如何在Python中读取具有32位浮点、64位浮点和另一个32位浮点的二进制文件

这是一个二进制文件，结构非常简单，便于学习。每个寄存器有3个数字：32位浮点、64位浮点和另一个32位浮点。如果以十六进制格式将其转储到屏幕上，则如下所示：

0000000: 0800 0000 0000 0000 0000 0000 0800 0000  ................
0000010: 0800 0000 0000 0000 0000 f03f 0800 0000  ...........?....
0000020: 0800 0000 182d 4454 fb21 0940 0800 0000  .....-DT.!.@....

（……）

如果我手动复制二进制格式的第三行，我可以将其读入三个变量：

import struct
data = b'\x08\x00\x00\x00\x18-DT\xfb!\t@\x08\x00\x00\x00'
l1, value, l2 = struct.unpack("<idi", data)
# (8, 3.141592653589793, 8)

---

在这里不起作用。

以二进制模式读取文件：

def read_stuff(fname='test_file.binary'):
    with open(fname, mode='rb') as f:
        while True:
            data = f.read(16)
            if len(data) < 16:
                # end of file
                return
            yield struct.unpack("<idi", data)

---

你可以试试这个方法

# includes core parts of numpy, matplotlib
import matplotlib.pyplot as plt
import numpy as np
# include scipy's signal processing functions
import scipy.signal as signal


# practice reading in complex values stored in a file
# Read in data that has been stored as raw I/Q interleaved 32-bit float samples
dat = np.fromfile("iqsamples.float32", dtype="float32")
# Look at the data. Is it complex?


dat = dat[0::2] + 1j*dat[1::2]
print(type(dat))
print(dat)

# # Plot the spectogram of this data
plt.specgram(dat, NFFT=1024, Fs=1000000)
plt.title("PSD of 'signal' loaded from file")
plt.xlabel("Time")
plt.ylabel("Frequency")
plt.show()  # if you've done this right, you should see a fun surprise here!

---

这是整个文件还是文件中有更多数据？如果这三个变量的值超过了这个值，那么您希望从这三个变量中得到什么？每个文件有几百万个寄存器（或行，或者您如何命名）。在这一条语句中缺少

If

？@BillBell修复，谢谢。请随时直接编辑next time.def read_stuff（fname='test_file.binary'）语法错误：语法无效，它指向右括号。隐秘的python错误消息。两小时后对着屏幕大喊大叫。它应该很简单。

for l1, value, l2 in read_stuff():
    ...

# includes core parts of numpy, matplotlib
import matplotlib.pyplot as plt
import numpy as np
# include scipy's signal processing functions
import scipy.signal as signal


# practice reading in complex values stored in a file
# Read in data that has been stored as raw I/Q interleaved 32-bit float samples
dat = np.fromfile("iqsamples.float32", dtype="float32")
# Look at the data. Is it complex?


dat = dat[0::2] + 1j*dat[1::2]
print(type(dat))
print(dat)

# # Plot the spectogram of this data
plt.specgram(dat, NFFT=1024, Fs=1000000)
plt.title("PSD of 'signal' loaded from file")
plt.xlabel("Time")
plt.ylabel("Frequency")
plt.show()  # if you've done this right, you should see a fun surprise here!