numpy.ma.masked_array.compress#
method
- ma.masked_array.compress(condition, axis=None, out=None)[source]#
Return a where condition is
True
.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
MaskedArray
object.
Notes
Please note the difference with
compressed
! The output ofcompress
has a mask, the output ofcompressed
does 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)