diff --git a/.gitignore b/.gitignore index 185ae7e..ab3e8ce 100644 --- a/.gitignore +++ b/.gitignore @@ -162,7 +162,3 @@ cython_debug/ # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ -.venv/ -.idea/ -.ipynb_checkpoints/ -Data/ \ No newline at end of file diff --git a/Code/1-extract.py b/Code/1-extract.py deleted file mode 100644 index fad1dd9..0000000 --- a/Code/1-extract.py +++ /dev/null @@ -1,72 +0,0 @@ -import openpyxl -import csv -import os.path -import glob - - -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 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, atlas, patient_dir) - patient_data = read_value(patient_dir, atlas, data_type) - - work_sheet.append(patient_data) - - -def main(): - # 选择导出的数据类型，请尝试增加VOL类型，并修改read_value、read_header函数以支持读取体积 - data_types = ['corr-CBF', 'ATT', 'ACBV', 'CBF1', 'CBF2', 'CBF3', 'CBF4', 'CBF5'] - # 选择导出后的图谱 - atlas_list = ['AnImage_WholeBrain', 'AnImage_BrainLobes', 'AnImage_AAL3'] - # 选择输出的位置 - output_file = r'..\Data\csv-extract.xlsx' - # 选择输入的数据 - patient_list = glob.glob(r'..\Data\csv-data\*') - # 创建新的excel workbook - work_book = openpyxl.Workbook() - # 删除默认worksheet - work_book.remove(work_book.active) - - for data_type in data_types: - for atlas in atlas_list: - work_sheet = work_book.create_sheet(title=f'{atlas}_{data_type}') - write_to_work_sheet(work_sheet, patient_list, atlas, data_type) - - # 保存workbook到xlsx文件 - work_book.save(output_file) - - -main() diff --git a/Code/10-registration.py b/Code/10-registration.py deleted file mode 100644 index 0abfd62..0000000 --- a/Code/10-registration.py +++ /dev/null @@ -1,53 +0,0 @@ -import SimpleITK as sitk - - -def command_iteration(method): - print(f"{method.GetOptimizerIteration()} = {method.GetMetricValue():.5f} {method.GetOptimizerPosition()}") - - -def registration(fixed_image_path, moving_image_path, new_image_path): - fixed_image = sitk.ReadImage(fixed_image_path, sitk.sitkFloat32) - moving_image = sitk.ReadImage(moving_image_path, sitk.sitkFloat32) - - registration_method = sitk.ImageRegistrationMethod() - - registration_method.SetMetricAsJointHistogramMutualInformation(numberOfHistogramBins=50) - registration_method.SetMetricSamplingStrategy(registration_method.REGULAR) - registration_method.SetMetricSamplingPercentage(0.2, 42) - registration_method.SetGlobalDefaultNumberOfThreads(1) - registration_method.SetOptimizerScalesFromPhysicalShift() - - registration_method.SetInterpolator(sitk.sitkLinear) - registration_method.AddCommand(sitk.sitkIterationEvent, lambda: command_iteration(registration_method)) - - registration_method.SetOptimizerAsRegularStepGradientDescent(minStep=0.0001, - learningRate=1.0, - numberOfIterations=400, - gradientMagnitudeTolerance=1e-8) - - initial_transform = sitk.CenteredTransformInitializer(fixed_image, moving_image, sitk.Euler3DTransform()) - registration_method.SetInitialTransform(initial_transform, inPlace=True) - - # 进行配准 - final_transform_v4 = registration_method.Execute(fixed_image, moving_image) - - # 打印结束条件 - stop_condition = registration_method.GetOptimizerStopConditionDescription() - print(stop_condition) - - # 重采样新的图像 - moving_resampled = sitk.Resample(moving_image, fixed_image, final_transform_v4, sitk.sitkLinear, 0.0, - moving_image.GetPixelID()) - - sitk.WriteImage(moving_resampled, new_image_path) - - -def main(): - fixed_image_path = r"..