compress(condition, a, axis=None)

This docstring was copied from numpy.compress.

Some inconsistencies with the Dask version may exist.

When working along a given axis, a slice along that axis is returned in :None:None:`output` for each index where :None:None:`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 (Not supported in Dask)

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 :None:None:`condition` is false.

Return selected slices of an array along given axis.

See Also

choose

diag

diagonal

extract

Equivalent method when working on 1-D arrays

ndarray.compress

Equivalent method in ndarray

select

take

ufuncs-output-type

ref

Examples

This example is valid syntax, but we were not able to check execution

>>> a = np.array([[1, 2], [3, 4], [5, 6]])  # doctest: +SKIP
... a  # doctest: +SKIP
array([[1, 2],
       [3, 4],
       [5, 6]])

This example is valid syntax, but we were not able to check execution

>>> np.compress([0, 1], a, axis=0)  # doctest: +SKIP
array([[3, 4]])

This example is valid syntax, but we were not able to check execution

>>> np.compress([False, True, True], a, axis=0)  # doctest: +SKIP
array([[3, 4],
       [5, 6]])

This example is valid syntax, but we were not able to check execution

>>> np.compress([False, True], a, axis=1)  # doctest: +SKIP
array([[2],
       [4],
       [6]])

Working on the flattened array does not return slices along an axis but selects elements.

This example is valid syntax, but we were not able to check execution

>>> np.compress([False, True], a)  # doctest: +SKIP
array([2])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.routines.extract dask.array.routines.select dask.array.routines.take dask.array.routines.compress

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