#!/usr/bin/env python3
"""Validation & Diagnostic Visualization for Medicine Quality Control Laboratories Dataset."""

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os

SCENARIOS = ['who_prequalified_lab', 'national_reference_lab', 'district_basic_lab']


def load_scenarios(data_dir='data'):
    dfs = {}
    for sc in SCENARIOS:
        path = os.path.join(data_dir, f'qc_lab_{sc}.csv')
        if os.path.exists(path):
            dfs[sc] = pd.read_csv(path)
    return dfs


def make_report(dfs, output='validation_report.png'):
    fig, axes = plt.subplots(4, 2, figsize=(16, 24))
    fig.suptitle(
        'Medicine Quality Control Laboratories — Validation Report\n'
        '(WHO-PQ Lab → National Reference → District Basic)',
        fontsize=15, fontweight='bold', y=0.99)
    colors = ['#2ecc71', '#f39c12', '#e74c3c']
    x = np.arange(len(SCENARIOS))
    labels = ['WHO-PQ', 'National Ref', 'District']

    ax = axes[0, 0]
    staff = [dfs[sc]['staff_analysts'].mean() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, staff, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(staff):
        ax.text(i, v+0.3, f'{v:.0f}', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Staff'); ax.set_title('Average Analyst Staff')

    ax = axes[0, 1]
    equip = [dfs[sc]['equipment_functional_pct'].mean() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, equip, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(equip):
        ax.text(i, v+1, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Rate (%)'); ax.set_title('Equipment Functional Rate')

    ax = axes[1, 0]
    samp = [dfs[sc]['samples_tested_per_year'].mean() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, samp, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(samp):
        ax.text(i, v+30, f'{v:.0f}', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Samples/Year'); ax.set_title('Annual Testing Volume')

    ax = axes[1, 1]
    prof = []
    for sc in SCENARIOS:
        if sc in dfs:
            enrolled = dfs[sc][dfs[sc]['proficiency_testing_enrolled']==1]
            prof.append(enrolled['proficiency_testing_pass_rate'].mean() if len(enrolled) > 0 else 0)
    ax.bar(x, prof, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(prof):
        ax.text(i, v+1, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Pass Rate (%)'); ax.set_title('Proficiency Testing Pass Rate')

    ax = axes[2, 0]
    tat = [dfs[sc]['turnaround_days_median'].median() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, tat, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(tat):
        ax.text(i, v+0.5, f'{v:.0f}d', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Days'); ax.set_title('Median Turnaround Time')

    ax = axes[2, 1]
    budget = [dfs[sc]['annual_budget_usd'].mean()/1000 for sc in SCENARIOS if sc in dfs]
    ax.bar(x, budget, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(budget):
        ax.text(i, v+5, f'${v:.0f}K', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Budget (USD K)'); ax.set_title('Average Annual Budget')

    ax = axes[3, 0]
    sf = [dfs[sc]['sf_detection_rate_pct'].mean() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, sf, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(sf):
        ax.text(i, v+0.5, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('SF Rate (%)'); ax.set_title('SF Detection Rate')

    ax = axes[3, 1]
    stockout = [dfs[sc]['reagent_stockout_days_per_year'].mean() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, stockout, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(stockout):
        ax.text(i, v+0.5, f'{v:.0f}d', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Days/Year'); ax.set_title('Reagent Stockout Days')

    plt.tight_layout(rect=[0, 0, 1, 0.97])
    plt.savefig(output, dpi=150, bbox_inches='tight')
    print(f'Saved validation report to {output}')
    plt.close()


if __name__ == '__main__':
    dfs = load_scenarios()
    if dfs:
        make_report(dfs)