The matmul()
method is used to perform matrix multiplication in NumPy.
Example
import numpy as np
# create two matrices
matrix1 = np.array([[1, 2], [3, 4]])
matrix2 = np.array([[5, 6], [7, 8]])
# perform matrix multiplication using matmul()
result = np.matmul(matrix1, matrix2)
print(result)
'''
Output:
[[19 22]
[43 50]]
'''
matmul() Syntax
The syntax of matmul()
is:
numpy.matmul(first_matrix, second_matrix, out=None)
matmul() Arguments
The matmul()
method takes the following arguments:
first_matrix
- represents the first matrix we want to multiplysecond_matrix
- represents the second matrix we want to multiplyout
(optional) - allows us to specify a matrix where the result will be stored
matmul() Return Value
The matmul()
method returns the matrix product of the input arrays.
Example 1: Multiply Two Matrices
import numpy as np
# create two matrices
matrix1 = np.array([[1, 3], [5, 7]])
matrix2 = np.array([[2, 6], [4, 8]])
# calculate the dot product of the two matrices
result = np.matmul(matrix1, matrix2)
print("matrix1 x matrix2: \n", result)
Output
matrix1 x matrix2: [[14 30] [38 86]]
Note: We can only multiply two matrices when they have a common dimension size. For example, For A = (M x N)
and B = (N x K)
when we multiply, C = A * B
the resulting matrix is of size C = (M x K)
.
Example 2: Use of out Argument in matmul()
import numpy as np
# create two matrices
matrix1 = np.array([[1, 2], [3, 4]])
matrix2 = np.array([[5, 6], [7, 8]])
# create an output array
result = np.zeros((2, 2), dtype=int)
# perform matrix multiplication using matmul() and store the output in the result array
np.matmul(matrix1, matrix2, out=result)
print(result)
Output
[[19 22] [43 50]]
In this example, we created an output array called result using np.zeros() with the desired shape (2, 2) and data type int
.
We then passed this result array as the out
parameter in np.matmul()
.
The matrix multiplication is computed and stored in the result array.