nums.numpy.fmod

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

Return the element-wise remainder of division.

This docstring was copied from numpy.fmod.

Some inconsistencies with the NumS version may exist.

This is the NumPy implementation of the C library function fmod, the remainder has the same sign as the dividend x1. It is equivalent to the Matlab(TM) rem function and should not be confused with the Python modulus operator x1 % x2.

Parameters

  • x1 (BlockArray) – Dividend.

  • x2 (BlockArray) – Divisor. 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 remainder of the division of x1 by x2.

Return type

BlockArray

See also

remainder

Equivalent to the Python % operator.

divide

Notes

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. The fmod function is equivalent to the Matlab(TM) rem function.

Examples

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

>>> nps.fmod(nps.array([-3, -2, -1, 1, 2, 3]), nps.array(2)).get()  
array([-1,  0, -1,  1,  0,  1])
>>> nps.remainder(nps.array([-3, -2, -1, 1, 2, 3]), nps.array(2)).get()  
array([1, 0, 1, 1, 0, 1])

>>> nps.fmod(nps.array([5, 3]), nps.array([2, 2.])).get()  
array([ 1.,  1.])
>>> a = nps.arange(-3, 3).reshape(3, 2)  
>>> a.get()  
array([[-3, -2],
       [-1,  0],
       [ 1,  2]])
>>> nps.fmod(a, nps.array([2,2])).get()  
array([[-1,  0],
       [-1,  0],
       [ 1,  0]])

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