F_curve = np.array([s['F'] for s in steps]) + m = res['metrics'] + dFrom = np.array([r['dFrom'] for r in recs]) + tmp = tempfile.mkdtemp() + W, H = geom['W'], geom['H'] + title = title or res['meta'].get('runId', '') + for k in range(n_frames): + d = dEnd * k / (n_frames - 1) + i = int(np.searchsorted(dFrom, d * (1 + 1e-12), side='right') - 1); i = max(0, i) + r = recs[i] + u = np.array(r['u1']) * d; util = np.array(r['util1']) * d; N = np.array(r['N1']) * d; st = np.array(r['state']) + fig = plt.figure(figsize=(11.5, 5.6), dpi=110) + ax1 = fig.add_axes([0.01, 0.05, 0.46, 0.9]); cax = fig.add_axes([0.475, 0.2, 0.012, 0.6]); ax2 = fig.add_axes([0.6, 0.14, 0.38, 0.72]) + render(geom, ax1, u=u, scale=scale, color_by='util', state=st, util=util, show_failed='ghost', line_scale=1.0, frame=False) + ax1.set_title('%s\nd = %.4f (ε = %.3f) failed members: %d' % (title, d, d / H, int((st == 2).sum()) - sum(1 for e in geom['elements'] if e.get('absent'))), fontsize=9) + F = r['F1'] * d + ax2.plot(d_curve, F_curve, color='#1f5fbf', lw=1.2) + ax2.plot([d], [F], 'o', color='#d62728', ms=6) + ax2.set_xlim(0, dEnd * 1.02); ax2.set_ylim(0, max(F_curve) * 1.08) + ax2.set_xlabel('applied displacement d [W]'); ax2.set_ylabel('reaction force F [E$_s$ W b$_z$]') + ax2.set_title('force–displacement (peak %.2e, W$_f$ = %.2e)' % (m['Fpeak'], m['Wf']), fontsize=9) + sm = plt.cm.ScalarMappable(cmap='viridis', norm=plt.Normalize(0, 1)); sm.set_array([]) + cb = fig.colorbar(sm, cax=cax); cb.set_label('utilisation ε/ε$_c$', fontsize=8); cb.ax.tick_params(labelsize=7) + fig.savefig(os.path.join(tmp, 'f%05d.png' % k), dpi=110); plt.close(fig) + # hold the last frame for 1.5 s + for k in range(n_frames, n_frames + int(1.5 * fps)): + shutil.copy(os.path.join(tmp, 'f%05d.png' % (n_frames - 1)), os.path.join(tmp, 'f%05d.png' % k)) + cmd = ['ffmpeg', '-y', '-loglevel', 'error', '-framerate', str(fps), '-i', os.path.join(tmp, 'f%05d.png'), '-c:v', 'libx264', '-pix_fmt', 'yuv420p', '-vf', 'scale=trunc(iw/2)*2:trunc(ih/2)*2', '-crf', '20', out] + subprocess.run(cmd, check=True) + shutil.rmtree(tmp) + print('wrote', out) + +if __name__ == '__main__': + run_dir = sys.argv[1]; out = sys.argv[2] + n = int(sys.argv[3]) if len(sys.argv) > 3 else 240 + title = sys.argv[4] if len(sys.argv) > 4 else None + main(run_dir, out, n, title) diff --git a/data/Run 1/RESULT Run 1/analysis/render_run_images.log b/data/Run 1/RESULT Run 1/analysis/render_run_images.log new file mode 100644 index 0000000000000000000000000000000000000000..2e45fcb0c66b1cb5f17b22d9d0ecdbdccd617a7d --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/render_run_images.log @@ -0,0 +1 @@ +rendered 345 run images diff --git a/data/Run 1/RESULT Run 1/analysis/render_run_images.py b/data/Run 1/RESULT Run 1/analysis/render_run_images.py new file mode 100644 index 0000000000000000000000000000000000000000..eb6cff43b9162ae609d65cf83e7ede7dc9a7395e --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/render_run_images.py @@ -0,0 +1,23 @@ +#!/usr/bin/env python3 +"""Render a PNG image (peak / final state + F-d curve) for every run in the experiment log.""" +import os, json, sys +import numpy as np +import matplotlib; matplotlib.use('Agg') +import matplotlib.pyplot as plt +from hfx_analysis import load_log, ROOT +from render_structure import render +df = load_log() +n = 0 +for _, r in df[df.status == 'ok'].iterrows(): + d = os.path.join(ROOT, r['dir']); out = os.path.join(d, 'snapshot.png') + if os.path.exists(out): continue + geom = json.load(open(os.path.join(d, 'geometry.json'))); snaps = json.load(open(os.path.join(d, 'snapshots.json'))); res = json.load(open(os.path.join(d, 'results.json'))) + fig, axes = plt.subplots(1, 3, figsize=(12, 4.2), dpi=100) + for ax, key, lab in [(axes[0], 'peak', 'at peak force'), (axes[1], 'final', 'at final failure')]: + s = snaps[key]; render(geom, ax, u=np.array(s['u']), color_by='util', state=np.array(s['state']), util=np.array(s['util']), show_failed='ghost', frame=True) + ax.set_title('%s: d=%.4f F=%.2e failed %d' % (lab, s['d'], s['F'], int((np.array(s['state']) == 2).sum())), fontsize=8) + dd = [s['d'] for s in res['steps']]; FF = [s['F'] for s in res['steps']] + axes[2].plot(dd, FF, color='#1f5fbf', lw=1); axes[2].set_xlabel('applied displacement d [W]'); axes[2].set_ylabel('reaction force F [E_s W b_z]') + m = res['metrics']; axes[2].set_title('%s\nK0=%.3g Fpk=%.2e Wf=%.2e A=%.2f LI=%.2f %s' % (r['runId'], m['K0'], m['Fpeak'], m['Wf'], m['abruptness'], m['localizationIndex'] or 0, m['fractureLabel']), fontsize=7.5) + fig.tight_layout(); fig.savefig(out, dpi=100); plt.close(fig); n += 1 +print('rendered', n, 'run images') diff --git a/data/Run 1/RESULT Run 1/analysis/render_structure.py b/data/Run 1/RESULT Run 1/analysis/render_structure.py new file mode 100644 index 0000000000000000000000000000000000000000..521f38288a70f0dd3281e4b5da45caffb73047e6 --- /dev/null +++ b/data/Run 1/RESULT Run 1/analysis/render_structure.py @@ -0,0 +1,95 @@ +#!/usr/bin/env python3 +"""Render an HFX structure (geometry JSON from HFX.geometryJSON) with matplotlib. +Usage as module: render(geom, ax, u=None, scale=1, color_by='level', state=None, util=None, N=None, fail_order=None, ...) +""" +import json, sys, math +import numpy as np +import matplotlib +matplotlib.use('Agg') +import matplotlib.pyplot as plt +from matplotlib.collections import LineCollection +from matplotlib import cm, colors + +LEVEL_COLORS = ['#d62728', '#ff7f0e', '#bcbd22', '#2ca02c', '#17becf', '#1f77b4', '#9467bd', '#e377c2', '#8c564b', '#7f7f7f', '#171717'] + +def element_colors(geom, color_by, state=None, util=None, N=None, fail_order=None, n_failed=0, disp=None): + els = geom['elements'] + out = [] + Nmax = max(1e-300, max(abs(x) for x in N)) if N is not None else 1 + dmax = max(1e-300, max(disp)) if disp is not None else 1 + tmin = geom['stats']['tMin']; tmax = geom['stats']['tMax'] + for i, e in enumerate(els): + st = state[i] if state is not None else 0 + if st == 2 and color_by != 'failOrder': + out.append((0.75, 0.75, 0.75, 1.0)); continue + if color_by == 'level': + out.append(colors.to_rgba(LEVEL_COLORS[min(e['level'], len(LEVEL_COLORS) - 1)])) + elif color_by == 'interface': + out.append(colors.to_rgba('#d62728' if e['iface'] else ('#ff7f0e' if e['kind'] == 'brace' else '#505050'))) + elif color_by == 'util': + u = util[i] if util is not None else 0 + out.append(cm.viridis(min(1.0, max(0.0, u)))) + elif color_by == 'N': + v = (N[i] / Nmax) if N is not None else 0 + out.append(cm.coolwarm(0.5 + 0.5 * max(-1, min(1, v)))) + elif color_by == 'disp': + out.append(cm.magma(min(1.0, (disp[i] / dmax) if disp is not None else 0))) + elif color_by == 'failOrder': + if fail_order is None or fail_order[i] < 0: out.append((0.82, 0.82, 0.82, 1.0)) + else: out.append(cm.viridis(fail_order[i] / max(1, n_failed - 1))) + elif color_by == 'thickness': + out.append(cm.magma(math.log(e['t'] / tmin) / max(1e-9, math.log(tmax / tmin)))) + else: + out.append((0.2, 0.2, 0.2, 1.0)) + return out + +def render(geom, ax, u=None, scale=1.0, color_by='level', state=None, util=None, N=None, fail_order=None, n_failed=0, + show_failed='ghost', line_scale=1.0, min_lw=0.3, title=None, show_cells=False, lw_units_per_inch=None, frame=True): + nodes = np.array([[n[0], n[1]] for n in geom['nodes']], dtype=float) + if u is not None: + uu = np.asarray(u, dtype=float).reshape(-1, 3) + nodes = nodes + scale * uu[:, :2] + els = geom['elements'] + W, H = geom['W'], geom['H'] + # line width in points: thickness (normalised) * axis width in points + fig = ax.figure + bbox = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted()) + pts_per_unit = bbox.width * 72.0 / (W * 1.08) + disp = None + if u is not None and color_by == 'disp': + uu = np.asarray(u, dtype=float).reshape(-1, 3) + disp = [0.5 * (np.hypot(*uu[e['n1'], :2]) + np.hypot(*uu[e['n2'], :2])) for e in els] + cols = element_colors(geom, color_by, state, util, N, fail_order, n_failed, disp) + order = sorted(range(len(els)), key=lambda i: els[i]['level']) + segs, widths, cc, ghost_segs, ghost_w = [], [], [], [], [] + for i in order: + e = els[i] + if e.get('absent'): continue + st = state[i] if state is not None else 0 + seg = [nodes[e['n1']], nodes[e['n2']]] + lw = max(min_lw, e['t'] * pts_per_unit * line_scale) + if st == 2: + if show_failed == 'hide': continue + if show_failed == 'ghost': ghost_segs.append(seg); ghost_w.append(lw * 0.6); continue + segs.append(seg); widths.append(lw); cc.append(cols[i]) + if show_cells and geom.get('leafCells'): + for c in geom['leafCells']: + poly = np.array(c + [c[0]]) + ax.plot(poly[:, 0], poly[:, 1], color='#e6e6e6', lw=0.4, zorder=0) + if ghost_segs: + ax.add_collection(LineCollection(ghost_segs, linewidths=ghost_w, colors='#c8c8c8', linestyles=(0, (2, 2)), capstyle='round', zorder=1)) + ax.add_collection(LineCollection(segs, linewidths=widths, colors=cc, capstyle='round', zorder=2)) + ax.set_xlim(-0.04 * W, 1.04 * W); ax.set_ylim(-0.04 * H, 1.04 * H) + ax.set_aspect('equal'); ax.set_xticks([]); ax.set_yticks([]) + if not frame: + for s in ax.spines.values(): s.set_visible(False) + if title: ax.set_title(title, fontsize=9) + return ax + +if __name__ == '__main__': + geom = json.load(open(sys.argv[1])) + out = sys.argv[2] + color_by = sys.argv[3] if len(sys.argv) > 3 else 'level' + fig, ax = plt.subplots(figsize=(5, 5 * geom['H'] / geom['W']), dpi=150) + render(geom, ax, color_by=color_by, title=sys.argv[4] if len(sys.argv) > 4 else None) + fig.tight_layout(); fig.savefig(out, dpi=150); print('wrote', out) diff --git a/data/Run 1/RESULT Run 1/app/HierarchicalFractureLab.html b/data/Run 1/RESULT Run 1/app/HierarchicalFractureLab.html new file mode 100644 index 0000000000000000000000000000000000000000..4d2d2343b3dbe7aa4c635d51cac68be8e4be28b2 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/HierarchicalFractureLab.html @@ -0,0 +1,3552 @@ + + + + + +Hierarchical Fracture Lab — generative design & fracture discovery platform + + + +
+

Hierarchical Fracture Lab

+ core v · build 2026-09-01T22:57:58.482Z + + + + + + + + + ready +
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+ 1 · Reference interpretation images → design principles +
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Inferred structural hierarchy of the current design
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Adopted interpretation (editable; the PARAMETER MAPPING block is parsed)
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The images are treated as inspiration for one coherent material concept, not as registered views of one object. Alternative interpretations and the reasons for the adopted one are recorded in the text.
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+ 2 · Geometry generation +
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+ 3 · Mechanics & fracture material · interfaces · failure +
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+ 4 · Loading & numerics displacement control +
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+ 5 · Physical units normalised → SI +
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The solver works in normalised units (length = specimen width W, modulus = Es, out-of-plane depth = 1). Enter physical values to convert displayed results; the mechanics are unchanged.
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+ 6 · Physics model equations · assumptions · BCs +
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+ 7 · Validation not run +
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≈ 1–3 s; analytical references, invariances, conservation checks, step-size and export consistency.
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+ 8 · Design comparison 0 designs +
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Store runs at controlled total material to compare stiffness, peak force, work to failure and fracture mode. Curves are overlaid in the F–d plot.
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+ 9 · Export data · geometry · media +
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Results & metadata
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Geometry & manufacturing
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Media
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+ + + + + + + + + +
+
—
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utilisation ε/εc
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Replay—
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+ + + + + + + + + diff --git a/data/Run 1/RESULT Run 1/app/SOLVER_DESCRIPTION.md b/data/Run 1/RESULT Run 1/app/SOLVER_DESCRIPTION.md new file mode 100644 index 0000000000000000000000000000000000000000..ae84b20832d06db72f98df624e9aeb016ad94e71 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/SOLVER_DESCRIPTION.md @@ -0,0 +1,65 @@ +# HFX simulator core — description of the numerical solver + +`app/src/hfx_core.js` (built from `app/src/core/*.js`) is the single mechanics core used by the browser application +(inlined into `HierarchicalFractureLab.html` and re-used inside a Web Worker) and by the Node.js study driver +(`study/hfx_batch.js`). All quantities are normalised: length unit W (specimen width), stiffness unit E_s, out-of-plane +depth b_z = 1; forces in E_s·W·b_z, energies in E_s·W²·b_z. + +## Structural model +* 2-D network of prismatic Euler–Bernoulli beam elements; nodal DOF (u, v, θ). +* Rectangular section t × b_z: A = t, I = β t³/12 (β = bending factor, 1 in the study). +* Linear elastic, small strain / small rotation, no shear deformation, no geometric nonlinearity, no contact, no + dynamics, no buckling (a compressive failure criterion exists and is switched off by default). +* Element stiffness: standard 6×6 axial + bending matrix in local axes, rotated to global axes (T = blockdiag(R, R)). +* Boundary conditions: bottom nodes u = v = θ = 0; top nodes v = d (applied displacement), u = θ = 0 (clamped grips); + options: pinned grips (θ free) and roller-top (u free at the top). +* Interfaces: explicit short elements (length fraction 0.15 of the child wall) where a level-(k+1) wall meets a coarser + wall, with strength ratio s_int and stiffness ratio k_int. + +## Assembly and linear solver +* Partitioned system K_ff u_f = −K_fp u_p (prescribed displacements eliminated); reactions r_p = K_pf u_f + K_pp u_p. +* Reverse Cuthill–McKee node ordering; envelope (profile) LDLᵀ factorisation (row storage of the lower envelope); + forward/back substitution for every loading step. +* Stabilisation: ground springs ε·k_ref on all free DOF (ε = 1e-12, k_ref = E·mean(t)/mean(L); rotational DOF scaled by + L_ref²). Their force is monitored (≤ 3e-9 of the peak force in the study). Detached fragments (components of the intact + network not connected to a grip) are frozen explicitly, which keeps the system well conditioned. +* Diagnostics per solve: relative residual ‖K u − f‖_free / max(‖reactions‖, 1e-3·F_intact(d)), absolute residual, + global force balance (including stabilisation forces), pivot signs, stabilisation force ratio. + +## Failure and load redistribution +* Utilisation ω = ε_max / ε_c,e with ε_max = N/(EA) + max(|M₁|,|M₂|)(t/2)/(EI) (max tensile fibre strain) and + ε_c,e = ε_c · s_l^level · (s_int for interfaces) · ξ_e (lognormal, mean 1, CV = strength disorder) · weak-zone factor. +* Brittle rule: a member with ω ≥ 1 is removed irreversibly. Optional damage stage: stiffness η E until ε_f = m ε_c. +* Exact event tracking: for a fixed topology ω_e(d) = d·ω_e(1); the next event is at d_crit = 1 / max_e ω_e(1). Each + increment Δd is cut back to d_crit, the critical member(s) (ties within tieTolerance) are removed, K is re-assembled and + re-factorised, the system is re-solved at the same d, and further overloaded members fail one at a time (most utilised + first) until ω < 1 everywhere (one cascade). Without exact tracking, failures are processed at the end of the increment + (overshoot; first-order step-size error, used only in the validation suite). +* Termination: force below stopForceFraction × F_peak after the peak, grip separation (no load path between the grips), + maximum displacement, or maximum number of events. + +## Energy bookkeeping +* External work W_ext = ∫ F dd (trapezoidal on the exact piecewise-linear response, event drops at constant d). +* Stored energy U = ½ F d (only the top displacements are non-zero prescribed values); released energy at an event + ½ (F_before − F_after) d. The balance W_ext = U + Σ released is checked (≤ 3e-12 relative in the study). + +## Metrics +K₀ = dF/dd of the intact structure; E_eff/E_s = K₀ H /(W E_s); F_peak; d_first, d_peak, d_final (F < 0.01 F_peak or +separation); W_f = work to final failure; failed members and fraction; pre-peak failures; abruptness A = largest +single-cascade force drop / F_peak; localisation index LI = 1 − participation ratio of the failed-member positions +binned along the loading axis (bins = leaf-cell size); interface-failure share; per-level failure counts; convergence +flags; result hash (FNV-1a of the response) for reproducibility checks. + +## Generator (summary) +Recursive clipped-Voronoi subdivision of a W×H rectangle (root grid n0x × n0y, branching b, depth D) with seeds on an +ordered layout (grid / staggered / radial) jittered by the disorder δ (optionally only for levels ≥ k_δ); thickness +t_k = t₀ r_t^k with t₀ set by the relative density; braces (redundancy), finest-wall pruning (connectivity), node +merging (short features), defects (notch / weak zone / missing members). Every random choice uses a seeded, +independent sub-stream. + +## Validation +44 tests (analytical stiffness of axial, clamped, guided and pinned inclined beams, mesh independence, bitwise +reproducibility, stiffness/strength scaling laws with unchanged failure sequences, mirror symmetry, force and energy +balance, residuals, stabilisation insensitivity, step-size independence, export consistency, density control, +nested-vs-flat grid identity, analytical ordered-grid stiffness, first failure, tie rupture and work to failure). +See `validation/validation_report.md`; the suite is also runnable in the application (panel 7). diff --git a/data/Run 1/RESULT Run 1/app/src/OrbitControls.r128.js b/data/Run 1/RESULT Run 1/app/src/OrbitControls.r128.js new file mode 100644 index 0000000000000000000000000000000000000000..0873097102ca98527d3f2b5132a57b0b9d62ce07 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/OrbitControls.r128.js @@ -0,0 +1,1045 @@ +( function () { + + // Unlike TrackballControls, it maintains the "up" direction object.up (+Y by default). + // + // Orbit - left mouse / touch: one-finger move + // Zoom - middle mouse, or mousewheel / touch: two-finger spread or squish + // Pan - right mouse, or left mouse + ctrl/meta/shiftKey, or arrow keys / touch: two-finger move + + const _changeEvent = { + type: 'change' + }; + const _startEvent = { + type: 'start' + }; + const _endEvent = { + type: 'end' + }; + + class OrbitControls extends THREE.EventDispatcher { + + constructor( object, domElement ) { + + super(); + if ( domElement === undefined ) console.warn( 'THREE.OrbitControls: The second parameter "domElement" is now mandatory.' ); + if ( domElement === document ) console.error( 'THREE.OrbitControls: "document" should not be used as the target "domElement". Please use "renderer.domElement" instead.' ); + this.object = object; + this.domElement = domElement; // Set to false to disable this control + + this.enabled = true; // "target" sets the location of focus, where the object orbits around + + this.target = new THREE.Vector3(); // How far you can dolly in and out ( PerspectiveCamera only ) + + this.minDistance = 0; + this.maxDistance = Infinity; // How far you can zoom in and out ( OrthographicCamera only ) + + this.minZoom = 0; + this.maxZoom = Infinity; // How far you can orbit vertically, upper and lower limits. + // Range is 0 to Math.PI radians. + + this.minPolarAngle = 0; // radians + + this.maxPolarAngle = Math.PI; // radians + // How far you can orbit horizontally, upper and lower limits. + // If set, the interval [ min, max ] must be a sub-interval of [ - 2 PI, 2 PI ], with ( max - min < 2 PI ) + + this.minAzimuthAngle = - Infinity; // radians + + this.maxAzimuthAngle = Infinity; // radians + // Set to true to enable damping (inertia) + // If damping is enabled, you must call controls.update() in your animation loop + + this.enableDamping = false; + this.dampingFactor = 0.05; // This option actually enables dollying in and out; left as "zoom" for backwards compatibility. + // Set to false to disable zooming + + this.enableZoom = true; + this.zoomSpeed = 1.0; // Set to false to disable rotating + + this.enableRotate = true; + this.rotateSpeed = 1.0; // Set to false to disable panning + + this.enablePan = true; + this.panSpeed = 1.0; + this.screenSpacePanning = true; // if false, pan orthogonal to world-space direction camera.up + + this.keyPanSpeed = 7.0; // pixels moved per arrow key push + // Set to true to automatically rotate around the target + // If auto-rotate is enabled, you must call controls.update() in your animation loop + + this.autoRotate = false; + this.autoRotateSpeed = 2.0; // 30 seconds per orbit when fps is 60 + // The four arrow keys + + this.keys = { + LEFT: 'ArrowLeft', + UP: 'ArrowUp', + RIGHT: 'ArrowRight', + BOTTOM: 'ArrowDown' + }; // Mouse buttons + + this.mouseButtons = { + LEFT: THREE.MOUSE.ROTATE, + MIDDLE: THREE.MOUSE.DOLLY, + RIGHT: THREE.MOUSE.PAN + }; // Touch fingers + + this.touches = { + ONE: THREE.TOUCH.ROTATE, + TWO: THREE.TOUCH.DOLLY_PAN + }; // for reset + + this.target0 = this.target.clone(); + this.position0 = this.object.position.clone(); + this.zoom0 = this.object.zoom; // the target DOM element for key events + + this._domElementKeyEvents = null; // + // public methods + // + + this.getPolarAngle = function () { + + return spherical.phi; + + }; + + this.getAzimuthalAngle = function () { + + return spherical.theta; + + }; + + this.listenToKeyEvents = function ( domElement ) { + + domElement.addEventListener( 'keydown', onKeyDown ); + this._domElementKeyEvents = domElement; + + }; + + this.saveState = function () { + + scope.target0.copy( scope.target ); + scope.position0.copy( scope.object.position ); + scope.zoom0 = scope.object.zoom; + + }; + + this.reset = function () { + + scope.target.copy( scope.target0 ); + scope.object.position.copy( scope.position0 ); + scope.object.zoom = scope.zoom0; + scope.object.updateProjectionMatrix(); + scope.dispatchEvent( _changeEvent ); + scope.update(); + state = STATE.NONE; + + }; // this method is exposed, but perhaps it would be better if we can make it private... + + + this.update = function () { + + const offset = new THREE.Vector3(); // so camera.up is the orbit axis + + const quat = new THREE.Quaternion().setFromUnitVectors( object.up, new THREE.Vector3( 0, 1, 0 ) ); + const quatInverse = quat.clone().invert(); + const lastPosition = new THREE.Vector3(); + const lastQuaternion = new THREE.Quaternion(); + const twoPI = 2 * Math.PI; + return function update() { + + const position = scope.object.position; + offset.copy( position ).sub( scope.target ); // rotate offset to "y-axis-is-up" space + + offset.applyQuaternion( quat ); // angle from z-axis around y-axis + + spherical.setFromVector3( offset ); + + if ( scope.autoRotate && state === STATE.NONE ) { + + rotateLeft( getAutoRotationAngle() ); + + } + + if ( scope.enableDamping ) { + + spherical.theta += sphericalDelta.theta * scope.dampingFactor; + spherical.phi += sphericalDelta.phi * scope.dampingFactor; + + } else { + + spherical.theta += sphericalDelta.theta; + spherical.phi += sphericalDelta.phi; + + } // restrict theta to be between desired limits + + + let min = scope.minAzimuthAngle; + let max = scope.maxAzimuthAngle; + + if ( isFinite( min ) && isFinite( max ) ) { + + if ( min < - Math.PI ) min += twoPI; else if ( min > Math.PI ) min -= twoPI; + if ( max < - Math.PI ) max += twoPI; else if ( max > Math.PI ) max -= twoPI; + + if ( min <= max ) { + + spherical.theta = Math.max( min, Math.min( max, spherical.theta ) ); + + } else { + + spherical.theta = spherical.theta > ( min + max ) / 2 ? Math.max( min, spherical.theta ) : Math.min( max, spherical.theta ); + + } + + } // restrict phi to be between desired limits + + + spherical.phi = Math.max( scope.minPolarAngle, Math.min( scope.maxPolarAngle, spherical.phi ) ); + spherical.makeSafe(); + spherical.radius *= scale; // restrict radius to be between desired limits + + spherical.radius = Math.max( scope.minDistance, Math.min( scope.maxDistance, spherical.radius ) ); // move target to panned location + + if ( scope.enableDamping === true ) { + + scope.target.addScaledVector( panOffset, scope.dampingFactor ); + + } else { + + scope.target.add( panOffset ); + + } + + offset.setFromSpherical( spherical ); // rotate offset back to "camera-up-vector-is-up" space + + offset.applyQuaternion( quatInverse ); + position.copy( scope.target ).add( offset ); + scope.object.lookAt( scope.target ); + + if ( scope.enableDamping === true ) { + + sphericalDelta.theta *= 1 - scope.dampingFactor; + sphericalDelta.phi *= 1 - scope.dampingFactor; + panOffset.multiplyScalar( 1 - scope.dampingFactor ); + + } else { + + sphericalDelta.set( 0, 0, 0 ); + panOffset.set( 0, 0, 0 ); + + } + + scale = 1; // update condition is: + // min(camera displacement, camera rotation in radians)^2 > EPS + // using small-angle approximation cos(x/2) = 1 - x^2 / 8 + + if ( zoomChanged || lastPosition.distanceToSquared( scope.object.position ) > EPS || 8 * ( 1 - lastQuaternion.dot( scope.object.quaternion ) ) > EPS ) { + + scope.dispatchEvent( _changeEvent ); + lastPosition.copy( scope.object.position ); + lastQuaternion.copy( scope.object.quaternion ); + zoomChanged = false; + return true; + + } + + return false; + + }; + + }(); + + this.dispose = function () { + + scope.domElement.removeEventListener( 'contextmenu', onContextMenu ); + scope.domElement.removeEventListener( 'pointerdown', onPointerDown ); + scope.domElement.removeEventListener( 'wheel', onMouseWheel ); + scope.domElement.removeEventListener( 'touchstart', onTouchStart ); + scope.domElement.removeEventListener( 'touchend', onTouchEnd ); + scope.domElement.removeEventListener( 'touchmove', onTouchMove ); + scope.domElement.ownerDocument.removeEventListener( 'pointermove', onPointerMove ); + scope.domElement.ownerDocument.removeEventListener( 'pointerup', onPointerUp ); + + if ( scope._domElementKeyEvents !== null ) { + + scope._domElementKeyEvents.removeEventListener( 'keydown', onKeyDown ); + + } //scope.dispatchEvent( { type: 'dispose' } ); // should this be added here? + + }; // + // internals + // + + + const scope = this; + const STATE = { + NONE: - 1, + ROTATE: 0, + DOLLY: 1, + PAN: 2, + TOUCH_ROTATE: 3, + TOUCH_PAN: 4, + TOUCH_DOLLY_PAN: 5, + TOUCH_DOLLY_ROTATE: 6 + }; + let state = STATE.NONE; + const EPS = 0.000001; // current position in spherical coordinates + + const spherical = new THREE.Spherical(); + const sphericalDelta = new THREE.Spherical(); + let scale = 1; + const panOffset = new THREE.Vector3(); + let zoomChanged = false; + const rotateStart = new THREE.Vector2(); + const rotateEnd = new THREE.Vector2(); + const rotateDelta = new THREE.Vector2(); + const panStart = new THREE.Vector2(); + const panEnd = new THREE.Vector2(); + const panDelta = new THREE.Vector2(); + const dollyStart = new THREE.Vector2(); + const dollyEnd = new THREE.Vector2(); + const dollyDelta = new THREE.Vector2(); + + function getAutoRotationAngle() { + + return 2 * Math.PI / 60 / 60 * scope.autoRotateSpeed; + + } + + function getZoomScale() { + + return Math.pow( 0.95, scope.zoomSpeed ); + + } + + function rotateLeft( angle ) { + + sphericalDelta.theta -= angle; + + } + + function rotateUp( angle ) { + + sphericalDelta.phi -= angle; + + } + + const panLeft = function () { + + const v = new THREE.Vector3(); + return function panLeft( distance, objectMatrix ) { + + v.setFromMatrixColumn( objectMatrix, 0 ); // get X column of objectMatrix + + v.multiplyScalar( - distance ); + panOffset.add( v ); + + }; + + }(); + + const panUp = function () { + + const v = new THREE.Vector3(); + return function panUp( distance, objectMatrix ) { + + if ( scope.screenSpacePanning === true ) { + + v.setFromMatrixColumn( objectMatrix, 1 ); + + } else { + + v.setFromMatrixColumn( objectMatrix, 0 ); + v.crossVectors( scope.object.up, v ); + + } + + v.multiplyScalar( distance ); + panOffset.add( v ); + + }; + + }(); // deltaX and deltaY are in pixels; right and down are positive + + + const pan = function () { + + const offset = new THREE.Vector3(); + return function pan( deltaX, deltaY ) { + + const element = scope.domElement; + + if ( scope.object.isPerspectiveCamera ) { + + // perspective + const position = scope.object.position; + offset.copy( position ).sub( scope.target ); + let targetDistance = offset.length(); // half of the fov is center to top of screen + + targetDistance *= Math.tan( scope.object.fov / 2 * Math.PI / 180.0 ); // we use only clientHeight here so aspect ratio does not distort speed + + panLeft( 2 * deltaX * targetDistance / element.clientHeight, scope.object.matrix ); + panUp( 2 * deltaY * targetDistance / element.clientHeight, scope.object.matrix ); + + } else if ( scope.object.isOrthographicCamera ) { + + // orthographic + panLeft( deltaX * ( scope.object.right - scope.object.left ) / scope.object.zoom / element.clientWidth, scope.object.matrix ); + panUp( deltaY * ( scope.object.top - scope.object.bottom ) / scope.object.zoom / element.clientHeight, scope.object.matrix ); + + } else { + + // camera neither orthographic nor perspective + console.warn( 'WARNING: OrbitControls.js encountered an unknown camera type - pan disabled.' ); + scope.enablePan = false; + + } + + }; + + }(); + + function dollyOut( dollyScale ) { + + if ( scope.object.isPerspectiveCamera ) { + + scale /= dollyScale; + + } else if ( scope.object.isOrthographicCamera ) { + + scope.object.zoom = Math.max( scope.minZoom, Math.min( scope.maxZoom, scope.object.zoom * dollyScale ) ); + scope.object.updateProjectionMatrix(); + zoomChanged = true; + + } else { + + console.warn( 'WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.' ); + scope.enableZoom = false; + + } + + } + + function dollyIn( dollyScale ) { + + if ( scope.object.isPerspectiveCamera ) { + + scale *= dollyScale; + + } else if ( scope.object.isOrthographicCamera ) { + + scope.object.zoom = Math.max( scope.minZoom, Math.min( scope.maxZoom, scope.object.zoom / dollyScale ) ); + scope.object.updateProjectionMatrix(); + zoomChanged = true; + + } else { + + console.warn( 'WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.' ); + scope.enableZoom = false; + + } + + } // + // event callbacks - update the object state + // + + + function handleMouseDownRotate( event ) { + + rotateStart.set( event.clientX, event.clientY ); + + } + + function handleMouseDownDolly( event ) { + + dollyStart.set( event.clientX, event.clientY ); + + } + + function handleMouseDownPan( event ) { + + panStart.set( event.clientX, event.clientY ); + + } + + function handleMouseMoveRotate( event ) { + + rotateEnd.set( event.clientX, event.clientY ); + rotateDelta.subVectors( rotateEnd, rotateStart ).multiplyScalar( scope.rotateSpeed ); + const element = scope.domElement; + rotateLeft( 2 * Math.PI * rotateDelta.x / element.clientHeight ); // yes, height + + rotateUp( 2 * Math.PI * rotateDelta.y / element.clientHeight ); + rotateStart.copy( rotateEnd ); + scope.update(); + + } + + function handleMouseMoveDolly( event ) { + + dollyEnd.set( event.clientX, event.clientY ); + dollyDelta.subVectors( dollyEnd, dollyStart ); + + if ( dollyDelta.y > 0 ) { + + dollyOut( getZoomScale() ); + + } else if ( dollyDelta.y < 0 ) { + + dollyIn( getZoomScale() ); + + } + + dollyStart.copy( dollyEnd ); + scope.update(); + + } + + function handleMouseMovePan( event ) { + + panEnd.set( event.clientX, event.clientY ); + panDelta.subVectors( panEnd, panStart ).multiplyScalar( scope.panSpeed ); + pan( panDelta.x, panDelta.y ); + panStart.copy( panEnd ); + scope.update(); + + } + + function handleMouseUp( ) { // no-op + } + + function handleMouseWheel( event ) { + + if ( event.deltaY < 0 ) { + + dollyIn( getZoomScale() ); + + } else if ( event.deltaY > 0 ) { + + dollyOut( getZoomScale() ); + + } + + scope.update(); + + } + + function handleKeyDown( event ) { + + let needsUpdate = false; + + switch ( event.code ) { + + case scope.keys.UP: + pan( 0, scope.keyPanSpeed ); + needsUpdate = true; + break; + + case scope.keys.BOTTOM: + pan( 0, - scope.keyPanSpeed ); + needsUpdate = true; + break; + + case scope.keys.LEFT: + pan( scope.keyPanSpeed, 0 ); + needsUpdate = true; + break; + + case scope.keys.RIGHT: + pan( - scope.keyPanSpeed, 0 ); + needsUpdate = true; + break; + + } + + if ( needsUpdate ) { + + // prevent the browser from scrolling on cursor keys + event.preventDefault(); + scope.update(); + + } + + } + + function handleTouchStartRotate( event ) { + + if ( event.touches.length == 1 ) { + + rotateStart.set( event.touches[ 0 ].pageX, event.touches[ 0 ].pageY ); + + } else { + + const x = 0.5 * ( event.touches[ 0 ].pageX + event.touches[ 1 ].pageX ); + const y = 0.5 * ( event.touches[ 0 ].pageY + event.touches[ 1 ].pageY ); + rotateStart.set( x, y ); + + } + + } + + function handleTouchStartPan( event ) { + + if ( event.touches.length == 1 ) { + + panStart.set( event.touches[ 0 ].pageX, event.touches[ 0 ].pageY ); + + } else { + + const x = 0.5 * ( event.touches[ 0 ].pageX + event.touches[ 1 ].pageX ); + const y = 0.5 * ( event.touches[ 0 ].pageY + event.touches[ 1 ].pageY ); + panStart.set( x, y ); + + } + + } + + function handleTouchStartDolly( event ) { + + const dx = event.touches[ 0 ].pageX - event.touches[ 1 ].pageX; + const dy = event.touches[ 0 ].pageY - event.touches[ 1 ].pageY; + const distance = Math.sqrt( dx * dx + dy * dy ); + dollyStart.set( 0, distance ); + + } + + function handleTouchStartDollyPan( event ) { + + if ( scope.enableZoom ) handleTouchStartDolly( event ); + if ( scope.enablePan ) handleTouchStartPan( event ); + + } + + function handleTouchStartDollyRotate( event ) { + + if ( scope.enableZoom ) handleTouchStartDolly( event ); + if ( scope.enableRotate ) handleTouchStartRotate( event ); + + } + + function handleTouchMoveRotate( event ) { + + if ( event.touches.length == 1 ) { + + rotateEnd.set( event.touches[ 0 ].pageX, event.touches[ 0 ].pageY ); + + } else { + + const x = 0.5 * ( event.touches[ 0 ].pageX + event.touches[ 1 ].pageX ); + const y = 0.5 * ( event.touches[ 0 ].pageY + event.touches[ 1 ].pageY ); + rotateEnd.set( x, y ); + + } + + rotateDelta.subVectors( rotateEnd, rotateStart ).multiplyScalar( scope.rotateSpeed ); + const element = scope.domElement; + rotateLeft( 2 * Math.PI * rotateDelta.x / element.clientHeight ); // yes, height + + rotateUp( 2 * Math.PI * rotateDelta.y / element.clientHeight ); + rotateStart.copy( rotateEnd ); + + } + + function handleTouchMovePan( event ) { + + if ( event.touches.length == 1 ) { + + panEnd.set( event.touches[ 0 ].pageX, event.touches[ 0 ].pageY ); + + } else { + + const x = 0.5 * ( event.touches[ 0 ].pageX + event.touches[ 1 ].pageX ); + const y = 0.5 * ( event.touches[ 0 ].pageY + event.touches[ 1 ].pageY ); + panEnd.set( x, y ); + + } + + panDelta.subVectors( panEnd, panStart ).multiplyScalar( scope.panSpeed ); + pan( panDelta.x, panDelta.y ); + panStart.copy( panEnd ); + + } + + function handleTouchMoveDolly( event ) { + + const dx = event.touches[ 0 ].pageX - event.touches[ 1 ].pageX; + const dy = event.touches[ 0 ].pageY - event.touches[ 1 ].pageY; + const distance = Math.sqrt( dx * dx + dy * dy ); + dollyEnd.set( 0, distance ); + dollyDelta.set( 0, Math.pow( dollyEnd.y / dollyStart.y, scope.zoomSpeed ) ); + dollyOut( dollyDelta.y ); + dollyStart.copy( dollyEnd ); + + } + + function handleTouchMoveDollyPan( event ) { + + if ( scope.enableZoom ) handleTouchMoveDolly( event ); + if ( scope.enablePan ) handleTouchMovePan( event ); + + } + + function handleTouchMoveDollyRotate( event ) { + + if ( scope.enableZoom ) handleTouchMoveDolly( event ); + if ( scope.enableRotate ) handleTouchMoveRotate( event ); + + } + + function handleTouchEnd( ) { // no-op + } // + // event handlers - FSM: listen for events and reset state + // + + + function onPointerDown( event ) { + + if ( scope.enabled === false ) return; + + switch ( event.pointerType ) { + + case 'mouse': + case 'pen': + onMouseDown( event ); + break; + // TODO touch + + } + + } + + function onPointerMove( event ) { + + if ( scope.enabled === false ) return; + + switch ( event.pointerType ) { + + case 'mouse': + case 'pen': + onMouseMove( event ); + break; + // TODO touch + + } + + } + + function onPointerUp( event ) { + + switch ( event.pointerType ) { + + case 'mouse': + case 'pen': + onMouseUp( event ); + break; + // TODO touch + + } + + } + + function onMouseDown( event ) { + + // Prevent the browser from scrolling. + event.preventDefault(); // Manually set the focus since calling preventDefault above + // prevents the browser from setting it automatically. + + scope.domElement.focus ? scope.domElement.focus() : window.focus(); + let mouseAction; + + switch ( event.button ) { + + case 0: + mouseAction = scope.mouseButtons.LEFT; + break; + + case 1: + mouseAction = scope.mouseButtons.MIDDLE; + break; + + case 2: + mouseAction = scope.mouseButtons.RIGHT; + break; + + default: + mouseAction = - 1; + + } + + switch ( mouseAction ) { + + case THREE.MOUSE.DOLLY: + if ( scope.enableZoom === false ) return; + handleMouseDownDolly( event ); + state = STATE.DOLLY; + break; + + case THREE.MOUSE.ROTATE: + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + if ( scope.enablePan === false ) return; + handleMouseDownPan( event ); + state = STATE.PAN; + + } else { + + if ( scope.enableRotate === false ) return; + handleMouseDownRotate( event ); + state = STATE.ROTATE; + + } + + break; + + case THREE.MOUSE.PAN: + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + if ( scope.enableRotate === false ) return; + handleMouseDownRotate( event ); + state = STATE.ROTATE; + + } else { + + if ( scope.enablePan === false ) return; + handleMouseDownPan( event ); + state = STATE.PAN; + + } + + break; + + default: + state = STATE.NONE; + + } + + if ( state !== STATE.NONE ) { + + scope.domElement.ownerDocument.addEventListener( 'pointermove', onPointerMove ); + scope.domElement.ownerDocument.addEventListener( 'pointerup', onPointerUp ); + scope.dispatchEvent( _startEvent ); + + } + + } + + function onMouseMove( event ) { + + if ( scope.enabled === false ) return; + event.preventDefault(); + + switch ( state ) { + + case STATE.ROTATE: + if ( scope.enableRotate === false ) return; + handleMouseMoveRotate( event ); + break; + + case STATE.DOLLY: + if ( scope.enableZoom === false ) return; + handleMouseMoveDolly( event ); + break; + + case STATE.PAN: + if ( scope.enablePan === false ) return; + handleMouseMovePan( event ); + break; + + } + + } + + function onMouseUp( event ) { + + scope.domElement.ownerDocument.removeEventListener( 'pointermove', onPointerMove ); + scope.domElement.ownerDocument.removeEventListener( 'pointerup', onPointerUp ); + if ( scope.enabled === false ) return; + handleMouseUp( event ); + scope.dispatchEvent( _endEvent ); + state = STATE.NONE; + + } + + function onMouseWheel( event ) { + + if ( scope.enabled === false || scope.enableZoom === false || state !== STATE.NONE && state !== STATE.ROTATE ) return; + event.preventDefault(); + scope.dispatchEvent( _startEvent ); + handleMouseWheel( event ); + scope.dispatchEvent( _endEvent ); + + } + + function onKeyDown( event ) { + + if ( scope.enabled === false || scope.enablePan === false ) return; + handleKeyDown( event ); + + } + + function onTouchStart( event ) { + + if ( scope.enabled === false ) return; + event.preventDefault(); // prevent scrolling + + switch ( event.touches.length ) { + + case 1: + switch ( scope.touches.ONE ) { + + case THREE.TOUCH.ROTATE: + if ( scope.enableRotate === false ) return; + handleTouchStartRotate( event ); + state = STATE.TOUCH_ROTATE; + break; + + case THREE.TOUCH.PAN: + if ( scope.enablePan === false ) return; + handleTouchStartPan( event ); + state = STATE.TOUCH_PAN; + break; + + default: + state = STATE.NONE; + + } + + break; + + case 2: + switch ( scope.touches.TWO ) { + + case THREE.TOUCH.DOLLY_PAN: + if ( scope.enableZoom === false && scope.enablePan === false ) return; + handleTouchStartDollyPan( event ); + state = STATE.TOUCH_DOLLY_PAN; + break; + + case THREE.TOUCH.DOLLY_ROTATE: + if ( scope.enableZoom === false && scope.enableRotate === false ) return; + handleTouchStartDollyRotate( event ); + state = STATE.TOUCH_DOLLY_ROTATE; + break; + + default: + state = STATE.NONE; + + } + + break; + + default: + state = STATE.NONE; + + } + + if ( state !== STATE.NONE ) { + + scope.dispatchEvent( _startEvent ); + + } + + } + + function onTouchMove( event ) { + + if ( scope.enabled === false ) return; + event.preventDefault(); // prevent scrolling + + switch ( state ) { + + case STATE.TOUCH_ROTATE: + if ( scope.enableRotate === false ) return; + handleTouchMoveRotate( event ); + scope.update(); + break; + + case STATE.TOUCH_PAN: + if ( scope.enablePan === false ) return; + handleTouchMovePan( event ); + scope.update(); + break; + + case STATE.TOUCH_DOLLY_PAN: + if ( scope.enableZoom === false && scope.enablePan === false ) return; + handleTouchMoveDollyPan( event ); + scope.update(); + break; + + case STATE.TOUCH_DOLLY_ROTATE: + if ( scope.enableZoom === false && scope.enableRotate === false ) return; + handleTouchMoveDollyRotate( event ); + scope.update(); + break; + + default: + state = STATE.NONE; + + } + + } + + function onTouchEnd( event ) { + + if ( scope.enabled === false ) return; + handleTouchEnd( event ); + scope.dispatchEvent( _endEvent ); + state = STATE.NONE; + + } + + function onContextMenu( event ) { + + if ( scope.enabled === false ) return; + event.preventDefault(); + + } // + + + scope.domElement.addEventListener( 'contextmenu', onContextMenu ); + scope.domElement.addEventListener( 'pointerdown', onPointerDown ); + scope.domElement.addEventListener( 'wheel', onMouseWheel, { + passive: false + } ); + scope.domElement.addEventListener( 'touchstart', onTouchStart, { + passive: false + } ); + scope.domElement.addEventListener( 'touchend', onTouchEnd ); + scope.domElement.addEventListener( 'touchmove', onTouchMove, { + passive: false + } ); // force an update at start + + this.update(); + + } + + } // This set of controls performs orbiting, dollying (zooming), and panning. + // Unlike TrackballControls, it maintains the "up" direction object.up (+Y by default). + // This is very similar to OrbitControls, another set of touch behavior + // + // Orbit - right mouse, or left mouse + ctrl/meta/shiftKey / touch: two-finger rotate + // Zoom - middle mouse, or mousewheel / touch: two-finger spread or squish + // Pan - left mouse, or arrow keys / touch: one-finger move + + + class MapControls extends OrbitControls { + + constructor( object, domElement ) { + + super( object, domElement ); + this.screenSpacePanning = false; // pan orthogonal to world-space direction camera.up + + this.mouseButtons.LEFT = THREE.MOUSE.PAN; + this.mouseButtons.RIGHT = THREE.MOUSE.ROTATE; + this.touches.ONE = THREE.TOUCH.PAN; + this.touches.TWO = THREE.TOUCH.DOLLY_ROTATE; + + } + + } + + THREE.MapControls = MapControls; + THREE.OrbitControls = OrbitControls; + +} )(); diff --git a/data/Run 1/RESULT Run 1/app/src/build.js b/data/Run 1/RESULT Run 1/app/src/build.js new file mode 100644 index 0000000000000000000000000000000000000000..26efdc44f32966bcc2c5b562fef312ef78f24c99 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/build.js @@ -0,0 +1,30 @@ +// Build script: concatenates core modules into hfx_core.js and inlines everything into the single-file app. +const fs = require('fs'), path = require('path'), crypto = require('crypto'); +const src = __dirname; +const coreFiles = fs.readdirSync(path.join(src, 'core')).filter(f => f.endsWith('.js')).sort(); +let core = coreFiles.map(f => fs.readFileSync(path.join(src, 'core', f), 'utf8')).join('\n'); +const buildStamp = new Date().toISOString(); +core = core.replace("NAME: 'HFX Hierarchical Fracture eXplorer core'", "NAME: 'HFX Hierarchical Fracture eXplorer core', BUILD: '" + buildStamp + "'"); +fs.writeFileSync(path.join(src, 'hfx_core.js'), core); +const coreHash = crypto.createHash('sha256').update(core).digest('hex'); +console.log('hfx_core.js written:', core.length, 'bytes, sha256', coreHash.slice(0, 16), 'modules:', coreFiles.join(' ')); +if (process.argv.includes('--app')) { + const uiFiles = fs.readdirSync(path.join(src, 'ui')).sort(); + const part = (name) => fs.readFileSync(path.join(src, 'ui', name), 'utf8'); + const tpl = part('01_head.html') + part('02_body.html') + + '\n\n\n' + + '\n' + + uiFiles.filter(f => f.endsWith('.js')).map(f => '\n').join('') + '\n\n'; + const three = fs.readFileSync(path.join(src, 'three.min.r128.js'), 'utf8'); + const orbit = fs.readFileSync(path.join(src, 'OrbitControls.r128.js'), 'utf8'); + const imgDir = path.join(src, '..', '..', 'reference_images'); + const imgs = ['ref1_nested_rings_wire_mesh_512.jpg', 'ref2_organic_thread_net_512.jpg', 'ref3_polygonal_cells_inner_venation_512.jpg', 'ref4_triangulated_lattice_defects_512.jpg', 'ref5_leaf_venation_hierarchy_512.jpg']; + const dataUris = imgs.map(f => 'data:image/jpeg;base64,' + fs.readFileSync(path.join(imgDir, f)).toString('base64')); + let html = tpl.replace('/*__THREE_JS__*/', () => three).replace('/*__ORBIT_CONTROLS__*/', () => orbit) + .replace('/*__HFX_CORE__*/', () => core.replace(/<\/script>/g, '<\\/script>')) + .replace('"__REF_IMAGES__"', () => JSON.stringify(dataUris)) + .replace(/__BUILD_STAMP__/g, buildStamp).replace(/__CORE_HASH__/g, coreHash); + const out = path.join(src, '..', 'HierarchicalFractureLab.html'); + fs.writeFileSync(out, html); + console.log('app written:', out, (html.length / 1e6).toFixed(2), 'MB'); +} diff --git a/data/Run 1/RESULT Run 1/app/src/core/00_header.js b/data/Run 1/RESULT Run 1/app/src/core/00_header.js new file mode 100644 index 0000000000000000000000000000000000000000..3747b47cce5bc36f13460abaf8fd58e2efc9b517 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/00_header.js @@ -0,0 +1,23 @@ +/* + * HFX — Hierarchical Fracture eXplorer: simulator core + * --------------------------------------------------------------------------- + * Shared by the single-file browser application and the Node.js study driver. + * Contents: + * 10 RNG + convex-polygon geometry utilities + * 20 Hierarchical cellular-network generator (recursive clipped Voronoi) + * 30 2-D Euler–Bernoulli beam-network assembly + envelope LDL^T solver + * 40 Quasi-static displacement-controlled fracture driver (event tracking) + * 50 Metrics, CSV/JSON export helpers + * 60 Validation test suite + * 70 Binary STL export (extruded plate, thickening variants), SVG rendering + * All quantities are NORMALISED unless explicitly converted: length unit = specimen + * width W (=1), stiffness unit = solid modulus E_s (=1), out-of-plane depth b_z = 1. + * Force unit = E_s * W * b_z ; energy unit = E_s * W^2 * b_z. + * --------------------------------------------------------------------------- + */ +(function (root, factory) { + if (typeof module === 'object' && module.exports) { module.exports = factory(); } + else { root.HFX = factory(); } +})(typeof self !== 'undefined' ? self : this, function () { +'use strict'; +const HFX = { VERSION: '1.0.0', NAME: 'HFX Hierarchical Fracture eXplorer core' }; diff --git a/data/Run 1/RESULT Run 1/app/src/core/10_rng_geom.js b/data/Run 1/RESULT Run 1/app/src/core/10_rng_geom.js new file mode 100644 index 0000000000000000000000000000000000000000..17dc0bfe92624385fc278d0eb8833f2b51b40a34 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/10_rng_geom.js @@ -0,0 +1,123 @@ +// ============================================================================ +// 10. Seeded RNG and convex-polygon geometry utilities +// ============================================================================ +function xmur3(str) { + let h = 1779033703 ^ str.length; + for (let i = 0; i < str.length; i++) { + h = Math.imul(h ^ str.charCodeAt(i), 3432918353); + h = (h << 13) | (h >>> 19); + } + return function () { + h = Math.imul(h ^ (h >>> 16), 2246822507); + h = Math.imul(h ^ (h >>> 13), 3266489909); + h ^= h >>> 16; + return h >>> 0; + }; +} +function mulberry32(a) { + return function () { + a |= 0; a = (a + 0x6D2B79F5) | 0; + let t = Math.imul(a ^ (a >>> 15), 1 | a); + t = (t + Math.imul(t ^ (t >>> 7), 61 | t)) ^ t; + return ((t ^ (t >>> 14)) >>> 0) / 4294967296; + }; +} +/** Deterministic RNG. seed: number or string; stream: string label (independent sub-streams). */ +HFX.makeRNG = function (seed, stream) { + const h = xmur3(String(seed) + '|' + (stream || 'main')); + const next = mulberry32(h()); + const rng = { + next: next, + uniform: function (a, b) { return a + (b - a) * next(); }, + int: function (n) { return Math.floor(next() * n); }, + normal: function () { // Box–Muller + let u = 0, v = 0; while (u === 0) u = next(); while (v === 0) v = next(); + return Math.sqrt(-2.0 * Math.log(u)) * Math.cos(2.0 * Math.PI * v); + }, + lognormalMean1: function (cv) { // lognormal with mean 1 and coefficient of variation cv + if (!(cv > 0)) return 1; + const s2 = Math.log(1 + cv * cv); + return Math.exp(-0.5 * s2 + Math.sqrt(s2) * rng.normal()); + } + }; + return rng; +}; + +// ---- polygon utilities. A polygon is {pts:[[x,y],...] (CCW), tags:[edge tag per edge i: pts[i]->pts[i+1]]} +const G = {}; +G.area = function (pts) { let a = 0; for (let i = 0, n = pts.length; i < n; i++) { const p = pts[i], q = pts[(i + 1) % n]; a += p[0] * q[1] - q[0] * p[1]; } return 0.5 * a; }; +G.centroid = function (pts) { + let cx = 0, cy = 0, a = 0; + for (let i = 0, n = pts.length; i < n; i++) { const p = pts[i], q = pts[(i + 1) % n]; const w = p[0] * q[1] - q[0] * p[1]; a += w; cx += (p[0] + q[0]) * w; cy += (p[1] + q[1]) * w; } + if (Math.abs(a) < 1e-300) { cx = 0; cy = 0; for (const p of pts) { cx += p[0]; cy += p[1]; } return [cx / pts.length, cy / pts.length]; } + return [cx / (3 * a), cy / (3 * a)]; +}; +G.aabb = function (pts) { let xmin = Infinity, ymin = Infinity, xmax = -Infinity, ymax = -Infinity; for (const p of pts) { if (p[0] < xmin) xmin = p[0]; if (p[0] > xmax) xmax = p[0]; if (p[1] < ymin) ymin = p[1]; if (p[1] > ymax) ymax = p[1]; } return { xmin, ymin, xmax, ymax }; }; +/** Clip convex polygon by half-plane a*x+b*y+c <= 0. New edge on the clip line receives `tag`. */ +G.clipHalfPlane = function (poly, a, b, c, tag) { + const pts = poly.pts, tags = poly.tags, n = pts.length, outP = [], outT = []; + for (let i = 0; i < n; i++) { + const P = pts[i], Q = pts[(i + 1) % n]; + const dP = a * P[0] + b * P[1] + c, dQ = a * Q[0] + b * Q[1] + c; + const inP = dP <= 0, inQ = dQ <= 0; + if (inP) { + outP.push(P); outT.push(tags[i]); + if (!inQ) { const t = dP / (dP - dQ); outP.push([P[0] + t * (Q[0] - P[0]), P[1] + t * (Q[1] - P[1])]); outT.push(tag); } + } else if (inQ) { + const t = dP / (dP - dQ); outP.push([P[0] + t * (Q[0] - P[0]), P[1] + t * (Q[1] - P[1])]); outT.push(tags[i]); + } + } + return { pts: outP, tags: outT }; +}; +/** Remove near-duplicate vertices and collinear vertices whose adjacent edges carry the same tag. */ +G.cleanPolygon = function (poly, eps) { + let pts = poly.pts.slice(), tags = poly.tags.slice(); + // pass 1: duplicates + let P = [], T = []; + for (let i = 0; i < pts.length; i++) { + const p = pts[i]; + if (P.length && Math.hypot(p[0] - P[P.length - 1][0], p[1] - P[P.length - 1][1]) < eps) { T[T.length - 1] = tags[i]; continue; } + P.push(p); T.push(tags[i]); + } + if (P.length > 1 && Math.hypot(P[0][0] - P[P.length - 1][0], P[0][1] - P[P.length - 1][1]) < eps) { P.pop(); T.pop(); } + // pass 2: collinear with same tag on both edges + let changed = true; + while (changed && P.length > 3) { + changed = false; + for (let i = 0; i < P.length; i++) { + const im = (i + P.length - 1) % P.length, ip = (i + 1) % P.length; + const ax = P[i][0] - P[im][0], ay = P[i][1] - P[im][1], bx = P[ip][0] - P[i][0], by = P[ip][1] - P[i][1]; + const cross = ax * by - ay * bx, dot = ax * bx + ay * by; + const la = Math.hypot(ax, ay), lb = Math.hypot(bx, by); + if (Math.abs(cross) < eps * (la + lb) && dot > 0 && T[im] === T[i]) { P.splice(i, 1); T.splice(i, 1); changed = true; break; } + } + } + return { pts: P, tags: T }; +}; +G.pointInConvex = function (pts, x, y, margin) { + const n = pts.length; + for (let i = 0; i < n; i++) { const p = pts[i], q = pts[(i + 1) % n]; const cr = (q[0] - p[0]) * (y - p[1]) - (q[1] - p[1]) * (x - p[0]); if (cr < (margin || 0)) return false; } + return true; +}; +/** Move point p toward the centroid until it is strictly inside (convex polygon). */ +G.pushInside = function (p, pts, cen, frac) { + if (G.pointInConvex(pts, p[0], p[1], 1e-12)) return p; + const dx = p[0] - cen[0], dy = p[1] - cen[1]; + let tHit = 1; + for (let i = 0, n = pts.length; i < n; i++) { + const a = pts[i], b = pts[(i + 1) % n]; + const ex = b[0] - a[0], ey = b[1] - a[1]; + const den = dx * ey - dy * ex; if (Math.abs(den) < 1e-300) continue; + const t = ((a[0] - cen[0]) * ey - (a[1] - cen[1]) * ex) / den; + const s = ((a[0] - cen[0]) * dy - (a[1] - cen[1]) * dx) / den; + if (t > 0 && s >= -1e-12 && s <= 1 + 1e-12 && t < tHit) tHit = t; + } + const f = (frac === undefined ? 0.8 : frac) * tHit; + return [cen[0] + f * dx, cen[1] + f * dy]; +}; +G.polygonInradiusEstimate = function (pts) { // min distance from centroid to edges + const c = G.centroid(pts); let r = Infinity; + for (let i = 0, n = pts.length; i < n; i++) { const a = pts[i], b = pts[(i + 1) % n]; const ex = b[0] - a[0], ey = b[1] - a[1]; const L = Math.hypot(ex, ey); if (L < 1e-300) continue; const d = Math.abs(ex * (c[1] - a[1]) - ey * (c[0] - a[0])) / L; if (d < r) r = d; } + return r; +}; +HFX.geom = G; diff --git a/data/Run 1/RESULT Run 1/app/src/core/20_generator.js b/data/Run 1/RESULT Run 1/app/src/core/20_generator.js new file mode 100644 index 0000000000000000000000000000000000000000..9eb3b1b6c3c6b6a7437df2cd1fb0b4b8f74488ba --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/20_generator.js @@ -0,0 +1,409 @@ +// ============================================================================ +// 20. Hierarchical cellular-network generator +// Concept: a rectangular specimen W x H is tessellated by a level-0 grid of +// n0x x n0y cells (plus an optional frame). Every cell of level k is recursively +// subdivided into `branching` sub-cells by a clipped Voronoi tessellation of +// seeds placed on an ordered layout (grid / staggered / radial) and jittered by +// `disorder`. Walls created at level k carry thickness t_k = t_0 * thicknessRatio^k. +// Where a level-(k+1) wall meets a coarser wall an INTERFACE element is created. +// Leaf cells may receive diagonal braces (redundancy). Total material is fixed by +// the relative density. Defects (notch / weak zone / missing members) are applied +// after the density calibration. +// ============================================================================ +HFX.defaultParams = function () { + return { + // --- specimen & topology + W: 1.0, H: 1.0, n0x: 1, n0y: 1, depth: 3, branching: 4, layout: 'grid', + disorder: 0.0, disorderMinLevel: 0, seed: 1, includeFrame: true, frameMode: 'sides', + thicknessRatio: 0.6, densityMode: 'relative', relDensity: 0.2, slenderness0: 20, + redundancy: 0.0, connectivity: 1.0, + interfaceMode: 'segment', interfaceFraction: 0.15, + mergeFraction: 0.05, minSeedSeparation: 0.25, + defectType: 'none', defectX: 0.5, defectY: 0.5, defectSize: 0.05, defectWeakFactor: 0.5, missingFraction: 0.0, + // --- material (normalised: E_s = 1) + E: 1.0, failStrain: 0.02, strengthCV: 0.0, strengthLevelRatio: 1.0, + interfaceStrengthRatio: 1.0, interfaceStiffnessRatio: 1.0, + bendingFactor: 1.0, residualStiffness: 0.0, ductilityRatio: 1.0, compressiveRatio: 0.0, + // --- loading & numerics + gripType: 'clamped', dispIncrement: 0.0005, maxDisp: 0.08, exactEvents: true, + maxIterations: 2000, tolerance: 1e-8, stabilization: 1e-12, tieTolerance: 1e-9, + stopForceFraction: 0.01, maxEvents: 20000, maxElements: 40000, + recordMemberHistory: false, memberHistoryEvery: 1, recordStates: false, maxStates: 600, + // --- physical unit scaling (display / export only) + phys: { E_MPa: 2000, W_mm: 100, depth_mm: 4 } + }; +}; +HFX.PARAM_DOC = { + W: 'specimen width (length unit)', H: 'specimen height', n0x: 'level-0 cells along x', n0y: 'level-0 cells along y', + depth: 'hierarchy depth D (number of nested subdivision levels below level 0)', branching: 'branching ratio b (sub-cells per cell per level)', + layout: 'ordered seed layout language: grid | staggered | radial', disorder: 'geometric disorder 0 (ordered) .. 1 (organic Voronoi)', disorderMinLevel: 'disorder is applied only to levels >= this value (coarser levels stay ordered, e.g. straight midrib + organic areoles)', + seed: 'random seed (geometry, strength, braces, defects use independent sub-streams)', includeFrame: 'include boundary frame walls (level 0)', frameMode: 'full: all four boundary walls | sides: only the two side walls (top/bottom boundaries are the grips) | none', + thicknessRatio: 'inter-level thickness ratio r_t: t_k = t_0 r_t^k (1 = no thickness hierarchy)', + densityMode: 'relative: fix relative density; slenderness: fix level-0 slenderness', relDensity: 'relative density = member area / (W H)', + slenderness0: 'level-0 slenderness L_0/t_0 (used in slenderness mode)', redundancy: 'fraction of possible leaf-cell fan diagonals (braces) added', + connectivity: 'fraction of finest-level walls retained (1 = closed cells)', interfaceMode: 'segment: explicit short interface element | element: whole first element | none', + interfaceFraction: 'interface element length as fraction of the child wall segment length', mergeFraction: 'merge nodes closer than this fraction of the leaf cell size', + minSeedSeparation: 'minimum seed spacing as fraction of sqrt(cell area / b)', defectType: 'none | notch (members removed) | weak (strength reduced)', + defectX: 'defect centre x / W', defectY: 'defect centre y / H', defectSize: 'defect radius / W', defectWeakFactor: 'strength multiplier inside a weak zone', + missingFraction: 'fraction of members removed at random (diffuse defects)', + E: 'solid modulus (normalised, 1)', failStrain: 'failure strain eps_c = sigma_c / E of a level-0 member', + strengthCV: 'coefficient of variation of member strength (lognormal, mean 1)', strengthLevelRatio: 'strength multiplier per level: eps_c,k = eps_c s_l^k', + interfaceStrengthRatio: 'interface strength / member strength (inter-level strength)', interfaceStiffnessRatio: 'interface modulus / member modulus', + bendingFactor: 'multiplier on second moment of area I (bending-to-axial stiffness ratio control)', + residualStiffness: 'residual stiffness fraction after damage (0 = brittle removal)', ductilityRatio: 'final strain / eps_c for the damaged stage', + compressiveRatio: 'compressive failure strain / eps_c (0 = no compressive failure)', + gripType: 'clamped (u=v=theta prescribed) | pinned (u,v) | roller-top (v only at top)', dispIncrement: 'displacement increment', maxDisp: 'maximum applied displacement', + exactEvents: 'locate the exact displacement of each failure event (step-size independent)', maxIterations: 'maximum failure iterations per step', + tolerance: 'relative equilibrium residual tolerance', stabilization: 'ground-spring stabilisation relative to reference axial stiffness', + tieTolerance: 'elements within this relative utilisation of the maximum fail simultaneously', stopForceFraction: 'stop when force drops below this fraction of the peak', + maxEvents: 'maximum number of failure events', maxElements: 'element cap' +}; + +function factorPair(b, aspect) { + let best = null, bestScore = Infinity; + for (let n = 1; n <= b; n++) { + if (b % n) continue; + const m = b / n; + const score = Math.abs(Math.log(m / n) - Math.log(Math.max(aspect, 1))) + (m < n ? 1e-6 : 0); + if (score < bestScore) { bestScore = score; best = [m, n]; } + } + return best; +} + +function makeSeeds(poly, count, layout, disorder, rng, explicitMN, minSep) { + const pts = poly.pts, bb = HFX.geom.aabb(pts), cen = HFX.geom.centroid(pts); + const dx = Math.max(bb.xmax - bb.xmin, 1e-12), dy = Math.max(bb.ymax - bb.ymin, 1e-12); + const longX = dx >= dy, aspect = longX ? dx / dy : dy / dx; + let m, n; + if (explicitMN) { m = explicitMN[0]; n = explicitMN[1]; } + else { const mn = factorPair(count, aspect); m = longX ? mn[0] : mn[1]; n = longX ? mn[1] : mn[0]; } + const seeds = []; + const area = Math.abs(HFX.geom.area(pts)); + const cellScale = Math.sqrt(area / Math.max(count, 1)); + if (layout === 'radial' && !explicitMN && count >= 3) { + seeds.push(cen.slice()); + const rr = 0.55 * HFX.geom.polygonInradiusEstimate(pts); + const th0 = disorder > 0 ? rng.uniform(0, 2 * Math.PI) * disorder : 0; + for (let i = 0; i < count - 1; i++) { + const th = th0 + 2 * Math.PI * i / (count - 1) + (longX ? 0 : Math.PI / 2); + let sx = cen[0] + rr * Math.cos(th), sy = cen[1] + rr * Math.sin(th); + if (disorder > 0) { sx += disorder * rng.uniform(-0.5, 0.5) * rr; sy += disorder * rng.uniform(-0.5, 0.5) * rr; } + seeds.push(HFX.geom.pushInside([sx, sy], pts, cen, 0.8)); + } + } else { + const pitchX = dx / m, pitchY = dy / n; + for (let j = 0; j < n; j++) for (let i = 0; i < m; i++) { + let sx = bb.xmin + (i + 0.5) * pitchX, sy = bb.ymin + (j + 0.5) * pitchY; + if (layout === 'staggered' && n > 1 && (j % 2 === 1)) { sx += 0.5 * pitchX; if (sx > bb.xmax - 0.15 * pitchX) sx = bb.xmax - 0.15 * pitchX; } + if (disorder > 0) { sx += disorder * rng.uniform(-0.5, 0.5) * pitchX; sy += disorder * rng.uniform(-0.5, 0.5) * pitchY; } + seeds.push(HFX.geom.pushInside([sx, sy], pts, cen, 0.8)); + } + } + // enforce a minimum seed separation (only meaningful for disordered layouts) + if (disorder > 0 && minSep > 0) { + const dmin = minSep * cellScale; + for (let tries = 0; tries < 40; tries++) { + let moved = false; + for (let i = 0; i < seeds.length; i++) for (let j = 0; j < i; j++) { + if (Math.hypot(seeds[i][0] - seeds[j][0], seeds[i][1] - seeds[j][1]) < dmin) { + const ang = rng.uniform(0, 2 * Math.PI), r = cellScale * rng.uniform(0.3, 0.8); + seeds[i] = HFX.geom.pushInside([cen[0] + r * Math.cos(ang), cen[1] + r * Math.sin(ang)], pts, cen, 0.8); + moved = true; + } + } + if (!moved) break; + } + } + return seeds; +} + +function voronoiCells(poly, seeds, epsClean) { + const cells = []; + for (let i = 0; i < seeds.length; i++) { + const s = seeds[i]; + let cell = poly; + for (let j = 0; j < seeds.length; j++) { + if (j === i) continue; + const t = seeds[j]; + const ax = t[0] - s[0], ay = t[1] - s[1], mx = 0.5 * (s[0] + t[0]), my = 0.5 * (s[1] + t[1]); + cell = HFX.geom.clipHalfPlane(cell, ax, ay, -(ax * mx + ay * my), j); + if (cell.pts.length < 3) break; + } + cells.push(cell.pts.length >= 3 ? HFX.geom.cleanPolygon(cell, epsClean) : null); + } + return cells; +} + +/** Generate the hierarchical structure. Returns a structure object (undeformed geometry, element properties). */ +HFX.generateStructure = function (paramsIn) { + const p = Object.assign(HFX.defaultParams(), paramsIn || {}); + if (paramsIn && paramsIn.phys) p.phys = Object.assign({}, HFX.defaultParams().phys, paramsIn.phys); + const warnings = []; + const W = p.W, H = p.H, Lref = Math.max(W, H); + const D = Math.max(0, Math.round(p.depth)); + const b = Math.max(2, Math.round(p.branching)); + const n0x = Math.max(1, Math.round(p.n0x)), n0y = Math.max(1, Math.round(p.n0y)); + const rngGeom = HFX.makeRNG(p.seed, 'geometry'); + const rngBrace = HFX.makeRNG(p.seed, 'brace'); + const rngPrune = HFX.makeRNG(p.seed, 'prune'); + const rngStrength = HFX.makeRNG(p.seed, 'strength'); + const rngDefect = HFX.makeRNG(p.seed, 'defect'); + const expectedLeaves = n0x * n0y * Math.pow(b, D); + if (expectedLeaves > p.maxElements) { + throw new Error('Requested hierarchy (' + expectedLeaves + ' leaf cells) exceeds the element cap (' + p.maxElements + '). Reduce depth or branching.'); + } + const segments = []; // {p1,p2,level,kind,segId} + const leafCells = []; // polygons (pts arrays) + const cellsByLevel = []; + for (let k = 0; k <= D; k++) cellsByLevel.push([]); + const rootPts = [[0, 0], [W, 0], [W, H], [0, H]]; + if (p.includeFrame && p.frameMode !