numpy.compress¶

numpy.
compress
(condition, a, axis=None, out=None)[source]¶ Return selected slices of an array along given axis.
When working along a given axis, a slice along that axis is returned in output for each index where condition evaluates to True. When working on a 1D array,
compress
is equivalent toextract
. Parameters
 condition1D array of bools
Array that selects which entries to return. If len(condition) is less than the size of a along the given axis, then output is truncated to the length of the condition array.
 aarray_like
Array from which to extract a part.
 axisint, optional
Axis along which to take slices. If None (default), work on the flattened array.
 outndarray, optional
Output array. Its type is preserved and it must be of the right shape to hold the output.
 Returns
 compressed_arrayndarray
A copy of a without the slices along axis for which condition is false.
See also
take
,choose
,diag
,diagonal
,select
ndarray.compress
Equivalent method in ndarray
np.extract
Equivalent method when working on 1D arrays
ufuncsoutputtype
Examples
>>> a = np.array([[1, 2], [3, 4], [5, 6]]) >>> a array([[1, 2], [3, 4], [5, 6]]) >>> np.compress([0, 1], a, axis=0) array([[3, 4]]) >>> np.compress([False, True, True], a, axis=0) array([[3, 4], [5, 6]]) >>> np.compress([False, True], a, axis=1) array([[2], [4], [6]])
Working on the flattened array does not return slices along an axis but selects elements.
>>> np.compress([False, True], a) array([2])