numpy.ma.masked_array.compress¶
- masked_array.compress(condition, axis=None, out=None)[source]¶
Return a where condition is True.
If condition is a MaskedArray, missing values are considered as False.
Parameters: condition : var
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: result : MaskedArray
A MaskedArray object.
Notes
Please note the difference with compressed ! The output of compress has a mask, the output of compressed does not.
Examples
>>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4) >>> print x [[1 -- 3] [-- 5 --] [7 -- 9]] >>> 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)