apply numpy.histogram to multidimensional array

Question

I want to apply numpy.histogram() to a multi-dimensional array along an axis.

Say, for example I have a 2D array and I want to apply histogram() along axis=1.

Code:

import numpy

array = numpy.array([[0.6, 0.7, -0.3, 1.0, -0.8], [0.2, -1.0, -0.5, 0.5, 0.8], 
                    [0.25, 0.3, -0.1, -0.8, 1.0]])
bins = [-1.0, -0.5, 0, 0.5, 1.0, 1.0]
hist, bin_edges = numpy.histogram(array, bins)
print(hist)

Output:

[3 3 3 4 2]

Expected Output:

[[1 1 0 2 1],
 [1 1 1 2 0],
 [1 1 2 0 1]]

How can I get my expected output?

I tried to use the solution suggested in this post, but it doesn't get me to the expected output.

you can use apply_along_axis as suggested in this post stackoverflow.com/a/18871667/8366805 — meTchaikovsky
– meTchaikovsky, Commented Oct 9, 2020 at 7:47

Daniel F · Accepted Answer · 2017-08-02 06:36:11Z

0

For n-d cases, you can do this with np.histogram2d just by making a dummy x-axis (i):

def vec_hist(a, bins):
    i = np.repeat(np.arange(np.product(a.shape[:-1]), a.shape[-1]))
    return np.histogram2d(i, a.flatten(), (a.shape[0], bins)).reshape(a.shape[:-1], -1)

Output

vec_hist(array, bins)
Out[453]: 
(array([[ 1.,  1.,  0.,  2.,  1.],
        [ 1.,  1.,  1.,  2.,  0.],
        [ 1.,  1.,  2.,  0.,  1.]]),
 array([ 0.        ,  0.66666667,  1.33333333,  2.        ]),
 array([-1.       , -0.5      ,  0.       ,  0.5      ,  0.9999999,  1.       ]))

For histograms over arbitrary axis, you'll probably need to create i using np.meshgrid and np.ravel_multi_axis and then use that to reshape the resulting histogram.

edited Aug 2, 2017 at 6:36

answered Jul 28, 2017 at 7:11

Daniel F

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5 Comments

Wasi Ahmad Over a year ago

thanks for your answer. I appreciate. can you give me an example in case of having n-dimensional array? your solution works for 2d case.

Daniel F Over a year ago

Expanded it to n-d, but it only works if the histogram is over the last axis. And implementation over arbitrary axes will need a lot more work.

Wasi Ahmad Over a year ago

can you give me an example? In my case, I need to apply histogram over the last axis.

Daniel F Over a year ago

Fixed some errors, should hopefully work now for multidimensional.

Cunningham Over a year ago

Not working anymore. See my answer.

Cunningham · Accepted Answer · 2024-01-02 18:02:10Z

Numpy code changed and the answer proposed by Daniel F is not working anymore. Here is a simplified version for 2D arrays:

def vec_hist(a, bins):
    i = np.tile(np.arange(a.shape[0]), (a.shape[1], 1)).T.flatten()
    H, _, _ = np.histogram2d(i, a.flatten(), (a.shape[0], bins))
    return H

So basically first we build a list of coordinates "i" that is simply the index of the data along the last axis. Then we flatten it, along with the data array "a" before sending it to np.histogram2d. The bin argument of histogram2d are the bin the dummy and the actually desired dimension.

Code:

array = np.array([[0.6, 0.7, -0.3, 1.0, -0.8], 
                  [0.2, -1.0, -0.5, 0.5, 0.8], 
                  [0.25, 0.3, -0.1, -0.8, 1.0]])
bins = [-1.0, -0.5, 0, 0.5, 1.0, 1.0]
vec_hist(array, bins)

Output

array([[1., 1., 0., 2., 1.],
       [1., 1., 1., 2., 0.],
       [1., 1., 2., 0., 1.]])

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