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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
outputfor each index whereconditionevaluates to True. When working on a 1-D array,compressis equivalent toextract.- Parameters
-
condition1-D array of bools-
Array that selects which entries to return. If len(condition) is less than the size of
aalong 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
awithout the slices along axis for whichconditionis false.
See also
take,choose,diag,diagonal,selectndarray.compress-
Equivalent method in ndarray
np.extract-
Equivalent method when working on 1-D arrays
ufuncs-output-typeExamples
>>> 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])
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https://numpy.org/doc/1.19/reference/generated/numpy.compress.html