50 lines
1.5 KiB
Python
50 lines
1.5 KiB
Python
import re
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import matplotlib.pyplot as plt
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def extract_cv_mse(log_path):
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"""
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从日志文件中提取特征数和对应的CV MSE。
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日志行格式示例：
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"Current number of features: 156, CV MSE: 4.9253"
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"""
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feature_counts = []
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cv_mses = []
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pattern = re.compile(r"Current number of features:\s*(\d+),\s*CV MSE:\s*([\d\.]+)")
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with open(log_path, "r") as f:
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for line in f:
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match = pattern.search(line)
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if match:
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feature_counts.append(int(match.group(1)))
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cv_mses.append(float(match.group(2)))
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return feature_counts, cv_mses
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def plot_cv_mse(log_path, output_image="cv_mse_curve.png"):
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"""
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根据日志文件中的数据绘制 CV MSE 曲线，并保存图片
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"""
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feature_counts, cv_mses = extract_cv_mse(log_path)
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if not feature_counts:
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print("没有在日志文件中找到有效的 'Current number of features' 数据。")
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return
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plt.figure(figsize=(8,6))
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plt.plot(feature_counts, cv_mses, marker='o', linestyle='-')
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plt.xlabel("Number of Features")
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plt.ylabel("CV MSE")
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plt.title("CV MSE vs. Number of Features")
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plt.grid(True)
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plt.savefig(output_image, dpi=300)
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plt.close()
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print(f"CV MSE 曲线图已保存为: {output_image}")
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if __name__ == "__main__":
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import sys
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if len(sys.argv) < 2:
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print("用法: python script.py <log_file_path>")
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else:
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log_file = sys.argv[1]
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plot_cv_mse(log_file)
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# python 1d-qsar/cuda/RFE_cuml_permutation_update.log
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