numpy.fmod#

numpy.fmod(x1,x2,/,out=None,*,where=True,casting='same_kind',order='K',dtype=None,subok=True[,signature])=<ufunc'fmod'>#

Returns the element-wise remainder of division.

This is the NumPy implementation of the C library function fmod, theremainder has the same sign as the dividendx1. It is equivalent tothe Matlab(TM)rem function and should not be confused with thePython modulus operatorx1%x2.

Parameters:
x1array_like

Dividend.

x2array_like

Divisor.Ifx1.shape!=x2.shape, they must be broadcastable to a commonshape (which becomes the shape of the output).

outndarray, None, or tuple of ndarray and None, optional

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

wherearray_like, optional

This condition is broadcast over the input. At locations where thecondition is True, theout array will be set to the ufunc result.Elsewhere, theout array will retain its original value.Note that if an uninitializedout array is created via the defaultout=None, locations within it where the condition is False willremain uninitialized.

**kwargs

For other keyword-only arguments, see theufunc docs.

Returns:
yarray_like

The remainder of the division ofx1 byx2.This is a scalar if bothx1 andx2 are scalars.

See also

remainder

Equivalent to the Python% operator.

divide

Notes

The result of the modulo operation for negative dividend and divisorsis bound by conventions. Forfmod, the sign of result is the sign ofthe dividend, while forremainder the sign of the result is the signof the divisor. Thefmod function is equivalent to the Matlab(TM)rem function.

Examples

>>>importnumpyasnp>>>np.fmod([-3,-2,-1,1,2,3],2)array([-1,  0, -1,  1,  0,  1])>>>np.remainder([-3,-2,-1,1,2,3],2)array([1, 0, 1, 1, 0, 1])
>>>np.fmod([5,3],[2,2.])array([ 1.,  1.])>>>a=np.arange(-3,3).reshape(3,2)>>>aarray([[-3, -2],       [-1,  0],       [ 1,  2]])>>>np.fmod(a,[2,2])array([[-1,  0],       [-1,  0],       [ 1,  0]])
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