dpnp.clip

dpnp.clip(a, /, min=None, max=None, *, out=None, order='K', **kwargs)

Clip (limit) the values in an array.

For full documentation refer to numpy.clip.

Parameters:

a{dpnp.ndarray, usm_ndarray}

Array containing elements to clip.

min, max{None, dpnp.ndarray, usm_ndarray}, optional

Minimum and maximum value. If None, clipping is not performed on the corresponding edge. If both min and max are None, the elements of the returned array stay the same. Both are broadcast against a.

Default: None.

out{None, dpnp.ndarray, usm_ndarray}, optional

The results will be placed in this array. It may be the input array for in-place clipping. out must be of the right shape to hold the output. Its type is preserved.

Default: None.

order{None, "C", "F", "A", "K"}, optional

Memory layout of the newly output array, if parameter out is None. If order is None, the default value "K" will be used.

Default: "K".

Returns:

outdpnp.ndarray

An array with the elements of a, but where values < min are replaced with min, and those > max with max.

Limitations

Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

Examples

>>> import dpnp as np
>>> a = np.arange(10)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.clip(a, 1, 8)
array([1, 1, 2, 3, 4, 5, 6, 7, 8, 8])
>>> np.clip(a, 8, 1)
array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
>>> np.clip(a, 3, 6, out=a)
array([3, 3, 3, 3, 4, 5, 6, 6, 6, 6])
>>> a
array([3, 3, 3, 3, 4, 5, 6, 6, 6, 6])

>>> a = np.arange(10)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> min = np.array([3, 4, 1, 1, 1, 4, 4, 4, 4, 4])
>>> np.clip(a, min, 8)
array([3, 4, 2, 3, 4, 5, 6, 7, 8, 8])