import sys
sys.stdout.reconfigure(encoding='utf-8')
import pandas as pd
import numpy as np
import openpyxl
from openpyxl.utils.dataframe import dataframe_to_rows
from openpyxl.styles import Font, Alignment
import os
import shutil

base_dir = r'c:\Users\NASPC\Documents\Du án tại SG tháng 8'
orig_file = os.path.join(base_dir, 'KẾT QUẢ PHÂN TÍCH.xlsx')
final_file = os.path.join(base_dir, 'Project_Code_and_Results', 'KẾT_QUẢ_PHÂN_TÍCH_MASTER.xlsx')

# Copy original to new file
shutil.copy(orig_file, final_file)

# Load workbook
wb = openpyxl.load_workbook(final_file)

# Helper to process CSV into JASP layout dataframe
def get_jasp_df(filepath, model_name="M₁"):
    df = pd.read_csv(filepath, index_col=0)
    se_col = 'S.E.' if 'S.E.' in df.columns else ('std err' if 'std err' in df.columns else 'SE')
    
    estimate = df['Beta (B)']
    se = df[se_col]
    odds_ratio = df['Odds Ratio EXP(B)']
    p_val = df['P-value']
    
    z_stat = estimate / se
    wald = z_stat ** 2
    lower = np.exp(estimate - 1.96 * se)
    upper = np.exp(estimate + 1.96 * se)
    
    def map_name(name):
        if name == 'const': return '(Intercept)'
        if '_' in name:
            parts = name.split('_')
            return f"{parts[0]} ({parts[1]})"
        return name
    
    new_index = [map_name(str(i)) for i in df.index]
    
    out_df = pd.DataFrame({
        'Model': [model_name] + [np.nan] * (len(df) - 1),
        '': new_index,
        'Estimate': estimate.values,
        'Standard Error': se.values,
        'Odds Ratio': odds_ratio.values,
        'z': z_stat.values,
        'Wald Statistic': wald.values,
        'df': [1] * len(df),
        'p': p_val.values,
        'Lower bound': lower.values,
        'Upper bound': upper.values
    })
    
    # Format
    out_df['p'] = out_df['p'].apply(lambda x: '< .00001' if pd.notnull(x) and x < 0.00001 else (round(x, 5) if pd.notnull(x) else x))
    out_df = out_df.round(5)
    return out_df

# Replace a sheet's content
def replace_sheet(sheet_name, csv_path):
    idx = wb.sheetnames.index(sheet_name)
    del wb[sheet_name]
    ws = wb.create_sheet(sheet_name, idx)
            
    # Write Title
    ws.cell(row=1, column=1, value="Logistic Regression (Updated with Firth/Optimized)").font = Font(bold=True)
    ws.cell(row=3, column=1, value="Coefficients").font = Font(bold=True)
    
    # Headers
    df_jasp = get_jasp_df(csv_path)
    headers = list(df_jasp.columns)
    
    for c_idx, col_name in enumerate(headers, 1):
        cell = ws.cell(row=4, column=c_idx, value=col_name)
        cell.font = Font(bold=True)
        cell.alignment = Alignment(horizontal='center')
        
    ws.cell(row=3, column=10, value="95% Confidence interval").font = Font(bold=True)
    ws.cell(row=3, column=10).alignment = Alignment(horizontal='center')
    
    # Write Data
    for r_idx, row in enumerate(dataframe_to_rows(df_jasp, index=False, header=False), 5):
        for c_idx, value in enumerate(row, 1):
            # Check for NaN float
            if isinstance(value, float) and np.isnan(value):
                ws.cell(row=r_idx, column=c_idx, value="")
            else:
                ws.cell(row=r_idx, column=c_idx, value=value)

path_don = os.path.join(base_dir, 'Project_Code_and_Results', '4_Logistic_Regression', 'Logistic_Results_Donation_Firth.csv')
path_dec = os.path.join(base_dir, 'Project_Code_and_Results', '4_Logistic_Regression', 'Logistic_Results_Decision_Final.csv')

replace_sheet('Donation', path_don)
replace_sheet('Decision', path_dec)

wb.save(final_file)
print("Tạo thành công MASTER file!")