\Data\registration\t1.nii.gz" - moving_image_path = r"..\Data\registration\t2 flair.nii.gz" - new_image_path = r"..\Data\registration\t2 flair_resampled.nii.gz" - - registration(fixed_image_path, moving_image_path, new_image_path) - - -main() diff --git a/Code/2-simple-stat.py b/Code/2-simple-stat.py deleted file mode 100644 index e75abe5..0000000 --- a/Code/2-simple-stat.py +++ /dev/null @@ -1,93 +0,0 @@ -import openpyxl -import csv -import os.path -import glob - - -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): - 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})') - - 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))) - # 请尝试在空格的位置添加 5% 25% 50% 75% 95% 分位数，使用excel的PERCENTILE函数 - work_sheet.append([]) - work_sheet.append([]) - work_sheet.append([]) - work_sheet.append([]) - work_sheet.append([]) - work_sheet.append(generate_stats_row('最大值', region_size, 'MAX', len(patient_list))) - - -def main(): - data_types = ['corr-CBF', 'ATT', 'ACBV', 'CBF1', 'CBF2', 'CBF3', 'CBF4', 'CBF5'] - atlas_list = ['AnImage_WholeBrain', 'AnImage_BrainLobes', 'AnImage_AAL3'] - - output_file = r'..\Data\csv-simple-stat.xlsx' - - patient_list = glob.glob(r'..\Data\csv-data\*') - - work_book = openpyxl.Workbook() - work_book.remove(work_book.active) - - for data_type in data_types: - for atlas in atlas_list: - work_sheet = work_book.create_sheet(title=f'{atlas}_{data_type}') - write_to_work_sheet(work_sheet, patient_list, atlas, data_type) - - work_book.save(output_file) - - -main() diff --git a/Code/3-group.py b/Code/3-group.py deleted file mode 100644 index 0bdc69c..0000000 --- a/Code/3-group.py +++ /dev/null @@ -1,104 +0,0 @@ -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 main(): - data_types = ['corr-CBF', "ATT"] - atlas_list = ['AnImage_WholeBrain', 'AnImage_BrainLobes', 'AnImage_AAL3'] - - output_file = r'..\Data\csv-group.xlsx' - group_file = r'..\Data\group.xlsx' - patient_root = r'..\Data\csv-data' - - groups = {} - # 读取分组信息 - 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 - - work_book = openpyxl.Workbook() - work_book.remove(work_book.active) - - for group_key in groups.keys(): - for data_type in data_types: - for atlas in atlas_list: - work_sheet = work_book.create_sheet(title=f'{group_key}_{atlas}_{data_type}') - write_to_work_sheet(work_sheet, groups[group_key], atlas, data_type) - - work_book.save(output_file) - - -main() diff --git a/Code/4-ANOVA.py b/Code/4-ANOVA.py deleted file mode 100644 index 075e8db..0000000 --- a/Code/4-ANOVA.py +++ /dev/null @@ -1,184 +0,0 @@ -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() diff --git a/Code/5-ANOVA-SciPy.py b/Code/5-ANOVA-SciPy.py deleted file mode 100644 index cceccad..0000000 --- a/Code/5-ANOVA-SciPy.py +++ /dev/null @@ -1,150 +0,0 @@ -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() diff --git a/Code/6-cbf-graph.py b/Code/6-cbf-graph.py deleted file mode 100644 index 5013607..0000000 --- a/Code/6-cbf-graph.py +++ /dev/null @@ -1,68 +0,0 @@ -import numpy as np -import openpyxl -import os.path -import matplotlib.pyplot as plt - - -def draw_cbf_graph(region, data, save_path): - bar_x = np.array(['0.5', '1', '1.5', '2', '2.5', 'cCBF']) - bar_y = np.array(data) - color = ['#4CAF50', '#4CAF50', '#4CAF50', '#4CAF50', '#4CAF50', '#478FC1'] - - # Plotting the Graph - font_color = '#FFFFFF' - plt.rcParams['text.color'] = font_color - plt.rcParams['axes.labelcolor'] = font_color - plt.rcParams['xtick.color'] = font_color - plt.rcParams['ytick.color'] = font_color - - plt.figure(facecolor='#000000') - ax = plt.axes() - ax.set_facecolor('#000000') - ax.spines['left'].set_color(font_color) - ax.spines['right'].set_color(font_color) - ax.spines['bottom'].set_color(font_color) - ax.spines['top'].set_color(font_color) - - plt.rcParams["font.sans-serif"] = ["SimHei"] # 设置字体 - plt.bar(bar_x, bar_y, width=0.5, color=color) - - for i in range(len(bar_x)): - plt.text(i - 0.2, bar_y[i] - 2, f"{bar_y[i]:.2f}") - - plt.title(f"221例健康人西门子5延迟数据矫正前后{region}CBF对比") - plt.xlabel("PLD") - plt.ylabel("CBF") - plt.savefig(save_path, dpi=200) - plt.cla() - plt.close('all') - - -def main(): - data_types = ['CBF1', 'CBF2', 'CBF3', 'CBF4', 'CBF5', 'corr-CBF'] - # 请尝试添加'AnImage_AAL3'图谱,并修复错误 - atlas_list = ['AnImage_WholeBrain', 'AnImage_BrainLobes'] - output_dir = r'..\Data\cbf-graph' - os.makedirs(output_dir, exist_ok=True) - - input_file = r'..\Data\csv-simple-stat.xlsx' - workbook = openpyxl.load_workbook(input_file, data_only=True) - - for atlas in atlas_list: - cbf_mean_dict = {} - for data_type in data_types: - worksheet = workbook[f'{atlas}_{data_type}'] - for column_num in range(2, worksheet.max_column + 1): - name = worksheet.cell(row=1, column=column_num).value - mean = worksheet.cell(row=worksheet.max_row - 8, column=column_num).value - print(atlas, data_type, name, mean) - - if name not in cbf_mean_dict: - cbf_mean_dict[name] = [] - cbf_mean_dict[name].append(mean) - - for region, data in cbf_mean_dict.items(): - draw_cbf_graph(region, data, os.path.join(output_dir, f'{region}.png')) - - -main() diff --git a/Code/7-box-graph.py b/Code/7-box-graph.py deleted file mode 100644 index 313a1f4..0000000 --- a/Code/7-box-graph.py +++ /dev/null @@ -1,50 +0,0 @@ -import openpyxl -import os.path -import matplotlib.pyplot as plt - - -def draw_box_graph(region, data, groups, data_type, save_path): - plt.rcParams["font.sans-serif"] = ["SimHei"] # 设置字体 - plt.boxplot(data, - patch_artist=True, # 是否填色 - labels=groups) - - plt.title(f"各个分组{region}{data_type}对比") - plt.xlabel("分组") - plt.ylabel(data_type) - plt.savefig(save_path, dpi=200) - plt.cla() - plt.close('all') - - -def main(): - data_types = ['corr-CBF', "ATT"] - # 请尝试添加'AnImage_AAL3'图谱,并修复错误 - atlas_list = ['AnImage_WholeBrain', 'AnImage_BrainLobes'] - output_dir = r'..\Data\box-graph' - os.makedirs(output_dir, exist_ok=True) - - input_file = r'..\Data\csv-group.xlsx' - workbook = openpyxl.load_workbook(input_file, data_only=True) - groups = ['A', 'B', 'C'] - - for data_type in data_types: - for atlas in atlas_list: - value_dict = {} - for group in groups: - worksheet = workbook[f'{group}_{atlas}_{data_type}'] - for column_num in range(2, worksheet.max_column + 1): - data = [] - name = worksheet.cell(row=1, column=column_num).value - for row in range(2, worksheet.max_row - 10): - data.append(worksheet.cell(row=row, column=column_num).value) - - if name not in value_dict: - value_dict[name] = [] - value_dict[name].append(data) - - for region, data in value_dict.items(): - draw_box_graph(region, data, groups, data_type, os.path.join(output_dir, f'{region}{data_type}.png')) - - -main() diff --git a/Code/8-subplot.py b/Code/8-subplot.py deleted file mode 100644 index 03f955a..0000000 --- a/Code/8-subplot.py +++ /dev/null @@ -1,55 +0,0 @@ -import