The numpy.repeat() function repeats elements of the array – arr. Syntax :
numpy.repeat(arr, repetitions, axis = None)
Parameters :
array : [array_like]Input array. repetitions : No. of repetitions of each array elements along the given axis. axis : Axis along which we want to repeat values. By default, it returns a flat output array.
Return :
An array with repetitions of array - arr elements as per repetitions, number of times we want to repeat arr
Code 1 :
Python
# Python Program illustrating # numpy.repeat() import numpy as geek
#Working on 1D arr = geek.arange( 5 )
print ("arr : \n", arr)
repetitions = 2
a = geek.repeat(arr, repetitions)
print ("\nRepeating arr 2 times : \n", a)
print ("Shape : ", a.shape)
repetitions = 3
a = geek.repeat(arr, repetitions)
print ("\nRepeating arr 3 times : \n", a)
# [0 0 0 ..., 4 4 4] means [0 0 0 1 1 1 2 2 2 3 3 3 4 4 4] # since it was long output, so it uses [ ... ] print ("Shape : ", a.shape)
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Output :
arr : [0 1 2 3 4] Repeating arr 2 times : [0 0 1 1 2 2 3 3 4 4] Shape : (10,) Repeating arr 3 times : [0 0 0 ..., 4 4 4] Shape : (15,)
Code 2 :
Python
# Python Program illustrating # numpy.repeat() import numpy as geek
arr = geek.arange( 6 ).reshape( 2 , 3 )
print ("arr : \n", arr)
repetitions = 2
print ("\nRepeating arr : \n", geek.repeat(arr, repetitions, 1 ))
print ("arr Shape : \n", geek.repeat(arr, repetitions).shape)
repetitions = 2
print ("\nRepeating arr : \n", geek.repeat(arr, repetitions, 0 ))
print ("arr Shape : \n", geek.repeat(arr, repetitions).shape)
repetitions = 3
print ("\nRepeating arr : \n", geek.repeat(arr, repetitions, 1 ))
print ("arr Shape : \n", geek.repeat(arr, repetitions).shape)
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Output :
arr : [[0 1 2] [3 4 5]] Repeating arr : [[0 0 1 1 2 2] [3 3 4 4 5 5]] arr Shape : (12,) Repeating arr : [[0 1 2] [0 1 2] [3 4 5] [3 4 5]] arr Shape : (12,) Repeating arr : [[0 0 0 ..., 2 2 2] [3 3 3 ..., 5 5 5]] arr Shape : (18,)
References : https://docs.scipy.org/doc/numpy/reference/generated/numpy.repeat.html Note : These codes won’t run on online IDE’s. Please run them on your systems to explore the working .