CODEWITHSUNDEEP
pythonnumpy
Luca
Luca

Reputation: 10996

numpy write the permuted version of the array

I have to dump the contents of a numpy ndarray to a binary file which is going to be read by a third party program. However, what I want to do is write the contents of a permuted axes. As an example, I have something like:

import numpy as np
x = np.random.rand(3, 3, 3)

a = np.transpose(x, (1, 0, 2))
a.tofile("a.bin")
x.tofile("x.bin")

In both the cases, the outputted files are the same. Is there a transpose like operation which willa ctually move the contents of the array around rather than just swap the stride and dimensions? This way the raw content would be serialized in the order that I need.

Upvotes: 2

Views: 66

Answers (2)

AGN Gazer
AGN Gazer

Reputation: 8378

I cannot reproduce your findings: I get different arrays:

In [11]: np.fromfile('a.bin').reshape((3,3,3))
Out[11]: 
array([[[0.95499073, 0.53044188, 0.31122484],
        [0.44293225, 0.23932913, 0.13954034],
        [0.08992127, 0.59397388, 0.72471928]],

       [[0.43503453, 0.15910105, 0.10589887],
        [0.39610877, 0.68784233, 0.87956587],
        [0.89785046, 0.64688383, 0.40787343]],

       [[0.91490793, 0.31428658, 0.85234109],
        [0.36403572, 0.99601086, 0.46086401],
        [0.43524914, 0.85182394, 0.01254642]]])

In [12]: np.fromfile('x.bin').reshape((3,3,3))
Out[12]: 
array([[[0.95499073, 0.53044188, 0.31122484],
        [0.43503453, 0.15910105, 0.10589887],
        [0.91490793, 0.31428658, 0.85234109]],

       [[0.44293225, 0.23932913, 0.13954034],
        [0.39610877, 0.68784233, 0.87956587],
        [0.36403572, 0.99601086, 0.46086401]],

       [[0.08992127, 0.59397388, 0.72471928],
        [0.89785046, 0.64688383, 0.40787343],
        [0.43524914, 0.85182394, 0.01254642]]])

Without reshape:

In [22]: np.fromfile('a.bin')
Out[22]: 
array([0.95499073, 0.53044188, 0.31122484, 0.44293225, 0.23932913,
       0.13954034, 0.08992127, 0.59397388, 0.72471928, 0.43503453,
       0.15910105, 0.10589887, 0.39610877, 0.68784233, 0.87956587,
       0.89785046, 0.64688383, 0.40787343, 0.91490793, 0.31428658,
       0.85234109, 0.36403572, 0.99601086, 0.46086401, 0.43524914,
       0.85182394, 0.01254642])

In [23]: np.fromfile('x.bin')
Out[23]: 
array([0.95499073, 0.53044188, 0.31122484, 0.43503453, 0.15910105,
       0.10589887, 0.91490793, 0.31428658, 0.85234109, 0.44293225,
       0.23932913, 0.13954034, 0.39610877, 0.68784233, 0.87956587,
       0.36403572, 0.99601086, 0.46086401, 0.08992127, 0.59397388,
       0.72471928, 0.89785046, 0.64688383, 0.40787343, 0.43524914,
       0.85182394, 0.01254642])

My version of numpy and Python are:

In [21]: import sys
    ...: print(sys.version)
    ...: print("\nNumpy version: " + np.__version__)
    ...: 
2.7.15 |Anaconda, Inc.| (default, May  1 2018, 18:37:05) 
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]

Numpy version: 1.14.5

I also tried a different environment with the same result:

In [1]: import sys
   ...: import numpy as np
   ...: print(sys.version)
   ...: print(np.__version__)
   ...: 
3.6.5 |Anaconda, Inc.| (default, Apr 26 2018, 08:42:37) 
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]
1.13.3

In [2]: x = np.random.rand(3, 3, 3)
   ...: a = np.transpose(x, (1, 0, 2))
   ...: a.tofile("a.bin")
   ...: x.tofile("x.bin")
   ...: 

In [3]: np.fromfile('a.bin').reshape((3,3,3))
Out[3]: 
array([[[ 0.7628757 ,  0.5117887 ,  0.85286206],
        [ 0.27096479,  0.5056376 ,  0.14519906],
        [ 0.9517039 ,  0.92225717,  0.85885034]],

       [[ 0.57380259,  0.74694459,  0.19207375],
        [ 0.50738877,  0.33581015,  0.57100872],
        [ 0.54989565,  0.35004858,  0.9527302 ]],

       [[ 0.94359803,  0.6223541 ,  0.57774136],
        [ 0.92983442,  0.98074324,  0.62467311],
        [ 0.49712549,  0.73399765,  0.56790972]]])

In [4]: np.fromfile('x.bin').reshape((3,3,3))
Out[4]: 
array([[[ 0.7628757 ,  0.5117887 ,  0.85286206],
        [ 0.57380259,  0.74694459,  0.19207375],
        [ 0.94359803,  0.6223541 ,  0.57774136]],

       [[ 0.27096479,  0.5056376 ,  0.14519906],
        [ 0.50738877,  0.33581015,  0.57100872],
        [ 0.92983442,  0.98074324,  0.62467311]],

       [[ 0.9517039 ,  0.92225717,  0.85885034],
        [ 0.54989565,  0.35004858,  0.9527302 ],
        [ 0.49712549,  0.73399765,  0.56790972]]])

Upvotes: 2

Parth Sharma
Parth Sharma

Reputation: 29

I think you just need to use numpy's swapaxes.

import numpy as np
x = np.random.rand(3, 3)
a = np.swapaxes(x,0,1)
a.tofile("a.bin")
x.tofile("x.bin")

Hope this helps!

Upvotes: 1

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