import re
import matplotlib.pyplot as plt

def extract_cv_mse(log_path):
    """
    从日志文件中提取特征数和对应的CV MSE。
    日志行格式示例：
    "Current number of features: 156, CV MSE: 4.9253"
    """
    feature_counts = []
    cv_mses = []
    pattern = re.compile(r"Current number of features:\s*(\d+),\s*CV MSE:\s*([\d\.]+)")
    with open(log_path, "r") as f:
        for line in f:
            match = pattern.search(line)
            if match:
                feature_counts.append(int(match.group(1)))
                cv_mses.append(float(match.group(2)))
    return feature_counts, cv_mses

def plot_cv_mse(log_path, output_image="cv_mse_curve.png"):
    """
    根据日志文件中的数据绘制 CV MSE 曲线，并保存图片
    """
    feature_counts, cv_mses = extract_cv_mse(log_path)
    
    if not feature_counts:
        print("没有在日志文件中找到有效的 'Current number of features' 数据。")
        return

    plt.figure(figsize=(8,6))
    plt.plot(feature_counts, cv_mses, marker='o', linestyle='-')
    plt.xlabel("Number of Features")
    plt.ylabel("CV MSE")
    plt.title("CV MSE vs. Number of Features")
    plt.grid(True)
    plt.savefig(output_image, dpi=300)
    plt.close()
    print(f"CV MSE 曲线图已保存为: {output_image}")

if __name__ == "__main__":
    import sys
    if len(sys.argv) < 2:
        print("用法: python script.py <log_file_path>")
    else:
        log_file = sys.argv[1]
        plot_cv_mse(log_file)

# python 1d-qsar/cuda/RFE_cuml_permutation_update.log