沿numpy的一个轴进行数据分箱 [英] Binning of data along one axis in numpy

问题描述

我有一个很大的二维数组arr，我想使用numpy在第二个轴上进行装箱.因为np.histogram展平了我当前使用的for循环数组:

I have a large two dimensional array arr which I would like to bin over the second axis using numpy. Because np.histogram flattens the array I'm currently using a for loop:

import numpy as np

arr = np.random.randn(100, 100)

nbins = 10
binned = np.empty((arr.shape[0], nbins))

for i in range(arr.shape[0]):
    binned[i,:] = np.histogram(arr[i,:], bins=nbins)[0]

我觉得在numpy中应该有一种更直接，更有效的方法来做到这一点，但我没有找到一个.

I feel like there should be a more direct and more efficient way to do that within numpy but I failed to find one.

推荐答案

您可以使用 np.apply_along_axis :

You could use np.apply_along_axis:

x = np.array([range(20), range(1, 21), range(2, 22)])

nbins = 2
>>> np.apply_along_axis(lambda a: np.histogram(a, bins=nbins)[0], 1, x)
array([[10, 10],
       [10, 10],
       [10, 10]])

主要优点(如果有的话)是稍微短一点，但是我不希望性能有太大提高.组装每行结果的效率可能略高.

The main advantage (if any) is that it's slightly shorter, but I wouldn't expect much of a performance gain. It's possibly marginally more efficient in the assembly of the per-row results.

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