82 lines
2.7 KiB
Python
82 lines
2.7 KiB
Python
from datetime import datetime, timedelta
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import struct
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import pandas as pd
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def read_binary_file(file_path):
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df = pd.DataFrame()
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with open(file_path, "rb") as file:
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index = 0
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# 读取前8个字节，表示数据列数
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column_bytes = file.read(8)
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if not column_bytes:
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return # 文件结束
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column_count = struct.unpack("<d", column_bytes)[0]
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column_count_int = int(column_count)
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print(f"Column Count: {column_count_int}")
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# 读取接下来的8个字节，表示日期
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date_bytes = file.read(8)
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date_float = struct.unpack("<d", date_bytes)[0]
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date_str = str(int(date_float))
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year = int(date_str[:4])
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month = int(date_str[4:6])
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day = int(date_str[6:8])
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# start_date = datetime(year, month, day)
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# print(f"Date: {datetime(year, month, day)}")
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# 第一个时间戳所有数据
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# time_bytes = file.read(8)
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# time = struct.unpack("<d", time_bytes)[0]
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# print(f"Time: {time}")
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# hours = int(time / 60)
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# first_date = start_date + timedelta(hours=hours)
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# print(f"Minute: {minute}")
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# data_size = column_count_int * 8 # 每个数据点8个字节
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# file.seek(data_size, 1)
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# time1_bytes = file.read(8)
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# time1 = struct.unpack("<d", time1_bytes)[0]
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# print(f"Time: {time1}")
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# file.seek(data_size, 1)
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# time2_bytes = file.read(8)
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# time2 = struct.unpack("<d", time2_bytes)[0]
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# print(f"Time: {time2}")
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# for i in range(column_count_int):
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# print(i)
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# if i > 10:
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# break
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# data_bytes = file.read(8)
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# data = struct.unpack("<d", data_bytes)[0]
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# print(f"Data: {data}")
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while True:
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# print("index", index)
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if index > 335:
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break
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time_bytes = file.read(8)
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time = struct.unpack("<d", time_bytes)[0]
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# print(f"time: {time}")
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# 读取数据矩阵
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data_size = column_count_int * 8 # 每个数据点8个字节
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data_bytes = file.read(data_size)
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data_matrix = struct.unpack(f"<{column_count_int}d", data_bytes)
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data_matrix = [data_matrix]
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new_df = pd.DataFrame(data_matrix)
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df = pd.concat([df, new_df], ignore_index=True)
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# print(f"Data Matrix: {data_matrix}")
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index = index + 1
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print("index", index)
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return df
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if __name__ == "__main__":
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# 使用函数读取文件
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file_path = "lz.out/lz.rivqdown.dat"
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df = read_binary_file(file_path)
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print(df.shape)
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print(df.head())
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