numpy.ma.masked_all() function | Python

numpy.ma.notmasked_edges() function | Python

Last Updated : 22 Apr, 2020

numpy.ma.notmasked_edges() function find the indices of the first and last unmasked values along an axis. Return None, if all values are masked. Otherwise, return a list of two tuples, corresponding to the indices of the first and last unmasked values respectively.

Syntax : numpy.ma.notmasked_edges(arr, axis = None) Parameters : arr : [array_like] The input array. axis : [int, optional] Axis along which to perform the operation. Default is None. Return : [ ndarray or list] An array of start and end indexes if there are any masked data in the array. If there are no masked data in the array, edges is a list of the first and last index.

Code #1 :

Python3

# Python program explaining
# numpy.ma.notmasked_edges() function

# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 

arr = geek.arange(12).reshape((3, 4))

gfg = geek.ma.notmasked_edges(arr)

print (gfg)

Output :

[ 0, 11]

Code #2 :

Python3

# Python program explaining
# numpy.ma.notmasked_edges() function

# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 

arr = geek.arange(12).reshape((3, 4))
m = geek.zeros_like(arr)
m[1:, 1:] = 1

am = geek.ma.array(arr, mask = m)

gfg = geek.ma.notmasked_edges(am)

print (gfg)

Output :

[0, 8]

numpy.ma.masked_all() function | Python

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