#!/usr/bin/env python3
"""Validation & Diagnostic Visualization for Obstetric Fistula Dataset."""

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

SCENARIOS = ['specialized_fistula_centre', 'district_hospital', 'no_surgical_access']


def load_scenarios(data_dir='data'):
    dfs = {}
    for sc in SCENARIOS:
        path = os.path.join(data_dir, f'fistula_{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, 22))
    fig.suptitle('Obstetric Fistula — Validation Report',
                 fontsize=16, fontweight='bold', y=0.98)
    df = dfs.get('district_hospital', list(dfs.values())[0])
    colors = ['#2ecc71', '#f39c12', '#e74c3c']

    ax = axes[0, 0]
    x = np.arange(len(SCENARIOS))
    repair = [dfs[sc]['repair_performed'].mean()*100 for sc in SCENARIOS if sc in dfs]
    success = []
    for sc in SCENARIOS:
        if sc in dfs:
            d = dfs[sc]
            rep = d[d['repair_performed'] == 1]
            success.append(rep['repair_successful'].mean()*100 if len(rep) > 0 else 0)
    w = 0.3
    ax.bar(x - w/2, repair, w, label='Repair Performed', color='#3498db', alpha=0.8)
    ax.bar(x + w/2, success, w, label='Repair Success', color='#2ecc71', alpha=0.8)
    ax.set_xticks(x)
    ax.set_xticklabels(['Specialist', 'District', 'No Access'], fontsize=9)
    ax.set_ylabel('Rate (%)')
    ax.set_title('Repair Access & Success (85-90% at specialist)')
    ax.legend(fontsize=8)

    ax = axes[0, 1]
    ft = df['fistula_type'].value_counts()
    c_colors = ['#e74c3c', '#f39c12', '#9b59b6']
    ax.pie(ft.values,
           labels=[s.replace('_', ' ').upper() for s in ft.index],
           autopct='%1.0f%%', colors=c_colors[:len(ft)],
           startangle=90, textprops={'fontsize': 9})
    ax.set_title('Fistula Type (VVF = 80%)')

    ax = axes[1, 0]
    social = ['divorced_separated', 'social_isolation', 'depression',
              'unable_to_work', 'skin_excoriation', 'malodour']
    s_labels = ['Divorced', 'Isolated', 'Depression', 'Unable Work', 'Excoriation', 'Malodour']
    vals = [df[s].mean()*100 for s in social]
    ax.barh(range(6), vals, color='#9b59b6', alpha=0.7)
    ax.set_yticks(range(6))
    ax.set_yticklabels(s_labels, fontsize=9)
    for i, v in enumerate(vals):
        ax.text(v + 0.5, i, f'{v:.0f}%', va='center', fontsize=9)
    ax.set_xlabel('Prevalence (%)')
    ax.set_title('Social Consequences (devastating)')

    ax = axes[1, 1]
    ax.hist(df['years_living_with_fistula'], bins=20, color='#e74c3c',
            alpha=0.7, edgecolor='white')
    ax.set_xlabel('Years Living with Fistula')
    ax.set_title('Duration Before Presentation')

    ax = axes[2, 0]
    risks = ['child_marriage', 'short_stature', 'prolonged_labour',
             'obstructed_labour', 'stillbirth']
    r_labels = ['Child Marriage', 'Short Stature', 'Prolonged Labour',
                'Obstructed Labour', 'Stillbirth']
    vals = [df[r].mean()*100 for r in risks]
    ax.bar(range(5), vals, color=['#e74c3c', '#f39c12', '#9b59b6', '#3498db', '#e67e22'], alpha=0.8)
    ax.set_xticks(range(5))
    ax.set_xticklabels(r_labels, fontsize=7, rotation=15)
    for i, v in enumerate(vals):
        ax.text(i, v + 0.5, f'{v:.0f}%', ha='center', fontsize=8)
    ax.set_ylabel('Prevalence (%)')
    ax.set_title('Risk Factors (obstructed labour = key cause)')

    ax = axes[2, 1]
    barriers = df[df['barrier_to_care'] != 'none']['barrier_to_care'].value_counts()
    if len(barriers) > 0:
        ax.barh(range(len(barriers)), barriers.values, color='#3498db', alpha=0.8)
        ax.set_yticks(range(len(barriers)))
        ax.set_yticklabels([s.replace('_', ' ').title() for s in barriers.index], fontsize=9)
    ax.set_xlabel('Count')
    ax.set_title('Barriers to Care')

    ax = axes[3, 0]
    sizes = ['small', 'medium', 'large', 'extensive']
    rep_d = df[df['repair_performed'] == 1]
    if len(rep_d) > 0:
        size_success = []
        for sz in sizes:
            sz_d = rep_d[rep_d['fistula_size'] == sz]
            size_success.append(sz_d['repair_successful'].mean()*100 if len(sz_d) > 0 else 0)
        ax.bar(range(4), size_success,
               color=['#2ecc71', '#f39c12', '#e74c3c', '#9b59b6'], alpha=0.8)
        ax.set_xticks(range(4))
        ax.set_xticklabels(sizes, fontsize=9)
        for i, v in enumerate(size_success):
            ax.text(i, v + 1, f'{v:.0f}%', ha='center', fontsize=9)
    ax.set_ylabel('Success Rate (%)')
    ax.set_title('Repair Success by Fistula Size')

    ax = axes[3, 1]
    ax.hist(df['age_at_fistula_onset'], bins=20, color='#f39c12',
            alpha=0.7, edgecolor='white', label='Onset')
    ax.hist(df['age_at_presentation'], bins=20, color='#3498db',
            alpha=0.5, edgecolor='white', label='Presentation')
    ax.set_xlabel('Age (years)')
    ax.set_title('Age at Onset vs Presentation')
    ax.legend(fontsize=8)

    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)