You can use the following methods to convert a NumPy matrix to an array:

Method 1: Use A1

my_array = my_matrix.A1

Method 2: Use ravel()

my_array = np.asarray(my_matrix).ravel()

Both methods return the same result, but the second method simply requires more typing.

The following examples show how to use each method in practice.

Example 1: Convert NumPy Matrix to Array Using A1

The following code shows how to use the to convert a NumPy matrix to an array:

import numpy as np

#create NumPy matrix with 3 columns and 5 rows
my_matrix = np.matrix(np.arange(15).reshape((5, 3)))

#view NumPy matrix
print(my_matrix)

[[ 0  1  2]
 [ 3  4  5]
 [ 6  7  8]
 [ 9 10 11]
 [12 13 14]]

#convert matrix to array
my_array = my_matrix.A1#view NumPy array
print(my_array)

[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14]

We can see that the NumPy matrix has been converted to an array with 15 values.

We can confirm that it is NumPy array by using the type() function:

#check type of my_array
type(my_array)

numpy.ndarray

It is indeed a NumPy array.

Example 2: Convert NumPy Matrix to Array Using ravel()

The following code shows how to use the function to convert a NumPy matrix to an array:

import numpy as np

#create NumPy matrix with 3 columns and 5 rows
my_matrix = np.matrix(np.arange(15).reshape((5, 3)))

#view NumPy matrix
print(my_matrix)

[[ 0  1  2]
 [ 3  4  5]
 [ 6  7  8]
 [ 9 10 11]
 [12 13 14]]

#convert matrix to array
my_array = np.asarray(my_matrix).ravel()

#view NumPy array
print(my_array)

[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14]

We can confirm that it is NumPy array by using the type() function:

#check type of my_array
type(my_array)

numpy.ndarray

It is indeed a NumPy array.

The following tutorials explain how to perform other common tasks in NumPy: