numpy.compress

numpy.compress(condition, a, axis=None, out=None)

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])