numpy.
mod
Return element-wise remainder of division.
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 np.remainder is mod.
floor_divide
np.remainder
Warning
This should not be confused with:
Python 3.7’s math.remainder and C’s remainder, which computes the IEEE remainder, which are the complement to round(x1 / x2).
math.remainder
remainder
round(x1 / x2)
The MATLAB rem function and or the C % operator which is the complement to int(x1 / x2).
rem
%
int(x1 / x2)
Dividend array.
Divisor array. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
x1.shape != x2.shape
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.
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.
out=None
For other keyword-only arguments, see the ufunc docs.
The element-wise remainder of the quotient floor_divide(x1, x2). This is a scalar if both x1 and x2 are scalars.
floor_divide(x1, x2)
See also
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
>>> 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 for np.remainder on ndarrays.
>>> x1 = np.arange(7) >>> x1 % 5 array([0, 1, 2, 3, 4, 0, 1])