compress(condition, a, axis=None, out=None)
When working along a given axis, a slice along that axis is returned in output
for each index where :None:None:`condition` evaluates to True. When working on a 1-D array, compress
is equivalent to extract
.
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.
Array from which to extract a part.
Axis along which to take slices. If None (default), work on the flattened array.
Output array. Its type is preserved and it must be of the right shape to hold the output.
A copy of a without the slices along axis for which :None:None:`condition` is false.
Return selected slices of an array along given axis.
extract
Equivalent method when working on 1-D arrays
ndarray.compress
Equivalent method in ndarray
>>> 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])See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.take
numpy.extract
numpy.compress
dask.array.routines.compress
numpy.select
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