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
# Python program explaining # numpy.atleast_1d() function 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
# Python program explaining # numpy.atleast_1d() function 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
# Python program explaining # numpy.atleast_1d() function # when inputs are in high dimension 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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