== 'none') for (let i = 0; i < 4; i++) { + const horizontal = (i === 0 || i === 2); + if (horizontal && p.frameMode === 'sides') continue; + segments.push({ p1: rootPts[i], p2: rootPts[(i + 1) % 4], level: 0, kind: 'frame' }); + } + const root = { pts: rootPts, tags: [-1, -1, -1, -1] }; + + function subdivide(poly, level, count, explicitMN) { + const bbox = HFX.geom.aabb(poly.pts); + const diag = Math.hypot(bbox.xmax - bbox.xmin, bbox.ymax - bbox.ymin); + const epsClean = 1e-7 * diag; + const levelDisorder = level >= (p.disorderMinLevel || 0) ? p.disorder : 0; + const seeds = makeSeeds(poly, count, p.layout, levelDisorder, rngGeom, explicitMN, p.minSeedSeparation); + const cells = voronoiCells(poly, seeds, epsClean); + for (let i = 0; i < cells.length; i++) { + const c = cells[i]; if (!c) { warnings.push('degenerate Voronoi cell skipped at level ' + level); continue; } + const n = c.pts.length; + for (let e = 0; e < n; e++) { + const tag = c.tags[e]; + if (typeof tag === 'number' && tag > i && cells[tag]) { + const p1 = c.pts[e], p2 = c.pts[(e + 1) % n]; + if (Math.hypot(p2[0] - p1[0], p2[1] - p1[1]) > 10 * epsClean) segments.push({ p1: p1, p2: p2, level: level, kind: 'wall' }); + } + } + } + for (let i = 0; i < cells.length; i++) { + const c = cells[i]; if (!c) continue; + cellsByLevel[level].push(c.pts); + const child = { pts: c.pts, tags: c.pts.map(function () { return -1; }) }; + if (level < D) subdivide(child, level + 1, b, null); else leafCells.push(c.pts); + } + } + if (n0x * n0y > 1) subdivide(root, 0, n0x * n0y, [n0x, n0y]); + else { cellsByLevel[0].push(rootPts); if (D > 0) subdivide(root, 1, b, null); else leafCells.push(rootPts); } + + // ---- connectivity pruning of finest-level walls (design choice, before density calibration) + let prunedSegments = 0; + if (p.connectivity < 1) { + for (const s of segments) if (s.kind === 'wall' && s.level === D && rngPrune.next() > p.connectivity) { s.pruned = true; prunedSegments++; } + } + // ---- braces (fan diagonals in leaf cells) + let braceCount = 0; + if (p.redundancy > 0) { + for (let ci = 0; ci < leafCells.length; ci++) { + const pts = leafCells[ci], n = pts.length; if (n < 4) continue; + const cen = HFX.geom.centroid(pts); + let c0 = 0; + if (p.disorder > 0) c0 = rngBrace.int(n); + else { // mirror-symmetric deterministic choice: corner nearest (0,0) on the left half, nearest (W,0) on the right half + const tx = cen[0] < 0.5 * W ? 0 : W; let best = Infinity; + for (let i = 0; i < n; i++) { const dd = Math.hypot(pts[i][0] - tx, pts[i][1]); if (dd < best - 1e-12) { best = dd; c0 = i; } } + } + for (let k = 2; k <= n - 2; k++) { + const take = p.redundancy >= 1 ? true : (rngBrace.next() < p.redundancy); + if (!take) continue; + segments.push({ p1: pts[c0], p2: pts[(c0 + k) % n], level: D, kind: 'brace' }); + braceCount++; + } + } + } + const activeSegments = segments.filter(function (s) { return !s.pruned; }); + activeSegments.forEach(function (s, i) { s.segId = i; }); + + // ---- noding: nodes from endpoints, T-junction detection, splitting + const tolN = 1e-7 * Lref; + const nodes = []; const nodeIndex = new Map(); + function nodeId(x, y) { + const kx = Math.round(x / tolN), ky = Math.round(y / tolN); + for (let a = -1; a <= 1; a++) for (let c = -1; c <= 1; c++) { + const id = nodeIndex.get((kx + a) + ',' + (ky + c)); + if (id !== undefined && Math.hypot(nodes[id].x - x, nodes[id].y - y) <= 2 * tolN) return id; + } + const id = nodes.length; nodes.push({ x: x, y: y, level: Infinity }); nodeIndex.set(kx + ',' + ky, id); return id; + } + for (const s of activeSegments) { + s.nA = nodeId(s.p1[0], s.p1[1]); s.nB = nodeId(s.p2[0], s.p2[1]); + s.L = Math.hypot(s.p2[0] - s.p1[0], s.p2[1] - s.p1[1]); + if (s.level < nodes[s.nA].level) nodes[s.nA].level = s.level; + if (s.level < nodes[s.nB].level) nodes[s.nB].level = s.level; + s.interior = []; + } + // spatial hash of nodes for on-segment search + const cellSize = Math.max(Lref / 64, 1e-6); + const hash = new Map(); + const hk = function (ix, iy) { return ix + ',' + iy; }; + nodes.forEach(function (nd, id) { const k = hk(Math.floor(nd.x / cellSize), Math.floor(nd.y / cellSize)); if (!hash.has(k)) hash.set(k, []); hash.get(k).push(id); }); + const tolOn = 1e-7 * Lref; + for (const s of activeSegments) { + const ex = (s.p2[0] - s.p1[0]) / s.L, ey = (s.p2[1] - s.p1[1]) / s.L; + const xmin = Math.min(s.p1[0], s.p2[0]) - tolOn, xmax = Math.max(s.p1[0], s.p2[0]) + tolOn; + const ymin = Math.min(s.p1[1], s.p2[1]) - tolOn, ymax = Math.max(s.p1[1], s.p2[1]) + tolOn; + const ix0 = Math.floor(xmin / cellSize), ix1 = Math.floor(xmax / cellSize), iy0 = Math.floor(ymin / cellSize), iy1 = Math.floor(ymax / cellSize); + for (let ix = ix0; ix <= ix1; ix++) for (let iy = iy0; iy <= iy1; iy++) { + const bucket = hash.get(hk(ix, iy)); if (!bucket) continue; + for (const id of bucket) { + if (id === s.nA || id === s.nB) continue; + const nd = nodes[id]; + const rx = nd.x - s.p1[0], ry = nd.y - s.p1[1]; + const t = rx * ex + ry * ey; + if (t <= tolOn || t >= s.L - tolOn) continue; + const dist = Math.abs(rx * ey - ry * ex); + if (dist <= tolOn) { s.interior.push({ id: id, t: t }); if (s.level < nd.level) nd.level = s.level; } + } + } + } + // ---- split segments into elements (with interface nodes) + const elements = []; + const fInt = Math.min(0.45, Math.max(0.01, p.interfaceFraction)); + for (const s of activeSegments) { + s.interior.sort(function (a, b2) { return a.t - b2.t; }); + const chain = [{ id: s.nA, t: 0 }].concat(s.interior, [{ id: s.nB, t: s.L }]); + const flags = chain.map(function () { return { ifaceA: false, ifaceB: false }; }); + if (s.kind === 'wall') { + const coarseA = nodes[s.nA].level < s.level, coarseB = nodes[s.nB].level < s.level; + if (p.interfaceMode === 'segment') { + const insert = function (tPos, fromA) { + // do not insert if an existing chain node is already within the interface zone + for (const c of chain) { if (fromA ? (c.t > 1e-12 && c.t <= tPos + 1e-12) : (c.t < s.L - 1e-12 && c.t >= tPos - 1e-12)) return; } + const x = s.p1[0] + (s.p2[0] - s.p1[0]) * tPos / s.L, y = s.p1[1] + (s.p2[1] - s.p1[1]) * tPos / s.L; + const id = nodeId(x, y); nodes[id].level = Math.min(nodes[id].level, s.level); nodes[id].ifaceNode = true; + chain.push({ id: id, t: tPos }); chain.sort(function (a, b2) { return a.t - b2.t; }); + }; + if (coarseA) insert(fInt * s.L, true); + if (coarseB) insert(s.L - fInt * s.L, false); + } + if (p.interfaceMode !== 'none') { s.coarseA = coarseA; s.coarseB = coarseB; } + } + for (let i = 0; i + 1 < chain.length; i++) { + const a = chain[i].id, c = chain[i + 1].id; + if (a === c) continue; + const isIface = (s.kind === 'wall' && p.interfaceMode !== 'none') && ((i === 0 && s.coarseA) || (i === chain.length - 2 && s.coarseB)); + elements.push({ n1: a, n2: c, level: s.level, kind: s.kind, isInterface: !!isIface, segId: s.segId, ifaceEnd: isIface ? (i === 0 ? 'A' : 'B') : '' }); + } + } + // ---- short-feature merge (union–find on nodes closer than mergeFraction * leaf cell size) + const leafScale = Math.sqrt(W * H / Math.max(1, leafCells.length)); + const lMin = p.mergeFraction * leafScale; + const parent = nodes.map(function (_, i) { return i; }); + const find = function (i) { while (parent[i] !== i) { parent[i] = parent[parent[i]]; i = parent[i]; } return i; }; + let mergedNodes = 0; + if (lMin > 0) { + const hash2 = new Map(); const cs2 = Math.max(lMin, 1e-9); + nodes.forEach(function (nd, id) { const k = hk(Math.floor(nd.x / cs2), Math.floor(nd.y / cs2)); if (!hash2.has(k)) hash2.set(k, []); hash2.get(k).push(id); }); + nodes.forEach(function (nd, id) { + const ix = Math.floor(nd.x / cs2), iy = Math.floor(nd.y / cs2); + for (let a = -1; a <= 1; a++) for (let c = -1; c <= 1; c++) { + const bucket = hash2.get(hk(ix + a, iy + c)); if (!bucket) continue; + for (const j of bucket) { if (j <= id) continue; if (Math.hypot(nodes[j].x - nd.x, nodes[j].y - nd.y) < lMin) { const ra = find(id), rb = find(j); if (ra !== rb) { parent[rb] = ra; mergedNodes++; } } } + } + }); + } + // compact nodes + const clusters = new Map(); const newNodes = []; const mapId = new Int32Array(nodes.length); + nodes.forEach(function (nd, id) { + const r = find(id); + if (!clusters.has(r)) { clusters.set(r, newNodes.length); newNodes.push({ x: 0, y: 0, level: Infinity, count: 0, ifaceNode: false }); } + const ni = clusters.get(r); mapId[id] = ni; const nn = newNodes[ni]; + nn.x += nd.x; nn.y += nd.y; nn.count++; nn.level = Math.min(nn.level, nd.level); nn.ifaceNode = nn.ifaceNode || !!nd.ifaceNode; + }); + newNodes.forEach(function (nn) { nn.x /= nn.count; nn.y /= nn.count; delete nn.count; }); + // snap boundary nodes exactly onto the specimen boundary + const tolBC = 1e-6 * Lref; + newNodes.forEach(function (nn) { + if (Math.abs(nn.x) < tolBC) nn.x = 0; if (Math.abs(nn.x - W) < tolBC) nn.x = W; + if (Math.abs(nn.y) < tolBC) nn.y = 0; if (Math.abs(nn.y - H) < tolBC) nn.y = H; + nn.onBottom = nn.y === 0; nn.onTop = nn.y === H; nn.onLeft = nn.x === 0; nn.onRight = nn.x === W; + }); + // remap elements, drop degenerate and duplicates + const seen = new Map(); const finalElements = []; let dropped = 0; + for (const e of elements) { + const a = mapId[e.n1], c = mapId[e.n2]; if (a === c) { dropped++; continue; } + const key = Math.min(a, c) + ',' + Math.max(a, c); + if (seen.has(key)) { const prev = finalElements[seen.get(key)]; if (e.level < prev.level) { prev.level = e.level; prev.kind = e.kind; } dropped++; continue; } + seen.set(key, finalElements.length); + e.n1 = a; e.n2 = c; finalElements.push(e); + } + finalElements.forEach(function (e, i) { + e.id = i; const A = newNodes[e.n1], B = newNodes[e.n2]; + e.L = Math.hypot(B.x - A.x, B.y - A.y); e.cx = 0.5 * (A.x + B.x); e.cy = 0.5 * (A.y + B.y); + e.absent = false; e.strengthFactor = 1; + }); + // ---- defects (applied to the finished design): notch / weak zone / random missing members + let defectRemoved = 0, defectWeakened = 0; + if (p.defectType === 'notch' || p.defectType === 'weak') { + const cx = p.defectX * W, cy = p.defectY * H, r = p.defectSize * W; + for (const e of finalElements) { + const A = newNodes[e.n1], B = newNodes[e.n2]; + // distance from defect centre to the segment + const ex = B.x - A.x, ey = B.y - A.y, L2 = ex * ex + ey * ey; + let t = L2 > 0 ? ((cx - A.x) * ex + (cy - A.y) * ey) / L2 : 0; t = Math.max(0, Math.min(1, t)); + const dd = Math.hypot(A.x + t * ex - cx, A.y + t * ey - cy); + if (dd <= r) { if (p.defectType === 'notch') { e.absent = true; e.defect = 'notch'; defectRemoved++; } else { e.strengthFactor *= p.defectWeakFactor; e.defect = 'weak'; defectWeakened++; } } + } + } + if (p.missingFraction > 0) { + for (const e of finalElements) { if (!e.absent && e.kind !== 'frame' && rngDefect.next() < p.missingFraction) { e.absent = true; e.defect = 'missing'; defectRemoved++; } } + } + // ---- density calibration (design members, i.e. before defects are cut) + const rt = Math.max(1e-6, p.thicknessRatio); + // members lying entirely on a grip line (both nodes on the same grip) are rigidly held by the grip: they carry no strain and are + // excluded from the material budget (they belong to the grip region, not to the gauge structure) + for (const e of finalElements) { const A = newNodes[e.n1], B = newNodes[e.n2]; e.gripLine = (A.onTop && B.onTop) || (A.onBottom && B.onBottom); } + let S = 0, L0sum = 0, L0n = 0; + for (const e of finalElements) { if (e.gripLine) continue; S += e.L * Math.pow(rt, e.level); if (e.level === 0) { L0sum += e.L; L0n++; } } + let t0; + const L0ref = L0n > 0 ? L0sum / L0n : W / n0x; + if (p.densityMode === 'slenderness') t0 = L0ref / Math.max(1e-9, p.slenderness0); + else t0 = p.relDensity * W * H / Math.max(S, 1e-300); + let matDesign = 0, matActual = 0, matGrip = 0; + const levelStats = []; + for (let k = 0; k <= D; k++) levelStats.push({ level: k, count: 0, length: 0, thickness: t0 * Math.pow(rt, k), material: 0, interfaces: 0, braces: 0, meanSlenderness: 0, wallSlenderness: 0, walls: 0, absent: 0 }); + const wallSets = []; for (let k = 0; k <= D; k++) wallSets.push(new Set()); + for (const e of finalElements) { + e.t = t0 * Math.pow(rt, e.level); + e.A = e.t; e.I = p.bendingFactor * e.t * e.t * e.t / 12; + e.Emod = p.E * (e.isInterface ? p.interfaceStiffnessRatio : 1); + const xi = rngStrength.lognormalMean1(p.strengthCV); + e.epsC = p.failStrain * Math.pow(p.strengthLevelRatio, e.level) * (e.isInterface ? p.interfaceStrengthRatio : 1) * xi * e.strengthFactor; + e.xi = xi; + if (e.gripLine) { matGrip += e.L * e.t; continue; } + matDesign += e.L * e.t; if (!e.absent) matActual += e.L * e.t; + const ls = levelStats[e.level]; ls.count++; ls.length += e.L; ls.material += e.L * e.t; if (e.isInterface) ls.interfaces++; if (e.kind === 'brace') ls.braces++; if (e.absent) ls.absent++; + wallSets[e.level].add(e.segId); + } + levelStats.forEach(function (ls, k) { ls.walls = wallSets[k].size; ls.meanSlenderness = ls.count ? (ls.length / ls.count) / ls.thickness : 0; ls.wallSlenderness = ls.walls ? (ls.length / ls.walls) / ls.thickness : 0; ls.materialFraction = matDesign > 0 ? ls.material / matDesign : 0; }); + // ---- connectivity statistics + const deg = new Int32Array(newNodes.length); let nActive = 0; + for (const e of finalElements) if (!e.absent) { deg[e.n1]++; deg[e.n2]++; } + for (let i = 0; i < newNodes.length; i++) if (deg[i] > 0) nActive++; + const nEl = finalElements.filter(function (e) { return !e.absent; }).length; + const nTop = newNodes.filter(function (n) { return n.onTop; }).length, nBottom = newNodes.filter(function (n) { return n.onBottom; }).length; + const structure = { + params: p, W: W, H: H, depth: D, branching: b, nodes: newNodes, elements: finalElements, leafCells: leafCells, cellsByLevel: cellsByLevel, + t0: t0, levelStats: levelStats, warnings: warnings, + stats: { + nodes: newNodes.length, activeNodes: nActive, elements: finalElements.length, activeElements: nEl, leafCells: leafCells.length, + relDensityDesign: matDesign / (W * H), relDensityActual: matActual / (W * H), gripLineMaterial: matGrip / (W * H), t0: t0, tMin: t0 * Math.pow(rt, D), tMax: t0, + meanCoordination: nActive ? 2 * nEl / nActive : 0, braces: braceCount, prunedSegments: prunedSegments, mergedNodes: mergedNodes, droppedElements: dropped, + defectRemoved: defectRemoved, defectWeakened: defectWeakened, interfaces: finalElements.filter(function (e) { return e.isInterface; }).length, + gripNodesTop: nTop, gripNodesBottom: nBottom, leafScale: leafScale, minSlendernessLevel: Math.min.apply(null, levelStats.filter(function (l) { return l.count; }).map(function (l) { return l.wallSlenderness; })), minElementSlenderness: Math.min.apply(null, levelStats.filter(function (l) { return l.count; }).map(function (l) { return l.meanSlenderness; })) + } + }; + if (nTop === 0 || nBottom === 0) warnings.push('no grip nodes found on top/bottom boundary'); + return structure; +}; + +/** Compact, human-readable parameter summary */ +HFX.paramsSummary = function (p) { + return 'D=' + p.depth + ' b=' + p.branching + ' n0=' + p.n0x + 'x' + p.n0y + ' ' + p.layout + ' dis=' + p.disorder + (p.disorderMinLevel ? '(L>=' + p.disorderMinLevel + ')' : '') + ' rt=' + p.thicknessRatio + ' rho=' + p.relDensity + ' red=' + p.redundancy + ' con=' + p.connectivity + ' sInt=' + p.interfaceStrengthRatio + ' cv=' + p.strengthCV + ' seed=' + p.seed; +}; diff --git a/data/Run 1/RESULT Run 1/app/src/core/30_solver.js b/data/Run 1/RESULT Run 1/app/src/core/30_solver.js new file mode 100644 index 0000000000000000000000000000000000000000..b9d83856300dd3d97227fd1b29b080d6726edc57 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/30_solver.js @@ -0,0 +1,310 @@ +// ============================================================================ +// 30. 2-D Euler–Bernoulli beam-network model +// DOF per node: (u, v, theta). Element: prismatic beam, axial + bending, +// small strain, small rotation, linear elastic. Global K = sum T^T k_local T. +// Prescribed displacements (grips) are eliminated by partitioning: +// K_ff u_f = - K_fp u_p ; reactions r_p = K_pf u_f + K_pp u_p +// Linear system: envelope (profile) LDL^T with reverse Cuthill–McKee ordering. +// Stabilisation: a tiny ground spring eps * k_ref on every free DOF keeps K_ff +// positive definite when fragments detach (its force is reported in residuals). +// ============================================================================ +function localBeamStiffness(EA_L, EI, L, out) { + const k1 = 12 * EI / (L * L * L), k2 = 6 * EI / (L * L), k3 = 4 * EI / L, k4 = 2 * EI / L; + out.fill(0); + out[0] = EA_L; out[3] = -EA_L; out[18] = -EA_L; out[21] = EA_L; + out[7] = k1; out[8] = k2; out[10] = -k1; out[11] = k2; + out[13] = k2; out[14] = k3; out[16] = -k2; out[17] = k4; + out[25] = -k1; out[26] = -k2; out[28] = k1; out[29] = -k2; + out[31] = k2; out[32] = k4; out[34] = -k2; out[35] = k3; + return out; +} +/** K_global = T^T k_local T with T = blockdiag(R, R), R = [[c,s,0],[-s,c,0],[0,0,1]] */ +function transformToGlobal(kl, c, s, out) { + // T is 6x6: rows: [c s 0 0 0 0],[-s c 0 0 0 0],[0 0 1 0 0 0],[0 0 0 c s 0],[0 0 0 -s c 0],[0 0 0 0 0 1] + const T = [[c, s, 0, 0, 0, 0], [-s, c, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0], [0, 0, 0, c, s, 0], [0, 0, 0, -s, c, 0], [0, 0, 0, 0, 0, 1]]; + const tmp = new Float64Array(36); + for (let i = 0; i < 6; i++) for (let j = 0; j < 6; j++) { let v = 0; for (let k = 0; k < 6; k++) v += kl[i * 6 + k] * T[k][j]; tmp[i * 6 + j] = v; } + for (let i = 0; i < 6; i++) for (let j = 0; j < 6; j++) { let v = 0; for (let k = 0; k < 6; k++) v += T[k][i] * tmp[k * 6 + j]; out[i * 6 + j] = v; } + return out; +} + +/** Envelope (profile) symmetric LDL^T factorisation. Row storage of the lower triangle. */ +function EnvelopeLDL(n, first) { + this.n = n; this.first = first; + this.rowStart = new Int32Array(n + 1); + for (let i = 0; i < n; i++) this.rowStart[i + 1] = this.rowStart[i] + (i - first[i] + 1); + this.vals = new Float64Array(this.rowStart[n]); + this.D = new Float64Array(n); + this.factorized = false; + this.minPivot = Infinity; this.maxPivot = 0; this.nonPositive = 0; +} +EnvelopeLDL.prototype.add = function (i, j, v) { // i >= j + if (i < j) { const t = i; i = j; j = t; } + this.vals[this.rowStart[i] + (j - this.first[i])] += v; +}; +EnvelopeLDL.prototype.factorize = function () { + const n = this.n, first = this.first, rs = this.rowStart, a = this.vals, D = this.D; + const g = new Float64Array(n); + let minP = Infinity, maxP = 0, nonPos = 0; + for (let i = 0; i < n; i++) { + const fi = first[i], ri = rs[i]; + for (let j = fi; j < i; j++) { + const fj = first[j], rj = rs[j]; + const ks = fi > fj ? fi : fj; + let s = a[ri + (j - fi)]; + let ai = ks - fi, aj = rj + (ks - fj); + for (let k = ks; k < j; k++, ai++, aj++) s -= g[ai] * a[aj]; + a[ri + (j - fi)] = s / D[j]; + g[j - fi] = s; + } + let d = a[ri + (i - fi)]; + for (let k = fi; k < i; k++) d -= g[k - fi] * a[ri + (k - fi)]; + D[i] = d; + if (d <= 0) { nonPos++; D[i] = 1e-300; } + if (d < minP) minP = d; if (d > maxP) maxP = d; + } + this.minPivot = minP; this.maxPivot = maxP; this.nonPositive = nonPos; this.factorized = true; + return nonPos === 0; +}; +EnvelopeLDL.prototype.solve = function (b, x) { + const n = this.n, first = this.first, rs = this.rowStart, a = this.vals, D = this.D; + if (!x) x = new Float64Array(n); + for (let i = 0; i < n; i++) { const fi = first[i], ri = rs[i]; let s = b[i]; for (let k = fi; k < i; k++) s -= a[ri + (k - fi)] * x[k]; x[i] = s; } + for (let i = 0; i < n; i++) x[i] /= D[i]; + for (let i = n - 1; i >= 0; i--) { const fi = first[i], ri = rs[i]; const xi = x[i]; for (let k = fi; k < i; k++) x[k] -= a[ri + (k - fi)] * xi; } + return x; +}; +HFX.EnvelopeLDL = EnvelopeLDL; + +/** Reverse Cuthill–McKee ordering of the nodes in `mask` given adjacency lists. */ +function rcmOrder(nNodes, adj, mask) { + const visited = new Uint8Array(nNodes); const order = []; + const deg = new Int32Array(nNodes); for (let i = 0; i < nNodes; i++) deg[i] = adj[i].length; + const bfs = function (start, collect) { + const q = [start]; const seen = new Uint8Array(nNodes); seen[start] = 1; let last = start; const dist = new Int32Array(nNodes); + for (let h = 0; h < q.length; h++) { + const v = q[h]; last = v; + const nb = adj[v].filter(function (w) { return mask[w] && !seen[w]; }).sort(function (x, y) { return deg[x] - deg[y]; }); + for (const w of nb) { seen[w] = 1; dist[w] = dist[v] + 1; q.push(w); } + } + if (collect) return q; + // pick the farthest node with minimum degree as pseudo-peripheral + const maxD = dist[last]; let best = last; + for (let i = 0; i < q.length; i++) if (dist[q[i]] === maxD && deg[q[i]] < deg[best]) best = q[i]; + return best; + }; + for (let s = 0; s < nNodes; s++) { + if (!mask[s] || visited[s]) continue; + let start = s; + // pseudo-peripheral start: two BFS passes + start = bfs(bfs(start, false), false); + const comp = bfs(start, true); + for (const v of comp) { visited[v] = 1; order.push(v); } + } + order.reverse(); + return order; +} + +/** + * BeamModel: manages element states, boundary conditions, assembly, factorisation, + * unit-displacement solution and element force recovery. + */ +HFX.BeamModel = function (structure, params) { + this.s = structure; this.p = Object.assign({}, structure.params, params || {}); + const nodes = structure.nodes, els = structure.elements; + this.nNodes = nodes.length; this.nEl = els.length; this.ndof = 3 * nodes.length; + this.state = new Int8Array(this.nEl); // 0 intact, 1 damaged, 2 failed + for (let i = 0; i < this.nEl; i++) if (els[i].absent) this.state[i] = 2; + // per-element geometric data + this.cosE = new Float64Array(this.nEl); this.sinE = new Float64Array(this.nEl); this.LE = new Float64Array(this.nEl); + for (let i = 0; i < this.nEl; i++) { const e = els[i], A = nodes[e.n1], B = nodes[e.n2]; const dx = B.x - A.x, dy = B.y - A.y; const L = Math.hypot(dx, dy); this.LE[i] = L; this.cosE[i] = dx / L; this.sinE[i] = dy / L; } + this.Ke = new Array(this.nEl); // global element stiffness (intact); scaled by residual factor when damaged + const kl = new Float64Array(36); + for (let i = 0; i < this.nEl; i++) { const e = els[i]; const out = new Float64Array(36); localBeamStiffness(e.Emod * e.A / this.LE[i], e.Emod * e.I, this.LE[i], kl); transformToGlobal(kl, this.cosE[i], this.sinE[i], out); this.Ke[i] = out; } + // reference stiffness for stabilisation + // reference axial stiffness for the stabilisation springs: E * mean(t) / mean(L) (robust to short stubby elements) + let tsum = 0, lsum = 0, cnt = 0; for (let i = 0; i < this.nEl; i++) { const e = els[i]; tsum += e.Emod * e.A; lsum += this.LE[i]; cnt++; } + this.kRef = cnt ? (tsum / cnt) / (lsum / cnt) : 1; this.Lref = Math.max(structure.W, structure.H); + this.u = new Float64Array(this.ndof); this.u1 = new Float64Array(this.ndof); + this.fint = new Float64Array(this.ndof); + this.N = new Float64Array(this.nEl); this.M1 = new Float64Array(this.nEl); this.M2 = new Float64Array(this.nEl); this.V = new Float64Array(this.nEl); + this.epsMax = new Float64Array(this.nEl); this.epsMin = new Float64Array(this.nEl); this.util = new Float64Array(this.nEl); + this.util1 = new Float64Array(this.nEl); this.N1 = new Float64Array(this.nEl); + this.rebuildCount = 0; this.solveCount = 0; this.factorTimeMs = 0; this.lastRebuild = null; + this.setupBC(); +}; +HFX.BeamModel.prototype.stiffnessFactor = function (i) { const st = this.state[i]; return st === 0 ? 1 : (st === 1 ? this.p.residualStiffness : 0); }; +HFX.BeamModel.prototype.setupBC = function () { + const nodes = this.s.nodes, p = this.p; const n = this.nNodes; + this.presc = new Uint8Array(this.ndof); this.prescVal = new Float64Array(this.ndof); // pattern for unit applied displacement + this.topV = []; this.bottomV = []; + for (let i = 0; i < n; i++) { + const nd = nodes[i]; + if (nd.bc) { // explicit per-node override {u:0|1, v:0|1, th:0|1, vValue} + if (nd.bc.u) this.presc[3 * i] = 1; if (nd.bc.v) { this.presc[3 * i + 1] = 1; if (nd.bc.vValue) { this.prescVal[3 * i + 1] = nd.bc.vValue; this.topV.push(3 * i + 1); } else if (nd.onBottom) this.bottomV.push(3 * i + 1); } + if (nd.bc.th) this.presc[3 * i + 2] = 1; + continue; + } + if (nd.onTop) { + this.presc[3 * i + 1] = 1; this.prescVal[3 * i + 1] = 1; this.topV.push(3 * i + 1); + if (p.gripType === 'clamped') { this.presc[3 * i] = 1; this.presc[3 * i + 2] = 1; } + else if (p.gripType === 'pinned') { this.presc[3 * i] = 1; } + } + if (nd.onBottom) { + this.presc[3 * i + 1] = 1; this.bottomV.push(3 * i + 1); + this.presc[3 * i] = 1; // horizontal fixed at the bottom for all grip types (removes rigid-body translation) + if (p.gripType === 'clamped') this.presc[3 * i + 2] = 1; + } + } +}; +/** Rebuild the active system (after any state change): ordering, envelope, factorisation, unit solution. */ +HFX.BeamModel.prototype.rebuild = function () { + const t0 = (typeof performance !== 'undefined' && performance.now) ? performance.now() : Date.now(); + const els = this.s.elements, n = this.nNodes, ndof = this.ndof; + // active nodes and adjacency + const adj = new Array(n); for (let i = 0; i < n; i++) adj[i] = []; + const active = new Uint8Array(n); + for (let i = 0; i < this.nEl; i++) { if (this.state[i] === 2) continue; if (this.state[i] === 1 && this.p.residualStiffness <= 0) continue; const e = els[i]; adj[e.n1].push(e.n2); adj[e.n2].push(e.n1); active[e.n1] = 1; active[e.n2] = 1; } + // effective prescribed set: inactive nodes fully fixed (zero). Detached fragments (components of the intact network that + // touch neither grip) are unloaded rigid bodies; their DOFs are frozen (displayed undeformed) instead of being held by the + // stabilisation springs alone, which keeps the system well conditioned. + const presc = new Uint8Array(this.presc); for (let i = 0; i < n; i++) if (!active[i]) { presc[3 * i] = 1; presc[3 * i + 1] = 1; presc[3 * i + 2] = 1; } + const reach = new Uint8Array(n); const q = []; + for (let i = 0; i < n; i++) if (active[i] && (this.s.nodes[i].onTop || this.s.nodes[i].onBottom || this.s.nodes[i].bc)) { reach[i] = 1; q.push(i); } + for (let h = 0; h < q.length; h++) { const v = q[h]; for (const w of adj[v]) if (!reach[w]) { reach[w] = 1; q.push(w); } } + let frozen = 0; + for (let i = 0; i < n; i++) if (active[i] && !reach[i]) { presc[3 * i] = 1; presc[3 * i + 1] = 1; presc[3 * i + 2] = 1; frozen++; } + this.frozenNodes = frozen; + const mask = new Uint8Array(n); for (let i = 0; i < n; i++) mask[i] = active[i] && (!presc[3 * i] || !presc[3 * i + 1] || !presc[3 * i + 2]) ? 1 : 0; + const order = rcmOrder(n, adj, mask); + const dofNew = new Int32Array(ndof).fill(-1); let nf = 0; + for (const v of order) for (let c = 0; c < 3; c++) { const d = 3 * v + c; if (!presc[d]) dofNew[d] = nf++; } + this.nFree = nf; this.dofNew = dofNew; this.prescEff = presc; + // envelope structure + const first = new Int32Array(nf); for (let i = 0; i < nf; i++) first[i] = i; + const dofs = new Int32Array(6); + for (let ei = 0; ei < this.nEl; ei++) { + const sf = this.stiffnessFactor(ei); if (sf <= 0) continue; + const e = els[ei]; dofs[0] = 3 * e.n1; dofs[1] = 3 * e.n1 + 1; dofs[2] = 3 * e.n1 + 2; dofs[3] = 3 * e.n2; dofs[4] = 3 * e.n2 + 1; dofs[5] = 3 * e.n2 + 2; + let mn = Infinity, mx = -1; + for (let a = 0; a < 6; a++) { const r = dofNew[dofs[a]]; if (r < 0) continue; if (r < mn) mn = r; if (r > mx) mx = r; } + if (mx < 0) continue; + for (let a = 0; a < 6; a++) { const r = dofNew[dofs[a]]; if (r >= 0 && mn < first[r]) first[r] = mn; } + } + const ldl = new EnvelopeLDL(nf, first); + const rhs1 = new Float64Array(nf); + const stab = this.p.stabilization * this.kRef; + for (let ei = 0; ei < this.nEl; ei++) { + const sf = this.stiffnessFactor(ei); if (sf <= 0) continue; + const e = els[ei], K = this.Ke[ei]; + dofs[0] = 3 * e.n1; dofs[1] = 3 * e.n1 + 1; dofs[2] = 3 * e.n1 + 2; dofs[3] = 3 * e.n2; dofs[4] = 3 * e.n2 + 1; dofs[5] = 3 * e.n2 + 2; + for (let a = 0; a < 6; a++) { + const ra = dofNew[dofs[a]]; if (ra < 0) continue; + for (let b2 = 0; b2 < 6; b2++) { + const kab = K[a * 6 + b2] * sf; if (kab === 0) continue; + const rb = dofNew[dofs[b2]]; + if (rb >= 0) { if (rb <= ra) ldl.add(ra, rb, kab); } + else { const up = this.prescVal[dofs[b2]]; if (up !== 0) rhs1[ra] -= kab * up; } + } + } + } + // ground-spring stabilisation on every free DOF (rotational DOFs scaled by Lref^2) + for (let d = 0; d < ndof; d++) { const r = dofNew[d]; if (r >= 0) ldl.vals[ldl.rowStart[r] + (r - first[r])] += (d % 3 === 2 ? stab * this.Lref * this.Lref : stab); } + const ok = ldl.factorize(); + this.ldl = ldl; this.rhs1 = rhs1; + // unit solution + const uf = ldl.solve(rhs1); + this.u1.fill(0); + for (let d = 0; d < ndof; d++) { const r = dofNew[d]; this.u1[d] = r >= 0 ? uf[r] : (presc[d] ? this.prescVal[d] : 0); } + this.computeElementResults(this.u1, this.util1, this.N1); + const dSaved = this.d; this.d = 1; + const react = this.computeReactions(this.u1); + this.d = dSaved; + this.F1 = react.Ftop; this.Fbot1 = react.Fbot; this.residual1 = react.residual; this.stabForce1 = react.stabForce; + if (this.Fref === undefined) this.Fref = Math.abs(react.Ftop); // force per unit displacement of the intact structure + let envelope = ldl.vals.length; let maxBand = 0; for (let i = 0; i < nf; i++) if (i - first[i] > maxBand) maxBand = i - first[i]; + this.rebuildCount++; + const t1 = (typeof performance !== 'undefined' && performance.now) ? performance.now() : Date.now(); + this.factorTimeMs += (t1 - t0); + this.lastRebuild = { nFree: nf, envelope: envelope, maxBandwidth: maxBand, factorOK: ok, minPivot: ldl.minPivot, maxPivot: ldl.maxPivot, nonPositivePivots: ldl.nonPositive, timeMs: t1 - t0, residualUnit: react.residual, frozenNodes: frozen }; + return this.lastRebuild; +}; +/** Solve at applied displacement d (forward/back substitution with the cached factorisation). */ +HFX.BeamModel.prototype.solveAt = function (d) { + const nf = this.nFree, ndof = this.ndof, dofNew = this.dofNew, presc = this.prescEff; + const rhs = new Float64Array(nf); for (let i = 0; i < nf; i++) rhs[i] = this.rhs1[i] * d; + const uf = this.ldl.solve(rhs); + for (let dd = 0; dd < ndof; dd++) { const r = dofNew[dd]; this.u[dd] = r >= 0 ? uf[r] : (presc[dd] ? this.prescVal[dd] * d : 0); } + this.solveCount++; this.d = d; + this.computeElementResults(this.u, this.util, this.N); + const react = this.computeReactions(this.u); + this.F = react.Ftop; this.Fbot = react.Fbot; this.residual = react.residual; this.stabForce = react.stabForce; this.d = d; this.lastReact = react; + return react; +}; +/** Element internal forces, fibre strains and utilisation for displacement vector u. */ +HFX.BeamModel.prototype.computeElementResults = function (u, utilOut, NOut) { + const els = this.s.elements, p = this.p; + const ug = new Float64Array(6), ul = new Float64Array(6); + for (let i = 0; i < this.nEl; i++) { + const e = els[i], st = this.state[i]; + if (st === 2 || (st === 1 && p.residualStiffness <= 0)) { utilOut[i] = 0; NOut[i] = 0; this.M1[i] = 0; this.M2[i] = 0; this.V[i] = 0; this.epsMax[i] = 0; this.epsMin[i] = 0; continue; } + const c = this.cosE[i], s = this.sinE[i], L = this.LE[i]; + ug[0] = u[3 * e.n1]; ug[1] = u[3 * e.n1 + 1]; ug[2] = u[3 * e.n1 + 2]; ug[3] = u[3 * e.n2]; ug[4] = u[3 * e.n2 + 1]; ug[5] = u[3 * e.n2 + 2]; + ul[0] = c * ug[0] + s * ug[1]; ul[1] = -s * ug[0] + c * ug[1]; ul[2] = ug[2]; + ul[3] = c * ug[3] + s * ug[4]; ul[4] = -s * ug[3] + c * ug[4]; ul[5] = ug[5]; + const sf = st === 0 ? 1 : p.residualStiffness; + const E = e.Emod * sf, EA = E * e.A, EI = E * e.I; + const epsAx = (ul[3] - ul[0]) / L; + const N = EA * epsAx; + // end moments (Hermitian beam): M1 = EI*(6/L^2*(v2-v1)*(-1)... use stiffness rows + const k2 = 6 * EI / (L * L), k3 = 4 * EI / L, k4 = 2 * EI / L, k1 = 12 * EI / (L * L * L); + const M1 = k2 * ul[1] + k3 * ul[2] - k2 * ul[4] + k4 * ul[5]; + const M2 = k2 * ul[1] + k4 * ul[2] - k2 * ul[4] + k3 * ul[5]; + const V = k1 * ul[1] + k2 * ul[2] - k1 * ul[4] + k2 * ul[5]; + NOut[i] = N; this.M1[i] = M1; this.M2[i] = M2; this.V[i] = V; + const kappaMax = Math.max(Math.abs(M1), Math.abs(M2)) / EI; + const epsB = kappaMax * e.t * 0.5; + const eMax = epsAx + epsB, eMin = epsAx - epsB; + this.epsMax[i] = eMax; this.epsMin[i] = eMin; + const limit = st === 0 ? e.epsC : e.epsC * p.ductilityRatio; + let w = eMax / limit; + if (p.compressiveRatio > 0) { const wc = -eMin / (p.compressiveRatio * e.epsC); if (wc > w) w = wc; } + utilOut[i] = w; + } +}; +/** Internal force vector, reactions (top/bottom vertical sums) and equilibrium residual at free DOFs. */ +HFX.BeamModel.prototype.computeReactions = function (u) { + const els = this.s.elements, f = this.fint; f.fill(0); + const ue = new Float64Array(6); const dofs = new Int32Array(6); + for (let i = 0; i < this.nEl; i++) { + const sf = this.stiffnessFactor(i); if (sf <= 0) continue; + const e = els[i], K = this.Ke[i]; + dofs[0] = 3 * e.n1; dofs[1] = 3 * e.n1 + 1; dofs[2] = 3 * e.n1 + 2; dofs[3] = 3 * e.n2; dofs[4] = 3 * e.n2 + 1; dofs[5] = 3 * e.n2 + 2; + for (let a = 0; a < 6; a++) ue[a] = u[dofs[a]]; + for (let a = 0; a < 6; a++) { let v = 0; for (let b2 = 0; b2 < 6; b2++) v += K[a * 6 + b2] * ue[b2]; f[dofs[a]] += v * sf; } + } + const stab = this.p.stabilization * this.kRef; let stabForce = 0, stabV = 0; + const presc = this.prescEff, dofNew = this.dofNew; + let res2 = 0, react2 = 0; + for (let d = 0; d < this.ndof; d++) { + if (dofNew[d] >= 0) { const fs = (d % 3 === 2 ? stab * this.Lref * this.Lref : stab) * u[d]; f[d] += fs; stabForce += Math.abs(fs); if (d % 3 === 1) stabV += fs; res2 += f[d] * f[d]; } + else if (presc[d]) react2 += f[d] * f[d]; + } + let Ftop = 0, Fbot = 0; for (const d of this.topV) Ftop += f[d]; for (const d of this.bottomV) Fbot += f[d]; + // residual scale: reaction norm, floored at 0.1% of the force the intact structure carries at the same displacement + // (the floor only matters after complete separation, when the reactions reduce to the negligible stabilisation forces) + const dApplied = Math.abs(this.d || 0); + const scale = Math.max(Math.sqrt(react2), (this.Fref || 0) * dApplied * 1e-3, 1e-300); + const residual = Math.sqrt(res2) / scale; + this.residualAbs = Math.sqrt(res2); + // global vertical equilibrium: F_top + F_bottom = sum of vertical stabilisation forces at free DOFs (the only other external forces) + return { Ftop: Ftop, Fbot: Fbot, residual: residual, residualAbs: Math.sqrt(res2), stabForce: stabForce, stabV: stabV, forceBalance: Math.abs(Ftop + Fbot - stabV) / Math.max(Math.abs(Ftop), 1e-300), forceBalanceRaw: Math.abs(Ftop + Fbot) / Math.max(Math.abs(Ftop), 1e-300) }; +}; +/** Is there a load path (through non-failed elements) between the bottom and the top grip? */ +HFX.BeamModel.prototype.isConnected = function () { + const els = this.s.elements, n = this.nNodes; const adj = new Array(n); for (let i = 0; i < n; i++) adj[i] = []; + for (let i = 0; i < this.nEl; i++) { if (this.stiffnessFactor(i) <= 0) continue; const e = els[i]; adj[e.n1].push(e.n2); adj[e.n2].push(e.n1); } + const seen = new Uint8Array(n); const q = []; for (let i = 0; i < n; i++) if (this.s.nodes[i].onBottom) { seen[i] = 1; q.push(i); } + for (let h = 0; h < q.length; h++) { const v = q[h]; if (this.s.nodes[v].onTop) return true; for (const w of adj[v]) if (!seen[w]) { seen[w] = 1; q.push(w); } } + return false; +}; diff --git a/data/Run 1/RESULT Run 1/app/src/core/40_driver.js b/data/Run 1/RESULT Run 1/app/src/core/40_driver.js new file mode 100644 index 0000000000000000000000000000000000000000..fabdc720c599fb615d2d5a1af3a3103c88cdd744 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/40_driver.js @@ -0,0 +1,156 @@ +// ============================================================================ +// 40. Quasi-static, displacement-controlled fracture driver +// Loading: the top grip displacement d is increased in increments. For every +// topology state the response is linear, so the exact displacement at which the +// most utilised element reaches its limit is d_crit = 1 / max_e(omega_e(1)). +// With exactEvents the increment is cut back to d_crit (step-size independent); +// otherwise failures are processed at the end of the increment (overshoot). +// At an event the critical element(s) change state (intact -> damaged/failed), +// the system is re-assembled, re-factorised and re-solved at the SAME d; if the +// redistributed load overloads further elements they fail one at a time (most +// utilised first) until equilibrium with all omega_e < 1 (avalanche/cascade). +// ============================================================================ +function nowMs() { return (typeof performance !== 'undefined' && performance.now) ? performance.now() : Date.now(); } + +HFX.Simulation = function (structure, params) { + const p = this.p = Object.assign({}, structure.params, params || {}); + this.s = structure; + this.model = new HFX.BeamModel(structure, p); + const nEl = structure.elements.length; + this.nEl = nEl; + this.failDisp = new Float64Array(nEl).fill(-1); this.failOrder = new Int32Array(nEl).fill(-1); this.failStep = new Int32Array(nEl).fill(-1); + this.damageDisp = new Float64Array(nEl).fill(-1); + this.peakUtil = new Float64Array(nEl); + this.utilAtPeak = new Float64Array(nEl); this.NAtPeak = new Float64Array(nEl); this.utilInitial = new Float64Array(nEl); this.NInitial = new Float64Array(nEl); + this.steps = []; this.events = []; this.cascades = []; + this.d = 0; this.dGrid = 0; this.F = 0; this.Fpeak = 0; this.dPeak = 0; this.peakStep = 0; this.Wext = 0; this.dissipated = 0; + this.nFailed = 0; this.nDamaged = 0; this.nEvents = 0; this.done = false; this.status = 'ready'; + this.convergence = { residualExceeded: 0, iterationCapHits: 0, maxResidual: 0, nonPositivePivots: 0, maxForceBalance: 0, maxStabForceRatio: 0 }; + this.memberHistory = p.recordMemberHistory ? { disp: [], stepIndex: [], util: [] } : null; + this.stateRecords = p.recordStates ? [] : null; this.stateSkip = 1; this.stateCounter = 0; + this.firstFailureD = -1; this.separated = false; this.finalFailureD = -1; this.finalFailureStep = -1; this.Wf = -1; + this.startTime = nowMs(); this.elapsedMs = 0; this.initialized = false; this.K0 = 0; +}; +HFX.Simulation.prototype.init = function () { + const rb = this.model.rebuild(); this.checkRebuild(rb); + this.K0 = this.model.F1; this.K0residual = this.model.residual1; + this.utilInitial.set(this.model.util1); this.NInitial.set(this.model.N1); + this.model.solveAt(0); + this.recordStep(0, 0, '', 0, 0); + this.recordState(0); + this.initialized = true; + if (!this.model.isConnected()) { this.separated = true; this.finish('no-load-path'); } +}; +HFX.Simulation.prototype.checkRebuild = function (rb) { if (rb.nonPositivePivots) this.convergence.nonPositivePivots += rb.nonPositivePivots; }; +HFX.Simulation.prototype.checkSolve = function (react) { + const c = this.convergence; + if (react.residual > c.maxResidual) c.maxResidual = react.residual; + if (react.residualAbs > (c.maxResidualAbs || 0)) c.maxResidualAbs = react.residualAbs; + if (react.residual > this.p.tolerance) c.residualExceeded++; + if (react.forceBalance > c.maxForceBalance) c.maxForceBalance = react.forceBalance; + const sr = react.stabForce / Math.max(Math.abs(react.Ftop), this.Fpeak, 1e-300); if (sr > c.maxStabForceRatio) c.maxStabForceRatio = sr; + if (react.forceBalanceRaw > (c.maxForceBalanceRaw || 0)) c.maxForceBalanceRaw = react.forceBalanceRaw; +}; +HFX.Simulation.prototype.maxUtil = function () { const u = this.model.util, st = this.model.state; let w = 0, id = -1; for (let i = 0; i < this.nEl; i++) if (st[i] < 2 && u[i] > w) { w = u[i]; id = i; } return { w: w, id: id }; }; +HFX.Simulation.prototype.maxUtilUnit = function () { const u = this.model.util1, st = this.model.state; let w = 0; for (let i = 0; i < this.nEl; i++) if (st[i] < 2 && u[i] > w) w = u[i]; return w; }; +HFX.Simulation.prototype.criticalElements = function () { + const mu = this.maxUtil(); const tie = this.p.tieTolerance; + if (mu.w < 1 - Math.max(tie, 1e-12)) return []; + const u = this.model.util, st = this.model.state, out = []; + const thr = mu.w * (1 - tie); + for (let i = 0; i < this.nEl; i++) if (st[i] < 2 && u[i] >= thr) out.push(i); + return out; +}; +HFX.Simulation.prototype.recordStep = function (d, F, flag, cascade, iter) { + const m = this.model; + const prev = this.steps.length ? this.steps[this.steps.length - 1] : null; + if (prev) this.Wext += 0.5 * (prev.F + F) * (d - prev.d); + const mu = this.maxUtil(); + const st = { i: this.steps.length, d: d, F: F, U: 0.5 * F * d, W: this.Wext, Diss: this.dissipated, nFailed: this.nFailed, nDamaged: this.nDamaged, + maxUtil: mu.w, maxUtilId: mu.id, residual: m.residual, residualAbs: m.lastReact ? m.lastReact.residualAbs : 0, forceBalance: m.lastReact ? m.lastReact.forceBalance : 0, event: flag, cascade: cascade, iter: iter, + K: d > 0 ? F / d : this.K0, t: nowMs() - this.startTime }; + this.steps.push(st); + if (F > this.Fpeak) { this.Fpeak = F; this.dPeak = d; this.peakStep = st.i; this.utilAtPeak.set(m.util); this.NAtPeak.set(m.N); } + for (let i = 0; i < this.nEl; i++) if (m.util[i] > this.peakUtil[i]) this.peakUtil[i] = m.util[i]; + if (this.memberHistory && (flag !== '' || (st.i % Math.max(1, this.p.memberHistoryEvery)) === 0)) { this.memberHistory.disp.push(d); this.memberHistory.stepIndex.push(st.i); this.memberHistory.util.push(Float32Array.from(m.util)); } + return st; +}; +HFX.Simulation.prototype.recordState = function (dFrom) { + if (!this.stateRecords) return; + this.stateCounter++; + if (this.stateRecords.length >= this.p.maxStates) { // thin out: keep every second record (always keep the first) + const kept = this.stateRecords.filter(function (r, i) { return i === 0 || (i % 2 === 1); }); + this.stateRecords = kept; this.stateSkip *= 2; + } + if ((this.stateCounter - 1) % this.stateSkip !== 0 && this.stateRecords.length > 0) { this.stateRecords[this.stateRecords.length - 1].dTo = dFrom; return; } + const m = this.model; + if (this.stateRecords.length) this.stateRecords[this.stateRecords.length - 1].dTo = dFrom; + this.stateRecords.push({ index: this.cascades.length, dFrom: dFrom, dTo: Infinity, F1: m.F1, u1: Float32Array.from(m.u1), util1: Float32Array.from(m.util1), N1: Float32Array.from(m.N1), state: Int8Array.from(m.state), nFailed: this.nFailed }); +}; +HFX.Simulation.prototype.failElement = function (id, d, Fbefore) { + const m = this.model, e = this.s.elements[id], p = this.p, st = m.state[id]; + let type; + if (st === 0 && p.residualStiffness > 0 && p.ductilityRatio > 1) { m.state[id] = 1; this.nDamaged++; this.damageDisp[id] = d; type = 'damage'; } + else { m.state[id] = 2; if (st === 1) this.nDamaged--; this.failOrder[id] = this.nFailed; this.nFailed++; this.failDisp[id] = d; this.failStep[id] = this.steps.length - 1; type = 'rupture'; if (this.firstFailureD < 0) this.firstFailureD = d; } + this.events.push({ index: this.nEvents, d: d, elementId: id, level: e.level, kind: e.kind, isInterface: e.isInterface, type: type, util: m.util[id], N: m.N[id], F: m.F, Fcascade: Fbefore, x: e.cx, y: e.cy, step: this.steps.length - 1, cascade: this.cascades.length }); + this.nEvents++; +}; +/** One loading step (possibly containing a failure cascade). Returns false when finished. */ +HFX.Simulation.prototype.step = function () { + if (!this.initialized) this.init(); + if (this.done) return false; + const p = this.p, m = this.model; + const dTarget = Math.min(this.dGrid + p.dispIncrement, p.maxDisp); + let dNext = dTarget, eventNow = false; + if (p.exactEvents) { + const wmax1 = this.maxUtilUnit(); + if (wmax1 > 0) { const dCrit = 1 / wmax1; if (dCrit <= dTarget * (1 + 1e-12)) { dNext = Math.max(dCrit, this.d); eventNow = true; } } + } + let react = m.solveAt(dNext); this.checkSolve(react); + if (!p.exactEvents) eventNow = this.maxUtil().w >= 1; + this.recordStep(dNext, m.F, eventNow ? 'pre' : '', 0, 0); + if (eventNow) { + const Fbefore = m.F; let iter = 0, cascade = 0; + while (true) { + const crit = this.criticalElements(); + if (!crit.length) break; + if (iter >= p.maxIterations) { this.convergence.iterationCapHits++; break; } + for (const id of crit) this.failElement(id, dNext, Fbefore); + iter++; cascade += crit.length; + const rb = m.rebuild(); this.checkRebuild(rb); + react = m.solveAt(dNext); this.checkSolve(react); + if (this.nEvents >= p.maxEvents) break; + if (!m.isConnected()) { this.separated = true; break; } + } + const drop = Fbefore - m.F; this.dissipated += 0.5 * drop * dNext; + this.cascades.push({ index: this.cascades.length, d: dNext, Fbefore: Fbefore, Fafter: m.F, size: cascade, iterations: iter, drop: drop, dropFraction: drop / Math.max(this.Fpeak, 1e-300) }); + this.recordStep(dNext, m.F, 'post', cascade, iter); + this.recordState(dNext); + } + this.d = dNext; this.F = m.F; + if (dNext >= dTarget * (1 - 1e-12)) this.dGrid = dTarget; + if (this.separated) this.finish('completed'); + else if (this.nEvents > 0 && this.d > this.dPeak && this.F <= p.stopForceFraction * this.Fpeak) this.finish('completed'); + else if (this.d >= p.maxDisp * (1 - 1e-12)) this.finish('maxDisp'); + else if (this.nEvents >= p.maxEvents) this.finish('maxEvents'); + return !this.done; +}; +HFX.Simulation.prototype.advance = function (budgetMs) { + const t0 = nowMs(); + while (!this.done) { this.step(); if (budgetMs !== undefined && nowMs() - t0 > budgetMs) break; } + return !this.done; +}; +HFX.Simulation.prototype.run = function () { while (this.step()) { /* loop */ } return this; }; +HFX.Simulation.prototype.finish = function (status) { + this.done = true; this.status = status; this.elapsedMs = nowMs() - this.startTime; + const p = this.p, steps = this.steps; + // final failure: first step after the peak with F <= stopForceFraction * Fpeak (or separation) + this.finalFailureStep = -1; + for (let i = this.peakStep + 1; i < steps.length; i++) { if (steps[i].F <= p.stopForceFraction * this.Fpeak) { this.finalFailureStep = i; break; } } + if (this.finalFailureStep < 0 && this.separated) this.finalFailureStep = steps.length - 1; + if (this.finalFailureStep >= 0) { this.finalFailureD = steps[this.finalFailureStep].d; this.Wf = steps[this.finalFailureStep].W; } + else { this.finalFailureD = -1; this.Wf = this.Wext; } + const last = steps[steps.length - 1]; + this.energyBalanceError = Math.abs(this.Wext - (last.U + this.dissipated)) / Math.max(this.Wext, 1e-300); + this.converged = this.convergence.residualExceeded === 0 && this.convergence.iterationCapHits === 0 && this.convergence.nonPositivePivots === 0; +}; diff --git a/data/Run 1/RESULT Run 1/app/src/core/50_metrics.js b/data/Run 1/RESULT Run 1/app/src/core/50_metrics.js new file mode 100644 index 0000000000000000000000000000000000000000..ecfb1680608f60aab0aecfa62ec483e2b84ce76c --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/50_metrics.js @@ -0,0 +1,161 @@ +// ============================================================================ +// 50. Metrics, result bundles, CSV/JSON export helpers, hashing +// ============================================================================ +HFX.computeMetrics = function (sim) { + const s = sim.s, p = sim.p, W = s.W, H = s.H, els = s.elements, steps = sim.steps; + const rho = s.stats.relDensityActual; + const nActive = s.stats.activeElements; + const m = {}; + m.K0 = sim.K0; // initial stiffness F/d [E_s b_z] (normalised) + m.EeffRel = sim.K0 * H / (W * p.E); // effective modulus / solid modulus + m.EeffRelPerDensity = rho > 0 ? m.EeffRel / rho : NaN; + m.Fpeak = sim.Fpeak; m.dPeak = sim.dPeak; m.epsPeak = sim.dPeak / H; + m.sigmaPeakRel = sim.Fpeak / (W * p.E); // nominal peak stress / E_s + m.strengthRel = m.sigmaPeakRel / p.failStrain; // nominal peak stress / (E_s eps_c) = strength relative to solid strength + m.strengthRelPerDensity = rho > 0 ? m.strengthRel / rho : NaN; + m.dFirst = sim.firstFailureD; m.epsFirst = sim.firstFailureD >= 0 ? sim.firstFailureD / H : NaN; + m.dFinal = sim.finalFailureD; m.epsFinal = sim.finalFailureD >= 0 ? sim.finalFailureD / H : NaN; + m.finalFailureReached = sim.finalFailureStep >= 0; + m.Wf = sim.Wf; m.Wtotal = sim.Wext; + m.WfPerArea = sim.Wf / (W * H); // work to failure per specimen area [E_s b_z] (normalised toughness density) + m.WfPerMaterial = rho > 0 ? sim.Wf / (rho * W * H) : NaN; + m.WfRel = sim.Wf / (0.5 * p.E * p.failStrain * p.failStrain * rho * W * H); // relative to the elastic energy capacity of the same material volume loaded uniformly to eps_c + m.nFailed = sim.nFailed; m.nDamaged = sim.nDamaged; m.fractionFailed = nActive ? sim.nFailed / nActive : 0; + m.nEvents = sim.nEvents; m.nCascades = sim.cascades.length; + m.maxCascade = sim.cascades.reduce(function (a, c) { return Math.max(a, c.size); }, 0); + m.prePeakFailures = sim.events.filter(function (e) { return e.d < sim.dPeak * (1 - 1e-12); }).length; + m.prePeakFraction = sim.nEvents ? m.prePeakFailures / sim.nEvents : 0; + m.abruptness = sim.cascades.reduce(function (a, c) { return Math.max(a, c.drop); }, 0) / Math.max(sim.Fpeak, 1e-300); + // post-peak work fraction + const Wpeak = steps[sim.peakStep] ? steps[sim.peakStep].W : 0; + m.postPeakWorkFraction = sim.Wf > 0 ? Math.max(0, (sim.Wf - Wpeak) / sim.Wf) : 0; + // damage localisation: participation ratio of failed-element positions along the loading axis (y) + const failed = []; for (let i = 0; i < els.length; i++) if (sim.failDisp[i] >= 0) failed.push(i); + const leafScale = s.stats.leafScale; + const nBins = Math.max(4, Math.round(H / leafScale)); + if (failed.length) { + const hist = new Float64Array(nBins); let sy = 0, sy2 = 0; + for (const i of failed) { const y = els[i].cy; let bI = Math.floor(y / H * nBins); if (bI >= nBins) bI = nBins - 1; if (bI < 0) bI = 0; hist[bI]++; sy += y; sy2 += y * y; } + let s1 = 0, s2 = 0; for (let bI = 0; bI < nBins; bI++) { s1 += hist[bI]; s2 += hist[bI] * hist[bI]; } + m.participationRatio = (s1 * s1) / (nBins * s2); + m.localizationIndex = 1 - m.participationRatio; + const meanY = sy / failed.length; m.damageBandStd = Math.sqrt(Math.max(0, sy2 / failed.length - meanY * meanY)) / H; m.damageBandCentre = meanY / H; + m.localizationBins = nBins; + } else { m.participationRatio = NaN; m.localizationIndex = NaN; m.damageBandStd = NaN; m.damageBandCentre = NaN; m.localizationBins = nBins; } + // failure composition + const perLevel = []; for (let k = 0; k <= s.depth; k++) perLevel.push(0); + let ifFail = 0, braceFail = 0; + for (const i of failed) { perLevel[els[i].level]++; if (els[i].isInterface) ifFail++; if (els[i].kind === 'brace') braceFail++; } + m.failedPerLevel = perLevel; m.interfaceFailures = ifFail; m.braceFailures = braceFail; + m.interfaceFailureFraction = failed.length ? ifFail / failed.length : 0; + m.interfaceFailureShare = s.stats.interfaces ? ifFail / s.stats.interfaces : 0; + m.meanFailLevel = failed.length ? failed.reduce(function (a, i) { return a + els[i].level; }, 0) / failed.length : NaN; + // first-failure level and location + if (sim.events.length) { const e0 = sim.events[0]; m.firstFailLevel = e0.level; m.firstFailInterface = e0.isInterface; m.firstFailX = e0.x / W; m.firstFailY = e0.y / H; } + // classification of the fracture mode + let mode; + if (sim.nEvents === 0) mode = 'no-failure'; + else if (m.abruptness >= 0.6) mode = 'abrupt-brittle'; + else if (m.abruptness <= 0.25) mode = 'progressive'; + else mode = 'intermediate'; + let loc = failed.length >= 10 ? (m.localizationIndex >= 0.6 ? 'localized' : 'distributed') : 'few-failures'; + m.fractureMode = mode; m.damagePattern = loc; m.fractureLabel = mode + '/' + loc; + // numerical diagnostics + m.maxResidual = sim.convergence.maxResidual; m.maxResidualAbs = sim.convergence.maxResidualAbs || 0; m.residualExceeded = sim.convergence.residualExceeded; m.iterationCapHits = sim.convergence.iterationCapHits; + m.nonPositivePivots = sim.convergence.nonPositivePivots; m.maxForceBalance = sim.convergence.maxForceBalance; m.maxStabForceRatio = sim.convergence.maxStabForceRatio; + m.energyBalanceError = sim.energyBalanceError; m.converged = !!sim.converged; m.status = sim.status; + m.steps = steps.length; m.rebuilds = sim.model.rebuildCount; m.solves = sim.model.solveCount; m.elapsedMs = sim.elapsedMs; m.factorTimeMs = sim.model.factorTimeMs; + m.nFree = sim.model.nFree; m.maxBandwidth = sim.model.lastRebuild ? sim.model.lastRebuild.maxBandwidth : 0; + return m; +}; + +HFX.METRIC_DOC = { + K0: 'initial stiffness dF/dd of the undamaged structure [E_s b_z]', EeffRel: 'effective tensile modulus / solid modulus', Fpeak: 'peak reaction force [E_s W b_z]', + sigmaPeakRel: 'nominal peak stress F_peak/(W b_z) divided by E_s', strengthRel: 'nominal peak stress / (E_s eps_c)', dFirst: 'displacement at first failure event', + dPeak: 'displacement at peak force', dFinal: 'displacement at final failure (force < stopForceFraction * F_peak or separation)', Wf: 'work to final failure [E_s W^2 b_z]', + WfPerArea: 'work to failure per specimen area W*H', WfPerMaterial: 'work to failure per unit material area', WfRel: 'work to failure relative to 1/2 E eps_c^2 x material area', + abruptness: 'largest single-cascade force drop / F_peak (1 = fully abrupt)', localizationIndex: '1 - participation ratio of failed-element positions along y (1 = single band)', + prePeakFailures: 'number of failure events before the peak force', fractionFailed: 'failed elements / active elements', interfaceFailureFraction: 'share of failures that are interface elements', + energyBalanceError: '|W_ext - (U + dissipated)| / W_ext', maxResidual: 'max relative equilibrium residual over all solves' +}; + +// ---------------------------------------------------------------------------- export helpers +function fmt(v) { if (typeof v === 'number') { if (!isFinite(v)) return String(v); return Number(v.toPrecision(12)).toString(); } return String(v); } +HFX.fmt = fmt; +HFX.stepsCSV = function (sim) { + const rows = ['step,d,F,U,W,Diss,nFailed,nDamaged,maxUtil,maxUtilId,residual,residualAbs,forceBalance,event,cascade,iter,K,time_ms']; + for (const s of sim.steps) rows.push([s.i, fmt(s.d), fmt(s.F), fmt(s.U), fmt(s.W), fmt(s.Diss), s.nFailed, s.nDamaged, fmt(s.maxUtil), s.maxUtilId, fmt(s.residual), fmt(s.residualAbs), fmt(s.forceBalance), s.event, s.cascade, s.iter, fmt(s.K), fmt(s.t)].join(',')); + return rows.join('\n'); +}; +HFX.eventsCSV = function (sim) { + const rows = ['event,d,elementId,level,kind,isInterface,type,util,N,F_before_subevent,F_before_cascade,x,y,step,cascade']; + for (const e of sim.events) rows.push([e.index, fmt(e.d), e.elementId, e.level, e.kind, e.isInterface ? 1 : 0, e.type, fmt(e.util), fmt(e.N), fmt(e.F), fmt(e.Fcascade), fmt(e.x), fmt(e.y), e.step, e.cascade].join(',')); + return rows.join('\n'); +}; +HFX.membersCSV = function (sim) { + const s = sim.s, nodes = s.nodes; + const rows = ['id,n1,n2,x1,y1,x2,y2,level,kind,isInterface,L,t,epsC,xi,absent,state,damageDisp,failDisp,failOrder,peakUtil,utilInitial_perUnitDisp,NInitial_perUnitDisp,utilAtPeakLoad,NAtPeakLoad']; + for (let i = 0; i < s.elements.length; i++) { + const e = s.elements[i], A = nodes[e.n1], B = nodes[e.n2]; + rows.push([e.id, e.n1, e.n2, fmt(A.x), fmt(A.y), fmt(B.x), fmt(B.y), e.level, e.kind, e.isInterface ? 1 : 0, fmt(e.L), fmt(e.t), fmt(e.epsC), fmt(e.xi), e.absent ? 1 : 0, sim.model.state[i], + fmt(sim.damageDisp[i]), fmt(sim.failDisp[i]), sim.failOrder[i], fmt(sim.peakUtil[i]), fmt(sim.utilInitial[i]), fmt(sim.NInitial[i]), fmt(sim.utilAtPeak[i]), fmt(sim.NAtPeak[i])].join(',')); + } + return rows.join('\n'); +}; +HFX.memberHistoryCSV = function (sim) { + if (!sim.memberHistory) return ''; + const mh = sim.memberHistory; const rows = ['step,d,' + Array.from({ length: sim.nEl }, function (_, i) { return 'u' + i; }).join(',')]; + for (let r = 0; r < mh.disp.length; r++) { const u = mh.util[r]; const arr = new Array(u.length); for (let i = 0; i < u.length; i++) arr[i] = Number(u[i].toPrecision(6)); rows.push(mh.stepIndex[r] + ',' + fmt(mh.disp[r]) + ',' + arr.join(',')); } + return rows.join('\n'); +}; +HFX.geometryJSON = function (structure) { + return { + W: structure.W, H: structure.H, depth: structure.depth, branching: structure.branching, params: structure.params, stats: structure.stats, levelStats: structure.levelStats, + nodes: structure.nodes.map(function (n) { return [Number(n.x.toPrecision(12)), Number(n.y.toPrecision(12)), n.level === Infinity ? -1 : n.level, n.onBottom ? 1 : 0, n.onTop ? 1 : 0]; }), + elements: structure.elements.map(function (e) { return { id: e.id, n1: e.n1, n2: e.n2, level: e.level, kind: e.kind, iface: e.isInterface ? 1 : 0, L: Number(e.L.toPrecision(10)), t: Number(e.t.toPrecision(10)), epsC: Number(e.epsC.toPrecision(10)), absent: e.absent ? 1 : 0 }; }), + leafCells: structure.leafCells.map(function (c) { return c.map(function (q) { return [Number(q[0].toPrecision(10)), Number(q[1].toPrecision(10))]; }); }) + }; +}; +/** Full result bundle (JSON-serialisable). */ +HFX.resultsBundle = function (sim, extra) { + const metrics = HFX.computeMetrics(sim); + const s = sim.s; + const bundle = { + meta: Object.assign({ core: HFX.NAME, coreVersion: HFX.VERSION, created: new Date().toISOString(), units: 'normalised: length W=1, modulus E_s=1, depth b_z=1; force in E_s*W*b_z; energy in E_s*W^2*b_z' }, extra || {}), + params: sim.p, structureStats: s.stats, levelStats: s.levelStats, warnings: s.warnings, metrics: metrics, + steps: sim.steps, events: sim.events, cascades: sim.cascades, + members: s.elements.map(function (e, i) { return { id: e.id, level: e.level, kind: e.kind, iface: e.isInterface ? 1 : 0, L: e.L, t: e.t, epsC: e.epsC, absent: e.absent ? 1 : 0, state: sim.model.state[i], failDisp: sim.failDisp[i], failOrder: sim.failOrder[i], peakUtil: sim.peakUtil[i], utilAtPeak: sim.utilAtPeak[i] }; }), + diagnostics: { convergence: sim.convergence, energyBalanceError: sim.energyBalanceError, converged: sim.converged, status: sim.status, rebuilds: sim.model.rebuildCount, solves: sim.model.solveCount, lastRebuild: sim.model.lastRebuild, elapsedMs: sim.elapsedMs } + }; + return bundle; +}; +/** FNV-1a hash of the response (steps + events) for reproducibility checks. */ +HFX.hashResults = function (sim) { + let h = 0x811c9dc5; + const feed = function (str) { for (let i = 0; i < str.length; i++) { h ^= str.charCodeAt(i); h = Math.imul(h, 0x01000193) >>> 0; } }; + for (const s of sim.steps) feed(s.d.toPrecision(12) + ':' + s.F.toPrecision(12) + ';'); + for (const e of sim.events) feed(e.elementId + '@' + e.d.toPrecision(12) + ';'); + return ('00000000' + h.toString(16)).slice(-8); +}; +/** Convenience: generate + simulate + metrics. */ +HFX.runExperiment = function (params, opts) { + opts = opts || {}; + const t0 = nowMs(); + const structure = HFX.generateStructure(params); + const tGen = nowMs() - t0; + const sim = new HFX.Simulation(structure, params); + sim.run(); + const metrics = HFX.computeMetrics(sim); + return { structure: structure, sim: sim, metrics: metrics, hash: HFX.hashResults(sim), timing: { generateMs: tGen, simulateMs: sim.elapsedMs } }; +}; +/** Physical-unit conversion of the key metrics (display/export only). */ +HFX.toPhysical = function (metrics, phys, structure) { + const E = phys.E_MPa, Wmm = phys.W_mm, bmm = phys.depth_mm; // MPa, mm, mm + const Fscale = E * Wmm * bmm; // N (E [MPa=N/mm^2] * W [mm] * b [mm]) for normalised force in E_s W b_z + const dscale = Wmm; // mm per normalised length unit (W = 1) + return { + E_MPa: E, W_mm: Wmm, H_mm: structure.H * Wmm, depth_mm: bmm, t0_mm: structure.t0 * Wmm, tMin_mm: structure.stats.tMin * Wmm, + K0_N_per_mm: metrics.K0 * Fscale / dscale, Fpeak_N: metrics.Fpeak * Fscale, dPeak_mm: metrics.dPeak * dscale, dFirst_mm: metrics.dFirst * dscale, dFinal_mm: metrics.dFinal * dscale, + Wf_mJ: metrics.Wf * Fscale * dscale, sigmaPeak_MPa: metrics.sigmaPeakRel * E, Eeff_MPa: metrics.EeffRel * E + }; +}; diff --git a/data/Run 1/RESULT Run 1/app/src/core/60_validation.js b/data/Run 1/RESULT Run 1/app/src/core/60_validation.js new file mode 100644 index 0000000000000000000000000000000000000000..411a2c7bee0d76e5a64f568e3ca210f5675b0ec4 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/60_validation.js @@ -0,0 +1,184 @@ +// ============================================================================ +// 60. Validation suite (analytical references, invariances, conservation checks) +// ============================================================================ +/** Build a structure from explicit nodes [[x,y],...] and elements [[n1,n2,level,thickness],...] (unit material). */ +HFX.structureFromLines = function (nodesXY, elems, paramsIn) { + const p = Object.assign(HFX.defaultParams(), paramsIn || {}); + const W = p.W, H = p.H, tolBC = 1e-9; + const nodes = nodesXY.map(function (q) { return { x: q[0], y: q[1], level: 0, onBottom: Math.abs(q[1]) < tolBC, onTop: Math.abs(q[1] - H) < tolBC, onLeft: q[0] === 0, onRight: q[0] === W }; }); + const elements = elems.map(function (e, i) { + const A = nodes[e[0]], B = nodes[e[1]]; const t = e[3]; + return { id: i, n1: e[0], n2: e[1], level: e[2] || 0, kind: 'wall', isInterface: false, L: Math.hypot(B.x - A.x, B.y - A.y), cx: 0.5 * (A.x + B.x), cy: 0.5 * (A.y + B.y), absent: false, strengthFactor: 1, t: t, A: t, I: p.bendingFactor * t * t * t / 12, Emod: p.E, epsC: p.failStrain, xi: 1 }; + }); + let mat = 0; for (const e of elements) mat += e.L * e.t; + return { params: p, W: W, H: H, depth: 0, branching: 0, nodes: nodes, elements: elements, leafCells: [], cellsByLevel: [[]], t0: elements[0].t, levelStats: [{ level: 0, count: elements.length, thickness: elements[0].t }], warnings: [], + stats: { nodes: nodes.length, activeNodes: nodes.length, elements: elements.length, activeElements: elements.length, leafCells: 1, relDensityDesign: mat / (W * H), relDensityActual: mat / (W * H), t0: elements[0].t, tMin: elements[0].t, tMax: elements[0].t, meanCoordination: 2 * elements.length / nodes.length, interfaces: 0, leafScale: Math.sqrt(W * H), gripNodesTop: nodes.filter(function (n) { return n.onTop; }).length, gripNodesBottom: nodes.filter(function (n) { return n.onBottom; }).length } }; +}; +function relErr(obs, exp) { return Math.abs(obs - exp) / Math.max(Math.abs(exp), 1e-300); } +function mkResult(id, name, expected, observed, tol, details, absolute) { + const err = absolute ? Math.abs(observed - expected) : relErr(observed, expected); + return { id: id, name: name, expected: expected, observed: observed, error: err, tol: tol, pass: err <= tol, details: details || '', absolute: !!absolute }; +} +HFX.mkResult = mkResult; +/** Run the validation suite. Returns {results:[...], allPass, essentialPass, elapsedMs}. `log` optional callback. */ +HFX.runValidation = function (log, options) { + options = options || {}; + const t0 = nowMs(); const R = []; const say = function (s) { if (log) log(s); }; + const baseP = HFX.defaultParams(); + const study = Object.assign({}, baseP, { n0x: 1, n0y: 1, depth: 3, branching: 4, disorder: 0.35, seed: 7, thicknessRatio: 0.6, relDensity: 0.2, strengthCV: 0.08, interfaceStrengthRatio: 0.8, dispIncrement: 0.001, maxDisp: 0.1 }); + try { + // ---- T1 single axial member + { + const t = 0.05, L = 1.0; + const st = HFX.structureFromLines([[0.5, 0], [0.5, L]], [[0, 1, 0, t]], { H: L, E: 1, failStrain: 0.02, dispIncrement: 0.001, maxDisp: 0.01 }); + const sim = new HFX.Simulation(st, {}); sim.run(); + const Kexp = 1 * t / L; + R.push(mkResult('T1', 'Single axial member stiffness vs EA/L', Kexp, sim.K0, 1e-12, 'E=1, A=t=0.05, L=1 (clamped grips); F/d compared with EA/L; ' + sim.steps.length + ' steps, max residual ' + sim.convergence.maxResidual.toExponential(2))); + const s5 = sim.steps[5]; + R.push(mkResult('T1b', 'Single member: linear response F(d) = (EA/L) d at step 5', Kexp * s5.d, s5.F, 1e-12)); + } + // ---- T2 inclined clamped-clamped / clamped-pinned beam: axial + bending (exact Euler–Bernoulli) + { + const t = 0.05, W = 1, H = 1; const L = Math.SQRT2, sa = H / L, ca = W / L, EA = t, EI = t * t * t / 12; + const st = HFX.structureFromLines([[0, 0], [W, H]], [[0, 1, 0, t]], { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005, gripType: 'clamped' }); + const sim = new HFX.Simulation(st, {}); sim.run(); + const Kexp = EA / L * sa * sa + 12 * EI / (L * L * L) * ca * ca; + R.push(mkResult('T2', 'Inclined beam, clamped ends: K = EA/L sin^2 + 12EI/L^3 cos^2', Kexp, sim.K0, 1e-10, 'bending stiffness term verified (45 deg beam, tip rotation fixed)')); + // clamped base, tip free to rotate (guided cantilever): transverse stiffness 3EI/L^3 + const st2 = HFX.structureFromLines([[0, 0], [W, H]], [[0, 1, 0, t]], { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005 }); + st2.nodes[0].bc = { u: 1, v: 1, th: 1 }; st2.nodes[1].bc = { u: 1, v: 1, th: 0, vValue: 1 }; + const sim2 = new HFX.Simulation(st2, {}); sim2.run(); + const Kexp2 = EA / L * sa * sa + 3 * EI / (L * L * L) * ca * ca; + R.push(mkResult('T2b', 'Inclined beam, clamped base / tip rotation free: K = EA/L sin^2 + 3EI/L^3 cos^2', Kexp2, sim2.K0, 1e-10, 'guided-cantilever bending term 3EI/L^3 verified')); + // mesh refinement: 4 elements along the beam must give the identical answer (EB element exact for nodal loads) + const nn = [[0, 0], [0.25, 0.25], [0.5, 0.5], [0.75, 0.75], [1, 1]]; const ee = [[0, 1, 0, t], [1, 2, 0, t], [2, 3, 0, t], [3, 4, 0, t]]; + const st3 = HFX.structureFromLines(nn, ee, { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005 }); + st3.nodes[0].bc = { u: 1, v: 1, th: 1 }; st3.nodes[4].bc = { u: 1, v: 1, th: 0, vValue: 1 }; + const sim3 = new HFX.Simulation(st3, {}); sim3.run(); + R.push(mkResult('T2c', 'Inclined beam, 4-element mesh identical to 1 element', Kexp2, sim3.K0, 1e-9, 'Euler–Bernoulli element is exact for nodal loading')); + // pinned-pinned inclined bar: rigid rotation carries the transverse component, only the axial term remains + const st4 = HFX.structureFromLines([[0, 0], [W, H]], [[0, 1, 0, t]], { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005, gripType: 'pinned' }); + const sim4 = new HFX.Simulation(st4, {}); sim4.run(); + R.push(mkResult('T2d', 'Inclined bar, both ends pinned: K = EA/L sin^2 (no bending transmitted)', EA / L * sa * sa, sim4.K0, 1e-8, 'rotation-free ends: transverse motion is a rigid rotation, stabilisation-limited accuracy')); + } + // ---- T3 reproducibility + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(study); + R.push(mkResult('T3', 'Reproducibility: identical parameters and seed give identical results (hash)', 1, a.hash === b.hash ? 