np.MaskedArray.transpose() produces partial views

>>> src = np.ma.masked_where([0, 1, 0], [1, 1337, 1])
>>> dst = np.ma.masked_where([1, 0, 0, 0, 0], np.zeros(5))
>>> dst_view = dst.transpose()
# check the views look ok
>>> dst
masked_array(data = [-- 0 0 0 0],
             mask = [ True False False False False],
       fill_value = 999999)
>>> dst_view
masked_array(data = [-- 0 0 0 0],
             mask = [ True False False False False],
       fill_value = 999999)

# now write a slice of the view
>>> dst_view[2:5] = src
>>> dst_view
masked_array(data = [-- 0 1 -- 1],
             mask = [ True False False  True False],
       fill_value = 999999)

# but looking back at the original, the data was updated but the mask was not!
>>> dst
masked_array(data = [-- 0 1 1337 1],
             mask = [ True False False False False],
       fill_value = 999999)

[mhvk]

This behaviour is as intended originally (see masked array docs), but it is not obvious it is a good idea (see #5558), and hence plans are afoot to change it: #5580. The latter PR is also the reason you are getting FutureWarning. One thing that might be useful for #5580 is to check that your examples would work with that PR (in particular for the transpose, for which you do not get the FutureWarning).

[seberg]

I am not sure, but it might be possible to set _sharedmask to true. However, it may not actually warn in all cases that will change, but only for assignments.