openpyxl -import os.path -import matplotlib.pyplot as plt - - -def draw_box_graph(data_dict, groups, data_type, save_path): - plt.rcParams["font.sans-serif"] = ["SimHei"] # 设置字体 - - grid_height = 2 - grid_width = 4 - - _, ax = plt.subplots(grid_height, grid_width, figsize=(20, 15), sharey=True) - keys = list(data_dict.keys()) - for x in range(grid_width): - for y in range(grid_height): - region_name = keys[x + y * grid_width] - ax[y][x].boxplot(data_dict[region_name], patch_artist=True, labels=groups) - ax[y][x].set_title(f"{region_name}{data_type}对比") - ax[y][x].set_ylabel(data_type) - - plt.tight_layout() - plt.savefig(save_path, dpi=200) - plt.cla() - plt.close('all') - - -def main(): - data_types = ['corr-CBF', "ATT"] - atlas_list = ['AnImage_BrainLobes'] - output_dir = r'..\Data\subplot' - os.makedirs(output_dir, exist_ok=True) - - input_file = r'..\Data\csv-group.xlsx' - workbook = openpyxl.load_workbook(input_file, data_only=True) - groups = ['A', 'B', 'C'] - - for data_type in data_types: - for atlas in atlas_list: - value_dict = {} - for group in groups: - worksheet = workbook[f'{group}_{atlas}_{data_type}'] - for column_num in range(2, worksheet.max_column + 1): - data = [] - name = worksheet.cell(row=1, column=column_num).value - for row in range(2, worksheet.max_row - 10): - data.append(worksheet.cell(row=row, column=column_num).value) - - if name not in value_dict: - value_dict[name] = [] - value_dict[name].append(data) - - draw_box_graph(value_dict, groups, data_type, os.path.join(output_dir, f'{atlas}_{data_type}.png')) - - -main() diff --git a/Code/9-polar-graph.py b/Code/9-polar-graph.py deleted file mode 100644 index 1b8f2a4..0000000 --- a/Code/9-polar-graph.py +++ /dev/null @@ -1,71 +0,0 @@ -import numpy as np -import openpyxl -import os.path -import matplotlib.pyplot as plt - - -def draw_cbf_graph(cbf_mean_dict, data_type, save_path): - plt.rcParams["figure.figsize"] = [32, 18] - plt.rcParams["figure.autolayout"] = True - plt.rcParams["font.sans-serif"] = ["SimHei"] # 设置字体 - subplot = plt.subplot(1, 1, 1, projection='polar') - - count = len(cbf_mean_dict) - theta = np.linspace(0.0, 2 * np.pi, count, endpoint=False) - data = np.array(list(cbf_mean_dict.values())) - width = 1.8 * np.pi / count - subplot.set_theta_zero_location('N') - subplot.set_theta_direction(-1) - subplot.xaxis.set_ticks(theta) - subplot.yaxis.set_ticks([]) - - bars = subplot.bar(x=theta, height=data, width=width) - for data_value, bar in zip(data, bars): - bar.set_facecolor(plt.cm.turbo(data_value / 60)) - bar.set_alpha(0.8) - for theta_value, data_value in zip(theta, data): - margin = data.max() * 0.08 - subplot.annotate(str(round(data_value, 2)), xy=(theta_value, data_value + margin)) - - subplot.set_xticklabels(list(cbf_mean_dict.keys())) - for label, angle in zip(subplot.get_xticklabels(), theta): - x, y = label.get_position() - lab = subplot.text(x, y - 0.1, label.get_text(), transform=label.get_transform(), ha=label.get_ha(), - va=label.get_va()) - rotation = - np.rad2deg(angle) + 90 - if rotation < -90: - rotation += 180 - lab.set_rotation(rotation) - subplot.set_xticklabels([]) - - plt.title(f"221例健康人西门子5延迟数据各脑区{data_type}") - plt.savefig(save_path, dpi=200) - plt.cla() - plt.close('all') - - -def main(): - # 请尝试添加att参数，并调整色阶范围使得CBF=40时为红色，60时为蓝色 - data_types = ['corr-CBF'] - atlas_list = ['AnImage_AAL3'] - output_dir = r'..