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"""
Interface of the counting function of the dpnp
Notes
-----
This module is a face or public interface file for the library
it contains:
- Interface functions
- documentation for the functions
- The functions parameters check
"""
import dpctl.tensor as dpt
import dpnp
__all__ = ["count_nonzero"]
[docs]
def count_nonzero(a, axis=None, *, keepdims=False, out=None):
"""
Counts the number of non-zero values in the array `a`.
For full documentation refer to :obj:`numpy.count_nonzero`.
Parameters
----------
a : {dpnp.ndarray, usm_ndarray}
The array for which to count non-zeros.
axis : {None, int, tuple}, optional
Axis or tuple of axes along which to count non-zeros.
Default value means that non-zeros will be counted along a flattened
version of `a`.
Default: ``None``.
keepdims : bool, optional
If this is set to ``True``, the axes that are counted are left in the
result as dimensions with size one. With this option, the result will
broadcast correctly against the input array.
Default: ``False``.
out : {None, dpnp.ndarray, usm_ndarray}, optional
The array into which the result is written. The data type of `out` must
match the expected shape and the expected data type of the result.
If ``None`` then a new array is returned.
Default: ``None``.
Returns
-------
out : dpnp.ndarray
Number of non-zero values in the array along a given axis.
Otherwise, a zero-dimensional array with the total number of non-zero
values in the array is returned.
See Also
--------
:obj:`dpnp.nonzero` : Return the coordinates of all the non-zero values.
Examples
--------
>>> import dpnp as np
>>> np.count_nonzero(np.eye(4))
array(4)
>>> a = np.array([[0, 1, 7, 0],
[3, 0, 2, 19]])
>>> np.count_nonzero(a)
array(5)
>>> np.count_nonzero(a, axis=0)
array([1, 1, 2, 1])
>>> np.count_nonzero(a, axis=1)
array([2, 3])
>>> np.count_nonzero(a, axis=1, keepdims=True)
array([[2],
[3]])
"""
usm_a = dpnp.get_usm_ndarray(a)
usm_out = None if out is None else dpnp.get_usm_ndarray(out)
usm_res = dpt.count_nonzero(
usm_a, axis=axis, keepdims=keepdims, out=usm_out
)
return dpnp.get_result_array(usm_res, out)