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numpy.compress — NumPy v2.3 Manual

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:

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 which condition is false.

Examples

>>> import numpy as np
>>> 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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