numpy.mod#
- numpy.mod(x1,x2,/,out=None,*,where=True,casting='same_kind',order='K',dtype=None,subok=True[,signature])=<ufunc'remainder'>#
Returns the element-wise remainder of division.
Computes the remainder complementary to the
floor_dividefunction. It isequivalent to the Python modulus operatorx1%x2and has the same signas the divisorx2. The MATLAB function equivalent tonp.remainderismod.Warning
This should not be confused with:
Python’s
math.remainderand C’sremainder, whichcompute the IEEE remainder, which are the complement toround(x1/x2).The MATLAB
remfunction and or the C%operator which is thecomplement toint(x1/x2).
- Parameters:
- x1array_like
Dividend array.
- x2array_like
Divisor array.If
x1.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 default
out=None, locations within it where the condition is False willremain uninitialized.- **kwargs
For other keyword-only arguments, see theufunc docs.
- Returns:
- yndarray
The element-wise remainder of the quotient
floor_divide(x1,x2).This is a scalar if bothx1 andx2 are scalars.
See also
floor_divideEquivalent of Python
//operator.divmodSimultaneous floor division and remainder.
fmodEquivalent of the MATLAB
remfunction.divide,floor
Notes
Returns 0 whenx2 is 0 and bothx1 andx2 are (arrays of)integers.
modis an alias ofremainder.Examples
>>>importnumpyasnp>>>np.remainder([4,7],[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 fornp.remainderonndarrays.>>>x1=np.arange(7)>>>x1%5array([0, 1, 2, 3, 4, 0, 1])