numpy 元素乘向量和矩阵具有相同的行数

Question

I have a matrix and a vector that both have n rows. I would like to have the kth row of the matrix be elementwise multiplied by the kth element in my vector, without a for loop. I have already tried np,multiply. and it doesn't work.

Is this possible? Thanks for your help.

Answer 1

numpy.multiply can do it. It has matrix multiply semantics so you need to transpose the matrix. Is below what you were looking for?

In [19]: >>> x1 = np.arange(9.0).reshape((3, 3))

In [20]: >>> x2 = np.arange(3.0)

In [21]: np.multiply(x1.T, x2.T).T
Out[21]:
array([[ 0.,  0.,  0.],
       [ 3.,  4.,  5.],
       [12., 14., 16.]])