python – 沿给定轴乘以1d数组的numpy ndarray

发布时间：2020-12-16 23:18:43 所属栏目：Python 来源：网络整理

导读：看来我迷失在可能愚蠢的东西中. 我有一个n维numpy数组,我想将它与一个维度(可以改变！)的向量(1d数组)相乘. 举个例子,假设我想将第二个数组乘以第一个数组的0轴的1d数组,我可以这样做： a=np.arange(20).reshape((5,4))b=np.ones(5)c=a*b[:,np.newaxis] 很简

看来我迷失在可能愚蠢的东西中.
我有一个n维numpy数组,我想将它与一个维度(可以改变！)的向量(1d数组)相乘.
举个例子,假设我想将第二个数组乘以第一个数组的0轴的1d数组,我可以这样做：

a=np.arange(20).reshape((5,4))
b=np.ones(5)
c=a*b[:,np.newaxis]

很简单,但我想将这个想法扩展到n维(对于a,而b总是1d)和任何轴.换句话说,我想知道如何在正确的位置生成np.newaxis的切片.假设a是3d并且我想沿轴= 1乘以,我想生成正确给出的切片：

c=a*b[np.newaxis,:,np.newaxis]

即给定a(比如3)的维数,以及我想要乘以的轴(比如轴= 1),我如何生成并传递切片：

np.newaxis,np.newaxis

谢谢.

解决方法

解决方案代码

import numpy as np

# Given axis along which elementwise multiplication with broadcasting 
# is to be performed
given_axis = 1

# Create an array which would be used to reshape 1D array,b to have 
# singleton dimensions except for the given axis where we would put -1 
# signifying to use the entire length of elements along that axis  
dim_array = np.ones((1,a.ndim),int).ravel()
dim_array[given_axis] = -1

# Reshape b with dim_array and perform elementwise multiplication with 
# broadcasting along the singleton dimensions for the final output
b_reshaped = b.reshape(dim_array)
mult_out = a*b_reshaped

示例运行步骤的演示 –

In [149]: import numpy as np

In [150]: a = np.random.randint(0,9,(4,2,3))

In [151]: b = np.random.randint(0,(2,1)).ravel()

In [152]: whos
Variable   Type       Data/Info
-------------------------------
a          ndarray    4x2x3: 24 elems,type `int32`,96 bytes
b          ndarray    2: 2 elems,8 bytes

In [153]: given_axis = 1

现在,我们想沿给定的轴= 1执行元素乘法.让我们创建dim_array：

In [154]: dim_array = np.ones((1,int).ravel()
     ...: dim_array[given_axis] = -1
     ...: 

In [155]: dim_array
Out[155]: array([ 1,-1,1])

最后,重塑b&执行元素乘法：

In [156]: b_reshaped = b.reshape(dim_array)
     ...: mult_out = a*b_reshaped
     ...:

再次查看whos信息并特别注意b_reshaped& mult_out：

In [157]: whos
Variable     Type       Data/Info
---------------------------------
a            ndarray    4x2x3: 24 elems,96 bytes
b            ndarray    2: 2 elems,8 bytes
b_reshaped   ndarray    1x2x1: 2 elems,8 bytes
dim_array    ndarray    3: 3 elems,12 bytes
given_axis   int        1
mult_out     ndarray    4x2x3: 24 elems,96 bytes

（编辑：李大同）

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