Matrix multiply two 1-D numpy arrays

Question

I have a two numpy 1-D arrays: a and b .

a is of shape (10,) b is of shape (16,).

I want to make a have the shape (10,1) and b to have the shape (16,1) to matrix multiply them as so: np.matmul(a, bT).

If successful, this should result in a (10,16) 2-D array. Does anyone know how to do this?

Answer 1

IIUC:

In [47]: a = np.arange(10)

In [48]: b = np.arange(16)

In [49]: a[:,None] * b
Out[49]:
array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
       [  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,  14,  15],
       [  0,   2,   4,   6,   8,  10,  12,  14,  16,  18,  20,  22,  24,  26,  28,  30],
       [  0,   3,   6,   9,  12,  15,  18,  21,  24,  27,  30,  33,  36,  39,  42,  45],
       [  0,   4,   8,  12,  16,  20,  24,  28,  32,  36,  40,  44,  48,  52,  56,  60],
       [  0,   5,  10,  15,  20,  25,  30,  35,  40,  45,  50,  55,  60,  65,  70,  75],
       [  0,   6,  12,  18,  24,  30,  36,  42,  48,  54,  60,  66,  72,  78,  84,  90],
       [  0,   7,  14,  21,  28,  35,  42,  49,  56,  63,  70,  77,  84,  91,  98, 105],
       [  0,   8,  16,  24,  32,  40,  48,  56,  64,  72,  80,  88,  96, 104, 112, 120],
       [  0,   9,  18,  27,  36,  45,  54,  63,  72,  81,  90,  99, 108, 117, 126, 135]])

Answer 2

You need to explicitly use reshape . bT and b.transpose() do not do anything meaningful for 1D arrays:

a = np.arange(10)
b = np.arange(16)
c = a.reshape(10, 1) @ b.reshape(1, 16)

c.shape will now be (10, 16) , as expected.

Answer 3

You can use reshape method.

import numpy as np

a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]).reshape((10, 1))
b = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]).reshape((16, 1))
c = np.matmul(a, b.T)
print(c.shape)