Select elements of numpy array via boolean mask array

Solution 1:

You probably want something like this:

>>> a = np.array([True, True, True, False, False])
>>> b = np.array([[1,2,3,4,5], [1,2,3,4,5]])
>>> b[:,a]
array([[1, 2, 3],
       [1, 2, 3]])

Note that for this kind of indexing to work, it needs to be an ndarray, like you were using, not a list, or it'll interpret the False and True as 0 and 1 and give you those columns:

>>> b[:,[True, True, True, False, False]]   
array([[2, 2, 2, 1, 1],
       [2, 2, 2, 1, 1]])

Solution 2:

You can use numpy.ma module and use np.ma.masked_array function to do so.

>>> x = np.array([1, 2, 3, -1, 5])                                                
>>> mx = ma.masked_array(x, mask=[0, 0, 0, 1, 0])
masked_array(data=[1, 2, 3, --, 5], mask=[False, False,  False, True, False], fill_value=999999)