JIYIK CN >

This tutorial will introduce methods for shifting NumPy arrays.

np.roll()NumPy Shift Arrays Using the

If we want to shift the elements of a NumPy array right or left, we can use the numpy.roll() method in Python. The roll() numpy.roll()method is used to roll the elements of an array along the specified axis. It accepts the array and the number of positions by which we want to shift the elements of the array and returns the shifted array. If we want to shift the elements to the right, we have to use a positive integer as the shift value. If we want to shift the elements to the left, we have to specify a negative shift value. The following code example shows how to numpy.roll()shift the elements of an array using the roll() method.

import numpy as np

array = np.array([1, 2, 3, 4, 5])

array_new = np.roll(array, 3)
print(array_new)

Output:

[3 4 5 1 2]

We first np.array()created the array using the function. Then we np.roll()shifted the elements to the right using the function and stored the resulting array in array_new.

NumPy Shift Array and Slicing Methods in Python

If we want to shift elements to the right or left and replace the shifted indices with constant values, we have to use array slicing method in Python. We can create a new empty array just like the original array. If the shift value is positive, we fill the left side of the array with the constant value, and if the shift value is negative, we fill the right side of the array with the constant value. Then we can fill the remaining indices of the new array with the values ​​from the original array. The following code example shows how to shift the elements of an array using array slicing method.

import numpy as np

array = np.array([1, 2, 3, 4, 5])
num = -3
fill_value = 0


def shift(arr, num, fill_value):
    result = np.empty_like(arr)
    if num > 0:
        result[:num] = fill_value
        result[num:] = arr[:-num]
    elif num < 0:
        result[num:] = fill_value
        result[:num] = arr[-num:]
    else:
        result[:] = arr
    print(result)


shift(array, num, fill_value)

Output:

[4 5 0 0 0]

We defined the function shift()that shifts the elements of an array to the left by three positions using the array slicing method in the code above. We first np.array()created our original array using the shift_by method. We then specified the number of indices we wanted to shift the array elements by numand the constant value we wanted to replace all the shifted indices with fill_value. Finally, we passed these values ​​to shift()the shift_by function, which np.empty_like(arr)created a new array using the shift_by function resultjust like our original array, stored the shifted elements, and printed the shifted array.

NumPy Shift Arrays scipy.ndimage.interpolationwith Shift function in Python libraryshift()

scipy.ndimage.interpolationThe shift() method in the library is used to shift an array using the spline interpolation method in Python. Unlike numpy.roll()the method, the shift shift()() method can shift an array and replace the shifted indexes with the specified constant value at the same time. shift()The shift() function takes as input parameters the original array, the number of indexes we want to shift, and the constant value we want to replace with the shifted indexes, and returns the shifted array where each shifted index is replaced with the specified constant value. The following code example shows us how to shift()shift the elements of an array using the shift() function.

import numpy as np
from scipy.ndimage.interpolation import shift

array = np.array([1, 2, 3, 4, 5])

result = shift(array, 3, cval=0)
print(result)

Output:

[0 0 0 1 2]

We shifted the elements of by three positions to the right and replaced the shifted indices with using the shift function arrayin the code above . We first created our array using the shift function. We then shifted to the right by positions using the shift function and replaced the first three indices of the original array with the constant value . We stored the output of the shift function in the array. Finally, we printed the values ​​in the array.shift()0np.array()array30shift()resultresult

All of these methods work fine. If we only want to shift the values ​​within the array and do not want to replace the shifted indices with constant values, we should use numpy.roll()the shift() function. On the other hand, if we want to replace the shifted indices with specific constant values, the array slicing method is the fastest way to do this operation. The array slicing method is faster but a bit more complicated than using the shift() function scipyfrom the Array library shift(). If we do not care about the performance of the code, we can use shift()the shift() function to accomplish this task.