import openpyxl import csv import os.path 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_sum(start_index, step, count, row_num): result = f"={openpyxl.utils.cell.get_column_letter(start_index)}{row_num}" for i in range(1, count): letter = openpyxl.utils.cell.get_column_letter(start_index + i * step) result += f'+{letter}{row_num}' return result def write_anova(workbook, work_sheet, groups, atlas, data_type): header_group = [""] * 14 for group_name in groups.keys(): header_group += [group_name] * 5 work_sheet.append(header_group) header_cn = ['', '样本数量', '平均值', '标准差', '总平方和', '组间平方和', '组内平方和', '检验', '组间均方', '自由度', '组内均方', '自由度', '', ''] for _ in groups.keys(): header_cn += ['样本数量', '平均值', '标准差', '组间平方和', '组内平方和'] work_sheet.append(header_cn) header_en = ['', 'N', 'AVG', 'STD', 'TSS', 'BSS', 'WSS', 'check', 'BMSS', 'df', 'WMSS', 'df', 'F', 'p'] for _ in groups.keys(): header_en += ['N', 'AVG', 'STD', 'BSS', 'WSS'] work_sheet.append(header_en) sheet_dict = {} all_group_count = 0 for group_name, group in groups.items(): sheet_dict[group_name] = f'{group_name}_{atlas}_{data_type}' all_group_count += len(group) all_group_sheet_name = f'ALL_{atlas}_{data_type}' first_group_sheet = workbook[list(sheet_dict.values())[0]] for column_num in range(2, first_group_sheet.max_column + 1): column_letter = openpyxl.utils.cell.get_column_letter(column_num) curr_row_number = column_num + 2 data_row = [first_group_sheet.cell(row=1, column=column_num).value] data_row += [write_sum(15, 5, len(sheet_dict), curr_row_number)] data_row += [f'=AVERAGE(\'{all_group_sheet_name}\'!{column_letter}2:{column_letter}{all_group_count + 1})'] data_row += [f'=STDEV(\'{all_group_sheet_name}\'!{column_letter}2:{column_letter}{all_group_count + 1})'] data_row += [f'=DEVSQ(\'{all_group_sheet_name}\'!{column_letter}2:{column_letter}{all_group_count + 1})'] data_row += [write_sum(18, 5, len(sheet_dict), curr_row_number)] data_row += [write_sum(19, 5, len(sheet_dict), curr_row_number)] data_row += [f'=E{curr_row_number}-F{curr_row_number}-G{curr_row_number}'] data_row += [f'=F{curr_row_number}/J{curr_row_number}'] data_row += [len(groups) - 1] data_row += [f'=G{curr_row_number}/L{curr_row_number}'] data_row += [f'=B{curr_row_number}-J{curr_row_number}-1'] data_row += [f'=I{curr_row_number}/K{curr_row_number}'] data_row += [f'=FDIST(M{curr_row_number}, J{curr_row_number}, L{curr_row_number})'] for group_name, sheet_name in sheet_dict.items(): data_count = len(groups[group_name]) current_column_num = len(data_row) + 1 count_letter = openpyxl.utils.cell.get_column_letter(current_column_num) avg_letter = openpyxl.utils.cell.get_column_letter(current_column_num + 1) data_row += [f'=COUNTA(\'{sheet_name}\'!{column_letter}2:{column_letter}{data_count + 1})'] data_row += [f'=AVERAGE(\'{sheet_name}\'!{column_letter}2:{column_letter}{data_count + 1})'] data_row += [f'=STDEV(\'{sheet_name}\'!{column_letter}2:{column_letter}{data_count + 1})'] data_row += [f'={count_letter}{curr_row_number}*({avg_letter}{curr_row_number}-C{curr_row_number})^2'] data_row += [f'=DEVSQ(\'{sheet_name}\'!{column_letter}2:{column_letter}{data_count + 1})'] work_sheet.append(data_row) def main(): data_types = ['corr-CBF'] atlas_list = ['AnImage_AAL3'] output_file = r'..\Data\csv-ANOVA.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()