Apart from element-wise calculations using the np.dot() function, you can also apply multiplications to your two-dimensional arrays based on matrix calculations, such as vector-matrix and matrix-matrix multiplications:
In: import numpy as np M = np.arange(5*5, dtype=float).reshape(5,5) MOut: array([[ 0., 1., 2., 3., 4.], [ 5., 6., 7., 8., 9.], [ 10., 11., 12., 13., 14.], [ 15., 16., 17., 18., 19.], [ 20., 21., 22., 23., 24.]])
As an example, we will create a 5 x 5 two-dimensional array of ordinal numbers from 0 to 24:
- We will define a vector of coefficients and an array column stacking the vector and its reverse:
In: coefs = np.array([1., 0.5, 0.5, 0.5, 0.5]) coefs_matrix = np.column_stack((coefs,coefs[::-1])) print (coefs_matrix) ...
