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)
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)
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 .
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