Answers for "np random shuffle"

Python

np random seed

>>> import numpy as np
>>> 
>>> np.random.seed(0)
>>> 
>>> np.random.rand(3)
array([0.5488135 , 0.71518937, 0.60276338])
>>> np.random.rand(3)
array([0.54488318, 0.4236548 , 0.64589411])
>>> 
>>> 
>>> np.random.seed(1)
>>> 
>>> np.random.rand(3)
array([4.17022005e-01, 7.20324493e-01, 1.14374817e-04])
>>> np.random.rand(3)
array([0.30233257, 0.14675589, 0.09233859])
>>> 
>>> 
>>> np.random.seed(0)
>>> 
>>> np.random.rand(3)
array([0.5488135 , 0.71518937, 0.60276338])
>>> np.random.rand(3)
array([0.54488318, 0.4236548 , 0.64589411])

Posted by: Guest on October-28-2020

Source

randomly shuffle array python

import random
l = list(range(5))
print(l)
# [0, 1, 2, 3, 4]

lr = random.sample(l, len(l))
print(lr)
# [3, 2, 4, 1, 0]

print(l)
# [0, 1, 2, 3, 4]

Posted by: Guest on June-17-2020

Source

Python shuffle array

import random
new_array = random.sample( array, len(array) )

Posted by: Guest on July-21-2021

Source

numpy randomly swap lines

>>> X = np.random.random((6, 2))
>>> X
array([[ 0.9818058 ,  0.67513579],
       [ 0.82312674,  0.82768118],
       [ 0.29468324,  0.59305925],
       [ 0.25731731,  0.16676408],
       [ 0.27402974,  0.55215778],
       [ 0.44323485,  0.78779887]])

>>> np.random.shuffle(X)
>>> X
array([[ 0.9818058 ,  0.67513579],
       [ 0.44323485,  0.78779887],
       [ 0.82312674,  0.82768118],
       [ 0.29468324,  0.59305925],
       [ 0.25731731,  0.16676408],
       [ 0.27402974,  0.55215778]])

Posted by: Guest on November-27-2020

Source

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