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 as False.

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 of compress has a mask, the output of compressed does not.

Examples

>>> import numpy as np
>>> 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)