import os
import re

import pandas as pd

measure_dir = (
    r"\\gabor\Project\内科\舌診\TIAS\開発\カラーチャート\TCC2025-01\退色調査3 マットフォト" + "\\"
)
target_lab_csv = (
    r"\\gabor\Project\内科\舌診\TIAS\開発\カラーチャート\TCC2025-01\色調整\Target_Lab.csv"
)
tcc_lab = []


def read_data():
    """Read data files and check for required columns."""

    global tcc_lab
    kinds = ["tcc1", "tcc2", "tcc3", "tcc4", "tcc5", "tcc6"]
    for i in range(24):
        tcc_lab.append([])

    target_lab = pd.read_csv(target_lab_csv, encoding="utf-8", header=None)

    files = []
    for kind in kinds:
        csv_files = [
            f for f in os.listdir(measure_dir) if f.endswith(".csv") and f.startswith(kind)
        ]
        csv_files.sort(reverse=True)
        files.append(csv_files[0])  # Get the latest file for each kind

    for file in files:
        file_path = os.path.join(measure_dir, file)
        print(f"Reading {file}")
        df = pd.read_csv(file_path, encoding="utf-8")
        required_columns = {"no", "L*", "a*", "b*"}
        if not required_columns.issubset(df.columns):
            print(f"Error: Missing required columns in {file_path}")
            exit(1)
        for index, row in df.iterrows():
            no = int(row["no"])
            L = float(row["L*"])
            a = float(row["a*"])
            b = float(row["b*"])
            tcc_lab[no - 1].append((L, a, b))

    for index, row in target_lab.iterrows():
        print(f"CC{index + 1:02d} Target Lab: L={row[0]}, a={row[1]}, b={row[2]}")
        for i in range(len(tcc_lab[index])):
            L, a, b = tcc_lab[index][i]
            print(
                f"  Measured in {kinds[i]}: L={L}, a={a}, b={b} "
                f"(ΔE*={((L - row[0]) ** 2 + (a - row[1]) ** 2 + (b - row[2]) ** 2) ** 0.5:.2f})"
            )
    # print(tcc_lab)


if __name__ == "__main__":
    read_data()