numpy.ma.masked_array.compress
method
- 
masked_array.compress(self, condition, axis=None, out=None)[source] - 
Return
awhere condition isTrue.If condition is a
MaskedArray, missing values are considered asFalse.- Parameters
 - 
- 
conditionvar - 
Boolean 1-d array selecting which entries to return. If len(condition) is less than the size of a along the axis, then output is truncated to length of condition array.
 - 
axis{None, int}, optional - 
Axis along which the operation must be performed.
 - 
out{None, ndarray}, optional - 
Alternative output array in which to place the result. It must have the same shape as the expected output but the type will be cast if necessary.
 
 - 
 - Returns
 - 
- 
resultMaskedArray - 
A
MaskedArrayobject. 
 - 
 
Notes
Please note the difference with
compressed! The output ofcompresshas a mask, the output ofcompresseddoes not.Examples
>>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4) >>> x masked_array( data=[[1, --, 3], [--, 5, --], [7, --, 9]], mask=[[False, True, False], [ True, False, True], [False, True, False]], fill_value=999999) >>> x.compress([1, 0, 1]) masked_array(data=[1, 3], mask=[False, False], fill_value=999999)>>> x.compress([1, 0, 1], axis=1) masked_array( data=[[1, 3], [--, --], [7, 9]], mask=[[False, False], [ True, True], [False, False]], fill_value=999999) 
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    https://numpy.org/doc/1.18/reference/generated/numpy.ma.masked_array.compress.html