import numpy as np
import openpyxl
import csv
import os.path
from scipy.stats import f_oneway


def read_value(patient_dir, atlas, data_type):
    folder_name = os.path.basename(patient_dir)
    csv_file_path = os.path.join(patient_dir, f"{data_type}_{atlas}_result", "result_atlas.csv")

    result = [folder_name]
    with open(csv_file_path, mode='r') as data_csv_file:
        csv_reader = csv.DictReader(data_csv_file)
        for row in csv_reader:
            mean = float(row["meanValue"])
            result.append(mean)

    return result


def read_header(patient_dir, atlas, data_type):
    header = ['编号']

    csv_file_path = os.path.join(patient_dir, f"{data_type}_{atlas}_result", "result_atlas.csv")

    with open(csv_file_path, mode='r') as data_csv_file:
        csv_reader = csv.DictReader(data_csv_file)
        for row in csv_reader:
            region_name = row["Chinese Name"]
            header.append(region_name)

    return header


def generate_stats_row(name, region_size, function, patient_size, extra_parameter):
    result = [name]

    for i in range(region_size):
        letter = openpyxl.utils.cell.get_column_letter(i + 2)
        result.append(f'={function}({letter}2:{letter}{patient_size + 1}{extra_parameter})')

    return result


def write_to_work_sheet(work_sheet, patient_list, atlas, data_type):
    if len(patient_list) == 0:
        return

    header = read_header(patient_list[0], atlas, data_type)

    work_sheet.append(header)

    for patient_dir in patient_list:
        print(data_type, patient_dir)
        patient_data = read_value(patient_dir, atlas, data_type)

        work_sheet.append(patient_data)

    region_size = len(header) - 1
    work_sheet.append([])
    work_sheet.append([])
    work_sheet.append(generate_stats_row('均值', region_size, 'AVERAGE', len(patient_list), ''))
    work_sheet.append(generate_stats_row('标准差', region_size, 'STDEV', len(patient_list), ''))
    work_sheet.append(generate_stats_row('最小值', region_size, 'MIN', len(patient_list), ''))
    work_sheet.append(generate_stats_row('5%', region_size, 'PERCENTILE', len(patient_list), ',0.05'))
    work_sheet.append(generate_stats_row('25%', region_size, 'PERCENTILE', len(patient_list), ',0.25'))
    work_sheet.append(generate_stats_row('50%', region_size, 'PERCENTILE', len(patient_list), ',0.50'))
    work_sheet.append(generate_stats_row('75%', region_size, 'PERCENTILE', len(patient_list), ',0.75'))
    work_sheet.append(generate_stats_row('95%', region_size, 'PERCENTILE', len(patient_list), ',0.95'))
    work_sheet.append(generate_stats_row('最大值', region_size, 'MAX', len(patient_list), ''))


def write_anova(workbook, work_sheet, groups, atlas, data_type):
    header = ['', 'F', 'p']
    work_sheet.append(header)

    sheet_dict = {}
    for group_name, group in groups.items():
        sheet_dict[group_name] = f'{group_name}_{atlas}_{data_type}'

    first_group_sheet = workbook[list(sheet_dict.values())[0]]
    for column_num in range(2, first_group_sheet.max_column + 1):
        data_list = []
        data_row = [first_group_sheet.cell(row=1, column=column_num).value]

        for group_name, sheet_name in sheet_dict.items():
            group_data = []
            data_count = len(groups[group_name])
            for i in range(2, data_count + 2):
                data_value = workbook[sheet_name].cell(row=i, column=column_num).value
                if not np.isnan(data_value):
                    group_data.append(data_value)
            data_list.append(group_data)

        if len(data_list[0]) == 0:
            continue

        f_value, p_value = f_oneway(*data_list)
        data_row += [f_value, p_value]
        work_sheet.append(data_row)


def main():
    data_types = ['corr-CBF']
    atlas_list = ['AnImage_AAL3']

    output_file = r'..\Data\csv-ANOVA-SciPy.xlsx'
    group_file = r'..\Data\group.xlsx'
    patient_root = r'..\Data\csv-data'

    groups = {}

    group_workbook = openpyxl.load_workbook(group_file)
    for sheet_name in group_workbook.sheetnames:
        group = []
        group_sheet = group_workbook[sheet_name]
        for i in range(1, group_sheet.max_row + 1):
            patient_id = group_sheet.cell(row=i, column=1).value
            patient_path = os.path.join(patient_root, patient_id)
            group.append(patient_path)
        groups[sheet_name] = group

    all_group = []
    for group in groups.values():
        all_group += group

    work_book = openpyxl.Workbook()
    work_book.remove(work_book.active)

    for data_type in data_types:
        for atlas in atlas_list:
            atlas_new_name = atlas.replace("AnImage_", "")
            for group_key in groups.keys():
                work_sheet = work_book.create_sheet(title=f'{group_key}_{atlas_new_name}_{data_type}')
                write_to_work_sheet(work_sheet, groups[group_key], atlas, data_type)

            work_sheet = work_book.create_sheet(title=f'ALL_{atlas_new_name}_{data_type}')
            write_to_work_sheet(work_sheet, all_group, atlas, data_type)

    for data_type in data_types:
        for atlas in atlas_list:
            atlas_new_name = atlas.replace("AnImage_", "")
            work_sheet = work_book.create_sheet(title=f'ANOVA_{atlas_new_name}_{data_type}')
            write_anova(work_book, work_sheet, groups, atlas_new_name, data_type)

    work_book.save(output_file)


main()