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numpy.ma.MaskedArray.compress
method
- MaskedArray.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.
 
 NotesPlease 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/1.19/reference/generated/numpy.ma.MaskedArray.compress.html