好的，首先，大家好 :) 我正在运行 Python 3.2 x86 @ windows
所以我有一个具有以下结构的二进制文件（6 412字节）：
header: 256 bytes
maxZ: 4 bytes (1 32-bit word)
Zvalues: 2048 bytes (512 32-bit words)
maxX: *same as maxZ*
Xvalues: *same as Zvalues*
maxY: *same as maxZ*
Yvalues: *same as Zvalues*
我知道（由于格式规范）数字存储为 32 位整数，写为 2 的补码
假设我不需要读取标题，这就是我要做的（我有 1539 个 4 字节样本要读取）：
import struct
file = open('C:/02.adb', 'rb')
file.seek(256)
fmt = '<i'
nbytes = 4
for i in range(1539):
packed_data = file.read(nbytes)
unpacked_data = struct.unpack(fmt, packed_data)
print('Sample: ',i,'Value: ',unpacked_data[0])
file.close()
它读取文件并将其内容打印到标准输出，但标志有问题。我想我不是在这里读数字作为 2 的补码......我该如何改进脚本？
tnx 引起注意
补充（23.10.12）：
我意识到，通过编写一个更大的外部脚本的简短版本，我刚刚解决了主要问题本身——我自己的无意识。
可以从文件头读取的样本数不是存储在其中的确切样本总数，而是 ZXY 值组合的数量，不包括存储在每个通道数据块的第一个字中的那些最大幅度。
这是脚本的最终简短版本及其输出（是的，有符号整数的 python 表示是“2 的补码”）：
import struct
file = open('C:/02.adb', 'rb')
file.seek(256)
transfer_ratio = 31446.540881
fmt = '<i'
nbytes = 4
samples = []
for i in range(1539):
packed_data = file.read(nbytes)
unpacked_data = struct.unpack(fmt, packed_data)
samples.append(int(unpacked_data[0])/transfer_ratio)
for i in range(32):
print('Ch1_val: ',samples[i+1],' Ch2_val: ',samples[i+1+513],' Ch3_val: ',samples[i+1+(513*2)])
file.close()
输出：
Ch1_val: 42.20127119933322 Ch2_val: 36.47237399942374 Ch3_val: -3.4996535999447054
Ch1_val: 41.37017819934635 Ch2_val: 36.64441199942102 Ch3_val: -4.35822179993114
Ch1_val: 42.43585979932951 Ch2_val: 34.9874729994472 Ch3_val: -4.125827399934812
Ch1_val: 44.08278179930349 Ch2_val: 34.42912859945602 Ch3_val: -4.1604257999342655
Ch1_val: 44.50289159929685 Ch2_val: 35.507053199438985 Ch3_val: -3.092836199951133
Ch1_val: 43.69110119930968 Ch2_val: 35.53335179943857 Ch3_val: -2.613991799958699
Ch1_val: 42.73662419932476 Ch2_val: 34.1708807994601 Ch3_val: -5.254886399916972
Ch1_val: 42.14097839933417 Ch2_val: 34.08460739946146 Ch3_val: -8.582724599864394
Ch1_val: 41.982105599336684 Ch2_val: 35.58544019943775 Ch3_val: -8.84688719986022
Ch1_val: 42.503816399328436 Ch2_val: 36.06170879943022 Ch3_val: -6.777056999892922
Ch1_val: 43.17568679931782 Ch2_val: 35.291926199442386 Ch3_val: -4.984618199921243
Ch1_val: 42.4303583993296 Ch2_val: 36.03750899943061 Ch3_val: -4.502275799928864
Ch1_val: 39.92264219936922 Ch2_val: 38.354075399394006 Ch3_val: -6.050744999904398
Ch1_val: 37.65501599940505 Ch2_val: 38.48181599939198 Ch3_val: -9.010943399857627
Ch1_val: 37.04642759941466 Ch2_val: 35.152642199444585 Ch3_val: -9.89107199984372
Ch1_val: 36.571876199422164 Ch2_val: 32.21988719949093 Ch3_val: -7.850465999875962
Ch1_val: 34.488403799455085 Ch2_val: 32.62164839948458 Ch3_val: -7.712485799878142
Ch1_val: 32.00259779949436 Ch2_val: 34.05570119946192 Ch3_val: -11.215064999822802
Ch1_val: 31.132422599508107 Ch2_val: 33.44755799947153 Ch3_val: -12.461179799803112
Ch1_val: 31.245853199506314 Ch2_val: 31.730771399498654 Ch3_val: -8.723057999862176
Ch1_val: 30.40820939951955 Ch2_val: 31.03355639950967 Ch3_val: -6.433076399898357
Ch1_val: 28.474165199550107 Ch2_val: 30.714824999514704 Ch3_val: -9.730672799846255
Ch1_val: 26.481449999581592 Ch2_val: 29.53720739953331 Ch3_val: -13.227496199791005
Ch1_val: 24.79611359960822 Ch2_val: 28.60448159954805 Ch3_val: -12.1075955998087
Ch1_val: 23.74938479962476 Ch2_val: 28.95253259954255 Ch3_val: -9.411305399851301
Ch1_val: 23.92663799962196 Ch2_val: 29.24305739953796 Ch3_val: -8.856490799860067
Ch1_val: 24.37285559961491 Ch2_val: 28.72398599954616 Ch3_val: -9.611549999848137
Ch1_val: 23.155774199634138 Ch2_val: 29.22521759953824 Ch3_val: -10.701304199830918
Ch1_val: 20.822671799671003 Ch2_val: 31.46641799950283 Ch3_val: -12.57088979980138
Ch1_val: 20.15302739968158 Ch2_val: 32.95071479947938 Ch3_val: -13.581175799785417
Ch1_val: 21.440195999661245 Ch2_val: 32.28628559948987 Ch3_val: -11.66643419981567
Ch1_val: 21.51502139966006 Ch2_val: 31.7910959994977 Ch3_val: -8.843802599860268