dpnp.extract

dpnp.extract(condition, a)[source]

Return the elements of an array that satisfy some condition.

This is equivalent to dpnp.compress(dpnp.ravel(condition), dpnp.ravel(a)). If condition is boolean dpnp.extract is equivalent to a[condition].

Note that dpnp.place does the exact opposite of dpnp.extract.

For full documentation refer to numpy.extract.

Parameters:

condition ({array_like, scalar}) -- An array whose non-zero or True entries indicate the element of a to extract.
a ({dpnp.ndarray, usm_ndarray}) -- Input array of the same size as condition.

Returns:

out -- Rank 1 array of values from a where condition is True.

Return type:

dpnp.ndarray

See also

dpnp.take: Take elements from an array along an axis.
dpnp.put: Replaces specified elements of an array with given values.
dpnp.copyto: Copies values from one array to another, broadcasting as necessary.
dpnp.compress: Return selected slices of an array along given axis.
dpnp.place: Change elements of an array based on conditional and input values.

Examples

>>> import dpnp as np
>>> a = np.arange(12).reshape((3, 4))
>>> a
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
>>> condition = np.mod(a, 3) == 0
>>> condition
array([[ True, False, False,  True],
       [False, False,  True, False],
       [False,  True, False, False]])
>>> np.extract(condition, a)
array([0, 3, 6, 9])

If condition is boolean:

>>> a[condition]
array([0, 3, 6, 9])