1 : 0, 0, 'hash ' + a.hash + ' vs ' + b.hash + '; Wf ' + a.metrics.Wf + ' vs ' + b.metrics.Wf + '; ' + a.metrics.nFailed + ' failures', true)); + R.push(mkResult('T3b', 'Reproducibility: work to failure bitwise equal', a.metrics.Wf, b.metrics.Wf, 0)); + const c = HFX.runExperiment(Object.assign({}, study, { seed: 8 })); + R.push(mkResult('T3c', 'Different seed changes the result (hash differs)', 1, a.hash !== c.hash ? 1 : 0, 0, 'seed 7 hash ' + a.hash + ', seed 8 hash ' + c.hash, true)); + } + // ---- T4 stiffness scaling + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { E: 2.0 })); + R.push(mkResult('T4', 'Doubling E doubles the initial stiffness', 2 * a.metrics.K0, b.metrics.K0, 1e-10)); + R.push(mkResult('T4b', 'Doubling E (fixed eps_c) leaves first-failure displacement unchanged', a.metrics.dFirst, b.metrics.dFirst, 1e-9, 'failure criterion is strain based: d_first independent of E')); + R.push(mkResult('T4c', 'Doubling E doubles the peak force', 2 * a.metrics.Fpeak, b.metrics.Fpeak, 1e-9)); + const seqA = a.sim.events.map(function (e) { return e.elementId; }).join(','), seqB = b.sim.events.map(function (e) { return e.elementId; }).join(','); + R.push(mkResult('T4d', 'Doubling E leaves the failure sequence unchanged', 1, seqA === seqB ? 1 : 0, 0, a.sim.events.length + ' events', true)); + } + // ---- T5 strength scaling + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { failStrain: 2 * study.failStrain })); + R.push(mkResult('T5', 'Doubling strength leaves the initial stiffness unchanged', a.metrics.K0, b.metrics.K0, 0, 'bitwise equal expected')); + R.push(mkResult('T5b', 'Doubling strength doubles the first-failure displacement', 2 * a.metrics.dFirst, b.metrics.dFirst, 1e-9)); + R.push(mkResult('T5c', 'Doubling strength doubles the peak force', 2 * a.metrics.Fpeak, b.metrics.Fpeak, 1e-9)); + R.push(mkResult('T5d', 'Doubling strength quadruples the work to failure', 4 * a.metrics.Wf, b.metrics.Wf, 1e-8, 'linear-elastic brittle model: energy scales with strength^2')); + const seqA = a.sim.events.map(function (e) { return e.elementId; }).join(','), seqB = b.sim.events.map(function (e) { return e.elementId; }).join(','); + R.push(mkResult('T5e', 'Doubling strength leaves the failure sequence unchanged', 1, seqA === seqB ? 1 : 0, 0, a.sim.events.length + ' events', true)); + } + // ---- T6 symmetry + { + const sp = Object.assign({}, baseP, { n0x: 1, n0y: 1, depth: 3, branching: 4, disorder: 0, strengthCV: 0, redundancy: 1, thicknessRatio: 0.6, relDensity: 0.2, dispIncrement: 0.002, maxDisp: 0.004, exactEvents: true, failStrain: 1 }); + const st = HFX.generateStructure(sp); const sim = new HFX.Simulation(st, {}); sim.run(); + const u = sim.model.u; const nodes = st.nodes; const W = st.W; + const idx = new Map(); nodes.forEach(function (n, i) { idx.set(n.x.toFixed(9) + ',' + n.y.toFixed(9), i); }); + let maxErr = 0, vmax = 0, paired = 0; + nodes.forEach(function (n, i) { + const j = idx.get((W - n.x).toFixed(9) + ',' + n.y.toFixed(9)); if (j === undefined) return; paired++; + const eu = Math.abs(u[3 * i] + u[3 * j]), ev = Math.abs(u[3 * i + 1] - u[3 * j + 1]), et = Math.abs(u[3 * i + 2] + u[3 * j + 2]); + maxErr = Math.max(maxErr, eu, ev, et); vmax = Math.max(vmax, Math.abs(u[3 * i + 1])); + }); + R.push(mkResult('T6', 'Mirror symmetry of the displacement field (ordered braced specimen)', 0, maxErr / Math.max(vmax, 1e-300), 1e-9, paired + ' of ' + nodes.length + ' nodes paired; |u(x)+u(W-x)|, |v(x)-v(W-x)|, |th(x)+th(W-x)| relative to max|v|', true)); + } + // ---- T7 force balance and residual over a full fracture run + { + const a = HFX.runExperiment(study); + R.push(mkResult('T7', 'Force balance |F_top + F_bottom - F_stab| / |F_top| over all steps', 0, a.sim.convergence.maxForceBalance, 1e-9, a.sim.steps.length + ' steps; raw |F_top+F_bottom|/|F_top| = ' + (a.sim.convergence.maxForceBalanceRaw || 0).toExponential(2) + ' (difference = stabilisation forces)', true)); + R.push(mkResult('T7b', 'Equilibrium residual ||K u - f||_free / ||reactions|| (max over all solves)', 0, a.sim.convergence.maxResidual, study.tolerance, 'tolerance = params.tolerance; ' + a.sim.model.solveCount + ' solves, ' + a.sim.model.rebuildCount + ' refactorisations', true)); + R.push(mkResult('T7c', 'Stabilisation force / peak reaction force (max over run)', 0, a.sim.convergence.maxStabForceRatio, 1e-6, 'ground-spring stabilisation must be negligible', true)); + R.push(mkResult('T8', 'Energy balance |W_ext - (U + dissipated)| / W_ext', 0, a.sim.energyBalanceError, 1e-9, 'external work vs stored + released energy', true)); + R.push(mkResult('T8b', 'Solver converged (no residual/iteration/pivot flags)', 1, a.sim.converged ? 1 : 0, 0, JSON.stringify(a.sim.convergence), true)); + } + // ---- T9 load-step sensitivity + { + const a = HFX.runExperiment(Object.assign({}, study, { dispIncrement: 0.002 })); + const b = HFX.runExperiment(Object.assign({}, study, { dispIncrement: 0.001 })); + const c = HFX.runExperiment(Object.assign({}, study, { dispIncrement: 0.0005 })); + R.push(mkResult('T9', 'Exact event tracking: peak force independent of step size (dd, dd/2, dd/4)', a.metrics.Fpeak, c.metrics.Fpeak, 1e-9, 'F_peak: ' + [a, b, c].map(function (r) { return r.metrics.Fpeak.toPrecision(10); }).join(', '))); + R.push(mkResult('T9b', 'Exact event tracking: work to failure independent of step size', a.metrics.Wf, c.metrics.Wf, 1e-9, 'W_f: ' + [a, b, c].map(function (r) { return r.metrics.Wf.toPrecision(10); }).join(', '))); + const na = HFX.runExperiment(Object.assign({}, study, { exactEvents: false, dispIncrement: 0.002 })); + const nb = HFX.runExperiment(Object.assign({}, study, { exactEvents: false, dispIncrement: 0.0005 })); + const ea = relErr(na.metrics.Fpeak, a.metrics.Fpeak), eb = relErr(nb.metrics.Fpeak, a.metrics.Fpeak); + R.push(mkResult('T9c', 'Without event tracking the peak-force error decreases with step size', 0, eb, Math.max(ea, 1e-12), 'error(dd=0.002) = ' + ea.toExponential(3) + ', error(dd=0.0005) = ' + eb.toExponential(3) + ' relative to the exact-event result', true)); + } + // ---- T10 export consistency + { + const a = HFX.runExperiment(study); const bundle = HFX.resultsBundle(a.sim); + const csv = HFX.stepsCSV(a.sim).split('\n').slice(1).map(function (l) { return l.split(','); }); + let Fmax = 0, Wfinal = 0; for (const r of csv) { const F = parseFloat(r[2]); if (F > Fmax) Fmax = F; } + const fi = a.sim.finalFailureStep >= 0 ? a.sim.finalFailureStep : csv.length - 1; Wfinal = parseFloat(csv[fi][4]); + R.push(mkResult('T10', 'Exported CSV peak force equals displayed metric', bundle.metrics.Fpeak, Fmax, 1e-11)); + R.push(mkResult('T10b', 'Exported CSV work at final failure equals displayed metric', bundle.metrics.Wf, Wfinal, 1e-11)); + const json = JSON.parse(JSON.stringify(bundle)); + R.push(mkResult('T10c', 'JSON bundle round-trip preserves metrics', bundle.metrics.Wf, json.metrics.Wf, 0)); + } + // ---- T11 density control + { + const cfgs = [{ disorder: 0, depth: 3 }, { disorder: 0.5, depth: 4, branching: 3, seed: 3 }, { disorder: 1, depth: 2, branching: 6, layout: 'radial', redundancy: 0.5 }]; + let maxErr = 0; const details = []; + for (const c of cfgs) { const st = HFX.generateStructure(Object.assign({}, baseP, { relDensity: 0.17 }, c)); const e = relErr(st.stats.relDensityDesign, 0.17); maxErr = Math.max(maxErr, e); details.push(st.stats.elements + ' elements, rho=' + st.stats.relDensityDesign.toPrecision(8)); } + R.push(mkResult('T11', 'Relative density is exactly controlled for ordered/disordered/radial designs', 0, maxErr, 1e-12, details.join('; '), true)); + } + // ---- T12 topology equivalence: nested ordered subdivision equals a flat grid + { + const pa = Object.assign({}, baseP, { n0x: 1, n0y: 1, depth: 3, branching: 4, disorder: 0, thicknessRatio: 1, interfaceMode: 'none', strengthCV: 0, relDensity: 0.2, dispIncrement: 0.002, maxDisp: 0.1 }); + const pb = Object.assign({}, pa, { n0x: 8, n0y: 8, depth: 0 }); + const a = HFX.runExperiment(pa), b = HFX.runExperiment(pb); + R.push(mkResult('T12', 'Nested subdivision (1x1, b=4, D=3) has the same node count as the flat 8x8 grid', a.structure.stats.nodes, b.structure.stats.nodes, 0, 'elements: ' + a.structure.stats.elements + ' vs ' + b.structure.stats.elements, true)); + R.push(mkResult('T12b', 'Nested vs flat grid: identical initial stiffness (uniform thickness)', b.metrics.K0, a.metrics.K0, 1e-10)); + R.push(mkResult('T12c', 'Nested vs flat grid: identical peak force', b.metrics.Fpeak, a.metrics.Fpeak, 1e-9)); + R.push(mkResult('T12d', 'Nested vs flat grid: identical work to failure', b.metrics.Wf, a.metrics.Wf, 1e-8)); + } + // ---- T13 analytical lattice stiffness, first failure and simultaneous rupture + { + const pl = Object.assign({}, baseP, { n0x: 4, n0y: 4, depth: 0, disorder: 0, strengthCV: 0, relDensity: 0.2, interfaceMode: 'none', dispIncrement: 0.002, maxDisp: 0.1, failStrain: 0.02 }); + const a = HFX.runExperiment(pl); const st = a.structure; + const t = st.t0; const nLines = 5; const Kexp = nLines * pl.E * t / st.H; + R.push(mkResult('T13', 'Ordered 4x4 grid, clamped grips: K0 = N_lines E t / H', Kexp, a.metrics.K0, 1e-10, 't0 = ' + t.toPrecision(8) + ' from rho=0.2 (total wall length 10)')); + R.push(mkResult('T13b', 'Ordered grid: first failure at d = eps_c H (uniform strain)', pl.failStrain * st.H, a.metrics.dFirst, 1e-9)); + R.push(mkResult('T13c', 'Ordered grid: peak force = K0 eps_c H', Kexp * pl.failStrain * st.H, a.metrics.Fpeak, 1e-9)); + R.push(mkResult('T13d', 'Ordered grid: all 20 vertical elements rupture in one tie-event (abrupt separation)', 20, a.sim.cascades.length ? a.sim.cascades[0].size : 0, 0, 'cascade sizes: ' + a.sim.cascades.map(function (c) { return c.size; }).join(','), true)); + R.push(mkResult('T13e', 'Ordered grid: work to failure = 1/2 K0 (eps_c H)^2', 0.5 * Kexp * Math.pow(pl.failStrain * st.H, 2), a.metrics.Wf, 1e-9)); + } + // ---- T14 stabilisation sensitivity + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { stabilization: 1e-10 })); + R.push(mkResult('T14', 'Stabilisation spring 100x larger changes K0 by < 1e-6', a.metrics.K0, b.metrics.K0, 1e-6)); + R.push(mkResult('T14b', 'Stabilisation spring 100x larger changes F_peak by < 1e-5', a.metrics.Fpeak, b.metrics.Fpeak, 1e-5)); + } + // ---- T15 interface strength only affects failure, not stiffness + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { interfaceStrengthRatio: 0.4 })); + R.push(mkResult('T15', 'Changing interface strength leaves the initial stiffness unchanged', a.metrics.K0, b.metrics.K0, 0)); + R.push(mkResult('T15b', 'Weaker interfaces fail earlier (first failure displacement decreases or is equal)', 1, b.metrics.dFirst <= a.metrics.dFirst + 1e-12 ? 1 : 0, 0, 'd_first ' + a.metrics.dFirst.toPrecision(6) + ' -> ' + b.metrics.dFirst.toPrecision(6) + '; interface failures ' + a.metrics.interfaceFailures + ' -> ' + b.metrics.interfaceFailures, true)); + } + } catch (err) { + R.push({ id: 'ERR', name: 'Validation suite threw an exception', expected: 'no exception', observed: String(err && err.stack || err), error: NaN, tol: 0, pass: false, details: '' }); + } + const essential = ['T1', 'T2', 'T2b', 'T3', 'T4', 'T5', 'T6', 'T7', 'T7b', 'T8', 'T9', 'T9b', 'T10', 'T11', 'T12b', 'T13', 'T13b']; + const allPass = R.every(function (r) { return r.pass; }); + const essentialPass = R.filter(function (r) { return essential.indexOf(r.id) >= 0; }).every(function (r) { return r.pass; }) && R.some(function (r) { return r.id === 'T1'; }); + return { results: R, allPass: allPass, essentialPass: essentialPass, elapsedMs: nowMs() - t0, coreVersion: HFX.VERSION }; +}; diff --git a/data/Run 1/RESULT Run 1/app/src/core/70_stl_svg.js b/data/Run 1/RESULT Run 1/app/src/core/70_stl_svg.js new file mode 100644 index 0000000000000000000000000000000000000000..518fa9459edc27d201a9ef579d7cdf213cf73d9e --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/70_stl_svg.js @@ -0,0 +1,148 @@ +// ============================================================================ +// 70. Geometry export (binary STL, extruded plate) and SVG rendering +// ============================================================================ +/** + * Binary STL of the undeformed design extruded to a plate. + * opts: { scale_mm (length of W in mm), depth_mm, minWidth_mm, widthFactor, gripTab_mm, includeAbsent, includeFailed, state (Int8Array), jointFill } + * Overlapping closed shells (one box per member, one prism per joint, tabs) — sliced as a union by common slicers. + */ +HFX.exportSTL = function (structure, opts) { + opts = Object.assign({ scale_mm: 100, depth_mm: 4, minWidth_mm: 0, widthFactor: 1, gripTab_mm: 0, includeAbsent: false, includeFailed: true, state: null, jointFill: true, jointSides: 8 }, opts || {}); + const S = opts.scale_mm, Z = opts.depth_mm; const tris = []; // each: [nx,ny,nz, x1,y1,z1, x2,y2,z2, x3,y3,z3] + const nodes = structure.nodes, els = structure.elements; + const widthOf = function (e) { return Math.max(e.t * S * opts.widthFactor, opts.minWidth_mm); }; + const addQuad = function (a, b, c, d, n) { tris.push([n, a, b, c]); tris.push([n, a, c, d]); }; + const addBox = function (x1, y1, x2, y2, w) { // rectangle around the segment (x1,y1)-(x2,y2), width w, extruded 0..Z + const dx = x2 - x1, dy = y2 - y1, L = Math.hypot(dx, dy); if (L <= 0) return; + const nx = -dy / L * w / 2, ny = dx / L * w / 2; + const P = [[x1 - nx, y1 - ny], [x2 - nx, y2 - ny], [x2 + nx, y2 + ny], [x1 + nx, y1 + ny]]; // counter-clockwise in the plane + const B = P.map(function (q) { return [q[0], q[1], 0]; }), T = P.map(function (q) { return [q[0], q[1], Z]; }); + addQuad(T[0], T[1], T[2], T[3], [0, 0, 1]); addQuad(B[3], B[2], B[1], B[0], [0, 0, -1]); + for (let i = 0; i < 4; i++) { const j = (i + 1) % 4; const ex = P[j][0] - P[i][0], ey = P[j][1] - P[i][1], el = Math.hypot(ex, ey) || 1; addQuad(B[i], B[j], T[j], T[i], [ey / el, -ex / el, 0]); } + }; + const addPrism = function (cx, cy, r, sides) { + const ring = []; for (let i = 0; i < sides; i++) { const a = 2 * Math.PI * (i + 0.5) / sides; ring.push([cx + r * Math.cos(a), cy + r * Math.sin(a)]); } + for (let i = 0; i < sides; i++) { const j = (i + 1) % sides; const a = ring[i], b = ring[j]; + tris.push([[0, 0, 1], [cx, cy, Z], [a[0], a[1], Z], [b[0], b[1], Z]]); tris.push([[0, 0, -1], [cx, cy, 0], [b[0], b[1], 0], [a[0], a[1], 0]]); + const ex = b[0] - a[0], ey = b[1] - a[1], el = Math.hypot(ex, ey) || 1; addQuad([a[0], a[1], 0], [b[0], b[1], 0], [b[0], b[1], Z], [a[0], a[1], Z], [ey / el, -ex / el, 0]); } + }; + const jointR = new Float64Array(nodes.length); let nMembers = 0, wMin = Infinity, wMax = 0, nThickened = 0; + for (let i = 0; i < els.length; i++) { + const e = els[i]; + if (e.absent && !opts.includeAbsent) continue; + if (opts.state && opts.state[i] === 2 && !opts.includeFailed) continue; + const A = nodes[e.n1], B = nodes[e.n2]; const w = widthOf(e); + if (w > e.t * S * opts.widthFactor + 1e-12) nThickened++; + wMin = Math.min(wMin, w); wMax = Math.max(wMax, w); nMembers++; + addBox(A.x * S, A.y * S, B.x * S, B.y * S, w); + jointR[e.n1] = Math.max(jointR[e.n1], w / 2); jointR[e.n2] = Math.max(jointR[e.n2], w / 2); + } + if (opts.jointFill) for (let i = 0; i < nodes.length; i++) if (jointR[i] > 0) addPrism(nodes[i].x * S, nodes[i].y * S, jointR[i] * 1.02, opts.jointSides); + if (opts.gripTab_mm > 0) { + const W = structure.W * S, H = structure.H * S, tab = opts.gripTab_mm; + addBox(W / 2, -tab, W / 2, 0, W); addBox(W / 2, H, W / 2, H + tab, W); + // overlap into the specimen by a small margin so the tabs fuse with the frame/members + const ov = Math.max(0.5, Math.min(2, 0.02 * H)); addBox(W / 2, -0.01, W / 2, ov, W); addBox(W / 2, H - ov, W / 2, H + 0.01, W); + } + const n = tris.length; const buf = new ArrayBuffer(84 + n * 50); const dv = new DataView(buf); + const header = 'HFX hierarchical fracture design; units mm; W=' + S + 'mm depth=' + Z + 'mm minW=' + opts.minWidth_mm + ' wf=' + opts.widthFactor; + for (let i = 0; i < 80; i++) dv.setUint8(i, i < header.length ? header.charCodeAt(i) : 32); + dv.setUint32(80, n, true); + let off = 84; + for (const t of tris) { for (let k = 0; k < 4; k++) for (let c = 0; c < 3; c++) { dv.setFloat32(off, t[k][c], true); off += 4; } dv.setUint16(off, 0, true); off += 2; } + return { buffer: buf, triangles: n, members: nMembers, minWidth_mm: wMin, maxWidth_mm: wMax, thickened: nThickened, bytes: buf.byteLength, header: header }; +}; + +// ---------------------------------------------------------------------------- colour maps +const VIRIDIS = [[68, 1, 84], [72, 40, 120], [62, 74, 137], [49, 104, 142], [38, 130, 142], [31, 158, 137], [53, 183, 121], [109, 205, 89], [180, 222, 44], [253, 231, 37]]; +const MAGMA = [[0, 0, 4], [28, 16, 68], [79, 18, 123], [129, 37, 129], [181, 54, 122], [229, 80, 100], [251, 135, 97], [254, 194, 135], [252, 253, 191]]; +function lerpMap(map, t) { t = Math.max(0, Math.min(1, t)); const x = t * (map.length - 1); const i = Math.min(map.length - 2, Math.floor(x)); const f = x - i; const a = map[i], b = map[i + 1]; return [a[0] + f * (b[0] - a[0]), a[1] + f * (b[1] - a[1]), a[2] + f * (b[2] - a[2])]; } +function rgbStr(c) { return 'rgb(' + Math.round(c[0]) + ',' + Math.round(c[1]) + ',' + Math.round(c[2]) + ')'; } +HFX.colormaps = { + viridis: function (t) { return lerpMap(VIRIDIS, t); }, + magma: function (t) { return lerpMap(MAGMA, t); }, + coolwarm: function (t) { t = Math.max(0, Math.min(1, t)); if (t < 0.5) { const f = t / 0.5; return [59 + f * (221 - 59), 76 + f * (221 - 76), 192 + f * (221 - 192)]; } const f = (t - 0.5) / 0.5; return [221 + f * (180 - 221), 221 + f * (4 - 221), 221 + f * (38 - 221)]; }, + level: function (k) { const P = [[214, 39, 40], [255, 127, 14], [188, 189, 34], [44, 160, 44], [23, 190, 207], [31, 119, 180], [148, 103, 189], [227, 119, 194], [140, 86, 75], [127, 127, 127], [23, 23, 23]]; return P[Math.max(0, Math.min(P.length - 1, k))]; }, + rgb: rgbStr +}; +/** Colour for one element given the colouring mode. Returns [r,g,b] */ +HFX.elementColor = function (mode, e, i, data) { + const cm = HFX.colormaps; const st = data.state ? data.state[i] : 0; + if (st === 2 && mode !== 'failOrder') return [190, 190, 190]; + switch (mode) { + case 'level': return cm.level(e.level); + case 'interface': return e.isInterface ? [214, 39, 40] : (e.kind === 'brace' ? [255, 127, 14] : [80, 80, 80]); + case 'util': { const u = data.util ? data.util[i] : 0; return cm.viridis(0.12 + 0.88 * Math.min(1, Math.max(0, u))); } + case 'state': return st === 1 ? [255, 160, 0] : ((data.util && data.util[i] >= 0.8) ? [220, 120, 0] : [40, 90, 200]); + case 'N': { const Nn = data.N ? data.N[i] / Math.max(data.Nmax || 1e-300, 1e-300) : 0; return cm.coolwarm(0.5 + 0.5 * Math.max(-1, Math.min(1, Nn))); } + case 'disp': { const d = data.disp ? data.disp[i] / Math.max(data.dispMax || 1e-300, 1e-300) : 0; return cm.magma(d); } + case 'failOrder': { if (!data.failOrder || data.failOrder[i] < 0) return [200, 200, 200]; return cm.viridis(data.failOrder[i] / Math.max(1, data.nFailed - 1)); } + case 'thickness': return cm.magma(Math.log(e.t / data.tMin) / Math.max(1e-9, Math.log(data.tMax / data.tMin))); + default: return [60, 60, 60]; + } +}; +/** + * Render the structure as SVG. opts: {width, height, u (Float64Array or null), scale (deformation magnification), colorBy, state, util, N, failOrder, nFailed, + * showFailed ('hide'|'ghost'|'show'), title, lineScale, background, padding, showCells} + */ +HFX.renderSVG = function (structure, opts) { + opts = Object.assign({ width: 800, height: 800, u: null, scale: 1, colorBy: 'level', showFailed: 'ghost', title: '', lineScale: 1, background: '#ffffff', padding: 30, showCells: false, minLine: 0.5 }, opts || {}); + const W = structure.W, H = structure.H, nodes = structure.nodes, els = structure.elements; + const pad = opts.padding; const sx = (opts.width - 2 * pad) / W, sy = (opts.height - 2 * pad) / H; const sc = Math.min(sx, sy); + const ox = pad + (opts.width - 2 * pad - W * sc) / 2, oy = pad + (opts.height - 2 * pad - H * sc) / 2; + const X = function (x) { return ox + x * sc; }, Y = function (y) { return opts.height - (oy + y * sc); }; + const u = opts.u, mag = opts.scale; + const px = function (i) { return nodes[i].x + (u ? mag * u[3 * i] : 0); }, py = function (i) { return nodes[i].y + (u ? mag * u[3 * i + 1] : 0); }; + let Nmax = 0, dispMax = 0; const disp = new Float64Array(els.length); + if (opts.N) for (let i = 0; i < els.length; i++) Nmax = Math.max(Nmax, Math.abs(opts.N[i])); + if (u) for (let i = 0; i < els.length; i++) { const e = els[i]; const d = 0.5 * (Math.hypot(u[3 * e.n1], u[3 * e.n1 + 1]) + Math.hypot(u[3 * e.n2], u[3 * e.n2 + 1])); disp[i] = d; dispMax = Math.max(dispMax, d); } + const data = { state: opts.state, util: opts.util, N: opts.N, Nmax: Nmax, disp: disp, dispMax: dispMax, failOrder: opts.failOrder, nFailed: opts.nFailed || 0, tMin: structure.stats.tMin, tMax: structure.stats.tMax }; + const parts = ['']; + parts.push(''); + if (opts.showCells && structure.leafCells) { for (const c of structure.leafCells) parts.push(''); } + // draw thick (coarse) members first so fine members are visible on top + const order = els.map(function (e, i) { return i; }).sort(function (a, b) { return els[a].level - els[b].level; }); + for (const i of order) { + const e = els[i]; const st = opts.state ? opts.state[i] : 0; + if (e.absent) continue; + if (st === 2 && opts.showFailed === 'hide') continue; + const wpx = Math.max(opts.minLine, e.t * sc * opts.lineScale); + const col = rgbStr(HFX.elementColor(opts.colorBy, e, i, data)); + const x1 = X(px(e.n1)), y1 = Y(py(e.n1)), x2 = X(px(e.n2)), y2 = Y(py(e.n2)); + if (st === 2 && opts.showFailed === 'ghost') parts.push(''); + else parts.push(''); + } + if (opts.title) parts.push('' + opts.title.replace(/&/g, '&').replace(/'); + parts.push(''); + return parts.join('\n'); +}; +/** Simple SVG line plot. series: [{x:[],y:[],label,color,width,dash}], opts: {width,height,xlabel,ylabel,title,xmin,xmax,ymin,ymax,marker:{x,y}} */ +HFX.plotSVG = function (series, opts) { + opts = Object.assign({ width: 640, height: 420, xlabel: 'x', ylabel: 'y', title: '', legend: true, fontSize: 12 }, opts || {}); + const ml = 64, mr = 16, mt = opts.title ? 30 : 14, mb = 46; const pw = opts.width - ml - mr, ph = opts.height - mt - mb; + let xmin = Infinity, xmax = -Infinity, ymin = Infinity, ymax = -Infinity; + for (const s of series) for (let i = 0; i < s.x.length; i++) { const x = s.x[i], y = s.y[i]; if (!isFinite(x) || !isFinite(y)) continue; xmin = Math.min(xmin, x); xmax = Math.max(xmax, x); ymin = Math.min(ymin, y); ymax = Math.max(ymax, y); } + if (!isFinite(xmin)) { xmin = 0; xmax = 1; ymin = 0; ymax = 1; } + if (opts.xmin !== undefined) xmin = opts.xmin; if (opts.xmax !== undefined) xmax = opts.xmax; if (opts.ymin !== undefined) ymin = opts.ymin; if (opts.ymax !== undefined) ymax = opts.ymax; + if (xmax - xmin <= 0) xmax = xmin + 1; if (ymax - ymin <= 0) ymax = ymin + 1; + ymax += 0.05 * (ymax - ymin); + const X = function (x) { return ml + (x - xmin) / (xmax - xmin) * pw; }, Y = function (y) { return mt + ph - (y - ymin) / (ymax - ymin) * ph; }; + const niceTicks = function (a, b, n) { const span = b - a; const raw = span / n; const mag = Math.pow(10, Math.floor(Math.log10(raw))); const norm = raw / mag; const step = (norm < 1.5 ? 1 : norm < 3.5 ? 2 : norm < 7.5 ? 5 : 10) * mag; const t = []; for (let v = Math.ceil(a / step) * step; v <= b + 1e-12 * span; v += step) t.push(Number(v.toPrecision(10))); return t; }; + const fmtT = function (v) { return Math.abs(v) < 1e-3 && v !== 0 ? v.toExponential(1) : (Number.isInteger(v) ? String(v) : v.toPrecision(3).replace(/\.?0+$/, '')); }; + const P = ['', '']; + for (const t of niceTicks(xmin, xmax, 6)) { P.push(''); P.push(''); P.push('' + fmtT(t) + ''); } + for (const t of niceTicks(ymin, ymax, 6)) { P.push(''); P.push(''); P.push('' + fmtT(t) + ''); } + P.push(''); + series.forEach(function (s, k) { + const col = s.color || ['#1f77b4', '#d62728', '#2ca02c', '#ff7f0e', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f'][k % 8]; + let d = ''; for (let i = 0; i < s.x.length; i++) { if (!isFinite(s.x[i]) || !isFinite(s.y[i])) continue; d += (d ? 'L' : 'M') + X(s.x[i]).toFixed(2) + ' ' + Y(s.y[i]).toFixed(2); } + P.push(''); + if (opts.legend && s.label) { P.push(''); P.push('' + s.label + ''); } + }); + if (opts.marker) P.push(''); + P.push('' + opts.xlabel + ''); + P.push('' + opts.ylabel + ''); + if (opts.title) P.push('' + opts.title + ''); + P.push(''); + return P.join('\n'); +}; diff --git a/data/Run 1/RESULT Run 1/app/src/core/99_footer.js b/data/Run 1/RESULT Run 1/app/src/core/99_footer.js new file mode 100644 index 0000000000000000000000000000000000000000..bb26db4da47ab04e4b4e8760cec10ef8192b43c8 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/core/99_footer.js @@ -0,0 +1,4 @@ +// ============================================================================ +HFX.nowMs = nowMs; +return HFX; +}); diff --git a/data/Run 1/RESULT Run 1/app/src/hfx_core.js b/data/Run 1/RESULT Run 1/app/src/hfx_core.js new file mode 100644 index 0000000000000000000000000000000000000000..c3301ccd50e62fcef8e5b3ef07c5ebc14695c8dc --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/hfx_core.js @@ -0,0 +1,1526 @@ +/* + * HFX — Hierarchical Fracture eXplorer: simulator core + * --------------------------------------------------------------------------- + * Shared by the single-file browser application and the Node.js study driver. + * Contents: + * 10 RNG + convex-polygon geometry utilities + * 20 Hierarchical cellular-network generator (recursive clipped Voronoi) + * 30 2-D Euler–Bernoulli beam-network assembly + envelope LDL^T solver + * 40 Quasi-static displacement-controlled fracture driver (event tracking) + * 50 Metrics, CSV/JSON export helpers + * 60 Validation test suite + * 70 Binary STL export (extruded plate, thickening variants), SVG rendering + * All quantities are NORMALISED unless explicitly converted: length unit = specimen + * width W (=1), stiffness unit = solid modulus E_s (=1), out-of-plane depth b_z = 1. + * Force unit = E_s * W * b_z ; energy unit = E_s * W^2 * b_z. + * --------------------------------------------------------------------------- + */ +(function (root, factory) { + if (typeof module === 'object' && module.exports) { module.exports = factory(); } + else { root.HFX = factory(); } +})(typeof self !== 'undefined' ? self : this, function () { +'use strict'; +const HFX = { VERSION: '1.0.0', NAME: 'HFX Hierarchical Fracture eXplorer core', BUILD: '2026-09-01T22:57:58.482Z' }; + +// ============================================================================ +// 10. Seeded RNG and convex-polygon geometry utilities +// ============================================================================ +function xmur3(str) { + let h = 1779033703 ^ str.length; + for (let i = 0; i < str.length; i++) { + h = Math.imul(h ^ str.charCodeAt(i), 3432918353); + h = (h << 13) | (h >>> 19); + } + return function () { + h = Math.imul(h ^ (h >>> 16), 2246822507); + h = Math.imul(h ^ (h >>> 13), 3266489909); + h ^= h >>> 16; + return h >>> 0; + }; +} +function mulberry32(a) { + return function () { + a |= 0; a = (a + 0x6D2B79F5) | 0; + let t = Math.imul(a ^ (a >>> 15), 1 | a); + t = (t + Math.imul(t ^ (t >>> 7), 61 | t)) ^ t; + return ((t ^ (t >>> 14)) >>> 0) / 4294967296; + }; +} +/** Deterministic RNG. seed: number or string; stream: string label (independent sub-streams). */ +HFX.makeRNG = function (seed, stream) { + const h = xmur3(String(seed) + '|' + (stream || 'main')); + const next = mulberry32(h()); + const rng = { + next: next, + uniform: function (a, b) { return a + (b - a) * next(); }, + int: function (n) { return Math.floor(next() * n); }, + normal: function () { // Box–Muller + let u = 0, v = 0; while (u === 0) u = next(); while (v === 0) v = next(); + return Math.sqrt(-2.0 * Math.log(u)) * Math.cos(2.0 * Math.PI * v); + }, + lognormalMean1: function (cv) { // lognormal with mean 1 and coefficient of variation cv + if (!(cv > 0)) return 1; + const s2 = Math.log(1 + cv * cv); + return Math.exp(-0.5 * s2 + Math.sqrt(s2) * rng.normal()); + } + }; + return rng; +}; + +// ---- polygon utilities. A polygon is {pts:[[x,y],...] (CCW), tags:[edge tag per edge i: pts[i]->pts[i+1]]} +const G = {}; +G.area = function (pts) { let a = 0; for (let i = 0, n = pts.length; i < n; i++) { const p = pts[i], q = pts[(i + 1) % n]; a += p[0] * q[1] - q[0] * p[1]; } return 0.5 * a; }; +G.centroid = function (pts) { + let cx = 0, cy = 0, a = 0; + for (let i = 0, n = pts.length; i < n; i++) { const p = pts[i], q = pts[(i + 1) % n]; const w = p[0] * q[1] - q[0] * p[1]; a += w; cx += (p[0] + q[0]) * w; cy += (p[1] + q[1]) * w; } + if (Math.abs(a) < 1e-300) { cx = 0; cy = 0; for (const p of pts) { cx += p[0]; cy += p[1]; } return [cx / pts.length, cy / pts.length]; } + return [cx / (3 * a), cy / (3 * a)]; +}; +G.aabb = function (pts) { let xmin = Infinity, ymin = Infinity, xmax = -Infinity, ymax = -Infinity; for (const p of pts) { if (p[0] < xmin) xmin = p[0]; if (p[0] > xmax) xmax = p[0]; if (p[1] < ymin) ymin = p[1]; if (p[1] > ymax) ymax = p[1]; } return { xmin, ymin, xmax, ymax }; }; +/** Clip convex polygon by half-plane a*x+b*y+c <= 0. New edge on the clip line receives `tag`. */ +G.clipHalfPlane = function (poly, a, b, c, tag) { + const pts = poly.pts, tags = poly.tags, n = pts.length, outP = [], outT = []; + for (let i = 0; i < n; i++) { + const P = pts[i], Q = pts[(i + 1) % n]; + const dP = a * P[0] + b * P[1] + c, dQ = a * Q[0] + b * Q[1] + c; + const inP = dP <= 0, inQ = dQ <= 0; + if (inP) { + outP.push(P); outT.push(tags[i]); + if (!inQ) { const t = dP / (dP - dQ); outP.push([P[0] + t * (Q[0] - P[0]), P[1] + t * (Q[1] - P[1])]); outT.push(tag); } + } else if (inQ) { + const t = dP / (dP - dQ); outP.push([P[0] + t * (Q[0] - P[0]), P[1] + t * (Q[1] - P[1])]); outT.push(tags[i]); + } + } + return { pts: outP, tags: outT }; +}; +/** Remove near-duplicate vertices and collinear vertices whose adjacent edges carry the same tag. */ +G.cleanPolygon = function (poly, eps) { + let pts = poly.pts.slice(), tags = poly.tags.slice(); + // pass 1: duplicates + let P = [], T = []; + for (let i = 0; i < pts.length; i++) { + const p = pts[i]; + if (P.length && Math.hypot(p[0] - P[P.length - 1][0], p[1] - P[P.length - 1][1]) < eps) { T[T.length - 1] = tags[i]; continue; } + P.push(p); T.push(tags[i]); + } + if (P.length > 1 && Math.hypot(P[0][0] - P[P.length - 1][0], P[0][1] - P[P.length - 1][1]) < eps) { P.pop(); T.pop(); } + // pass 2: collinear with same tag on both edges + let changed = true; + while (changed && P.length > 3) { + changed = false; + for (let i = 0; i < P.length; i++) { + const im = (i + P.length - 1) % P.length, ip = (i + 1) % P.length; + const ax = P[i][0] - P[im][0], ay = P[i][1] - P[im][1], bx = P[ip][0] - P[i][0], by = P[ip][1] - P[i][1]; + const cross = ax * by - ay * bx, dot = ax * bx + ay * by; + const la = Math.hypot(ax, ay), lb = Math.hypot(bx, by); + if (Math.abs(cross) < eps * (la + lb) && dot > 0 && T[im] === T[i]) { P.splice(i, 1); T.splice(i, 1); changed = true; break; } + } + } + return { pts: P, tags: T }; +}; +G.pointInConvex = function (pts, x, y, margin) { + const n = pts.length; + for (let i = 0; i < n; i++) { const p = pts[i], q = pts[(i + 1) % n]; const cr = (q[0] - p[0]) * (y - p[1]) - (q[1] - p[1]) * (x - p[0]); if (cr < (margin || 0)) return false; } + return true; +}; +/** Move point p toward the centroid until it is strictly inside (convex polygon). */ +G.pushInside = function (p, pts, cen, frac) { + if (G.pointInConvex(pts, p[0], p[1], 1e-12)) return p; + const dx = p[0] - cen[0], dy = p[1] - cen[1]; + let tHit = 1; + for (let i = 0, n = pts.length; i < n; i++) { + const a = pts[i], b = pts[(i + 1) % n]; + const ex = b[0] - a[0], ey = b[1] - a[1]; + const den = dx * ey - dy * ex; if (Math.abs(den) < 1e-300) continue; + const t = ((a[0] - cen[0]) * ey - (a[1] - cen[1]) * ex) / den; + const s = ((a[0] - cen[0]) * dy - (a[1] - cen[1]) * dx) / den; + if (t > 0 && s >= -1e-12 && s <= 1 + 1e-12 && t < tHit) tHit = t; + } + const f = (frac === undefined ? 0.8 : frac) * tHit; + return [cen[0] + f * dx, cen[1] + f * dy]; +}; +G.polygonInradiusEstimate = function (pts) { // min distance from centroid to edges + const c = G.centroid(pts); let r = Infinity; + for (let i = 0, n = pts.length; i < n; i++) { const a = pts[i], b = pts[(i + 1) % n]; const ex = b[0] - a[0], ey = b[1] - a[1]; const L = Math.hypot(ex, ey); if (L < 1e-300) continue; const d = Math.abs(ex * (c[1] - a[1]) - ey * (c[0] - a[0])) / L; if (d < r) r = d; } + return r; +}; +HFX.geom = G; + +// ============================================================================ +// 20. Hierarchical cellular-network generator +// Concept: a rectangular specimen W x H is tessellated by a level-0 grid of +// n0x x n0y cells (plus an optional frame). Every cell of level k is recursively +// subdivided into `branching` sub-cells by a clipped Voronoi tessellation of +// seeds placed on an ordered layout (grid / staggered / radial) and jittered by +// `disorder`. Walls created at level k carry thickness t_k = t_0 * thicknessRatio^k. +// Where a level-(k+1) wall meets a coarser wall an INTERFACE element is created. +// Leaf cells may receive diagonal braces (redundancy). Total material is fixed by +// the relative density. Defects (notch / weak zone / missing members) are applied +// after the density calibration. +// ============================================================================ +HFX.defaultParams = function () { + return { + // --- specimen & topology + W: 1.0, H: 1.0, n0x: 1, n0y: 1, depth: 3, branching: 4, layout: 'grid', + disorder: 0.0, disorderMinLevel: 0, seed: 1, includeFrame: true, frameMode: 'sides', + thicknessRatio: 0.6, densityMode: 'relative', relDensity: 0.2, slenderness0: 20, + redundancy: 0.0, connectivity: 1.0, + interfaceMode: 'segment', interfaceFraction: 0.15, + mergeFraction: 0.05, minSeedSeparation: 0.25, + defectType: 'none', defectX: 0.5, defectY: 0.5, defectSize: 0.05, defectWeakFactor: 0.5, missingFraction: 0.0, + // --- material (normalised: E_s = 1) + E: 1.0, failStrain: 0.02, strengthCV: 0.0, strengthLevelRatio: 1.0, + interfaceStrengthRatio: 1.0, interfaceStiffnessRatio: 1.0, + bendingFactor: 1.0, residualStiffness: 0.0, ductilityRatio: 1.0, compressiveRatio: 0.0, + // --- loading & numerics + gripType: 'clamped', dispIncrement: 0.0005, maxDisp: 0.08, exactEvents: true, + maxIterations: 2000, tolerance: 1e-8, stabilization: 1e-12, tieTolerance: 1e-9, + stopForceFraction: 0.01, maxEvents: 20000, maxElements: 40000, + recordMemberHistory: false, memberHistoryEvery: 1, recordStates: false, maxStates: 600, + // --- physical unit scaling (display / export only) + phys: { E_MPa: 2000, W_mm: 100, depth_mm: 4 } + }; +}; +HFX.PARAM_DOC = { + W: 'specimen width (length unit)', H: 'specimen height', n0x: 'level-0 cells along x', n0y: 'level-0 cells along y', + depth: 'hierarchy depth D (number of nested subdivision levels below level 0)', branching: 'branching ratio b (sub-cells per cell per level)', + layout: 'ordered seed layout language: grid | staggered | radial', disorder: 'geometric disorder 0 (ordered) .. 1 (organic Voronoi)', disorderMinLevel: 'disorder is applied only to levels >= this value (coarser levels stay ordered, e.g. straight midrib + organic areoles)', + seed: 'random seed (geometry, strength, braces, defects use independent sub-streams)', includeFrame: 'include boundary frame walls (level 0)', frameMode: 'full: all four boundary walls | sides: only the two side walls (top/bottom boundaries are the grips) | none', + thicknessRatio: 'inter-level thickness ratio r_t: t_k = t_0 r_t^k (1 = no thickness hierarchy)', + densityMode: 'relative: fix relative density; slenderness: fix level-0 slenderness', relDensity: 'relative density = member area / (W H)', + slenderness0: 'level-0 slenderness L_0/t_0 (used in slenderness mode)', redundancy: 'fraction of possible leaf-cell fan diagonals (braces) added', + connectivity: 'fraction of finest-level walls retained (1 = closed cells)', interfaceMode: 'segment: explicit short interface element | element: whole first element | none', + interfaceFraction: 'interface element length as fraction of the child wall segment length', mergeFraction: 'merge nodes closer than this fraction of the leaf cell size', + minSeedSeparation: 'minimum seed spacing as fraction of sqrt(cell area / b)', defectType: 'none | notch (members removed) | weak (strength reduced)', + defectX: 'defect centre x / W', defectY: 'defect centre y / H', defectSize: 'defect radius / W', defectWeakFactor: 'strength multiplier inside a weak zone', + missingFraction: 'fraction of members removed at random (diffuse defects)', + E: 'solid modulus (normalised, 1)', failStrain: 'failure strain eps_c = sigma_c / E of a level-0 member', + strengthCV: 'coefficient of variation of member strength (lognormal, mean 1)', strengthLevelRatio: 'strength multiplier per level: eps_c,k = eps_c s_l^k', + interfaceStrengthRatio: 'interface strength / member strength (inter-level strength)', interfaceStiffnessRatio: 'interface modulus / member modulus', + bendingFactor: 'multiplier on second moment of area I (bending-to-axial stiffness ratio control)', + residualStiffness: 'residual stiffness fraction after damage (0 = brittle removal)', ductilityRatio: 'final strain / eps_c for the damaged stage', + compressiveRatio: 'compressive failure strain / eps_c (0 = no compressive failure)', + gripType: 'clamped (u=v=theta prescribed) | pinned (u,v) | roller-top (v only at top)', dispIncrement: 'displacement increment', maxDisp: 'maximum applied displacement', + exactEvents: 'locate the exact displacement of each failure event (step-size independent)', maxIterations: 'maximum failure iterations per step', + tolerance: 'relative equilibrium residual tolerance', stabilization: 'ground-spring stabilisation relative to reference axial stiffness', + tieTolerance: 'elements within this relative utilisation of the maximum fail simultaneously', stopForceFraction: 'stop when force drops below this fraction of the peak', + maxEvents: 'maximum number of failure events', maxElements: 'element cap' +}; + +function factorPair(b, aspect) { + let best = null, bestScore = Infinity; + for (let n = 1; n <= b; n++) { + if (b % n) continue; + const m = b / n; + const score = Math.abs(Math.log(m / n) - Math.log(Math.max(aspect, 1))) + (m < n ? 1e-6 : 0); + if (score < bestScore) { bestScore = score; best = [m, n]; } + } + return best; +} + +function makeSeeds(poly, count, layout, disorder, rng, explicitMN, minSep) { + const pts = poly.pts, bb = HFX.geom.aabb(pts), cen = HFX.geom.centroid(pts); + const dx = Math.max(bb.xmax - bb.xmin, 1e-12), dy = Math.max(bb.ymax - bb.ymin, 1e-12); + const longX = dx >= dy, aspect = longX ? dx / dy : dy / dx; + let m, n; + if (explicitMN) { m = explicitMN[0]; n = explicitMN[1]; } + else { const mn = factorPair(count, aspect); m = longX ? mn[0] : mn[1]; n = longX ? mn[1] : mn[0]; } + const seeds = []; + const area = Math.abs(HFX.geom.area(pts)); + const cellScale = Math.sqrt(area / Math.max(count, 1)); + if (layout === 'radial' && !explicitMN && count >= 3) { + seeds.push(cen.slice()); + const rr = 0.55 * HFX.geom.polygonInradiusEstimate(pts); + const th0 = disorder > 0 ? rng.uniform(0, 2 * Math.PI) * disorder : 0; + for (let i = 0; i < count - 1; i++) { + const th = th0 + 2 * Math.PI * i / (count - 1) + (longX ? 0 : Math.PI / 2); + let sx = cen[0] + rr * Math.cos(th), sy = cen[1] + rr * Math.sin(th); + if (disorder > 0) { sx += disorder * rng.uniform(-0.5, 0.5) * rr; sy += disorder * rng.uniform(-0.5, 0.5) * rr; } + seeds.push(HFX.geom.pushInside([sx, sy], pts, cen, 0.8)); + } + } else { + const pitchX = dx / m, pitchY = dy / n; + for (let j = 0; j < n; j++) for (let i = 0; i < m; i++) { + let sx = bb.xmin + (i + 0.5) * pitchX, sy = bb.ymin + (j + 0.5) * pitchY; + if (layout === 'staggered' && n > 1 && (j % 2 === 1)) { sx += 0.5 * pitchX; if (sx > bb.xmax - 0.15 * pitchX) sx = bb.xmax - 0.15 * pitchX; } + if (disorder > 0) { sx += disorder * rng.uniform(-0.5, 0.5) * pitchX; sy += disorder * rng.uniform(-0.5, 0.5) * pitchY; } + seeds.push(HFX.geom.pushInside([sx, sy], pts, cen, 0.8)); + } + } + // enforce a minimum seed separation (only meaningful for disordered layouts) + if (disorder > 0 && minSep > 0) { + const dmin = minSep * cellScale; + for (let tries = 0; tries < 40; tries++) { + let moved = false; + for (let i = 0; i < seeds.length; i++) for (let j = 0; j < i; j++) { + if (Math.hypot(seeds[i][0] - seeds[j][0], seeds[i][1] - seeds[j][1]) < dmin) { + const ang = rng.uniform(0, 2 * Math.PI), r = cellScale * rng.uniform(0.3, 0.8); + seeds[i] = HFX.geom.pushInside([cen[0] + r * Math.cos(ang), cen[1] + r * Math.sin(ang)], pts, cen, 0.8); + moved = true; + } + } + if (!moved) break; + } + } + return seeds; +} + +function voronoiCells(poly, seeds, epsClean) { + const cells = []; + for (let i = 0; i < seeds.length; i++) { + const s = seeds[i]; + let cell = poly; + for (let j = 0; j < seeds.length; j++) { + if (j === i) continue; + const t = seeds[j]; + const ax = t[0] - s[0], ay = t[1] - s[1], mx = 0.5 * (s[0] + t[0]), my = 0.5 * (s[1] + t[1]); + cell = HFX.geom.clipHalfPlane(cell, ax, ay, -(ax * mx + ay * my), j); + if (cell.pts.length < 3) break; + } + cells.push(cell.pts.length >= 3 ? HFX.geom.cleanPolygon(cell, epsClean) : null); + } + return cells; +} + +/** Generate the hierarchical structure. Returns a structure object (undeformed geometry, element properties). */ +HFX.generateStructure = function (paramsIn) { + const p = Object.assign(HFX.defaultParams(), paramsIn || {}); + if (paramsIn && paramsIn.phys) p.phys = Object.assign({}, HFX.defaultParams().phys, paramsIn.phys); + const warnings = []; + const W = p.W, H = p.H, Lref = Math.max(W, H); + const D = Math.max(0, Math.round(p.depth)); + const b = Math.max(2, Math.round(p.branching)); + const n0x = Math.max(1, Math.round(p.n0x)), n0y = Math.max(1, Math.round(p.n0y)); + const rngGeom = HFX.makeRNG(p.seed, 'geometry'); + const rngBrace = HFX.makeRNG(p.seed, 'brace'); + const rngPrune = HFX.makeRNG(p.seed, 'prune'); + const rngStrength = HFX.makeRNG(p.seed, 'strength'); + const rngDefect = HFX.makeRNG(p.seed, 'defect'); + const expectedLeaves = n0x * n0y * Math.pow(b, D); + if (expectedLeaves > p.maxElements) { + throw new Error('Requested hierarchy (' + expectedLeaves + ' leaf cells) exceeds the element cap (' + p.maxElements + '). Reduce depth or branching.'); + } + const segments = []; // {p1,p2,level,kind,segId} + const leafCells = []; // polygons (pts arrays) + const cellsByLevel = []; + for (let k = 0; k <= D; k++) cellsByLevel.push([]); + const rootPts = [[0, 0], [W, 0], [W, H], [0, H]]; + if (p.includeFrame && p.frameMode !== 'none') for (let i = 0; i < 4; i++) { + const horizontal = (i === 0 || i === 2); + if (horizontal && p.frameMode === 'sides') continue; + segments.push({ p1: rootPts[i], p2: rootPts[(i + 1) % 4], level: 0, kind: 'frame' }); + } + const root = { pts: rootPts, tags: [-1, -1, -1, -1] }; + + function subdivide(poly, level, count, explicitMN) { + const bbox = HFX.geom.aabb(poly.pts); + const diag = Math.hypot(bbox.xmax - bbox.xmin, bbox.ymax - bbox.ymin); + const epsClean = 1e-7 * diag; + const levelDisorder = level >= (p.disorderMinLevel || 0) ? p.disorder : 0; + const seeds = makeSeeds(poly, count, p.layout, levelDisorder, rngGeom, explicitMN, p.minSeedSeparation); + const cells = voronoiCells(poly, seeds, epsClean); + for (let i = 0; i < cells.length; i++) { + const c = cells[i]; if (!c) { warnings.push('degenerate Voronoi cell skipped at level ' + level); continue; } + const n = c.pts.length; + for (let e = 0; e < n; e++) { + const tag = c.tags[e]; + if (typeof tag === 'number' && tag > i && cells[tag]) { + const p1 = c.pts[e], p2 = c.pts[(e + 1) % n]; + if (Math.hypot(p2[0] - p1[0], p2[1] - p1[1]) > 10 * epsClean) segments.push({ p1: p1, p2: p2, level: level, kind: 'wall' }); + } + } + } + for (let i = 0; i < cells.length; i++) { + const c = cells[i]; if (!c) continue; + cellsByLevel[level].push(c.pts); + const child = { pts: c.pts, tags: c.pts.map(function () { return -1; }) }; + if (level < D) subdivide(child, level + 1, b, null); else leafCells.push(c.pts); + } + } + if (n0x * n0y > 1) subdivide(root, 0, n0x * n0y, [n0x, n0y]); + else { cellsByLevel[0].push(rootPts); if (D > 0) subdivide(root, 1, b, null); else leafCells.push(rootPts); } + + // ---- connectivity pruning of finest-level walls (design choice, before density calibration) + let prunedSegments = 0; + if (p.connectivity < 1) { + for (const s of segments) if (s.kind === 'wall' && s.level === D && rngPrune.next() > p.connectivity) { s.pruned = true; prunedSegments++; } + } + // ---- braces (fan diagonals in leaf cells) + let braceCount = 0; + if (p.redundancy > 0) { + for (let ci = 0; ci < leafCells.length; ci++) { + const pts = leafCells[ci], n = pts.length; if (n < 4) continue; + const cen = HFX.geom.centroid(pts); + let c0 = 0; + if (p.disorder > 0) c0 = rngBrace.int(n); + else { // mirror-symmetric deterministic choice: corner nearest (0,0) on the left half, nearest (W,0) on the right half + const tx = cen[0] < 0.5 * W ? 0 : W; let best = Infinity; + for (let i = 0; i < n; i++) { const dd = Math.hypot(pts[i][0] - tx, pts[i][1]); if (dd < best - 1e-12) { best = dd; c0 = i; } } + } + for (let k = 2; k <= n - 2; k++) { + const take = p.redundancy >= 1 ? true : (rngBrace.next() < p.redundancy); + if (!take) continue; + segments.push({ p1: pts[c0], p2: pts[(c0 + k) % n], level: D, kind: 'brace' }); + braceCount++; + } + } + } + const activeSegments = segments.filter(function (s) { return !s.pruned; }); + activeSegments.forEach(function (s, i) { s.segId = i; }); + + // ---- noding: nodes from endpoints, T-junction detection, splitting + const tolN = 1e-7 * Lref; + const nodes = []; const nodeIndex = new Map(); + function nodeId(x, y) { + const kx = Math.round(x / tolN), ky = Math.round(y / tolN); + for (let a = -1; a <= 1; a++) for (let c = -1; c <= 1; c++) { + const id = nodeIndex.get((kx + a) + ',' + (ky + c)); + if (id !== undefined && Math.hypot(nodes[id].x - x, nodes[id].y - y) <= 2 * tolN) return id; + } + const id = nodes.length; nodes.push({ x: x, y: y, level: Infinity }); nodeIndex.set(kx + ',' + ky, id); return id; + } + for (const s of activeSegments) { + s.nA = nodeId(s.p1[0], s.p1[1]); s.nB = nodeId(s.p2[0], s.p2[1]); + s.L = Math.hypot(s.p2[0] - s.p1[0], s.p2[1] - s.p1[1]); + if (s.level < nodes[s.nA].level) nodes[s.nA].level = s.level; + if (s.level < nodes[s.nB].level) nodes[s.nB].level = s.level; + s.interior = []; + } + // spatial hash of nodes for on-segment search + const cellSize = Math.max(Lref / 64, 1e-6); + const hash = new Map(); + const hk = function (ix, iy) { return ix + ',' + iy; }; + nodes.forEach(function (nd, id) { const k = hk(Math.floor(nd.x / cellSize), Math.floor(nd.y / cellSize)); if (!hash.has(k)) hash.set(k, []); hash.get(k).push(id); }); + const tolOn = 1e-7 * Lref; + for (const s of activeSegments) { + const ex = (s.p2[0] - s.p1[0]) / s.L, ey = (s.p2[1] - s.p1[1]) / s.L; + const xmin = Math.min(s.p1[0], s.p2[0]) - tolOn, xmax = Math.max(s.p1[0], s.p2[0]) + tolOn; + const ymin = Math.min(s.p1[1], s.p2[1]) - tolOn, ymax = Math.max(s.p1[1], s.p2[1]) + tolOn; + const ix0 = Math.floor(xmin / cellSize), ix1 = Math.floor(xmax / cellSize), iy0 = Math.floor(ymin / cellSize), iy1 = Math.floor(ymax / cellSize); + for (let ix = ix0; ix <= ix1; ix++) for (let iy = iy0; iy <= iy1; iy++) { + const bucket = hash.get(hk(ix, iy)); if (!bucket) continue; + for (const id of bucket) { + if (id === s.nA || id === s.nB) continue; + const nd = nodes[id]; + const rx = nd.x - s.p1[0], ry = nd.y - s.p1[1]; + const t = rx * ex + ry * ey; + if (t <= tolOn || t >= s.L - tolOn) continue; + const dist = Math.abs(rx * ey - ry * ex); + if (dist <= tolOn) { s.interior.push({ id: id, t: t }); if (s.level < nd.level) nd.level = s.level; } + } + } + } + // ---- split segments into elements (with interface nodes) + const elements = []; + const fInt = Math.min(0.45, Math.max(0.01, p.interfaceFraction)); + for (const s of activeSegments) { + s.interior.sort(function (a, b2) { return a.t - b2.t; }); + const chain = [{ id: s.nA, t: 0 }].concat(s.interior, [{ id: s.nB, t: s.L }]); + const flags = chain.map(function () { return { ifaceA: false, ifaceB: false }; }); + if (s.kind === 'wall') { + const coarseA = nodes[s.nA].level < s.level, coarseB = nodes[s.nB].level < s.level; + if (p.interfaceMode === 'segment') { + const insert = function (tPos, fromA) { + // do not insert if an existing chain node is already within the interface zone + for (const c of chain) { if (fromA ? (c.t > 1e-12 && c.t <= tPos + 1e-12) : (c.t < s.L - 1e-12 && c.t >= tPos - 1e-12)) return; } + const x = s.p1[0] + (s.p2[0] - s.p1[0]) * tPos / s.L, y = s.p1[1] + (s.p2[1] - s.p1[1]) * tPos / s.L; + const id = nodeId(x, y); nodes[id].level = Math.min(nodes[id].level, s.level); nodes[id].ifaceNode = true; + chain.push({ id: id, t: tPos }); chain.sort(function (a, b2) { return a.t - b2.t; }); + }; + if (coarseA) insert(fInt * s.L, true); + if (coarseB) insert(s.L - fInt * s.L, false); + } + if (p.interfaceMode !== 'none') { s.coarseA = coarseA; s.coarseB = coarseB; } + } + for (let i = 0; i + 1 < chain.length; i++) { + const a = chain[i].id, c = chain[i + 1].id; + if (a === c) continue; + const isIface = (s.kind === 'wall' && p.interfaceMode !== 'none') && ((i === 0 && s.coarseA) || (i === chain.length - 2 && s.coarseB)); + elements.push({ n1: a, n2: c, level: s.level, kind: s.kind, isInterface: !!isIface, segId: s.segId, ifaceEnd: isIface ? (i === 0 ? 'A' : 'B') : '' }); + } + } + // ---- short-feature merge (union–find on nodes closer than mergeFraction * leaf cell size) + const leafScale = Math.sqrt(W * H / Math.max(1, leafCells.length)); + const lMin = p.mergeFraction * leafScale; + const parent = nodes.map(function (_, i) { return i; }); + const find = function (i) { while (parent[i] !== i) { parent[i] = parent[parent[i]]; i = parent[i]; } return i; }; + let mergedNodes = 0; + if (lMin > 0) { + const hash2 = new Map(); const cs2 = Math.max(lMin, 1e-9); + nodes.forEach(function (nd, id) { const k = hk(Math.floor(nd.x / cs2), Math.floor(nd.y / cs2)); if (!hash2.has(k)) hash2.set(k, []); hash2.get(k).push(id); }); + nodes.forEach(function (nd, id) { + const ix = Math.floor(nd.x / cs2), iy = Math.floor(nd.y / cs2); + for (let a = -1; a <= 1; a++) for (let c = -1; c <= 1; c++) { + const bucket = hash2.get(hk(ix + a, iy + c)); if (!bucket) continue; + for (const j of bucket) { if (j <= id) continue; if (Math.hypot(nodes[j].x - nd.x, nodes[j].y - nd.y) < lMin) { const ra = find(id), rb = find(j); if (ra !== rb) { parent[rb] = ra; mergedNodes++; } } } + } + }); + } + // compact nodes + const clusters = new Map(); const newNodes = []; const mapId = new Int32Array(nodes.length); + nodes.forEach(function (nd, id) { + const r = find(id); + if (!clusters.has(r)) { clusters.set(r, newNodes.length); newNodes.push({ x: 0, y: 0, level: Infinity, count: 0, ifaceNode: false }); } + const ni = clusters.get(r); mapId[id] = ni; const nn = newNodes[ni]; + nn.x += nd.x; nn.y += nd.y; nn.count++; nn.level = Math.min(nn.level, nd.level); nn.ifaceNode = nn.ifaceNode || !!nd.ifaceNode; + }); + newNodes.forEach(function (nn) { nn.x /= nn.count; nn.y /= nn.count; delete nn.count; }); + // snap boundary nodes exactly onto the specimen boundary + const tolBC = 1e-6 * Lref; + newNodes.forEach(function (nn) { + if (Math.abs(nn.x) < tolBC) nn.x = 0; if (Math.abs(nn.x - W) < tolBC) nn.x = W; + if (Math.abs(nn.y) < tolBC) nn.y = 0; if (Math.abs(nn.y - H) < tolBC) nn.y = H; + nn.onBottom = nn.y === 0; nn.onTop = nn.y === H; nn.onLeft = nn.x === 0; nn.onRight = nn.x === W; + }); + // remap elements, drop degenerate and duplicates + const seen = new Map(); const finalElements = []; let dropped = 0; + for (const e of elements) { + const a = mapId[e.n1], c = mapId[e.n2]; if (a === c) { dropped++; continue; } + const key = Math.min(a, c) + ',' + Math.max(a, c); + if (seen.has(key)) { const prev = finalElements[seen.get(key)]; if (e.level < prev.level) { prev.level = e.level; prev.kind = e.kind; } dropped++; continue; } + seen.set(key, finalElements.length); + e.n1 = a; e.n2 = c; finalElements.push(e); + } + finalElements.forEach(function (e, i) { + e.id = i; const A = newNodes[e.n1], B = newNodes[e.n2]; + e.L = Math.hypot(B.x - A.x, B.y - A.y); e.cx = 0.5 * (A.x + B.x); e.cy = 0.5 * (A.y + B.y); + e.absent = false; e.strengthFactor = 1; + }); + // ---- defects (applied to the finished design): notch / weak zone / random missing members + let defectRemoved = 0, defectWeakened = 0; + if (p.defectType === 'notch' || p.defectType === 'weak') { + const cx = p.defectX * W, cy = p.defectY * H, r = p.defectSize * W; + for (const e of finalElements) { + const A = newNodes[e.n1], B = newNodes[e.n2]; + // distance from defect centre to the segment + const ex = B.x - A.x, ey = B.y - A.y, L2 = ex * ex + ey * ey; + let t = L2 > 0 ? ((cx - A.x) * ex + (cy - A.y) * ey) / L2 : 0; t = Math.max(0, Math.min(1, t)); + const dd = Math.hypot(A.x + t * ex - cx, A.y + t * ey - cy); + if (dd <= r) { if (p.defectType === 'notch') { e.absent = true; e.defect = 'notch'; defectRemoved++; } else { e.strengthFactor *= p.defectWeakFactor; e.defect = 'weak'; defectWeakened++; } } + } + } + if (p.missingFraction > 0) { + for (const e of finalElements) { if (!e.absent && e.kind !== 'frame' && rngDefect.next() < p.missingFraction) { e.absent = true; e.defect = 'missing'; defectRemoved++; } } + } + // ---- density calibration (design members, i.e. before defects are cut) + const rt = Math.max(1e-6, p.thicknessRatio); + // members lying entirely on a grip line (both nodes on the same grip) are rigidly held by the grip: they carry no strain and are + // excluded from the material budget (they belong to the grip region, not to the gauge structure) + for (const e of finalElements) { const A = newNodes[e.n1], B = newNodes[e.n2]; e.gripLine = (A.onTop && B.onTop) || (A.onBottom && B.onBottom); } + let S = 0, L0sum = 0, L0n = 0; + for (const e of finalElements) { if (e.gripLine) continue; S += e.L * Math.pow(rt, e.level); if (e.level === 0) { L0sum += e.L; L0n++; } } + let t0; + const L0ref = L0n > 0 ? L0sum / L0n : W / n0x; + if (p.densityMode === 'slenderness') t0 = L0ref / Math.max(1e-9, p.slenderness0); + else t0 = p.relDensity * W * H / Math.max(S, 1e-300); + let matDesign = 0, matActual = 0, matGrip = 0; + const levelStats = []; + for (let k = 0; k <= D; k++) levelStats.push({ level: k, count: 0, length: 0, thickness: t0 * Math.pow(rt, k), material: 0, interfaces: 0, braces: 0, meanSlenderness: 0, wallSlenderness: 0, walls: 0, absent: 0 }); + const wallSets = []; for (let k = 0; k <= D; k++) wallSets.push(new Set()); + for (const e of finalElements) { + e.t = t0 * Math.pow(rt, e.level); + e.A = e.t; e.I = p.bendingFactor * e.t * e.t * e.t / 12; + e.Emod = p.E * (e.isInterface ? p.interfaceStiffnessRatio : 1); + const xi = rngStrength.lognormalMean1(p.strengthCV); + e.epsC = p.failStrain * Math.pow(p.strengthLevelRatio, e.level) * (e.isInterface ? p.interfaceStrengthRatio : 1) * xi * e.strengthFactor; + e.xi = xi; + if (e.gripLine) { matGrip += e.L * e.t; continue; } + matDesign += e.L * e.t; if (!e.absent) matActual += e.L * e.t; + const ls = levelStats[e.level]; ls.count++; ls.length += e.L; ls.material += e.L * e.t; if (e.isInterface) ls.interfaces++; if (e.kind === 'brace') ls.braces++; if (e.absent) ls.absent++; + wallSets[e.level].add(e.segId); + } + levelStats.forEach(function (ls, k) { ls.walls = wallSets[k].size; ls.meanSlenderness = ls.count ? (ls.length / ls.count) / ls.thickness : 0; ls.wallSlenderness = ls.walls ? (ls.length / ls.walls) / ls.thickness : 0; ls.materialFraction = matDesign > 0 ? ls.material / matDesign : 0; }); + // ---- connectivity statistics + const deg = new Int32Array(newNodes.length); let nActive = 0; + for (const e of finalElements) if (!e.absent) { deg[e.n1]++; deg[e.n2]++; } + for (let i = 0; i < newNodes.length; i++) if (deg[i] > 0) nActive++; + const nEl = finalElements.filter(function (e) { return !e.absent; }).length; + const nTop = newNodes.filter(function (n) { return n.onTop; }).length, nBottom = newNodes.filter(function (n) { return n.onBottom; }).length; + const structure = { + params: p, W: W, H: H, depth: D, branching: b, nodes: newNodes, elements: finalElements, leafCells: leafCells, cellsByLevel: cellsByLevel, + t0: t0, levelStats: levelStats, warnings: warnings, + stats: { + nodes: newNodes.length, activeNodes: nActive, elements: finalElements.length, activeElements: nEl, leafCells: leafCells.length, + relDensityDesign: matDesign / (W * H), relDensityActual: matActual / (W * H), gripLineMaterial: matGrip / (W * H), t0: t0, tMin: t0 * Math.pow(rt, D), tMax: t0, + meanCoordination: nActive ? 2 * nEl / nActive : 0, braces: braceCount, prunedSegments: prunedSegments, mergedNodes: mergedNodes, droppedElements: dropped, + defectRemoved: defectRemoved, defectWeakened: defectWeakened, interfaces: finalElements.filter(function (e) { return e.isInterface; }).length, + gripNodesTop: nTop, gripNodesBottom: nBottom, leafScale: leafScale, minSlendernessLevel: Math.min.apply(null, levelStats.filter(function (l) { return l.count; }).map(function (l) { return l.wallSlenderness; })), minElementSlenderness: Math.min.apply(null, levelStats.filter(function (l) { return l.count; }).map(function (l) { return l.meanSlenderness; })) + } + }; + if (nTop === 0 || nBottom === 0) warnings.push('no grip nodes found on top/bottom boundary'); + return structure; +}; + +/** Compact, human-readable parameter summary */ +HFX.paramsSummary = function (p) { + return 'D=' + p.depth + ' b=' + p.branching + ' n0=' + p.n0x + 'x' + p.n0y + ' ' + p.layout + ' dis=' + p.disorder + (p.disorderMinLevel ? '(L>=' + p.disorderMinLevel + ')' : '') + ' rt=' + p.thicknessRatio + ' rho=' + p.relDensity + ' red=' + p.redundancy + ' con=' + p.connectivity + ' sInt=' + p.interfaceStrengthRatio + ' cv=' + p.strengthCV + ' seed=' + p.seed; +}; + +// ============================================================================ +// 30. 2-D Euler–Bernoulli beam-network model +// DOF per node: (u, v, theta). Element: prismatic beam, axial + bending, +// small strain, small rotation, linear elastic. Global K = sum T^T k_local T. +// Prescribed displacements (grips) are eliminated by partitioning: +// K_ff u_f = - K_fp u_p ; reactions r_p = K_pf u_f + K_pp u_p +// Linear system: envelope (profile) LDL^T with reverse Cuthill–McKee ordering. +// Stabilisation: a tiny ground spring eps * k_ref on every free DOF keeps K_ff +// positive definite when fragments detach (its force is reported in residuals). +// ============================================================================ +function localBeamStiffness(EA_L, EI, L, out) { + const k1 = 12 * EI / (L * L * L), k2 = 6 * EI / (L * L), k3 = 4 * EI / L, k4 = 2 * EI / L; + out.fill(0); + out[0] = EA_L; out[3] = -EA_L; out[18] = -EA_L; out[21] = EA_L; + out[7] = k1; out[8] = k2; out[10] = -k1; out[11] = k2; + out[13] = k2; out[14] = k3; out[16] = -k2; out[17] = k4; + out[25] = -k1; out[26] = -k2; out[28] = k1; out[29] = -k2; + out[31] = k2; out[32] = k4; out[34] = -k2; out[35] = k3; + return out; +} +/** K_global = T^T k_local T with T = blockdiag(R, R), R = [[c,s,0],[-s,c,0],[0,0,1]] */ +function transformToGlobal(kl, c, s, out) { + // T is 6x6: rows: [c s 0 0 0 0],[-s c 0 0 0 0],[0 0 1 0 0 0],[0 0 0 c s 0],[0 0 0 -s c 0],[0 0 0 0 0 1] + const T = [[c, s, 0, 0, 0, 0], [-s, c, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0], [0, 0, 0, c, s, 0], [0, 0, 0, -s, c, 0], [0, 0, 0, 0, 0, 1]]; + const tmp = new Float64Array(36); + for (let i = 0; i < 6; i++) for (let j = 0; j < 6; j++) { let v = 0; for (let k = 0; k < 6; k++) v += kl[i * 6 + k] * T[k][j]; tmp[i * 6 + j] = v; } + for (let i = 0; i < 6; i++) for (let j = 0; j < 6; j++) { let v = 0; for (let k = 0; k < 6; k++) v += T[k][i] * tmp[k * 6 + j]; out[i * 6 + j] = v; } + return out; +} + +/** Envelope (profile) symmetric LDL^T factorisation. Row storage of the lower triangle. */ +function EnvelopeLDL(n, first) { + this.n = n; this.first = first; + this.rowStart = new Int32Array(n + 1); + for (let i = 0; i < n; i++) this.rowStart[i + 1] = this.rowStart[i] + (i - first[i] + 1); + this.vals = new Float64Array(this.rowStart[n]); + this.D = new Float64Array(n); + this.factorized = false; + this.minPivot = Infinity; this.maxPivot = 0; this.nonPositive = 0; +} +EnvelopeLDL.prototype.add = function (i, j, v) { // i >= j + if (i < j) { const t = i; i = j; j = t; } + this.vals[this.rowStart[i] + (j - this.first[i])] += v; +}; +EnvelopeLDL.prototype.factorize = function () { + const n = this.n, first = this.first, rs = this.rowStart, a = this.vals, D = this.D; + const g = new Float64Array(n); + let minP = Infinity, maxP = 0, nonPos = 0; + for (let i = 0; i < n; i++) { + const fi = first[i], ri = rs[i]; + for (let j = fi; j < i; j++) { + const fj = first[j], rj = rs[j]; + const ks = fi > fj ? fi : fj; + let s = a[ri + (j - fi)]; + let ai = ks - fi, aj = rj + (ks - fj); + for (let k = ks; k < j; k++, ai++, aj++) s -= g[ai] * a[aj]; + a[ri + (j - fi)] = s / D[j]; + g[j - fi] = s; + } + let d = a[ri + (i - fi)]; + for (let k = fi; k < i; k++) d -= g[k - fi] * a[ri + (k - fi)]; + D[i] = d; + if (d <= 0) { nonPos++; D[i] = 1e-300; } + if (d < minP) minP = d; if (d > maxP) maxP = d; + } + this.minPivot = minP; this.maxPivot = maxP; this.nonPositive = nonPos; this.factorized = true; + return nonPos === 0; +}; +EnvelopeLDL.prototype.solve = function (b, x) { + const n = this.n, first = this.first, rs = this.rowStart, a = this.vals, D = this.D; + if (!x) x = new Float64Array(n); + for (let i = 0; i < n; i++) { const fi = first[i], ri = rs[i]; let s = b[i]; for (let k = fi; k < i; k++) s -= a[ri + (k - fi)] * x[k]; x[i] = s; } + for (let i = 0; i < n; i++) x[i] /= D[i]; + for (let i = n - 1; i >= 0; i--) { const fi = first[i], ri = rs[i]; const xi = x[i]; for (let k = fi; k < i; k++) x[k] -= a[ri + (k - fi)] * xi; } + return x; +}; +HFX.EnvelopeLDL = EnvelopeLDL; + +/** Reverse Cuthill–McKee ordering of the nodes in `mask` given adjacency lists. */ +function rcmOrder(nNodes, adj, mask) { + const visited = new Uint8Array(nNodes); const order = []; + const deg = new Int32Array(nNodes); for (let i = 0; i < nNodes; i++) deg[i] = adj[i].length; + const bfs = function (start, collect) { + const q = [start]; const seen = new Uint8Array(nNodes); seen[start] = 1; let last = start; const dist = new Int32Array(nNodes); + for (let h = 0; h < q.length; h++) { + const v = q[h]; last = v; + const nb = adj[v].filter(function (w) { return mask[w] && !seen[w]; }).sort(function (x, y) { return deg[x] - deg[y]; }); + for (const w of nb) { seen[w] = 1; dist[w] = dist[v] + 1; q.push(w); } + } + if (collect) return q; + // pick the farthest node with minimum degree as pseudo-peripheral + const maxD = dist[last]; let best = last; + for (let i = 0; i < q.length; i++) if (dist[q[i]] === maxD && deg[q[i]] < deg[best]) best = q[i]; + return best; + }; + for (let s = 0; s < nNodes; s++) { + if (!mask[s] || visited[s]) continue; + let start = s; + // pseudo-peripheral start: two BFS passes + start = bfs(bfs(start, false), false); + const comp = bfs(start, true); + for (const v of comp) { visited[v] = 1; order.push(v); } + } + order.reverse(); + return order; +} + +/** + * BeamModel: manages element states, boundary conditions, assembly, factorisation, + * unit-displacement solution and element force recovery. + */ +HFX.BeamModel = function (structure, params) { + this.s = structure; this.p = Object.assign({}, structure.params, params || {}); + const nodes = structure.nodes, els = structure.elements; + this.nNodes = nodes.length; this.nEl = els.length; this.ndof = 3 * nodes.length; + this.state = new Int8Array(this.nEl); // 0 intact, 1 damaged, 2 failed + for (let i = 0; i < this.nEl; i++) if (els[i].absent) this.state[i] = 2; + // per-element geometric data + this.cosE = new Float64Array(this.nEl); this.sinE = new Float64Array(this.nEl); this.LE = new Float64Array(this.nEl); + for (let i = 0; i < this.nEl; i++) { const e = els[i], A = nodes[e.n1], B = nodes[e.n2]; const dx = B.x - A.x, dy = B.y - A.y; const L = Math.hypot(dx, dy); this.LE[i] = L; this.cosE[i] = dx / L; this.sinE[i] = dy / L; } + this.Ke = new Array(this.nEl); // global element stiffness (intact); scaled by residual factor when damaged + const kl = new Float64Array(36); + for (let i = 0; i < this.nEl; i++) { const e = els[i]; const out = new Float64Array(36); localBeamStiffness(e.Emod * e.A / this.LE[i], e.Emod * e.I, this.LE[i], kl); transformToGlobal(kl, this.cosE[i], this.sinE[i], out); this.Ke[i] = out; } + // reference stiffness for stabilisation + // reference axial stiffness for the stabilisation springs: E * mean(t) / mean(L) (robust to short stubby elements) + let tsum = 0, lsum = 0, cnt = 0; for (let i = 0; i < this.nEl; i++) { const e = els[i]; tsum += e.Emod * e.A; lsum += this.LE[i]; cnt++; } + this.kRef = cnt ? (tsum / cnt) / (lsum / cnt) : 1; this.Lref = Math.max(structure.W, structure.H); + this.u = new Float64Array(this.ndof); this.u1 = new Float64Array(this.ndof); + this.fint = new Float64Array(this.ndof); + this.N = new Float64Array(this.nEl); this.M1 = new Float64Array(this.nEl); this.M2 = new Float64Array(this.nEl); this.V = new Float64Array(this.nEl); + this.epsMax = new Float64Array(this.nEl); this.epsMin = new Float64Array(this.nEl); this.util = new Float64Array(this.nEl); + this.util1 = new Float64Array(this.nEl); this.N1 = new Float64Array(this.nEl); + this.rebuildCount = 0; this.solveCount = 0; this.factorTimeMs = 0; this.lastRebuild = null; + this.setupBC(); +}; +HFX.BeamModel.prototype.stiffnessFactor = function (i) { const st = this.state[i]; return st === 0 ? 