Save.npy masked array to a .npy array with NaNs where mask == True

Question

Is there a way to convert a masked 3D numpy array to a numpy array with NaNs in place of the mask? This way I can easily write the numpy array out using np.save. The alternative is to find a way to write out the masked array with some clear indicator for elements that are masked. I have tried:

a = np.ma.zeros((500, 500))
a.dump('test')

but I need the file to be in a format so it can be read into R. Thanks.

Answer 1

A scan of the masked array operations page shows np.ma.filled does what you are looking for. For example,

import numpy as np

arr = np.arange(2*3*4).reshape(2,3,4).astype(float)
mask = arr % 5 == 0

marr = np.ma.array(arr, mask=mask)
print(np.ma.filled(marr, np.nan))

yields

[[[ nan   1.   2.   3.]
  [  4.  nan   6.   7.]
  [  8.   9.  nan  11.]]

 [[ 12.  13.  14.  nan]
  [ 16.  17.  18.  19.]
  [ nan  21.  22.  23.]]]

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Alternatively, you could use the masked array's filled method. marr.filled(np.nan) is equivalent to np.ma.filled(marr, np.nan).