62 lines
2.2 KiB
Python
62 lines
2.2 KiB
Python
import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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import os
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import glob
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def read_csv_columns(csv_file_path, header_names):
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df = pd.read_csv(csv_file_path)
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return df[header_names].values
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def normalize(data):
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mean = np.mean(data, axis=0)
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std = np.std(data, axis=0)
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return (data - mean) / std
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def save_to_csv(data, header_names, output_file):
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df = pd.DataFrame(data, columns=header_names)
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df.to_csv(output_file, index=False)
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def plot_comparison_and_save(original_data, normalized_data, header_names, save_path):
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plt.figure(figsize=(14, 10))
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for i, col_name in enumerate(header_names):
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plt.plot(normalized_data[:, i], label='Normalized ' + col_name)
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plt.title('Normalization')
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plt.xlabel('Time')
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plt.ylabel('Value')
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plt.legend(loc='lower left') # 固定图例在左下角
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plt.tight_layout()
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plt.savefig(save_path)
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if __name__ == "__main__":
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input_directory = r'D:\pycharmProjects\python_server\KalManData' # 输入目录路径
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output_csv_directory = r'D:\pycharmProjects\python_server\NormalizeData' # 输出目录路径
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output_png_directory = r'D:\pycharmProjects\python_server\NormalizePng' # 输出png目录路径
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columns_to_process = ['accX', 'accY', 'accZ', 'gyroX', 'gyroY', 'gyroZ', 'magX', 'magY', 'magZ']
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# 创建输出目录（如果不存在）
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if not os.path.exists(output_csv_directory):
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os.makedirs(output_csv_directory)
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if not os.path.exists(output_png_directory):
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os.makedirs(output_png_directory)
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csv_files = glob.glob(os.path.join(input_directory, '*.csv'))
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for input_csv_file in csv_files:
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file_name = os.path.basename(input_csv_file)
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output_csv_file = os.path.join(output_csv_directory, os.path.splitext(file_name)[0] + '_normalized.csv')
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output_plot_file = os.path.join(output_png_directory,
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os.path.splitext(file_name)[0] + '_normalization_comparison.png')
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data = read_csv_columns(input_csv_file, columns_to_process)
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normalized_data = normalize(data)
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save_to_csv(normalized_data, columns_to_process, output_csv_file)
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plot_comparison_and_save(data, normalized_data, columns_to_process, output_plot_file)
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