NumPy matrix()

import numpy as np

# create  2-D array
array1 = [[1, 2], [3, 4]]  

# use of matrix() to create matrix
result = np.matrix(array1)

print(result)

'''
Output:

[[1 2]
 [3 4]]
'''

matrix() Syntax

The syntax of matrix() is:

numpy.matrix(data, dtype=None, copy=True)

matrix() Arguments

The matrix() method takes the following arguments:

• data - input data used to create the matrix
• dtype (optional) - data type of the matrix
• copy (optional) - determines whether a copy of data should be made or not

matrix() Return Value

The matrix() method returns a matrix object from an array-like object.

Example 1: Create a Matrix

import numpy as np

# create a list
array1 = [[1, 2, 3], 
                [4, 5, 6], 
                [7, 8, 9]] 

# use matrix() to create a matrix
result = np.matrix(array1, dtype = int)

print(result)

Output

[[1 2 3]
 [4 5 6]
 [7 8 9]]

If unspecified, the default dtype is float.

Example 2: Use of copy Argument in matrix()

import numpy as np

# create a 2-D array
array1 = [[1, 2], [3, 4]] 
  
# create matrix with default copy=True 
matrix1 = np.matrix(array1)  

# modify the original data
array1[0][0] = 5

# create matrix with copy=False
matrix2 = np.matrix(array1, copy=False)  

print("Matrix with copy=True:")
print(matrix1)

print("Matrix with copy=False:")
print(matrix2)

Output

Matrix with copy=True:
[[1 2]
 [3 4]]
Matrix with copy=False:
[[5 2]
 [3 4]]

In the above example, when creating matrices using matrix() with copy=True, a copy of the data is made, resulting in a separate matrix.

With copy=False, the matrix shares the data with the original object. Modifying the original data affects the matrix.