Question

I have a 2d array and a 1d array and I need to multiply each element in the 1d array x each element in the 2d array columns. It’s basically a matrix multiplication but numpy won’t allow matrix multiplication because of the 1d array. This is because matrices are inherently 2d in numpy. How can I get around this problem? This is an example of what I want:

FrMtx = np.zeros(shape=(24,24)) #2d array
elem = np.zeros(24, dtype=float) #1d array
Result = np.zeros(shape=(24,24), dtype=float) #2d array to store results

some_loop to increment i:
    some_other_loop to increment j:
        Result[i][j] = (FrMtx[i][j] x elem[j])

Numerous efforts have given me errors such as arrays used as indices must be of integer or boolean type

Answer 1

Due to the NumPy broadcasting rules, a simple

Result = FrMtx * elem

Will give the desired result.