1 : (st === 1 ? this.p.residualStiffness : 0); }; +HFX.BeamModel.prototype.setupBC = function () { + const nodes = this.s.nodes, p = this.p; const n = this.nNodes; + this.presc = new Uint8Array(this.ndof); this.prescVal = new Float64Array(this.ndof); // pattern for unit applied displacement + this.topV = []; this.bottomV = []; + for (let i = 0; i < n; i++) { + const nd = nodes[i]; + if (nd.bc) { // explicit per-node override {u:0|1, v:0|1, th:0|1, vValue} + if (nd.bc.u) this.presc[3 * i] = 1; if (nd.bc.v) { this.presc[3 * i + 1] = 1; if (nd.bc.vValue) { this.prescVal[3 * i + 1] = nd.bc.vValue; this.topV.push(3 * i + 1); } else if (nd.onBottom) this.bottomV.push(3 * i + 1); } + if (nd.bc.th) this.presc[3 * i + 2] = 1; + continue; + } + if (nd.onTop) { + this.presc[3 * i + 1] = 1; this.prescVal[3 * i + 1] = 1; this.topV.push(3 * i + 1); + if (p.gripType === 'clamped') { this.presc[3 * i] = 1; this.presc[3 * i + 2] = 1; } + else if (p.gripType === 'pinned') { this.presc[3 * i] = 1; } + } + if (nd.onBottom) { + this.presc[3 * i + 1] = 1; this.bottomV.push(3 * i + 1); + this.presc[3 * i] = 1; // horizontal fixed at the bottom for all grip types (removes rigid-body translation) + if (p.gripType === 'clamped') this.presc[3 * i + 2] = 1; + } + } +}; +/** Rebuild the active system (after any state change): ordering, envelope, factorisation, unit solution. */ +HFX.BeamModel.prototype.rebuild = function () { + const t0 = (typeof performance !== 'undefined' && performance.now) ? performance.now() : Date.now(); + const els = this.s.elements, n = this.nNodes, ndof = this.ndof; + // active nodes and adjacency + const adj = new Array(n); for (let i = 0; i < n; i++) adj[i] = []; + const active = new Uint8Array(n); + for (let i = 0; i < this.nEl; i++) { if (this.state[i] === 2) continue; if (this.state[i] === 1 && this.p.residualStiffness <= 0) continue; const e = els[i]; adj[e.n1].push(e.n2); adj[e.n2].push(e.n1); active[e.n1] = 1; active[e.n2] = 1; } + // effective prescribed set: inactive nodes fully fixed (zero). Detached fragments (components of the intact network that + // touch neither grip) are unloaded rigid bodies; their DOFs are frozen (displayed undeformed) instead of being held by the + // stabilisation springs alone, which keeps the system well conditioned. + const presc = new Uint8Array(this.presc); for (let i = 0; i < n; i++) if (!active[i]) { presc[3 * i] = 1; presc[3 * i + 1] = 1; presc[3 * i + 2] = 1; } + const reach = new Uint8Array(n); const q = []; + for (let i = 0; i < n; i++) if (active[i] && (this.s.nodes[i].onTop || this.s.nodes[i].onBottom || this.s.nodes[i].bc)) { reach[i] = 1; q.push(i); } + for (let h = 0; h < q.length; h++) { const v = q[h]; for (const w of adj[v]) if (!reach[w]) { reach[w] = 1; q.push(w); } } + let frozen = 0; + for (let i = 0; i < n; i++) if (active[i] && !reach[i]) { presc[3 * i] = 1; presc[3 * i + 1] = 1; presc[3 * i + 2] = 1; frozen++; } + this.frozenNodes = frozen; + const mask = new Uint8Array(n); for (let i = 0; i < n; i++) mask[i] = active[i] && (!presc[3 * i] || !presc[3 * i + 1] || !presc[3 * i + 2]) ? 1 : 0; + const order = rcmOrder(n, adj, mask); + const dofNew = new Int32Array(ndof).fill(-1); let nf = 0; + for (const v of order) for (let c = 0; c < 3; c++) { const d = 3 * v + c; if (!presc[d]) dofNew[d] = nf++; } + this.nFree = nf; this.dofNew = dofNew; this.prescEff = presc; + // envelope structure + const first = new Int32Array(nf); for (let i = 0; i < nf; i++) first[i] = i; + const dofs = new Int32Array(6); + for (let ei = 0; ei < this.nEl; ei++) { + const sf = this.stiffnessFactor(ei); if (sf <= 0) continue; + const e = els[ei]; dofs[0] = 3 * e.n1; dofs[1] = 3 * e.n1 + 1; dofs[2] = 3 * e.n1 + 2; dofs[3] = 3 * e.n2; dofs[4] = 3 * e.n2 + 1; dofs[5] = 3 * e.n2 + 2; + let mn = Infinity, mx = -1; + for (let a = 0; a < 6; a++) { const r = dofNew[dofs[a]]; if (r < 0) continue; if (r < mn) mn = r; if (r > mx) mx = r; } + if (mx < 0) continue; + for (let a = 0; a < 6; a++) { const r = dofNew[dofs[a]]; if (r >= 0 && mn < first[r]) first[r] = mn; } + } + const ldl = new EnvelopeLDL(nf, first); + const rhs1 = new Float64Array(nf); + const stab = this.p.stabilization * this.kRef; + for (let ei = 0; ei < this.nEl; ei++) { + const sf = this.stiffnessFactor(ei); if (sf <= 0) continue; + const e = els[ei], K = this.Ke[ei]; + dofs[0] = 3 * e.n1; dofs[1] = 3 * e.n1 + 1; dofs[2] = 3 * e.n1 + 2; dofs[3] = 3 * e.n2; dofs[4] = 3 * e.n2 + 1; dofs[5] = 3 * e.n2 + 2; + for (let a = 0; a < 6; a++) { + const ra = dofNew[dofs[a]]; if (ra < 0) continue; + for (let b2 = 0; b2 < 6; b2++) { + const kab = K[a * 6 + b2] * sf; if (kab === 0) continue; + const rb = dofNew[dofs[b2]]; + if (rb >= 0) { if (rb <= ra) ldl.add(ra, rb, kab); } + else { const up = this.prescVal[dofs[b2]]; if (up !== 0) rhs1[ra] -= kab * up; } + } + } + } + // ground-spring stabilisation on every free DOF (rotational DOFs scaled by Lref^2) + for (let d = 0; d < ndof; d++) { const r = dofNew[d]; if (r >= 0) ldl.vals[ldl.rowStart[r] + (r - first[r])] += (d % 3 === 2 ? stab * this.Lref * this.Lref : stab); } + const ok = ldl.factorize(); + this.ldl = ldl; this.rhs1 = rhs1; + // unit solution + const uf = ldl.solve(rhs1); + this.u1.fill(0); + for (let d = 0; d < ndof; d++) { const r = dofNew[d]; this.u1[d] = r >= 0 ? uf[r] : (presc[d] ? this.prescVal[d] : 0); } + this.computeElementResults(this.u1, this.util1, this.N1); + const dSaved = this.d; this.d = 1; + const react = this.computeReactions(this.u1); + this.d = dSaved; + this.F1 = react.Ftop; this.Fbot1 = react.Fbot; this.residual1 = react.residual; this.stabForce1 = react.stabForce; + if (this.Fref === undefined) this.Fref = Math.abs(react.Ftop); // force per unit displacement of the intact structure + let envelope = ldl.vals.length; let maxBand = 0; for (let i = 0; i < nf; i++) if (i - first[i] > maxBand) maxBand = i - first[i]; + this.rebuildCount++; + const t1 = (typeof performance !== 'undefined' && performance.now) ? performance.now() : Date.now(); + this.factorTimeMs += (t1 - t0); + this.lastRebuild = { nFree: nf, envelope: envelope, maxBandwidth: maxBand, factorOK: ok, minPivot: ldl.minPivot, maxPivot: ldl.maxPivot, nonPositivePivots: ldl.nonPositive, timeMs: t1 - t0, residualUnit: react.residual, frozenNodes: frozen }; + return this.lastRebuild; +}; +/** Solve at applied displacement d (forward/back substitution with the cached factorisation). */ +HFX.BeamModel.prototype.solveAt = function (d) { + const nf = this.nFree, ndof = this.ndof, dofNew = this.dofNew, presc = this.prescEff; + const rhs = new Float64Array(nf); for (let i = 0; i < nf; i++) rhs[i] = this.rhs1[i] * d; + const uf = this.ldl.solve(rhs); + for (let dd = 0; dd < ndof; dd++) { const r = dofNew[dd]; this.u[dd] = r >= 0 ? uf[r] : (presc[dd] ? this.prescVal[dd] * d : 0); } + this.solveCount++; this.d = d; + this.computeElementResults(this.u, this.util, this.N); + const react = this.computeReactions(this.u); + this.F = react.Ftop; this.Fbot = react.Fbot; this.residual = react.residual; this.stabForce = react.stabForce; this.d = d; this.lastReact = react; + return react; +}; +/** Element internal forces, fibre strains and utilisation for displacement vector u. */ +HFX.BeamModel.prototype.computeElementResults = function (u, utilOut, NOut) { + const els = this.s.elements, p = this.p; + const ug = new Float64Array(6), ul = new Float64Array(6); + for (let i = 0; i < this.nEl; i++) { + const e = els[i], st = this.state[i]; + if (st === 2 || (st === 1 && p.residualStiffness <= 0)) { utilOut[i] = 0; NOut[i] = 0; this.M1[i] = 0; this.M2[i] = 0; this.V[i] = 0; this.epsMax[i] = 0; this.epsMin[i] = 0; continue; } + const c = this.cosE[i], s = this.sinE[i], L = this.LE[i]; + ug[0] = u[3 * e.n1]; ug[1] = u[3 * e.n1 + 1]; ug[2] = u[3 * e.n1 + 2]; ug[3] = u[3 * e.n2]; ug[4] = u[3 * e.n2 + 1]; ug[5] = u[3 * e.n2 + 2]; + ul[0] = c * ug[0] + s * ug[1]; ul[1] = -s * ug[0] + c * ug[1]; ul[2] = ug[2]; + ul[3] = c * ug[3] + s * ug[4]; ul[4] = -s * ug[3] + c * ug[4]; ul[5] = ug[5]; + const sf = st === 0 ? 1 : p.residualStiffness; + const E = e.Emod * sf, EA = E * e.A, EI = E * e.I; + const epsAx = (ul[3] - ul[0]) / L; + const N = EA * epsAx; + // end moments (Hermitian beam): M1 = EI*(6/L^2*(v2-v1)*(-1)... use stiffness rows + const k2 = 6 * EI / (L * L), k3 = 4 * EI / L, k4 = 2 * EI / L, k1 = 12 * EI / (L * L * L); + const M1 = k2 * ul[1] + k3 * ul[2] - k2 * ul[4] + k4 * ul[5]; + const M2 = k2 * ul[1] + k4 * ul[2] - k2 * ul[4] + k3 * ul[5]; + const V = k1 * ul[1] + k2 * ul[2] - k1 * ul[4] + k2 * ul[5]; + NOut[i] = N; this.M1[i] = M1; this.M2[i] = M2; this.V[i] = V; + const kappaMax = Math.max(Math.abs(M1), Math.abs(M2)) / EI; + const epsB = kappaMax * e.t * 0.5; + const eMax = epsAx + epsB, eMin = epsAx - epsB; + this.epsMax[i] = eMax; this.epsMin[i] = eMin; + const limit = st === 0 ? e.epsC : e.epsC * p.ductilityRatio; + let w = eMax / limit; + if (p.compressiveRatio > 0) { const wc = -eMin / (p.compressiveRatio * e.epsC); if (wc > w) w = wc; } + utilOut[i] = w; + } +}; +/** Internal force vector, reactions (top/bottom vertical sums) and equilibrium residual at free DOFs. */ +HFX.BeamModel.prototype.computeReactions = function (u) { + const els = this.s.elements, f = this.fint; f.fill(0); + const ue = new Float64Array(6); const dofs = new Int32Array(6); + for (let i = 0; i < this.nEl; i++) { + const sf = this.stiffnessFactor(i); if (sf <= 0) continue; + const e = els[i], K = this.Ke[i]; + dofs[0] = 3 * e.n1; dofs[1] = 3 * e.n1 + 1; dofs[2] = 3 * e.n1 + 2; dofs[3] = 3 * e.n2; dofs[4] = 3 * e.n2 + 1; dofs[5] = 3 * e.n2 + 2; + for (let a = 0; a < 6; a++) ue[a] = u[dofs[a]]; + for (let a = 0; a < 6; a++) { let v = 0; for (let b2 = 0; b2 < 6; b2++) v += K[a * 6 + b2] * ue[b2]; f[dofs[a]] += v * sf; } + } + const stab = this.p.stabilization * this.kRef; let stabForce = 0, stabV = 0; + const presc = this.prescEff, dofNew = this.dofNew; + let res2 = 0, react2 = 0; + for (let d = 0; d < this.ndof; d++) { + if (dofNew[d] >= 0) { const fs = (d % 3 === 2 ? stab * this.Lref * this.Lref : stab) * u[d]; f[d] += fs; stabForce += Math.abs(fs); if (d % 3 === 1) stabV += fs; res2 += f[d] * f[d]; } + else if (presc[d]) react2 += f[d] * f[d]; + } + let Ftop = 0, Fbot = 0; for (const d of this.topV) Ftop += f[d]; for (const d of this.bottomV) Fbot += f[d]; + // residual scale: reaction norm, floored at 0.1% of the force the intact structure carries at the same displacement + // (the floor only matters after complete separation, when the reactions reduce to the negligible stabilisation forces) + const dApplied = Math.abs(this.d || 0); + const scale = Math.max(Math.sqrt(react2), (this.Fref || 0) * dApplied * 1e-3, 1e-300); + const residual = Math.sqrt(res2) / scale; + this.residualAbs = Math.sqrt(res2); + // global vertical equilibrium: F_top + F_bottom = sum of vertical stabilisation forces at free DOFs (the only other external forces) + return { Ftop: Ftop, Fbot: Fbot, residual: residual, residualAbs: Math.sqrt(res2), stabForce: stabForce, stabV: stabV, forceBalance: Math.abs(Ftop + Fbot - stabV) / Math.max(Math.abs(Ftop), 1e-300), forceBalanceRaw: Math.abs(Ftop + Fbot) / Math.max(Math.abs(Ftop), 1e-300) }; +}; +/** Is there a load path (through non-failed elements) between the bottom and the top grip? */ +HFX.BeamModel.prototype.isConnected = function () { + const els = this.s.elements, n = this.nNodes; const adj = new Array(n); for (let i = 0; i < n; i++) adj[i] = []; + for (let i = 0; i < this.nEl; i++) { if (this.stiffnessFactor(i) <= 0) continue; const e = els[i]; adj[e.n1].push(e.n2); adj[e.n2].push(e.n1); } + const seen = new Uint8Array(n); const q = []; for (let i = 0; i < n; i++) if (this.s.nodes[i].onBottom) { seen[i] = 1; q.push(i); } + for (let h = 0; h < q.length; h++) { const v = q[h]; if (this.s.nodes[v].onTop) return true; for (const w of adj[v]) if (!seen[w]) { seen[w] = 1; q.push(w); } } + return false; +}; + +// ============================================================================ +// 40. Quasi-static, displacement-controlled fracture driver +// Loading: the top grip displacement d is increased in increments. For every +// topology state the response is linear, so the exact displacement at which the +// most utilised element reaches its limit is d_crit = 1 / max_e(omega_e(1)). +// With exactEvents the increment is cut back to d_crit (step-size independent); +// otherwise failures are processed at the end of the increment (overshoot). +// At an event the critical element(s) change state (intact -> damaged/failed), +// the system is re-assembled, re-factorised and re-solved at the SAME d; if the +// redistributed load overloads further elements they fail one at a time (most +// utilised first) until equilibrium with all omega_e < 1 (avalanche/cascade). +// ============================================================================ +function nowMs() { return (typeof performance !== 'undefined' && performance.now) ? performance.now() : Date.now(); } + +HFX.Simulation = function (structure, params) { + const p = this.p = Object.assign({}, structure.params, params || {}); + this.s = structure; + this.model = new HFX.BeamModel(structure, p); + const nEl = structure.elements.length; + this.nEl = nEl; + this.failDisp = new Float64Array(nEl).fill(-1); this.failOrder = new Int32Array(nEl).fill(-1); this.failStep = new Int32Array(nEl).fill(-1); + this.damageDisp = new Float64Array(nEl).fill(-1); + this.peakUtil = new Float64Array(nEl); + this.utilAtPeak = new Float64Array(nEl); this.NAtPeak = new Float64Array(nEl); this.utilInitial = new Float64Array(nEl); this.NInitial = new Float64Array(nEl); + this.steps = []; this.events = []; this.cascades = []; + this.d = 0; this.dGrid = 0; this.F = 0; this.Fpeak = 0; this.dPeak = 0; this.peakStep = 0; this.Wext = 0; this.dissipated = 0; + this.nFailed = 0; this.nDamaged = 0; this.nEvents = 0; this.done = false; this.status = 'ready'; + this.convergence = { residualExceeded: 0, iterationCapHits: 0, maxResidual: 0, nonPositivePivots: 0, maxForceBalance: 0, maxStabForceRatio: 0 }; + this.memberHistory = p.recordMemberHistory ? { disp: [], stepIndex: [], util: [] } : null; + this.stateRecords = p.recordStates ? [] : null; this.stateSkip = 1; this.stateCounter = 0; + this.firstFailureD = -1; this.separated = false; this.finalFailureD = -1; this.finalFailureStep = -1; this.Wf = -1; + this.startTime = nowMs(); this.elapsedMs = 0; this.initialized = false; this.K0 = 0; +}; +HFX.Simulation.prototype.init = function () { + const rb = this.model.rebuild(); this.checkRebuild(rb); + this.K0 = this.model.F1; this.K0residual = this.model.residual1; + this.utilInitial.set(this.model.util1); this.NInitial.set(this.model.N1); + this.model.solveAt(0); + this.recordStep(0, 0, '', 0, 0); + this.recordState(0); + this.initialized = true; + if (!this.model.isConnected()) { this.separated = true; this.finish('no-load-path'); } +}; +HFX.Simulation.prototype.checkRebuild = function (rb) { if (rb.nonPositivePivots) this.convergence.nonPositivePivots += rb.nonPositivePivots; }; +HFX.Simulation.prototype.checkSolve = function (react) { + const c = this.convergence; + if (react.residual > c.maxResidual) c.maxResidual = react.residual; + if (react.residualAbs > (c.maxResidualAbs || 0)) c.maxResidualAbs = react.residualAbs; + if (react.residual > this.p.tolerance) c.residualExceeded++; + if (react.forceBalance > c.maxForceBalance) c.maxForceBalance = react.forceBalance; + const sr = react.stabForce / Math.max(Math.abs(react.Ftop), this.Fpeak, 1e-300); if (sr > c.maxStabForceRatio) c.maxStabForceRatio = sr; + if (react.forceBalanceRaw > (c.maxForceBalanceRaw || 0)) c.maxForceBalanceRaw = react.forceBalanceRaw; +}; +HFX.Simulation.prototype.maxUtil = function () { const u = this.model.util, st = this.model.state; let w = 0, id = -1; for (let i = 0; i < this.nEl; i++) if (st[i] < 2 && u[i] > w) { w = u[i]; id = i; } return { w: w, id: id }; }; +HFX.Simulation.prototype.maxUtilUnit = function () { const u = this.model.util1, st = this.model.state; let w = 0; for (let i = 0; i < this.nEl; i++) if (st[i] < 2 && u[i] > w) w = u[i]; return w; }; +HFX.Simulation.prototype.criticalElements = function () { + const mu = this.maxUtil(); const tie = this.p.tieTolerance; + if (mu.w < 1 - Math.max(tie, 1e-12)) return []; + const u = this.model.util, st = this.model.state, out = []; + const thr = mu.w * (1 - tie); + for (let i = 0; i < this.nEl; i++) if (st[i] < 2 && u[i] >= thr) out.push(i); + return out; +}; +HFX.Simulation.prototype.recordStep = function (d, F, flag, cascade, iter) { + const m = this.model; + const prev = this.steps.length ? this.steps[this.steps.length - 1] : null; + if (prev) this.Wext += 0.5 * (prev.F + F) * (d - prev.d); + const mu = this.maxUtil(); + const st = { i: this.steps.length, d: d, F: F, U: 0.5 * F * d, W: this.Wext, Diss: this.dissipated, nFailed: this.nFailed, nDamaged: this.nDamaged, + maxUtil: mu.w, maxUtilId: mu.id, residual: m.residual, residualAbs: m.lastReact ? m.lastReact.residualAbs : 0, forceBalance: m.lastReact ? m.lastReact.forceBalance : 0, event: flag, cascade: cascade, iter: iter, + K: d > 0 ? F / d : this.K0, t: nowMs() - this.startTime }; + this.steps.push(st); + if (F > this.Fpeak) { this.Fpeak = F; this.dPeak = d; this.peakStep = st.i; this.utilAtPeak.set(m.util); this.NAtPeak.set(m.N); } + for (let i = 0; i < this.nEl; i++) if (m.util[i] > this.peakUtil[i]) this.peakUtil[i] = m.util[i]; + if (this.memberHistory && (flag !== '' || (st.i % Math.max(1, this.p.memberHistoryEvery)) === 0)) { this.memberHistory.disp.push(d); this.memberHistory.stepIndex.push(st.i); this.memberHistory.util.push(Float32Array.from(m.util)); } + return st; +}; +HFX.Simulation.prototype.recordState = function (dFrom) { + if (!this.stateRecords) return; + this.stateCounter++; + if (this.stateRecords.length >= this.p.maxStates) { // thin out: keep every second record (always keep the first) + const kept = this.stateRecords.filter(function (r, i) { return i === 0 || (i % 2 === 1); }); + this.stateRecords = kept; this.stateSkip *= 2; + } + if ((this.stateCounter - 1) % this.stateSkip !== 0 && this.stateRecords.length > 0) { this.stateRecords[this.stateRecords.length - 1].dTo = dFrom; return; } + const m = this.model; + if (this.stateRecords.length) this.stateRecords[this.stateRecords.length - 1].dTo = dFrom; + this.stateRecords.push({ index: this.cascades.length, dFrom: dFrom, dTo: Infinity, F1: m.F1, u1: Float32Array.from(m.u1), util1: Float32Array.from(m.util1), N1: Float32Array.from(m.N1), state: Int8Array.from(m.state), nFailed: this.nFailed }); +}; +HFX.Simulation.prototype.failElement = function (id, d, Fbefore) { + const m = this.model, e = this.s.elements[id], p = this.p, st = m.state[id]; + let type; + if (st === 0 && p.residualStiffness > 0 && p.ductilityRatio > 1) { m.state[id] = 1; this.nDamaged++; this.damageDisp[id] = d; type = 'damage'; } + else { m.state[id] = 2; if (st === 1) this.nDamaged--; this.failOrder[id] = this.nFailed; this.nFailed++; this.failDisp[id] = d; this.failStep[id] = this.steps.length - 1; type = 'rupture'; if (this.firstFailureD < 0) this.firstFailureD = d; } + this.events.push({ index: this.nEvents, d: d, elementId: id, level: e.level, kind: e.kind, isInterface: e.isInterface, type: type, util: m.util[id], N: m.N[id], F: m.F, Fcascade: Fbefore, x: e.cx, y: e.cy, step: this.steps.length - 1, cascade: this.cascades.length }); + this.nEvents++; +}; +/** One loading step (possibly containing a failure cascade). Returns false when finished. */ +HFX.Simulation.prototype.step = function () { + if (!this.initialized) this.init(); + if (this.done) return false; + const p = this.p, m = this.model; + const dTarget = Math.min(this.dGrid + p.dispIncrement, p.maxDisp); + let dNext = dTarget, eventNow = false; + if (p.exactEvents) { + const wmax1 = this.maxUtilUnit(); + if (wmax1 > 0) { const dCrit = 1 / wmax1; if (dCrit <= dTarget * (1 + 1e-12)) { dNext = Math.max(dCrit, this.d); eventNow = true; } } + } + let react = m.solveAt(dNext); this.checkSolve(react); + if (!p.exactEvents) eventNow = this.maxUtil().w >= 1; + this.recordStep(dNext, m.F, eventNow ? 'pre' : '', 0, 0); + if (eventNow) { + const Fbefore = m.F; let iter = 0, cascade = 0; + while (true) { + const crit = this.criticalElements(); + if (!crit.length) break; + if (iter >= p.maxIterations) { this.convergence.iterationCapHits++; break; } + for (const id of crit) this.failElement(id, dNext, Fbefore); + iter++; cascade += crit.length; + const rb = m.rebuild(); this.checkRebuild(rb); + react = m.solveAt(dNext); this.checkSolve(react); + if (this.nEvents >= p.maxEvents) break; + if (!m.isConnected()) { this.separated = true; break; } + } + const drop = Fbefore - m.F; this.dissipated += 0.5 * drop * dNext; + this.cascades.push({ index: this.cascades.length, d: dNext, Fbefore: Fbefore, Fafter: m.F, size: cascade, iterations: iter, drop: drop, dropFraction: drop / Math.max(this.Fpeak, 1e-300) }); + this.recordStep(dNext, m.F, 'post', cascade, iter); + this.recordState(dNext); + } + this.d = dNext; this.F = m.F; + if (dNext >= dTarget * (1 - 1e-12)) this.dGrid = dTarget; + if (this.separated) this.finish('completed'); + else if (this.nEvents > 0 && this.d > this.dPeak && this.F <= p.stopForceFraction * this.Fpeak) this.finish('completed'); + else if (this.d >= p.maxDisp * (1 - 1e-12)) this.finish('maxDisp'); + else if (this.nEvents >= p.maxEvents) this.finish('maxEvents'); + return !this.done; +}; +HFX.Simulation.prototype.advance = function (budgetMs) { + const t0 = nowMs(); + while (!this.done) { this.step(); if (budgetMs !== undefined && nowMs() - t0 > budgetMs) break; } + return !this.done; +}; +HFX.Simulation.prototype.run = function () { while (this.step()) { /* loop */ } return this; }; +HFX.Simulation.prototype.finish = function (status) { + this.done = true; this.status = status; this.elapsedMs = nowMs() - this.startTime; + const p = this.p, steps = this.steps; + // final failure: first step after the peak with F <= stopForceFraction * Fpeak (or separation) + this.finalFailureStep = -1; + for (let i = this.peakStep + 1; i < steps.length; i++) { if (steps[i].F <= p.stopForceFraction * this.Fpeak) { this.finalFailureStep = i; break; } } + if (this.finalFailureStep < 0 && this.separated) this.finalFailureStep = steps.length - 1; + if (this.finalFailureStep >= 0) { this.finalFailureD = steps[this.finalFailureStep].d; this.Wf = steps[this.finalFailureStep].W; } + else { this.finalFailureD = -1; this.Wf = this.Wext; } + const last = steps[steps.length - 1]; + this.energyBalanceError = Math.abs(this.Wext - (last.U + this.dissipated)) / Math.max(this.Wext, 1e-300); + this.converged = this.convergence.residualExceeded === 0 && this.convergence.iterationCapHits === 0 && this.convergence.nonPositivePivots === 0; +}; + +// ============================================================================ +// 50. Metrics, result bundles, CSV/JSON export helpers, hashing +// ============================================================================ +HFX.computeMetrics = function (sim) { + const s = sim.s, p = sim.p, W = s.W, H = s.H, els = s.elements, steps = sim.steps; + const rho = s.stats.relDensityActual; + const nActive = s.stats.activeElements; + const m = {}; + m.K0 = sim.K0; // initial stiffness F/d [E_s b_z] (normalised) + m.EeffRel = sim.K0 * H / (W * p.E); // effective modulus / solid modulus + m.EeffRelPerDensity = rho > 0 ? m.EeffRel / rho : NaN; + m.Fpeak = sim.Fpeak; m.dPeak = sim.dPeak; m.epsPeak = sim.dPeak / H; + m.sigmaPeakRel = sim.Fpeak / (W * p.E); // nominal peak stress / E_s + m.strengthRel = m.sigmaPeakRel / p.failStrain; // nominal peak stress / (E_s eps_c) = strength relative to solid strength + m.strengthRelPerDensity = rho > 0 ? m.strengthRel / rho : NaN; + m.dFirst = sim.firstFailureD; m.epsFirst = sim.firstFailureD >= 0 ? sim.firstFailureD / H : NaN; + m.dFinal = sim.finalFailureD; m.epsFinal = sim.finalFailureD >= 0 ? sim.finalFailureD / H : NaN; + m.finalFailureReached = sim.finalFailureStep >= 0; + m.Wf = sim.Wf; m.Wtotal = sim.Wext; + m.WfPerArea = sim.Wf / (W * H); // work to failure per specimen area [E_s b_z] (normalised toughness density) + m.WfPerMaterial = rho > 0 ? sim.Wf / (rho * W * H) : NaN; + m.WfRel = sim.Wf / (0.5 * p.E * p.failStrain * p.failStrain * rho * W * H); // relative to the elastic energy capacity of the same material volume loaded uniformly to eps_c + m.nFailed = sim.nFailed; m.nDamaged = sim.nDamaged; m.fractionFailed = nActive ? sim.nFailed / nActive : 0; + m.nEvents = sim.nEvents; m.nCascades = sim.cascades.length; + m.maxCascade = sim.cascades.reduce(function (a, c) { return Math.max(a, c.size); }, 0); + m.prePeakFailures = sim.events.filter(function (e) { return e.d < sim.dPeak * (1 - 1e-12); }).length; + m.prePeakFraction = sim.nEvents ? m.prePeakFailures / sim.nEvents : 0; + m.abruptness = sim.cascades.reduce(function (a, c) { return Math.max(a, c.drop); }, 0) / Math.max(sim.Fpeak, 1e-300); + // post-peak work fraction + const Wpeak = steps[sim.peakStep] ? steps[sim.peakStep].W : 0; + m.postPeakWorkFraction = sim.Wf > 0 ? Math.max(0, (sim.Wf - Wpeak) / sim.Wf) : 0; + // damage localisation: participation ratio of failed-element positions along the loading axis (y) + const failed = []; for (let i = 0; i < els.length; i++) if (sim.failDisp[i] >= 0) failed.push(i); + const leafScale = s.stats.leafScale; + const nBins = Math.max(4, Math.round(H / leafScale)); + if (failed.length) { + const hist = new Float64Array(nBins); let sy = 0, sy2 = 0; + for (const i of failed) { const y = els[i].cy; let bI = Math.floor(y / H * nBins); if (bI >= nBins) bI = nBins - 1; if (bI < 0) bI = 0; hist[bI]++; sy += y; sy2 += y * y; } + let s1 = 0, s2 = 0; for (let bI = 0; bI < nBins; bI++) { s1 += hist[bI]; s2 += hist[bI] * hist[bI]; } + m.participationRatio = (s1 * s1) / (nBins * s2); + m.localizationIndex = 1 - m.participationRatio; + const meanY = sy / failed.length; m.damageBandStd = Math.sqrt(Math.max(0, sy2 / failed.length - meanY * meanY)) / H; m.damageBandCentre = meanY / H; + m.localizationBins = nBins; + } else { m.participationRatio = NaN; m.localizationIndex = NaN; m.damageBandStd = NaN; m.damageBandCentre = NaN; m.localizationBins = nBins; } + // failure composition + const perLevel = []; for (let k = 0; k <= s.depth; k++) perLevel.push(0); + let ifFail = 0, braceFail = 0; + for (const i of failed) { perLevel[els[i].level]++; if (els[i].isInterface) ifFail++; if (els[i].kind === 'brace') braceFail++; } + m.failedPerLevel = perLevel; m.interfaceFailures = ifFail; m.braceFailures = braceFail; + m.interfaceFailureFraction = failed.length ? ifFail / failed.length : 0; + m.interfaceFailureShare = s.stats.interfaces ? ifFail / s.stats.interfaces : 0; + m.meanFailLevel = failed.length ? failed.reduce(function (a, i) { return a + els[i].level; }, 0) / failed.length : NaN; + // first-failure level and location + if (sim.events.length) { const e0 = sim.events[0]; m.firstFailLevel = e0.level; m.firstFailInterface = e0.isInterface; m.firstFailX = e0.x / W; m.firstFailY = e0.y / H; } + // classification of the fracture mode + let mode; + if (sim.nEvents === 0) mode = 'no-failure'; + else if (m.abruptness >= 0.6) mode = 'abrupt-brittle'; + else if (m.abruptness <= 0.25) mode = 'progressive'; + else mode = 'intermediate'; + let loc = failed.length >= 10 ? (m.localizationIndex >= 0.6 ? 'localized' : 'distributed') : 'few-failures'; + m.fractureMode = mode; m.damagePattern = loc; m.fractureLabel = mode + '/' + loc; + // numerical diagnostics + m.maxResidual = sim.convergence.maxResidual; m.maxResidualAbs = sim.convergence.maxResidualAbs || 0; m.residualExceeded = sim.convergence.residualExceeded; m.iterationCapHits = sim.convergence.iterationCapHits; + m.nonPositivePivots = sim.convergence.nonPositivePivots; m.maxForceBalance = sim.convergence.maxForceBalance; m.maxStabForceRatio = sim.convergence.maxStabForceRatio; + m.energyBalanceError = sim.energyBalanceError; m.converged = !!sim.converged; m.status = sim.status; + m.steps = steps.length; m.rebuilds = sim.model.rebuildCount; m.solves = sim.model.solveCount; m.elapsedMs = sim.elapsedMs; m.factorTimeMs = sim.model.factorTimeMs; + m.nFree = sim.model.nFree; m.maxBandwidth = sim.model.lastRebuild ? sim.model.lastRebuild.maxBandwidth : 0; + return m; +}; + +HFX.METRIC_DOC = { + K0: 'initial stiffness dF/dd of the undamaged structure [E_s b_z]', EeffRel: 'effective tensile modulus / solid modulus', Fpeak: 'peak reaction force [E_s W b_z]', + sigmaPeakRel: 'nominal peak stress F_peak/(W b_z) divided by E_s', strengthRel: 'nominal peak stress / (E_s eps_c)', dFirst: 'displacement at first failure event', + dPeak: 'displacement at peak force', dFinal: 'displacement at final failure (force < stopForceFraction * F_peak or separation)', Wf: 'work to final failure [E_s W^2 b_z]', + WfPerArea: 'work to failure per specimen area W*H', WfPerMaterial: 'work to failure per unit material area', WfRel: 'work to failure relative to 1/2 E eps_c^2 x material area', + abruptness: 'largest single-cascade force drop / F_peak (1 = fully abrupt)', localizationIndex: '1 - participation ratio of failed-element positions along y (1 = single band)', + prePeakFailures: 'number of failure events before the peak force', fractionFailed: 'failed elements / active elements', interfaceFailureFraction: 'share of failures that are interface elements', + energyBalanceError: '|W_ext - (U + dissipated)| / W_ext', maxResidual: 'max relative equilibrium residual over all solves' +}; + +// ---------------------------------------------------------------------------- export helpers +function fmt(v) { if (typeof v === 'number') { if (!isFinite(v)) return String(v); return Number(v.toPrecision(12)).toString(); } return String(v); } +HFX.fmt = fmt; +HFX.stepsCSV = function (sim) { + const rows = ['step,d,F,U,W,Diss,nFailed,nDamaged,maxUtil,maxUtilId,residual,residualAbs,forceBalance,event,cascade,iter,K,time_ms']; + for (const s of sim.steps) rows.push([s.i, fmt(s.d), fmt(s.F), fmt(s.U), fmt(s.W), fmt(s.Diss), s.nFailed, s.nDamaged, fmt(s.maxUtil), s.maxUtilId, fmt(s.residual), fmt(s.residualAbs), fmt(s.forceBalance), s.event, s.cascade, s.iter, fmt(s.K), fmt(s.t)].join(',')); + return rows.join('\n'); +}; +HFX.eventsCSV = function (sim) { + const rows = ['event,d,elementId,level,kind,isInterface,type,util,N,F_before_subevent,F_before_cascade,x,y,step,cascade']; + for (const e of sim.events) rows.push([e.index, fmt(e.d), e.elementId, e.level, e.kind, e.isInterface ? 1 : 0, e.type, fmt(e.util), fmt(e.N), fmt(e.F), fmt(e.Fcascade), fmt(e.x), fmt(e.y), e.step, e.cascade].join(',')); + return rows.join('\n'); +}; +HFX.membersCSV = function (sim) { + const s = sim.s, nodes = s.nodes; + const rows = ['id,n1,n2,x1,y1,x2,y2,level,kind,isInterface,L,t,epsC,xi,absent,state,damageDisp,failDisp,failOrder,peakUtil,utilInitial_perUnitDisp,NInitial_perUnitDisp,utilAtPeakLoad,NAtPeakLoad']; + for (let i = 0; i < s.elements.length; i++) { + const e = s.elements[i], A = nodes[e.n1], B = nodes[e.n2]; + rows.push([e.id, e.n1, e.n2, fmt(A.x), fmt(A.y), fmt(B.x), fmt(B.y), e.level, e.kind, e.isInterface ? 1 : 0, fmt(e.L), fmt(e.t), fmt(e.epsC), fmt(e.xi), e.absent ? 1 : 0, sim.model.state[i], + fmt(sim.damageDisp[i]), fmt(sim.failDisp[i]), sim.failOrder[i], fmt(sim.peakUtil[i]), fmt(sim.utilInitial[i]), fmt(sim.NInitial[i]), fmt(sim.utilAtPeak[i]), fmt(sim.NAtPeak[i])].join(',')); + } + return rows.join('\n'); +}; +HFX.memberHistoryCSV = function (sim) { + if (!sim.memberHistory) return ''; + const mh = sim.memberHistory; const rows = ['step,d,' + Array.from({ length: sim.nEl }, function (_, i) { return 'u' + i; }).join(',')]; + for (let r = 0; r < mh.disp.length; r++) { const u = mh.util[r]; const arr = new Array(u.length); for (let i = 0; i < u.length; i++) arr[i] = Number(u[i].toPrecision(6)); rows.push(mh.stepIndex[r] + ',' + fmt(mh.disp[r]) + ',' + arr.join(',')); } + return rows.join('\n'); +}; +HFX.geometryJSON = function (structure) { + return { + W: structure.W, H: structure.H, depth: structure.depth, branching: structure.branching, params: structure.params, stats: structure.stats, levelStats: structure.levelStats, + nodes: structure.nodes.map(function (n) { return [Number(n.x.toPrecision(12)), Number(n.y.toPrecision(12)), n.level === Infinity ? -1 : n.level, n.onBottom ? 1 : 0, n.onTop ? 1 : 0]; }), + elements: structure.elements.map(function (e) { return { id: e.id, n1: e.n1, n2: e.n2, level: e.level, kind: e.kind, iface: e.isInterface ? 1 : 0, L: Number(e.L.toPrecision(10)), t: Number(e.t.toPrecision(10)), epsC: Number(e.epsC.toPrecision(10)), absent: e.absent ? 1 : 0 }; }), + leafCells: structure.leafCells.map(function (c) { return c.map(function (q) { return [Number(q[0].toPrecision(10)), Number(q[1].toPrecision(10))]; }); }) + }; +}; +/** Full result bundle (JSON-serialisable). */ +HFX.resultsBundle = function (sim, extra) { + const metrics = HFX.computeMetrics(sim); + const s = sim.s; + const bundle = { + meta: Object.assign({ core: HFX.NAME, coreVersion: HFX.VERSION, created: new Date().toISOString(), units: 'normalised: length W=1, modulus E_s=1, depth b_z=1; force in E_s*W*b_z; energy in E_s*W^2*b_z' }, extra || {}), + params: sim.p, structureStats: s.stats, levelStats: s.levelStats, warnings: s.warnings, metrics: metrics, + steps: sim.steps, events: sim.events, cascades: sim.cascades, + members: s.elements.map(function (e, i) { return { id: e.id, level: e.level, kind: e.kind, iface: e.isInterface ? 1 : 0, L: e.L, t: e.t, epsC: e.epsC, absent: e.absent ? 1 : 0, state: sim.model.state[i], failDisp: sim.failDisp[i], failOrder: sim.failOrder[i], peakUtil: sim.peakUtil[i], utilAtPeak: sim.utilAtPeak[i] }; }), + diagnostics: { convergence: sim.convergence, energyBalanceError: sim.energyBalanceError, converged: sim.converged, status: sim.status, rebuilds: sim.model.rebuildCount, solves: sim.model.solveCount, lastRebuild: sim.model.lastRebuild, elapsedMs: sim.elapsedMs } + }; + return bundle; +}; +/** FNV-1a hash of the response (steps + events) for reproducibility checks. */ +HFX.hashResults = function (sim) { + let h = 0x811c9dc5; + const feed = function (str) { for (let i = 0; i < str.length; i++) { h ^= str.charCodeAt(i); h = Math.imul(h, 0x01000193) >>> 0; } }; + for (const s of sim.steps) feed(s.d.toPrecision(12) + ':' + s.F.toPrecision(12) + ';'); + for (const e of sim.events) feed(e.elementId + '@' + e.d.toPrecision(12) + ';'); + return ('00000000' + h.toString(16)).slice(-8); +}; +/** Convenience: generate + simulate + metrics. */ +HFX.runExperiment = function (params, opts) { + opts = opts || {}; + const t0 = nowMs(); + const structure = HFX.generateStructure(params); + const tGen = nowMs() - t0; + const sim = new HFX.Simulation(structure, params); + sim.run(); + const metrics = HFX.computeMetrics(sim); + return { structure: structure, sim: sim, metrics: metrics, hash: HFX.hashResults(sim), timing: { generateMs: tGen, simulateMs: sim.elapsedMs } }; +}; +/** Physical-unit conversion of the key metrics (display/export only). */ +HFX.toPhysical = function (metrics, phys, structure) { + const E = phys.E_MPa, Wmm = phys.W_mm, bmm = phys.depth_mm; // MPa, mm, mm + const Fscale = E * Wmm * bmm; // N (E [MPa=N/mm^2] * W [mm] * b [mm]) for normalised force in E_s W b_z + const dscale = Wmm; // mm per normalised length unit (W = 1) + return { + E_MPa: E, W_mm: Wmm, H_mm: structure.H * Wmm, depth_mm: bmm, t0_mm: structure.t0 * Wmm, tMin_mm: structure.stats.tMin * Wmm, + K0_N_per_mm: metrics.K0 * Fscale / dscale, Fpeak_N: metrics.Fpeak * Fscale, dPeak_mm: metrics.dPeak * dscale, dFirst_mm: metrics.dFirst * dscale, dFinal_mm: metrics.dFinal * dscale, + Wf_mJ: metrics.Wf * Fscale * dscale, sigmaPeak_MPa: metrics.sigmaPeakRel * E, Eeff_MPa: metrics.EeffRel * E + }; +}; + +// ============================================================================ +// 60. Validation suite (analytical references, invariances, conservation checks) +// ============================================================================ +/** Build a structure from explicit nodes [[x,y],...] and elements [[n1,n2,level,thickness],...] (unit material). */ +HFX.structureFromLines = function (nodesXY, elems, paramsIn) { + const p = Object.assign(HFX.defaultParams(), paramsIn || {}); + const W = p.W, H = p.H, tolBC = 1e-9; + const nodes = nodesXY.map(function (q) { return { x: q[0], y: q[1], level: 0, onBottom: Math.abs(q[1]) < tolBC, onTop: Math.abs(q[1] - H) < tolBC, onLeft: q[0] === 0, onRight: q[0] === W }; }); + const elements = elems.map(function (e, i) { + const A = nodes[e[0]], B = nodes[e[1]]; const t = e[3]; + return { id: i, n1: e[0], n2: e[1], level: e[2] || 0, kind: 'wall', isInterface: false, L: Math.hypot(B.x - A.x, B.y - A.y), cx: 0.5 * (A.x + B.x), cy: 0.5 * (A.y + B.y), absent: false, strengthFactor: 1, t: t, A: t, I: p.bendingFactor * t * t * t / 12, Emod: p.E, epsC: p.failStrain, xi: 1 }; + }); + let mat = 0; for (const e of elements) mat += e.L * e.t; + return { params: p, W: W, H: H, depth: 0, branching: 0, nodes: nodes, elements: elements, leafCells: [], cellsByLevel: [[]], t0: elements[0].t, levelStats: [{ level: 0, count: elements.length, thickness: elements[0].t }], warnings: [], + stats: { nodes: nodes.length, activeNodes: nodes.length, elements: elements.length, activeElements: elements.length, leafCells: 1, relDensityDesign: mat / (W * H), relDensityActual: mat / (W * H), t0: elements[0].t, tMin: elements[0].t, tMax: elements[0].t, meanCoordination: 2 * elements.length / nodes.length, interfaces: 0, leafScale: Math.sqrt(W * H), gripNodesTop: nodes.filter(function (n) { return n.onTop; }).length, gripNodesBottom: nodes.filter(function (n) { return n.onBottom; }).length } }; +}; +function relErr(obs, exp) { return Math.abs(obs - exp) / Math.max(Math.abs(exp), 1e-300); } +function mkResult(id, name, expected, observed, tol, details, absolute) { + const err = absolute ? Math.abs(observed - expected) : relErr(observed, expected); + return { id: id, name: name, expected: expected, observed: observed, error: err, tol: tol, pass: err <= tol, details: details || '', absolute: !!absolute }; +} +HFX.mkResult = mkResult; +/** Run the validation suite. Returns {results:[...], allPass, essentialPass, elapsedMs}. `log` optional callback. */ +HFX.runValidation = function (log, options) { + options = options || {}; + const t0 = nowMs(); const R = []; const say = function (s) { if (log) log(s); }; + const baseP = HFX.defaultParams(); + const study = Object.assign({}, baseP, { n0x: 1, n0y: 1, depth: 3, branching: 4, disorder: 0.35, seed: 7, thicknessRatio: 0.6, relDensity: 0.2, strengthCV: 0.08, interfaceStrengthRatio: 0.8, dispIncrement: 0.001, maxDisp: 0.1 }); + try { + // ---- T1 single axial member + { + const t = 0.05, L = 1.0; + const st = HFX.structureFromLines([[0.5, 0], [0.5, L]], [[0, 1, 0, t]], { H: L, E: 1, failStrain: 0.02, dispIncrement: 0.001, maxDisp: 0.01 }); + const sim = new HFX.Simulation(st, {}); sim.run(); + const Kexp = 1 * t / L; + R.push(mkResult('T1', 'Single axial member stiffness vs EA/L', Kexp, sim.K0, 1e-12, 'E=1, A=t=0.05, L=1 (clamped grips); F/d compared with EA/L; ' + sim.steps.length + ' steps, max residual ' + sim.convergence.maxResidual.toExponential(2))); + const s5 = sim.steps[5]; + R.push(mkResult('T1b', 'Single member: linear response F(d) = (EA/L) d at step 5', Kexp * s5.d, s5.F, 1e-12)); + } + // ---- T2 inclined clamped-clamped / clamped-pinned beam: axial + bending (exact Euler–Bernoulli) + { + const t = 0.05, W = 1, H = 1; const L = Math.SQRT2, sa = H / L, ca = W / L, EA = t, EI = t * t * t / 12; + const st = HFX.structureFromLines([[0, 0], [W, H]], [[0, 1, 0, t]], { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005, gripType: 'clamped' }); + const sim = new HFX.Simulation(st, {}); sim.run(); + const Kexp = EA / L * sa * sa + 12 * EI / (L * L * L) * ca * ca; + R.push(mkResult('T2', 'Inclined beam, clamped ends: K = EA/L sin^2 + 12EI/L^3 cos^2', Kexp, sim.K0, 1e-10, 'bending stiffness term verified (45 deg beam, tip rotation fixed)')); + // clamped base, tip free to rotate (guided cantilever): transverse stiffness 3EI/L^3 + const st2 = HFX.structureFromLines([[0, 0], [W, H]], [[0, 1, 0, t]], { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005 }); + st2.nodes[0].bc = { u: 1, v: 1, th: 1 }; st2.nodes[1].bc = { u: 1, v: 1, th: 0, vValue: 1 }; + const sim2 = new HFX.Simulation(st2, {}); sim2.run(); + const Kexp2 = EA / L * sa * sa + 3 * EI / (L * L * L) * ca * ca; + R.push(mkResult('T2b', 'Inclined beam, clamped base / tip rotation free: K = EA/L sin^2 + 3EI/L^3 cos^2', Kexp2, sim2.K0, 1e-10, 'guided-cantilever bending term 3EI/L^3 verified')); + // mesh refinement: 4 elements along the beam must give the identical answer (EB element exact for nodal loads) + const nn = [[0, 0], [0.25, 0.25], [0.5, 0.5], [0.75, 0.75], [1, 1]]; const ee = [[0, 1, 0, t], [1, 2, 0, t], [2, 3, 0, t], [3, 4, 0, t]]; + const st3 = HFX.structureFromLines(nn, ee, { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005 }); + st3.nodes[0].bc = { u: 1, v: 1, th: 1 }; st3.nodes[4].bc = { u: 1, v: 1, th: 0, vValue: 1 }; + const sim3 = new HFX.Simulation(st3, {}); sim3.run(); + R.push(mkResult('T2c', 'Inclined beam, 4-element mesh identical to 1 element', Kexp2, sim3.K0, 1e-9, 'Euler–Bernoulli element is exact for nodal loading')); + // pinned-pinned inclined bar: rigid rotation carries the transverse component, only the axial term remains + const st4 = HFX.structureFromLines([[0, 0], [W, H]], [[0, 1, 0, t]], { W: W, H: H, E: 1, failStrain: 1, dispIncrement: 0.001, maxDisp: 0.005, gripType: 'pinned' }); + const sim4 = new HFX.Simulation(st4, {}); sim4.run(); + R.push(mkResult('T2d', 'Inclined bar, both ends pinned: K = EA/L sin^2 (no bending transmitted)', EA / L * sa * sa, sim4.K0, 1e-8, 'rotation-free ends: transverse motion is a rigid rotation, stabilisation-limited accuracy')); + } + // ---- T3 reproducibility + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(study); + R.push(mkResult('T3', 'Reproducibility: identical parameters and seed give identical results (hash)', 1, a.hash === b.hash ? 1 : 0, 0, 'hash ' + a.hash + ' vs ' + b.hash + '; Wf ' + a.metrics.Wf + ' vs ' + b.metrics.Wf + '; ' + a.metrics.nFailed + ' failures', true)); + R.push(mkResult('T3b', 'Reproducibility: work to failure bitwise equal', a.metrics.Wf, b.metrics.Wf, 0)); + const c = HFX.runExperiment(Object.assign({}, study, { seed: 8 })); + R.push(mkResult('T3c', 'Different seed changes the result (hash differs)', 1, a.hash !== c.hash ? 1 : 0, 0, 'seed 7 hash ' + a.hash + ', seed 8 hash ' + c.hash, true)); + } + // ---- T4 stiffness scaling + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { E: 2.0 })); + R.push(mkResult('T4', 'Doubling E doubles the initial stiffness', 2 * a.metrics.K0, b.metrics.K0, 1e-10)); + R.push(mkResult('T4b', 'Doubling E (fixed eps_c) leaves first-failure displacement unchanged', a.metrics.dFirst, b.metrics.dFirst, 1e-9, 'failure criterion is strain based: d_first independent of E')); + R.push(mkResult('T4c', 'Doubling E doubles the peak force', 2 * a.metrics.Fpeak, b.metrics.Fpeak, 1e-9)); + const seqA = a.sim.events.map(function (e) { return e.elementId; }).join(','), seqB = b.sim.events.map(function (e) { return e.elementId; }).join(','); + R.push(mkResult('T4d', 'Doubling E leaves the failure sequence unchanged', 1, seqA === seqB ? 1 : 0, 0, a.sim.events.length + ' events', true)); + } + // ---- T5 strength scaling + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { failStrain: 2 * study.failStrain })); + R.push(mkResult('T5', 'Doubling strength leaves the initial stiffness unchanged', a.metrics.K0, b.metrics.K0, 0, 'bitwise equal expected')); + R.push(mkResult('T5b', 'Doubling strength doubles the first-failure displacement', 2 * a.metrics.dFirst, b.metrics.dFirst, 1e-9)); + R.push(mkResult('T5c', 'Doubling strength doubles the peak force', 2 * a.metrics.Fpeak, b.metrics.Fpeak, 1e-9)); + R.push(mkResult('T5d', 'Doubling strength quadruples the work to failure', 4 * a.metrics.Wf, b.metrics.Wf, 1e-8, 'linear-elastic brittle model: energy scales with strength^2')); + const seqA = a.sim.events.map(function (e) { return e.elementId; }).join(','), seqB = b.sim.events.map(function (e) { return e.elementId; }).join(','); + R.push(mkResult('T5e', 'Doubling strength leaves the failure sequence unchanged', 1, seqA === seqB ? 1 : 0, 0, a.sim.events.length + ' events', true)); + } + // ---- T6 symmetry + { + const sp = Object.assign({}, baseP, { n0x: 1, n0y: 1, depth: 3, branching: 4, disorder: 0, strengthCV: 0, redundancy: 1, thicknessRatio: 0.6, relDensity: 0.2, dispIncrement: 0.002, maxDisp: 0.004, exactEvents: true, failStrain: 1 }); + const st = HFX.generateStructure(sp); const sim = new HFX.Simulation(st, {}); sim.run(); + const u = sim.model.u; const nodes = st.nodes; const W = st.W; + const idx = new Map(); nodes.forEach(function (n, i) { idx.set(n.x.toFixed(9) + ',' + n.y.toFixed(9), i); }); + let maxErr = 0, vmax = 0, paired = 0; + nodes.forEach(function (n, i) { + const j = idx.get((W - n.x).toFixed(9) + ',' + n.y.toFixed(9)); if (j === undefined) return; paired++; + const eu = Math.abs(u[3 * i] + u[3 * j]), ev = Math.abs(u[3 * i + 1] - u[3 * j + 1]), et = Math.abs(u[3 * i + 2] + u[3 * j + 2]); + maxErr = Math.max(maxErr, eu, ev, et); vmax = Math.max(vmax, Math.abs(u[3 * i + 1])); + }); + R.push(mkResult('T6', 'Mirror symmetry of the displacement field (ordered braced specimen)', 0, maxErr / Math.max(vmax, 1e-300), 1e-9, paired + ' of ' + nodes.length + ' nodes paired; |u(x)+u(W-x)|, |v(x)-v(W-x)|, |th(x)+th(W-x)| relative to max|v|', true)); + } + // ---- T7 force balance and residual over a full fracture run + { + const a = HFX.runExperiment(study); + R.push(mkResult('T7', 'Force balance |F_top + F_bottom - F_stab| / |F_top| over all steps', 0, a.sim.convergence.maxForceBalance, 1e-9, a.sim.steps.length + ' steps; raw |F_top+F_bottom|/|F_top| = ' + (a.sim.convergence.maxForceBalanceRaw || 0).toExponential(2) + ' (difference = stabilisation forces)', true)); + R.push(mkResult('T7b', 'Equilibrium residual ||K u - f||_free / ||reactions|| (max over all solves)', 0, a.sim.convergence.maxResidual, study.tolerance, 'tolerance = params.tolerance; ' + a.sim.model.solveCount + ' solves, ' + a.sim.model.rebuildCount + ' refactorisations', true)); + R.push(mkResult('T7c', 'Stabilisation force / peak reaction force (max over run)', 0, a.sim.convergence.maxStabForceRatio, 1e-6, 'ground-spring stabilisation must be negligible', true)); + R.push(mkResult('T8', 'Energy balance |W_ext - (U + dissipated)| / W_ext', 0, a.sim.energyBalanceError, 1e-9, 'external work vs stored + released energy', true)); + R.push(mkResult('T8b', 'Solver converged (no residual/iteration/pivot flags)', 1, a.sim.converged ? 1 : 0, 0, JSON.stringify(a.sim.convergence), true)); + } + // ---- T9 load-step sensitivity + { + const a = HFX.runExperiment(Object.assign({}, study, { dispIncrement: 0.002 })); + const b = HFX.runExperiment(Object.assign({}, study, { dispIncrement: 0.001 })); + const c = HFX.runExperiment(Object.assign({}, study, { dispIncrement: 0.0005 })); + R.push(mkResult('T9', 'Exact event tracking: peak force independent of step size (dd, dd/2, dd/4)', a.metrics.Fpeak, c.metrics.Fpeak, 1e-9, 'F_peak: ' + [a, b, c].map(function (r) { return r.metrics.Fpeak.toPrecision(10); }).join(', '))); + R.push(mkResult('T9b', 'Exact event tracking: work to failure independent of step size', a.metrics.Wf, c.metrics.Wf, 1e-9, 'W_f: ' + [a, b, c].map(function (r) { return r.metrics.Wf.toPrecision(10); }).join(', '))); + const na = HFX.runExperiment(Object.assign({}, study, { exactEvents: false, dispIncrement: 0.002 })); + const nb = HFX.runExperiment(Object.assign({}, study, { exactEvents: false, dispIncrement: 0.0005 })); + const ea = relErr(na.metrics.Fpeak, a.metrics.Fpeak), eb = relErr(nb.metrics.Fpeak, a.metrics.Fpeak); + R.push(mkResult('T9c', 'Without event tracking the peak-force error decreases with step size', 0, eb, Math.max(ea, 1e-12), 'error(dd=0.002) = ' + ea.toExponential(3) + ', error(dd=0.0005) = ' + eb.toExponential(3) + ' relative to the exact-event result', true)); + } + // ---- T10 export consistency + { + const a = HFX.runExperiment(study); const bundle = HFX.resultsBundle(a.sim); + const csv = HFX.stepsCSV(a.sim).split('\n').slice(1).map(function (l) { return l.split(','); }); + let Fmax = 0, Wfinal = 0; for (const r of csv) { const F = parseFloat(r[2]); if (F > Fmax) Fmax = F; } + const fi = a.sim.finalFailureStep >= 0 ? a.sim.finalFailureStep : csv.length - 1; Wfinal = parseFloat(csv[fi][4]); + R.push(mkResult('T10', 'Exported CSV peak force equals displayed metric', bundle.metrics.Fpeak, Fmax, 1e-11)); + R.push(mkResult('T10b', 'Exported CSV work at final failure equals displayed metric', bundle.metrics.Wf, Wfinal, 1e-11)); + const json = JSON.parse(JSON.stringify(bundle)); + R.push(mkResult('T10c', 'JSON bundle round-trip preserves metrics', bundle.metrics.Wf, json.metrics.Wf, 0)); + } + // ---- T11 density control + { + const cfgs = [{ disorder: 0, depth: 3 }, { disorder: 0.5, depth: 4, branching: 3, seed: 3 }, { disorder: 1, depth: 2, branching: 6, layout: 'radial', redundancy: 0.5 }]; + let maxErr = 0; const details = []; + for (const c of cfgs) { const st = HFX.generateStructure(Object.assign({}, baseP, { relDensity: 0.17 }, c)); const e = relErr(st.stats.relDensityDesign, 0.17); maxErr = Math.max(maxErr, e); details.push(st.stats.elements + ' elements, rho=' + st.stats.relDensityDesign.toPrecision(8)); } + R.push(mkResult('T11', 'Relative density is exactly controlled for ordered/disordered/radial designs', 0, maxErr, 1e-12, details.join('; '), true)); + } + // ---- T12 topology equivalence: nested ordered subdivision equals a flat grid + { + const pa = Object.assign({}, baseP, { n0x: 1, n0y: 1, depth: 3, branching: 4, disorder: 0, thicknessRatio: 1, interfaceMode: 'none', strengthCV: 0, relDensity: 0.2, dispIncrement: 0.002, maxDisp: 0.1 }); + const pb = Object.assign({}, pa, { n0x: 8, n0y: 8, depth: 0 }); + const a = HFX.runExperiment(pa), b = HFX.runExperiment(pb); + R.push(mkResult('T12', 'Nested subdivision (1x1, b=4, D=3) has the same node count as the flat 8x8 grid', a.structure.stats.nodes, b.structure.stats.nodes, 0, 'elements: ' + a.structure.stats.elements + ' vs ' + b.structure.stats.elements, true)); + R.push(mkResult('T12b', 'Nested vs flat grid: identical initial stiffness (uniform thickness)', b.metrics.K0, a.metrics.K0, 1e-10)); + R.push(mkResult('T12c', 'Nested vs flat grid: identical peak force', b.metrics.Fpeak, a.metrics.Fpeak, 1e-9)); + R.push(mkResult('T12d', 'Nested vs flat grid: identical work to failure', b.metrics.Wf, a.metrics.Wf, 1e-8)); + } + // ---- T13 analytical lattice stiffness, first failure and simultaneous rupture + { + const pl = Object.assign({}, baseP, { n0x: 4, n0y: 4, depth: 0, disorder: 0, strengthCV: 0, relDensity: 0.2, interfaceMode: 'none', dispIncrement: 0.002, maxDisp: 0.1, failStrain: 0.02 }); + const a = HFX.runExperiment(pl); const st = a.structure; + const t = st.t0; const nLines = 5; const Kexp = nLines * pl.E * t / st.H; + R.push(mkResult('T13', 'Ordered 4x4 grid, clamped grips: K0 = N_lines E t / H', Kexp, a.metrics.K0, 1e-10, 't0 = ' + t.toPrecision(8) + ' from rho=0.2 (total wall length 10)')); + R.push(mkResult('T13b', 'Ordered grid: first failure at d = eps_c H (uniform strain)', pl.failStrain * st.H, a.metrics.dFirst, 1e-9)); + R.push(mkResult('T13c', 'Ordered grid: peak force = K0 eps_c H', Kexp * pl.failStrain * st.H, a.metrics.Fpeak, 1e-9)); + R.push(mkResult('T13d', 'Ordered grid: all 20 vertical elements rupture in one tie-event (abrupt separation)', 20, a.sim.cascades.length ? a.sim.cascades[0].size : 0, 0, 'cascade sizes: ' + a.sim.cascades.map(function (c) { return c.size; }).join(','), true)); + R.push(mkResult('T13e', 'Ordered grid: work to failure = 1/2 K0 (eps_c H)^2', 0.5 * Kexp * Math.pow(pl.failStrain * st.H, 2), a.metrics.Wf, 1e-9)); + } + // ---- T14 stabilisation sensitivity + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { stabilization: 1e-10 })); + R.push(mkResult('T14', 'Stabilisation spring 100x larger changes K0 by < 1e-6', a.metrics.K0, b.metrics.K0, 1e-6)); + R.push(mkResult('T14b', 'Stabilisation spring 100x larger changes F_peak by < 1e-5', a.metrics.Fpeak, b.metrics.Fpeak, 1e-5)); + } + // ---- T15 interface strength only affects failure, not stiffness + { + const a = HFX.runExperiment(study), b = HFX.runExperiment(Object.assign({}, study, { interfaceStrengthRatio: 0.4 })); + R.push(mkResult('T15', 'Changing interface strength leaves the initial stiffness unchanged', a.metrics.K0, b.metrics.K0, 0)); + R.push(mkResult('T15b', 'Weaker interfaces fail earlier (first failure displacement decreases or is equal)', 1, b.metrics.dFirst <= a.metrics.dFirst + 1e-12 ? 1 : 0, 0, 'd_first ' + a.metrics.dFirst.toPrecision(6) + ' -> ' + b.metrics.dFirst.toPrecision(6) + '; interface failures ' + a.metrics.interfaceFailures + ' -> ' + b.metrics.interfaceFailures, true)); + } + } catch (err) { + R.push({ id: 'ERR', name: 'Validation suite threw an exception', expected: 'no exception', observed: String(err && err.stack || err), error: NaN, tol: 0, pass: false, details: '' }); + } + const essential = ['T1', 'T2', 'T2b', 'T3', 'T4', 'T5', 'T6', 'T7', 'T7b', 'T8', 'T9', 'T9b', 'T10', 'T11', 'T12b', 'T13', 'T13b']; + const allPass = R.every(function (r) { return r.pass; }); + const essentialPass = R.filter(function (r) { return essential.indexOf(r.id) >= 0; }).every(function (r) { return r.pass; }) && R.some(function (r) { return r.id === 'T1'; }); + return { results: R, allPass: allPass, essentialPass: essentialPass, elapsedMs: nowMs() - t0, coreVersion: HFX.VERSION }; +}; + +// ============================================================================ +// 70. Geometry export (binary STL, extruded plate) and SVG rendering +// ============================================================================ +/** + * Binary STL of the undeformed design extruded to a plate. + * opts: { scale_mm (length of W in mm), depth_mm, minWidth_mm, widthFactor, gripTab_mm, includeAbsent, includeFailed, state (Int8Array), jointFill } + * Overlapping closed shells (one box per member, one prism per joint, tabs) — sliced as a union by common slicers. + */ +HFX.exportSTL = function (structure, opts) { + opts = Object.assign({ scale_mm: 100, depth_mm: 4, minWidth_mm: 0, widthFactor: 1, gripTab_mm: 0, includeAbsent: false, includeFailed: true, state: null, jointFill: true, jointSides: 8 }, opts || {}); + const S = opts.scale_mm, Z = opts.depth_mm; const tris = []; // each: [nx,ny,nz, x1,y1,z1, x2,y2,z2, x3,y3,z3] + const nodes = structure.nodes, els = structure.elements; + const widthOf = function (e) { return Math.max(e.t * S * opts.widthFactor, opts.minWidth_mm); }; + const addQuad = function (a, b, c, d, n) { tris.push([n, a, b, c]); tris.push([n, a, c, d]); }; + const addBox = function (x1, y1, x2, y2, w) { // rectangle around the segment (x1,y1)-(x2,y2), width w, extruded 0..Z + const dx = x2 - x1, dy = y2 - y1, L = Math.hypot(dx, dy); if (L <= 0) return; + const nx = -dy / L * w / 2, ny = dx / L * w / 2; + const P = [[x1 - nx, y1 - ny], [x2 - nx, y2 - ny], [x2 + nx, y2 + ny], [x1 + nx, y1 + ny]]; // counter-clockwise in the plane + const B = P.map(function (q) { return [q[0], q[1], 0]; }), T = P.map(function (q) { return [q[0], q[1], Z]; }); + addQuad(T[0], T[1], T[2], T[3], [0, 0, 1]); addQuad(B[3], B[2], B[1], B[0], [0, 0, -1]); + for (let i = 0; i < 4; i++) { const j = (i + 1) % 4; const ex = P[j][0] - P[i][0], ey = P[j][1] - P[i][1], el = Math.hypot(ex, ey) || 1; addQuad(B[i], B[j], T[j], T[i], [ey / el, -ex / el, 0]); } + }; + const addPrism = function (cx, cy, r, sides) { + const ring = []; for (let i = 0; i < sides; i++) { const a = 2 * Math.PI * (i + 0.5) / sides; ring.push([cx + r * Math.cos(a), cy + r * Math.sin(a)]); } + for (let i = 0; i < sides; i++) { const j = (i + 1) % sides; const a = ring[i], b = ring[j]; + tris.push([[0, 0, 1], [cx, cy, Z], [a[0], a[1], Z], [b[0], b[1], Z]]); tris.push([[0, 0, -1], [cx, cy, 0], [b[0], b[1], 0], [a[0], a[1], 0]]); + const ex = b[0] - a[0], ey = b[1] - a[1], el = Math.hypot(ex, ey) || 1; addQuad([a[0], a[1], 0], [b[0], b[1], 0], [b[0], b[1], Z], [a[0], a[1], Z], [ey / el, -ex / el, 0]); } + }; + const jointR = new Float64Array(nodes.length); let nMembers = 0, wMin = Infinity, wMax = 0, nThickened = 0; + for (let i = 0; i < els.length; i++) { + const e = els[i]; + if (e.absent && !opts.includeAbsent) continue; + if (opts.state && opts.state[i] === 2 && !opts.includeFailed) continue; + const A = nodes[e.n1], B = nodes[e.n2]; const w = widthOf(e); + if (w > e.t * S * opts.widthFactor + 1e-12) nThickened++; + wMin = Math.min(wMin, w); wMax = Math.max(wMax, w); nMembers++; + addBox(A.x * S, A.y * S, B.x * S, B.y * S, w); + jointR[e.n1] = Math.max(jointR[e.n1], w / 2); jointR[e.n2] = Math.max(jointR[e.n2], w / 2); + } + if (opts.jointFill) for (let i = 0; i < nodes.length; i++) if (jointR[i] > 0) addPrism(nodes[i].x * S, nodes[i].y * S, jointR[i] * 1.02, opts.jointSides); + if (opts.gripTab_mm > 0) { + const W = structure.W * S, H = structure.H * S, tab = opts.gripTab_mm; + addBox(W / 2, -tab, W / 2, 0, W); addBox(W / 2, H, W / 2, H + tab, W); + // overlap into the specimen by a small margin so the tabs fuse with the frame/members + const ov = Math.max(0.5, Math.min(2, 0.02 * H)); addBox(W / 2, -0.01, W / 2, ov, W); addBox(W / 2, H - ov, W / 2, H + 0.01, W); + } + const n = tris.length; const buf = new ArrayBuffer(84 + n * 50); const dv = new DataView(buf); + const header = 'HFX hierarchical fracture design; units mm; W=' + S + 'mm depth=' + Z + 'mm minW=' + opts.minWidth_mm + ' wf=' + opts.widthFactor; + for (let i = 0; i < 80; i++) dv.setUint8(i, i < header.length ? header.charCodeAt(i) : 32); + dv.setUint32(80, n, true); + let off = 84; + for (const t of tris) { for (let k = 0; k < 4; k++) for (let c = 0; c < 3; c++) { dv.setFloat32(off, t[k][c], true); off += 4; } dv.setUint16(off, 0, true); off += 2; } + return { buffer: buf, triangles: n, members: nMembers, minWidth_mm: wMin, maxWidth_mm: wMax, thickened: nThickened, bytes: buf.byteLength, header: header }; +}; + +// ---------------------------------------------------------------------------- colour maps +const VIRIDIS = [[68, 1, 84], [72, 40, 120], [62, 74, 137], [49, 104, 142], [38, 130, 142], [31, 158, 137], [53, 183, 121], [109, 205, 89], [180, 222, 44], [253, 231, 37]]; +const MAGMA = [[0, 0, 4], [28, 16, 68], [79, 18, 123], [129, 37, 129], [181, 54, 122], [229, 80, 100], [251, 135, 97], [254, 194, 135], [252, 253, 191]]; +function lerpMap(map, t) { t = Math.max(0, Math.min(1, t)); const x = t * (map.length - 1); const i = Math.min(map.length - 2, Math.floor(x)); const f = x - i; const a = map[i], b = map[i + 1]; return [a[0] + f * (b[0] - a[0]), a[1] + f * (b[1] - a[1]), a[2] + f * (b[2] - a[2])]; } +function rgbStr(c) { return 'rgb(' + Math.round(c[0]) + ',' + Math.round(c[1]) + ',' + Math.round(c[2]) + ')'; } +HFX.colormaps = { + viridis: function (t) { return lerpMap(VIRIDIS, t); }, + magma: function (t) { return lerpMap(MAGMA, t); }, + coolwarm: function (t) { t = Math.max(0, Math.min(1, t)); if (t < 0.5) { const f = t / 0.5; return [59 + f * (221 - 59), 76 + f * (221 - 76), 192 + f * (221 - 192)]; } const f = (t - 0.5) / 0.5; return [221 + f * (180 - 221), 221 + f * (4 - 221), 221 + f * (38 - 221)]; }, + level: function (k) { const P = [[214, 39, 40], [255, 127, 14], [188, 189, 34], [44, 160, 44], [23, 190, 207], [31, 119, 180], [148, 103, 189], [227, 119, 194], [140, 86, 75], [127, 127, 127], [23, 23, 23]]; return P[Math.max(0, Math.min(P.length - 1, k))]; }, + rgb: rgbStr +}; +/** Colour for one element given the colouring mode. Returns [r,g,b] */ +HFX.elementColor = function (mode, e, i, data) { + const cm = HFX.colormaps; const st = data.state ? data.state[i] : 0; + if (st === 2 && mode !== 'failOrder') return [190, 190, 190]; + switch (mode) { + case 'level': return cm.level(e.level); + case 'interface': return e.isInterface ? [214, 39, 40] : (e.kind === 'brace' ? [255, 127, 14] : [80, 80, 80]); + case 'util': { const u = data.util ? data.util[i] : 0; return cm.viridis(0.12 + 0.88 * Math.min(1, Math.max(0, u))); } + case 'state': return st === 1 ? [255, 160, 0] : ((data.util && data.util[i] >= 0.8) ? [220, 120, 0] : [40, 90, 200]); + case 'N': { const Nn = data.N ? data.N[i] / Math.max(data.Nmax || 1e-300, 1e-300) : 0; return cm.coolwarm(0.5 + 0.5 * Math.max(-1, Math.min(1, Nn))); } + case 'disp': { const d = data.disp ? data.disp[i] / Math.max(data.dispMax || 1e-300, 1e-300) : 0; return cm.magma(d); } + case 'failOrder': { if (!data.failOrder || data.failOrder[i] < 0) return [200, 200, 200]; return cm.viridis(data.failOrder[i] / Math.max(1, data.nFailed - 1)); } + case 'thickness': return cm.magma(Math.log(e.t / data.tMin) / Math.max(1e-9, Math.log(data.tMax / data.tMin))); + default: return [60, 60, 60]; + } +}; +/** + * Render the structure as SVG. opts: {width, height, u (Float64Array or null), scale (deformation magnification), colorBy, state, util, N, failOrder, nFailed, + * showFailed ('hide'|'ghost'|'show'), title, lineScale, background, padding, showCells} + */ +HFX.renderSVG = function (structure, opts) { + opts = Object.assign({ width: 800, height: 800, u: null, scale: 1, colorBy: 'level', showFailed: 'ghost', title: '', lineScale: 1, background: '#ffffff', padding: 30, showCells: false, minLine: 0.5 }, opts || {}); + const W = structure.W, H = structure.H, nodes = structure.nodes, els = structure.elements; + const pad = opts.padding; const sx = (opts.width - 2 * pad) / W, sy = (opts.height - 2 * pad) / H; const sc = Math.min(sx, sy); + const ox = pad + (opts.width - 2 * pad - W * sc) / 2, oy = pad + (opts.height - 2 * pad - H * sc) / 2; + const X = function (x) { return ox + x * sc; }, Y = function (y) { return opts.height - (oy + y * sc); }; + const u = opts.u, mag = opts.scale; + const px = function (i) { return nodes[i].x + (u ? mag * u[3 * i] : 0); }, py = function (i) { return nodes[i].y + (u ? mag * u[3 * i + 1] : 0); }; + let Nmax = 0, dispMax = 0; const disp = new Float64Array(els.length); + if (opts.N) for (let i = 0; i < els.length; i++) Nmax = Math.max(Nmax, Math.abs(opts.N[i])); + if (u) for (let i = 0; i < els.length; i++) { const e = els[i]; const d = 0.5 * (Math.hypot(u[3 * e.n1], u[3 * e.n1 + 1]) + Math.hypot(u[3 * e.n2], u[3 * e.n2 + 1])); disp[i] = d; dispMax = Math.max(dispMax, d); } + const data = { state: opts.state, util: opts.util, N: opts.N, Nmax: Nmax, disp: disp, dispMax: dispMax, failOrder: opts.failOrder, nFailed: opts.nFailed || 0, tMin: structure.stats.tMin, tMax: structure.stats.tMax }; + const parts = ['']; + parts.push(''); + if (opts.showCells && structure.leafCells) { for (const c of structure.leafCells) parts.push(''); } + // draw thick (coarse) members first so fine members are visible on top + const order = els.map(function (e, i) { return i; }).sort(function (a, b) { return els[a].level - els[b].level; }); + for (const i of order) { + const e = els[i]; const st = opts.state ? opts.state[i] : 0; + if (e.absent) continue; + if (st === 2 && opts.showFailed === 'hide') continue; + const wpx = Math.max(opts.minLine, e.t * sc * opts.lineScale); + const col = rgbStr(HFX.elementColor(opts.colorBy, e, i, data)); + const x1 = X(px(e.n1)), y1 = Y(py(e.n1)), x2 = X(px(e.n2)), y2 = Y(py(e.n2)); + if (st === 2 && opts.showFailed === 'ghost') parts.push(''); + else parts.push(''); + } + if (opts.title) parts.push('' + opts.title.replace(/&/g, '&').replace(/'); + parts.push(''); + return parts.join('\n'); +}; +/** Simple SVG line plot. series: [{x:[],y:[],label,color,width,dash}], opts: {width,height,xlabel,ylabel,title,xmin,xmax,ymin,ymax,marker:{x,y}} */ +HFX.plotSVG = function (series, opts) { + opts = Object.assign({ width: 640, height: 420, xlabel: 'x', ylabel: 'y', title: '', legend: true, fontSize: 12 }, opts || {}); + const ml = 64, mr = 16, mt = opts.title ? 