\Data\polar-graph' - os.makedirs(output_dir, exist_ok=True) - - input_file = r'..\Data\csv-simple-stat.xlsx' - workbook = openpyxl.load_workbook(input_file, data_only=True) - - for data_type in data_types: - for atlas in atlas_list: - cbf_mean_dict = {} - worksheet = workbook[f'{atlas}_{data_type}'] - for column_num in range(2, worksheet.max_column + 1): - name = worksheet.cell(row=1, column=column_num).value - mean = worksheet.cell(row=worksheet.max_row - 8, column=column_num).value - print(atlas, data_type, name, mean) - if type(mean) is float: - cbf_mean_dict[name] = mean - - draw_cbf_graph(cbf_mean_dict, data_type, os.path.join(output_dir, f'{atlas}_{data_type}.png')) - - -main() diff --git a/Exercise/exercise-1.1.py b/Exercise/exercise-1.1.py deleted file mode 100644 index 4fcde8f..0000000 --- a/Exercise/exercise-1.1.py +++ /dev/null @@ -1,13 +0,0 @@ - -# 计算 12879 * 36521 并打印 -# product = ??? -# print(product) - - -# 计算 100 模 32 并打印 -# mod = ??? -# print(mod) - -# 打印Hello\ "World!" -# msg = ??? -# print(msg) diff --git a/Exercise/exercise-1.2.py b/Exercise/exercise-1.2.py deleted file mode 100644 index eec36a0..0000000 --- a/Exercise/exercise-1.2.py +++ /dev/null @@ -1,8 +0,0 @@ -import math - -# 请输出以下关于圆的周长和面积的计算，保留3位小数 -radius = 3 -pi = math.pi - -# 应当输出 当圆的的半径是3时，它的周长是18.850，他的面积是28.274 -print('当圆的的半径是时，它的周长是，他的面积是') diff --git a/Exercise/exercise-2.1.py b/Exercise/exercise-2.1.py deleted file mode 100644 index 7648898..0000000 --- a/Exercise/exercise-2.1.py +++ /dev/null @@ -1,9 +0,0 @@ -# 请尝试修改list以满足输出 - -list_a = [0] - -list_a += ['Hello'] * 5 -list_a += [4, 5] * 3 - -# 输出[0, 'Hello', 'Hello', 'Hello', 'Hello', 'Hello', 4, 5, 4, 5, 4, 5] -print(list_a) diff --git a/Exercise/exercise-2.2.py b/Exercise/exercise-2.2.py deleted file mode 100644 index c2bf5ad..0000000 --- a/Exercise/exercise-2.2.py +++ /dev/null @@ -1,18 +0,0 @@ - -# 我们用如下数组存储一些患者的信息 -patient_info = [ - ["Zhang San", 52, "M"], - ["Li Si", 19, "F"], - ["Wang Wu", 47, "F"], -] - -# 检查后发现，张三的年龄和李四的年龄写反了，请将他们调整过来 - - - - -# 应当为 19 -print(patient_info[0][1]) - -# 应当为 52 -print(patient_info[1][1]) diff --git a/Exercise/exercise-2.3.py b/Exercise/exercise-2.3.py deleted file mode 100644 index 87c0ba9..0000000 --- a/Exercise/exercise-2.3.py +++ /dev/null @@ -1,19 +0,0 @@ -age_dict = { - "Zhang San": 52, - "Li Si": 19, - "Wang Wu": 47 -} - -# 检查后发现，张三的年龄和李四的年龄写反了，请将他们调整过来。并添加Zhao Liu，年龄为29 - - - - -# 应当为 19 -print(age_dict['Zhang San']) - -# 应当为 52 -print(age_dict['Li Si']) - -# 应当为 29 -print(age_dict['Zhao Liu']) diff --git a/Exercise/exercise-3.1.py b/Exercise/exercise-3.1.py deleted file mode 100644 index 5664c63..0000000 --- a/Exercise/exercise-3.1.py +++ /dev/null @@ -1,13 +0,0 @@ -# 请根据用户输入的年龄输出在学校的阶段： -# 0-5 输出 学龄前 -# 6-11 输出 小学 -# 12-14 输出 初中 -# 15-17 输出 高中 -# 18-21 输出 大学 -# 22-59 输出 打工人 -# 60+ 输出 退休了 - -print('请输入你的年龄：') -age = int(input()) -if age < 6: - print('学龄前') diff --git a/Exercise/exercise-4.1.py b/Exercise/exercise-4.1.py deleted file mode 100644 index 23777f1..0000000 --- a/Exercise/exercise-4.1.py +++ /dev/null @@ -1,33 +0,0 @@ - - -# 我们希望将患者按照信息，分别按照性别和年龄分成4个组别，分别存储他们的姓名 -patient_info = [ - ["Zhang San", 52, "M"], - ["Li Si", 19, "F"], - ["Wang Wu", 47, "F"], - ["Zhao Liu", 29, "M"], -] -group_M_under_30 = [] -group_M_over_30 = [] -group_F_under_30 = [] -group_F_over_30 = [] - -for patient in patient_info: - print('new