numpy.atleast_3d () in Python

Arrays | NumPy | Python Methods and Functions

Input includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays.

Syntax: numpy.atleast_3d (* arrays)

Parameters:
arrays1, arrays2,…: [array_like] One or more array-like sequences. Non-array inputs are converted to arrays. Arrays that already have three or more dimensions are preserved.

Return: An array, or list of arrays, each with arr.ndim & gt; = 3. Copies are avoided where possible , and views with three or more dimensions are returned. For example, a 1-D array of shape (N,) becomes a view of shape (1, N, 1), and a 2-D array of shape (M, N) becomes a view of shape (M, N, 1).

Code # 1: Work

# Python program explaining
# numpy.atleast_3d () function

 

import numpy as geek

in_num = 10

 

print ( "Input number:" , in_num)

 

 

out_arr   = geek.atleast_3d (in_num)

print ( "output 3d array from input number:" , out_arr) 

Output:

 Input number: 10 output 3d array from input number: [[[10]]] 

Code # 2: Work

# Python program explaining
# numpy.atleast_3d () function

 

import numpy as geek

 

my_list = [[ 2 , 6 , 10 ], 

[ 8 , 12 , 16 ]]

 

print ( "Input list:" , my_list)

 

out_arr = geek.atleast_3d (my_list) 

print ( "output array:" , out_arr) 

Output:

 Input lis t: [[2, 6, 10], [8, 12, 16]] output array: [[[2] [6] [10]] [[8] [12] [16]]] 

Code # 3: Work

# Python program explaining
# numpy.atleast_3d () function
# when inputs are in high dimension

 

import numpy as geek

 

in_arr = geek.arange ( 16 ). reshape ( 1 , 4 , 4 )

print   ( "Input array:" , in_arr)

 

out_arr = geek.atleast_3d (in_arr)

print ( "output array:" , out_arr)

print (in_arr is out_arr)

Output:

 Input array: [[[0 1 2 3] [4 5 6 7] [8 9 10 11] [12 13 14 15]]] output array: [[[0 1 2 3] [4 5 6 7] [8 9 10 11] [12 13 14 15]]] True 




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