30 : 14, mb = 46; const pw = opts.width - ml - mr, ph = opts.height - mt - mb; + let xmin = Infinity, xmax = -Infinity, ymin = Infinity, ymax = -Infinity; + for (const s of series) for (let i = 0; i < s.x.length; i++) { const x = s.x[i], y = s.y[i]; if (!isFinite(x) || !isFinite(y)) continue; xmin = Math.min(xmin, x); xmax = Math.max(xmax, x); ymin = Math.min(ymin, y); ymax = Math.max(ymax, y); } + if (!isFinite(xmin)) { xmin = 0; xmax = 1; ymin = 0; ymax = 1; } + if (opts.xmin !== undefined) xmin = opts.xmin; if (opts.xmax !== undefined) xmax = opts.xmax; if (opts.ymin !== undefined) ymin = opts.ymin; if (opts.ymax !== undefined) ymax = opts.ymax; + if (xmax - xmin <= 0) xmax = xmin + 1; if (ymax - ymin <= 0) ymax = ymin + 1; + ymax += 0.05 * (ymax - ymin); + const X = function (x) { return ml + (x - xmin) / (xmax - xmin) * pw; }, Y = function (y) { return mt + ph - (y - ymin) / (ymax - ymin) * ph; }; + const niceTicks = function (a, b, n) { const span = b - a; const raw = span / n; const mag = Math.pow(10, Math.floor(Math.log10(raw))); const norm = raw / mag; const step = (norm < 1.5 ? 1 : norm < 3.5 ? 2 : norm < 7.5 ? 5 : 10) * mag; const t = []; for (let v = Math.ceil(a / step) * step; v <= b + 1e-12 * span; v += step) t.push(Number(v.toPrecision(10))); return t; }; + const fmtT = function (v) { return Math.abs(v) < 1e-3 && v !== 0 ? v.toExponential(1) : (Number.isInteger(v) ? String(v) : v.toPrecision(3).replace(/\.?0+$/, '')); }; + const P = ['', '']; + for (const t of niceTicks(xmin, xmax, 6)) { P.push(''); P.push(''); P.push('' + fmtT(t) + ''); } + for (const t of niceTicks(ymin, ymax, 6)) { P.push(''); P.push(''); P.push('' + fmtT(t) + ''); } + P.push(''); + series.forEach(function (s, k) { + const col = s.color || ['#1f77b4', '#d62728', '#2ca02c', '#ff7f0e', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f'][k % 8]; + let d = ''; for (let i = 0; i < s.x.length; i++) { if (!isFinite(s.x[i]) || !isFinite(s.y[i])) continue; d += (d ? 'L' : 'M') + X(s.x[i]).toFixed(2) + ' ' + Y(s.y[i]).toFixed(2); } + P.push(''); + if (opts.legend && s.label) { P.push(''); P.push('' + s.label + ''); } + }); + if (opts.marker) P.push(''); + P.push('' + opts.xlabel + ''); + P.push('' + opts.ylabel + ''); + if (opts.title) P.push('' + opts.title + ''); + P.push(''); + return P.join('\n'); +}; + +// ============================================================================ +HFX.nowMs = nowMs; +return HFX; +}); diff --git a/data/Run 1/RESULT Run 1/app/src/three.min.r128.js b/data/Run 1/RESULT Run 1/app/src/three.min.r128.js new file mode 100644 index 0000000000000000000000000000000000000000..b14f47c0908bab15e890b468d53bb07db0be3a18 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/three.min.r128.js @@ -0,0 +1,6 @@ +/** + * @license + * Copyright 2010-2021 Three.js Authors + * SPDX-License-Identifier: MIT + */ +!function(t,e){"object"==typeof exports&&"undefined"!=typeof module?e(exports):"function"==typeof define&&define.amd?define(["exports"],e):e((t="undefined"!=typeof globalThis?globalThis:t||self).THREE={})}(this,(function(t){"use strict";const e="128",n=100,i=300,r=301,s=302,a=303,o=304,l=306,c=307,h=1e3,u=1001,d=1002,p=1003,m=1004,f=1005,g=1006,v=1007,y=1008,x=1009,_=1012,w=1014,b=1015,M=1016,S=1020,T=1022,E=1023,A=1026,L=1027,R=33776,C=33777,P=33778,D=33779,I=35840,N=35841,B=35842,z=35843,F=37492,O=37496,H=2300,G=2301,U=2302,k=2400,V=2401,W=2402,j=2500,q=2501,X=3e3,Y=3001,Z=3007,J=3002,Q=3004,K=3005,$=3006,tt=7680,et=35044,nt=35048,it="300 es";class rt{addEventListener(t,e){void 0===this._listeners&&(this._listeners={});const n=this._listeners;void 0===n[t]&&(n[t]=[]),-1===n[t].indexOf(e)&&n[t].push(e)}hasEventListener(t,e){if(void 0===this._listeners)return!1;const n=this._listeners;return void 0!==n[t]&&-1!==n[t].indexOf(e)}removeEventListener(t,e){if(void 0===this._listeners)return;const n=this._listeners[t];if(void 0!==n){const t=n.indexOf(e);-1!==t&&n.splice(t,1)}}dispatchEvent(t){if(void 0===this._listeners)return;const e=this._listeners[t.type];if(void 0!==e){t.target=this;const n=e.slice(0);for(let e=0,i=n.length;e>8&255]+st[t>>16&255]+st[t>>24&255]+"-"+st[255&e]+st[e>>8&255]+"-"+st[e>>16&15|64]+st[e>>24&255]+"-"+st[63&n|128]+st[n>>8&255]+"-"+st[n>>16&255]+st[n>>24&255]+st[255&i]+st[i>>8&255]+st[i>>16&255]+st[i>>24&255]).toUpperCase()}function ht(t,e,n){return Math.max(e,Math.min(n,t))}function ut(t,e){return(t%e+e)%e}function dt(t,e,n){return(1-n)*t+n*e}function pt(t){return 0==(t&t-1)&&0!==t}function mt(t){return Math.pow(2,Math.ceil(Math.log(t)/Math.LN2))}function ft(t){return Math.pow(2,Math.floor(Math.log(t)/Math.LN2))}var gt=Object.freeze({__proto__:null,DEG2RAD:ot,RAD2DEG:lt,generateUUID:ct,clamp:ht,euclideanModulo:ut,mapLinear:function(t,e,n,i,r){return i+(t-e)*(r-i)/(n-e)},inverseLerp:function(t,e,n){return t!==e?(n-t)/(e-t):0},lerp:dt,damp:function(t,e,n,i){return dt(t,e,1-Math.exp(-n*i))},pingpong:function(t,e=1){return e-Math.abs(ut(t,2*e)-e)},smoothstep:function(t,e,n){return t<=e?0:t>=n?1:(t=(t-e)/(n-e))*t*(3-2*t)},smootherstep:function(t,e,n){return t<=e?0:t>=n?1:(t=(t-e)/(n-e))*t*t*(t*(6*t-15)+10)},randInt:function(t,e){return t+Math.floor(Math.random()*(e-t+1))},randFloat:function(t,e){return t+Math.random()*(e-t)},randFloatSpread:function(t){return t*(.5-Math.random())},seededRandom:function(t){return void 0!==t&&(at=t%2147483647),at=16807*at%2147483647,(at-1)/2147483646},degToRad:function(t){return t*ot},radToDeg:function(t){return t*lt},isPowerOfTwo:pt,ceilPowerOfTwo:mt,floorPowerOfTwo:ft,setQuaternionFromProperEuler:function(t,e,n,i,r){const s=Math.cos,a=Math.sin,o=s(n/2),l=a(n/2),c=s((e+i)/2),h=a((e+i)/2),u=s((e-i)/2),d=a((e-i)/2),p=s((i-e)/2),m=a((i-e)/2);switch(r){case"XYX":t.set(o*h,l*u,l*d,o*c);break;case"YZY":t.set(l*d,o*h,l*u,o*c);break;case"ZXZ":t.set(l*u,l*d,o*h,o*c);break;case"XZX":t.set(o*h,l*m,l*p,o*c);break;case"YXY":t.set(l*p,o*h,l*m,o*c);break;case"ZYZ":t.set(l*m,l*p,o*h,o*c);break;default:console.warn("THREE.MathUtils: .setQuaternionFromProperEuler() encountered an unknown order: "+r)}}});class vt{constructor(t=0,e=0){this.x=t,this.y=e}get width(){return this.x}set width(t){this.x=t}get height(){return this.y}set height(t){this.y=t}set(t,e){return this.x=t,this.y=e,this}setScalar(t){return this.x=t,this.y=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;default:throw new Error("index is out of range: "+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;default:throw new Error("index is out of range: "+t)}}clone(){return new this.constructor(this.x,this.y)}copy(t){return this.x=t.x,this.y=t.y,this}add(t,e){return void 0!==e?(console.warn("THREE.Vector2: .add() now only accepts one argument. 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e[0]*=t,e[3]*=t,e[6]*=t,e[1]*=t,e[4]*=t,e[7]*=t,e[2]*=t,e[5]*=t,e[8]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[1],i=t[2],r=t[3],s=t[4],a=t[5],o=t[6],l=t[7],c=t[8];return e*s*c-e*a*l-n*r*c+n*a*o+i*r*l-i*s*o}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],r=t[3],s=t[4],a=t[5],o=t[6],l=t[7],c=t[8],h=c*s-a*l,u=a*o-c*r,d=l*r-s*o,p=e*h+n*u+i*d;if(0===p)return this.set(0,0,0,0,0,0,0,0,0);const m=1/p;return t[0]=h*m,t[1]=(i*l-c*n)*m,t[2]=(a*n-i*s)*m,t[3]=u*m,t[4]=(c*e-i*o)*m,t[5]=(i*r-a*e)*m,t[6]=d*m,t[7]=(n*o-l*e)*m,t[8]=(s*e-n*r)*m,this}transpose(){let t;const e=this.elements;return t=e[1],e[1]=e[3],e[3]=t,t=e[2],e[2]=e[6],e[6]=t,t=e[5],e[5]=e[7],e[7]=t,this}getNormalMatrix(t){return this.setFromMatrix4(t).invert().transpose()}transposeIntoArray(t){const e=this.elements;return t[0]=e[0],t[1]=e[3],t[2]=e[6],t[3]=e[1],t[4]=e[4],t[5]=e[7],t[6]=e[2],t[7]=e[5],t[8]=e[8],this}setUvTransform(t,e,n,i,r,s,a){const o=Math.cos(r),l=Math.sin(r);return this.set(n*o,n*l,-n*(o*s+l*a)+s+t,-i*l,i*o,-i*(-l*s+o*a)+a+e,0,0,1),this}scale(t,e){const n=this.elements;return n[0]*=t,n[3]*=t,n[6]*=t,n[1]*=e,n[4]*=e,n[7]*=e,this}rotate(t){const e=Math.cos(t),n=Math.sin(t),i=this.elements,r=i[0],s=i[3],a=i[6],o=i[1],l=i[4],c=i[7];return i[0]=e*r+n*o,i[3]=e*s+n*l,i[6]=e*a+n*c,i[1]=-n*r+e*o,i[4]=-n*s+e*l,i[7]=-n*a+e*c,this}translate(t,e){const n=this.elements;return n[0]+=t*n[2],n[3]+=t*n[5],n[6]+=t*n[8],n[1]+=e*n[2],n[4]+=e*n[5],n[7]+=e*n[8],this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<9;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<9;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t}clone(){return(new this.constructor).fromArray(this.elements)}}let xt;yt.prototype.isMatrix3=!0;class _t{static getDataURL(t){if(/^data:/i.test(t.src))return t.src;if("undefined"==typeof HTMLCanvasElement)return t.src;let e;if(t instanceof HTMLCanvasElement)e=t;else{void 0===xt&&(xt=document.createElementNS("http://www.w3.org/1999/xhtml","canvas")),xt.width=t.width,xt.height=t.height;const n=xt.getContext("2d");t instanceof ImageData?n.putImageData(t,0,0):n.drawImage(t,0,0,t.width,t.height),e=xt}return e.width>2048||e.height>2048?(console.warn("THREE.ImageUtils.getDataURL: Image converted to jpg for performance reasons",t),e.toDataURL("image/jpeg",.6)):e.toDataURL("image/png")}}let wt=0;class bt extends rt{constructor(t=bt.DEFAULT_IMAGE,e=bt.DEFAULT_MAPPING,n=1001,i=1001,r=1006,s=1008,a=1023,o=1009,l=1,c=3e3){super(),Object.defineProperty(this,"id",{value:wt++}),this.uuid=ct(),this.name="",this.image=t,this.mipmaps=[],this.mapping=e,this.wrapS=n,this.wrapT=i,this.magFilter=r,this.minFilter=s,this.anisotropy=l,this.format=a,this.internalFormat=null,this.type=o,this.offset=new vt(0,0),this.repeat=new vt(1,1),this.center=new vt(0,0),this.rotation=0,this.matrixAutoUpdate=!0,this.matrix=new yt,this.generateMipmaps=!0,this.premultiplyAlpha=!1,this.flipY=!0,this.unpackAlignment=4,this.encoding=c,this.version=0,this.onUpdate=null}updateMatrix(){this.matrix.setUvTransform(this.offset.x,this.offset.y,this.repeat.x,this.repeat.y,this.rotation,this.center.x,this.center.y)}clone(){return(new this.constructor).copy(this)}copy(t){return this.name=t.name,this.image=t.image,this.mipmaps=t.mipmaps.slice(0),this.mapping=t.mapping,this.wrapS=t.wrapS,this.wrapT=t.wrapT,this.magFilter=t.magFilter,this.minFilter=t.minFilter,this.anisotropy=t.anisotropy,this.format=t.format,this.internalFormat=t.internalFormat,this.type=t.type,this.offset.copy(t.offset),this.repeat.copy(t.repeat),this.center.copy(t.center),this.rotation=t.rotation,this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrix.copy(t.matrix),this.generateMipmaps=t.generateMipmaps,this.premultiplyAlpha=t.premultiplyAlpha,this.flipY=t.flipY,this.unpackAlignment=t.unpackAlignment,this.encoding=t.encoding,this}toJSON(t){const e=void 0===t||"string"==typeof t;if(!e&&void 0!==t.textures[this.uuid])return t.textures[this.uuid];const n={metadata:{version:4.5,type:"Texture",generator:"Texture.toJSON"},uuid:this.uuid,name:this.name,mapping:this.mapping,repeat:[this.repeat.x,this.repeat.y],offset:[this.offset.x,this.offset.y],center:[this.center.x,this.center.y],rotation:this.rotation,wrap:[this.wrapS,this.wrapT],format:this.format,type:this.type,encoding:this.encoding,minFilter:this.minFilter,magFilter:this.magFilter,anisotropy:this.anisotropy,flipY:this.flipY,premultiplyAlpha:this.premultiplyAlpha,unpackAlignment:this.unpackAlignment};if(void 0!==this.image){const i=this.image;if(void 0===i.uuid&&(i.uuid=ct()),!e&&void 0===t.images[i.uuid]){let e;if(Array.isArray(i)){e=[];for(let t=0,n=i.length;t1)switch(this.wrapS){case h:t.x=t.x-Math.floor(t.x);break;case u:t.x=t.x<0?0:1;break;case d:1===Math.abs(Math.floor(t.x)%2)?t.x=Math.ceil(t.x)-t.x:t.x=t.x-Math.floor(t.x)}if(t.y<0||t.y>1)switch(this.wrapT){case h:t.y=t.y-Math.floor(t.y);break;case u:t.y=t.y<0?0:1;break;case d:1===Math.abs(Math.floor(t.y)%2)?t.y=Math.ceil(t.y)-t.y:t.y=t.y-Math.floor(t.y)}return this.flipY&&(t.y=1-t.y),t}set needsUpdate(t){!0===t&&this.version++}}function Mt(t){return"undefined"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||"undefined"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||"undefined"!=typeof ImageBitmap&&t instanceof ImageBitmap?_t.getDataURL(t):t.data?{data:Array.prototype.slice.call(t.data),width:t.width,height:t.height,type:t.data.constructor.name}:(console.warn("THREE.Texture: Unable to serialize Texture."),{})}bt.DEFAULT_IMAGE=void 0,bt.DEFAULT_MAPPING=i,bt.prototype.isTexture=!0;class St{constructor(t=0,e=0,n=0,i=1){this.x=t,this.y=e,this.z=n,this.w=i}get width(){return this.z}set width(t){this.z=t}get height(){return this.w}set height(t){this.w=t}set(t,e,n,i){return this.x=t,this.y=e,this.z=n,this.w=i,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this.w=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setW(t){return this.w=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;case 3:this.w=e;break;default:throw new Error("index is out of range: "+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error("index is out of range: "+t)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this.w=void 0!==t.w?t.w:1,this}add(t,e){return void 0!==e?(console.warn("THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead."),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this.w+=t.w,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this.w+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this.w=t.w+e.w,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this.w+=t.w*e,this}sub(t,e){return void 0!==e?(console.warn("THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead."),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this.w-=t.w,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this.w-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this.w=t.w-e.w,this}multiply(t){return this.x*=t.x,this.y*=t.y,this.z*=t.z,this.w*=t.w,this}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this.w*=t,this}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,r=this.w,s=t.elements;return this.x=s[0]*e+s[4]*n+s[8]*i+s[12]*r,this.y=s[1]*e+s[5]*n+s[9]*i+s[13]*r,this.z=s[2]*e+s[6]*n+s[10]*i+s[14]*r,this.w=s[3]*e+s[7]*n+s[11]*i+s[15]*r,this}divideScalar(t){return this.multiplyScalar(1/t)}setAxisAngleFromQuaternion(t){this.w=2*Math.acos(t.w);const e=Math.sqrt(1-t.w*t.w);return e<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=t.x/e,this.y=t.y/e,this.z=t.z/e),this}setAxisAngleFromRotationMatrix(t){let e,n,i,r;const s=.01,a=.1,o=t.elements,l=o[0],c=o[4],h=o[8],u=o[1],d=o[5],p=o[9],m=o[2],f=o[6],g=o[10];if(Math.abs(c-u)o&&t>v?tv?o=0?1:-1,i=1-e*e;if(i>Number.EPSILON){const r=Math.sqrt(i),s=Math.atan2(r,e*n);t=Math.sin(t*s)/r,a=Math.sin(a*s)/r}const r=a*n;if(o=o*t+u*r,l=l*t+d*r,c=c*t+p*r,h=h*t+m*r,t===1-a){const t=1/Math.sqrt(o*o+l*l+c*c+h*h);o*=t,l*=t,c*=t,h*=t}}t[e]=o,t[e+1]=l,t[e+2]=c,t[e+3]=h}static multiplyQuaternionsFlat(t,e,n,i,r,s){const a=n[i],o=n[i+1],l=n[i+2],c=n[i+3],h=r[s],u=r[s+1],d=r[s+2],p=r[s+3];return t[e]=a*p+c*h+o*d-l*u,t[e+1]=o*p+c*u+l*h-a*d,t[e+2]=l*p+c*d+a*u-o*h,t[e+3]=c*p-a*h-o*u-l*d,t}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get w(){return this._w}set w(t){this._w=t,this._onChangeCallback()}set(t,e,n,i){return this._x=t,this._y=e,this._z=n,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(t){return this._x=t.x,this._y=t.y,this._z=t.z,this._w=t.w,this._onChangeCallback(),this}setFromEuler(t,e){if(!t||!t.isEuler)throw new Error("THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.");const n=t._x,i=t._y,r=t._z,s=t._order,a=Math.cos,o=Math.sin,l=a(n/2),c=a(i/2),h=a(r/2),u=o(n/2),d=o(i/2),p=o(r/2);switch(s){case"XYZ":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case"YXZ":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case"ZXY":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case"ZYX":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case"YZX":this._x=u*c*h+l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h-u*d*p;break;case"XZY":this._x=u*c*h-l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h+u*d*p;break;default:console.warn("THREE.Quaternion: .setFromEuler() encountered an unknown order: "+s)}return!1!==e&&this._onChangeCallback(),this}setFromAxisAngle(t,e){const n=e/2,i=Math.sin(n);return this._x=t.x*i,this._y=t.y*i,this._z=t.z*i,this._w=Math.cos(n),this._onChangeCallback(),this}setFromRotationMatrix(t){const e=t.elements,n=e[0],i=e[4],r=e[8],s=e[1],a=e[5],o=e[9],l=e[2],c=e[6],h=e[10],u=n+a+h;if(u>0){const t=.5/Math.sqrt(u+1);this._w=.25/t,this._x=(c-o)*t,this._y=(r-l)*t,this._z=(s-i)*t}else if(n>a&&n>h){const t=2*Math.sqrt(1+n-a-h);this._w=(c-o)/t,this._x=.25*t,this._y=(i+s)/t,this._z=(r+l)/t}else if(a>h){const t=2*Math.sqrt(1+a-n-h);this._w=(r-l)/t,this._x=(i+s)/t,this._y=.25*t,this._z=(o+c)/t}else{const t=2*Math.sqrt(1+h-n-a);this._w=(s-i)/t,this._x=(r+l)/t,this._y=(o+c)/t,this._z=.25*t}return this._onChangeCallback(),this}setFromUnitVectors(t,e){let n=t.dot(e)+1;return nMath.abs(t.z)?(this._x=-t.y,this._y=t.x,this._z=0,this._w=n):(this._x=0,this._y=-t.z,this._z=t.y,this._w=n)):(this._x=t.y*e.z-t.z*e.y,this._y=t.z*e.x-t.x*e.z,this._z=t.x*e.y-t.y*e.x,this._w=n),this.normalize()}angleTo(t){return 2*Math.acos(Math.abs(ht(this.dot(t),-1,1)))}rotateTowards(t,e){const n=this.angleTo(t);if(0===n)return this;const i=Math.min(1,e/n);return this.slerp(t,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(t){return this._x*t._x+this._y*t._y+this._z*t._z+this._w*t._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let t=this.length();return 0===t?(this._x=0,this._y=0,this._z=0,this._w=1):(t=1/t,this._x=this._x*t,this._y=this._y*t,this._z=this._z*t,this._w=this._w*t),this._onChangeCallback(),this}multiply(t,e){return void 0!==e?(console.warn("THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead."),this.multiplyQuaternions(t,e)):this.multiplyQuaternions(this,t)}premultiply(t){return this.multiplyQuaternions(t,this)}multiplyQuaternions(t,e){const n=t._x,i=t._y,r=t._z,s=t._w,a=e._x,o=e._y,l=e._z,c=e._w;return this._x=n*c+s*a+i*l-r*o,this._y=i*c+s*o+r*a-n*l,this._z=r*c+s*l+n*o-i*a,this._w=s*c-n*a-i*o-r*l,this._onChangeCallback(),this}slerp(t,e){if(0===e)return this;if(1===e)return this.copy(t);const n=this._x,i=this._y,r=this._z,s=this._w;let a=s*t._w+n*t._x+i*t._y+r*t._z;if(a<0?(this._w=-t._w,this._x=-t._x,this._y=-t._y,this._z=-t._z,a=-a):this.copy(t),a>=1)return this._w=s,this._x=n,this._y=i,this._z=r,this;const o=1-a*a;if(o<=Number.EPSILON){const t=1-e;return this._w=t*s+e*this._w,this._x=t*n+e*this._x,this._y=t*i+e*this._y,this._z=t*r+e*this._z,this.normalize(),this._onChangeCallback(),this}const l=Math.sqrt(o),c=Math.atan2(l,a),h=Math.sin((1-e)*c)/l,u=Math.sin(e*c)/l;return this._w=s*h+this._w*u,this._x=n*h+this._x*u,this._y=i*h+this._y*u,this._z=r*h+this._z*u,this._onChangeCallback(),this}slerpQuaternions(t,e,n){this.copy(t).slerp(e,n)}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._w===this._w}fromArray(t,e=0){return this._x=t[e],this._y=t[e+1],this._z=t[e+2],this._w=t[e+3],this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._w,t}fromBufferAttribute(t,e){return this._x=t.getX(e),this._y=t.getY(e),this._z=t.getZ(e),this._w=t.getW(e),this}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}At.prototype.isQuaternion=!0;class Lt{constructor(t=0,e=0,n=0){this.x=t,this.y=e,this.z=n}set(t,e,n){return void 0===n&&(n=this.z),this.x=t,this.y=e,this.z=n,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;default:throw new Error("index is out of range: "+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;default:throw new Error("index is out of range: "+t)}}clone(){return new this.constructor(this.x,this.y,this.z)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this}add(t,e){return void 0!==e?(console.warn("THREE.Vector3: .add() now only accepts one argument. Use .addVectors( a, b ) instead."),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this}sub(t,e){return void 0!==e?(console.warn("THREE.Vector3: .sub() now only accepts one argument. Use .subVectors( a, b ) instead."),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this}multiply(t,e){return void 0!==e?(console.warn("THREE.Vector3: .multiply() now only accepts one argument. Use .multiplyVectors( a, b ) instead."),this.multiplyVectors(t,e)):(this.x*=t.x,this.y*=t.y,this.z*=t.z,this)}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this}multiplyVectors(t,e){return this.x=t.x*e.x,this.y=t.y*e.y,this.z=t.z*e.z,this}applyEuler(t){return t&&t.isEuler||console.error("THREE.Vector3: .applyEuler() now expects an Euler rotation rather than a Vector3 and order."),this.applyQuaternion(Ct.setFromEuler(t))}applyAxisAngle(t,e){return this.applyQuaternion(Ct.setFromAxisAngle(t,e))}applyMatrix3(t){const e=this.x,n=this.y,i=this.z,r=t.elements;return this.x=r[0]*e+r[3]*n+r[6]*i,this.y=r[1]*e+r[4]*n+r[7]*i,this.z=r[2]*e+r[5]*n+r[8]*i,this}applyNormalMatrix(t){return this.applyMatrix3(t).normalize()}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,r=t.elements,s=1/(r[3]*e+r[7]*n+r[11]*i+r[15]);return this.x=(r[0]*e+r[4]*n+r[8]*i+r[12])*s,this.y=(r[1]*e+r[5]*n+r[9]*i+r[13])*s,this.z=(r[2]*e+r[6]*n+r[10]*i+r[14])*s,this}applyQuaternion(t){const e=this.x,n=this.y,i=this.z,r=t.x,s=t.y,a=t.z,o=t.w,l=o*e+s*i-a*n,c=o*n+a*e-r*i,h=o*i+r*n-s*e,u=-r*e-s*n-a*i;return this.x=l*o+u*-r+c*-a-h*-s,this.y=c*o+u*-s+h*-r-l*-a,this.z=h*o+u*-a+l*-s-c*-r,this}project(t){return this.applyMatrix4(t.matrixWorldInverse).applyMatrix4(t.projectionMatrix)}unproject(t){return this.applyMatrix4(t.projectionMatrixInverse).applyMatrix4(t.matrixWorld)}transformDirection(t){const e=this.x,n=this.y,i=this.z,r=t.elements;return this.x=r[0]*e+r[4]*n+r[8]*i,this.y=r[1]*e+r[5]*n+r[9]*i,this.z=r[2]*e+r[6]*n+r[10]*i,this.normalize()}divide(t){return this.x/=t.x,this.y/=t.y,this.z/=t.z,this}divideScalar(t){return this.multiplyScalar(1/t)}min(t){return this.x=Math.min(this.x,t.x),this.y=Math.min(this.y,t.y),this.z=Math.min(this.z,t.z),this}max(t){return this.x=Math.max(this.x,t.x),this.y=Math.max(this.y,t.y),this.z=Math.max(this.z,t.z),this}clamp(t,e){return this.x=Math.max(t.x,Math.min(e.x,this.x)),this.y=Math.max(t.y,Math.min(e.y,this.y)),this.z=Math.max(t.z,Math.min(e.z,this.z)),this}clampScalar(t,e){return this.x=Math.max(t,Math.min(e,this.x)),this.y=Math.max(t,Math.min(e,this.y)),this.z=Math.max(t,Math.min(e,this.z)),this}clampLength(t,e){const n=this.length();return this.divideScalar(n||1).multiplyScalar(Math.max(t,Math.min(e,n)))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this}roundToZero(){return this.x=this.x<0?Math.ceil(this.x):Math.floor(this.x),this.y=this.y<0?Math.ceil(this.y):Math.floor(this.y),this.z=this.z<0?Math.ceil(this.z):Math.floor(this.z),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this}dot(t){return this.x*t.x+this.y*t.y+this.z*t.z}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)}normalize(){return this.divideScalar(this.length()||1)}setLength(t){return this.normalize().multiplyScalar(t)}lerp(t,e){return this.x+=(t.x-this.x)*e,this.y+=(t.y-this.y)*e,this.z+=(t.z-this.z)*e,this}lerpVectors(t,e,n){return this.x=t.x+(e.x-t.x)*n,this.y=t.y+(e.y-t.y)*n,this.z=t.z+(e.z-t.z)*n,this}cross(t,e){return void 0!==e?(console.warn("THREE.Vector3: .cross() now only accepts one argument. Use .crossVectors( a, b ) instead."),this.crossVectors(t,e)):this.crossVectors(this,t)}crossVectors(t,e){const n=t.x,i=t.y,r=t.z,s=e.x,a=e.y,o=e.z;return this.x=i*o-r*a,this.y=r*s-n*o,this.z=n*a-i*s,this}projectOnVector(t){const e=t.lengthSq();if(0===e)return this.set(0,0,0);const n=t.dot(this)/e;return this.copy(t).multiplyScalar(n)}projectOnPlane(t){return Rt.copy(this).projectOnVector(t),this.sub(Rt)}reflect(t){return this.sub(Rt.copy(t).multiplyScalar(2*this.dot(t)))}angleTo(t){const e=Math.sqrt(this.lengthSq()*t.lengthSq());if(0===e)return Math.PI/2;const n=this.dot(t)/e;return Math.acos(ht(n,-1,1))}distanceTo(t){return Math.sqrt(this.distanceToSquared(t))}distanceToSquared(t){const e=this.x-t.x,n=this.y-t.y,i=this.z-t.z;return e*e+n*n+i*i}manhattanDistanceTo(t){return Math.abs(this.x-t.x)+Math.abs(this.y-t.y)+Math.abs(this.z-t.z)}setFromSpherical(t){return this.setFromSphericalCoords(t.radius,t.phi,t.theta)}setFromSphericalCoords(t,e,n){const i=Math.sin(e)*t;return this.x=i*Math.sin(n),this.y=Math.cos(e)*t,this.z=i*Math.cos(n),this}setFromCylindrical(t){return this.setFromCylindricalCoords(t.radius,t.theta,t.y)}setFromCylindricalCoords(t,e,n){return this.x=t*Math.sin(e),this.y=n,this.z=t*Math.cos(e),this}setFromMatrixPosition(t){const e=t.elements;return this.x=e[12],this.y=e[13],this.z=e[14],this}setFromMatrixScale(t){const e=this.setFromMatrixColumn(t,0).length(),n=this.setFromMatrixColumn(t,1).length(),i=this.setFromMatrixColumn(t,2).length();return this.x=e,this.y=n,this.z=i,this}setFromMatrixColumn(t,e){return this.fromArray(t.elements,4*e)}setFromMatrix3Column(t,e){return this.fromArray(t.elements,3*e)}equals(t){return t.x===this.x&&t.y===this.y&&t.z===this.z}fromArray(t,e=0){return this.x=t[e],this.y=t[e+1],this.z=t[e+2],this}toArray(t=[],e=0){return t[e]=this.x,t[e+1]=this.y,t[e+2]=this.z,t}fromBufferAttribute(t,e,n){return void 0!==n&&console.warn("THREE.Vector3: offset has been removed from .fromBufferAttribute()."),this.x=t.getX(e),this.y=t.getY(e),this.z=t.getZ(e),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this}}Lt.prototype.isVector3=!0;const Rt=new Lt,Ct=new At;class Pt{constructor(t=new Lt(1/0,1/0,1/0),e=new Lt(-1/0,-1/0,-1/0)){this.min=t,this.max=e}set(t,e){return this.min.copy(t),this.max.copy(e),this}setFromArray(t){let e=1/0,n=1/0,i=1/0,r=-1/0,s=-1/0,a=-1/0;for(let o=0,l=t.length;or&&(r=l),c>s&&(s=c),h>a&&(a=h)}return this.min.set(e,n,i),this.max.set(r,s,a),this}setFromBufferAttribute(t){let e=1/0,n=1/0,i=1/0,r=-1/0,s=-1/0,a=-1/0;for(let o=0,l=t.count;or&&(r=l),c>s&&(s=c),h>a&&(a=h)}return this.min.set(e,n,i),this.max.set(r,s,a),this}setFromPoints(t){this.makeEmpty();for(let e=0,n=t.length;ethis.max.x||t.ythis.max.y||t.zthis.max.z)}containsBox(t){return this.min.x<=t.min.x&&t.max.x<=this.max.x&&this.min.y<=t.min.y&&t.max.y<=this.max.y&&this.min.z<=t.min.z&&t.max.z<=this.max.z}getParameter(t,e){return void 0===e&&(console.warn("THREE.Box3: .getParameter() target is now required"),e=new Lt),e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y),(t.z-this.min.z)/(this.max.z-this.min.z))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y||t.max.zthis.max.z)}intersectsSphere(t){return this.clampPoint(t.center,It),It.distanceToSquared(t.center)<=t.radius*t.radius}intersectsPlane(t){let e,n;return t.normal.x>0?(e=t.normal.x*this.min.x,n=t.normal.x*this.max.x):(e=t.normal.x*this.max.x,n=t.normal.x*this.min.x),t.normal.y>0?(e+=t.normal.y*this.min.y,n+=t.normal.y*this.max.y):(e+=t.normal.y*this.max.y,n+=t.normal.y*this.min.y),t.normal.z>0?(e+=t.normal.z*this.min.z,n+=t.normal.z*this.max.z):(e+=t.normal.z*this.max.z,n+=t.normal.z*this.min.z),e<=-t.constant&&n>=-t.constant}intersectsTriangle(t){if(this.isEmpty())return!1;this.getCenter(Ut),kt.subVectors(this.max,Ut),Bt.subVectors(t.a,Ut),zt.subVectors(t.b,Ut),Ft.subVectors(t.c,Ut),Ot.subVectors(zt,Bt),Ht.subVectors(Ft,zt),Gt.subVectors(Bt,Ft);let e=[0,-Ot.z,Ot.y,0,-Ht.z,Ht.y,0,-Gt.z,Gt.y,Ot.z,0,-Ot.x,Ht.z,0,-Ht.x,Gt.z,0,-Gt.x,-Ot.y,Ot.x,0,-Ht.y,Ht.x,0,-Gt.y,Gt.x,0];return!!jt(e,Bt,zt,Ft,kt)&&(e=[1,0,0,0,1,0,0,0,1],!!jt(e,Bt,zt,Ft,kt)&&(Vt.crossVectors(Ot,Ht),e=[Vt.x,Vt.y,Vt.z],jt(e,Bt,zt,Ft,kt)))}clampPoint(t,e){return void 0===e&&(console.warn("THREE.Box3: .clampPoint() target is now required"),e=new Lt),e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return It.copy(t).clamp(this.min,this.max).sub(t).length()}getBoundingSphere(t){return void 0===t&&console.error("THREE.Box3: .getBoundingSphere() target is now required"),this.getCenter(t.center),t.radius=.5*this.getSize(It).length(),t}intersect(t){return this.min.max(t.min),this.max.min(t.max),this.isEmpty()&&this.makeEmpty(),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}applyMatrix4(t){return this.isEmpty()||(Dt[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(t),Dt[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(t),Dt[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(t),Dt[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(t),Dt[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(t),Dt[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(t),Dt[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(t),Dt[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(t),this.setFromPoints(Dt)),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}Pt.prototype.isBox3=!0;const Dt=[new Lt,new Lt,new Lt,new Lt,new Lt,new Lt,new Lt,new Lt],It=new Lt,Nt=new Pt,Bt=new Lt,zt=new Lt,Ft=new Lt,Ot=new Lt,Ht=new Lt,Gt=new Lt,Ut=new Lt,kt=new Lt,Vt=new Lt,Wt=new Lt;function jt(t,e,n,i,r){for(let s=0,a=t.length-3;s<=a;s+=3){Wt.fromArray(t,s);const a=r.x*Math.abs(Wt.x)+r.y*Math.abs(Wt.y)+r.z*Math.abs(Wt.z),o=e.dot(Wt),l=n.dot(Wt),c=i.dot(Wt);if(Math.max(-Math.max(o,l,c),Math.min(o,l,c))>a)return!1}return!0}const qt=new Pt,Xt=new Lt,Yt=new Lt,Zt=new Lt;class Jt{constructor(t=new Lt,e=-1){this.center=t,this.radius=e}set(t,e){return this.center.copy(t),this.radius=e,this}setFromPoints(t,e){const n=this.center;void 0!==e?n.copy(e):qt.setFromPoints(t).getCenter(n);let i=0;for(let e=0,r=t.length;ethis.radius*this.radius&&(e.sub(this.center).normalize(),e.multiplyScalar(this.radius).add(this.center)),e}getBoundingBox(t){return void 0===t&&(console.warn("THREE.Sphere: .getBoundingBox() target is now required"),t=new Pt),this.isEmpty()?(t.makeEmpty(),t):(t.set(this.center,this.center),t.expandByScalar(this.radius),t)}applyMatrix4(t){return this.center.applyMatrix4(t),this.radius=this.radius*t.getMaxScaleOnAxis(),this}translate(t){return this.center.add(t),this}expandByPoint(t){Zt.subVectors(t,this.center);const e=Zt.lengthSq();if(e>this.radius*this.radius){const t=Math.sqrt(e),n=.5*(t-this.radius);this.center.add(Zt.multiplyScalar(n/t)),this.radius+=n}return this}union(t){return Yt.subVectors(t.center,this.center).normalize().multiplyScalar(t.radius),this.expandByPoint(Xt.copy(t.center).add(Yt)),this.expandByPoint(Xt.copy(t.center).sub(Yt)),this}equals(t){return t.center.equals(this.center)&&t.radius===this.radius}clone(){return(new this.constructor).copy(this)}}const Qt=new Lt,Kt=new Lt,$t=new Lt,te=new Lt,ee=new Lt,ne=new Lt,ie=new Lt;class re{constructor(t=new Lt,e=new Lt(0,0,-1)){this.origin=t,this.direction=e}set(t,e){return this.origin.copy(t),this.direction.copy(e),this}copy(t){return this.origin.copy(t.origin),this.direction.copy(t.direction),this}at(t,e){return void 0===e&&(console.warn("THREE.Ray: .at() target is now required"),e=new Lt),e.copy(this.direction).multiplyScalar(t).add(this.origin)}lookAt(t){return this.direction.copy(t).sub(this.origin).normalize(),this}recast(t){return this.origin.copy(this.at(t,Qt)),this}closestPointToPoint(t,e){void 0===e&&(console.warn("THREE.Ray: .closestPointToPoint() target is now required"),e=new Lt),e.subVectors(t,this.origin);const n=e.dot(this.direction);return n<0?e.copy(this.origin):e.copy(this.direction).multiplyScalar(n).add(this.origin)}distanceToPoint(t){return Math.sqrt(this.distanceSqToPoint(t))}distanceSqToPoint(t){const e=Qt.subVectors(t,this.origin).dot(this.direction);return e<0?this.origin.distanceToSquared(t):(Qt.copy(this.direction).multiplyScalar(e).add(this.origin),Qt.distanceToSquared(t))}distanceSqToSegment(t,e,n,i){Kt.copy(t).add(e).multiplyScalar(.5),$t.copy(e).sub(t).normalize(),te.copy(this.origin).sub(Kt);const r=.5*t.distanceTo(e),s=-this.direction.dot($t),a=te.dot(this.direction),o=-te.dot($t),l=te.lengthSq(),c=Math.abs(1-s*s);let h,u,d,p;if(c>0)if(h=s*o-a,u=s*a-o,p=r*c,h>=0)if(u>=-p)if(u<=p){const t=1/c;h*=t,u*=t,d=h*(h+s*u+2*a)+u*(s*h+u+2*o)+l}else u=r,h=Math.max(0,-(s*u+a)),d=-h*h+u*(u+2*o)+l;else u=-r,h=Math.max(0,-(s*u+a)),d=-h*h+u*(u+2*o)+l;else u<=-p?(h=Math.max(0,-(-s*r+a)),u=h>0?-r:Math.min(Math.max(-r,-o),r),d=-h*h+u*(u+2*o)+l):u<=p?(h=0,u=Math.min(Math.max(-r,-o),r),d=u*(u+2*o)+l):(h=Math.max(0,-(s*r+a)),u=h>0?r:Math.min(Math.max(-r,-o),r),d=-h*h+u*(u+2*o)+l);else u=s>0?-r:r,h=Math.max(0,-(s*u+a)),d=-h*h+u*(u+2*o)+l;return n&&n.copy(this.direction).multiplyScalar(h).add(this.origin),i&&i.copy($t).multiplyScalar(u).add(Kt),d}intersectSphere(t,e){Qt.subVectors(t.center,this.origin);const n=Qt.dot(this.direction),i=Qt.dot(Qt)-n*n,r=t.radius*t.radius;if(i>r)return null;const s=Math.sqrt(r-i),a=n-s,o=n+s;return a<0&&o<0?null:a<0?this.at(o,e):this.at(a,e)}intersectsSphere(t){return this.distanceSqToPoint(t.center)<=t.radius*t.radius}distanceToPlane(t){const e=t.normal.dot(this.direction);if(0===e)return 0===t.distanceToPoint(this.origin)?0:null;const n=-(this.origin.dot(t.normal)+t.constant)/e;return n>=0?n:null}intersectPlane(t,e){const n=this.distanceToPlane(t);return null===n?null:this.at(n,e)}intersectsPlane(t){const e=t.distanceToPoint(this.origin);if(0===e)return!0;return t.normal.dot(this.direction)*e<0}intersectBox(t,e){let n,i,r,s,a,o;const l=1/this.direction.x,c=1/this.direction.y,h=1/this.direction.z,u=this.origin;return l>=0?(n=(t.min.x-u.x)*l,i=(t.max.x-u.x)*l):(n=(t.max.x-u.x)*l,i=(t.min.x-u.x)*l),c>=0?(r=(t.min.y-u.y)*c,s=(t.max.y-u.y)*c):(r=(t.max.y-u.y)*c,s=(t.min.y-u.y)*c),n>s||r>i?null:((r>n||n!=n)&&(n=r),(s=0?(a=(t.min.z-u.z)*h,o=(t.max.z-u.z)*h):(a=(t.max.z-u.z)*h,o=(t.min.z-u.z)*h),n>o||a>i?null:((a>n||n!=n)&&(n=a),(o=0?n:i,e)))}intersectsBox(t){return null!==this.intersectBox(t,Qt)}intersectTriangle(t,e,n,i,r){ee.subVectors(e,t),ne.subVectors(n,t),ie.crossVectors(ee,ne);let s,a=this.direction.dot(ie);if(a>0){if(i)return null;s=1}else{if(!(a<0))return null;s=-1,a=-a}te.subVectors(this.origin,t);const o=s*this.direction.dot(ne.crossVectors(te,ne));if(o<0)return null;const l=s*this.direction.dot(ee.cross(te));if(l<0)return null;if(o+l>a)return null;const c=-s*te.dot(ie);return c<0?null:this.at(c/a,r)}applyMatrix4(t){return this.origin.applyMatrix4(t),this.direction.transformDirection(t),this}equals(t){return t.origin.equals(this.origin)&&t.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}class se{constructor(){this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],arguments.length>0&&console.error("THREE.Matrix4: the constructor no longer reads arguments. use .set() instead.")}set(t,e,n,i,r,s,a,o,l,c,h,u,d,p,m,f){const g=this.elements;return g[0]=t,g[4]=e,g[8]=n,g[12]=i,g[1]=r,g[5]=s,g[9]=a,g[13]=o,g[2]=l,g[6]=c,g[10]=h,g[14]=u,g[3]=d,g[7]=p,g[11]=m,g[15]=f,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return(new se).fromArray(this.elements)}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],e[9]=n[9],e[10]=n[10],e[11]=n[11],e[12]=n[12],e[13]=n[13],e[14]=n[14],e[15]=n[15],this}copyPosition(t){const e=this.elements,n=t.elements;return e[12]=n[12],e[13]=n[13],e[14]=n[14],this}setFromMatrix3(t){const e=t.elements;return this.set(e[0],e[3],e[6],0,e[1],e[4],e[7],0,e[2],e[5],e[8],0,0,0,0,1),this}extractBasis(t,e,n){return t.setFromMatrixColumn(this,0),e.setFromMatrixColumn(this,1),n.setFromMatrixColumn(this,2),this}makeBasis(t,e,n){return this.set(t.x,e.x,n.x,0,t.y,e.y,n.y,0,t.z,e.z,n.z,0,0,0,0,1),this}extractRotation(t){const e=this.elements,n=t.elements,i=1/ae.setFromMatrixColumn(t,0).length(),r=1/ae.setFromMatrixColumn(t,1).length(),s=1/ae.setFromMatrixColumn(t,2).length();return e[0]=n[0]*i,e[1]=n[1]*i,e[2]=n[2]*i,e[3]=0,e[4]=n[4]*r,e[5]=n[5]*r,e[6]=n[6]*r,e[7]=0,e[8]=n[8]*s,e[9]=n[9]*s,e[10]=n[10]*s,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromEuler(t){t&&t.isEuler||console.error("THREE.Matrix4: .makeRotationFromEuler() now expects a Euler rotation rather than a Vector3 and order.");const e=this.elements,n=t.x,i=t.y,r=t.z,s=Math.cos(n),a=Math.sin(n),o=Math.cos(i),l=Math.sin(i),c=Math.cos(r),h=Math.sin(r);if("XYZ"===t.order){const t=s*c,n=s*h,i=a*c,r=a*h;e[0]=o*c,e[4]=-o*h,e[8]=l,e[1]=n+i*l,e[5]=t-r*l,e[9]=-a*o,e[2]=r-t*l,e[6]=i+n*l,e[10]=s*o}else if("YXZ"===t.order){const t=o*c,n=o*h,i=l*c,r=l*h;e[0]=t+r*a,e[4]=i*a-n,e[8]=s*l,e[1]=s*h,e[5]=s*c,e[9]=-a,e[2]=n*a-i,e[6]=r+t*a,e[10]=s*o}else if("ZXY"===t.order){const t=o*c,n=o*h,i=l*c,r=l*h;e[0]=t-r*a,e[4]=-s*h,e[8]=i+n*a,e[1]=n+i*a,e[5]=s*c,e[9]=r-t*a,e[2]=-s*l,e[6]=a,e[10]=s*o}else if("ZYX"===t.order){const t=s*c,n=s*h,i=a*c,r=a*h;e[0]=o*c,e[4]=i*l-n,e[8]=t*l+r,e[1]=o*h,e[5]=r*l+t,e[9]=n*l-i,e[2]=-l,e[6]=a*o,e[10]=s*o}else if("YZX"===t.order){const t=s*o,n=s*l,i=a*o,r=a*l;e[0]=o*c,e[4]=r-t*h,e[8]=i*h+n,e[1]=h,e[5]=s*c,e[9]=-a*c,e[2]=-l*c,e[6]=n*h+i,e[10]=t-r*h}else if("XZY"===t.order){const t=s*o,n=s*l,i=a*o,r=a*l;e[0]=o*c,e[4]=-h,e[8]=l*c,e[1]=t*h+r,e[5]=s*c,e[9]=n*h-i,e[2]=i*h-n,e[6]=a*c,e[10]=r*h+t}return e[3]=0,e[7]=0,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromQuaternion(t){return this.compose(le,t,ce)}lookAt(t,e,n){const i=this.elements;return de.subVectors(t,e),0===de.lengthSq()&&(de.z=1),de.normalize(),he.crossVectors(n,de),0===he.lengthSq()&&(1===Math.abs(n.z)?de.x+=1e-4:de.z+=1e-4,de.normalize(),he.crossVectors(n,de)),he.normalize(),ue.crossVectors(de,he),i[0]=he.x,i[4]=ue.x,i[8]=de.x,i[1]=he.y,i[5]=ue.y,i[9]=de.y,i[2]=he.z,i[6]=ue.z,i[10]=de.z,this}multiply(t,e){return void 0!==e?(console.warn("THREE.Matrix4: .multiply() now only accepts one argument. Use .multiplyMatrices( a, b ) instead."),this.multiplyMatrices(t,e)):this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,r=this.elements,s=n[0],a=n[4],o=n[8],l=n[12],c=n[1],h=n[5],u=n[9],d=n[13],p=n[2],m=n[6],f=n[10],g=n[14],v=n[3],y=n[7],x=n[11],_=n[15],w=i[0],b=i[4],M=i[8],S=i[12],T=i[1],E=i[5],A=i[9],L=i[13],R=i[2],C=i[6],P=i[10],D=i[14],I=i[3],N=i[7],B=i[11],z=i[15];return r[0]=s*w+a*T+o*R+l*I,r[4]=s*b+a*E+o*C+l*N,r[8]=s*M+a*A+o*P+l*B,r[12]=s*S+a*L+o*D+l*z,r[1]=c*w+h*T+u*R+d*I,r[5]=c*b+h*E+u*C+d*N,r[9]=c*M+h*A+u*P+d*B,r[13]=c*S+h*L+u*D+d*z,r[2]=p*w+m*T+f*R+g*I,r[6]=p*b+m*E+f*C+g*N,r[10]=p*M+m*A+f*P+g*B,r[14]=p*S+m*L+f*D+g*z,r[3]=v*w+y*T+x*R+_*I,r[7]=v*b+y*E+x*C+_*N,r[11]=v*M+y*A+x*P+_*B,r[15]=v*S+y*L+x*D+_*z,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[4]*=t,e[8]*=t,e[12]*=t,e[1]*=t,e[5]*=t,e[9]*=t,e[13]*=t,e[2]*=t,e[6]*=t,e[10]*=t,e[14]*=t,e[3]*=t,e[7]*=t,e[11]*=t,e[15]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[4],i=t[8],r=t[12],s=t[1],a=t[5],o=t[9],l=t[13],c=t[2],h=t[6],u=t[10],d=t[14];return t[3]*(+r*o*h-i*l*h-r*a*u+n*l*u+i*a*d-n*o*d)+t[7]*(+e*o*d-e*l*u+r*s*u-i*s*d+i*l*c-r*o*c)+t[11]*(+e*l*h-e*a*d-r*s*h+n*s*d+r*a*c-n*l*c)+t[15]*(-i*a*c-e*o*h+e*a*u+i*s*h-n*s*u+n*o*c)}transpose(){const t=this.elements;let e;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}setPosition(t,e,n){const i=this.elements;return t.isVector3?(i[12]=t.x,i[13]=t.y,i[14]=t.z):(i[12]=t,i[13]=e,i[14]=n),this}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],r=t[3],s=t[4],a=t[5],o=t[6],l=t[7],c=t[8],h=t[9],u=t[10],d=t[11],p=t[12],m=t[13],f=t[14],g=t[15],v=h*f*l-m*u*l+m*o*d-a*f*d-h*o*g+a*u*g,y=p*u*l-c*f*l-p*o*d+s*f*d+c*o*g-s*u*g,x=c*m*l-p*h*l+p*a*d-s*m*d-c*a*g+s*h*g,_=p*h*o-c*m*o-p*a*u+s*m*u+c*a*f-s*h*f,w=e*v+n*y+i*x+r*_;if(0===w)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const b=1/w;return t[0]=v*b,t[1]=(m*u*r-h*f*r-m*i*d+n*f*d+h*i*g-n*u*g)*b,t[2]=(a*f*r-m*o*r+m*i*l-n*f*l-a*i*g+n*o*g)*b,t[3]=(h*o*r-a*u*r-h*i*l+n*u*l+a*i*d-n*o*d)*b,t[4]=y*b,t[5]=(c*f*r-p*u*r+p*i*d-e*f*d-c*i*g+e*u*g)*b,t[6]=(p*o*r-s*f*r-p*i*l+e*f*l+s*i*g-e*o*g)*b,t[7]=(s*u*r-c*o*r+c*i*l-e*u*l-s*i*d+e*o*d)*b,t[8]=x*b,t[9]=(p*h*r-c*m*r-p*n*d+e*m*d+c*n*g-e*h*g)*b,t[10]=(s*m*r-p*a*r+p*n*l-e*m*l-s*n*g+e*a*g)*b,t[11]=(c*a*r-s*h*r-c*n*l+e*h*l+s*n*d-e*a*d)*b,t[12]=_*b,t[13]=(c*m*i-p*h*i+p*n*u-e*m*u-c*n*f+e*h*f)*b,t[14]=(p*a*i-s*m*i-p*n*o+e*m*o+s*n*f-e*a*f)*b,t[15]=(s*h*i-c*a*i+c*n*o-e*h*o-s*n*u+e*a*u)*b,this}scale(t){const e=this.elements,n=t.x,i=t.y,r=t.z;return e[0]*=n,e[4]*=i,e[8]*=r,e[1]*=n,e[5]*=i,e[9]*=r,e[2]*=n,e[6]*=i,e[10]*=r,e[3]*=n,e[7]*=i,e[11]*=r,this}getMaxScaleOnAxis(){const t=this.elements,e=t[0]*t[0]+t[1]*t[1]+t[2]*t[2],n=t[4]*t[4]+t[5]*t[5]+t[6]*t[6],i=t[8]*t[8]+t[9]*t[9]+t[10]*t[10];return Math.sqrt(Math.max(e,n,i))}makeTranslation(t,e,n){return this.set(1,0,0,t,0,1,0,e,0,0,1,n,0,0,0,1),this}makeRotationX(t){const e=Math.cos(t),n=Math.sin(t);return this.set(1,0,0,0,0,e,-n,0,0,n,e,0,0,0,0,1),this}makeRotationY(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,0,n,0,0,1,0,0,-n,0,e,0,0,0,0,1),this}makeRotationZ(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,-n,0,0,n,e,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(t,e){const n=Math.cos(e),i=Math.sin(e),r=1-n,s=t.x,a=t.y,o=t.z,l=r*s,c=r*a;return this.set(l*s+n,l*a-i*o,l*o+i*a,0,l*a+i*o,c*a+n,c*o-i*s,0,l*o-i*a,c*o+i*s,r*o*o+n,0,0,0,0,1),this}makeScale(t,e,n){return this.set(t,0,0,0,0,e,0,0,0,0,n,0,0,0,0,1),this}makeShear(t,e,n){return this.set(1,e,n,0,t,1,n,0,t,e,1,0,0,0,0,1),this}compose(t,e,n){const i=this.elements,r=e._x,s=e._y,a=e._z,o=e._w,l=r+r,c=s+s,h=a+a,u=r*l,d=r*c,p=r*h,m=s*c,f=s*h,g=a*h,v=o*l,y=o*c,x=o*h,_=n.x,w=n.y,b=n.z;return i[0]=(1-(m+g))*_,i[1]=(d+x)*_,i[2]=(p-y)*_,i[3]=0,i[4]=(d-x)*w,i[5]=(1-(u+g))*w,i[6]=(f+v)*w,i[7]=0,i[8]=(p+y)*b,i[9]=(f-v)*b,i[10]=(1-(u+m))*b,i[11]=0,i[12]=t.x,i[13]=t.y,i[14]=t.z,i[15]=1,this}decompose(t,e,n){const i=this.elements;let r=ae.set(i[0],i[1],i[2]).length();const s=ae.set(i[4],i[5],i[6]).length(),a=ae.set(i[8],i[9],i[10]).length();this.determinant()<0&&(r=-r),t.x=i[12],t.y=i[13],t.z=i[14],oe.copy(this);const o=1/r,l=1/s,c=1/a;return oe.elements[0]*=o,oe.elements[1]*=o,oe.elements[2]*=o,oe.elements[4]*=l,oe.elements[5]*=l,oe.elements[6]*=l,oe.elements[8]*=c,oe.elements[9]*=c,oe.elements[10]*=c,e.setFromRotationMatrix(oe),n.x=r,n.y=s,n.z=a,this}makePerspective(t,e,n,i,r,s){void 0===s&&console.warn("THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.");const a=this.elements,o=2*r/(e-t),l=2*r/(n-i),c=(e+t)/(e-t),h=(n+i)/(n-i),u=-(s+r)/(s-r),d=-2*s*r/(s-r);return a[0]=o,a[4]=0,a[8]=c,a[12]=0,a[1]=0,a[5]=l,a[9]=h,a[13]=0,a[2]=0,a[6]=0,a[10]=u,a[14]=d,a[3]=0,a[7]=0,a[11]=-1,a[15]=0,this}makeOrthographic(t,e,n,i,r,s){const a=this.elements,o=1/(e-t),l=1/(n-i),c=1/(s-r),h=(e+t)*o,u=(n+i)*l,d=(s+r)*c;return a[0]=2*o,a[4]=0,a[8]=0,a[12]=-h,a[1]=0,a[5]=2*l,a[9]=0,a[13]=-u,a[2]=0,a[6]=0,a[10]=-2*c,a[14]=-d,a[3]=0,a[7]=0,a[11]=0,a[15]=1,this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<16;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<16;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t[e+9]=n[9],t[e+10]=n[10],t[e+11]=n[11],t[e+12]=n[12],t[e+13]=n[13],t[e+14]=n[14],t[e+15]=n[15],t}}se.prototype.isMatrix4=!0;const ae=new Lt,oe=new se,le=new Lt(0,0,0),ce=new Lt(1,1,1),he=new Lt,ue=new Lt,de=new Lt,pe=new se,me=new At;class fe{constructor(t=0,e=0,n=0,i=fe.DefaultOrder){this._x=t,this._y=e,this._z=n,this._order=i}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get order(){return this._order}set order(t){this._order=t,this._onChangeCallback()}set(t,e,n,i){return this._x=t,this._y=e,this._z=n,this._order=i||this._order,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(t){return this._x=t._x,this._y=t._y,this._z=t._z,this._order=t._order,this._onChangeCallback(),this}setFromRotationMatrix(t,e,n){const i=t.elements,r=i[0],s=i[4],a=i[8],o=i[1],l=i[5],c=i[9],h=i[2],u=i[6],d=i[10];switch(e=e||this._order){case"XYZ":this._y=Math.asin(ht(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-c,d),this._z=Math.atan2(-s,r)):(this._x=Math.atan2(u,l),this._z=0);break;case"YXZ":this._x=Math.asin(-ht(c,-1,1)),Math.abs(c)<.9999999?(this._y=Math.atan2(a,d),this._z=Math.atan2(o,l)):(this._y=Math.atan2(-h,r),this._z=0);break;case"ZXY":this._x=Math.asin(ht(u,-1,1)),Math.abs(u)<.9999999?(this._y=Math.atan2(-h,d),this._z=Math.atan2(-s,l)):(this._y=0,this._z=Math.atan2(o,r));break;case"ZYX":this._y=Math.asin(-ht(h,-1,1)),Math.abs(h)<.9999999?(this._x=Math.atan2(u,d),this._z=Math.atan2(o,r)):(this._x=0,this._z=Math.atan2(-s,l));break;case"YZX":this._z=Math.asin(ht(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-c,l),this._y=Math.atan2(-h,r)):(this._x=0,this._y=Math.atan2(a,d));break;case"XZY":this._z=Math.asin(-ht(s,-1,1)),Math.abs(s)<.9999999?(this._x=Math.atan2(u,l),this._y=Math.atan2(a,r)):(this._x=Math.atan2(-c,d),this._y=0);break;default:console.warn("THREE.Euler: .setFromRotationMatrix() encountered an unknown order: "+e)}return this._order=e,!1!==n&&this._onChangeCallback(),this}setFromQuaternion(t,e,n){return pe.makeRotationFromQuaternion(t),this.setFromRotationMatrix(pe,e,n)}setFromVector3(t,e){return this.set(t.x,t.y,t.z,e||this._order)}reorder(t){return me.setFromEuler(this),this.setFromQuaternion(me,t)}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._order===this._order}fromArray(t){return this._x=t[0],this._y=t[1],this._z=t[2],void 0!==t[3]&&(this._order=t[3]),this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._order,t}toVector3(t){return t?t.set(this._x,this._y,this._z):new Lt(this._x,this._y,this._z)}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}fe.prototype.isEuler=!0,fe.DefaultOrder="XYZ",fe.RotationOrders=["XYZ","YZX","ZXY","XZY","YXZ","ZYX"];class ge{constructor(){this.mask=1}set(t){this.mask=1<1){for(let t=0;t1){for(let t=0;t0){i.children=[];for(let e=0;e0){i.animations=[];for(let e=0;e0&&(n.geometries=e),i.length>0&&(n.materials=i),r.length>0&&(n.textures=r),a.length>0&&(n.images=a),o.length>0&&(n.shapes=o),l.length>0&&(n.skeletons=l),c.length>0&&(n.animations=c)}return n.object=i,n;function s(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}}clone(t){return(new this.constructor).copy(this,t)}copy(t,e=!0){if(this.name=t.name,this.up.copy(t.up),this.position.copy(t.position),this.rotation.order=t.rotation.order,this.quaternion.copy(t.quaternion),this.scale.copy(t.scale),this.matrix.copy(t.matrix),this.matrixWorld.copy(t.matrixWorld),this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrixWorldNeedsUpdate=t.matrixWorldNeedsUpdate,this.layers.mask=t.layers.mask,this.visible=t.visible,this.castShadow=t.castShadow,this.receiveShadow=t.receiveShadow,this.frustumCulled=t.frustumCulled,this.renderOrder=t.renderOrder,this.userData=JSON.parse(JSON.stringify(t.userData)),!0===e)for(let e=0;e1?null:e.copy(n).multiplyScalar(r).add(t.start)}intersectsLine(t){const e=this.distanceToPoint(t.start),n=this.distanceToPoint(t.end);return e<0&&n>0||n<0&&e>0}intersectsBox(t){return t.intersectsPlane(this)}intersectsSphere(t){return t.intersectsPlane(this)}coplanarPoint(t){return void 0===t&&(console.warn("THREE.Plane: .coplanarPoint() target is now required"),t=new Lt),t.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(t,e){const n=e||Ie.getNormalMatrix(t),i=this.coplanarPoint(Pe).applyMatrix4(t),r=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(r),this}translate(t){return this.constant-=t.dot(this.normal),this}equals(t){return t.normal.equals(this.normal)&&t.constant===this.constant}clone(){return(new this.constructor).copy(this)}}Ne.prototype.isPlane=!0;const Be=new Lt,ze=new Lt,Fe=new Lt,Oe=new Lt,He=new Lt,Ge=new Lt,Ue=new Lt,ke=new Lt,Ve=new Lt,We=new Lt;class je{constructor(t=new Lt,e=new Lt,n=new Lt){this.a=t,this.b=e,this.c=n}static getNormal(t,e,n,i){void 0===i&&(console.warn("THREE.Triangle: .getNormal() target is now required"),i=new Lt),i.subVectors(n,e),Be.subVectors(t,e),i.cross(Be);const r=i.lengthSq();return r>0?i.multiplyScalar(1/Math.sqrt(r)):i.set(0,0,0)}static getBarycoord(t,e,n,i,r){Be.subVectors(i,e),ze.subVectors(n,e),Fe.subVectors(t,e);const s=Be.dot(Be),a=Be.dot(ze),o=Be.dot(Fe),l=ze.dot(ze),c=ze.dot(Fe),h=s*l-a*a;if(void 0===r&&(console.warn("THREE.Triangle: .getBarycoord() target is now required"),r=new Lt),0===h)return r.set(-2,-1,-1);const u=1/h,d=(l*o-a*c)*u,p=(s*c-a*o)*u;return r.set(1-d-p,p,d)}static containsPoint(t,e,n,i){return this.getBarycoord(t,e,n,i,Oe),Oe.x>=0&&Oe.y>=0&&Oe.x+Oe.y<=1}static getUV(t,e,n,i,r,s,a,o){return this.getBarycoord(t,e,n,i,Oe),o.set(0,0),o.addScaledVector(r,Oe.x),o.addScaledVector(s,Oe.y),o.addScaledVector(a,Oe.z),o}static isFrontFacing(t,e,n,i){return Be.subVectors(n,e),ze.subVectors(t,e),Be.cross(ze).dot(i)<0}set(t,e,n){return this.a.copy(t),this.b.copy(e),this.c.copy(n),this}setFromPointsAndIndices(t,e,n,i){return this.a.copy(t[e]),this.b.copy(t[n]),this.c.copy(t[i]),this}clone(){return(new this.constructor).copy(this)}copy(t){return this.a.copy(t.a),this.b.copy(t.b),this.c.copy(t.c),this}getArea(){return Be.subVectors(this.c,this.b),ze.subVectors(this.a,this.b),.5*Be.cross(ze).length()}getMidpoint(t){return void 0===t&&(console.warn("THREE.Triangle: .getMidpoint() target is now required"),t=new Lt),t.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(t){return je.getNormal(this.a,this.b,this.c,t)}getPlane(t){return void 0===t&&(console.warn("THREE.Triangle: .getPlane() target is now required"),t=new Ne),t.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(t,e){return je.getBarycoord(t,this.a,this.b,this.c,e)}getUV(t,e,n,i,r){return je.getUV(t,this.a,this.b,this.c,e,n,i,r)}containsPoint(t){return je.containsPoint(t,this.a,this.b,this.c)}isFrontFacing(t){return je.isFrontFacing(this.a,this.b,this.c,t)}intersectsBox(t){return t.intersectsTriangle(this)}closestPointToPoint(t,e){void 0===e&&(console.warn("THREE.Triangle: .closestPointToPoint() target is now required"),e=new Lt);const n=this.a,i=this.b,r=this.c;let s,a;He.subVectors(i,n),Ge.subVectors(r,n),ke.subVectors(t,n);const o=He.dot(ke),l=Ge.dot(ke);if(o<=0&&l<=0)return e.copy(n);Ve.subVectors(t,i);const c=He.dot(Ve),h=Ge.dot(Ve);if(c>=0&&h<=c)return e.copy(i);const u=o*h-c*l;if(u<=0&&o>=0&&c<=0)return s=o/(o-c),e.copy(n).addScaledVector(He,s);We.subVectors(t,r);const d=He.dot(We),p=Ge.dot(We);if(p>=0&&d<=p)return e.copy(r);const m=d*l-o*p;if(m<=0&&l>=0&&p<=0)return a=l/(l-p),e.copy(n).addScaledVector(Ge,a);const f=c*p-d*h;if(f<=0&&h-c>=0&&d-p>=0)return Ue.subVectors(r,i),a=(h-c)/(h-c+(d-p)),e.copy(i).addScaledVector(Ue,a);const g=1/(f+m+u);return s=m*g,a=u*g,e.copy(n).addScaledVector(He,s).addScaledVector(Ge,a)}equals(t){return t.a.equals(this.a)&&t.b.equals(this.b)&&t.c.equals(this.c)}}let qe=0;function Xe(){Object.defineProperty(this,"id",{value:qe++}),this.uuid=ct(),this.name="",this.type="Material",this.fog=!0,this.blending=1,this.side=0,this.vertexColors=!1,this.opacity=1,this.transparent=!1,this.blendSrc=204,this.blendDst=205,this.blendEquation=n,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.depthFunc=3,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=519,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=tt,this.stencilZFail=tt,this.stencilZPass=tt,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaTest=0,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0}Xe.prototype=Object.assign(Object.create(rt.prototype),{constructor:Xe,isMaterial:!0,onBuild:function(){},onBeforeCompile:function(){},customProgramCacheKey:function(){return this.onBeforeCompile.toString()},setValues:function(t){if(void 0!==t)for(const e in t){const n=t[e];if(void 0===n){console.warn("THREE.Material: '"+e+"' parameter is undefined.");continue}if("shading"===e){console.warn("THREE."+this.type+": .shading has been removed. Use the boolean .flatShading instead."),this.flatShading=1===n;continue}const i=this[e];void 0!==i?i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[e]=n:console.warn("THREE."+this.type+": '"+e+"' is not a property of this material.")}},toJSON:function(t){const e=void 0===t||"string"==typeof t;e&&(t={textures:{},images:{}});const n={metadata:{version:4.5,type:"Material",generator:"Material.toJSON"}};function i(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}if(n.uuid=this.uuid,n.type=this.type,""!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),this.sheen&&this.sheen.isColor&&(n.sheen=this.sheen.getHex()),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(t).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(t).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(t).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(t).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(t).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(t).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(t).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(t).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(t).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(t).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(t).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(t).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(t).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(t).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(t).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(t).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(t).uuid),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),1!==this.blending&&(n.blending=this.blending),0!==this.side&&(n.side=this.side),this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),!0===this.transparent&&(n.transparent=this.transparent),n.depthFunc=this.depthFunc,n.depthTest=this.depthTest,n.depthWrite=this.depthWrite,n.colorWrite=this.colorWrite,n.stencilWrite=this.stencilWrite,n.stencilWriteMask=this.stencilWriteMask,n.stencilFunc=this.stencilFunc,n.stencilRef=this.stencilRef,n.stencilFuncMask=this.stencilFuncMask,n.stencilFail=this.stencilFail,n.stencilZFail=this.stencilZFail,n.stencilZPass=this.stencilZPass,this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(n.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=this.premultipliedAlpha),!0===this.wireframe&&(n.wireframe=this.wireframe),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),"round"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),"round"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.morphTargets&&(n.morphTargets=!0),!0===this.morphNormals&&(n.morphNormals=!0),!0===this.skinning&&(n.skinning=!0),!0===this.flatShading&&(n.flatShading=this.flatShading),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),"{}"!==JSON.stringify(this.userData)&&(n.userData=this.userData),e){const e=i(t.textures),r=i(t.images);e.length>0&&(n.textures=e),r.length>0&&(n.images=r)}return n},clone:function(){return(new this.constructor).copy(this)},copy:function(t){this.name=t.name,this.fog=t.fog,this.blending=t.blending,this.side=t.side,this.vertexColors=t.vertexColors,this.opacity=t.opacity,this.transparent=t.transparent,this.blendSrc=t.blendSrc,this.blendDst=t.blendDst,this.blendEquation=t.blendEquation,this.blendSrcAlpha=t.blendSrcAlpha,this.blendDstAlpha=t.blendDstAlpha,this.blendEquationAlpha=t.blendEquationAlpha,this.depthFunc=t.depthFunc,this.depthTest=t.depthTest,this.depthWrite=t.depthWrite,this.stencilWriteMask=t.stencilWriteMask,this.stencilFunc=t.stencilFunc,this.stencilRef=t.stencilRef,this.stencilFuncMask=t.stencilFuncMask,this.stencilFail=t.stencilFail,this.stencilZFail=t.stencilZFail,this.stencilZPass=t.stencilZPass,this.stencilWrite=t.stencilWrite;const e=t.clippingPlanes;let n=null;if(null!==e){const t=e.length;n=new Array(t);for(let i=0;i!==t;++i)n[i]=e[i].clone()}return this.clippingPlanes=n,this.clipIntersection=t.clipIntersection,this.clipShadows=t.clipShadows,this.shadowSide=t.shadowSide,this.colorWrite=t.colorWrite,this.precision=t.precision,this.polygonOffset=t.polygonOffset,this.polygonOffsetFactor=t.polygonOffsetFactor,this.polygonOffsetUnits=t.polygonOffsetUnits,this.dithering=t.dithering,this.alphaTest=t.alphaTest,this.alphaToCoverage=t.alphaToCoverage,this.premultipliedAlpha=t.premultipliedAlpha,this.visible=t.visible,this.toneMapped=t.toneMapped,this.userData=JSON.parse(JSON.stringify(t.userData)),this},dispose:function(){this.dispatchEvent({type:"dispose"})}}),Object.defineProperty(Xe.prototype,"needsUpdate",{set:function(t){!0===t&&this.version++}});const Ye={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},Ze={h:0,s:0,l:0},Je={h:0,s:0,l:0};function Qe(t,e,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?t+6*(e-t)*n:n<.5?e:n<2/3?t+6*(e-t)*(2/3-n):t}function Ke(t){return t<.04045?.0773993808*t:Math.pow(.9478672986*t+.0521327014,2.4)}function $e(t){return t<.0031308?12.92*t:1.055*Math.pow(t,.41666)-.055}class tn{constructor(t,e,n){return void 0===e&&void 0===n?this.set(t):this.setRGB(t,e,n)}set(t){return t&&t.isColor?this.copy(t):"number"==typeof t?this.setHex(t):"string"==typeof t&&this.setStyle(t),this}setScalar(t){return this.r=t,this.g=t,this.b=t,this}setHex(t){return t=Math.floor(t),this.r=(t>>16&255)/255,this.g=(t>>8&255)/255,this.b=(255&t)/255,this}setRGB(t,e,n){return this.r=t,this.g=e,this.b=n,this}setHSL(t,e,n){if(t=ut(t,1),e=ht(e,0,1),n=ht(n,0,1),0===e)this.r=this.g=this.b=n;else{const i=n<=.5?n*(1+e):n+e-n*e,r=2*n-i;this.r=Qe(r,i,t+1/3),this.g=Qe(r,i,t),this.b=Qe(r,i,t-1/3)}return this}setStyle(t){function e(e){void 0!==e&&parseFloat(e)<1&&console.warn("THREE.Color: Alpha component of "+t+" will be ignored.")}let n;if(n=/^((?:rgb|hsl)a?)\(([^\)]*)\)/.exec(t)){let t;const i=n[1],r=n[2];switch(i){case"rgb":case"rgba":if(t=/^\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(r))return this.r=Math.min(255,parseInt(t[1],10))/255,this.g=Math.min(255,parseInt(t[2],10))/255,this.b=Math.min(255,parseInt(t[3],10))/255,e(t[4]),this;if(t=/^\s*(\d+)\%\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(r))return this.r=Math.min(100,parseInt(t[1],10))/100,this.g=Math.min(100,parseInt(t[2],10))/100,this.b=Math.min(100,parseInt(t[3],10))/100,e(t[4]),this;break;case"hsl":case"hsla":if(t=/^\s*(\d*\.?\d+)\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(r)){const n=parseFloat(t[1])/360,i=parseInt(t[2],10)/100,r=parseInt(t[3],10)/100;return e(t[4]),this.setHSL(n,i,r)}}}else if(n=/^\#([A-Fa-f\d]+)$/.exec(t)){const t=n[1],e=t.length;if(3===e)return this.r=parseInt(t.charAt(0)+t.charAt(0),16)/255,this.g=parseInt(t.charAt(1)+t.charAt(1),16)/255,this.b=parseInt(t.charAt(2)+t.charAt(2),16)/255,this;if(6===e)return this.r=parseInt(t.charAt(0)+t.charAt(1),16)/255,this.g=parseInt(t.charAt(2)+t.charAt(3),16)/255,this.b=parseInt(t.charAt(4)+t.charAt(5),16)/255,this}return t&&t.length>0?this.setColorName(t):this}setColorName(t){const e=Ye[t.toLowerCase()];return void 0!==e?this.setHex(e):console.warn("THREE.Color: Unknown color "+t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(t){return this.r=t.r,this.g=t.g,this.b=t.b,this}copyGammaToLinear(t,e=2){return this.r=Math.pow(t.r,e),this.g=Math.pow(t.g,e),this.b=Math.pow(t.b,e),this}copyLinearToGamma(t,e=2){const n=e>0?1/e:1;return this.r=Math.pow(t.r,n),this.g=Math.pow(t.g,n),this.b=Math.pow(t.b,n),this}convertGammaToLinear(t){return this.copyGammaToLinear(this,t),this}convertLinearToGamma(t){return this.copyLinearToGamma(this,t),this}copySRGBToLinear(t){return this.r=Ke(t.r),this.g=Ke(t.g),this.b=Ke(t.b),this}copyLinearToSRGB(t){return this.r=$e(t.r),this.g=$e(t.g),this.b=$e(t.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(){return 255*this.r<<16^255*this.g<<8^255*this.b<<0}getHexString(){return("000000"+this.getHex().toString(16)).slice(-6)}getHSL(t){void 0===t&&(console.warn("THREE.Color: .getHSL() target is now required"),t={h:0,s:0,l:0});const e=this.r,n=this.g,i=this.b,r=Math.max(e,n,i),s=Math.min(e,n,i);let a,o;const l=(s+r)/2;if(s===r)a=0,o=0;else{const t=r-s;switch(o=l<=.5?t/(r+s):t/(2-r-s),r){case e:a=(n-i)/t+(ne&&(e=t[n]);return e}const vn={Int8Array:Int8Array,Uint8Array:Uint8Array,Uint8ClampedArray:Uint8ClampedArray,Int16Array:Int16Array,Uint16Array:Uint16Array,Int32Array:Int32Array,Uint32Array:Uint32Array,Float32Array:Float32Array,Float64Array:Float64Array};function yn(t,e){return new vn[t](e)}let xn=0;const _n=new se,wn=new Ce,bn=new Lt,Mn=new Pt,Sn=new Pt,Tn=new Lt;class En extends rt{constructor(){super(),Object.defineProperty(this,"id",{value:xn++}),this.uuid=ct(),this.name="",this.type="BufferGeometry",this.index=null,this.attributes={},this.morphAttributes={},this.morphTargetsRelative=!1,this.groups=[],this.boundingBox=null,this.boundingSphere=null,this.drawRange={start:0,count:1/0},this.userData={}}getIndex(){return this.index}setIndex(t){return Array.isArray(t)?this.index=new(gn(t)>65535?dn:hn)(t,1):this.index=t,this}getAttribute(t){return this.attributes[t]}setAttribute(t,e){return this.attributes[t]=e,this}deleteAttribute(t){return delete this.attributes[t],this}hasAttribute(t){return void 0!==this.attributes[t]}addGroup(t,e,n=0){this.groups.push({start:t,count:e,materialIndex:n})}clearGroups(){this.groups=[]}setDrawRange(t,e){this.drawRange.start=t,this.drawRange.count=e}applyMatrix4(t){const e=this.attributes.position;void 0!==e&&(e.applyMatrix4(t),e.needsUpdate=!0);const n=this.attributes.normal;if(void 0!==n){const e=(new yt).getNormalMatrix(t);n.applyNormalMatrix(e),n.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(t),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}rotateX(t){return _n.makeRotationX(t),this.applyMatrix4(_n),this}rotateY(t){return _n.makeRotationY(t),this.applyMatrix4(_n),this}rotateZ(t){return _n.makeRotationZ(t),this.applyMatrix4(_n),this}translate(t,e,n){return _n.makeTranslation(t,e,n),this.applyMatrix4(_n),this}scale(t,e,n){return _n.makeScale(t,e,n),this.applyMatrix4(_n),this}lookAt(t){return wn.lookAt(t),wn.updateMatrix(),this.applyMatrix4(wn.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(bn).negate(),this.translate(bn.x,bn.y,bn.z),this}setFromPoints(t){const e=[];for(let n=0,i=t.length;n0&&(t.userData=this.userData),void 0!==this.parameters){const e=this.parameters;for(const n in e)void 0!==e[n]&&(t[n]=e[n]);return t}t.data={attributes:{}};const e=this.index;null!==e&&(t.data.index={type:e.array.constructor.name,array:Array.prototype.slice.call(e.array)});const n=this.attributes;for(const e in n){const i=n[e];t.data.attributes[e]=i.toJSON(t.data)}const i={};let r=!1;for(const e in this.morphAttributes){const n=this.morphAttributes[e],s=[];for(let e=0,i=n.length;e0&&(i[e]=s,r=!0)}r&&(t.data.morphAttributes=i,t.data.morphTargetsRelative=this.morphTargetsRelative);const s=this.groups;s.length>0&&(t.data.groups=JSON.parse(JSON.stringify(s)));const a=this.boundingSphere;return null!==a&&(t.data.boundingSphere={center:a.center.toArray(),radius:a.radius}),t}clone(){return(new En).copy(this)}copy(t){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const e={};this.name=t.name;const n=t.index;null!==n&&this.setIndex(n.clone(e));const i=t.attributes;for(const t in i){const n=i[t];this.setAttribute(t,n.clone(e))}const r=t.morphAttributes;for(const t in r){const n=[],i=r[t];for(let t=0,r=i.length;t0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error("THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.")}}raycast(t,e){const n=this.geometry,i=this.material,r=this.matrixWorld;if(void 0===i)return;if(null===n.boundingSphere&&n.computeBoundingSphere(),Rn.copy(n.boundingSphere),Rn.applyMatrix4(r),!1===t.ray.intersectsSphere(Rn))return;if(An.copy(r).invert(),Ln.copy(t.ray).applyMatrix4(An),null!==n.boundingBox&&!1===Ln.intersectsBox(n.boundingBox))return;let s;if(n.isBufferGeometry){const r=n.index,a=n.attributes.position,o=n.morphAttributes.position,l=n.morphTargetsRelative,c=n.attributes.uv,h=n.attributes.uv2,u=n.groups,d=n.drawRange;if(null!==r)if(Array.isArray(i))for(let n=0,p=u.length;nn.far?null:{distance:c,point:Vn.clone(),object:t}}(t,e,n,i,Cn,Pn,Dn,kn);if(p){o&&(Hn.fromBufferAttribute(o,c),Gn.fromBufferAttribute(o,h),Un.fromBufferAttribute(o,u),p.uv=je.getUV(kn,Cn,Pn,Dn,Hn,Gn,Un,new vt)),l&&(Hn.fromBufferAttribute(l,c),Gn.fromBufferAttribute(l,h),Un.fromBufferAttribute(l,u),p.uv2=je.getUV(kn,Cn,Pn,Dn,Hn,Gn,Un,new vt));const t={a:c,b:h,c:u,normal:new Lt,materialIndex:0};je.getNormal(Cn,Pn,Dn,t.normal),p.face=t}return p}Wn.prototype.isMesh=!0;class qn extends En{constructor(t=1,e=1,n=1,i=1,r=1,s=1){super(),this.type="BoxGeometry",this.parameters={width:t,height:e,depth:n,widthSegments:i,heightSegments:r,depthSegments:s};const a=this;i=Math.floor(i),r=Math.floor(r),s=Math.floor(s);const o=[],l=[],c=[],h=[];let u=0,d=0;function p(t,e,n,i,r,s,p,m,f,g,v){const y=s/f,x=p/g,_=s/2,w=p/2,b=m/2,M=f+1,S=g+1;let T=0,E=0;const A=new Lt;for(let s=0;s0?1:-1,c.push(A.x,A.y,A.z),h.push(o/f),h.push(1-s/g),T+=1}}for(let t=0;t0&&(e.defines=this.defines),e.vertexShader=this.vertexShader,e.fragmentShader=this.fragmentShader;const n={};for(const t in this.extensions)!0===this.extensions[t]&&(n[t]=!0);return Object.keys(n).length>0&&(e.extensions=n),e}}Jn.prototype.isShaderMaterial=!0;class Qn extends Ce{constructor(){super(),this.type="Camera",this.matrixWorldInverse=new se,this.projectionMatrix=new se,this.projectionMatrixInverse=new se}copy(t,e){return super.copy(t,e),this.matrixWorldInverse.copy(t.matrixWorldInverse),this.projectionMatrix.copy(t.projectionMatrix),this.projectionMatrixInverse.copy(t.projectionMatrixInverse),this}getWorldDirection(t){void 0===t&&(console.warn("THREE.Camera: .getWorldDirection() target is now required"),t=new Lt),this.updateWorldMatrix(!0,!1);const e=this.matrixWorld.elements;return t.set(-e[8],-e[9],-e[10]).normalize()}updateMatrixWorld(t){super.updateMatrixWorld(t),this.matrixWorldInverse.copy(this.matrixWorld).invert()}updateWorldMatrix(t,e){super.updateWorldMatrix(t,e),this.matrixWorldInverse.copy(this.matrixWorld).invert()}clone(){return(new this.constructor).copy(this)}}Qn.prototype.isCamera=!0;class Kn extends Qn{constructor(t=50,e=1,n=.1,i=2e3){super(),this.type="PerspectiveCamera",this.fov=t,this.zoom=1,this.near=n,this.far=i,this.focus=10,this.aspect=e,this.view=null,this.filmGauge=35,this.filmOffset=0,this.updateProjectionMatrix()}copy(t,e){return super.copy(t,e),this.fov=t.fov,this.zoom=t.zoom,this.near=t.near,this.far=t.far,this.focus=t.focus,this.aspect=t.aspect,this.view=null===t.view?null:Object.assign({},t.view),this.filmGauge=t.filmGauge,this.filmOffset=t.filmOffset,this}setFocalLength(t){const e=.5*this.getFilmHeight()/t;this.fov=2*lt*Math.atan(e),this.updateProjectionMatrix()}getFocalLength(){const t=Math.tan(.5*ot*this.fov);return.5*this.getFilmHeight()/t}getEffectiveFOV(){return 2*lt*Math.atan(Math.tan(.5*ot*this.fov)/this.zoom)}getFilmWidth(){return this.filmGauge*Math.min(this.aspect,1)}getFilmHeight(){return this.filmGauge/Math.max(this.aspect,1)}setViewOffset(t,e,n,i,r,s){this.aspect=t/e,null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=t,this.view.fullHeight=e,this.view.offsetX=n,this.view.offsetY=i,this.view.width=r,this.view.height=s,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const t=this.near;let e=t*Math.tan(.5*ot*this.fov)/this.zoom,n=2*e,i=this.aspect*n,r=-.5*i;const s=this.view;if(null!