python - R readBin 与 Python 结构

Question

我正在尝试使用 Python 读取二进制文件。其他人已使用以下代码使用 R 读入数据:

x <- readBin(webpage, numeric(), n=6e8, size = 4, endian = "little")
      myPoints <- data.frame("tmax" = x[1:(length(x)/4)],
                             "nmax" = x[(length(x)/4 + 1):(2*(length(x)/4))],
                             "tmin" = x[(2*length(x)/4 + 1):(3*(length(x)/4))],
                             "nmin" = x[(3*length(x)/4 + 1):(length(x))])

使用 Python，我正在尝试以下代码:

import struct

with open('file','rb') as f:
    val = f.read(16)
    while val != '':
        print(struct.unpack('4f', val))
        val = f.read(16) 

我得出的结果略有不同。例如，R 中的第一行返回 4 列，分别为 -999.9、0、-999.0、0。Python 为所有四列返回 -999.0(下图)。

Python 输出:

R输出:

我知道它们使用一些 [] 代码按文件的长度进行切片，但我不知道在 Python 中究竟如何做到这一点，我也不明白为什么它们做这个。基本上，我想重新创建 R 在 Python 中所做的事情。

如果需要，我可以提供更多的任一代码库。我不想被不必要的代码淹没。

Answer 1

从R代码推导，二进制文件首先包含一定数量的tmax，然后是相同数量的nmax，然后是tmin 和 nmin。代码所做的是读取整个文件，然后使用切片将其分成 4 个部分(tmax、nmax 等)。

在 python 中做同样的事情:

import struct

# Read entire file into memory first. This is done so we can count
# number of bytes before parsing the bytes. It is not a very memory
# efficient way, but it's the easiest. The R-code as posted wastes even
# more memory: it always takes 6e8 * 4 bytes (~ 2.2Gb) of memory no
# matter how small the file may be.
#
data = open('data.bin','rb').read()

# Calculate number of points in the file.  This is 
# file-size / 16, because there are 4 numeric()'s per
# point, and they are 4 bytes each.
#
num = int(len(data) / 16)

# Now we know how much there are, we take all tmax numbers first, then
# all nmax's, tmin's and lastly all nmin's.

# First generate a format string because it depends on the number points
# there are in the file. It will look like: "fffff"
#
format_string = 'f' * num

# Then, for cleaner code, calculate chunk size of the bytes we need to 
# slice off each time.
#
n = num * 4     # 4-byte floats

# Note that python has different interpretation of slicing indices
# than R, so no "+1" is needed here as it is in the R code.
#
tmax = struct.unpack(format_string, data[:n])
nmax = struct.unpack(format_string, data[n:2*n])
tmin = struct.unpack(format_string, data[2*n:3*n])
nmin = struct.unpack(format_string, data[3*n:])

print("tmax", tmax)
print("nmax", nmax)
print("tmin", tmin)
print("nmin", nmin)

如果目标是将此数据结构化为点列表(？)，如 (tmax,nmax,tmin,nmin)，则将其附加到代码中:

print()
print("Points:")

# Combine ("zip") all 4 lists into a list of (tmax,nmax,tmin,nmin) points.
# Python has a function to do this at once: zip()
#
i = 0
for point in zip(tmax, nmax, tmin, nmin):
    print(i, ":", point)
    i += 1