Masked 2D array replace value operation not working in numpy

Question

I would like to replace the values of a 2D numpy array based on a mask from another array. The idea is that values in arr_b should be set to 0.8 in the locations where arr_a value equals 0.4. Both arr_a and arr_b are always going to have the same size. And for the purpose of this toy example, you can assume that arr_a has sevreral values that are 0.4. But the code is not working:

import numpy
arr_a = numpy.random.rand(20,40)
arr_b = numpy.random.rand(20,40)
arr_a[0,1] = 0.4

mask_cntr = numpy.ma.masked_not_equal(arr_a[:], 0.4)
ma_arr = numpy.ma.masked_where(mask_cntr, arr_b)
ma_arr.filled(fill_value = 0.8)

Can someone tell me how to fix this?

What is it doing, and how is that wrong? Why are you using np.ma methods? — hpaulj
– hpaulj, Commented Sep 16, 2015 at 3:38

Julien · Accepted Answer · 2015-09-16 03:18:34Z

1

Your array definitions are wrong, as you can read in your error message.

arr_a = numpy.random.random((20,40))

answered Sep 16, 2015 at 3:18

Julien

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1 Comment

user308827 Over a year ago

thanks, this was a typo in my copy pasting here, but the code does corretly create the random array

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