Question

我有以下代码

import numpy as np
import sys

def barycenter( arr, axis=0 ) :
    bc = np.mean( arr, axis, keepdims=False )
    print( "src shape:", arr.shape, ", **** trg shape:", bc.shape, "****" )
    sys.stdout.flush()
    return bc

a = np.array([[[0.1, 0.2, 0.3], [0.2, 0.3, 0.4]],
              [[0.4, 0.4, 0.4], [0.7, 0.6, 0.8]]], np.float)

e = barycenter( a, 2 )
print( "direct application =", e, "**** (trg shape =", e.shape, ") ****\n" )
f = np.apply_over_axes( barycenter, a, 2 )
print( "application through apply_over_axes =", f, "**** (trg shape =", f.shape, ") ****\n" )

产生以下输出

src shape: (2, 2, 3) , **** trg shape: (2, 2) ****
direct application = [[ 0.2  0.3]
 [ 0.4  0.7]] **** (trg shape = (2, 2) ) ****

src shape: (2, 2, 3) , **** trg shape: (2, 2) ****
application through apply_over_axes = [[[ 0.2]
  [ 0.3]]

 [[ 0.4]
  [ 0.7]]] **** (trg shape = (2, 2, 1) ) ****

因此函数barycenter的返回值与apply_over_axes( barycenter, ...获得的值不同。

为什么会这样？

Answer 1

结果直接来自doc：

func被称为res = func（a，axis），其中axis是第一个元素轴。函数调用的结果res必须相同尺寸为一个或一个以下的尺寸。如果res的维度少一个比a，在轴之前插入尺寸。然后调用func 对轴中的每个轴重复，以res作为第一个参数。

您的func将维度减少1，因此apply_over_axes会插入维度。

numpy apply_over_axes强制keepdims = True？

1 个答案: