-
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: condition : 1-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.a : array_like
Array from which to extract a part.
axis : int, optional
Axis along which to take slices. If None (default), work on the flattened array.
out : ndarray, optional
Output array. Its type is preserved and it must be of the right shape to hold the output.
Returns: compressed_array : ndarray
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
-
numpy.doc.ufuncs
- Section ?Output arguments?
Examples
1234567891011121314>>> 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.
12>>> np.compress([
False
,
True
], a)
array([
2
])
-
numpy.compress()

2025-01-10 15:47:30
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