We can multiply two matrices with the function np.matmul(a,b). When we multiply two arrays of order (m*n) and (p*q ) in order to obtained matrix product then its output contains m rows and q columns where n is n==p is a necessary condition.
Syntax: numpy.matmul(x1, x2, /, out=None, *, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj])
To multiply two matrices take the row from first array and column of second array and multiply the corresponding elements. Then add the value for the final answer. Suppose there are two matrices A and B.
A = [[A00, A01],
[A10, A11]]
B = [[B00, B01],
[B10, B11]]
Then the product is calculated as shown below
A*B = [[(A00*B00 + A01*B10), (A00*B01 + A01*B11)],
[(A10*B00 + A11+B10), (A10*B01 + A11*B11)]]
Below is the implementation.
Python3
# Importing Library import numpy as np # Finding the matrix product arr1 = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) arr2 = np.array([[11, 12, 13], [14, 15, 16], [17, 18, 19]]) matrix_product = np.matmul(arr1, arr2) print("Matrix Product is ") print(matrix_product) print() arr1 = np.array([[2,2],[3,3]]) arr2 = np.array([[1,2,3],[4,5,6]]) matrix_product = np.matmul(arr1, arr2) print("Matrix Product is ") print(matrix_product) print() arr1 = np.array([[100,200],[300,400]]) arr2 = np.array([[1,2],[4,6]]) matrix_product = np.matmul(arr1, arr2) print("Matrix Product is ") print(matrix_product) |
Output:
Matrix Product is [[ 90 96 102] [216 231 246] [342 366 390]] Matrix Product is [[10 14 18] [15 21 27]] Matrix Product is [[ 900 1400] [1900 3000]]
