Numpy numpy.random.rand() Function

  1. Syntax of numpy.random.rand():
  2. Return
  3. Example Codes: numpy.random.rand() Method
  4. Example Codes: Specify Shape of Output Array numpy.random.rand() Method

Python Numpynumpy.random.rand() function generates an array of specified shape with random values.

Syntax of numpy.random.rand():

numpy.random.rand(d0, d1, ..., dn)

Parameters

d0, d1, ..., dn Integer. Represent the dimension of the output array from the random function. If no value is specified, a scalar value is returned.

Return

It returns a random array of specified shapes with random values.

Example Codes: numpy.random.rand() Method

import numpy as np

x = np.random.rand()
print(x)

Output:

0.6222151413197674

It generates a random number since no size is specified for the output array.

The range of generated output number lies between 0 and 1.

You might get different random numbers when you run the same code multiple times.

To generate the constant output, we fix the seed of np.random() function.

import numpy as np

np.random.seed(0)

x = np.random.rand()
print(x)

Output:

0.5488135039273248

It generates a constant output every time we run the function.

Example Codes: Specify Shape of Output Array numpy.random.rand() Method

To generate arrays of fixed size and shapes, we specify parameters which determine the shape of the output array in numpy.random.rand() function.

Generate 1-D Arrays With numpy.random.rand() Method

import numpy as np

np.random.seed(0)

x = np.random.rand(5)
print(x)

Output:

[0.5488135  0.71518937 0.60276338 0.54488318 0.4236548 ]

It generates a random 1-dimensional array with length 5 composed of random numbers.

The numbers in the here will also lie in the range (0,1).

Due to the fixed seed, the same random numbers are generated every time we run it.

If we need to generate numbers greater than 1, we can simply multiply the array by the desired range.

import numpy as np

np.random.seed(0)

x = np.random.rand(5)*10
print(x)

Output:

[5.48813504 7.15189366 6.02763376 5.44883183 4.23654799]

It generates random numbers ranging from 1 to 10.

Generate 2-D Arrays With numpy.random.rand() Method

import numpy as np

np.random.seed(0)

x = np.random.rand(2,3)
print("Array x:")
print(x)

print("\n Shape of Array x:")
print(x.shape)

Output:

Array x:
[[0.5488135  0.71518937 0.60276338]
 [0.54488318 0.4236548  0.64589411]]

 Shape of Array x:
(2, 3)

This generates 2-dimensional random array with 2 rows and 3 columns using numpy.random.rand() method.

Generate Higher Dimensional Arrays With numpy.random.rand() Method

import numpy as np

np.random.seed(0)

x = np.random.rand(2,3,2,3)
print("Array x:")
print(x)

print("\n Shape of Array x:")
print(x.shape)

Output:

Array x:
[[[[0.5488135  0.71518937 0.60276338]
   [0.54488318 0.4236548  0.64589411]]

  [[0.43758721 0.891773   0.96366276]
   [0.38344152 0.79172504 0.52889492]]

  [[0.56804456 0.92559664 0.07103606]
   [0.0871293  0.0202184  0.83261985]]]


 [[[0.77815675 0.87001215 0.97861834]
   [0.79915856 0.46147936 0.78052918]]

  [[0.11827443 0.63992102 0.14335329]
   [0.94466892 0.52184832 0.41466194]]

  [[0.26455561 0.77423369 0.45615033]
   [0.56843395 0.0187898  0.6176355 ]]]]

 Shape of Array x:
(2, 3, 2, 3)

This generates 4-dimensional random array with shape (2, 3, 2, 3) using numpy.random.rand() method.

Similarly, we can also generate any random arrays of any size using numpy.random.rand() method.

comments powered by Disqus