Numpy random_sample to get continuous uniform distribution of random number over an interval

We get continuous uniform random numbers over an interval ( below ).

dimension Int, optional , the dimension of returned array

Output is an array of numbers.

Example 1

import numpy as np
my_data=np.random.random_sample()
print(my_data) # 0.8541225764575974

my_data=np.random.random_sample(size=(2,3))

Output

[[0.48039485 0.87647483 0.02363604]
 [0.29335428 0.46199051 0.68764865]]

my_data=np.random.random_sample(size=(2,3,1))

Output

[[[0.8713458 ]
  [0.98421453]
  [0.69791198]]

 [[0.5539756 ]
  [0.71706405]
  [0.22790952]]]

# over a interval 5,8
import numpy as np
my_data=(8-5)*np.random.random_sample(size=(2,3))+5
print(my_data)

Output

[[6.65899659 5.75375084 7.45066966]
 [7.99360791 7.88499591 5.07648928]]

# over a interval -3,2
import numpy as np
my_data=(2-(-3))*np.random.random_sample(size=(2,3))-3
print(my_data)

Output

[[-2.16590208 -1.1939938  -0.95480836]
 [ 1.8298811   0.12518495 -1.02893354]]