dpnp.remainder

dpnp.remainder(x1, x2, out=None, where=True, order='K', dtype=None, subok=True, **kwargs)

Calculates the remainder of division for each element x1_i of the input array x1 with the respective element x2_i of the input array x2.

This function is equivalent to the Python modulus operator.

For full documentation refer to numpy.remainder.

Parameters:

x1 ({dpnp.ndarray, usm_ndarray, scalar}) -- First input array, expected to have a real-valued data type. Both inputs x1 and x2 can not be scalars at the same time.
x2 ({dpnp.ndarray, usm_ndarray, scalar}) -- Second input array, also expected to have a real-valued data type. Both inputs x1 and x2 can not be scalars at the same time. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
out ({None, dpnp.ndarray, usm_ndarray}, optional) -- Output array to populate. Array must have the correct shape and the expected data type. Default: None.
order ({"C", "F", "A", "K"}, optional) -- Memory layout of the newly output array, if parameter out is None. Default: "K".

Returns:

out -- An array containing the element-wise remainders. Each remainder has the same sign as respective element x2_i. The data type of the returned array is determined by the Type Promotion Rules.

Return type:

dpnp.ndarray

Limitations

Parameters where and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

See also

dpnp.fmod: Calculate the element-wise remainder of division.
dpnp.divide: Standard division.
dpnp.floor: Round a number to the nearest integer toward minus infinity.
dpnp.floor_divide: Compute the largest integer smaller or equal to the division of the inputs.
dpnp.mod: Calculate the element-wise remainder of division.

Notes

Returns 0 when x2 is 0 and both x1 and x2 are (arrays of) integers. dpnp.mod is an alias of dpnp.remainder.

Examples

>>> import dpnp as np
>>> np.remainder(np.array([4, 7]), np.array([2, 3]))
array([0, 1])

>>> np.remainder(np.arange(7), 5)
array([0, 1, 2, 3, 4, 0, 1])

The % operator can be used as a shorthand for remainder on dpnp.ndarray.

>>> x1 = np.arange(7)
>>> x1 % 5
array([0, 1, 2, 3, 4, 0, 1])