SciPy

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)