向量点乘 (dot) 和对应分量相乘 (multiply) :
> 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) :
> 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) :
> 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)
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