Numpy MaskedArray.atleast_1d() function | Python (original) (raw)

Last Updated : 13 Oct, 2019

numpy.MaskedArray.atleast_1d() function is used to convert inputs to masked arrays with at least one dimension.Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved.

Syntax : numpy.ma.atleast_1d(*arys)

Parameters:
**arys:**[ array_like] One or more input arrays.

Return : [ ndarray] An array, or list of arrays, each with arr.ndim >= 1

Code #1 :

import numpy as geek

import numpy.ma as ma

in_arr1 = geek.array([[ 1 , 2 ], [ 3 , - 1 ], [ 5 , - 3 ]])

print ( "1st Input array : " , in_arr1)

in_arr2 = geek.array( 2 )

print ( "2nd Input array : " , in_arr2)

mask_arr1 = ma.masked_array(in_arr1, mask = [[ 1 , 0 ], [ 0 , 1 ], [ 0 , 0 ]])

print ( "1st Masked array : " , mask_arr1)

mask_arr2 = ma.masked_array(in_arr2, mask = 0 )

print ( "2nd Masked array : " , mask_arr2)

out_arr = ma.atleast_1d(mask_arr1, mask_arr2)

print ( "Output masked array : " , out_arr)

Output:

1st Input array : [[ 1 2] [ 3 -1] [ 5 -3]] 2nd Input array : 2 1st Masked array : [[-- 2] [3 --] [5 -3]] 2nd Masked array : 2 Output masked array : [masked_array( data=[[--, 2], [3, --], [5, -3]], mask=[[ True, False], [False, True], [False, False]], fill_value=999999), masked_array(data=[2], mask=[False], fill_value=999999)]

Code #2 :

import numpy as geek

import numpy.ma as ma

in_arr = geek.array([[[ 2e8 , 3e - 5 ]], [[ - 45.0 , 2e5 ]]])

print ( "Input array : " , in_arr)

mask_arr = ma.masked_array(in_arr, mask = [[[ 1 , 0 ]], [[ 0 , 0 ]]])

print ( "3D Masked array : " , mask_arr)

out_arr = ma.atleast_1d(mask_arr)

print ( "Output masked array : " , out_arr)

Output:

Input array : [[[ 2.0e+08 3.0e-05]]

[[-4.5e+01 2.0e+05]]] 3D Masked array : [[[-- 3e-05]]

[[-45.0 200000.0]]] Output masked array : [[[-- 3e-05]]

[[-45.0 200000.0]]]

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