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Code/6-cbf-graph.py

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+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()