46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
import os
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import pandas as pd
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import pyedflib
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from pathlib import Path
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def get_time_to_seconds(time_str):
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h, m, s = map(int, time_str.split(":"))
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return h * 3600 + m * 60 + s
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base_event = ["Hypopnea", "Central apnea", "Obstructive apnea", "Mixed apnea"]
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# 输入设置
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sampID = 888
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dir_path = r"D:\code\SA_Label\data"
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# 数据路径设置
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PSG_Data_Path = Path(os.path.join(dir_path, "PSG"))
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PSG_Label_Path = Path(os.path.join(dir_path, "PSG_label"))
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BCG_Data_Path = Path(os.path.join(dir_path, "BCG"))
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BCG_Label_Path = Path(os.path.join(dir_path, "BCG_label"))
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# 读取PSG标签
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df_PSG_label = pd.read_csv(PSG_Label_Path / (f"export" + str(sampID) + ".csv"), encoding="gbk")
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df_PSG_label = df_PSG_label.loc[:, ~df_PSG_label.columns.str.contains('^Unnamed')]
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df_PSG_label = df_PSG_label[df_PSG_label["Event type"].isin(base_event)]
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df_PSG_label['Duration'] = df_PSG_label['Duration'].str.replace(r' \(.*?\)', '', regex=True)
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# 读取EDF文件
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edf_File = pyedflib.EdfReader(str(PSG_Data_Path / f"A{str(sampID).rjust(7, '0')}.edf"))
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# 获取PSG记录开始时间
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start_time = str(edf_File.getStartdatetime()).split(" ")[1]
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start_time_abs = get_time_to_seconds(start_time)
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# 计算起始时间秒数和终止时间秒数
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df_PSG_label['Start'] = (df_PSG_label['Time'].apply(get_time_to_seconds) - start_time_abs).apply(lambda x: x + 24 * 3600 if x < 0 else x).astype(int)
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df_PSG_label['End'] = df_PSG_label['Start'] + df_PSG_label['Duration'].astype(float).round(0).astype(int)
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# 打印结果
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print(df_PSG_label)
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# 写入csv文件
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df_PSG_label.to_csv(dir_path + r"\BCG_label\export" + str(sampID) + "_all.csv", index=False, encoding="gbk")
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# 打印结果
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print("sampID_" + str(sampID) + "写入csv成功") |