==this.view&&this.view.enabled){const t=s.fullWidth,a=s.fullHeight;r+=s.offsetX*i/t,e-=s.offsetY*n/a,i*=s.width/t,n*=s.height/a}const a=this.filmOffset;0!==a&&(r+=t*a/this.getFilmWidth()),this.projectionMatrix.makePerspective(r,r+i,e,e-n,t,this.far),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(t){const e=super.toJSON(t);return e.object.fov=this.fov,e.object.zoom=this.zoom,e.object.near=this.near,e.object.far=this.far,e.object.focus=this.focus,e.object.aspect=this.aspect,null!==this.view&&(e.object.view=Object.assign({},this.view)),e.object.filmGauge=this.filmGauge,e.object.filmOffset=this.filmOffset,e}}Kn.prototype.isPerspectiveCamera=!0;const $n=90;class ti extends Ce{constructor(t,e,n){if(super(),this.type="CubeCamera",!0!==n.isWebGLCubeRenderTarget)return void console.error("THREE.CubeCamera: The constructor now expects an instance of WebGLCubeRenderTarget as third parameter.");this.renderTarget=n;const i=new Kn($n,1,t,e);i.layers=this.layers,i.up.set(0,-1,0),i.lookAt(new Lt(1,0,0)),this.add(i);const r=new Kn($n,1,t,e);r.layers=this.layers,r.up.set(0,-1,0),r.lookAt(new Lt(-1,0,0)),this.add(r);const s=new Kn($n,1,t,e);s.layers=this.layers,s.up.set(0,0,1),s.lookAt(new Lt(0,1,0)),this.add(s);const a=new Kn($n,1,t,e);a.layers=this.layers,a.up.set(0,0,-1),a.lookAt(new Lt(0,-1,0)),this.add(a);const o=new Kn($n,1,t,e);o.layers=this.layers,o.up.set(0,-1,0),o.lookAt(new Lt(0,0,1)),this.add(o);const l=new Kn($n,1,t,e);l.layers=this.layers,l.up.set(0,-1,0),l.lookAt(new Lt(0,0,-1)),this.add(l)}update(t,e){null===this.parent&&this.updateMatrixWorld();const n=this.renderTarget,[i,r,s,a,o,l]=this.children,c=t.xr.enabled,h=t.getRenderTarget();t.xr.enabled=!1;const u=n.texture.generateMipmaps;n.texture.generateMipmaps=!1,t.setRenderTarget(n,0),t.render(e,i),t.setRenderTarget(n,1),t.render(e,r),t.setRenderTarget(n,2),t.render(e,s),t.setRenderTarget(n,3),t.render(e,a),t.setRenderTarget(n,4),t.render(e,o),n.texture.generateMipmaps=u,t.setRenderTarget(n,5),t.render(e,l),t.setRenderTarget(h),t.xr.enabled=c}}class ei extends bt{constructor(t,e,n,i,s,a,o,l,c,h){super(t=void 0!==t?t:[],e=void 0!==e?e:r,n,i,s,a,o=void 0!==o?o:T,l,c,h),this._needsFlipEnvMap=!0,this.flipY=!1}get images(){return this.image}set images(t){this.image=t}}ei.prototype.isCubeTexture=!0;class ni extends Tt{constructor(t,e,n){Number.isInteger(e)&&(console.warn("THREE.WebGLCubeRenderTarget: constructor signature is now WebGLCubeRenderTarget( size, options )"),e=n),super(t,t,e),e=e||{},this.texture=new ei(void 0,e.mapping,e.wrapS,e.wrapT,e.magFilter,e.minFilter,e.format,e.type,e.anisotropy,e.encoding),this.texture.generateMipmaps=void 0!==e.generateMipmaps&&e.generateMipmaps,this.texture.minFilter=void 0!==e.minFilter?e.minFilter:g,this.texture._needsFlipEnvMap=!1}fromEquirectangularTexture(t,e){this.texture.type=e.type,this.texture.format=E,this.texture.encoding=e.encoding,this.texture.generateMipmaps=e.generateMipmaps,this.texture.minFilter=e.minFilter,this.texture.magFilter=e.magFilter;const n={uniforms:{tEquirect:{value:null}},vertexShader:"\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\n\t\t\t\t\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n\n\t\t\t\t}\n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvWorldDirection = transformDirection( position, modelMatrix );\n\n\t\t\t\t\t#include \n\t\t\t\t\t#include \n\n\t\t\t\t}\n\t\t\t",fragmentShader:"\n\n\t\t\t\tuniform sampler2D tEquirect;\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\t#include \n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvec3 direction = normalize( vWorldDirection );\n\n\t\t\t\t\tvec2 sampleUV = equirectUv( direction );\n\n\t\t\t\t\tgl_FragColor = texture2D( tEquirect, sampleUV );\n\n\t\t\t\t}\n\t\t\t"},i=new qn(5,5,5),r=new Jn({name:"CubemapFromEquirect",uniforms:Xn(n.uniforms),vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,side:1,blending:0});r.uniforms.tEquirect.value=e;const s=new Wn(i,r),a=e.minFilter;e.minFilter===y&&(e.minFilter=g);return new ti(1,10,this).update(t,s),e.minFilter=a,s.geometry.dispose(),s.material.dispose(),this}clear(t,e,n,i){const r=t.getRenderTarget();for(let r=0;r<6;r++)t.setRenderTarget(this,r),t.clear(e,n,i);t.setRenderTarget(r)}}ni.prototype.isWebGLCubeRenderTarget=!0;class ii extends bt{constructor(t,e,n,i,r,s,a,o,l,c,h,u){super(null,s,a,o,l,c,i,r,h,u),this.image={data:t||null,width:e||1,height:n||1},this.magFilter=void 0!==l?l:p,this.minFilter=void 0!==c?c:p,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.needsUpdate=!0}}ii.prototype.isDataTexture=!0;const ri=new Jt,si=new Lt;class ai{constructor(t=new Ne,e=new Ne,n=new Ne,i=new Ne,r=new Ne,s=new Ne){this.planes=[t,e,n,i,r,s]}set(t,e,n,i,r,s){const a=this.planes;return a[0].copy(t),a[1].copy(e),a[2].copy(n),a[3].copy(i),a[4].copy(r),a[5].copy(s),this}copy(t){const e=this.planes;for(let n=0;n<6;n++)e[n].copy(t.planes[n]);return this}setFromProjectionMatrix(t){const e=this.planes,n=t.elements,i=n[0],r=n[1],s=n[2],a=n[3],o=n[4],l=n[5],c=n[6],h=n[7],u=n[8],d=n[9],p=n[10],m=n[11],f=n[12],g=n[13],v=n[14],y=n[15];return e[0].setComponents(a-i,h-o,m-u,y-f).normalize(),e[1].setComponents(a+i,h+o,m+u,y+f).normalize(),e[2].setComponents(a+r,h+l,m+d,y+g).normalize(),e[3].setComponents(a-r,h-l,m-d,y-g).normalize(),e[4].setComponents(a-s,h-c,m-p,y-v).normalize(),e[5].setComponents(a+s,h+c,m+p,y+v).normalize(),this}intersectsObject(t){const e=t.geometry;return null===e.boundingSphere&&e.computeBoundingSphere(),ri.copy(e.boundingSphere).applyMatrix4(t.matrixWorld),this.intersectsSphere(ri)}intersectsSprite(t){return ri.center.set(0,0,0),ri.radius=.7071067811865476,ri.applyMatrix4(t.matrixWorld),this.intersectsSphere(ri)}intersectsSphere(t){const e=this.planes,n=t.center,i=-t.radius;for(let t=0;t<6;t++){if(e[t].distanceToPoint(n)0?t.max.x:t.min.x,si.y=i.normal.y>0?t.max.y:t.min.y,si.z=i.normal.z>0?t.max.z:t.min.z,i.distanceToPoint(si)<0)return!1}return!0}containsPoint(t){const e=this.planes;for(let n=0;n<6;n++)if(e[n].distanceToPoint(t)<0)return!1;return!0}clone(){return(new this.constructor).copy(this)}}function oi(){let t=null,e=!1,n=null,i=null;function r(e,s){n(e,s),i=t.requestAnimationFrame(r)}return{start:function(){!0!==e&&null!==n&&(i=t.requestAnimationFrame(r),e=!0)},stop:function(){t.cancelAnimationFrame(i),e=!1},setAnimationLoop:function(t){n=t},setContext:function(e){t=e}}}function li(t,e){const n=e.isWebGL2,i=new WeakMap;return{get:function(t){return t.isInterleavedBufferAttribute&&(t=t.data),i.get(t)},remove:function(e){e.isInterleavedBufferAttribute&&(e=e.data);const n=i.get(e);n&&(t.deleteBuffer(n.buffer),i.delete(e))},update:function(e,r){if(e.isGLBufferAttribute){const t=i.get(e);return void((!t||t.version 0.0 ) {\n\t\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\n\t}\n\treturn distanceFalloff;\n#else\n\tif( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\n\t\treturn pow( saturate( -lightDistance / cutoffDistance + 1.0 ), decayExponent );\n\t}\n\treturn 1.0;\n#endif\n}\nvec3 BRDF_Diffuse_Lambert( const in vec3 diffuseColor ) {\n\treturn RECIPROCAL_PI * diffuseColor;\n}\nvec3 F_Schlick( const in vec3 specularColor, const in float dotLH ) {\n\tfloat fresnel = exp2( ( -5.55473 * dotLH - 6.98316 ) * dotLH );\n\treturn ( 1.0 - specularColor ) * fresnel + specularColor;\n}\nvec3 F_Schlick_RoughnessDependent( const in vec3 F0, const in float dotNV, const in float roughness ) {\n\tfloat fresnel = exp2( ( -5.55473 * dotNV - 6.98316 ) * dotNV );\n\tvec3 Fr = max( vec3( 1.0 - roughness ), F0 ) - F0;\n\treturn Fr * fresnel + F0;\n}\nfloat G_GGX_Smith( const in float alpha, const in float dotNL, const in float dotNV ) {\n\tfloat a2 = pow2( alpha );\n\tfloat gl = dotNL + sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\n\tfloat gv = dotNV + sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\n\treturn 1.0 / ( gl * gv );\n}\nfloat G_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\n\tfloat a2 = pow2( alpha );\n\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\n\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\n\treturn 0.5 / max( gv + gl, EPSILON );\n}\nfloat D_GGX( const in float alpha, const in float dotNH ) {\n\tfloat a2 = pow2( alpha );\n\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0;\n\treturn RECIPROCAL_PI * a2 / pow2( denom );\n}\nvec3 BRDF_Specular_GGX( const in IncidentLight incidentLight, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float roughness ) {\n\tfloat alpha = pow2( roughness );\n\tvec3 halfDir = normalize( incidentLight.direction + viewDir );\n\tfloat dotNL = saturate( dot( normal, incidentLight.direction ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotLH = saturate( dot( incidentLight.direction, halfDir ) );\n\tvec3 F = F_Schlick( specularColor, dotLH );\n\tfloat G = G_GGX_SmithCorrelated( alpha, dotNL, dotNV );\n\tfloat D = D_GGX( alpha, dotNH );\n\treturn F * ( G * D );\n}\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\n\tconst float LUT_SIZE = 64.0;\n\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\n\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\n\tfloat dotNV = saturate( dot( N, V ) );\n\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\n\tuv = uv * LUT_SCALE + LUT_BIAS;\n\treturn uv;\n}\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\n\tfloat l = length( f );\n\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\n}\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\n\tfloat x = dot( v1, v2 );\n\tfloat y = abs( x );\n\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\n\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\n\tfloat v = a / b;\n\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\n\treturn cross( v1, v2 ) * theta_sintheta;\n}\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\n\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\n\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\n\tvec3 lightNormal = cross( v1, v2 );\n\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\n\tvec3 T1, T2;\n\tT1 = normalize( V - N * dot( V, N ) );\n\tT2 = - cross( N, T1 );\n\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\n\tvec3 coords[ 4 ];\n\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\n\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\n\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\n\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\n\tcoords[ 0 ] = normalize( coords[ 0 ] );\n\tcoords[ 1 ] = normalize( coords[ 1 ] );\n\tcoords[ 2 ] = normalize( coords[ 2 ] );\n\tcoords[ 3 ] = normalize( coords[ 3 ] );\n\tvec3 vectorFormFactor = vec3( 0.0 );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\n\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\n\treturn vec3( result );\n}\nvec3 BRDF_Specular_GGX_Environment( const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tvec2 brdf = integrateSpecularBRDF( dotNV, roughness );\n\treturn specularColor * brdf.x + brdf.y;\n}\nvoid BRDF_Specular_Multiscattering_Environment( const in GeometricContext geometry, const in vec3 specularColor, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n\tfloat dotNV = saturate( dot( geometry.normal, geometry.viewDir ) );\n\tvec3 F = F_Schlick_RoughnessDependent( specularColor, dotNV, roughness );\n\tvec2 brdf = integrateSpecularBRDF( dotNV, roughness );\n\tvec3 FssEss = F * brdf.x + brdf.y;\n\tfloat Ess = brdf.x + brdf.y;\n\tfloat Ems = 1.0 - Ess;\n\tvec3 Favg = specularColor + ( 1.0 - specularColor ) * 0.047619;\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\n\tsingleScatter += FssEss;\n\tmultiScatter += Fms * Ems;\n}\nfloat G_BlinnPhong_Implicit( ) {\n\treturn 0.25;\n}\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\n\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\n}\nvec3 BRDF_Specular_BlinnPhong( const in IncidentLight incidentLight, const in GeometricContext geometry, const in vec3 specularColor, const in float shininess ) {\n\tvec3 halfDir = normalize( incidentLight.direction + geometry.viewDir );\n\tfloat dotNH = saturate( dot( geometry.normal, halfDir ) );\n\tfloat dotLH = saturate( dot( incidentLight.direction, halfDir ) );\n\tvec3 F = F_Schlick( specularColor, dotLH );\n\tfloat G = G_BlinnPhong_Implicit( );\n\tfloat D = D_BlinnPhong( shininess, dotNH );\n\treturn F * ( G * D );\n}\nfloat GGXRoughnessToBlinnExponent( const in float ggxRoughness ) {\n\treturn ( 2.0 / pow2( ggxRoughness + 0.0001 ) - 2.0 );\n}\nfloat BlinnExponentToGGXRoughness( const in float blinnExponent ) {\n\treturn sqrt( 2.0 / ( blinnExponent + 2.0 ) );\n}\n#if defined( USE_SHEEN )\nfloat D_Charlie(float roughness, float NoH) {\n\tfloat invAlpha = 1.0 / roughness;\n\tfloat cos2h = NoH * NoH;\n\tfloat sin2h = max(1.0 - cos2h, 0.0078125);\treturn (2.0 + invAlpha) * pow(sin2h, invAlpha * 0.5) / (2.0 * PI);\n}\nfloat V_Neubelt(float NoV, float NoL) {\n\treturn saturate(1.0 / (4.0 * (NoL + NoV - NoL * NoV)));\n}\nvec3 BRDF_Specular_Sheen( const in float roughness, const in vec3 L, const in GeometricContext geometry, vec3 specularColor ) {\n\tvec3 N = geometry.normal;\n\tvec3 V = geometry.viewDir;\n\tvec3 H = normalize( V + L );\n\tfloat dotNH = saturate( dot( N, H ) );\n\treturn specularColor * D_Charlie( roughness, dotNH ) * V_Neubelt( dot(N, V), dot(N, L) );\n}\n#endif",bumpmap_pars_fragment:"#ifdef USE_BUMPMAP\n\tuniform sampler2D bumpMap;\n\tuniform float bumpScale;\n\tvec2 dHdxy_fwd() {\n\t\tvec2 dSTdx = dFdx( vUv );\n\t\tvec2 dSTdy = dFdy( vUv );\n\t\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\n\t\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\n\t\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\n\t\treturn vec2( dBx, dBy );\n\t}\n\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\n\t\tvec3 vSigmaX = vec3( dFdx( surf_pos.x ), dFdx( surf_pos.y ), dFdx( surf_pos.z ) );\n\t\tvec3 vSigmaY = vec3( dFdy( surf_pos.x ), dFdy( surf_pos.y ), dFdy( surf_pos.z ) );\n\t\tvec3 vN = surf_norm;\n\t\tvec3 R1 = cross( vSigmaY, vN );\n\t\tvec3 R2 = cross( vN, vSigmaX );\n\t\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\n\t\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\n\t\treturn normalize( abs( fDet ) * surf_norm - vGrad );\n\t}\n#endif",clipping_planes_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvec4 plane;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\tplane = clippingPlanes[ i ];\n\t\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\n\t}\n\t#pragma unroll_loop_end\n\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\tbool clipped = true;\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\tif ( clipped ) discard;\n\t#endif\n#endif",clipping_planes_pars_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\n#endif",clipping_planes_pars_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n#endif",clipping_planes_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvClipPosition = - mvPosition.xyz;\n#endif",color_fragment:"#if defined( USE_COLOR_ALPHA )\n\tdiffuseColor *= vColor;\n#elif defined( USE_COLOR )\n\tdiffuseColor.rgb *= vColor;\n#endif",color_pars_fragment:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR )\n\tvarying vec3 vColor;\n#endif",color_pars_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\n\tvarying vec3 vColor;\n#endif",color_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvColor = vec4( 1.0 );\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\n\tvColor = vec3( 1.0 );\n#endif\n#ifdef USE_COLOR\n\tvColor *= color;\n#endif\n#ifdef USE_INSTANCING_COLOR\n\tvColor.xyz *= instanceColor.xyz;\n#endif",common:"#define PI 3.141592653589793\n#define PI2 6.283185307179586\n#define PI_HALF 1.5707963267948966\n#define RECIPROCAL_PI 0.3183098861837907\n#define RECIPROCAL_PI2 0.15915494309189535\n#define EPSILON 1e-6\n#ifndef saturate\n#define saturate(a) clamp( a, 0.0, 1.0 )\n#endif\n#define whiteComplement(a) ( 1.0 - saturate( a ) )\nfloat pow2( const in float x ) { return x*x; }\nfloat pow3( const in float x ) { return x*x*x; }\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\nfloat average( const in vec3 color ) { return dot( color, vec3( 0.3333 ) ); }\nhighp float rand( const in vec2 uv ) {\n\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\n\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\n\treturn fract(sin(sn) * c);\n}\n#ifdef HIGH_PRECISION\n\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\n#else\n\tfloat max3( vec3 v ) { return max( max( v.x, v.y ), v.z ); }\n\tfloat precisionSafeLength( vec3 v ) {\n\t\tfloat maxComponent = max3( abs( v ) );\n\t\treturn length( v / maxComponent ) * maxComponent;\n\t}\n#endif\nstruct IncidentLight {\n\tvec3 color;\n\tvec3 direction;\n\tbool visible;\n};\nstruct ReflectedLight {\n\tvec3 directDiffuse;\n\tvec3 directSpecular;\n\tvec3 indirectDiffuse;\n\tvec3 indirectSpecular;\n};\nstruct GeometricContext {\n\tvec3 position;\n\tvec3 normal;\n\tvec3 viewDir;\n#ifdef CLEARCOAT\n\tvec3 clearcoatNormal;\n#endif\n};\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n}\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\n}\nvec3 projectOnPlane(in vec3 point, in vec3 pointOnPlane, in vec3 planeNormal ) {\n\tfloat distance = dot( planeNormal, point - pointOnPlane );\n\treturn - distance * planeNormal + point;\n}\nfloat sideOfPlane( in vec3 point, in vec3 pointOnPlane, in vec3 planeNormal ) {\n\treturn sign( dot( point - pointOnPlane, planeNormal ) );\n}\nvec3 linePlaneIntersect( in vec3 pointOnLine, in vec3 lineDirection, in vec3 pointOnPlane, in vec3 planeNormal ) {\n\treturn lineDirection * ( dot( planeNormal, pointOnPlane - pointOnLine ) / dot( planeNormal, lineDirection ) ) + pointOnLine;\n}\nmat3 transposeMat3( const in mat3 m ) {\n\tmat3 tmp;\n\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\n\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\n\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\n\treturn tmp;\n}\nfloat linearToRelativeLuminance( const in vec3 color ) {\n\tvec3 weights = vec3( 0.2126, 0.7152, 0.0722 );\n\treturn dot( weights, color.rgb );\n}\nbool isPerspectiveMatrix( mat4 m ) {\n\treturn m[ 2 ][ 3 ] == - 1.0;\n}\nvec2 equirectUv( in vec3 dir ) {\n\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\n\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\n\treturn vec2( u, v );\n}",cube_uv_reflection_fragment:"#ifdef ENVMAP_TYPE_CUBE_UV\n\t#define cubeUV_maxMipLevel 8.0\n\t#define cubeUV_minMipLevel 4.0\n\t#define cubeUV_maxTileSize 256.0\n\t#define cubeUV_minTileSize 16.0\n\tfloat getFace( vec3 direction ) {\n\t\tvec3 absDirection = abs( direction );\n\t\tfloat face = - 1.0;\n\t\tif ( absDirection.x > absDirection.z ) {\n\t\t\tif ( absDirection.x > absDirection.y )\n\t\t\t\tface = direction.x > 0.0 ? 0.0 : 3.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t} else {\n\t\t\tif ( absDirection.z > absDirection.y )\n\t\t\t\tface = direction.z > 0.0 ? 2.0 : 5.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t}\n\t\treturn face;\n\t}\n\tvec2 getUV( vec3 direction, float face ) {\n\t\tvec2 uv;\n\t\tif ( face == 0.0 ) {\n\t\t\tuv = vec2( direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 1.0 ) {\n\t\t\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y );\n\t\t} else if ( face == 2.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.y ) / abs( direction.z );\n\t\t} else if ( face == 3.0 ) {\n\t\t\tuv = vec2( - direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 4.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.z ) / abs( direction.y );\n\t\t} else {\n\t\t\tuv = vec2( direction.x, direction.y ) / abs( direction.z );\n\t\t}\n\t\treturn 0.5 * ( uv + 1.0 );\n\t}\n\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\n\t\tfloat face = getFace( direction );\n\t\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\n\t\tmipInt = max( mipInt, cubeUV_minMipLevel );\n\t\tfloat faceSize = exp2( mipInt );\n\t\tfloat texelSize = 1.0 / ( 3.0 * cubeUV_maxTileSize );\n\t\tvec2 uv = getUV( direction, face ) * ( faceSize - 1.0 );\n\t\tvec2 f = fract( uv );\n\t\tuv += 0.5 - f;\n\t\tif ( face > 2.0 ) {\n\t\t\tuv.y += faceSize;\n\t\t\tface -= 3.0;\n\t\t}\n\t\tuv.x += face * faceSize;\n\t\tif ( mipInt < cubeUV_maxMipLevel ) {\n\t\t\tuv.y += 2.0 * cubeUV_maxTileSize;\n\t\t}\n\t\tuv.y += filterInt * 2.0 * cubeUV_minTileSize;\n\t\tuv.x += 3.0 * max( 0.0, cubeUV_maxTileSize - 2.0 * faceSize );\n\t\tuv *= texelSize;\n\t\tvec3 tl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\n\t\tuv.x += texelSize;\n\t\tvec3 tr = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\n\t\tuv.y += texelSize;\n\t\tvec3 br = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\n\t\tuv.x -= texelSize;\n\t\tvec3 bl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\n\t\tvec3 tm = mix( tl, tr, f.x );\n\t\tvec3 bm = mix( bl, br, f.x );\n\t\treturn mix( tm, bm, f.y );\n\t}\n\t#define r0 1.0\n\t#define v0 0.339\n\t#define m0 - 2.0\n\t#define r1 0.8\n\t#define v1 0.276\n\t#define m1 - 1.0\n\t#define r4 0.4\n\t#define v4 0.046\n\t#define m4 2.0\n\t#define r5 0.305\n\t#define v5 0.016\n\t#define m5 3.0\n\t#define r6 0.21\n\t#define v6 0.0038\n\t#define m6 4.0\n\tfloat roughnessToMip( float roughness ) {\n\t\tfloat mip = 0.0;\n\t\tif ( roughness >= r1 ) {\n\t\t\tmip = ( r0 - roughness ) * ( m1 - m0 ) / ( r0 - r1 ) + m0;\n\t\t} else if ( roughness >= r4 ) {\n\t\t\tmip = ( r1 - roughness ) * ( m4 - m1 ) / ( r1 - r4 ) + m1;\n\t\t} else if ( roughness >= r5 ) {\n\t\t\tmip = ( r4 - roughness ) * ( m5 - m4 ) / ( r4 - r5 ) + m4;\n\t\t} else if ( roughness >= r6 ) {\n\t\t\tmip = ( r5 - roughness ) * ( m6 - m5 ) / ( r5 - r6 ) + m5;\n\t\t} else {\n\t\t\tmip = - 2.0 * log2( 1.16 * roughness );\t\t}\n\t\treturn mip;\n\t}\n\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\n\t\tfloat mip = clamp( roughnessToMip( roughness ), m0, cubeUV_maxMipLevel );\n\t\tfloat mipF = fract( mip );\n\t\tfloat mipInt = floor( mip );\n\t\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\n\t\tif ( mipF == 0.0 ) {\n\t\t\treturn vec4( color0, 1.0 );\n\t\t} else {\n\t\t\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\n\t\t\treturn vec4( mix( color0, color1, mipF ), 1.0 );\n\t\t}\n\t}\n#endif",defaultnormal_vertex:"vec3 transformedNormal = objectNormal;\n#ifdef USE_INSTANCING\n\tmat3 m = mat3( instanceMatrix );\n\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\n\ttransformedNormal = m * transformedNormal;\n#endif\ntransformedNormal = normalMatrix * transformedNormal;\n#ifdef FLIP_SIDED\n\ttransformedNormal = - transformedNormal;\n#endif\n#ifdef USE_TANGENT\n\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\n\t#ifdef FLIP_SIDED\n\t\ttransformedTangent = - transformedTangent;\n\t#endif\n#endif",displacementmap_pars_vertex:"#ifdef USE_DISPLACEMENTMAP\n\tuniform sampler2D displacementMap;\n\tuniform float displacementScale;\n\tuniform float displacementBias;\n#endif",displacementmap_vertex:"#ifdef USE_DISPLACEMENTMAP\n\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\n#endif",emissivemap_fragment:"#ifdef USE_EMISSIVEMAP\n\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\n\temissiveColor.rgb = emissiveMapTexelToLinear( emissiveColor ).rgb;\n\ttotalEmissiveRadiance *= emissiveColor.rgb;\n#endif",emissivemap_pars_fragment:"#ifdef USE_EMISSIVEMAP\n\tuniform sampler2D emissiveMap;\n#endif",encodings_fragment:"gl_FragColor = linearToOutputTexel( gl_FragColor );",encodings_pars_fragment:"\nvec4 LinearToLinear( in vec4 value ) {\n\treturn value;\n}\nvec4 GammaToLinear( in vec4 value, in float gammaFactor ) {\n\treturn vec4( pow( value.rgb, vec3( gammaFactor ) ), value.a );\n}\nvec4 LinearToGamma( in vec4 value, in float gammaFactor ) {\n\treturn vec4( pow( value.rgb, vec3( 1.0 / gammaFactor ) ), value.a );\n}\nvec4 sRGBToLinear( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\n}\nvec4 LinearTosRGB( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\n}\nvec4 RGBEToLinear( in vec4 value ) {\n\treturn vec4( value.rgb * exp2( value.a * 255.0 - 128.0 ), 1.0 );\n}\nvec4 LinearToRGBE( in vec4 value ) {\n\tfloat maxComponent = max( max( value.r, value.g ), value.b );\n\tfloat fExp = clamp( ceil( log2( maxComponent ) ), -128.0, 127.0 );\n\treturn vec4( value.rgb / exp2( fExp ), ( fExp + 128.0 ) / 255.0 );\n}\nvec4 RGBMToLinear( in vec4 value, in float maxRange ) {\n\treturn vec4( value.rgb * value.a * maxRange, 1.0 );\n}\nvec4 LinearToRGBM( in vec4 value, in float maxRange ) {\n\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\n\tfloat M = clamp( maxRGB / maxRange, 0.0, 1.0 );\n\tM = ceil( M * 255.0 ) / 255.0;\n\treturn vec4( value.rgb / ( M * maxRange ), M );\n}\nvec4 RGBDToLinear( in vec4 value, in float maxRange ) {\n\treturn vec4( value.rgb * ( ( maxRange / 255.0 ) / value.a ), 1.0 );\n}\nvec4 LinearToRGBD( in vec4 value, in float maxRange ) {\n\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\n\tfloat D = max( maxRange / maxRGB, 1.0 );\n\tD = clamp( floor( D ) / 255.0, 0.0, 1.0 );\n\treturn vec4( value.rgb * ( D * ( 255.0 / maxRange ) ), D );\n}\nconst mat3 cLogLuvM = mat3( 0.2209, 0.3390, 0.4184, 0.1138, 0.6780, 0.7319, 0.0102, 0.1130, 0.2969 );\nvec4 LinearToLogLuv( in vec4 value ) {\n\tvec3 Xp_Y_XYZp = cLogLuvM * value.rgb;\n\tXp_Y_XYZp = max( Xp_Y_XYZp, vec3( 1e-6, 1e-6, 1e-6 ) );\n\tvec4 vResult;\n\tvResult.xy = Xp_Y_XYZp.xy / Xp_Y_XYZp.z;\n\tfloat Le = 2.0 * log2(Xp_Y_XYZp.y) + 127.0;\n\tvResult.w = fract( Le );\n\tvResult.z = ( Le - ( floor( vResult.w * 255.0 ) ) / 255.0 ) / 255.0;\n\treturn vResult;\n}\nconst mat3 cLogLuvInverseM = mat3( 6.0014, -2.7008, -1.7996, -1.3320, 3.1029, -5.7721, 0.3008, -1.0882, 5.6268 );\nvec4 LogLuvToLinear( in vec4 value ) {\n\tfloat Le = value.z * 255.0 + value.w;\n\tvec3 Xp_Y_XYZp;\n\tXp_Y_XYZp.y = exp2( ( Le - 127.0 ) / 2.0 );\n\tXp_Y_XYZp.z = Xp_Y_XYZp.y / value.y;\n\tXp_Y_XYZp.x = value.x * Xp_Y_XYZp.z;\n\tvec3 vRGB = cLogLuvInverseM * Xp_Y_XYZp.rgb;\n\treturn vec4( max( vRGB, 0.0 ), 1.0 );\n}",envmap_fragment:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvec3 cameraToFrag;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\n\t\t#else\n\t\t\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\n\t\t#endif\n\t#else\n\t\tvec3 reflectVec = vReflect;\n\t#endif\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\n\t#elif defined( ENVMAP_TYPE_CUBE_UV )\n\t\tvec4 envColor = textureCubeUV( envMap, reflectVec, 0.0 );\n\t#else\n\t\tvec4 envColor = vec4( 0.0 );\n\t#endif\n\t#ifndef ENVMAP_TYPE_CUBE_UV\n\t\tenvColor = envMapTexelToLinear( envColor );\n\t#endif\n\t#ifdef ENVMAP_BLENDING_MULTIPLY\n\t\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_MIX )\n\t\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_ADD )\n\t\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\n\t#endif\n#endif",envmap_common_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float envMapIntensity;\n\tuniform float flipEnvMap;\n\tuniform int maxMipLevel;\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tuniform samplerCube envMap;\n\t#else\n\t\tuniform sampler2D envMap;\n\t#endif\n\t\n#endif",envmap_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float reflectivity;\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\tvarying vec3 vWorldPosition;\n\t\tuniform float refractionRatio;\n\t#else\n\t\tvarying vec3 vReflect;\n\t#endif\n#endif",envmap_pars_vertex:"#ifdef USE_ENVMAP\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) ||defined( PHONG )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\t\n\t\tvarying vec3 vWorldPosition;\n\t#else\n\t\tvarying vec3 vReflect;\n\t\tuniform float refractionRatio;\n\t#endif\n#endif",envmap_physical_pars_fragment:"#if defined( USE_ENVMAP )\n\t#ifdef ENVMAP_MODE_REFRACTION\n\t\tuniform float refractionRatio;\n\t#endif\n\tvec3 getLightProbeIndirectIrradiance( const in GeometricContext geometry, const in int maxMIPLevel ) {\n\t\tvec3 worldNormal = inverseTransformDirection( geometry.normal, viewMatrix );\n\t\t#ifdef ENVMAP_TYPE_CUBE\n\t\t\tvec3 queryVec = vec3( flipEnvMap * worldNormal.x, worldNormal.yz );\n\t\t\t#ifdef TEXTURE_LOD_EXT\n\t\t\t\tvec4 envMapColor = textureCubeLodEXT( envMap, queryVec, float( maxMIPLevel ) );\n\t\t\t#else\n\t\t\t\tvec4 envMapColor = textureCube( envMap, queryVec, float( maxMIPLevel ) );\n\t\t\t#endif\n\t\t\tenvMapColor.rgb = envMapTexelToLinear( envMapColor ).rgb;\n\t\t#elif defined( ENVMAP_TYPE_CUBE_UV )\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\n\t\t#else\n\t\t\tvec4 envMapColor = vec4( 0.0 );\n\t\t#endif\n\t\treturn PI * envMapColor.rgb * envMapIntensity;\n\t}\n\tfloat getSpecularMIPLevel( const in float roughness, const in int maxMIPLevel ) {\n\t\tfloat maxMIPLevelScalar = float( maxMIPLevel );\n\t\tfloat sigma = PI * roughness * roughness / ( 1.0 + roughness );\n\t\tfloat desiredMIPLevel = maxMIPLevelScalar + log2( sigma );\n\t\treturn clamp( desiredMIPLevel, 0.0, maxMIPLevelScalar );\n\t}\n\tvec3 getLightProbeIndirectRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness, const in int maxMIPLevel ) {\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvec3 reflectVec = reflect( -viewDir, normal );\n\t\t\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\n\t\t#else\n\t\t\tvec3 reflectVec = refract( -viewDir, normal, refractionRatio );\n\t\t#endif\n\t\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\n\t\tfloat specularMIPLevel = getSpecularMIPLevel( roughness, maxMIPLevel );\n\t\t#ifdef ENVMAP_TYPE_CUBE\n\t\t\tvec3 queryReflectVec = vec3( flipEnvMap * reflectVec.x, reflectVec.yz );\n\t\t\t#ifdef TEXTURE_LOD_EXT\n\t\t\t\tvec4 envMapColor = textureCubeLodEXT( envMap, queryReflectVec, specularMIPLevel );\n\t\t\t#else\n\t\t\t\tvec4 envMapColor = textureCube( envMap, queryReflectVec, specularMIPLevel );\n\t\t\t#endif\n\t\t\tenvMapColor.rgb = envMapTexelToLinear( envMapColor ).rgb;\n\t\t#elif defined( ENVMAP_TYPE_CUBE_UV )\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\n\t\t#endif\n\t\treturn envMapColor.rgb * envMapIntensity;\n\t}\n#endif",envmap_vertex:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvWorldPosition = worldPosition.xyz;\n\t#else\n\t\tvec3 cameraToVertex;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvReflect = reflect( cameraToVertex, worldNormal );\n\t\t#else\n\t\t\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\n\t\t#endif\n\t#endif\n#endif",fog_vertex:"#ifdef USE_FOG\n\tfogDepth = - mvPosition.z;\n#endif",fog_pars_vertex:"#ifdef USE_FOG\n\tvarying float fogDepth;\n#endif",fog_fragment:"#ifdef USE_FOG\n\t#ifdef FOG_EXP2\n\t\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * fogDepth * fogDepth );\n\t#else\n\t\tfloat fogFactor = smoothstep( fogNear, fogFar, fogDepth );\n\t#endif\n\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\n#endif",fog_pars_fragment:"#ifdef USE_FOG\n\tuniform vec3 fogColor;\n\tvarying float fogDepth;\n\t#ifdef FOG_EXP2\n\t\tuniform float fogDensity;\n\t#else\n\t\tuniform float fogNear;\n\t\tuniform float fogFar;\n\t#endif\n#endif",gradientmap_pars_fragment:"#ifdef USE_GRADIENTMAP\n\tuniform sampler2D gradientMap;\n#endif\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\n\tfloat dotNL = dot( normal, lightDirection );\n\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\n\t#ifdef USE_GRADIENTMAP\n\t\treturn texture2D( gradientMap, coord ).rgb;\n\t#else\n\t\treturn ( coord.x < 0.7 ) ? vec3( 0.7 ) : vec3( 1.0 );\n\t#endif\n}",lightmap_fragment:"#ifdef USE_LIGHTMAP\n\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\n\treflectedLight.indirectDiffuse += PI * lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\n#endif",lightmap_pars_fragment:"#ifdef USE_LIGHTMAP\n\tuniform sampler2D lightMap;\n\tuniform float lightMapIntensity;\n#endif",lights_lambert_vertex:"vec3 diffuse = vec3( 1.0 );\nGeometricContext geometry;\ngeometry.position = mvPosition.xyz;\ngeometry.normal = normalize( transformedNormal );\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( -mvPosition.xyz );\nGeometricContext backGeometry;\nbackGeometry.position = geometry.position;\nbackGeometry.normal = -geometry.normal;\nbackGeometry.viewDir = geometry.viewDir;\nvLightFront = vec3( 0.0 );\nvIndirectFront = vec3( 0.0 );\n#ifdef DOUBLE_SIDED\n\tvLightBack = vec3( 0.0 );\n\tvIndirectBack = vec3( 0.0 );\n#endif\nIncidentLight directLight;\nfloat dotNL;\nvec3 directLightColor_Diffuse;\nvIndirectFront += getAmbientLightIrradiance( ambientLightColor );\nvIndirectFront += getLightProbeIrradiance( lightProbe, geometry );\n#ifdef DOUBLE_SIDED\n\tvIndirectBack += getAmbientLightIrradiance( ambientLightColor );\n\tvIndirectBack += getLightProbeIrradiance( lightProbe, backGeometry );\n#endif\n#if NUM_POINT_LIGHTS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\n\t\tgetPointDirectLightIrradiance( pointLights[ i ], geometry, directLight );\n\t\tdotNL = dot( geometry.normal, directLight.direction );\n\t\tdirectLightColor_Diffuse = PI * directLight.color;\n\t\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\n\t\t#ifdef DOUBLE_SIDED\n\t\t\tvLightBack += saturate( -dotNL ) * directLightColor_Diffuse;\n\t\t#endif\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if NUM_SPOT_LIGHTS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\n\t\tgetSpotDirectLightIrradiance( spotLights[ i ], geometry, directLight );\n\t\tdotNL = dot( geometry.normal, directLight.direction );\n\t\tdirectLightColor_Diffuse = PI * directLight.color;\n\t\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\n\t\t#ifdef DOUBLE_SIDED\n\t\t\tvLightBack += saturate( -dotNL ) * directLightColor_Diffuse;\n\t\t#endif\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if NUM_DIR_LIGHTS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\n\t\tgetDirectionalDirectLightIrradiance( directionalLights[ i ], geometry, directLight );\n\t\tdotNL = dot( geometry.normal, directLight.direction );\n\t\tdirectLightColor_Diffuse = PI * directLight.color;\n\t\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\n\t\t#ifdef DOUBLE_SIDED\n\t\t\tvLightBack += saturate( -dotNL ) * directLightColor_Diffuse;\n\t\t#endif\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if NUM_HEMI_LIGHTS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\n\t\tvIndirectFront += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry );\n\t\t#ifdef DOUBLE_SIDED\n\t\t\tvIndirectBack += getHemisphereLightIrradiance( hemisphereLights[ i ], backGeometry );\n\t\t#endif\n\t}\n\t#pragma unroll_loop_end\n#endif",lights_pars_begin:"uniform bool receiveShadow;\nuniform vec3 ambientLightColor;\nuniform vec3 lightProbe[ 9 ];\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\n\tfloat x = normal.x, y = normal.y, z = normal.z;\n\tvec3 result = shCoefficients[ 0 ] * 0.886227;\n\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\n\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\n\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\n\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\n\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\n\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\n\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\n\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\n\treturn result;\n}\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in GeometricContext geometry ) {\n\tvec3 worldNormal = inverseTransformDirection( geometry.normal, viewMatrix );\n\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\n\treturn irradiance;\n}\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\n\tvec3 irradiance = ambientLightColor;\n\t#ifndef PHYSICALLY_CORRECT_LIGHTS\n\t\tirradiance *= PI;\n\t#endif\n\treturn irradiance;\n}\n#if NUM_DIR_LIGHTS > 0\n\tstruct DirectionalLight {\n\t\tvec3 direction;\n\t\tvec3 color;\n\t};\n\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\n\tvoid getDirectionalDirectLightIrradiance( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight directLight ) {\n\t\tdirectLight.color = directionalLight.color;\n\t\tdirectLight.direction = directionalLight.direction;\n\t\tdirectLight.visible = true;\n\t}\n#endif\n#if NUM_POINT_LIGHTS > 0\n\tstruct PointLight {\n\t\tvec3 position;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t};\n\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\n\tvoid getPointDirectLightIrradiance( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight directLight ) {\n\t\tvec3 lVector = pointLight.position - geometry.position;\n\t\tdirectLight.direction = normalize( lVector );\n\t\tfloat lightDistance = length( lVector );\n\t\tdirectLight.color = pointLight.color;\n\t\tdirectLight.color *= punctualLightIntensityToIrradianceFactor( lightDistance, pointLight.distance, pointLight.decay );\n\t\tdirectLight.visible = ( directLight.color != vec3( 0.0 ) );\n\t}\n#endif\n#if NUM_SPOT_LIGHTS > 0\n\tstruct SpotLight {\n\t\tvec3 position;\n\t\tvec3 direction;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t\tfloat coneCos;\n\t\tfloat penumbraCos;\n\t};\n\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\n\tvoid getSpotDirectLightIrradiance( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight directLight ) {\n\t\tvec3 lVector = spotLight.position - geometry.position;\n\t\tdirectLight.direction = normalize( lVector );\n\t\tfloat lightDistance = length( lVector );\n\t\tfloat angleCos = dot( directLight.direction, spotLight.direction );\n\t\tif ( angleCos > spotLight.coneCos ) {\n\t\t\tfloat spotEffect = smoothstep( spotLight.coneCos, spotLight.penumbraCos, angleCos );\n\t\t\tdirectLight.color = spotLight.color;\n\t\t\tdirectLight.color *= spotEffect * punctualLightIntensityToIrradianceFactor( lightDistance, spotLight.distance, spotLight.decay );\n\t\t\tdirectLight.visible = true;\n\t\t} else {\n\t\t\tdirectLight.color = vec3( 0.0 );\n\t\t\tdirectLight.visible = false;\n\t\t}\n\t}\n#endif\n#if NUM_RECT_AREA_LIGHTS > 0\n\tstruct RectAreaLight {\n\t\tvec3 color;\n\t\tvec3 position;\n\t\tvec3 halfWidth;\n\t\tvec3 halfHeight;\n\t};\n\tuniform sampler2D ltc_1;\tuniform sampler2D ltc_2;\n\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\n#endif\n#if NUM_HEMI_LIGHTS > 0\n\tstruct HemisphereLight {\n\t\tvec3 direction;\n\t\tvec3 skyColor;\n\t\tvec3 groundColor;\n\t};\n\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\n\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in GeometricContext geometry ) {\n\t\tfloat dotNL = dot( geometry.normal, hemiLight.direction );\n\t\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\n\t\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\n\t\t#ifndef PHYSICALLY_CORRECT_LIGHTS\n\t\t\tirradiance *= PI;\n\t\t#endif\n\t\treturn irradiance;\n\t}\n#endif",lights_toon_fragment:"ToonMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;",lights_toon_pars_fragment:"varying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\nstruct ToonMaterial {\n\tvec3 diffuseColor;\n};\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\n\t#ifndef PHYSICALLY_CORRECT_LIGHTS\n\t\tirradiance *= PI;\n\t#endif\n\treflectedLight.directDiffuse += irradiance * BRDF_Diffuse_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Diffuse_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Toon\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Toon\n#define Material_LightProbeLOD( material )\t(0)",lights_phong_fragment:"BlinnPhongMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularColor = specular;\nmaterial.specularShininess = shininess;\nmaterial.specularStrength = specularStrength;",lights_phong_pars_fragment:"varying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\nstruct BlinnPhongMaterial {\n\tvec3 diffuseColor;\n\tvec3 specularColor;\n\tfloat specularShininess;\n\tfloat specularStrength;\n};\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\t#ifndef PHYSICALLY_CORRECT_LIGHTS\n\t\tirradiance *= PI;\n\t#endif\n\treflectedLight.directDiffuse += irradiance * BRDF_Diffuse_Lambert( material.diffuseColor );\n\treflectedLight.directSpecular += irradiance * BRDF_Specular_BlinnPhong( directLight, geometry, material.specularColor, material.specularShininess ) * material.specularStrength;\n}\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Diffuse_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_BlinnPhong\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_BlinnPhong\n#define Material_LightProbeLOD( material )\t(0)",lights_physical_fragment:"PhysicalMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\nmaterial.specularRoughness = max( roughnessFactor, 0.0525 );material.specularRoughness += geometryRoughness;\nmaterial.specularRoughness = min( material.specularRoughness, 1.0 );\n#ifdef REFLECTIVITY\n\tmaterial.specularColor = mix( vec3( MAXIMUM_SPECULAR_COEFFICIENT * pow2( reflectivity ) ), diffuseColor.rgb, metalnessFactor );\n#else\n\tmaterial.specularColor = mix( vec3( DEFAULT_SPECULAR_COEFFICIENT ), diffuseColor.rgb, metalnessFactor );\n#endif\n#ifdef CLEARCOAT\n\tmaterial.clearcoat = clearcoat;\n\tmaterial.clearcoatRoughness = clearcoatRoughness;\n\t#ifdef USE_CLEARCOATMAP\n\t\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\n\t#endif\n\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\t\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\n\t#endif\n\tmaterial.clearcoat = saturate( material.clearcoat );\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\n\tmaterial.clearcoatRoughness += geometryRoughness;\n\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\n#endif\n#ifdef USE_SHEEN\n\tmaterial.sheenColor = sheen;\n#endif",lights_physical_pars_fragment:"struct PhysicalMaterial {\n\tvec3 diffuseColor;\n\tfloat specularRoughness;\n\tvec3 specularColor;\n#ifdef CLEARCOAT\n\tfloat clearcoat;\n\tfloat clearcoatRoughness;\n#endif\n#ifdef USE_SHEEN\n\tvec3 sheenColor;\n#endif\n};\n#define MAXIMUM_SPECULAR_COEFFICIENT 0.16\n#define DEFAULT_SPECULAR_COEFFICIENT 0.04\nfloat clearcoatDHRApprox( const in float roughness, const in float dotNL ) {\n\treturn DEFAULT_SPECULAR_COEFFICIENT + ( 1.0 - DEFAULT_SPECULAR_COEFFICIENT ) * ( pow( 1.0 - dotNL, 5.0 ) * pow( 1.0 - roughness, 2.0 ) );\n}\n#if NUM_RECT_AREA_LIGHTS > 0\n\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\t\tvec3 normal = geometry.normal;\n\t\tvec3 viewDir = geometry.viewDir;\n\t\tvec3 position = geometry.position;\n\t\tvec3 lightPos = rectAreaLight.position;\n\t\tvec3 halfWidth = rectAreaLight.halfWidth;\n\t\tvec3 halfHeight = rectAreaLight.halfHeight;\n\t\tvec3 lightColor = rectAreaLight.color;\n\t\tfloat roughness = material.specularRoughness;\n\t\tvec3 rectCoords[ 4 ];\n\t\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight;\t\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\n\t\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\n\t\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\n\t\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\n\t\tvec4 t1 = texture2D( ltc_1, uv );\n\t\tvec4 t2 = texture2D( ltc_2, uv );\n\t\tmat3 mInv = mat3(\n\t\t\tvec3( t1.x, 0, t1.y ),\n\t\t\tvec3(\t\t0, 1,\t\t0 ),\n\t\t\tvec3( t1.z, 0, t1.w )\n\t\t);\n\t\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\n\t\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\n\t\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\n\t}\n#endif\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\t#ifndef PHYSICALLY_CORRECT_LIGHTS\n\t\tirradiance *= PI;\n\t#endif\n\t#ifdef CLEARCOAT\n\t\tfloat ccDotNL = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\n\t\tvec3 ccIrradiance = ccDotNL * directLight.color;\n\t\t#ifndef PHYSICALLY_CORRECT_LIGHTS\n\t\t\tccIrradiance *= PI;\n\t\t#endif\n\t\tfloat clearcoatDHR = material.clearcoat * clearcoatDHRApprox( material.clearcoatRoughness, ccDotNL );\n\t\treflectedLight.directSpecular += ccIrradiance * material.clearcoat * BRDF_Specular_GGX( directLight, geometry.viewDir, geometry.clearcoatNormal, vec3( DEFAULT_SPECULAR_COEFFICIENT ), material.clearcoatRoughness );\n\t#else\n\t\tfloat clearcoatDHR = 0.0;\n\t#endif\n\t#ifdef USE_SHEEN\n\t\treflectedLight.directSpecular += ( 1.0 - clearcoatDHR ) * irradiance * BRDF_Specular_Sheen(\n\t\t\tmaterial.specularRoughness,\n\t\t\tdirectLight.direction,\n\t\t\tgeometry,\n\t\t\tmaterial.sheenColor\n\t\t);\n\t#else\n\t\treflectedLight.directSpecular += ( 1.0 - clearcoatDHR ) * irradiance * BRDF_Specular_GGX( directLight, geometry.viewDir, geometry.normal, material.specularColor, material.specularRoughness);\n\t#endif\n\treflectedLight.directDiffuse += ( 1.0 - clearcoatDHR ) * irradiance * BRDF_Diffuse_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Diffuse_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\n\t#ifdef CLEARCOAT\n\t\tfloat ccDotNV = saturate( dot( geometry.clearcoatNormal, geometry.viewDir ) );\n\t\treflectedLight.indirectSpecular += clearcoatRadiance * material.clearcoat * BRDF_Specular_GGX_Environment( geometry.viewDir, geometry.clearcoatNormal, vec3( DEFAULT_SPECULAR_COEFFICIENT ), material.clearcoatRoughness );\n\t\tfloat ccDotNL = ccDotNV;\n\t\tfloat clearcoatDHR = material.clearcoat * clearcoatDHRApprox( material.clearcoatRoughness, ccDotNL );\n\t#else\n\t\tfloat clearcoatDHR = 0.0;\n\t#endif\n\tfloat clearcoatInv = 1.0 - clearcoatDHR;\n\tvec3 singleScattering = vec3( 0.0 );\n\tvec3 multiScattering = vec3( 0.0 );\n\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\n\tBRDF_Specular_Multiscattering_Environment( geometry, material.specularColor, material.specularRoughness, singleScattering, multiScattering );\n\tvec3 diffuse = material.diffuseColor * ( 1.0 - ( singleScattering + multiScattering ) );\n\treflectedLight.indirectSpecular += clearcoatInv * radiance * singleScattering;\n\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\n\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\n}\n#define RE_Direct\t\t\t\tRE_Direct_Physical\n#define RE_Direct_RectArea\t\tRE_Direct_RectArea_Physical\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Physical\n#define RE_IndirectSpecular\t\tRE_IndirectSpecular_Physical\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\n\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\n}",lights_fragment_begin:"\nGeometricContext geometry;\ngeometry.position = - vViewPosition;\ngeometry.normal = normal;\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\n#ifdef CLEARCOAT\n\tgeometry.clearcoatNormal = clearcoatNormal;\n#endif\nIncidentLight directLight;\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\n\tPointLight pointLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\n\t\tpointLight = pointLights[ i ];\n\t\tgetPointDirectLightIrradiance( pointLight, geometry, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\n\t\tpointLightShadow = pointLightShadows[ i ];\n\t\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\n\tSpotLight spotLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\n\t\tspotLight = spotLights[ i ];\n\t\tgetSpotDirectLightIrradiance( spotLight, geometry, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\tspotLightShadow = spotLightShadows[ i ];\n\t\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\n\tDirectionalLight directionalLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\n\t\tdirectionalLight = directionalLights[ i ];\n\t\tgetDirectionalDirectLightIrradiance( directionalLight, geometry, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\n\t\tdirectionalLightShadow = directionalLightShadows[ i ];\n\t\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\n\tRectAreaLight rectAreaLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\n\t\trectAreaLight = rectAreaLights[ i ];\n\t\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if defined( RE_IndirectDiffuse )\n\tvec3 iblIrradiance = vec3( 0.0 );\n\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\n\tirradiance += getLightProbeIrradiance( lightProbe, geometry );\n\t#if ( NUM_HEMI_LIGHTS > 0 )\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\n\t\t\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry );\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if defined( RE_IndirectSpecular )\n\tvec3 radiance = vec3( 0.0 );\n\tvec3 clearcoatRadiance = vec3( 0.0 );\n#endif",lights_fragment_maps:"#if defined( RE_IndirectDiffuse )\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\n\t\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\n\t\t#ifndef PHYSICALLY_CORRECT_LIGHTS\n\t\t\tlightMapIrradiance *= PI;\n\t\t#endif\n\t\tirradiance += lightMapIrradiance;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\n\t\tiblIrradiance += getLightProbeIndirectIrradiance( geometry, maxMipLevel );\n\t#endif\n#endif\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\n\tradiance += getLightProbeIndirectRadiance( geometry.viewDir, geometry.normal, material.specularRoughness, maxMipLevel );\n\t#ifdef CLEARCOAT\n\t\tclearcoatRadiance += getLightProbeIndirectRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness, maxMipLevel );\n\t#endif\n#endif",lights_fragment_end:"#if defined( RE_IndirectDiffuse )\n\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\n#endif\n#if defined( RE_IndirectSpecular )\n\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\n#endif",logdepthbuf_fragment:"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\n\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\n#endif",logdepthbuf_pars_fragment:"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\n\tuniform float logDepthBufFC;\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif",logdepthbuf_pars_vertex:"#ifdef USE_LOGDEPTHBUF\n\t#ifdef USE_LOGDEPTHBUF_EXT\n\t\tvarying float vFragDepth;\n\t\tvarying float vIsPerspective;\n\t#else\n\t\tuniform float logDepthBufFC;\n\t#endif\n#endif",logdepthbuf_vertex:"#ifdef USE_LOGDEPTHBUF\n\t#ifdef USE_LOGDEPTHBUF_EXT\n\t\tvFragDepth = 1.0 + gl_Position.w;\n\t\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\n\t#else\n\t\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\n\t\t\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\n\t\t\tgl_Position.z *= gl_Position.w;\n\t\t}\n\t#endif\n#endif",map_fragment:"#ifdef USE_MAP\n\tvec4 texelColor = texture2D( map, vUv );\n\ttexelColor = mapTexelToLinear( texelColor );\n\tdiffuseColor *= texelColor;\n#endif",map_pars_fragment:"#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif",map_particle_fragment:"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\n#endif\n#ifdef USE_MAP\n\tvec4 mapTexel = texture2D( map, uv );\n\tdiffuseColor *= mapTexelToLinear( mapTexel );\n#endif\n#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\n#endif",map_particle_pars_fragment:"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\tuniform mat3 uvTransform;\n#endif\n#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif",metalnessmap_fragment:"float metalnessFactor = metalness;\n#ifdef USE_METALNESSMAP\n\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\n\tmetalnessFactor *= texelMetalness.b;\n#endif",metalnessmap_pars_fragment:"#ifdef USE_METALNESSMAP\n\tuniform sampler2D metalnessMap;\n#endif",morphnormal_vertex:"#ifdef USE_MORPHNORMALS\n\tobjectNormal *= morphTargetBaseInfluence;\n\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\n\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\n\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\n\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\n#endif",morphtarget_pars_vertex:"#ifdef USE_MORPHTARGETS\n\tuniform float morphTargetBaseInfluence;\n\t#ifndef USE_MORPHNORMALS\n\t\tuniform float morphTargetInfluences[ 8 ];\n\t#else\n\t\tuniform float morphTargetInfluences[ 4 ];\n\t#endif\n#endif",morphtarget_vertex:"#ifdef USE_MORPHTARGETS\n\ttransformed *= morphTargetBaseInfluence;\n\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\n\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\n\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\n\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\n\t#ifndef USE_MORPHNORMALS\n\t\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\n\t\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\n\t\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\n\t\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\n\t#endif\n#endif",normal_fragment_begin:"float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\n#ifdef FLAT_SHADED\n\tvec3 fdx = vec3( dFdx( vViewPosition.x ), dFdx( vViewPosition.y ), dFdx( vViewPosition.z ) );\n\tvec3 fdy = vec3( dFdy( vViewPosition.x ), dFdy( vViewPosition.y ), dFdy( vViewPosition.z ) );\n\tvec3 normal = normalize( cross( fdx, fdy ) );\n#else\n\tvec3 normal = normalize( vNormal );\n\t#ifdef DOUBLE_SIDED\n\t\tnormal = normal * faceDirection;\n\t#endif\n\t#ifdef USE_TANGENT\n\t\tvec3 tangent = normalize( vTangent );\n\t\tvec3 bitangent = normalize( vBitangent );\n\t\t#ifdef DOUBLE_SIDED\n\t\t\ttangent = tangent * faceDirection;\n\t\t\tbitangent = bitangent * faceDirection;\n\t\t#endif\n\t\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\n\t\t\tmat3 vTBN = mat3( tangent, bitangent, normal );\n\t\t#endif\n\t#endif\n#endif\nvec3 geometryNormal = normal;",normal_fragment_maps:"#ifdef OBJECTSPACE_NORMALMAP\n\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\n\t#ifdef FLIP_SIDED\n\t\tnormal = - normal;\n\t#endif\n\t#ifdef DOUBLE_SIDED\n\t\tnormal = normal * faceDirection;\n\t#endif\n\tnormal = normalize( normalMatrix * normal );\n#elif defined( TANGENTSPACE_NORMALMAP )\n\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\n\tmapN.xy *= normalScale;\n\t#ifdef USE_TANGENT\n\t\tnormal = normalize( vTBN * mapN );\n\t#else\n\t\tnormal = perturbNormal2Arb( -vViewPosition, normal, mapN, faceDirection );\n\t#endif\n#elif defined( USE_BUMPMAP )\n\tnormal = perturbNormalArb( -vViewPosition, normal, dHdxy_fwd(), faceDirection );\n#endif",normalmap_pars_fragment:"#ifdef USE_NORMALMAP\n\tuniform sampler2D normalMap;\n\tuniform vec2 normalScale;\n#endif\n#ifdef OBJECTSPACE_NORMALMAP\n\tuniform mat3 normalMatrix;\n#endif\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\n\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\n\t\tvec3 q0 = vec3( dFdx( eye_pos.x ), dFdx( eye_pos.y ), dFdx( eye_pos.z ) );\n\t\tvec3 q1 = vec3( dFdy( eye_pos.x ), dFdy( eye_pos.y ), dFdy( eye_pos.z ) );\n\t\tvec2 st0 = dFdx( vUv.st );\n\t\tvec2 st1 = dFdy( vUv.st );\n\t\tvec3 N = surf_norm;\n\t\tvec3 q1perp = cross( q1, N );\n\t\tvec3 q0perp = cross( N, q0 );\n\t\tvec3 T = q1perp * st0.x + q0perp * st1.x;\n\t\tvec3 B = q1perp * st0.y + q0perp * st1.y;\n\t\tfloat det = max( dot( T, T ), dot( B, B ) );\n\t\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\n\t\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\n\t}\n#endif",clearcoat_normal_fragment_begin:"#ifdef CLEARCOAT\n\tvec3 clearcoatNormal = geometryNormal;\n#endif",clearcoat_normal_fragment_maps:"#ifdef USE_CLEARCOAT_NORMALMAP\n\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\n\tclearcoatMapN.xy *= clearcoatNormalScale;\n\t#ifdef USE_TANGENT\n\t\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\n\t#else\n\t\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\n\t#endif\n#endif",clearcoat_pars_fragment:"#ifdef USE_CLEARCOATMAP\n\tuniform sampler2D clearcoatMap;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform sampler2D clearcoatRoughnessMap;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform sampler2D clearcoatNormalMap;\n\tuniform vec2 clearcoatNormalScale;\n#endif",packing:"vec3 packNormalToRGB( const in vec3 normal ) {\n\treturn normalize( normal ) * 0.5 + 0.5;\n}\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\n\treturn 2.0 * rgb.xyz - 1.0;\n}\nconst float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\nconst float ShiftRight8 = 1. / 256.;\nvec4 packDepthToRGBA( const in float v ) {\n\tvec4 r = vec4( fract( v * PackFactors ), v );\n\tr.yzw -= r.xyz * ShiftRight8;\treturn r * PackUpscale;\n}\nfloat unpackRGBAToDepth( const in vec4 v ) {\n\treturn dot( v, UnpackFactors );\n}\nvec4 pack2HalfToRGBA( vec2 v ) {\n\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ));\n\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w);\n}\nvec2 unpackRGBATo2Half( vec4 v ) {\n\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\n}\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( viewZ + near ) / ( near - far );\n}\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\n\treturn linearClipZ * ( near - far ) - near;\n}\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn (( near + viewZ ) * far ) / (( far - near ) * viewZ );\n}\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\n\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\n}",premultiplied_alpha_fragment:"#ifdef PREMULTIPLIED_ALPHA\n\tgl_FragColor.rgb *= gl_FragColor.a;\n#endif",project_vertex:"vec4 mvPosition = vec4( transformed, 1.0 );\n#ifdef USE_INSTANCING\n\tmvPosition = instanceMatrix * mvPosition;\n#endif\nmvPosition = modelViewMatrix * mvPosition;\ngl_Position = projectionMatrix * mvPosition;",dithering_fragment:"#ifdef DITHERING\n\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\n#endif",dithering_pars_fragment:"#ifdef DITHERING\n\tvec3 dithering( vec3 color ) {\n\t\tfloat grid_position = rand( gl_FragCoord.xy );\n\t\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\n\t\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\n\t\treturn color + dither_shift_RGB;\n\t}\n#endif",roughnessmap_fragment:"float roughnessFactor = roughness;\n#ifdef USE_ROUGHNESSMAP\n\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\n\troughnessFactor *= texelRoughness.g;\n#endif",roughnessmap_pars_fragment:"#ifdef USE_ROUGHNESSMAP\n\tuniform sampler2D roughnessMap;\n#endif",shadowmap_pars_fragment:"#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\n\t\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\n\t}\n\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\n\t\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\n\t}\n\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\n\t\tfloat occlusion = 1.0;\n\t\tvec2 distribution = texture2DDistribution( shadow, uv );\n\t\tfloat hard_shadow = step( compare , distribution.x );\n\t\tif (hard_shadow != 1.0 ) {\n\t\t\tfloat distance = compare - distribution.x ;\n\t\t\tfloat variance = max( 0.00000, distribution.y * distribution.y );\n\t\t\tfloat softness_probability = variance / (variance + distance * distance );\t\t\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );\t\t\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\n\t\t}\n\t\treturn occlusion;\n\t}\n\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\n\t\tfloat shadow = 1.0;\n\t\tshadowCoord.xyz /= shadowCoord.w;\n\t\tshadowCoord.z += shadowBias;\n\t\tbvec4 inFrustumVec = bvec4 ( shadowCoord.x >= 0.0, shadowCoord.x <= 1.0, shadowCoord.y >= 0.0, shadowCoord.y <= 1.0 );\n\t\tbool inFrustum = all( inFrustumVec );\n\t\tbvec2 frustumTestVec = bvec2( inFrustum, shadowCoord.z <= 1.0 );\n\t\tbool frustumTest = all( frustumTestVec );\n\t\tif ( frustumTest ) {\n\t\t#if defined( SHADOWMAP_TYPE_PCF )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx0 = - texelSize.x * shadowRadius;\n\t\t\tfloat dy0 = - texelSize.y * shadowRadius;\n\t\t\tfloat dx1 = + texelSize.x * shadowRadius;\n\t\t\tfloat dy1 = + texelSize.y * shadowRadius;\n\t\t\tfloat dx2 = dx0 / 2.0;\n\t\t\tfloat dy2 = dy0 / 2.0;\n\t\t\tfloat dx3 = dx1 / 2.0;\n\t\t\tfloat dy3 = dy1 / 2.0;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\n\t\t\t) * ( 1.0 / 17.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx = texelSize.x;\n\t\t\tfloat dy = texelSize.y;\n\t\t\tvec2 uv = shadowCoord.xy;\n\t\t\tvec2 f = fract( uv * shadowMapSize + 0.5 );\n\t\t\tuv -= f * texelSize;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ), \n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ), \n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ), \n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ), \n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ), \n\t\t\t\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t\tf.x ),\n\t\t\t\t\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ), \n\t\t\t\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t\tf.x ),\n\t\t\t\t\t f.y )\n\t\t\t) * ( 1.0 / 9.