dpnp.mod¶

dpnp.mod = <DPNPBinaryFunc 'remainder'>¶

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.

x2{dpnp.ndarray, usm_ndarray, scalar}

Second input array, also expected to have a real-valued data type.

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

Output array to populate. Array must have the correct shape and the expected data type. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

Default: None.

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

Memory layout of the newly output array, if parameter out is None.

Default: "K".

Returns:

outdpnp.ndarray: 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.

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.divmod: Simultaneous floor division and remainder.
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

At least one of x1 or x2 must be an array.

If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

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])