向量点乘 (dot) 和对应分量相乘 (multiply) :
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>>> a array([ 1 , 2 , 3 ]) >>> b array([ 1. , 1. , 1. ]) >>> np.multiply(a,b) array([ 1. , 2. , 3. ]) >>> np.dot(a,b) 6.0 |
矩阵乘法 (dot) 和对应分量相乘 (multiply) :
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>>> c matrix([[ 1 , 2 , 3 ]]) >>> d matrix([[ 1. , 1. , 1. ]]) >>> np.multiply(c,d) matrix([[ 1. , 2. , 3. ]]) >>> np.dot(c,d) Traceback (most recent call last): File "<stdin>" , line 1 , in <module> ValueError: shapes ( 1 , 3 ) and ( 1 , 3 ) not aligned: 3 (dim 1 ) ! = 1 (dim 0 ) |
写代码过程中,*表示对应分量相乘 (multiply) :
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>>> a * b array([ 1. , 2. , 3. ]) >>> c * d Traceback (most recent call last): File "<stdin>" , line 1 , in <module> File "C:\ProgramData\Anaconda3\lib\site-packages\numpy\matrixlib\defmatrix.py" , line 343 , in __mul__ return N.dot( self , asmatrix(other)) ValueError: shapes ( 1 , 3 ) and ( 1 , 3 ) not aligned: 3 (dim 1 ) ! = 1 (dim 0 ) |
以上这篇对python中的乘法dot和对应分量相乘multiply详解就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持服务器之家。
原文链接:https://blog.csdn.net/ztf312/article/details/76222233