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 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 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 which condition 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
>>> 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])