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The NumPy package contains matlib module. This module contains all the functions in the numpy namespace that return matrices instead of ndarray objects. Below mentioned are most commonly used functions of this module:

FunctionDescription
matlib.empty() Returns a matrix of given shape and type, without initializing entries.
matlib.zeros() Returns a matrix of given shape and type, filled with zeros.
matlib.ones() Returns a matrix of given shape and type, filled with ones.
matlib.eye() Returns a matrix with ones on the diagonal and zeros elsewhere.
matlib.identity() Returns the square identity matrix of given size.
matlib.rand() Return a matrix of random values with given shape.
matlib.randn() Return a random matrix with data from the “standard normal” distribution.

Lets discuss these functions in detail:

numpy.matlib.empty() function

The numpy.matlib.empty() function returns a matrix of given shape and type, without initializing entries.

Syntax

numpy.matlib.empty(shape, dtype=None, order='C')

Parameters

shape Required. Specify shape of the matrix.
dtype Optional. Specify the desired data-type for the matrix.
order Optional. Specify whether to store the result. Two possible values are: C (C-style) and F (Fortran-style). Default: 'C'

Example:

The function is used to create a matrix of uninitialized (arbitrary) entries of specified shape.

import numpy as np
import numpy.matlib

mat = np.matlib.empty((2,2))
print(mat)

The output of the above code will be:

[[1.58262349e-316 0.00000000e+000]
 [6.21064510e+175 6.78850084e+199]]

numpy.matlib.zeros() function

The numpy.matlib.zeros() function returns a matrix of given shape and type, filled with zeros.

Syntax

numpy.matlib.zeros(shape, dtype=None, order='C')

Parameters

shape Required. Specify shape of the matrix.
dtype Optional. Specify the desired data-type for the matrix. Default: float
order Optional. Specify whether to store the result. Two possible values are: C (C-style) and F (Fortran-style). Default: 'C'

Example:

The function is used to create a matrix of zeros of specified shape.

import numpy as np
import numpy.matlib

mat = np.matlib.zeros((2,3))
print(mat)

The output of the above code will be:

[[ 0.  0.  0.]
 [ 0.  0.  0.]]

numpy.matlib.ones() function

The numpy.matlib.ones() function returns a matrix of given shape and type, filled with ones.

Syntax

numpy.matlib.ones(shape, dtype=None, order='C')

Parameters

shape Required. Specify shape of the matrix.
dtype Optional. Specify the desired data-type for the matrix. Default: float
order Optional. Specify whether to store the result. Two possible values are: C (C-style) and F (Fortran-style). Default: 'C'

Example:

The function is used to create a matrix of ones of specified shape.

import numpy as np
import numpy.matlib

mat = np.matlib.ones((2,3))
print(mat)

The output of the above code will be:

[[1. 1. 1.]
 [1. 1. 1.]]

numpy.matlib.eye() function

The numpy.matlib.eye() function returns a matrix with ones on the diagonal and zeros elsewhere.

Syntax

numpy.matlib.eye(n, M=None, k=0, dtype='float', order='C')

Parameters

n Required. Specify number of rows in the matrix.
M Optional. Specify number of columns in the matrix. Default is n.
k Optional. Specify index of the diagonal. 0 refers to the main diagonal, a positive value refers to an upper diagonal, and a negative value to a lower diagonal.
dtype Optional. Specify the desired data-type for the matrix. Default: float
order Optional. Specify whether to store the result. Two possible values are: C (C-style) and F (Fortran-style). Default: 'C'

Example:

In the below example, the function is used to fill the diagonal at index=1 with one and zero elsewhere.

import numpy as np
import numpy.matlib

mat = np.matlib.eye(n=3, M=4, k=1)
print(mat)

The output of the above code will be:

[[0. 1. 0. 0.]
 [0. 0. 1. 0.]
 [0. 0. 0. 1.]]

numpy.matlib.identity() function

The numpy.matlib.identity() function returns a square identity matrix of given size.

Syntax

numpy.matlib.identity(n, dtype=None)

Parameters

n Required. Specify the size of the returned identity matrix.
dtype Optional. Specify the desired data-type for the matrix. Default: float

Example:

The below example shows the usage of matlib.identity() function.

import numpy as np
import numpy.matlib

mat = np.matlib.identity(3, dtype=int)
print(mat)

The output of the above code will be:

[[1 0 0]
 [0 1 0]
 [0 0 1]]

numpy.matlib.rand() function

The numpy.matlib.rand() function returns a matrix of random values with given shape. The function creates a matrix of the given shape and propagate it with random samples from a uniform distribution over [0, 1).

Syntax

numpy.matlib.rand(*args)

Parameters

*args Required. Specify shape of the output. If given as N integers, each integer specifies the size of one dimension. If given as a tuple, this tuple gives the complete shape.

Example:

In the below example, the function is used to create a matrix of given shape containing random values from a uniform distribution over [0, 1).

import numpy as np
import numpy.matlib

mat = np.matlib.rand(3,2)
print(mat)

The possible output of the above code could be:

[[0.76220569 0.45832152]
 [0.2573741  0.16884502]
 [0.67076371 0.94206513]]

numpy.matlib.randn() function

The numpy.matlib.randn() function returns a matrix filled with random floats sampled from a univariate normal (Gaussian) distribution of mean 0 and variance 1.

Syntax

numpy.matlib.randn(*args)

Parameters

*args Required. Specify shape of the output. If given as N integers, each integer specifies the size of one dimension. If given as a tuple, this tuple gives the complete shape.

Example:

In the below example, matlib.randn() function is used to create a matrix of given shape containing random values from the standard normal distribution, N(0, 1).

import numpy as np
import numpy.matlib

mat = np.matlib.randn(3,3)
print(mat)

The possible output of the above code could be:

[[-0.48017485  1.19876658  1.05405775]
 [ 2.03861756  0.06356518 -0.40892882]
 [ 1.25324351  0.50041813  0.73766593]]