71 lines
2.6 KiB
Python
71 lines
2.6 KiB
Python
import numpy as np
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import openpyxl
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import os.path
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import matplotlib.pyplot as plt
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def draw_cbf_graph(cbf_mean_dict, data_type, save_path):
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plt.rcParams["figure.figsize"] = [32, 18]
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plt.rcParams["figure.autolayout"] = True
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plt.rcParams["font.sans-serif"] = ["SimHei"] # 设置字体
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subplot = plt.subplot(1, 1, 1, projection='polar')
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count = len(cbf_mean_dict)
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theta = np.linspace(0.0, 2 * np.pi, count, endpoint=False)
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data = np.array(list(cbf_mean_dict.values()))
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width = 1.8 * np.pi / count
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subplot.set_theta_zero_location('N')
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subplot.set_theta_direction(-1)
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subplot.xaxis.set_ticks(theta)
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subplot.yaxis.set_ticks([])
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bars = subplot.bar(x=theta, height=data, width=width)
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for data_value, bar in zip(data, bars):
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bar.set_facecolor(plt.cm.turbo(data_value / 60))
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bar.set_alpha(0.8)
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for theta_value, data_value in zip(theta, data):
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margin = data.max() * 0.08
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subplot.annotate(str(round(data_value, 2)), xy=(theta_value, data_value + margin))
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subplot.set_xticklabels(list(cbf_mean_dict.keys()))
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for label, angle in zip(subplot.get_xticklabels(), theta):
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x, y = label.get_position()
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lab = subplot.text(x, y - 0.1, label.get_text(), transform=label.get_transform(), ha=label.get_ha(),
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va=label.get_va())
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rotation = - np.rad2deg(angle) + 90
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if rotation < -90:
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rotation += 180
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lab.set_rotation(rotation)
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subplot.set_xticklabels([])
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plt.title(f"221例健康人西门子5延迟数据各脑区{data_type}")
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plt.savefig(save_path, dpi=200)
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plt.cla()
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plt.close('all')
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def main():
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# 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
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data_types = ['corr-CBF']
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atlas_list = ['AnImage_AAL3']
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output_dir = r'..\Data\polar-graph'
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os.makedirs(output_dir, exist_ok=True)
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input_file = r'..\Data\csv-simple-stat.xlsx'
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workbook = openpyxl.load_workbook(input_file, data_only=True)
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for data_type in data_types:
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for atlas in atlas_list:
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cbf_mean_dict = {}
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worksheet = workbook[f'{atlas}_{data_type}']
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for column_num in range(2, worksheet.max_column + 1):
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name = worksheet.cell(row=1, column=column_num).value
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mean = worksheet.cell(row=worksheet.max_row - 8, column=column_num).value
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print(atlas, data_type, name, mean)
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if type(mean) is float:
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cbf_mean_dict[name] = mean
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draw_cbf_graph(cbf_mean_dict, data_type, os.path.join(output_dir, f'{atlas}_{data_type}.png'))
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main()
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