nums.numpy.remainder

nums.numpy.remainder(x1, x2, out=None, where=True, **kwargs)[source]

Return element-wise remainder of division.

This docstring was copied from numpy.remainder.

Some inconsistencies with the NumS version may exist.

Computes the remainder complementary to the floor_divide function. It is equivalent to the Python modulus operator``x1 % x2`` and has the same sign as the divisor x2. The MATLAB function equivalent to nps.remainder is mod.

Parameters

  • x1 (BlockArray) – Dividend array.

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

  • out (BlockArray, None, or optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

  • where (BlockArray, optional) – This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.

  • **kwargs – For other keyword-only arguments, see the ufunc docs.

Returns

y – The element-wise remainder of the quotient floor_divide(x1, x2).

Return type

BlockArray

See also

floor_divide

Equivalent of Python // operator.

divmod

Simultaneous floor division and remainder.

fmod

Equivalent of the MATLAB rem function.

divide, floor

Notes

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

Examples

The doctests shown below are copied from NumPy. They won’t show the correct result until you operate get().

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

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