patient:', patient) - # 补充代码，使用条件判断，将患者分为4组，分别存储他们的姓名即可 - - - - - -# 应当为 ["Zhao Liu"] -print(group_M_under_30) - -# 应当为 ["Zhang San"] -print(group_M_over_30) - -# 应当为 ["Li Si"] -print(group_F_under_30) - -# 应当为 ["Wang Wu"] -print(group_F_over_30) diff --git a/Exercise/exercise-4.2.py b/Exercise/exercise-4.2.py deleted file mode 100644 index 6b3548b..0000000 --- a/Exercise/exercise-4.2.py +++ /dev/null @@ -1,15 +0,0 @@ -# 给定一组整数，计算他们的和并输出等式 - -magic_number_list = [4, 8, 15, 16, 23, 42] - -sum = 0 -expression = '' -for index in range(len(magic_number_list)): - print(index) - - - - - -# 应输出4 + 8 + 15 + 16 + 23 + 42 = 108 -print(expression) \ No newline at end of file diff --git a/Exercise/exercise-4.3.py b/Exercise/exercise-4.3.py deleted file mode 100644 index 1255156..0000000 --- a/Exercise/exercise-4.3.py +++ /dev/null @@ -1,14 +0,0 @@ -import random - -# 我们来写一个猜数字的小游戏 - -# 生成一个随机的1-100整数作为答案 -answer = random.randint(1, 100) -game_over = False -count = 0 -while not game_over: - print(f"你已经猜了{count}次，请输入下一次猜测") - count += 1 - guess = int(input()) - print(f"你的猜测是{guess}") - # 如果猜对了，输出“猜对了”并结束游戏。否则输出“猜大了”或者“猜小了” \ No newline at end of file diff --git a/Exercise/exercise-5.1.py b/Exercise/exercise-5.1.py deleted file mode 100644 index 2894ecf..0000000 --- a/Exercise/exercise-5.1.py +++ /dev/null @@ -1,10 +0,0 @@ -# 我们来输出100以内的素数 - -def is_prime(n): - # 检查n是否是素数，一个简易的办法是，遍历小于n的自然数，判断是否有自然数可以整除n - return False - - -for i in range(100): - # 遍历100以内的自然数，检查他们是不是素数，并输出其中的素数 - result = is_prime(i) diff --git a/Exercise/exercise-5.2.py b/Exercise/exercise-5.2.py deleted file mode 100644 index 955de4f..0000000 --- a/Exercise/exercise-5.2.py +++ /dev/null @@ -1,23 +0,0 @@ -import random - - -# 概率计算表明，23个人中有至少两人生日相同的概率高达50.7%，听起来有些反直觉，我们来通过计算估计这一概率。 -def contains_same_birthday(birthdays): - # 修改代码，判断birthdays这个list中是否有相同的元素 - return True - - -# 我们进行10000次测试 -test_count = 10000 -# 有至少两人生日相同的次数 -true_count = 0 - -for i in range(test_count): - birth_days = [] - for j in range(23): - birth_days.append(random.randint(1, 365)) - - # 统计满足条件的测试次数 - -# 输出测试结果，保留4位小数 -print('23个人中有至少两人生日相同的概率是:') diff --git a/Exercise/exercise-5.3.py b/Exercise/exercise-5.3.py deleted file mode 100644 index 06f1fde..0000000 --- a/Exercise/exercise-5.3.py +++ /dev/null @@ -1,8 +0,0 @@ - - -# 哥德巴赫猜想（Goldbach's conjecture）是数论中存在最久的未解问题之一。这个猜想最早出现在1742年普鲁士数学家克里斯蒂安·哥德巴赫与瑞士数学家莱昂哈德·欧拉的通信中。用现代的数学语言，哥德巴赫猜想可以陈述为： -# 任一大于2的偶数，都可表示成两个素数之和 -# 验证1000以内偶数是否满足这一猜想，并输出每一个结果，例如 -# 4 = 2 + 2 -# 6 = 3 + 3 -# 8 = 3 + 5 \ No newline at end of file diff --git a/README.md b/README.md index 63bda06..86813d1 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,2 @@ -# ASL成像基于Python的定量数据处理基础 - +# python_for_asl diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 43df810..0000000 --- a/requirements.txt +++ /dev/null @@ -1,32 +0,0 @@ -attr==0.3.2 -ConfigParser==7.2.0 -contextlib2==21.6.0 -cryptography==45.0.5 -Cython==3.1.2 -dl==0.1.0 -docutils==0.22 -HTMLParser==0.0.2 -ipython==7.34.0 -ipywidgets==8.1.7 -Jinja2==3.0.3 -jnius==1.1.0 -keyring==25.6.0 -lockfile==0.12.2 -matplotlib==3.3.4 -mock==5.2.0 -numpy==1.21.6 -openpyxl==3.1.3 -Pillow==9.5.0 -Pillow==11.3.0 -protobuf==3.14.0 -pyOpenSSL==25.1.0 -pywin32==308 -railroad==0.5.0 -scipy==1.5.4 -Sphinx==8.2.3 -thread==2.0.5 -tornado==6.2 -trove_classifiers==2025.5.9.12 -truststore==0.10.3 -urllib3_secure_extra==0.1.0 -xmlrpclib==1.0.1