nlcpy.fmod

nlcpy.fmod = <ufunc 'nlcpy_fmod'>

Computes the element-wise remainder of division.

This is the NLCPy implementation of the C library function fmod, the remainder has the same sign as the dividend x1.

Parameters
x1, x2array_like

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

outndarray or None, 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.

wherearray_like, 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 section Optional Keyword Arguments.

Returns
yndarray

The element-wise remainder of the quotient floor_divide(x1,x2). If x1 and x2 are both scalars, this function returns the result as a 0-dimension ndarray.

See also

remainder

Computes the element-wise remainder of division.

divide

Computes the element-wise division of the inputs.

Note

The result of the modulo operation for negative dividend and divisors is bound by conventions. For fmod(), the sign of result is the sign of the dividend, while for remainder() the sign of the result is the sign of the divisor.

Examples

>>> import nlcpy as vp
>>> vp.fmod([-3, -2, -1, 1, 2, 3], 2)
array([-1,  0, -1,  1,  0,  1])
>>> vp.remainder([-3, -2, -1, 1, 2, 3], 2)
array([1, 0, 1, 1, 0, 1])
>>> vp.fmod([5, 3], [2, 2.])
array([1., 1.])
>>> a = vp.arange(-3, 3).reshape(3, 2)
>>> a
array([[-3, -2],
       [-1,  0],
       [ 1,  2]])
>>> vp.fmod(a, [2,2])
array([[-1,  0],
       [-1,  0],
       [ 1,  0]])