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_VSM )\n\t\t\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#else\n\t\t\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#endif\n\t\t}\n\t\treturn shadow;\n\t}\n\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\n\t\tvec3 absV = abs( v );\n\t\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\n\t\tabsV *= scaleToCube;\n\t\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\n\t\tvec2 planar = v.xy;\n\t\tfloat almostATexel = 1.5 * texelSizeY;\n\t\tfloat almostOne = 1.0 - almostATexel;\n\t\tif ( absV.z >= almostOne ) {\n\t\t\tif ( v.z > 0.0 )\n\t\t\t\tplanar.x = 4.0 - v.x;\n\t\t} else if ( absV.x >= almostOne ) {\n\t\t\tfloat signX = sign( v.x );\n\t\t\tplanar.x = v.z * signX + 2.0 * signX;\n\t\t} else if ( absV.y >= almostOne ) {\n\t\t\tfloat signY = sign( v.y );\n\t\t\tplanar.x = v.x + 2.0 * signY + 2.0;\n\t\t\tplanar.y = v.z * signY - 2.0;\n\t\t}\n\t\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\n\t}\n\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\n\t\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\n\t\tvec3 lightToPosition = shadowCoord.xyz;\n\t\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );\t\tdp += shadowBias;\n\t\tvec3 bd3D = normalize( lightToPosition );\n\t\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\n\t\t\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\n\t\t\treturn (\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\n\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\n\t\t\t) * ( 1.0 / 9.0 );\n\t\t#else\n\t\t\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\n\t\t#endif\n\t}\n#endif",shadowmap_pars_vertex:"#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tuniform mat4 spotShadowMatrix[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n#endif",shadowmap_vertex:"#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SPOT_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0\n\t\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\t\tvec4 shadowWorldPosition;\n\t#endif\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\n\t\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\n\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias, 0 );\n\t\tvSpotShadowCoord[ i ] = spotShadowMatrix[ i ] * shadowWorldPosition;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\n\t\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n#endif",shadowmask_pars_fragment:"float getShadowMask() {\n\tfloat shadow = 1.0;\n\t#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\tdirectionalLight = directionalLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\n\t\tspotLight = spotLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\tpointLight = pointLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#endif\n\treturn shadow;\n}",skinbase_vertex:"#ifdef USE_SKINNING\n\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\n\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\n\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\n\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\n#endif",skinning_pars_vertex:"#ifdef USE_SKINNING\n\tuniform mat4 bindMatrix;\n\tuniform mat4 bindMatrixInverse;\n\t#ifdef BONE_TEXTURE\n\t\tuniform highp sampler2D boneTexture;\n\t\tuniform int boneTextureSize;\n\t\tmat4 getBoneMatrix( const in float i ) {\n\t\t\tfloat j = i * 4.0;\n\t\t\tfloat x = mod( j, float( boneTextureSize ) );\n\t\t\tfloat y = floor( j / float( boneTextureSize ) );\n\t\t\tfloat dx = 1.0 / float( boneTextureSize );\n\t\t\tfloat dy = 1.0 / float( boneTextureSize );\n\t\t\ty = dy * ( y + 0.5 );\n\t\t\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\n\t\t\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\n\t\t\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\n\t\t\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\n\t\t\tmat4 bone = mat4( v1, v2, v3, v4 );\n\t\t\treturn bone;\n\t\t}\n\t#else\n\t\tuniform mat4 boneMatrices[ MAX_BONES ];\n\t\tmat4 getBoneMatrix( const in float i ) {\n\t\t\tmat4 bone = boneMatrices[ int(i) ];\n\t\t\treturn bone;\n\t\t}\n\t#endif\n#endif",skinning_vertex:"#ifdef USE_SKINNING\n\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\n\tvec4 skinned = vec4( 0.0 );\n\tskinned += boneMatX * skinVertex * skinWeight.x;\n\tskinned += boneMatY * skinVertex * skinWeight.y;\n\tskinned += boneMatZ * skinVertex * skinWeight.z;\n\tskinned += boneMatW * skinVertex * skinWeight.w;\n\ttransformed = ( bindMatrixInverse * skinned ).xyz;\n#endif",skinnormal_vertex:"#ifdef USE_SKINNING\n\tmat4 skinMatrix = mat4( 0.0 );\n\tskinMatrix += skinWeight.x * boneMatX;\n\tskinMatrix += skinWeight.y * boneMatY;\n\tskinMatrix += skinWeight.z * boneMatZ;\n\tskinMatrix += skinWeight.w * boneMatW;\n\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\n\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\n\t#ifdef USE_TANGENT\n\t\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\n\t#endif\n#endif",specularmap_fragment:"float specularStrength;\n#ifdef USE_SPECULARMAP\n\tvec4 texelSpecular = texture2D( specularMap, vUv );\n\tspecularStrength = texelSpecular.r;\n#else\n\tspecularStrength = 1.0;\n#endif",specularmap_pars_fragment:"#ifdef USE_SPECULARMAP\n\tuniform sampler2D specularMap;\n#endif",tonemapping_fragment:"#if defined( TONE_MAPPING )\n\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\n#endif",tonemapping_pars_fragment:"#ifndef saturate\n#define saturate(a) clamp( a, 0.0, 1.0 )\n#endif\nuniform float toneMappingExposure;\nvec3 LinearToneMapping( vec3 color ) {\n\treturn toneMappingExposure * color;\n}\nvec3 ReinhardToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\treturn saturate( color / ( vec3( 1.0 ) + color ) );\n}\nvec3 OptimizedCineonToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\tcolor = max( vec3( 0.0 ), color - 0.004 );\n\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\n}\nvec3 RRTAndODTFit( vec3 v ) {\n\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\n\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\n\treturn a / b;\n}\nvec3 ACESFilmicToneMapping( vec3 color ) {\n\tconst mat3 ACESInputMat = mat3(\n\t\tvec3( 0.59719, 0.07600, 0.02840 ),\t\tvec3( 0.35458, 0.90834, 0.13383 ),\n\t\tvec3( 0.04823, 0.01566, 0.83777 )\n\t);\n\tconst mat3 ACESOutputMat = mat3(\n\t\tvec3(\t1.60475, -0.10208, -0.00327 ),\t\tvec3( -0.53108,\t1.10813, -0.07276 ),\n\t\tvec3( -0.07367, -0.00605,\t1.07602 )\n\t);\n\tcolor *= toneMappingExposure / 0.6;\n\tcolor = ACESInputMat * color;\n\tcolor = RRTAndODTFit( color );\n\tcolor = ACESOutputMat * color;\n\treturn saturate( color );\n}\nvec3 CustomToneMapping( vec3 color ) { return color; }",transmissionmap_fragment:"#ifdef USE_TRANSMISSIONMAP\n\ttotalTransmission *= texture2D( transmissionMap, vUv ).r;\n#endif",transmissionmap_pars_fragment:"#ifdef USE_TRANSMISSIONMAP\n\tuniform sampler2D transmissionMap;\n#endif",uv_pars_fragment:"#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\n\tvarying vec2 vUv;\n#endif",uv_pars_vertex:"#ifdef USE_UV\n\t#ifdef UVS_VERTEX_ONLY\n\t\tvec2 vUv;\n\t#else\n\t\tvarying vec2 vUv;\n\t#endif\n\tuniform mat3 uvTransform;\n#endif",uv_vertex:"#ifdef USE_UV\n\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n#endif",uv2_pars_fragment:"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\n\tvarying vec2 vUv2;\n#endif",uv2_pars_vertex:"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\n\tattribute vec2 uv2;\n\tvarying vec2 vUv2;\n\tuniform mat3 uv2Transform;\n#endif",uv2_vertex:"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\n\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\n#endif",worldpos_vertex:"#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP )\n\tvec4 worldPosition = vec4( transformed, 1.0 );\n\t#ifdef USE_INSTANCING\n\t\tworldPosition = instanceMatrix * worldPosition;\n\t#endif\n\tworldPosition = modelMatrix * worldPosition;\n#endif",background_frag:"uniform sampler2D t2D;\nvarying vec2 vUv;\nvoid main() {\n\tvec4 texColor = texture2D( t2D, vUv );\n\tgl_FragColor = mapTexelToLinear( texColor );\n\t#include \n\t#include \n}",background_vert:"varying vec2 vUv;\nuniform mat3 uvTransform;\nvoid main() {\n\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\tgl_Position = vec4( position.xy, 1.0, 1.0 );\n}",cube_frag:"#include \nuniform float opacity;\nvarying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvec3 vReflect = vWorldDirection;\n\t#include \n\tgl_FragColor = envColor;\n\tgl_FragColor.a *= opacity;\n\t#include \n\t#include \n}",cube_vert:"varying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include \n\t#include \n\tgl_Position.z = gl_Position.w;\n}",depth_frag:"#if DEPTH_PACKING == 3200\n\tuniform float opacity;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( 1.0 );\n\t#if DEPTH_PACKING == 3200\n\t\tdiffuseColor.a = opacity;\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\n\t#if DEPTH_PACKING == 3200\n\t\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\n\t#elif DEPTH_PACKING == 3201\n\t\tgl_FragColor = packDepthToRGBA( fragCoordZ );\n\t#endif\n}",depth_vert:"#include \n#include \n#include \n#include \n#include \n#include \n#include \nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\t#include \n\t#include \n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include \n\t\t#include \n\t\t#include \n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvHighPrecisionZW = gl_Position.zw;\n}",distanceRGBA_frag:"#define DISTANCE\nuniform vec3 referencePosition;\nuniform float nearDistance;\nuniform float farDistance;\nvarying vec3 vWorldPosition;\n#include \n#include \n#include \n#include \n#include \n#include \nvoid main () {\n\t#include \n\tvec4 diffuseColor = vec4( 1.0 );\n\t#include \n\t#include \n\t#include \n\tfloat dist = length( vWorldPosition - referencePosition );\n\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\n\tdist = saturate( dist );\n\tgl_FragColor = packDepthToRGBA( dist );\n}",distanceRGBA_vert:"#define DISTANCE\nvarying vec3 vWorldPosition;\n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include \n\t\t#include \n\t\t#include \n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvWorldPosition = worldPosition.xyz;\n}",equirect_frag:"uniform sampler2D tEquirect;\nvarying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvec3 direction = normalize( vWorldDirection );\n\tvec2 sampleUV = equirectUv( direction );\n\tvec4 texColor = texture2D( tEquirect, sampleUV );\n\tgl_FragColor = mapTexelToLinear( texColor );\n\t#include \n\t#include \n}",equirect_vert:"varying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include \n\t#include \n}",linedashed_frag:"uniform vec3 diffuse;\nuniform float opacity;\nuniform float dashSize;\nuniform float totalSize;\nvarying float vLineDistance;\n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\n\t\tdiscard;\n\t}\n\tvec3 outgoingLight = vec3( 0.0 );\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\t#include \n\toutgoingLight = diffuseColor.rgb;\n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n}",linedashed_vert:"uniform float scale;\nattribute float lineDistance;\nvarying float vLineDistance;\n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvLineDistance = scale * lineDistance;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshbasic_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\t#ifdef USE_LIGHTMAP\n\t\n\t\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\n\t\treflectedLight.indirectDiffuse += lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\n\t#else\n\t\treflectedLight.indirectDiffuse += vec3( 1.0 );\n\t#endif\n\t#include \n\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\n\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\n\t#include \n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshbasic_vert:"#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#ifdef USE_ENVMAP\n\t#include \n\t#include \n\t#include \n\t#include \n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshlambert_frag:"uniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\nvarying vec3 vLightFront;\nvarying vec3 vIndirectFront;\n#ifdef DOUBLE_SIDED\n\tvarying vec3 vLightBack;\n\tvarying vec3 vIndirectBack;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#ifdef DOUBLE_SIDED\n\t\treflectedLight.indirectDiffuse += ( gl_FrontFacing ) ? vIndirectFront : vIndirectBack;\n\t#else\n\t\treflectedLight.indirectDiffuse += vIndirectFront;\n\t#endif\n\t#include \n\treflectedLight.indirectDiffuse *= BRDF_Diffuse_Lambert( diffuseColor.rgb );\n\t#ifdef DOUBLE_SIDED\n\t\treflectedLight.directDiffuse = ( gl_FrontFacing ) ? vLightFront : vLightBack;\n\t#else\n\t\treflectedLight.directDiffuse = vLightFront;\n\t#endif\n\treflectedLight.directDiffuse *= BRDF_Diffuse_Lambert( diffuseColor.rgb ) * getShadowMask();\n\t#include \n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\t#include \n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshlambert_vert:"#define LAMBERT\nvarying vec3 vLightFront;\nvarying vec3 vIndirectFront;\n#ifdef DOUBLE_SIDED\n\tvarying vec3 vLightBack;\n\tvarying vec3 vIndirectBack;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshmatcap_frag:"#define MATCAP\nuniform vec3 diffuse;\nuniform float opacity;\nuniform sampler2D matcap;\nvarying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 viewDir = normalize( vViewPosition );\n\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\n\tvec3 y = cross( viewDir, x );\n\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;\n\t#ifdef USE_MATCAP\n\t\tvec4 matcapColor = texture2D( matcap, uv );\n\t\tmatcapColor = matcapTexelToLinear( matcapColor );\n\t#else\n\t\tvec4 matcapColor = vec4( 1.0 );\n\t#endif\n\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshmatcap_vert:"#define MATCAP\nvarying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#ifndef FLAT_SHADED\n\t\tvNormal = normalize( transformedNormal );\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n}",meshtoon_frag:"#define TOON\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshtoon_vert:"#define TOON\nvarying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n\t#include \n\t#include \n\t#include \n}",meshphong_frag:"#define PHONG\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform vec3 specular;\nuniform float shininess;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\n\t#include \n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshphong_vert:"#define PHONG\nvarying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n\t#include \n\t#include \n\t#include \n\t#include \n}",meshphysical_frag:"#define STANDARD\n#ifdef PHYSICAL\n\t#define REFLECTIVITY\n\t#define CLEARCOAT\n\t#define TRANSMISSION\n#endif\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float roughness;\nuniform float metalness;\nuniform float opacity;\n#ifdef TRANSMISSION\n\tuniform float transmission;\n#endif\n#ifdef REFLECTIVITY\n\tuniform float reflectivity;\n#endif\n#ifdef CLEARCOAT\n\tuniform float clearcoat;\n\tuniform float clearcoatRoughness;\n#endif\n#ifdef USE_SHEEN\n\tuniform vec3 sheen;\n#endif\nvarying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#ifdef TRANSMISSION\n\t\tfloat totalTransmission = transmission;\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\n\t#ifdef TRANSMISSION\n\t\tdiffuseColor.a *= mix( saturate( 1. - totalTransmission + linearToRelativeLuminance( reflectedLight.directSpecular + reflectedLight.indirectSpecular ) ), 1.0, metalness );\n\t#endif\n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",meshphysical_vert:"#define STANDARD\nvarying vec3 vViewPosition;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n\t#ifdef USE_TANGENT\n\t\tvTangent = normalize( transformedTangent );\n\t\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\n\t#endif\n#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n\t#include \n\t#include \n\t#include \n}",normal_frag:"#define NORMAL\nuniform float opacity;\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\n\tvarying vec3 vViewPosition;\n#endif\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\tgl_FragColor = vec4( packNormalToRGB( normal ), opacity );\n}",normal_vert:"#define NORMAL\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\n\tvarying vec3 vViewPosition;\n#endif\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n\t#ifdef USE_TANGENT\n\t\tvTangent = normalize( transformedTangent );\n\t\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\n\t#endif\n#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\n\tvViewPosition = - mvPosition.xyz;\n#endif\n}",points_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec3 outgoingLight = vec3( 0.0 );\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\t#include \n\t#include \n\t#include \n\toutgoingLight = diffuseColor.rgb;\n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n\t#include \n}",points_vert:"uniform float size;\nuniform float scale;\n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\tgl_PointSize = size;\n\t#ifdef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n}",shadow_frag:"uniform vec3 color;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\n\t#include \n\t#include \n\t#include \n}",shadow_vert:"#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}",sprite_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec3 outgoingLight = vec3( 0.0 );\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\t#include \n\t#include \n\t#include \n\toutgoingLight = diffuseColor.rgb;\n\tgl_FragColor = vec4( outgoingLight, diffuseColor.a );\n\t#include \n\t#include \n\t#include \n}",sprite_vert:"uniform float rotation;\nuniform vec2 center;\n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\n\tvec2 scale;\n\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\n\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\n\t#ifndef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) scale *= - mvPosition.z;\n\t#endif\n\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\n\tvec2 rotatedPosition;\n\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\n\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\n\tmvPosition.xy += rotatedPosition;\n\tgl_Position = projectionMatrix * mvPosition;\n\t#include \n\t#include \n\t#include \n}"},ui={common:{diffuse:{value:new tn(15658734)},opacity:{value:1},map:{value:null},uvTransform:{value:new yt},uv2Transform:{value:new yt},alphaMap:{value:null}},specularmap:{specularMap:{value:null}},envmap:{envMap:{value:null},flipEnvMap:{value:-1},reflectivity:{value:1},refractionRatio:{value:.98},maxMipLevel:{value:0}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1}},emissivemap:{emissiveMap:{value:null}},bumpmap:{bumpMap:{value:null},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalScale:{value:new vt(1,1)}},displacementmap:{displacementMap:{value:null},displacementScale:{value:1},displacementBias:{value:0}},roughnessmap:{roughnessMap:{value:null}},metalnessmap:{metalnessMap:{value:null}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new tn(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotShadowMap:{value:[]},spotShadowMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new tn(15658734)},opacity:{value:1},size:{value:1},scale:{value:1},map:{value:null},alphaMap:{value:null},uvTransform:{value:new yt}},sprite:{diffuse:{value:new tn(15658734)},opacity:{value:1},center:{value:new vt(.5,.5)},rotation:{value:0},map:{value:null},alphaMap:{value:null},uvTransform:{value:new yt}}},di={basic:{uniforms:Yn([ui.common,ui.specularmap,ui.envmap,ui.aomap,ui.lightmap,ui.fog]),vertexShader:hi.meshbasic_vert,fragmentShader:hi.meshbasic_frag},lambert:{uniforms:Yn([ui.common,ui.specularmap,ui.envmap,ui.aomap,ui.lightmap,ui.emissivemap,ui.fog,ui.lights,{emissive:{value:new tn(0)}}]),vertexShader:hi.meshlambert_vert,fragmentShader:hi.meshlambert_frag},phong:{uniforms:Yn([ui.common,ui.specularmap,ui.envmap,ui.aomap,ui.lightmap,ui.emissivemap,ui.bumpmap,ui.normalmap,ui.displacementmap,ui.fog,ui.lights,{emissive:{value:new tn(0)},specular:{value:new tn(1118481)},shininess:{value:30}}]),vertexShader:hi.meshphong_vert,fragmentShader:hi.meshphong_frag},standard:{uniforms:Yn([ui.common,ui.envmap,ui.aomap,ui.lightmap,ui.emissivemap,ui.bumpmap,ui.normalmap,ui.displacementmap,ui.roughnessmap,ui.metalnessmap,ui.fog,ui.lights,{emissive:{value:new tn(0)},roughness:{value:1},metalness:{value:0},envMapIntensity:{value:1}}]),vertexShader:hi.meshphysical_vert,fragmentShader:hi.meshphysical_frag},toon:{uniforms:Yn([ui.common,ui.aomap,ui.lightmap,ui.emissivemap,ui.bumpmap,ui.normalmap,ui.displacementmap,ui.gradientmap,ui.fog,ui.lights,{emissive:{value:new tn(0)}}]),vertexShader:hi.meshtoon_vert,fragmentShader:hi.meshtoon_frag},matcap:{uniforms:Yn([ui.common,ui.bumpmap,ui.normalmap,ui.displacementmap,ui.fog,{matcap:{value:null}}]),vertexShader:hi.meshmatcap_vert,fragmentShader:hi.meshmatcap_frag},points:{uniforms:Yn([ui.points,ui.fog]),vertexShader:hi.points_vert,fragmentShader:hi.points_frag},dashed:{uniforms:Yn([ui.common,ui.fog,{scale:{value:1},dashSize:{value:1},totalSize:{value:2}}]),vertexShader:hi.linedashed_vert,fragmentShader:hi.linedashed_frag},depth:{uniforms:Yn([ui.common,ui.displacementmap]),vertexShader:hi.depth_vert,fragmentShader:hi.depth_frag},normal:{uniforms:Yn([ui.common,ui.bumpmap,ui.normalmap,ui.displacementmap,{opacity:{value:1}}]),vertexShader:hi.normal_vert,fragmentShader:hi.normal_frag},sprite:{uniforms:Yn([ui.sprite,ui.fog]),vertexShader:hi.sprite_vert,fragmentShader:hi.sprite_frag},background:{uniforms:{uvTransform:{value:new 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0!==r.depthPacking&&r.depthPacking,index0AttributeName:r.index0AttributeName,extensionDerivatives:r.extensions&&r.extensions.derivatives,extensionFragDepth:r.extensions&&r.extensions.fragDepth,extensionDrawBuffers:r.extensions&&r.extensions.drawBuffers,extensionShaderTextureLOD:r.extensions&&r.extensions.shaderTextureLOD,rendererExtensionFragDepth:o||n.has("EXT_frag_depth"),rendererExtensionDrawBuffers:o||n.has("WEBGL_draw_buffers"),rendererExtensionShaderTextureLod:o||n.has("EXT_shader_texture_lod"),customProgramCacheKey:r.customProgramCacheKey()}},getProgramCacheKey:function(e){const n=[];if(e.shaderID?n.push(e.shaderID):(n.push(e.fragmentShader),n.push(e.vertexShader)),void 0!==e.defines)for(const t in e.defines)n.push(t),n.push(e.defines[t]);if(!1===e.isRawShaderMaterial){for(let t=0;t1&&i.sort(t||$r),r.length>1&&r.sort(e||ts)}}}function ns(t){let e=new WeakMap;return{get:function(n,i){let r;return!1===e.has(n)?(r=new es(t),e.set(n,[r])):i>=e.get(n).length?(r=new es(t),e.get(n).push(r)):r=e.get(n)[i],r},dispose:function(){e=new WeakMap}}}function is(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case"DirectionalLight":n={direction:new Lt,color:new tn};break;case"SpotLight":n={position:new Lt,direction:new Lt,color:new tn,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case"PointLight":n={position:new Lt,color:new tn,distance:0,decay:0};break;case"HemisphereLight":n={direction:new Lt,skyColor:new tn,groundColor:new tn};break;case"RectAreaLight":n={color:new tn,position:new Lt,halfWidth:new Lt,halfHeight:new Lt}}return t[e.id]=n,n}}}let rs=0;function ss(t,e){return(e.castShadow?1:0)-(t.castShadow?1:0)}function as(t,e){const n=new is,i=function(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case"DirectionalLight":case"SpotLight":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new vt};break;case"PointLight":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new vt,shadowCameraNear:1,shadowCameraFar:1e3}}return t[e.id]=n,n}}}(),r={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotShadow:[],spotShadowMap:[],spotShadowMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[]};for(let t=0;t<9;t++)r.probe.push(new Lt);const s=new Lt,a=new se,o=new se;return{setup:function(s){let a=0,o=0,l=0;for(let t=0;t<9;t++)r.probe[t].set(0,0,0);let c=0,h=0,u=0,d=0,p=0,m=0,f=0,g=0;s.sort(ss);for(let t=0,e=s.length;t0&&(e.isWebGL2||!0===t.has("OES_texture_float_linear")?(r.rectAreaLTC1=ui.LTC_FLOAT_1,r.rectAreaLTC2=ui.LTC_FLOAT_2):!0===t.has("OES_texture_half_float_linear")?(r.rectAreaLTC1=ui.LTC_HALF_1,r.rectAreaLTC2=ui.LTC_HALF_2):console.error("THREE.WebGLRenderer: Unable to use RectAreaLight. Missing WebGL extensions.")),r.ambient[0]=a,r.ambient[1]=o,r.ambient[2]=l;const v=r.hash;v.directionalLength===c&&v.pointLength===h&&v.spotLength===u&&v.rectAreaLength===d&&v.hemiLength===p&&v.numDirectionalShadows===m&&v.numPointShadows===f&&v.numSpotShadows===g||(r.directional.length=c,r.spot.length=u,r.rectArea.length=d,r.point.length=h,r.hemi.length=p,r.directionalShadow.length=m,r.directionalShadowMap.length=m,r.pointShadow.length=f,r.pointShadowMap.length=f,r.spotShadow.length=g,r.spotShadowMap.length=g,r.directionalShadowMatrix.length=m,r.pointShadowMatrix.length=f,r.spotShadowMatrix.length=g,v.directionalLength=c,v.pointLength=h,v.spotLength=u,v.rectAreaLength=d,v.hemiLength=p,v.numDirectionalShadows=m,v.numPointShadows=f,v.numSpotShadows=g,r.version=rs++)},setupView:function(t,e){let n=0,i=0,l=0,c=0,h=0;const u=e.matrixWorldInverse;for(let e=0,d=t.length;e=n.get(i).length?(s=new os(t,e),n.get(i).push(s)):s=n.get(i)[r],s},dispose:function(){n=new WeakMap}}}class cs extends Xe{constructor(t){super(),this.type="MeshDepthMaterial",this.depthPacking=3200,this.skinning=!1,this.morphTargets=!1,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.depthPacking=t.depthPacking,this.skinning=t.skinning,this.morphTargets=t.morphTargets,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this}}cs.prototype.isMeshDepthMaterial=!0;class hs extends Xe{constructor(t){super(),this.type="MeshDistanceMaterial",this.referencePosition=new 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r=i.get(t);t.version>0&&r.__version!==t.version?Z(r,t,e):(n.activeTexture(33984+e),n.bindTexture(32879,r.__webglTexture))},this.setTextureCube=W,this.setupRenderTarget=function(e){const r=e.texture,l=i.get(e),c=i.get(r);e.addEventListener("dispose",U),c.__webglTexture=t.createTexture(),c.__version=r.version,a.memory.textures++;const h=!0===e.isWebGLCubeRenderTarget,u=!0===e.isWebGLMultisampleRenderTarget,d=r.isDataTexture3D||r.isDataTexture2DArray,p=B(e)||o;if(!o||r.format!==T||r.type!==b&&r.type!==M||(r.format=E,console.warn("THREE.WebGLRenderer: Rendering to textures with RGB format is not supported. Using RGBA format instead.")),h){l.__webglFramebuffer=[];for(let e=0;e<6;e++)l.__webglFramebuffer[e]=t.createFramebuffer()}else if(l.__webglFramebuffer=t.createFramebuffer(),u)if(o){l.__webglMultisampledFramebuffer=t.createFramebuffer(),l.__webglColorRenderbuffer=t.createRenderbuffer(),t.bindRenderbuffer(36161,l.__webglColorRenderbuffer);const i=s.convert(r.format),a=s.convert(r.type),o=O(r.internalFormat,i,a),c=$(e);t.renderbufferStorageMultisample(36161,c,o,e.width,e.height),n.bindFramebuffer(36160,l.__webglMultisampledFramebuffer),t.framebufferRenderbuffer(36160,36064,36161,l.__webglColorRenderbuffer),t.bindRenderbuffer(36161,null),e.depthBuffer&&(l.__webglDepthRenderbuffer=t.createRenderbuffer(),Q(l.__webglDepthRenderbuffer,e,!0)),n.bindFramebuffer(36160,null)}else console.warn("THREE.WebGLRenderer: WebGLMultisampleRenderTarget can only be used with WebGL2.");if(h){n.bindTexture(34067,c.__webglTexture),X(34067,r,p);for(let t=0;t<6;t++)J(l.__webglFramebuffer[t],e,36064,34069+t);z(r,p)&&F(34067,r,e.width,e.height),n.bindTexture(34067,null)}else{let t=3553;if(d)if(o){t=r.isDataTexture3D?32879:35866}else console.warn("THREE.DataTexture3D and THREE.DataTexture2DArray only supported with WebGL2.");n.bindTexture(t,c.__webglTexture),X(t,r,p),J(l.__webglFramebuffer,e,36064,t),z(r,p)&&F(3553,r,e.width,e.height),n.bindTexture(3553,null)}e.depthBuffer&&K(e)},this.updateRenderTargetMipmap=function(t){const e=t.texture;if(z(e,B(t)||o)){const r=t.isWebGLCubeRenderTarget?34067:3553,s=i.get(e).__webglTexture;n.bindTexture(r,s),F(r,e,t.width,t.height),n.bindTexture(r,null)}},this.updateMultisampleRenderTarget=function(e){if(e.isWebGLMultisampleRenderTarget)if(o){const r=e.width,s=e.height;let a=16384;e.depthBuffer&&(a|=256),e.stencilBuffer&&(a|=1024);const o=i.get(e);n.bindFramebuffer(36008,o.__webglMultisampledFramebuffer),n.bindFramebuffer(36009,o.__webglFramebuffer),t.blitFramebuffer(0,0,r,s,0,0,r,s,a,9728),n.bindFramebuffer(36008,null),n.bindFramebuffer(36009,o.__webglMultisampledFramebuffer)}else console.warn("THREE.WebGLRenderer: WebGLMultisampleRenderTarget can only be used with WebGL2.")},this.safeSetTexture2D=function(t,e){t&&t.isWebGLRenderTarget&&(!1===tt&&(console.warn("THREE.WebGLTextures.safeSetTexture2D: don't use render targets as textures. Use their .texture property instead."),tt=!0),t=t.texture),V(t,e)},this.safeSetTextureCube=function(t,e){t&&t.isWebGLCubeRenderTarget&&(!1===et&&(console.warn("THREE.WebGLTextures.safeSetTextureCube: don't use cube render targets as textures. Use their .texture property instead."),et=!0),t=t.texture),W(t,e)}}function ms(t,e,n){const i=n.isWebGL2;return{convert:function(t){let n;if(t===x)return 5121;if(1017===t)return 32819;if(1018===t)return 32820;if(1019===t)return 33635;if(1010===t)return 5120;if(1011===t)return 5122;if(t===_)return 5123;if(1013===t)return 5124;if(t===w)return 5125;if(t===b)return 5126;if(t===M)return i?5131:(n=e.get("OES_texture_half_float"),null!==n?n.HALF_FLOAT_OES:null);if(1021===t)return 6406;if(t===T)return 6407;if(t===E)return 6408;if(1024===t)return 6409;if(1025===t)return 6410;if(t===A)return 6402;if(t===L)return 34041;if(1028===t)return 6403;if(1029===t)return 36244;if(1030===t)return 33319;if(1031===t)return 33320;if(1032===t)return 36248;if(1033===t)return 36249;if(t===R||t===C||t===P||t===D){if(n=e.get("WEBGL_compressed_texture_s3tc"),null===n)return null;if(t===R)return n.COMPRESSED_RGB_S3TC_DXT1_EXT;if(t===C)return n.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(t===P)return n.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(t===D)return n.COMPRESSED_RGBA_S3TC_DXT5_EXT}if(t===I||t===N||t===B||t===z){if(n=e.get("WEBGL_compressed_texture_pvrtc"),null===n)return null;if(t===I)return n.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(t===N)return n.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(t===B)return n.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(t===z)return n.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}if(36196===t)return n=e.get("WEBGL_compressed_texture_etc1"),null!==n?n.COMPRESSED_RGB_ETC1_WEBGL:null;if((t===F||t===O)&&(n=e.get("WEBGL_compressed_texture_etc"),null!==n)){if(t===F)return n.COMPRESSED_RGB8_ETC2;if(t===O)return n.COMPRESSED_RGBA8_ETC2_EAC}return 37808===t||37809===t||37810===t||37811===t||37812===t||37813===t||37814===t||37815===t||37816===t||37817===t||37818===t||37819===t||37820===t||37821===t||37840===t||37841===t||37842===t||37843===t||37844===t||37845===t||37846===t||37847===t||37848===t||37849===t||37850===t||37851===t||37852===t||37853===t?(n=e.get("WEBGL_compressed_texture_astc"),null!==n?t:null):36492===t?(n=e.get("EXT_texture_compression_bptc"),null!==n?t:null):t===S?i?34042:(n=e.get("WEBGL_depth_texture"),null!==n?n.UNSIGNED_INT_24_8_WEBGL:null):void 0}}}class fs extends Kn{constructor(t=[]){super(),this.cameras=t}}fs.prototype.isArrayCamera=!0;class gs extends Ce{constructor(){super(),this.type="Group"}}gs.prototype.isGroup=!0;const vs={type:"move"};class ys{constructor(){this._targetRay=null,this._grip=null,this._hand=null}getHandSpace(){return null===this._hand&&(this._hand=new gs,this._hand.matrixAutoUpdate=!1,this._hand.visible=!1,this._hand.joints={},this._hand.inputState={pinching:!1}),this._hand}getTargetRaySpace(){return null===this._targetRay&&(this._targetRay=new gs,this._targetRay.matrixAutoUpdate=!1,this._targetRay.visible=!1,this._targetRay.hasLinearVelocity=!1,this._targetRay.linearVelocity=new Lt,this._targetRay.hasAngularVelocity=!1,this._targetRay.angularVelocity=new Lt),this._targetRay}getGripSpace(){return null===this._grip&&(this._grip=new gs,this._grip.matrixAutoUpdate=!1,this._grip.visible=!1,this._grip.hasLinearVelocity=!1,this._grip.linearVelocity=new Lt,this._grip.hasAngularVelocity=!1,this._grip.angularVelocity=new Lt),this._grip}dispatchEvent(t){return null!==this._targetRay&&this._targetRay.dispatchEvent(t),null!==this._grip&&this._grip.dispatchEvent(t),null!==this._hand&&this._hand.dispatchEvent(t),this}disconnect(t){return this.dispatchEvent({type:"disconnected",data:t}),null!==this._targetRay&&(this._targetRay.visible=!1),null!==this._grip&&(this._grip.visible=!1),null!==this._hand&&(this._hand.visible=!1),this}update(t,e,n){let i=null,r=null,s=null;const a=this._targetRay,o=this._grip,l=this._hand;if(t&&"visible-blurred"!==e.session.visibilityState)if(null!==a&&(i=e.getPose(t.targetRaySpace,n),null!==i&&(a.matrix.fromArray(i.transform.matrix),a.matrix.decompose(a.position,a.rotation,a.scale),i.linearVelocity?(a.hasLinearVelocity=!0,a.linearVelocity.copy(i.linearVelocity)):a.hasLinearVelocity=!1,i.angularVelocity?(a.hasAngularVelocity=!0,a.angularVelocity.copy(i.angularVelocity)):a.hasAngularVelocity=!1,this.dispatchEvent(vs))),l&&t.hand){s=!0;for(const i of t.hand.values()){const t=e.getJointPose(i,n);if(void 0===l.joints[i.jointName]){const t=new gs;t.matrixAutoUpdate=!1,t.visible=!1,l.joints[i.jointName]=t,l.add(t)}const r=l.joints[i.jointName];null!==t&&(r.matrix.fromArray(t.transform.matrix),r.matrix.decompose(r.position,r.rotation,r.scale),r.jointRadius=t.radius),r.visible=null!==t}const i=l.joints["index-finger-tip"],r=l.joints["thumb-tip"],a=i.position.distanceTo(r.position),o=.02,c=.005;l.inputState.pinching&&a>o+c?(l.inputState.pinching=!1,this.dispatchEvent({type:"pinchend",handedness:t.handedness,target:this})):!l.inputState.pinching&&a<=o-c&&(l.inputState.pinching=!0,this.dispatchEvent({type:"pinchstart",handedness:t.handedness,target:this}))}else null!==o&&t.gripSpace&&(r=e.getPose(t.gripSpace,n),null!==r&&(o.matrix.fromArray(r.transform.matrix),o.matrix.decompose(o.position,o.rotation,o.scale),r.linearVelocity?(o.hasLinearVelocity=!0,o.linearVelocity.copy(r.linearVelocity)):o.hasLinearVelocity=!1,r.angularVelocity?(o.hasAngularVelocity=!0,o.angularVelocity.copy(r.angularVelocity)):o.hasAngularVelocity=!1));return null!==a&&(a.visible=null!==i),null!==o&&(o.visible=null!==r),null!==l&&(l.visible=null!==s),this}}class xs extends rt{constructor(t,e){super();const n=this,i=t.state;let r=null,s=1,a=null,o="local-floor",l=null;const c=[],h=new Map,u=new Kn;u.layers.enable(1),u.viewport=new St;const d=new Kn;d.layers.enable(2),d.viewport=new St;const p=[u,d],m=new fs;m.layers.enable(1),m.layers.enable(2);let f=null,g=null;function v(t){const e=h.get(t.inputSource);e&&e.dispatchEvent({type:t.type,data:t.inputSource})}function y(){h.forEach((function(t,e){t.disconnect(e)})),h.clear(),f=null,g=null,i.bindXRFramebuffer(null),t.setRenderTarget(t.getRenderTarget()),S.stop(),n.isPresenting=!1,n.dispatchEvent({type:"sessionend"})}function x(t){const e=r.inputSources;for(let t=0;t0&&Rt(s,t,e),a.length>0&&Rt(a,t,e),null!==_&&(J.updateRenderTargetMipmap(_),J.updateMultisampleRenderTarget(_)),!0===t.isScene&&t.onAfterRender(f,t,e),q.buffers.depth.setTest(!0),q.buffers.depth.setMask(!0),q.buffers.color.setMask(!0),q.setPolygonOffset(!1),dt.resetDefaultState(),w=-1,S=null,m.pop(),d=m.length>0?m[m.length-1]:null,p.pop(),u=p.length>0?p[p.length-1]:null},this.getActiveCubeFace=function(){return v},this.getActiveMipmapLevel=function(){return y},this.getRenderTarget=function(){return _},this.setRenderTarget=function(t,e=0,n=0){_=t,v=e,y=n,t&&void 0===Z.get(t).__webglFramebuffer&&J.setupRenderTarget(t);let i=null,r=!1,s=!1;if(t){const n=t.texture;(n.isDataTexture3D||n.isDataTexture2DArray)&&(s=!0);const a=Z.get(t).__webglFramebuffer;t.isWebGLCubeRenderTarget?(i=a[e],r=!0):i=t.isWebGLMultisampleRenderTarget?Z.get(t).__webglMultisampledFramebuffer:a,T.copy(t.viewport),A.copy(t.scissor),L=t.scissorTest}else T.copy(N).multiplyScalar(P).floor(),A.copy(B).multiplyScalar(P).floor(),L=z;if(q.bindFramebuffer(36160,i),q.viewport(T),q.scissor(A),q.setScissorTest(L),r){const i=Z.get(t.texture);pt.framebufferTexture2D(36160,36064,34069+e,i.__webglTexture,n)}else if(s){const i=Z.get(t.texture),r=e||0;pt.framebufferTextureLayer(36160,36064,i.__webglTexture,n||0,r)}},this.readRenderTargetPixels=function(t,e,n,i,r,s,a){if(!t||!t.isWebGLRenderTarget)return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.");let o=Z.get(t).__webglFramebuffer;if(t.isWebGLCubeRenderTarget&&void 0!==a&&(o=o[a]),o){q.bindFramebuffer(36160,o);try{const a=t.texture,o=a.format,l=a.type;if(o!==E&&ut.convert(o)!==pt.getParameter(35739))return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in RGBA or implementation defined format.");const c=l===M&&(W.has("EXT_color_buffer_half_float")||j.isWebGL2&&W.has("EXT_color_buffer_float"));if(!(l===x||ut.convert(l)===pt.getParameter(35738)||l===b&&(j.isWebGL2||W.has("OES_texture_float")||W.has("WEBGL_color_buffer_float"))||c))return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in UnsignedByteType or implementation defined type.");36053===pt.checkFramebufferStatus(36160)?e>=0&&e<=t.width-i&&n>=0&&n<=t.height-r&&pt.readPixels(e,n,i,r,ut.convert(o),ut.convert(l),s):console.error("THREE.WebGLRenderer.readRenderTargetPixels: readPixels from renderTarget failed. Framebuffer not complete.")}finally{const t=null!==_?Z.get(_).__webglFramebuffer:null;q.bindFramebuffer(36160,t)}}},this.copyFramebufferToTexture=function(t,e,n=0){const i=Math.pow(2,-n),r=Math.floor(e.image.width*i),s=Math.floor(e.image.height*i),a=ut.convert(e.format);J.setTexture2D(e,0),pt.copyTexImage2D(3553,n,a,t.x,t.y,r,s,0),q.unbindTexture()},this.copyTextureToTexture=function(t,e,n,i=0){const r=e.image.width,s=e.image.height,a=ut.convert(n.format),o=ut.convert(n.type);J.setTexture2D(n,0),pt.pixelStorei(37440,n.flipY),pt.pixelStorei(37441,n.premultiplyAlpha),pt.pixelStorei(3317,n.unpackAlignment),e.isDataTexture?pt.texSubImage2D(3553,i,t.x,t.y,r,s,a,o,e.image.data):e.isCompressedTexture?pt.compressedTexSubImage2D(3553,i,t.x,t.y,e.mipmaps[0].width,e.mipmaps[0].height,a,e.mipmaps[0].data):pt.texSubImage2D(3553,i,t.x,t.y,a,o,e.image),0===i&&n.generateMipmaps&&pt.generateMipmap(3553),q.unbindTexture()},this.copyTextureToTexture3D=function(t,e,n,i,r=0){if(f.isWebGL1Renderer)return void console.warn("THREE.WebGLRenderer.copyTextureToTexture3D: can only be used with WebGL2.");const{width:s,height:a,data:o}=n.image,l=ut.convert(i.format),c=ut.convert(i.type);let h;if(i.isDataTexture3D)J.setTexture3D(i,0),h=32879;else{if(!i.isDataTexture2DArray)return void console.warn("THREE.WebGLRenderer.copyTextureToTexture3D: only supports THREE.DataTexture3D and THREE.DataTexture2DArray.");J.setTexture2DArray(i,0),h=35866}pt.pixelStorei(37440,i.flipY),pt.pixelStorei(37441,i.premultiplyAlpha),pt.pixelStorei(3317,i.unpackAlignment);const u=pt.getParameter(3314),d=pt.getParameter(32878),p=pt.getParameter(3316),m=pt.getParameter(3315),g=pt.getParameter(32877);pt.pixelStorei(3314,s),pt.pixelStorei(32878,a),pt.pixelStorei(3316,t.min.x),pt.pixelStorei(3315,t.min.y),pt.pixelStorei(32877,t.min.z),pt.texSubImage3D(h,r,e.x,e.y,e.z,t.max.x-t.min.x+1,t.max.y-t.min.y+1,t.max.z-t.min.z+1,l,c,o),pt.pixelStorei(3314,u),pt.pixelStorei(32878,d),pt.pixelStorei(3316,p),pt.pixelStorei(3315,m),pt.pixelStorei(32877,g),0===r&&i.generateMipmaps&&pt.generateMipmap(h),q.unbindTexture()},this.initTexture=function(t){J.setTexture2D(t,0),q.unbindTexture()},this.resetState=function(){v=0,y=0,_=null,q.reset(),dt.reset()},"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}class bs extends ws{}bs.prototype.isWebGL1Renderer=!0;class Ms{constructor(t,e=25e-5){this.name="",this.color=new tn(t),this.density=e}clone(){return new Ms(this.color,this.density)}toJSON(){return{type:"FogExp2",color:this.color.getHex(),density:this.density}}}Ms.prototype.isFogExp2=!0;class Ss{constructor(t,e=1,n=1e3){this.name="",this.color=new tn(t),this.near=e,this.far=n}clone(){return new Ss(this.color,this.near,this.far)}toJSON(){return{type:"Fog",color:this.color.getHex(),near:this.near,far:this.far}}}Ss.prototype.isFog=!0;class Ts extends Ce{constructor(){super(),this.type="Scene",this.background=null,this.environment=null,this.fog=null,this.overrideMaterial=null,this.autoUpdate=!0,"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}copy(t,e){return super.copy(t,e),null!==t.background&&(this.background=t.background.clone()),null!==t.environment&&(this.environment=t.environment.clone()),null!==t.fog&&(this.fog=t.fog.clone()),null!==t.overrideMaterial&&(this.overrideMaterial=t.overrideMaterial.clone()),this.autoUpdate=t.autoUpdate,this.matrixAutoUpdate=t.matrixAutoUpdate,this}toJSON(t){const e=super.toJSON(t);return null!==this.background&&(e.object.background=this.background.toJSON(t)),null!==this.environment&&(e.object.environment=this.environment.toJSON(t)),null!==this.fog&&(e.object.fog=this.fog.toJSON()),e}}Ts.prototype.isScene=!0;class Es{constructor(t,e){this.array=t,this.stride=e,this.count=void 0!==t?t.length/e:0,this.usage=et,this.updateRange={offset:0,count:-1},this.version=0,this.uuid=ct(),this.onUploadCallback=function(){}}set needsUpdate(t){!0===t&&this.version++}setUsage(t){return this.usage=t,this}copy(t){return this.array=new t.array.constructor(t.array),this.count=t.count,this.stride=t.stride,this.usage=t.usage,this}copyAt(t,e,n){t*=this.stride,n*=e.stride;for(let i=0,r=this.stride;it.far||e.push({distance:o,point:Ps.clone(),uv:je.getUV(Ps,Fs,Os,Hs,Gs,Us,ks,new vt),face:null,object:this})}copy(t){return super.copy(t),void 0!==t.center&&this.center.copy(t.center),this.material=t.material,this}}function Ws(t,e,n,i,r,s){Ns.subVectors(t,n).addScalar(.5).multiply(i),void 0!==r?(Bs.x=s*Ns.x-r*Ns.y,Bs.y=r*Ns.x+s*Ns.y):Bs.copy(Ns),t.copy(e),t.x+=Bs.x,t.y+=Bs.y,t.applyMatrix4(zs)}Vs.prototype.isSprite=!0;const js=new Lt,qs=new Lt;class Xs extends Ce{constructor(){super(),this._currentLevel=0,this.type="LOD",Object.defineProperties(this,{levels:{enumerable:!0,value:[]},isLOD:{value:!0}}),this.autoUpdate=!0}copy(t){super.copy(t,!1);const e=t.levels;for(let t=0,n=e.length;t0){let n,i;for(n=1,i=e.length;n0){js.setFromMatrixPosition(this.matrixWorld);const n=t.ray.origin.distanceTo(js);this.getObjectForDistance(n).raycast(t,e)}}update(t){const e=this.levels;if(e.length>1){js.setFromMatrixPosition(t.matrixWorld),qs.setFromMatrixPosition(this.matrixWorld);const n=js.distanceTo(qs)/t.zoom;let i,r;for(e[0].object.visible=!0,i=1,r=e.length;i=e[i].distance;i++)e[i-1].object.visible=!1,e[i].object.visible=!0;for(this._currentLevel=i-1;io)continue;u.applyMatrix4(this.matrixWorld);const d=t.ray.origin.distanceTo(u);dt.far||e.push({distance:d,point:h.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}else{for(let n=Math.max(0,s.start),i=Math.min(r.count,s.start+s.count)-1;no)continue;u.applyMatrix4(this.matrixWorld);const i=t.ray.origin.distanceTo(u);it.far||e.push({distance:i,point:h.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}}else n.isGeometry&&console.error("THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.")}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,n=Object.keys(e);if(n.length>0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error("THREE.Line.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.")}}}fa.prototype.isLine=!0;const ga=new Lt,va=new Lt;class ya extends fa{constructor(t,e){super(t,e),this.type="LineSegments"}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,n=[];for(let t=0,i=e.count;t0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error("THREE.Points.updateMorphTargets() does not support THREE.Geometry. 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p=a.times.length;for(let t=0;t=r)break t;{const a=e[1];t=r)break e}s=n,n=0}}for(;n>>1;te;)--s;if(++s,0!==r||s!==i){r>=s&&(s=Math.max(s,1),r=s-1);const t=this.getValueSize();this.times=Vo.arraySlice(n,r,s),this.values=Vo.arraySlice(this.values,r*t,s*t)}return this}validate(){let t=!0;const e=this.getValueSize();e-Math.floor(e)!=0&&(console.error("THREE.KeyframeTrack: Invalid value size in track.",this),t=!1);const n=this.times,i=this.values,r=n.length;0===r&&(console.error("THREE.KeyframeTrack: Track is empty.",this),t=!1);let s=null;for(let e=0;e!==r;e++){const i=n[e];if("number"==typeof i&&isNaN(i)){console.error("THREE.KeyframeTrack: Time is not a valid number.",this,e,i),t=!1;break}if(null!==s&&s>i){console.error("THREE.KeyframeTrack: Out of order keys.",this,e,i,s),t=!1;break}s=i}if(void 0!==i&&Vo.isTypedArray(i))for(let e=0,n=i.length;e!==n;++e){const n=i[e];if(isNaN(n)){console.error("THREE.KeyframeTrack: Value is not a valid number.",this,e,n),t=!1;break}}return t}optimize(){const t=Vo.arraySlice(this.times),e=Vo.arraySlice(this.values),n=this.getValueSize(),i=this.getInterpolation()===U,r=t.length-1;let s=1;for(let a=1;a0){t[s]=t[r];for(let t=r*n,i=s*n,a=0;a!==n;++a)e[i+a]=e[t+a];++s}return s!==t.length?(this.times=Vo.arraySlice(t,0,s),this.values=Vo.arraySlice(e,0,s*n)):(this.times=t,this.values=e),this}clone(){const t=Vo.arraySlice(this.times,0),e=Vo.arraySlice(this.values,0),n=new(0,this.constructor)(this.name,t,e);return n.createInterpolant=this.createInterpolant,n}}Yo.prototype.TimeBufferType=Float32Array,Yo.prototype.ValueBufferType=Float32Array,Yo.prototype.DefaultInterpolation=G;class Zo extends Yo{}Zo.prototype.ValueTypeName="bool",Zo.prototype.ValueBufferType=Array,Zo.prototype.DefaultInterpolation=H,Zo.prototype.InterpolantFactoryMethodLinear=void 0,Zo.prototype.InterpolantFactoryMethodSmooth=void 0;class Jo extends Yo{}Jo.prototype.ValueTypeName="color";class Qo extends Yo{}Qo.prototype.ValueTypeName="number";class Ko extends Wo{constructor(t,e,n,i){super(t,e,n,i)}interpolate_(t,e,n,i){const r=this.resultBuffer,s=this.sampleValues,a=this.valueSize,o=(n-e)/(i-e);let l=t*a;for(let t=l+a;l!==t;l+=4)At.slerpFlat(r,0,s,l-a,s,l,o);return r}}class $o extends Yo{InterpolantFactoryMethodLinear(t){return new Ko(this.times,this.values,this.getValueSize(),t)}}$o.prototype.ValueTypeName="quaternion",$o.prototype.DefaultInterpolation=G,$o.prototype.InterpolantFactoryMethodSmooth=void 0;class tl extends Yo{}tl.prototype.ValueTypeName="string",tl.prototype.ValueBufferType=Array,tl.prototype.DefaultInterpolation=H,tl.prototype.InterpolantFactoryMethodLinear=void 0,tl.prototype.InterpolantFactoryMethodSmooth=void 0;class el extends Yo{}el.prototype.ValueTypeName="vector";class nl{constructor(t,e=-1,n,i=2500){this.name=t,this.tracks=n,this.duration=e,this.blendMode=i,this.uuid=ct(),this.duration<0&&this.resetDuration()}static parse(t){const e=[],n=t.tracks,i=1/(t.fps||1);for(let t=0,r=n.length;t!==r;++t)e.push(il(n[t]).scale(i));const r=new this(t.name,t.duration,e,t.blendMode);return r.uuid=t.uuid,r}static toJSON(t){const e=[],n=t.tracks,i={name:t.name,duration:t.duration,tracks:e,uuid:t.uuid,blendMode:t.blendMode};for(let t=0,i=n.length;t!==i;++t)e.push(Yo.toJSON(n[t]));return i}static CreateFromMorphTargetSequence(t,e,n,i){const r=e.length,s=[];for(let t=0;t1){const t=s[1];let e=i[t];e||(i[t]=e=[]),e.push(n)}}const s=[];for(const t in i)s.push(this.CreateFromMorphTargetSequence(t,i[t],e,n));return s}static parseAnimation(t,e){if(!t)return console.error("THREE.AnimationClip: No animation in JSONLoader data."),null;const n=function(t,e,n,i,r){if(0!==n.length){const s=[],a=[];Vo.flattenJSON(n,s,a,i),0!==s.length&&r.push(new t(e,s,a))}},i=[],r=t.name||"default",s=t.fps||30,a=t.blendMode;let o=t.length||-1;const l=t.hierarchy||[];for(let t=0;t0||0===t.search(/^data\:image\/jpeg/);r.format=i?T:E,r.needsUpdate=!0,void 0!==e&&e(r)}),n,i),r}}class ml{constructor(){this.type="Curve",this.arcLengthDivisions=200}getPoint(){return console.warn("THREE.Curve: .getPoint() not implemented."),null}getPointAt(t,e){const n=this.getUtoTmapping(t);return this.getPoint(n,e)}getPoints(t=5){const e=[];for(let n=0;n<=t;n++)e.push(this.getPoint(n/t));return e}getSpacedPoints(t=5){const e=[];for(let n=0;n<=t;n++)e.push(this.getPointAt(n/t));return e}getLength(){const t=this.getLengths();return t[t.length-1]}getLengths(t=this.arcLengthDivisions){if(this.cacheArcLengths&&this.cacheArcLengths.length===t+1&&!this.needsUpdate)return this.cacheArcLengths;this.needsUpdate=!1;const e=[];let n,i=this.getPoint(0),r=0;e.push(0);for(let s=1;s<=t;s++)n=this.getPoint(s/t),r+=n.distanceTo(i),e.push(r),i=n;return this.cacheArcLengths=e,e}updateArcLengths(){this.needsUpdate=!0,this.getLengths()}getUtoTmapping(t,e){const n=this.getLengths();let i=0;const r=n.length;let s;s=e||t*n[r-1];let a,o=0,l=r-1;for(;o<=l;)if(i=Math.floor(o+(l-o)/2),a=n[i]-s,a<0)o=i+1;else{if(!(a>0)){l=i;break}l=i-1}if(i=l,n[i]===s)return i/(r-1);const c=n[i];return(i+(s-c)/(n[i+1]-c))/(r-1)}getTangent(t,e){const n=1e-4;let i=t-n,r=t+n;i<0&&(i=0),r>1&&(r=1);const s=this.getPoint(i),a=this.getPoint(r),o=e||(s.isVector2?new vt:new Lt);return o.copy(a).sub(s).normalize(),o}getTangentAt(t,e){const n=this.getUtoTmapping(t);return this.getTangent(n,e)}computeFrenetFrames(t,e){const n=new Lt,i=[],r=[],s=[],a=new Lt,o=new se;for(let e=0;e<=t;e++){const n=e/t;i[e]=this.getTangentAt(n,new Lt),i[e].normalize()}r[0]=new Lt,s[0]=new Lt;let l=Number.MAX_VALUE;const c=Math.abs(i[0].x),h=Math.abs(i[0].y),u=Math.abs(i[0].z);c<=l&&(l=c,n.set(1,0,0)),h<=l&&(l=h,n.set(0,1,0)),u<=l&&n.set(0,0,1),a.crossVectors(i[0],n).normalize(),r[0].crossVectors(i[0],a),s[0].crossVectors(i[0],r[0]);for(let e=1;e<=t;e++){if(r[e]=r[e-1].clone(),s[e]=s[e-1].clone(),a.crossVectors(i[e-1],i[e]),a.length()>Number.EPSILON){a.normalize();const t=Math.acos(ht(i[e-1].dot(i[e]),-1,1));r[e].applyMatrix4(o.makeRotationAxis(a,t))}s[e].crossVectors(i[e],r[e])}if(!0===e){let e=Math.acos(ht(r[0].dot(r[t]),-1,1));e/=t,i[0].dot(a.crossVectors(r[0],r[t]))>0&&(e=-e);for(let n=1;n<=t;n++)r[n].applyMatrix4(o.makeRotationAxis(i[n],e*n)),s[n].crossVectors(i[n],r[n])}return{tangents:i,normals:r,binormals:s}}clone(){return(new this.constructor).copy(this)}copy(t){return this.arcLengthDivisions=t.arcLengthDivisions,this}toJSON(){const t={metadata:{version:4.5,type:"Curve",generator:"Curve.toJSON"}};return t.arcLengthDivisions=this.arcLengthDivisions,t.type=this.type,t}fromJSON(t){return this.arcLengthDivisions=t.arcLengthDivisions,this}}class fl extends ml{constructor(t=0,e=0,n=1,i=1,r=0,s=2*Math.PI,a=!1,o=0){super(),this.type="EllipseCurve",this.aX=t,this.aY=e,this.xRadius=n,this.yRadius=i,this.aStartAngle=r,this.aEndAngle=s,this.aClockwise=a,this.aRotation=o}getPoint(t,e){const n=e||new vt,i=2*Math.PI;let r=this.aEndAngle-this.aStartAngle;const s=Math.abs(r)i;)r-=i;r0?0:(Math.floor(Math.abs(l)/r)+1)*r:0===c&&l===r-1&&(l=r-2,c=1),this.closed||l>0?a=i[(l-1)%r]:(yl.subVectors(i[0],i[1]).add(i[0]),a=yl);const h=i[l%r],u=i[(l+1)%r];if(this.closed||l+2i.length-2?i.length-1:s+1],h=i[s>i.length-3?i.length-1:s+2];return n.set(Ml(a,o.x,l.x,c.x,h.x),Ml(a,o.y,l.y,c.y,h.y)),n}copy(t){super.copy(t),this.points=[];for(let e=0,n=t.points.length;e=e){const t=n[i]-e,r=this.curves[i],s=r.getLength(),a=0===s?0:1-t/s;return r.getPointAt(a)}i++}return null}getLength(){const t=this.getCurveLengths();return t[t.length-1]}updateArcLengths(){this.needsUpdate=!0,this.cacheLengths=null,this.getCurveLengths()}getCurveLengths(){if(this.cacheLengths&&this.cacheLengths.length===this.curves.length)return this.cacheLengths;const t=[];let e=0;for(let n=0,i=this.curves.length;n1&&!e[e.length-1].equals(e[0])&&e.push(e[0]),e}copy(t){super.copy(t),this.curves=[];for(let e=0,n=t.curves.length;e0){const t=l.getPoint(0);t.equals(this.currentPoint)||this.lineTo(t.x,t.y)}this.curves.push(l);const c=l.getPoint(1);return this.currentPoint.copy(c),this}copy(t){return super.copy(t),this.currentPoint.copy(t.currentPoint),this}toJSON(){const t=super.toJSON();return t.currentPoint=this.currentPoint.toArray(),t}fromJSON(t){return super.fromJSON(t),this.currentPoint.fromArray(t.currentPoint),this}}class zl extends Bl{constructor(t){super(t),this.uuid=ct(),this.type="Shape",this.holes=[]}getPointsHoles(t){const e=[];for(let n=0,i=this.holes.length;n0:i.vertexColors=t.vertexColors),void 0!==t.uniforms)for(const e in t.uniforms){const r=t.uniforms[e];switch(i.uniforms[e]={},r.type){case"t":i.uniforms[e].value=n(r.value);break;case"c":i.uniforms[e].value=(new tn).setHex(r.value);break;case"v2":i.uniforms[e].value=(new vt).fromArray(r.value);break;case"v3":i.uniforms[e].value=(new Lt).fromArray(r.value);break;case"v4":i.uniforms[e].value=(new St).fromArray(r.value);break;case"m3":i.uniforms[e].value=(new yt).fromArray(r.value);break;case"m4":i.uniforms[e].value=(new se).fromArray(r.value);break;default:i.uniforms[e].value=r.value}}if(void 0!==t.defines&&(i.defines=t.defines),void 0!==t.vertexShader&&(i.vertexShader=t.vertexShader),void 0!==t.fragmentShader&&(i.fragmentShader=t.fragmentShader),void 0!==t.extensions)for(const e in t.extensions)i.extensions[e]=t.extensions[e];if(void 0!==t.shading&&(i.flatShading=1===t.shading),void 0!==t.size&&(i.size=t.size),void 0!==t.sizeAttenuation&&(i.sizeAttenuation=t.sizeAttenuation),void 0!==t.map&&(i.map=n(t.map)),void 0!==t.matcap&&(i.matcap=n(t.matcap)),void 0!==t.alphaMap&&(i.alphaMap=n(t.alphaMap)),void 0!==t.bumpMap&&(i.bumpMap=n(t.bumpMap)),void 0!==t.bumpScale&&(i.bumpScale=t.bumpScale),void 0!==t.normalMap&&(i.normalMap=n(t.normalMap)),void 0!==t.normalMapType&&(i.normalMapType=t.normalMapType),void 0!==t.normalScale){let e=t.normalScale;!1===Array.isArray(e)&&(e=[e,e]),i.normalScale=(new vt).fromArray(e)}return void 0!==t.displacementMap&&(i.displacementMap=n(t.displacementMap)),void 0!==t.displacementScale&&(i.displacementScale=t.displacementScale),void 0!==t.displacementBias&&(i.displacementBias=t.displacementBias),void 0!==t.roughnessMap&&(i.roughnessMap=n(t.roughnessMap)),void 0!==t.metalnessMap&&(i.metalnessMap=n(t.metalnessMap)),void 0!==t.emissiveMap&&(i.emissiveMap=n(t.emissiveMap)),void 0!==t.emissiveIntensity&&(i.emissiveIntensity=t.emissiveIntensity),void 0!==t.specularMap&&(i.specularMap=n(t.specularMap)),void 0!==t.envMap&&(i.envMap=n(t.envMap)),void 0!==t.envMapIntensity&&(i.envMapIntensity=t.envMapIntensity),void 0!==t.reflectivity&&(i.reflectivity=t.reflectivity),void 0!==t.refractionRatio&&(i.refractionRatio=t.refractionRatio),void 0!==t.lightMap&&(i.lightMap=n(t.lightMap)),void 0!==t.lightMapIntensity&&(i.lightMapIntensity=t.lightMapIntensity),void 0!==t.aoMap&&(i.aoMap=n(t.aoMap)),void 0!==t.aoMapIntensity&&(i.aoMapIntensity=t.aoMapIntensity),void 0!==t.gradientMap&&(i.gradientMap=n(t.gradientMap)),void 0!==t.clearcoatMap&&(i.clearcoatMap=n(t.clearcoatMap)),void 0!==t.clearcoatRoughnessMap&&(i.clearcoatRoughnessMap=n(t.clearcoatRoughnessMap)),void 0!==t.clearcoatNormalMap&&(i.clearcoatNormalMap=n(t.clearcoatNormalMap)),void 0!==t.clearcoatNormalScale&&(i.clearcoatNormalScale=(new vt).fromArray(t.clearcoatNormalScale)),void 0!==t.transmission&&(i.transmission=t.transmission),void 0!==t.transmissionMap&&(i.transmissionMap=n(t.transmissionMap)),i}setTextures(t){return this.textures=t,this}}class rc{static decodeText(t){if("undefined"!=typeof TextDecoder)return(new TextDecoder).decode(t);let e="";for(let n=0,i=t.length;nNumber.EPSILON){if(l<0&&(n=e[s],o=-o,a=e[r],l=-l),t.ya.y)continue;if(t.y===n.y){if(t.x===n.x)return!0}else{const e=l*(t.x-n.x)-o*(t.y-n.y);if(0===e)return!0;if(e<0)continue;i=!i}}else{if(t.y!==n.y)continue;if(a.x<=t.x&&t.x<=n.x||n.x<=t.x&&t.x<=a.x)return!0}}return i}const r=po.isClockWise,s=this.subPaths;if(0===s.length)return[];if(!0===e)return n(s);let a,o,l;const c=[];if(1===s.length)return o=s[0],l=new zl,l.curves=o.curves,c.push(l),c;let h=!r(s[0].getPoints());h=t?!h:h;const u=[],d=[];let p,m,f=[],g=0;d[g]=void 0,f[g]=[];for(let e=0,n=s.length;e1){let t=!1;const e=[];for(let t=0,e=d.length;t0&&(t||(f=u))}for(let t=0,e=d.length;t0){this.source.connect(this.filters[0]);for(let t=1,e=this.filters.length;t0){this.source.disconnect(this.filters[0]);for(let t=1,e=this.filters.length;t0&&this._mixBufferRegionAdditive(n,i,this._addIndex*e,1,e);for(let t=e,r=e+e;t!==r;++t)if(n[t]!==n[t+e]){a.setValue(n,i);break}}saveOriginalState(){const t=this.binding,e=this.buffer,n=this.valueSize,i=n*this._origIndex;t.getValue(e,i);for(let t=n,r=i;t!==r;++t)e[t]=e[i+t%n];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){const t=3*this.valueSize;this.binding.setValue(this.buffer,t)}_setAdditiveIdentityNumeric(){const t=this._addIndex*this.valueSize,e=t+this.valueSize;for(let n=t;n=.5)for(let i=0;i!==r;++i)t[e+i]=t[n+i]}_slerp(t,e,n,i){At.slerpFlat(t,e,t,e,t,n,i)}_slerpAdditive(t,e,n,i,r){const s=this._workIndex*r;At.multiplyQuaternionsFlat(t,s,t,e,t,n),At.slerpFlat(t,e,t,e,t,s,i)}_lerp(t,e,n,i,r){const s=1-i;for(let a=0;a!==r;++a){const r=e+a;t[r]=t[r]*s+t[n+a]*i}}_lerpAdditive(t,e,n,i,r){for(let s=0;s!==r;++s){const r=e+s;t[r]=t[r]+t[n+s]*i}}}const Bc="\\[\\]\\.:\\/",zc=new RegExp("[\\[\\]\\.:\\/]","g"),Fc="[^\\[\\]\\.:\\/]",Oc="[^"+Bc.replace("\\.","")+"]",Hc=/((?:WC+[\/:])*)/.source.replace("WC",Fc),Gc=/(WCOD+)?/.source.replace("WCOD",Oc),Uc=/(?:\.(WC+)(?:\[(.+)\])?)?/.source.replace("WC",Fc),kc=/\.(WC+)(?:\[(.+)\])?/.source.replace("WC",Fc),Vc=new RegExp("^"+Hc+Gc+Uc+kc+"$"),Wc=["material","materials","bones"];class jc{constructor(t,e,n){this.path=e,this.parsedPath=n||jc.parseTrackName(e),this.node=jc.findNode(t,this.parsedPath.nodeName)||t,this.rootNode=t,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}static create(t,e,n){return t&&t.isAnimationObjectGroup?new jc.Composite(t,e,n):new jc(t,e,n)}static sanitizeNodeName(t){return t.replace(/\s/g,"_").replace(zc,"")}static parseTrackName(t){const e=Vc.exec(t);if(!e)throw new Error("PropertyBinding: Cannot parse trackName: "+t);const n={nodeName:e[2],objectName:e[3],objectIndex:e[4],propertyName:e[5],propertyIndex:e[6]},i=n.nodeName&&n.nodeName.lastIndexOf(".");if(void 0!==i&&-1!==i){const t=n.nodeName.substring(i+1);-1!==Wc.indexOf(t)&&(n.nodeName=n.nodeName.substring(0,i),n.objectName=t)}if(null===n.propertyName||0===n.propertyName.length)throw new Error("PropertyBinding: can not parse propertyName from trackName: "+t);return n}static findNode(t,e){if(!e||""===e||"."===e||-1===e||e===t.name||e===t.uuid)return t;if(t.skeleton){const n=t.skeleton.getBoneByName(e);if(void 0!==n)return n}if(t.children){const n=function(t){for(let i=0;i=r){const s=r++,c=t[s];e[c.uuid]=l,t[l]=c,e[o]=s,t[s]=a;for(let t=0,e=i;t!==e;++t){const e=n[t],i=e[s],r=e[l];e[l]=i,e[s]=r}}}this.nCachedObjects_=r}uncache(){const t=this._objects,e=this._indicesByUUID,n=this._bindings,i=n.length;let r=this.nCachedObjects_,s=t.length;for(let a=0,o=arguments.length;a!==o;++a){const o=arguments[a].uuid,l=e[o];if(void 0!==l)if(delete e[o],l0&&(e[a.uuid]=l),t[l]=a,t.pop();for(let t=0,e=i;t!==e;++t){const e=n[t];e[l]=e[r],e.pop()}}}this.nCachedObjects_=r}subscribe_(t,e){const n=this._bindingsIndicesByPath;let i=n[t];const r=this._bindings;if(void 0!==i)return r[i];const s=this._paths,a=this._parsedPaths,o=this._objects,l=o.length,c=this.nCachedObjects_,h=new Array(l);i=r.length,n[t]=i,s.push(t),a.push(e),r.push(h);for(let n=c,i=o.length;n!==i;++n){const i=o[n];h[n]=new jc(i,t,e)}return h}unsubscribe_(t){const e=this._bindingsIndicesByPath,n=e[t];if(void 0!==n){const i=this._paths,r=this._parsedPaths,s=this._bindings,a=s.length-1,o=s[a];e[t[a]]=n,s[n]=o,s.pop(),r[n]=r[a],r.pop(),i[n]=i[a],i.pop()}}}qc.prototype.isAnimationObjectGroup=!0;class Xc{constructor(t,e,n=null,i=e.blendMode){this._mixer=t,this._clip=e,this._localRoot=n,this.blendMode=i;const r=e.tracks,s=r.length,a=new Array(s),o={endingStart:k,endingEnd:k};for(let t=0;t!==s;++t){const e=r[t].createInterpolant(null);a[t]=e,e.settings=o}this._interpolantSettings=o,this._interpolants=a,this._propertyBindings=new Array(s),this._cacheIndex=null,this._byClipCacheIndex=null,this._timeScaleInterpolant=null,this._weightInterpolant=null,this.loop=2201,this._loopCount=-1,this._startTime=null,this.time=0,this.timeScale=1,this._effectiveTimeScale=1,this.weight=1,this._effectiveWeight=1,this.repetitions=1/0,this.paused=!1,this.enabled=!0,this.clampWhenFinished=!1,this.zeroSlopeAtStart=!0,this.zeroSlopeAtEnd=!0}play(){return this._mixer._activateAction(this),this}stop(){return this._mixer._deactivateAction(this),this.reset()}reset(){return this.paused=!1,this.enabled=!0,this.time=0,this._loopCount=-1,this._startTime=null,this.stopFading().stopWarping()}isRunning(){return this.enabled&&!this.paused&&0!==this.timeScale&&null===this._startTime&&this._mixer._isActiveAction(this)}isScheduled(){return this._mixer._isActiveAction(this)}startAt(t){return this._startTime=t,this}setLoop(t,e){return this.loop=t,this.repetitions=e,this}setEffectiveWeight(t){return this.weight=t,this._effectiveWeight=this.enabled?t:0,this.stopFading()}getEffectiveWeight(){return this._effectiveWeight}fadeIn(t){return this._scheduleFading(t,0,1)}fadeOut(t){return this._scheduleFading(t,1,0)}crossFadeFrom(t,e,n){if(t.fadeOut(e),this.fadeIn(e),n){const n=this._clip.duration,i=t._clip.duration,r=i/n,s=n/i;t.warp(1,r,e),this.warp(s,1,e)}return this}crossFadeTo(t,e,n){return t.crossFadeFrom(this,e,n)}stopFading(){const t=this._weightInterpolant;return null!==t&&(this._weightInterpolant=null,this._mixer._takeBackControlInterpolant(t)),this}setEffectiveTimeScale(t){return this.timeScale=t,this._effectiveTimeScale=this.paused?0:t,this.stopWarping()}getEffectiveTimeScale(){return this._effectiveTimeScale}setDuration(t){return this.timeScale=this._clip.duration/t,this.stopWarping()}syncWith(t){return this.time=t.time,this.timeScale=t.timeScale,this.stopWarping()}halt(t){return this.warp(this._effectiveTimeScale,0,t)}warp(t,e,n){const i=this._mixer,r=i.time,s=this.timeScale;let a=this._timeScaleInterpolant;null===a&&(a=i._lendControlInterpolant(),this._timeScaleInterpolant=a);const o=a.parameterPositions,l=a.sampleValues;return o[0]=r,o[1]=r+n,l[0]=t/s,l[1]=e/s,this}stopWarping(){const t=this._timeScaleInterpolant;return null!==t&&(this._timeScaleInterpolant=null,this._mixer._takeBackControlInterpolant(t)),this}getMixer(){return this._mixer}getClip(){return this._clip}getRoot(){return this._localRoot||this._mixer._root}_update(t,e,n,i){if(!this.enabled)return void this._updateWeight(t);const r=this._startTime;if(null!==r){const i=(t-r)*n;if(i<0||0===n)return;this._startTime=null,e=n*i}e*=this._updateTimeScale(t);const s=this._updateTime(e),a=this._updateWeight(t);if(a>0){const t=this._interpolants,e=this._propertyBindings;switch(this.blendMode){case q:for(let n=0,i=t.length;n!==i;++n)t[n].evaluate(s),e[n].accumulateAdditive(a);break;case j:default:for(let n=0,r=t.length;n!==r;++n)t[n].evaluate(s),e[n].accumulate(i,a)}}}_updateWeight(t){let e=0;if(this.enabled){e=this.weight;const n=this._weightInterpolant;if(null!==n){const i=n.evaluate(t)[0];e*=i,t>n.parameterPositions[1]&&(this.stopFading(),0===i&&(this.enabled=!1))}}return this._effectiveWeight=e,e}_updateTimeScale(t){let e=0;if(!this.paused){e=this.timeScale;const n=this._timeScaleInterpolant;if(null!==n){e*=n.evaluate(t)[0],t>n.parameterPositions[1]&&(this.stopWarping(),0===e?this.paused=!0:this.timeScale=e)}}return this._effectiveTimeScale=e,e}_updateTime(t){const e=this._clip.duration,n=this.loop;let i=this.time+t,r=this._loopCount;const s=2202===n;if(0===t)return-1===r?i:s&&1==(1&r)?e-i:i;if(2200===n){-1===r&&(this._loopCount=0,this._setEndings(!0,!0,!1));t:{if(i>=e)i=e;else{if(!(i<0)){this.time=i;break t}i=0}this.clampWhenFinished?this.paused=!0:this.enabled=!1,this.time=i,this._mixer.dispatchEvent({type:"finished",action:this,direction:t<0?-1:1})}}else{if(-1===r&&(t>=0?(r=0,this._setEndings(!0,0===this.repetitions,s)):this._setEndings(0===this.repetitions,!0,s)),i>=e||i<0){const n=Math.floor(i/e);i-=e*n,r+=Math.abs(n);const a=this.repetitions-r;if(a<=0)this.clampWhenFinished?this.paused=!0:this.enabled=!1,i=t>0?e:0,this.time=i,this._mixer.dispatchEvent({type:"finished",action:this,direction:t>0?1:-1});else{if(1===a){const e=t<0;this._setEndings(e,!e,s)}else this._setEndings(!1,!1,s);this._loopCount=r,this.time=i,this._mixer.dispatchEvent({type:"loop",action:this,loopDelta:n})}}else this.time=i;if(s&&1==(1&r))return e-i}return i}_setEndings(t,e,n){const i=this._interpolantSettings;n?(i.endingStart=V,i.endingEnd=V):(i.endingStart=t?this.zeroSlopeAtStart?V:k:W,i.endingEnd=e?this.zeroSlopeAtEnd?V:k:W)}_scheduleFading(t,e,n){const i=this._mixer,r=i.time;let s=this._weightInterpolant;null===s&&(s=i._lendControlInterpolant(),this._weightInterpolant=s);const a=s.parameterPositions,o=s.sampleValues;return a[0]=r,o[0]=e,a[1]=r+t,o[1]=n,this}}class Yc extends rt{constructor(t){super(),this._root=t,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1}_bindAction(t,e){const n=t._localRoot||this._root,i=t._clip.tracks,r=i.length,s=t._propertyBindings,a=t._interpolants,o=n.uuid,l=this._bindingsByRootAndName;let c=l[o];void 0===c&&(c={},l[o]=c);for(let t=0;t!==r;++t){const r=i[t],l=r.name;let h=c[l];if(void 0!==h)s[t]=h;else{if(h=s[t],void 0!==h){null===h._cacheIndex&&(++h.referenceCount,this._addInactiveBinding(h,o,l));continue}const i=e&&e._propertyBindings[t].binding.parsedPath;h=new Nc(jc.create(n,l,i),r.ValueTypeName,r.getValueSize()),++h.referenceCount,this._addInactiveBinding(h,o,l),s[t]=h}a[t].resultBuffer=h.buffer}}_activateAction(t){if(!this._isActiveAction(t)){if(null===t._cacheIndex){const e=(t._localRoot||this._root).uuid,n=t._clip.uuid,i=this._actionsByClip[n];this._bindAction(t,i&&i.knownActions[0]),this._addInactiveAction(t,n,e)}const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==n.useCount++&&(this._lendBinding(n),n.saveOriginalState())}this._lendAction(t)}}_deactivateAction(t){if(this._isActiveAction(t)){const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==--n.useCount&&(n.restoreOriginalState(),this._takeBackBinding(n))}this._takeBackAction(t)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;const t=this;this.stats={actions:{get total(){return t._actions.length},get inUse(){return t._nActiveActions}},bindings:{get total(){return t._bindings.length},get inUse(){return t._nActiveBindings}},controlInterpolants:{get total(){return t._controlInterpolants.length},get inUse(){return t._nActiveControlInterpolants}}}}_isActiveAction(t){const e=t._cacheIndex;return null!==e&&e=0;--e)t[e].stop();return this}update(t){t*=this.timeScale;const e=this._actions,n=this._nActiveActions,i=this.time+=t,r=Math.sign(t),s=this._accuIndex^=1;for(let a=0;a!==n;++a){e[a]._update(i,t,r,s)}const a=this._bindings,o=this._nActiveBindings;for(let t=0;t!