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 1-D array, compress
is equivalent to extract
.
Parameters: |
condition : 1-D array of bools Array that selects which entries to return. If len(condition) is less than the size of 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 |
See also
take
, choose
, diag
, diagonal
, select
ndarray.compress
np.extract
numpy.doc.ufuncs
>>> 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://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.compress.html