Let us see how to compute matrix multiplication with NumPy. We will be using the numpy.dot() method to find the product of 2 matrices.
For example, for two matrices A and B. A = [[1, 2], [2, 3]] B = [[4, 5], [6, 7]] So, A.B = [[1*4 + 2*6, 2*4 + 3*6], [1*5 + 2*7, 2*5 + 3*7] So the computed answer will be: [[16, 26], [19, 31]]
In Python numpy.dot() method is used to calculate the dot product between two arrays.
Example 1 : Matrix multiplication of 2 square matrices.
# importing the module import numpy as np # creating two matrices p = [[1, 2], [2, 3]] q = [[4, 5], [6, 7]] print("Matrix p :") print(p) print("Matrix q :") print(q) # computing product result = np.dot(p, q) # printing the result print("The matrix multiplication is :") print(result) |
Output :
Matrix p : [[1, 2], [2, 3]] Matrix q : [[4, 5], [6, 7]] The matrix multiplication is : [[16 19] [26 31]]
Example 2 : Matrix multiplication of 2 rectangular matrices.
# importing the module import numpy as np # creating two matrices p = [[1, 2], [2, 3], [4, 5]] q = [[4, 5, 1], [6, 7, 2]] print("Matrix p :") print(p) print("Matrix q :") print(q) # computing product result = np.dot(p, q) # printing the result print("The matrix multiplication is :") print(result) |
Output :
Matrix p : [[1, 2], [2, 3], [4, 5]] Matrix q : [[4, 5, 1], [6, 7, 2]] The matrix multiplication is : [[16 19 5] [26 31 8] [46 55 14]]
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