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 wherecondition
evaluates to True. When working on a 1-D array,compress
is equivalent toextract
.- Parameters
-
-
condition1-D 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 whichcondition
is false.
-
See also
take
,choose
,diag
,diagonal
,select
-
ndarray.compress
-
Equivalent method in ndarray
-
np.extract
-
Equivalent method when working on 1-D arrays
ufuncs-output-type
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])
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https://numpy.org/doc/1.19/reference/generated/numpy.compress.html