==o;++t)a[t].apply(s);return this}setTime(t){this.time=0;for(let t=0;tthis.max.x||t.ythis.max.y)}containsBox(t){return this.min.x<=t.min.x&&t.max.x<=this.max.x&&this.min.y<=t.min.y&&t.max.y<=this.max.y}getParameter(t,e){return void 0===e&&(console.warn("THREE.Box2: .getParameter() target is now required"),e=new vt),e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y)}clampPoint(t,e){return void 0===e&&(console.warn("THREE.Box2: .clampPoint() target is now required"),e=new vt),e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return th.copy(t).clamp(this.min,this.max).sub(t).length()}intersect(t){return this.min.max(t.min),this.max.min(t.max),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}eh.prototype.isBox2=!0;const nh=new Lt,ih=new Lt;class rh{constructor(t=new Lt,e=new Lt){this.start=t,this.end=e}set(t,e){return this.start.copy(t),this.end.copy(e),this}copy(t){return this.start.copy(t.start),this.end.copy(t.end),this}getCenter(t){return void 0===t&&(console.warn("THREE.Line3: .getCenter() target is now required"),t=new Lt),t.addVectors(this.start,this.end).multiplyScalar(.5)}delta(t){return void 0===t&&(console.warn("THREE.Line3: .delta() target is now required"),t=new Lt),t.subVectors(this.end,this.start)}distanceSq(){return this.start.distanceToSquared(this.end)}distance(){return this.start.distanceTo(this.end)}at(t,e){return void 0===e&&(console.warn("THREE.Line3: .at() target is now required"),e=new Lt),this.delta(e).multiplyScalar(t).add(this.start)}closestPointToPointParameter(t,e){nh.subVectors(t,this.start),ih.subVectors(this.end,this.start);const n=ih.dot(ih);let i=ih.dot(nh)/n;return e&&(i=ht(i,0,1)),i}closestPointToPoint(t,e,n){const i=this.closestPointToPointParameter(t,e);return void 0===n&&(console.warn("THREE.Line3: .closestPointToPoint() target is now required"),n=new Lt),this.delta(n).multiplyScalar(i).add(this.start)}applyMatrix4(t){return this.start.applyMatrix4(t),this.end.applyMatrix4(t),this}equals(t){return t.start.equals(this.start)&&t.end.equals(this.end)}clone(){return(new this.constructor).copy(this)}}class sh extends Ce{constructor(t){super(),this.material=t,this.render=function(){},this.hasPositions=!1,this.hasNormals=!1,this.hasColors=!1,this.hasUvs=!1,this.positionArray=null,this.normalArray=null,this.colorArray=null,this.uvArray=null,this.count=0}}sh.prototype.isImmediateRenderObject=!0;const ah=new Lt;const oh=new Lt,lh=new se,ch=new se;class hh extends ya{constructor(t){const e=uh(t),n=new En,i=[],r=[],s=new tn(0,0,1),a=new tn(0,1,0);for(let t=0;t4?a=Ph[r-8+4-1]:0==r&&(a=0),n.push(a);const o=1/(s-1),l=-o/2,c=1+o/2,h=[l,l,c,l,c,c,l,l,c,c,l,c],u=6,d=6,p=3,m=2,f=1,g=new Float32Array(p*d*u),v=new Float32Array(m*d*u),y=new Float32Array(f*d*u);for(let t=0;t2?0:-1,i=[e,n,0,e+2/3,n,0,e+2/3,n+1,0,e,n,0,e+2/3,n+1,0,e,n+1,0];g.set(i,p*d*t),v.set(h,m*d*t);const r=[t,t,t,t,t,t];y.set(r,f*d*t)}const x=new En;x.setAttribute("position",new sn(g,p)),x.setAttribute("uv",new sn(v,m)),x.setAttribute("faceIndex",new sn(y,f)),t.push(x),i>4&&i--}return{_lodPlanes:t,_sizeLods:e,_sigmas:n}}function Zh(t){const e=new Tt(3*Ch,3*Ch,t);return e.texture.mapping=l,e.texture.name="PMREM.cubeUv",e.scissorTest=!0,e}function Jh(t,e,n,i,r){t.viewport.set(e,n,i,r),t.scissor.set(e,n,i,r)}function Qh(){const t=new vt(1,1);return new Io({name:"EquirectangularToCubeUV",uniforms:{envMap:{value:null},texelSize:{value:t},inputEncoding:{value:Nh[3e3]},outputEncoding:{value:Nh[3e3]}},vertexShader:$h(),fragmentShader:`\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform sampler2D envMap;\n\t\t\tuniform vec2 texelSize;\n\n\t\t\t${tu()}\n\n\t\t\t#include \n\n\t\t\tvoid main() {\n\n\t\t\t\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\n\t\t\t\tvec3 outputDirection = normalize( vOutputDirection );\n\t\t\t\tvec2 uv = equirectUv( outputDirection );\n\n\t\t\t\tvec2 f = fract( uv / texelSize - 0.5 );\n\t\t\t\tuv -= f * texelSize;\n\t\t\t\tvec3 tl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\n\t\t\t\tuv.x += texelSize.x;\n\t\t\t\tvec3 tr = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\n\t\t\t\tuv.y += texelSize.y;\n\t\t\t\tvec3 br = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\n\t\t\t\tuv.x -= texelSize.x;\n\t\t\t\tvec3 bl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\n\n\t\t\t\tvec3 tm = mix( tl, tr, f.x );\n\t\t\t\tvec3 bm = mix( bl, br, f.x );\n\t\t\t\tgl_FragColor.rgb = mix( tm, bm, f.y );\n\n\t\t\t\tgl_FragColor = linearToOutputTexel( gl_FragColor );\n\n\t\t\t}\n\t\t`,blending:0,depthTest:!1,depthWrite:!1})}function Kh(){return new Io({name:"CubemapToCubeUV",uniforms:{envMap:{value:null},inputEncoding:{value:Nh[3e3]},outputEncoding:{value:Nh[3e3]}},vertexShader:$h(),fragmentShader:`\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform samplerCube envMap;\n\n\t\t\t${tu()}\n\n\t\t\tvoid main() {\n\n\t\t\t\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t\t\t\tgl_FragColor.rgb = envMapTexelToLinear( textureCube( envMap, vec3( - vOutputDirection.x, vOutputDirection.yz ) ) ).rgb;\n\t\t\t\tgl_FragColor = linearToOutputTexel( gl_FragColor );\n\n\t\t\t}\n\t\t`,blending:0,depthTest:!1,depthWrite:!1})}function $h(){return"\n\n\t\tprecision mediump float;\n\t\tprecision mediump int;\n\n\t\tattribute vec3 position;\n\t\tattribute vec2 uv;\n\t\tattribute float faceIndex;\n\n\t\tvarying vec3 vOutputDirection;\n\n\t\t// RH coordinate system; PMREM face-indexing convention\n\t\tvec3 getDirection( vec2 uv, float face ) {\n\n\t\t\tuv = 2.0 * uv - 1.0;\n\n\t\t\tvec3 direction = vec3( uv, 1.0 );\n\n\t\t\tif ( face == 0.0 ) {\n\n\t\t\t\tdirection = direction.zyx; // ( 1, v, u ) pos x\n\n\t\t\t} else if ( face == 1.0 ) {\n\n\t\t\t\tdirection = direction.xzy;\n\t\t\t\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\n\n\t\t\t} else if ( face == 2.0 ) {\n\n\t\t\t\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\n\n\t\t\t} else if ( face == 3.0 ) {\n\n\t\t\t\tdirection = direction.zyx;\n\t\t\t\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\n\n\t\t\t} else if ( face == 4.0 ) {\n\n\t\t\t\tdirection = direction.xzy;\n\t\t\t\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\n\n\t\t\t} else if ( face == 5.0 ) {\n\n\t\t\t\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\n\n\t\t\t}\n\n\t\t\treturn direction;\n\n\t\t}\n\n\t\tvoid main() {\n\n\t\t\tvOutputDirection = getDirection( uv, faceIndex );\n\t\t\tgl_Position = vec4( position, 1.0 );\n\n\t\t}\n\t"}function tu(){return"\n\n\t\tuniform int inputEncoding;\n\t\tuniform int outputEncoding;\n\n\t\t#include \n\n\t\tvec4 inputTexelToLinear( vec4 value ) {\n\n\t\t\tif ( inputEncoding == 0 ) {\n\n\t\t\t\treturn value;\n\n\t\t\t} else if ( inputEncoding == 1 ) {\n\n\t\t\t\treturn sRGBToLinear( value );\n\n\t\t\t} else if ( inputEncoding == 2 ) {\n\n\t\t\t\treturn RGBEToLinear( value );\n\n\t\t\t} else if ( inputEncoding == 3 ) {\n\n\t\t\t\treturn RGBMToLinear( value, 7.0 );\n\n\t\t\t} else if ( inputEncoding == 4 ) {\n\n\t\t\t\treturn RGBMToLinear( value, 16.0 );\n\n\t\t\t} else if ( inputEncoding == 5 ) {\n\n\t\t\t\treturn RGBDToLinear( value, 256.0 );\n\n\t\t\t} else {\n\n\t\t\t\treturn GammaToLinear( value, 2.2 );\n\n\t\t\t}\n\n\t\t}\n\n\t\tvec4 linearToOutputTexel( vec4 value ) {\n\n\t\t\tif ( outputEncoding == 0 ) {\n\n\t\t\t\treturn value;\n\n\t\t\t} else if ( outputEncoding == 1 ) {\n\n\t\t\t\treturn LinearTosRGB( value );\n\n\t\t\t} else if ( outputEncoding == 2 ) {\n\n\t\t\t\treturn LinearToRGBE( value );\n\n\t\t\t} else if ( outputEncoding == 3 ) {\n\n\t\t\t\treturn LinearToRGBM( value, 7.0 );\n\n\t\t\t} else if ( outputEncoding == 4 ) {\n\n\t\t\t\treturn LinearToRGBM( value, 16.0 );\n\n\t\t\t} else if ( outputEncoding == 5 ) {\n\n\t\t\t\treturn LinearToRGBD( value, 256.0 );\n\n\t\t\t} else {\n\n\t\t\t\treturn LinearToGamma( value, 2.2 );\n\n\t\t\t}\n\n\t\t}\n\n\t\tvec4 envMapTexelToLinear( vec4 color ) {\n\n\t\t\treturn inputTexelToLinear( color );\n\n\t\t}\n\t"}ml.create=function(t,e){return console.log("THREE.Curve.create() has been deprecated"),t.prototype=Object.create(ml.prototype),t.prototype.constructor=t,t.prototype.getPoint=e,t},Bl.prototype.fromPoints=function(t){return console.warn("THREE.Path: .fromPoints() has been renamed to .setFromPoints()."),this.setFromPoints(t)},fh.prototype.setColors=function(){console.error("THREE.GridHelper: setColors() has been deprecated, pass them in the constructor instead.")},hh.prototype.update=function(){console.error("THREE.SkeletonHelper: update() no longer needs to be called.")},ol.prototype.extractUrlBase=function(t){return console.warn("THREE.Loader: .extractUrlBase() has been deprecated. Use THREE.LoaderUtils.extractUrlBase() instead."),rc.extractUrlBase(t)},ol.Handlers={add:function(){console.error("THREE.Loader: Handlers.add() has been removed. Use LoadingManager.addHandler() instead.")},get:function(){console.error("THREE.Loader: Handlers.get() has been removed. Use LoadingManager.getHandler() instead.")}},eh.prototype.center=function(t){return console.warn("THREE.Box2: .center() has been renamed to .getCenter()."),this.getCenter(t)},eh.prototype.empty=function(){return console.warn("THREE.Box2: .empty() has been renamed to .isEmpty()."),this.isEmpty()},eh.prototype.isIntersectionBox=function(t){return console.warn("THREE.Box2: .isIntersectionBox() has been renamed to .intersectsBox()."),this.intersectsBox(t)},eh.prototype.size=function(t){return console.warn("THREE.Box2: .size() has been renamed to .getSize()."),this.getSize(t)},Pt.prototype.center=function(t){return console.warn("THREE.Box3: .center() has been renamed to .getCenter()."),this.getCenter(t)},Pt.prototype.empty=function(){return console.warn("THREE.Box3: .empty() has been renamed to .isEmpty()."),this.isEmpty()},Pt.prototype.isIntersectionBox=function(t){return console.warn("THREE.Box3: .isIntersectionBox() has been renamed to .intersectsBox()."),this.intersectsBox(t)},Pt.prototype.isIntersectionSphere=function(t){return console.warn("THREE.Box3: .isIntersectionSphere() has been renamed to .intersectsSphere()."),this.intersectsSphere(t)},Pt.prototype.size=function(t){return console.warn("THREE.Box3: .size() has been renamed to .getSize()."),this.getSize(t)},Jt.prototype.empty=function(){return console.warn("THREE.Sphere: .empty() has been renamed to .isEmpty()."),this.isEmpty()},ai.prototype.setFromMatrix=function(t){return console.warn("THREE.Frustum: .setFromMatrix() has been renamed to .setFromProjectionMatrix()."),this.setFromProjectionMatrix(t)},rh.prototype.center=function(t){return console.warn("THREE.Line3: .center() has been renamed to .getCenter()."),this.getCenter(t)},yt.prototype.flattenToArrayOffset=function(t,e){return console.warn("THREE.Matrix3: .flattenToArrayOffset() has been deprecated. Use .toArray() instead."),this.toArray(t,e)},yt.prototype.multiplyVector3=function(t){return console.warn("THREE.Matrix3: .multiplyVector3() has been removed. Use vector.applyMatrix3( matrix ) instead."),t.applyMatrix3(this)},yt.prototype.multiplyVector3Array=function(){console.error("THREE.Matrix3: .multiplyVector3Array() has been removed.")},yt.prototype.applyToBufferAttribute=function(t){return console.warn("THREE.Matrix3: .applyToBufferAttribute() has been removed. Use attribute.applyMatrix3( matrix ) instead."),t.applyMatrix3(this)},yt.prototype.applyToVector3Array=function(){console.error("THREE.Matrix3: .applyToVector3Array() has been removed.")},yt.prototype.getInverse=function(t){return console.warn("THREE.Matrix3: .getInverse() has been removed. Use matrixInv.copy( matrix ).invert(); instead."),this.copy(t).invert()},se.prototype.extractPosition=function(t){return console.warn("THREE.Matrix4: .extractPosition() has been renamed to .copyPosition()."),this.copyPosition(t)},se.prototype.flattenToArrayOffset=function(t,e){return console.warn("THREE.Matrix4: .flattenToArrayOffset() has been deprecated. Use .toArray() instead."),this.toArray(t,e)},se.prototype.getPosition=function(){return console.warn("THREE.Matrix4: .getPosition() has been removed. Use Vector3.setFromMatrixPosition( matrix ) instead."),(new Lt).setFromMatrixColumn(this,3)},se.prototype.setRotationFromQuaternion=function(t){return console.warn("THREE.Matrix4: .setRotationFromQuaternion() has been renamed to .makeRotationFromQuaternion()."),this.makeRotationFromQuaternion(t)},se.prototype.multiplyToArray=function(){console.warn("THREE.Matrix4: .multiplyToArray() has been removed.")},se.prototype.multiplyVector3=function(t){return console.warn("THREE.Matrix4: .multiplyVector3() has been removed. Use vector.applyMatrix4( matrix ) instead."),t.applyMatrix4(this)},se.prototype.multiplyVector4=function(t){return console.warn("THREE.Matrix4: .multiplyVector4() has been removed. Use vector.applyMatrix4( matrix ) instead."),t.applyMatrix4(this)},se.prototype.multiplyVector3Array=function(){console.error("THREE.Matrix4: .multiplyVector3Array() has been removed.")},se.prototype.rotateAxis=function(t){console.warn("THREE.Matrix4: .rotateAxis() has been removed. Use Vector3.transformDirection( matrix ) instead."),t.transformDirection(this)},se.prototype.crossVector=function(t){return console.warn("THREE.Matrix4: .crossVector() has been removed. Use vector.applyMatrix4( matrix ) instead."),t.applyMatrix4(this)},se.prototype.translate=function(){console.error("THREE.Matrix4: .translate() has been removed.")},se.prototype.rotateX=function(){console.error("THREE.Matrix4: .rotateX() has been removed.")},se.prototype.rotateY=function(){console.error("THREE.Matrix4: .rotateY() has been removed.")},se.prototype.rotateZ=function(){console.error("THREE.Matrix4: .rotateZ() has been removed.")},se.prototype.rotateByAxis=function(){console.error("THREE.Matrix4: .rotateByAxis() has been removed.")},se.prototype.applyToBufferAttribute=function(t){return console.warn("THREE.Matrix4: .applyToBufferAttribute() has been removed. Use attribute.applyMatrix4( matrix ) instead."),t.applyMatrix4(this)},se.prototype.applyToVector3Array=function(){console.error("THREE.Matrix4: .applyToVector3Array() has been removed.")},se.prototype.makeFrustum=function(t,e,n,i,r,s){return console.warn("THREE.Matrix4: .makeFrustum() has been removed. Use .makePerspective( left, right, top, bottom, near, far ) instead."),this.makePerspective(t,e,i,n,r,s)},se.prototype.getInverse=function(t){return console.warn("THREE.Matrix4: .getInverse() has been removed. Use matrixInv.copy( matrix ).invert(); instead."),this.copy(t).invert()},Ne.prototype.isIntersectionLine=function(t){return console.warn("THREE.Plane: .isIntersectionLine() has been renamed to .intersectsLine()."),this.intersectsLine(t)},At.prototype.multiplyVector3=function(t){return console.warn("THREE.Quaternion: .multiplyVector3() has been removed. Use is now vector.applyQuaternion( quaternion ) instead."),t.applyQuaternion(this)},At.prototype.inverse=function(){return console.warn("THREE.Quaternion: .inverse() has been renamed to invert()."),this.invert()},re.prototype.isIntersectionBox=function(t){return console.warn("THREE.Ray: .isIntersectionBox() has been renamed to .intersectsBox()."),this.intersectsBox(t)},re.prototype.isIntersectionPlane=function(t){return console.warn("THREE.Ray: .isIntersectionPlane() has been renamed to .intersectsPlane()."),this.intersectsPlane(t)},re.prototype.isIntersectionSphere=function(t){return console.warn("THREE.Ray: .isIntersectionSphere() has been renamed to .intersectsSphere()."),this.intersectsSphere(t)},je.prototype.area=function(){return console.warn("THREE.Triangle: .area() has been renamed to .getArea()."),this.getArea()},je.prototype.barycoordFromPoint=function(t,e){return console.warn("THREE.Triangle: .barycoordFromPoint() has been renamed to .getBarycoord()."),this.getBarycoord(t,e)},je.prototype.midpoint=function(t){return console.warn("THREE.Triangle: .midpoint() has been renamed to .getMidpoint()."),this.getMidpoint(t)},je.prototypenormal=function(t){return console.warn("THREE.Triangle: .normal() has been renamed to .getNormal()."),this.getNormal(t)},je.prototype.plane=function(t){return console.warn("THREE.Triangle: .plane() has been renamed to .getPlane()."),this.getPlane(t)},je.barycoordFromPoint=function(t,e,n,i,r){return console.warn("THREE.Triangle: .barycoordFromPoint() has been renamed to .getBarycoord()."),je.getBarycoord(t,e,n,i,r)},je.normal=function(t,e,n,i){return console.warn("THREE.Triangle: .normal() has been renamed to .getNormal()."),je.getNormal(t,e,n,i)},zl.prototype.extractAllPoints=function(t){return console.warn("THREE.Shape: .extractAllPoints() has been removed. Use .extractPoints() instead."),this.extractPoints(t)},zl.prototype.extrude=function(t){return console.warn("THREE.Shape: .extrude() has been removed. Use ExtrudeGeometry() instead."),new go(this,t)},zl.prototype.makeGeometry=function(t){return console.warn("THREE.Shape: .makeGeometry() has been removed. Use ShapeGeometry() instead."),new Mo(this,t)},vt.prototype.fromAttribute=function(t,e,n){return console.warn("THREE.Vector2: .fromAttribute() has been renamed to .fromBufferAttribute()."),this.fromBufferAttribute(t,e,n)},vt.prototype.distanceToManhattan=function(t){return console.warn("THREE.Vector2: .distanceToManhattan() has been renamed to .manhattanDistanceTo()."),this.manhattanDistanceTo(t)},vt.prototype.lengthManhattan=function(){return console.warn("THREE.Vector2: .lengthManhattan() has been renamed to .manhattanLength()."),this.manhattanLength()},Lt.prototype.setEulerFromRotationMatrix=function(){console.error("THREE.Vector3: .setEulerFromRotationMatrix() has been removed. Use Euler.setFromRotationMatrix() instead.")},Lt.prototype.setEulerFromQuaternion=function(){console.error("THREE.Vector3: .setEulerFromQuaternion() has been removed. Use Euler.setFromQuaternion() instead.")},Lt.prototype.getPositionFromMatrix=function(t){return console.warn("THREE.Vector3: .getPositionFromMatrix() has been renamed to .setFromMatrixPosition()."),this.setFromMatrixPosition(t)},Lt.prototype.getScaleFromMatrix=function(t){return console.warn("THREE.Vector3: .getScaleFromMatrix() has been renamed to .setFromMatrixScale()."),this.setFromMatrixScale(t)},Lt.prototype.getColumnFromMatrix=function(t,e){return console.warn("THREE.Vector3: .getColumnFromMatrix() has been renamed to .setFromMatrixColumn()."),this.setFromMatrixColumn(e,t)},Lt.prototype.applyProjection=function(t){return console.warn("THREE.Vector3: .applyProjection() has been removed. Use .applyMatrix4( m ) instead."),this.applyMatrix4(t)},Lt.prototype.fromAttribute=function(t,e,n){return console.warn("THREE.Vector3: .fromAttribute() has been renamed to .fromBufferAttribute()."),this.fromBufferAttribute(t,e,n)},Lt.prototype.distanceToManhattan=function(t){return console.warn("THREE.Vector3: .distanceToManhattan() has been renamed to .manhattanDistanceTo()."),this.manhattanDistanceTo(t)},Lt.prototype.lengthManhattan=function(){return console.warn("THREE.Vector3: .lengthManhattan() has been renamed to .manhattanLength()."),this.manhattanLength()},St.prototype.fromAttribute=function(t,e,n){return console.warn("THREE.Vector4: .fromAttribute() has been renamed to .fromBufferAttribute()."),this.fromBufferAttribute(t,e,n)},St.prototype.lengthManhattan=function(){return console.warn("THREE.Vector4: .lengthManhattan() has been renamed to .manhattanLength()."),this.manhattanLength()},Ce.prototype.getChildByName=function(t){return console.warn("THREE.Object3D: .getChildByName() has been renamed to .getObjectByName()."),this.getObjectByName(t)},Ce.prototype.renderDepth=function(){console.warn("THREE.Object3D: .renderDepth has been removed. Use .renderOrder, instead.")},Ce.prototype.translate=function(t,e){return console.warn("THREE.Object3D: .translate() has been removed. Use .translateOnAxis( axis, distance ) instead."),this.translateOnAxis(e,t)},Ce.prototype.getWorldRotation=function(){console.error("THREE.Object3D: .getWorldRotation() has been removed. Use THREE.Object3D.getWorldQuaternion( target ) instead.")},Ce.prototype.applyMatrix=function(t){return console.warn("THREE.Object3D: .applyMatrix() has been renamed to .applyMatrix4()."),this.applyMatrix4(t)},Object.defineProperties(Ce.prototype,{eulerOrder:{get:function(){return console.warn("THREE.Object3D: .eulerOrder is now .rotation.order."),this.rotation.order},set:function(t){console.warn("THREE.Object3D: .eulerOrder is now .rotation.order."),this.rotation.order=t}},useQuaternion:{get:function(){console.warn("THREE.Object3D: .useQuaternion has been removed. The library now uses quaternions by default.")},set:function(){console.warn("THREE.Object3D: .useQuaternion has been removed. The library now uses quaternions by default.")}}}),Wn.prototype.setDrawMode=function(){console.error("THREE.Mesh: .setDrawMode() has been removed. The renderer now always assumes THREE.TrianglesDrawMode. Transform your geometry via BufferGeometryUtils.toTrianglesDrawMode() if necessary.")},Object.defineProperties(Wn.prototype,{drawMode:{get:function(){return console.error("THREE.Mesh: .drawMode has been removed. The renderer now always assumes THREE.TrianglesDrawMode."),0},set:function(){console.error("THREE.Mesh: .drawMode has been removed. The renderer now always assumes THREE.TrianglesDrawMode. Transform your geometry via BufferGeometryUtils.toTrianglesDrawMode() if necessary.")}}}),$s.prototype.initBones=function(){console.error("THREE.SkinnedMesh: initBones() has been removed.")},Kn.prototype.setLens=function(t,e){console.warn("THREE.PerspectiveCamera.setLens is deprecated. Use .setFocalLength and .filmGauge for a photographic setup."),void 0!==e&&(this.filmGauge=e),this.setFocalLength(t)},Object.defineProperties(Fl.prototype,{onlyShadow:{set:function(){console.warn("THREE.Light: .onlyShadow has been removed.")}},shadowCameraFov:{set:function(t){console.warn("THREE.Light: .shadowCameraFov is now .shadow.camera.fov."),this.shadow.camera.fov=t}},shadowCameraLeft:{set:function(t){console.warn("THREE.Light: .shadowCameraLeft is now .shadow.camera.left."),this.shadow.camera.left=t}},shadowCameraRight:{set:function(t){console.warn("THREE.Light: .shadowCameraRight is now .shadow.camera.right."),this.shadow.camera.right=t}},shadowCameraTop:{set:function(t){console.warn("THREE.Light: .shadowCameraTop is now .shadow.camera.top."),this.shadow.camera.top=t}},shadowCameraBottom:{set:function(t){console.warn("THREE.Light: .shadowCameraBottom is now .shadow.camera.bottom."),this.shadow.camera.bottom=t}},shadowCameraNear:{set:function(t){console.warn("THREE.Light: .shadowCameraNear is now .shadow.camera.near."),this.shadow.camera.near=t}},shadowCameraFar:{set:function(t){console.warn("THREE.Light: .shadowCameraFar is now .shadow.camera.far."),this.shadow.camera.far=t}},shadowCameraVisible:{set:function(){console.warn("THREE.Light: .shadowCameraVisible has been removed. Use new THREE.CameraHelper( light.shadow.camera ) instead.")}},shadowBias:{set:function(t){console.warn("THREE.Light: .shadowBias is now .shadow.bias."),this.shadow.bias=t}},shadowDarkness:{set:function(){console.warn("THREE.Light: .shadowDarkness has been removed.")}},shadowMapWidth:{set:function(t){console.warn("THREE.Light: .shadowMapWidth is now .shadow.mapSize.width."),this.shadow.mapSize.width=t}},shadowMapHeight:{set:function(t){console.warn("THREE.Light: .shadowMapHeight is now .shadow.mapSize.height."),this.shadow.mapSize.height=t}}}),Object.defineProperties(sn.prototype,{length:{get:function(){return console.warn("THREE.BufferAttribute: .length has been deprecated. Use .count instead."),this.array.length}},dynamic:{get:function(){return console.warn("THREE.BufferAttribute: .dynamic has been deprecated. Use .usage instead."),this.usage===nt},set:function(){console.warn("THREE.BufferAttribute: .dynamic has been deprecated. Use .usage instead."),this.setUsage(nt)}}}),sn.prototype.setDynamic=function(t){return console.warn("THREE.BufferAttribute: .setDynamic() has been deprecated. Use .setUsage() instead."),this.setUsage(!0===t?nt:et),this},sn.prototype.copyIndicesArray=function(){console.error("THREE.BufferAttribute: .copyIndicesArray() has been removed.")},sn.prototype.setArray=function(){console.error("THREE.BufferAttribute: .setArray has been removed. Use BufferGeometry .setAttribute to replace/resize attribute buffers")},En.prototype.addIndex=function(t){console.warn("THREE.BufferGeometry: .addIndex() has been renamed to .setIndex()."),this.setIndex(t)},En.prototype.addAttribute=function(t,e){return console.warn("THREE.BufferGeometry: .addAttribute() has been renamed to .setAttribute()."),e&&e.isBufferAttribute||e&&e.isInterleavedBufferAttribute?"index"===t?(console.warn("THREE.BufferGeometry.addAttribute: Use .setIndex() for index attribute."),this.setIndex(e),this):this.setAttribute(t,e):(console.warn("THREE.BufferGeometry: .addAttribute() now expects ( name, attribute )."),this.setAttribute(t,new sn(arguments[1],arguments[2])))},En.prototype.addDrawCall=function(t,e,n){void 0!==n&&console.warn("THREE.BufferGeometry: .addDrawCall() no longer supports indexOffset."),console.warn("THREE.BufferGeometry: .addDrawCall() is now .addGroup()."),this.addGroup(t,e)},En.prototype.clearDrawCalls=function(){console.warn("THREE.BufferGeometry: .clearDrawCalls() is now .clearGroups()."),this.clearGroups()},En.prototype.computeOffsets=function(){console.warn("THREE.BufferGeometry: .computeOffsets() has been removed.")},En.prototype.removeAttribute=function(t){return console.warn("THREE.BufferGeometry: .removeAttribute() has been renamed to .deleteAttribute()."),this.deleteAttribute(t)},En.prototype.applyMatrix=function(t){return console.warn("THREE.BufferGeometry: .applyMatrix() has been renamed to .applyMatrix4()."),this.applyMatrix4(t)},Object.defineProperties(En.prototype,{drawcalls:{get:function(){return console.error("THREE.BufferGeometry: .drawcalls has been renamed to .groups."),this.groups}},offsets:{get:function(){return console.warn("THREE.BufferGeometry: .offsets has been renamed to .groups."),this.groups}}}),Es.prototype.setDynamic=function(t){return console.warn("THREE.InterleavedBuffer: .setDynamic() has been deprecated. Use .setUsage() instead."),this.setUsage(!0===t?nt:et),this},Es.prototype.setArray=function(){console.error("THREE.InterleavedBuffer: .setArray has been removed. Use BufferGeometry .setAttribute to replace/resize attribute buffers")},go.prototype.getArrays=function(){console.error("THREE.ExtrudeGeometry: .getArrays() has been removed.")},go.prototype.addShapeList=function(){console.error("THREE.ExtrudeGeometry: .addShapeList() has been removed.")},go.prototype.addShape=function(){console.error("THREE.ExtrudeGeometry: .addShape() has been removed.")},Ts.prototype.dispose=function(){console.error("THREE.Scene: .dispose() has been removed.")},Zc.prototype.onUpdate=function(){return console.warn("THREE.Uniform: .onUpdate() has been removed. Use object.onBeforeRender() instead."),this},Object.defineProperties(Xe.prototype,{wrapAround:{get:function(){console.warn("THREE.Material: .wrapAround has been removed.")},set:function(){console.warn("THREE.Material: .wrapAround has been removed.")}},overdraw:{get:function(){console.warn("THREE.Material: .overdraw has been removed.")},set:function(){console.warn("THREE.Material: .overdraw has been removed.")}},wrapRGB:{get:function(){return console.warn("THREE.Material: .wrapRGB has been removed."),new tn}},shading:{get:function(){console.error("THREE."+this.type+": .shading has been removed. Use the boolean .flatShading instead.")},set:function(t){console.warn("THREE."+this.type+": .shading has been removed. Use the boolean .flatShading instead."),this.flatShading=1===t}},stencilMask:{get:function(){return console.warn("THREE."+this.type+": .stencilMask has been removed. Use .stencilFuncMask instead."),this.stencilFuncMask},set:function(t){console.warn("THREE."+this.type+": .stencilMask has been removed. Use .stencilFuncMask instead."),this.stencilFuncMask=t}}}),Object.defineProperties(Jn.prototype,{derivatives:{get:function(){return console.warn("THREE.ShaderMaterial: .derivatives has been moved to .extensions.derivatives."),this.extensions.derivatives},set:function(t){console.warn("THREE. ShaderMaterial: .derivatives has been moved to .extensions.derivatives."),this.extensions.derivatives=t}}}),ws.prototype.clearTarget=function(t,e,n,i){console.warn("THREE.WebGLRenderer: .clearTarget() has been deprecated. Use .setRenderTarget() and .clear() instead."),this.setRenderTarget(t),this.clear(e,n,i)},ws.prototype.animate=function(t){console.warn("THREE.WebGLRenderer: .animate() is now .setAnimationLoop()."),this.setAnimationLoop(t)},ws.prototype.getCurrentRenderTarget=function(){return console.warn("THREE.WebGLRenderer: .getCurrentRenderTarget() is now .getRenderTarget()."),this.getRenderTarget()},ws.prototype.getMaxAnisotropy=function(){return console.warn("THREE.WebGLRenderer: .getMaxAnisotropy() is now .capabilities.getMaxAnisotropy()."),this.capabilities.getMaxAnisotropy()},ws.prototype.getPrecision=function(){return console.warn("THREE.WebGLRenderer: .getPrecision() is now .capabilities.precision."),this.capabilities.precision},ws.prototype.resetGLState=function(){return console.warn("THREE.WebGLRenderer: .resetGLState() is now .state.reset()."),this.state.reset()},ws.prototype.supportsFloatTextures=function(){return console.warn("THREE.WebGLRenderer: .supportsFloatTextures() is now .extensions.get( 'OES_texture_float' )."),this.extensions.get("OES_texture_float")},ws.prototype.supportsHalfFloatTextures=function(){return console.warn("THREE.WebGLRenderer: .supportsHalfFloatTextures() is now .extensions.get( 'OES_texture_half_float' )."),this.extensions.get("OES_texture_half_float")},ws.prototype.supportsStandardDerivatives=function(){return console.warn("THREE.WebGLRenderer: .supportsStandardDerivatives() is now .extensions.get( 'OES_standard_derivatives' )."),this.extensions.get("OES_standard_derivatives")},ws.prototype.supportsCompressedTextureS3TC=function(){return console.warn("THREE.WebGLRenderer: .supportsCompressedTextureS3TC() is now .extensions.get( 'WEBGL_compressed_texture_s3tc' )."),this.extensions.get("WEBGL_compressed_texture_s3tc")},ws.prototype.supportsCompressedTexturePVRTC=function(){return console.warn("THREE.WebGLRenderer: .supportsCompressedTexturePVRTC() is now .extensions.get( 'WEBGL_compressed_texture_pvrtc' )."),this.extensions.get("WEBGL_compressed_texture_pvrtc")},ws.prototype.supportsBlendMinMax=function(){return console.warn("THREE.WebGLRenderer: .supportsBlendMinMax() is now .extensions.get( 'EXT_blend_minmax' )."),this.extensions.get("EXT_blend_minmax")},ws.prototype.supportsVertexTextures=function(){return console.warn("THREE.WebGLRenderer: .supportsVertexTextures() is now .capabilities.vertexTextures."),this.capabilities.vertexTextures},ws.prototype.supportsInstancedArrays=function(){return console.warn("THREE.WebGLRenderer: .supportsInstancedArrays() is now .extensions.get( 'ANGLE_instanced_arrays' )."),this.extensions.get("ANGLE_instanced_arrays")},ws.prototype.enableScissorTest=function(t){console.warn("THREE.WebGLRenderer: .enableScissorTest() is now .setScissorTest()."),this.setScissorTest(t)},ws.prototype.initMaterial=function(){console.warn("THREE.WebGLRenderer: .initMaterial() has been removed.")},ws.prototype.addPrePlugin=function(){console.warn("THREE.WebGLRenderer: .addPrePlugin() has been removed.")},ws.prototype.addPostPlugin=function(){console.warn("THREE.WebGLRenderer: .addPostPlugin() has been removed.")},ws.prototype.updateShadowMap=function(){console.warn("THREE.WebGLRenderer: .updateShadowMap() has been removed.")},ws.prototype.setFaceCulling=function(){console.warn("THREE.WebGLRenderer: .setFaceCulling() has been removed.")},ws.prototype.allocTextureUnit=function(){console.warn("THREE.WebGLRenderer: .allocTextureUnit() has been removed.")},ws.prototype.setTexture=function(){console.warn("THREE.WebGLRenderer: .setTexture() has been removed.")},ws.prototype.setTexture2D=function(){console.warn("THREE.WebGLRenderer: .setTexture2D() has been removed.")},ws.prototype.setTextureCube=function(){console.warn("THREE.WebGLRenderer: .setTextureCube() has been removed.")},ws.prototype.getActiveMipMapLevel=function(){return console.warn("THREE.WebGLRenderer: .getActiveMipMapLevel() is now .getActiveMipmapLevel()."),this.getActiveMipmapLevel()},Object.defineProperties(ws.prototype,{shadowMapEnabled:{get:function(){return this.shadowMap.enabled},set:function(t){console.warn("THREE.WebGLRenderer: .shadowMapEnabled is now .shadowMap.enabled."),this.shadowMap.enabled=t}},shadowMapType:{get:function(){return this.shadowMap.type},set:function(t){console.warn("THREE.WebGLRenderer: .shadowMapType is now .shadowMap.type."),this.shadowMap.type=t}},shadowMapCullFace:{get:function(){console.warn("THREE.WebGLRenderer: .shadowMapCullFace has been removed. Set Material.shadowSide instead.")},set:function(){console.warn("THREE.WebGLRenderer: .shadowMapCullFace has been removed. Set Material.shadowSide instead.")}},context:{get:function(){return console.warn("THREE.WebGLRenderer: .context has been removed. Use .getContext() instead."),this.getContext()}},vr:{get:function(){return console.warn("THREE.WebGLRenderer: .vr has been renamed to .xr"),this.xr}},gammaInput:{get:function(){return console.warn("THREE.WebGLRenderer: .gammaInput has been removed. Set the encoding for textures via Texture.encoding instead."),!1},set:function(){console.warn("THREE.WebGLRenderer: .gammaInput has been removed. Set the encoding for textures via Texture.encoding instead.")}},gammaOutput:{get:function(){return console.warn("THREE.WebGLRenderer: .gammaOutput has been removed. Set WebGLRenderer.outputEncoding instead."),!1},set:function(t){console.warn("THREE.WebGLRenderer: .gammaOutput has been removed. Set WebGLRenderer.outputEncoding instead."),this.outputEncoding=!0===t?Y:X}},toneMappingWhitePoint:{get:function(){return console.warn("THREE.WebGLRenderer: .toneMappingWhitePoint has been removed."),1},set:function(){console.warn("THREE.WebGLRenderer: .toneMappingWhitePoint has been removed.")}}}),Object.defineProperties(us.prototype,{cullFace:{get:function(){console.warn("THREE.WebGLRenderer: .shadowMap.cullFace has been removed. Set Material.shadowSide instead.")},set:function(){console.warn("THREE.WebGLRenderer: .shadowMap.cullFace has been removed. Set Material.shadowSide instead.")}},renderReverseSided:{get:function(){console.warn("THREE.WebGLRenderer: .shadowMap.renderReverseSided has been removed. Set Material.shadowSide instead.")},set:function(){console.warn("THREE.WebGLRenderer: .shadowMap.renderReverseSided has been removed. Set Material.shadowSide instead.")}},renderSingleSided:{get:function(){console.warn("THREE.WebGLRenderer: .shadowMap.renderSingleSided has been removed. Set Material.shadowSide instead.")},set:function(){console.warn("THREE.WebGLRenderer: .shadowMap.renderSingleSided has been removed. Set Material.shadowSide instead.")}}}),Object.defineProperties(Tt.prototype,{wrapS:{get:function(){return console.warn("THREE.WebGLRenderTarget: .wrapS is now .texture.wrapS."),this.texture.wrapS},set:function(t){console.warn("THREE.WebGLRenderTarget: .wrapS is now .texture.wrapS."),this.texture.wrapS=t}},wrapT:{get:function(){return console.warn("THREE.WebGLRenderTarget: .wrapT is now .texture.wrapT."),this.texture.wrapT},set:function(t){console.warn("THREE.WebGLRenderTarget: .wrapT is now .texture.wrapT."),this.texture.wrapT=t}},magFilter:{get:function(){return console.warn("THREE.WebGLRenderTarget: .magFilter is now .texture.magFilter."),this.texture.magFilter},set:function(t){console.warn("THREE.WebGLRenderTarget: .magFilter is now .texture.magFilter."),this.texture.magFilter=t}},minFilter:{get:function(){return console.warn("THREE.WebGLRenderTarget: .minFilter is now .texture.minFilter."),this.texture.minFilter},set:function(t){console.warn("THREE.WebGLRenderTarget: .minFilter is now .texture.minFilter."),this.texture.minFilter=t}},anisotropy:{get:function(){return console.warn("THREE.WebGLRenderTarget: .anisotropy is now .texture.anisotropy."),this.texture.anisotropy},set:function(t){console.warn("THREE.WebGLRenderTarget: .anisotropy is now .texture.anisotropy."),this.texture.anisotropy=t}},offset:{get:function(){return console.warn("THREE.WebGLRenderTarget: .offset is now .texture.offset."),this.texture.offset},set:function(t){console.warn("THREE.WebGLRenderTarget: .offset is now .texture.offset."),this.texture.offset=t}},repeat:{get:function(){return console.warn("THREE.WebGLRenderTarget: .repeat is now .texture.repeat."),this.texture.repeat},set:function(t){console.warn("THREE.WebGLRenderTarget: .repeat is now .texture.repeat."),this.texture.repeat=t}},format:{get:function(){return console.warn("THREE.WebGLRenderTarget: .format is now .texture.format."),this.texture.format},set:function(t){console.warn("THREE.WebGLRenderTarget: .format is now .texture.format."),this.texture.format=t}},type:{get:function(){return console.warn("THREE.WebGLRenderTarget: .type is now .texture.type."),this.texture.type},set:function(t){console.warn("THREE.WebGLRenderTarget: .type is now .texture.type."),this.texture.type=t}},generateMipmaps:{get:function(){return console.warn("THREE.WebGLRenderTarget: .generateMipmaps is now .texture.generateMipmaps."),this.texture.generateMipmaps},set:function(t){console.warn("THREE.WebGLRenderTarget: .generateMipmaps is now .texture.generateMipmaps."),this.texture.generateMipmaps=t}}}),Lc.prototype.load=function(t){console.warn("THREE.Audio: .load has been deprecated. Use THREE.AudioLoader instead.");const e=this;return(new vc).load(t,(function(t){e.setBuffer(t)})),this},Ic.prototype.getData=function(){return console.warn("THREE.AudioAnalyser: .getData() is now .getFrequencyData()."),this.getFrequencyData()},ti.prototype.updateCubeMap=function(t,e){return console.warn("THREE.CubeCamera: .updateCubeMap() is now .update()."),this.update(t,e)},ti.prototype.clear=function(t,e,n,i){return console.warn("THREE.CubeCamera: .clear() is now .renderTarget.clear()."),this.renderTarget.clear(t,e,n,i)},_t.crossOrigin=void 0,_t.loadTexture=function(t,e,n,i){console.warn("THREE.ImageUtils.loadTexture has been deprecated. Use THREE.TextureLoader() instead.");const r=new pl;r.setCrossOrigin(this.crossOrigin);const s=r.load(t,n,void 0,i);return e&&(s.mapping=e),s},_t.loadTextureCube=function(t,e,n,i){console.warn("THREE.ImageUtils.loadTextureCube has been deprecated. Use THREE.CubeTextureLoader() instead.");const r=new ul;r.setCrossOrigin(this.crossOrigin);const s=r.load(t,n,void 0,i);return e&&(s.mapping=e),s},_t.loadCompressedTexture=function(){console.error("THREE.ImageUtils.loadCompressedTexture has been removed. Use THREE.DDSLoader instead.")},_t.loadCompressedTextureCube=function(){console.error("THREE.ImageUtils.loadCompressedTextureCube has been removed. Use THREE.DDSLoader instead.")};const eu={createMultiMaterialObject:function(){console.error("THREE.SceneUtils has been moved to /examples/jsm/utils/SceneUtils.js")},detach:function(){console.error("THREE.SceneUtils has been moved to /examples/jsm/utils/SceneUtils.js")},attach:function(){console.error("THREE.SceneUtils has been moved to /examples/jsm/utils/SceneUtils.js")}};"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("register",{detail:{revision:e}})),"undefined"!=typeof window&&(window.__THREE__?console.warn("WARNING: Multiple instances of Three.js being imported."):window.__THREE__=e),t.ACESFilmicToneMapping=4,t.AddEquation=n,t.AddOperation=2,t.AdditiveAnimationBlendMode=q,t.AdditiveBlending=2,t.AlphaFormat=1021,t.AlwaysDepth=1,t.AlwaysStencilFunc=519,t.AmbientLight=$l,t.AmbientLightProbe=xc,t.AnimationClip=nl,t.AnimationLoader=class extends ol{constructor(t){super(t)}load(t,e,n,i){const r=this,s=new cl(this.manager);s.setPath(this.path),s.setRequestHeader(this.requestHeader),s.setWithCredentials(this.withCredentials),s.load(t,(function(n){try{e(r.parse(JSON.parse(n)))}catch(e){i?i(e):console.error(e),r.manager.itemError(t)}}),n,i)}parse(t){const e=[];for(let n=0;n.99999)this.quaternion.set(0,0,0,1);else if(t.y<-.99999)this.quaternion.set(1,0,0,0);else{Sh.set(t.z,0,-t.x).normalize();const e=Math.acos(t.y);this.quaternion.setFromAxisAngle(Sh,e)}}setLength(t,e=.2*t,n=.2*e){this.line.scale.set(1,Math.max(1e-4,t-e),1),this.line.updateMatrix(),this.cone.scale.set(n,e,n),this.cone.position.y=t,this.cone.updateMatrix()}setColor(t){this.line.material.color.set(t),this.cone.material.color.set(t)}copy(t){return super.copy(t,!1),this.line.copy(t.line),this.cone.copy(t.cone),this}},t.Audio=Lc,t.AudioAnalyser=Ic,t.AudioContext=gc,t.AudioListener=class extends Ce{constructor(){super(),this.type="AudioListener",this.context=gc.getContext(),this.gain=this.context.createGain(),this.gain.connect(this.context.destination),this.filter=null,this.timeDelta=0,this._clock=new bc}getInput(){return this.gain}removeFilter(){return null!==this.filter&&(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination),this.gain.connect(this.context.destination),this.filter=null),this}getFilter(){return this.filter}setFilter(t){return null!==this.filter?(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination)):this.gain.disconnect(this.context.destination),this.filter=t,this.gain.connect(this.filter),this.filter.connect(this.context.destination),this}getMasterVolume(){return this.gain.gain.value}setMasterVolume(t){return this.gain.gain.setTargetAtTime(t,this.context.currentTime,.01),this}updateMatrixWorld(t){super.updateMatrixWorld(t);const e=this.context.listener,n=this.up;if(this.timeDelta=this._clock.getDelta(),this.matrixWorld.decompose(Sc,Tc,Ec),Ac.set(0,0,-1).applyQuaternion(Tc),e.positionX){const t=this.context.currentTime+this.timeDelta;e.positionX.linearRampToValueAtTime(Sc.x,t),e.positionY.linearRampToValueAtTime(Sc.y,t),e.positionZ.linearRampToValueAtTime(Sc.z,t),e.forwardX.linearRampToValueAtTime(Ac.x,t),e.forwardY.linearRampToValueAtTime(Ac.y,t),e.forwardZ.linearRampToValueAtTime(Ac.z,t),e.upX.linearRampToValueAtTime(n.x,t),e.upY.linearRampToValueAtTime(n.y,t),e.upZ.linearRampToValueAtTime(n.z,t)}else e.setPosition(Sc.x,Sc.y,Sc.z),e.setOrientation(Ac.x,Ac.y,Ac.z,n.x,n.y,n.z)}},t.AudioLoader=vc,t.AxesHelper=Ah,t.AxisHelper=function(t){return console.warn("THREE.AxisHelper has been renamed to THREE.AxesHelper."),new Ah(t)},t.BackSide=1,t.BasicDepthPacking=3200,t.BasicShadowMap=0,t.BinaryTextureLoader=function(t){return console.warn("THREE.BinaryTextureLoader has been renamed to THREE.DataTextureLoader."),new dl(t)},t.Bone=ta,t.BooleanKeyframeTrack=Zo,t.BoundingBoxHelper=function(t,e){return console.warn("THREE.BoundingBoxHelper has been deprecated. Creating a THREE.BoxHelper instead."),new Mh(t,e)},t.Box2=eh,t.Box3=Pt,t.Box3Helper=class extends ya{constructor(t,e=16776960){const n=new Uint16Array([0,1,1,2,2,3,3,0,4,5,5,6,6,7,7,4,0,4,1,5,2,6,3,7]),i=new En;i.setIndex(new sn(n,1)),i.setAttribute("position",new mn([1,1,1,-1,1,1,-1,-1,1,1,-1,1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1],3)),super(i,new ca({color:e,toneMapped:!1})),this.box=t,this.type="Box3Helper",this.geometry.computeBoundingSphere()}updateMatrixWorld(t){const e=this.box;e.isEmpty()||(e.getCenter(this.position),e.getSize(this.scale),this.scale.multiplyScalar(.5),super.updateMatrixWorld(t))}},t.BoxBufferGeometry=qn,t.BoxGeometry=qn,t.BoxHelper=Mh,t.BufferAttribute=sn,t.BufferGeometry=En,t.BufferGeometryLoader=oc,t.ByteType=1010,t.Cache=rl,t.Camera=Qn,t.CameraHelper=class extends ya{constructor(t){const e=new En,n=new ca({color:16777215,vertexColors:!0,toneMapped:!1}),i=[],r=[],s={},a=new tn(16755200),o=new tn(16711680),l=new tn(43775),c=new tn(16777215),h=new tn(3355443);function u(t,e,n){d(t,n),d(e,n)}function d(t,e){i.push(0,0,0),r.push(e.r,e.g,e.b),void 0===s[t]&&(s[t]=[]),s[t].push(i.length/3-1)}u("n1","n2",a),u("n2","n4",a),u("n4","n3",a),u("n3","n1",a),u("f1","f2",a),u("f2","f4",a),u("f4","f3",a),u("f3","f1",a),u("n1","f1",a),u("n2","f2",a),u("n3","f3",a),u("n4","f4",a),u("p","n1",o),u("p","n2",o),u("p","n3",o),u("p","n4",o),u("u1","u2",l),u("u2","u3",l),u("u3","u1",l),u("c","t",c),u("p","c",h),u("cn1","cn2",h),u("cn3","cn4",h),u("cf1","cf2",h),u("cf3","cf4",h),e.setAttribute("position",new mn(i,3)),e.setAttribute("color",new mn(r,3)),super(e,n),this.type="CameraHelper",this.camera=t,this.camera.updateProjectionMatrix&&this.camera.updateProjectionMatrix(),this.matrix=t.matrixWorld,this.matrixAutoUpdate=!1,this.pointMap=s,this.update()}update(){const t=this.geometry,e=this.pointMap;_h.projectionMatrixInverse.copy(this.camera.projectionMatrixInverse),wh("c",e,t,_h,0,0,-1),wh("t",e,t,_h,0,0,1),wh("n1",e,t,_h,-1,-1,-1),wh("n2",e,t,_h,1,-1,-1),wh("n3",e,t,_h,-1,1,-1),wh("n4",e,t,_h,1,1,-1),wh("f1",e,t,_h,-1,-1,1),wh("f2",e,t,_h,1,-1,1),wh("f3",e,t,_h,-1,1,1),wh("f4",e,t,_h,1,1,1),wh("u1",e,t,_h,.7,1.1,-1),wh("u2",e,t,_h,-.7,1.1,-1),wh("u3",e,t,_h,0,2,-1),wh("cf1",e,t,_h,-1,0,1),wh("cf2",e,t,_h,1,0,1),wh("cf3",e,t,_h,0,-1,1),wh("cf4",e,t,_h,0,1,1),wh("cn1",e,t,_h,-1,0,-1),wh("cn2",e,t,_h,1,0,-1),wh("cn3",e,t,_h,0,-1,-1),wh("cn4",e,t,_h,0,1,-1),t.getAttribute("position").needsUpdate=!0}dispose(){this.geometry.dispose(),this.material.dispose()}},t.CanvasRenderer=function(){console.error("THREE.CanvasRenderer has been removed")},t.CanvasTexture=Ra,t.CatmullRomCurve3=bl,t.CineonToneMapping=3,t.CircleBufferGeometry=Pa,t.CircleGeometry=Pa,t.ClampToEdgeWrapping=u,t.Clock=bc,t.Color=tn,t.ColorKeyframeTrack=Jo,t.CompressedTexture=La,t.CompressedTextureLoader=class extends ol{constructor(t){super(t)}load(t,e,n,i){const r=this,s=[],a=new La,o=new cl(this.manager);o.setPath(this.path),o.setResponseType("arraybuffer"),o.setRequestHeader(this.requestHeader),o.setWithCredentials(r.withCredentials);let l=0;function c(c){o.load(t[c],(function(t){const n=r.parse(t,!0);s[c]={width:n.width,height:n.height,format:n.format,mipmaps:n.mipmaps},l+=1,6===l&&(1===n.mipmapCount&&(a.minFilter=g),a.image=s,a.format=n.format,a.needsUpdate=!0,e&&e(a))}),n,i)}if(Array.isArray(t))for(let e=0,n=t.length;e>16&32768,i=e>>12&2047;const r=e>>23&255;return r<103?n:r>142?(n|=31744,n|=(255==r?0:1)&&8388607&e,n):r<113?(i|=2048,n|=(i>>114-r)+(i>>113-r&1),n):(n|=r-112<<10|i>>1,n+=1&i,n)}},t.DecrementStencilOp=7683,t.DecrementWrapStencilOp=34056,t.DefaultLoadingManager=al,t.DepthFormat=A,t.DepthStencilFormat=L,t.DepthTexture=Ca,t.DirectionalLight=Kl,t.DirectionalLightHelper=class extends Ce{constructor(t,e,n){super(),this.light=t,this.light.updateMatrixWorld(),this.matrix=t.matrixWorld,this.matrixAutoUpdate=!1,this.color=n,void 0===e&&(e=1);let i=new En;i.setAttribute("position",new mn([-e,e,0,e,e,0,e,-e,0,-e,-e,0,-e,e,0],3));const r=new ca({fog:!1,toneMapped:!1});this.lightPlane=new fa(i,r),this.add(this.lightPlane),i=new En,i.setAttribute("position",new mn([0,0,0,0,0,1],3)),this.targetLine=new fa(i,r),this.add(this.targetLine),this.update()}dispose(){this.lightPlane.geometry.dispose(),this.lightPlane.material.dispose(),this.targetLine.geometry.dispose(),this.targetLine.material.dispose()}update(){gh.setFromMatrixPosition(this.light.matrixWorld),vh.setFromMatrixPosition(this.light.target.matrixWorld),yh.subVectors(vh,gh),this.lightPlane.lookAt(vh),void 0!==this.color?(this.lightPlane.material.color.set(this.color),this.targetLine.material.color.set(this.color)):(this.lightPlane.material.color.copy(this.light.color),this.targetLine.material.color.copy(this.light.color)),this.targetLine.lookAt(vh),this.targetLine.scale.z=yh.length()}},t.DiscreteInterpolant=Xo,t.DodecahedronBufferGeometry=Ba,t.DodecahedronGeometry=Ba,t.DoubleSide=2,t.DstAlphaFactor=206,t.DstColorFactor=208,t.DynamicBufferAttribute=function(t,e){return console.warn("THREE.DynamicBufferAttribute has been removed. Use new THREE.BufferAttribute().setUsage( THREE.DynamicDrawUsage ) instead."),new sn(t,e).setUsage(nt)},t.DynamicCopyUsage=35050,t.DynamicDrawUsage=nt,t.DynamicReadUsage=35049,t.EdgesGeometry=Ga,t.EdgesHelper=function(t,e){return console.warn("THREE.EdgesHelper has been removed. Use THREE.EdgesGeometry instead."),new ya(new Ga(t.geometry),new ca({color:void 0!==e?e:16777215}))},t.EllipseCurve=fl,t.EqualDepth=4,t.EqualStencilFunc=514,t.EquirectangularReflectionMapping=a,t.EquirectangularRefractionMapping=o,t.Euler=fe,t.EventDispatcher=rt,t.ExtrudeBufferGeometry=go,t.ExtrudeGeometry=go,t.FaceColors=1,t.FileLoader=cl,t.FlatShading=1,t.Float16BufferAttribute=pn,t.Float32Attribute=function(t,e){return console.warn("THREE.Float32Attribute has been removed. Use new THREE.Float32BufferAttribute() instead."),new mn(t,e)},t.Float32BufferAttribute=mn,t.Float64Attribute=function(t,e){return console.warn("THREE.Float64Attribute has been removed. Use new THREE.Float64BufferAttribute() instead."),new fn(t,e)},t.Float64BufferAttribute=fn,t.FloatType=b,t.Fog=Ss,t.FogExp2=Ms,t.Font=pc,t.FontLoader=class extends ol{constructor(t){super(t)}load(t,e,n,i){const r=this,s=new cl(this.manager);s.setPath(this.path),s.setRequestHeader(this.requestHeader),s.setWithCredentials(r.withCredentials),s.load(t,(function(t){let n;try{n=JSON.parse(t)}catch(e){console.warn("THREE.FontLoader: typeface.js support is being deprecated. Use typeface.json instead."),n=JSON.parse(t.substring(65,t.length-2))}const i=r.parse(n);e&&e(i)}),n,i)}parse(t){return new pc(t)}},t.FrontSide=0,t.Frustum=ai,t.GLBufferAttribute=Qc,t.GLSL1="100",t.GLSL3=it,t.GammaEncoding=Z,t.GreaterDepth=6,t.GreaterEqualDepth=5,t.GreaterEqualStencilFunc=518,t.GreaterStencilFunc=516,t.GridHelper=fh,t.Group=gs,t.HalfFloatType=M,t.HemisphereLight=Ol,t.HemisphereLightHelper=class extends Ce{constructor(t,e,n){super(),this.light=t,this.light.updateMatrixWorld(),this.matrix=t.matrixWorld,this.matrixAutoUpdate=!1,this.color=n;const i=new _o(e);i.rotateY(.5*Math.PI),this.material=new en({wireframe:!0,fog:!1,toneMapped:!1}),void 0===this.color&&(this.material.vertexColors=!0);const r=i.getAttribute("position"),s=new Float32Array(3*r.count);i.setAttribute("color",new sn(s,3)),this.add(new Wn(i,this.material)),this.update()}dispose(){this.children[0].geometry.dispose(),this.children[0].material.dispose()}update(){const t=this.children[0];if(void 0!==this.color)this.material.color.set(this.color);else{const e=t.geometry.getAttribute("color");ph.copy(this.light.color),mh.copy(this.light.groundColor);for(let t=0,n=e.count;t0){const n=new sl(e);r=new hl(n),r.setCrossOrigin(this.crossOrigin);for(let e=0,n=t.length;e\n\n\t\t\tvec3 getSample( float theta, vec3 axis ) {\n\n\t\t\t\tfloat cosTheta = cos( theta );\n\t\t\t\t// Rodrigues' axis-angle rotation\n\t\t\t\tvec3 sampleDirection = vOutputDirection * cosTheta\n\t\t\t\t\t+ cross( axis, vOutputDirection ) * sin( theta )\n\t\t\t\t\t+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );\n\n\t\t\t\treturn bilinearCubeUV( envMap, sampleDirection, mipInt );\n\n\t\t\t}\n\n\t\t\tvoid main() {\n\n\t\t\t\tvec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );\n\n\t\t\t\tif ( all( equal( axis, vec3( 0.0 ) ) ) ) {\n\n\t\t\t\t\taxis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );\n\n\t\t\t\t}\n\n\t\t\t\taxis = normalize( axis );\n\n\t\t\t\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t\t\t\tgl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );\n\n\t\t\t\tfor ( int i = 1; i < n; i++ ) {\n\n\t\t\t\t\tif ( i >= samples ) {\n\n\t\t\t\t\t\tbreak;\n\n\t\t\t\t\t}\n\n\t\t\t\t\tfloat theta = dTheta * float( i );\n\t\t\t\t\tgl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );\n\t\t\t\t\tgl_FragColor.rgb += weights[ i ] * getSample( theta, axis );\n\n\t\t\t\t}\n\n\t\t\t\tgl_FragColor = linearToOutputTexel( gl_FragColor );\n\n\t\t\t}\n\t\t`,blending:0,depthTest:!1,depthWrite:!1})}(Ih),this._equirectShader=null,this._cubemapShader=null,this._compileMaterial(this._blurMaterial)}fromScene(t,e=0,n=.1,i=100){kh=this._renderer.getRenderTarget();const r=this._allocateTargets();return this._sceneToCubeUV(t,n,i,r),e>0&&this._blur(r,0,0,e),this._applyPMREM(r),this._cleanup(r),r}fromEquirectangular(t){return this._fromTexture(t)}fromCubemap(t){return this._fromTexture(t)}compileCubemapShader(){null===this._cubemapShader&&(this._cubemapShader=Kh(),this._compileMaterial(this._cubemapShader))}compileEquirectangularShader(){null===this._equirectShader&&(this._equirectShader=Qh(),this._compileMaterial(this._equirectShader))}dispose(){this._blurMaterial.dispose(),null!==this._cubemapShader&&this._cubemapShader.dispose(),null!==this._equirectShader&&this._equirectShader.dispose();for(let t=0;t2?Ch:0,Ch,Ch),o.setRenderTarget(i),u&&o.render(zh,r),o.render(t,r)}o.toneMapping=h,o.outputEncoding=c,o.autoClear=l}_textureToCubeUV(t,e){const n=this._renderer;t.isCubeTexture?null==this._cubemapShader&&(this._cubemapShader=Kh()):null==this._equirectShader&&(this._equirectShader=Qh());const i=t.isCubeTexture?this._cubemapShader:this._equirectShader,r=new Wn(Oh[0],i),s=i.uniforms;s.envMap.value=t,t.isCubeTexture||s.texelSize.value.set(1/t.image.width,1/t.image.height),s.inputEncoding.value=Nh[t.encoding],s.outputEncoding.value=Nh[e.texture.encoding],Jh(e,0,0,3*Ch,2*Ch),n.setRenderTarget(e),n.render(r,Fh)}_applyPMREM(t){const e=this._renderer,n=e.autoClear;e.autoClear=!1;for(let e=1;eIh&&console.warn(`sigmaRadians, ${r}, is too large and will clip, as it requested ${m} samples when the maximum is set to 20`);const f=[];let g=0;for(let t=0;t4?i-8+4:0),3*v,2*v),o.setRenderTarget(e),o.render(c,Fh)}},t.ParametricBufferGeometry=wo,t.ParametricGeometry=wo,t.Particle=function(t){return console.warn("THREE.Particle has been renamed to THREE.Sprite."),new Vs(t)},t.ParticleBasicMaterial=function(t){return console.warn("THREE.ParticleBasicMaterial has been renamed to THREE.PointsMaterial."),new _a(t)},t.ParticleSystem=function(t,e){return console.warn("THREE.ParticleSystem has been renamed to THREE.Points."),new Ta(t,e)},t.ParticleSystemMaterial=function(t){return console.warn("THREE.ParticleSystemMaterial has been renamed to THREE.PointsMaterial."),new _a(t)},t.Path=Bl,t.PerspectiveCamera=Kn,t.Plane=Ne,t.PlaneBufferGeometry=ci,t.PlaneGeometry=ci,t.PlaneHelper=class extends fa{constructor(t,e=1,n=16776960){const i=n,r=new En;r.setAttribute("position",new mn([1,-1,1,-1,1,1,-1,-1,1,1,1,1,-1,1,1,-1,-1,1,1,-1,1,1,1,1,0,0,1,0,0,0],3)),r.computeBoundingSphere(),super(r,new ca({color:i,toneMapped:!1})),this.type="PlaneHelper",this.plane=t,this.size=e;const s=new En;s.setAttribute("position",new mn([1,1,1,-1,1,1,-1,-1,1,1,1,1,-1,-1,1,1,-1,1],3)),s.computeBoundingSphere(),this.add(new Wn(s,new en({color:i,opacity:.2,transparent:!0,depthWrite:!1,toneMapped:!1})))}updateMatrixWorld(t){let e=-this.plane.constant;Math.abs(e)<1e-8&&(e=1e-8),this.scale.set(.5*this.size,.5*this.size,e),this.children[0].material.side=e<0?1:0,this.lookAt(this.plane.normal),super.updateMatrixWorld(t)}},t.PointCloud=function(t,e){return console.warn("THREE.PointCloud has been renamed to THREE.Points."),new Ta(t,e)},t.PointCloudMaterial=function(t){return console.warn("THREE.PointCloudMaterial has been renamed to THREE.PointsMaterial."),new _a(t)},t.PointLight=Zl,t.PointLightHelper=class extends Wn{constructor(t,e,n){super(new So(e,4,2),new en({wireframe:!0,fog:!1,toneMapped:!1})),this.light=t,this.light.updateMatrixWorld(),this.color=n,this.type="PointLightHelper",this.matrix=this.light.matrixWorld,this.matrixAutoUpdate=!1,this.update()}dispose(){this.geometry.dispose(),this.material.dispose()}update(){void 0!==this.color?this.material.color.set(this.color):this.material.color.copy(this.light.color)}},t.Points=Ta,t.PointsMaterial=_a,t.PolarGridHelper=class extends ya{constructor(t=10,e=16,n=8,i=64,r=4473924,s=8947848){r=new tn(r),s=new tn(s);const a=[],o=[];for(let n=0;n<=e;n++){const i=n/e*(2*Math.PI),l=Math.sin(i)*t,c=Math.cos(i)*t;a.push(0,0,0),a.push(l,0,c);const h=1&n?r:s;o.push(h.r,h.g,h.b),o.push(h.r,h.g,h.b)}for(let e=0;e<=n;e++){const l=1&e?r:s,c=t-t/n*e;for(let t=0;t + + + + +Hierarchical Fracture Lab — generative design & fracture discovery platform + + diff --git a/data/Run 1/RESULT Run 1/app/src/ui/02_body.html b/data/Run 1/RESULT Run 1/app/src/ui/02_body.html new file mode 100644 index 0000000000000000000000000000000000000000..dd0e8906ac694f50dc7cf7947b43b71efd78acf6 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/ui/02_body.html @@ -0,0 +1,140 @@ + +
+

Hierarchical Fracture Lab

+ core v · build __BUILD_STAMP__ + + + + + + + + + ready +
+
+
+
+ 1 · Reference interpretation images → design principles +
+
+
Inferred structural hierarchy of the current design
+ +
+
Adopted interpretation (editable; the PARAMETER MAPPING block is parsed)
+ +
+ + +
+
The images are treated as inspiration for one coherent material concept, not as registered views of one object. Alternative interpretations and the reasons for the adopted one are recorded in the text.
+
+
+
+ 2 · Geometry generation +
+
+
+ 3 · Mechanics & fracture material · interfaces · failure +
+
+
+ 4 · Loading & numerics displacement control +
+
+
+ 5 · Physical units normalised → SI +
+
The solver works in normalised units (length = specimen width W, modulus = Es, out-of-plane depth = 1). Enter physical values to convert displayed results; the mechanics are unchanged.
+
+
+
+ 6 · Physics model equations · assumptions · BCs +
+
+
+ 7 · Validation not run +
+
≈ 1–3 s; analytical references, invariances, conservation checks, step-size and export consistency.
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+
+
+
+
+ 8 · Design comparison 0 designs +
+
Store runs at controlled total material to compare stiffness, peak force, work to failure and fracture mode. Curves are overlaid in the F–d plot.
+
+
+
+
+
+ 9 · Export data · geometry · media +
+
Results & metadata
+
+ + + + + + +
+
Geometry & manufacturing
+
+
+
+
+
+
+
+
Media
+
+
+
+
+
+
+
+ + + + + + + + + +
+
—
+
utilisation ε/εc
+
Replay—
+
+ +
+ diff --git a/data/Run 1/RESULT Run 1/app/src/ui/02_viewer.js b/data/Run 1/RESULT Run 1/app/src/ui/02_viewer.js new file mode 100644 index 0000000000000000000000000000000000000000..b7d262d676df9871534c6a5a4ac06ec80710c9f5 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/ui/02_viewer.js @@ -0,0 +1,121 @@ +/* =================================================================================== + Viewer: Three.js rendering of the beam network (2-D quads or extruded 3-D plate), + colour maps, deformation, orbit/pan/zoom controls, standard views, screenshots. + =================================================================================== */ +const Viewer = (function () { + let renderer, scene, camera, controls, container, structure = null; + let mesh = null, geom = null, nodeMesh = null, gripMesh = null; + let colorMode = 'util', failedMode = 'ghost', deformScale = 1, extrude = false, showNodes = false; + let cur = { u: null, util: null, N: null, state: null, failOrder: null, nFailed: 0 }; + let depthZ = 0.03, needsRender = true; + function init(el) { + container = el; + renderer = new THREE.WebGLRenderer({ antialias: true, preserveDrawingBuffer: true, alpha: false }); + renderer.setPixelRatio(Math.min(window.devicePixelRatio || 1, 2)); + renderer.setClearColor(0x0f1218, 1); + el.appendChild(renderer.domElement); + scene = new THREE.Scene(); + camera = new THREE.PerspectiveCamera(35, 1, 0.001, 100); + camera.position.set(0.5, 0.5, 2.6); camera.up.set(0, 1, 0); + controls = new THREE.OrbitControls(camera, renderer.domElement); + controls.target.set(0.5, 0.5, 0); controls.enableDamping = true; controls.dampingFactor = 0.12; controls.screenSpacePanning = true; + controls.mouseButtons = { LEFT: THREE.MOUSE.ROTATE, MIDDLE: THREE.MOUSE.DOLLY, RIGHT: THREE.MOUSE.PAN }; + controls.addEventListener('change', () => { needsRender = true; }); + scene.add(new THREE.AmbientLight(0xffffff, 0.75)); + const dl = new THREE.DirectionalLight(0xffffff, 0.7); dl.position.set(1, 1.5, 2.5); scene.add(dl); + const dl2 = new THREE.DirectionalLight(0xffffff, 0.3); dl2.position.set(-1, -0.5, 1.5); scene.add(dl2); + window.addEventListener('resize', resize); resize(); + animate(); + } + function resize() { + if (!container) return; const w = container.clientWidth || 600, h = container.clientHeight || 600; + renderer.setSize(w, h, false); renderer.domElement.style.width = w + 'px'; renderer.domElement.style.height = h + 'px'; + camera.aspect = w / h; camera.updateProjectionMatrix(); needsRender = true; + } + function animate() { requestAnimationFrame(animate); controls.update(); if (needsRender) { renderer.render(scene, camera); needsRender = false; } } + function render() { renderer.render(scene, camera); } + function dispose() { if (mesh) { scene.remove(mesh); mesh.geometry.dispose(); mesh.material.dispose(); mesh = null; } if (nodeMesh) { scene.remove(nodeMesh); nodeMesh.geometry.dispose(); nodeMesh = null; } if (gripMesh) { scene.remove(gripMesh); gripMesh.geometry.dispose(); gripMesh = null; } } + function setStructure(st) { + structure = st; cur = { u: null, util: null, N: null, state: null, failOrder: null, nFailed: 0 }; + buildMesh(); view('fit'); + } + function buildMesh() { + dispose(); if (!structure) return; + const els = structure.elements; const nEl = els.length; + const vPer = extrude ? 8 : 4, iPer = extrude ? 36 : 6; + const pos = new Float32Array(nEl * vPer * 3), col = new Float32Array(nEl * vPer * 3), idx = new Uint32Array(nEl * iPer); + for (let i = 0; i < nEl; i++) { + const b = i * vPer; + if (!extrude) { const k = i * 6; idx[k] = b; idx[k + 1] = b + 1; idx[k + 2] = b + 2; idx[k + 3] = b; idx[k + 4] = b + 2; idx[k + 5] = b + 3; } + else { // box: bottom 0-3, top 4-7 + const faces = [[4, 5, 6, 7], [3, 2, 1, 0], [0, 1, 5, 4], [1, 2, 6, 5], [2, 3, 7, 6], [3, 0, 4, 7]]; let k = i * 36; + for (const f of faces) { idx[k++] = b + f[0]; idx[k++] = b + f[1]; idx[k++] = b + f[2]; idx[k++] = b + f[0]; idx[k++] = b + f[2]; idx[k++] = b + f[3]; } + } + } + geom = new THREE.BufferGeometry(); + geom.setAttribute('position', new THREE.BufferAttribute(pos, 3)); geom.setAttribute('color', new THREE.BufferAttribute(col, 3)); geom.setIndex(new THREE.BufferAttribute(idx, 1)); + const mat = extrude ? new THREE.MeshLambertMaterial({ vertexColors: true, side: THREE.DoubleSide }) : new THREE.MeshBasicMaterial({ vertexColors: true, side: THREE.DoubleSide }); + mesh = new THREE.Mesh(geom, mat); scene.add(mesh); + // grip lines + const gg = new THREE.BufferGeometry(); const W = structure.W, H = structure.H; + gg.setAttribute('position', new THREE.BufferAttribute(new Float32Array([-0.03 * W, 0, 0.001, 1.03 * W, 0, 0.001, -0.03 * W, H, 0.001, 1.03 * W, H, 0.001]), 3)); + gripMesh = new THREE.LineSegments(gg, new THREE.LineBasicMaterial({ color: 0x8892a6 })); scene.add(gripMesh); + // nodes + const np = new Float32Array(structure.nodes.length * 3); structure.nodes.forEach((n, i) => { np[3 * i] = n.x; np[3 * i + 1] = n.y; np[3 * i + 2] = 0.002; }); + const ng = new THREE.BufferGeometry(); ng.setAttribute('position', new THREE.BufferAttribute(np, 3)); + nodeMesh = new THREE.Points(ng, new THREE.PointsMaterial({ color: 0xffffff, size: 3, sizeAttenuation: false })); nodeMesh.visible = showNodes; scene.add(nodeMesh); + updateGeometry(); updateColors(); + } + function updateGeometry() { + if (!mesh || !structure) return; + const els = structure.elements, nodes = structure.nodes, pos = geom.attributes.position.array, u = cur.u, s = deformScale; + const vPer = extrude ? 8 : 4; const Z = extrude ? depthZ * structure.W : 0; + for (let i = 0; i < els.length; i++) { + const e = els[i]; const A = nodes[e.n1], B = nodes[e.n2]; + let x1 = A.x, y1 = A.y, x2 = B.x, y2 = B.y; + if (u) { x1 += s * u[3 * e.n1]; y1 += s * u[3 * e.n1 + 1]; x2 += s * u[3 * e.n2]; y2 += s * u[3 * e.n2 + 1]; } + const dx = x2 - x1, dy = y2 - y1, L = Math.hypot(dx, dy) || 1e-12; const hw = 0.5 * e.t; const nx = -dy / L * hw, ny = dx / L * hw; + const hidden = e.absent || (cur.state && cur.state[i] === 2 && failedMode === 'hide'); + const q = hidden ? [[x1, y1], [x1, y1], [x1, y1], [x1, y1]] : [[x1 + nx, y1 + ny], [x2 + nx, y2 + ny], [x2 - nx, y2 - ny], [x1 - nx, y1 - ny]]; + const b = i * vPer * 3; + if (!extrude) { for (let k = 0; k < 4; k++) { pos[b + 3 * k] = q[k][0]; pos[b + 3 * k + 1] = q[k][1]; pos[b + 3 * k + 2] = 0.0002 * e.level; } } + else { for (let k = 0; k < 4; k++) { pos[b + 3 * k] = q[k][0]; pos[b + 3 * k + 1] = q[k][1]; pos[b + 3 * k + 2] = 0; pos[b + 12 + 3 * k] = q[k][0]; pos[b + 12 + 3 * k + 1] = q[k][1]; pos[b + 12 + 3 * k + 2] = Z; } } + } + geom.attributes.position.needsUpdate = true; geom.computeBoundingSphere(); if (extrude) geom.computeVertexNormals(); + if (nodeMesh && u) { const np = nodeMesh.geometry.attributes.position.array; nodes.forEach((n, i) => { np[3 * i] = n.x + s * u[3 * i]; np[3 * i + 1] = n.y + s * u[3 * i + 1]; }); nodeMesh.geometry.attributes.position.needsUpdate = true; } + needsRender = true; + } + function updateColors() { + if (!mesh || !structure) return; + const els = structure.elements, col = geom.attributes.color.array; const vPer = extrude ? 8 : 4; + let Nmax = 0, dispMax = 0; const disp = new Float32Array(els.length); + if (cur.N) for (let i = 0; i < els.length; i++) Nmax = Math.max(Nmax, Math.abs(cur.N[i])); + if (cur.u) for (let i = 0; i < els.length; i++) { const e = els[i]; const d = 0.5 * (Math.hypot(cur.u[3 * e.n1], cur.u[3 * e.n1 + 1]) + Math.hypot(cur.u[3 * e.n2], cur.u[3 * e.n2 + 1])); disp[i] = d; if (d > dispMax) dispMax = d; } + const data = { state: cur.state, util: cur.util, N: cur.N, Nmax: Nmax, disp: disp, dispMax: dispMax, failOrder: cur.failOrder, nFailed: cur.nFailed, tMin: structure.stats.tMin, tMax: structure.stats.tMax }; + for (let i = 0; i < els.length; i++) { + let c = HFX.elementColor(colorMode, els[i], i, data); + if (cur.state && cur.state[i] === 2 && failedMode === 'ghost' && colorMode !== 'failOrder') c = [70, 74, 84]; + const r = c[0] / 255, g = c[1] / 255, b = c[2] / 255; const base = i * vPer * 3; + for (let k = 0; k < vPer; k++) { col[base + 3 * k] = r; col[base + 3 * k + 1] = g; col[base + 3 * k + 2] = b; } + } + geom.attributes.color.needsUpdate = true; needsRender = true; + } + function setDeformation(u, util, N, st) { cur.u = u; cur.util = util; cur.N = N; cur.state = st; updateGeometry(); updateColors(); } + function setFailOrder(fo, n) { cur.failOrder = fo; cur.nFailed = n; updateColors(); } + function setColorMode(m) { colorMode = m; updateColors(); } + function setFailedMode(m) { failedMode = m; updateGeometry(); updateColors(); } + function setDeformScale(s) { deformScale = s; updateGeometry(); } + function setExtrude(b) { extrude = b; buildMesh(); } + function setShowNodes(b) { showNodes = b; if (nodeMesh) nodeMesh.visible = b; needsRender = true; } + function view(kind) { + if (!structure) return; const W = structure.W, H = structure.H; const cx = W / 2, cy = H / 2; + const fov = camera.fov * Math.PI / 180; const size = Math.max(W, H / camera.aspect) * 1.12; const dist = (size / 2) / Math.tan(fov / 2); + controls.target.set(cx, cy, 0); + if (kind === 'iso') camera.position.set(cx + 0.7 * dist, cy - 0.6 * dist, 0.65 * dist); + else if (kind === 'fit') { const dir = camera.position.clone().sub(controls.target).normalize(); if (dir.length() === 0) dir.set(0, 0, 1); camera.position.copy(controls.target.clone().add(dir.multiplyScalar(dist))); } + else camera.position.set(cx, cy, dist); + camera.up.set(0, 1, 0); camera.lookAt(controls.target); controls.update(); needsRender = true; + } + function screenshot() { renderer.render(scene, camera); return renderer.domElement.toDataURL('image/png'); } + return { init, setStructure, setDeformation, setFailOrder, setColorMode, setFailedMode, setDeformScale, setExtrude, setShowNodes, view, screenshot, render, canvas: () => renderer.domElement, resize }; +})(); diff --git a/data/Run 1/RESULT Run 1/app/src/ui/03_app.js b/data/Run 1/RESULT Run 1/app/src/ui/03_app.js new file mode 100644 index 0000000000000000000000000000000000000000..d44fc350078aae85e70d165fbe70756323b73bd8 --- /dev/null +++ b/data/Run 1/RESULT Run 1/app/src/ui/03_app.js @@ -0,0 +1,619 @@ +/* =================================================================================== + Hierarchical Fracture Lab — application logic (main thread) + The mechanics core (HFX) is included above as