numpy.ma.where() function return a masked array with elements from x or y, depending on condition.
Syntax : numpy.ma.where(condition, x, y)
Parameter :
condition : [array_like, bool] Where True, yield x, otherwise yield y.
x, y : [array_like, optional] Values from which to choose. x, y and condition need to be broadcastable to some shape.Return : [MaskedArray] An masked array with masked elements where the condition is masked, elements from x where condition is True, and elements from y elsewhere.
Code #1 :
# Python program explaining # numpy.ma.where() function # importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma x = geek.ma.array(geek.arange(4.).reshape(2, 2), mask =[[0, 1], [1, 0]]) gfg = geek.ma.where(x > 5, x, -3.1416) print (gfg) |
Output :
[[-3.1416 --] [-- -3.1416]]
Code #2 :
# Python program explaining # numpy.ma.where() function # importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma x = geek.ma.array(geek.arange(9.).reshape(3, 3), mask =[[0, 1, 0], [1, 0, 1], [0, 1, 0]]) gfg = geek.ma.where(x > 5, x, -3.1416) print (gfg) |
Output :
[[-3.1416 -- -3.1416] [-- -3.1416 --] [6.0 -- 8.0]]
