#!/usr/bin/env python3
"""Validation & Diagnostic Visualization for Laboratory Reagent Supply Dataset."""

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

SCENARIOS = ['reference_laboratory', 'district_laboratory', 'health_centre_lab']


def load_scenarios(data_dir='data'):
    dfs = {}
    for sc in SCENARIOS:
        path = os.path.join(data_dir, f'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(
        'Laboratory Reagent Supply — Validation Report\n'
        '(Reference Lab → District Lab → Health Centre)',
        fontsize=15, fontweight='bold', y=0.99)
    colors = ['#2ecc71', '#f39c12', '#e74c3c']
    x = np.arange(len(SCENARIOS))
    labels = ['Reference Lab', 'District Lab', 'Health Centre']

    ax = axes[0, 0]
    avail = [dfs[sc]['available_on_survey_day'].mean()*100 for sc in SCENARIOS if sc in dfs]
    ax.bar(x, avail, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(avail):
        ax.text(i, v+1, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Availability (%)'); ax.set_title('Reagent Availability'); ax.set_ylim(0,100)

    ax = axes[0, 1]
    df = dfs.get('district_laboratory', list(dfs.values())[0])
    dept = df.groupby('department')['available_on_survey_day'].mean().sort_values()
    ax.barh(range(len(dept)), dept.values*100, color='#3498db', alpha=0.7)
    ax.set_yticks(range(len(dept)))
    ax.set_yticklabels([s.replace('_',' ').title() for s in dept.index], fontsize=7)
    ax.set_xlabel('Availability (%)'); ax.set_title('Availability by Department (District)')

    ax = axes[1, 0]
    so = [dfs[sc]['stocked_out_in_last_6m'].mean()*100 for sc in SCENARIOS if sc in dfs]
    ax.bar(x, so, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(so):
        ax.text(i, v+1, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Rate (%)'); ax.set_title('Stocked Out ≥1x in Last 6 Months')

    ax = axes[1, 1]
    eq = [dfs[sc]['equipment_functional'].mean()*100 for sc in SCENARIOS if sc in dfs]
    ax.bar(x, eq, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(eq):
        ax.text(i, v+1, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Rate (%)'); ax.set_title('Equipment Functional')

    ax = axes[2, 0]
    so_df = df[df['stocked_out_in_last_6m']==1]
    if len(so_df)>0:
        causes = so_df['stockout_cause'].value_counts().head(8)
        ax.barh(range(len(causes)), causes.values, color='#e74c3c', alpha=0.7)
        ax.set_yticks(range(len(causes)))
        ax.set_yticklabels([s.replace('_',' ').title() for s in causes.index], fontsize=7)
        ax.set_xlabel('Count')
    ax.set_title('Top Stockout Causes (District)')

    ax = axes[2, 1]
    tests_missed = [dfs[sc]['tests_not_done_no_reagent'].mean() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, tests_missed, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(tests_missed):
        ax.text(i, v+0.2, f'{v:.1f}', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Mean Tests Missed'); ax.set_title('Tests Not Done Due to Reagent Stockout')

    ax = axes[3, 0]
    expired = [dfs[sc]['expired_reagent_found'].mean()*100 for sc in SCENARIOS if sc in dfs]
    ax.bar(x, expired, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(expired):
        ax.text(i, v+0.5, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Rate (%)'); ax.set_title('Expired Reagents Found on Shelf')

    ax = axes[3, 1]
    ofr = [dfs[sc]['order_fill_rate_pct'].mean() for sc in SCENARIOS if sc in dfs]
    ax.bar(x, ofr, color=colors, alpha=0.8)
    ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=9)
    for i, v in enumerate(ofr):
        ax.text(i, v+1, f'{v:.0f}%', ha='center', fontsize=10, fontweight='bold')
    ax.set_ylabel('Fill Rate (%)'); ax.set_title('Order Fill Rate')

    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)