numpy.atleast_3d() in Python (original) (raw)

Last Updated : 28 Nov, 2018

numpy.atleast_3d() function is used when we want to Convert inputs to arrays with at least three dimension. Scalar, 1 and 2 dimensional inputs are converted to 3-dimensional arrays, whilst higher-dimensional inputs are preserved.

Input includes scalar, 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 >= 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 : Working

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 : Working

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 list : [[2, 6, 10], [8, 12, 16]] output array : [[[ 2] [ 6] [10]]

[[ 8] [12] [16]]]

Code #3 : Working

import numpy as geek

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

print ( "Input array :\n " , in_arr)

out_arr = geek.atleast_3d(in_arr)

print ( "output array :\n " , 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