numpy.atleast_1d() in Python (original) (raw)

Last Updated : 28 Nov, 2018

**numpy.atleast_1d()**function is used when we want to Convert inputs to arrays with at least one dimension. Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved.

Syntax : numpy.atleast_1d(*arrays)

Parameters :
arrays1, arrays2, … : [array_like] One or more input arrays.

Return : [ndarray] An array, or list of arrays, each with a.ndim >= 1. Copies are made only if necessary.

Code #1 : Working

import numpy as geek

in_num = 10

print ( "Input number : " , in_num)

out_arr = geek.atleast_1d(in_num)

print ( "output 1d array from input number : " , out_arr)

Output :

Input number : 10 output 1d 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_1d(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( 9 ).reshape( 3 , 3 )

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

out_arr = geek.atleast_1d(in_arr)

print ( "output array :\n " , out_arr)

print (in_arr is out_arr)

Output :

IInput array : [[0 1 2] [3 4 5] [6 7 8]] output array : [[0 1 2] [3 4 5] [6 7 8]] True'

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