fmod(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Some inconsistencies with the Dask version may exist.
Returns the element-wise remainder of division.
This is the NumPy implementation of the C library function fmod, the remainder has the same sign as the dividend :None:None:`x1`
. It is equivalent to the Matlab(TM) rem
function and should not be confused with the Python modulus operator x1 % x2
.
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.
Dividend.
Divisor. If x1.shape != x2.shape
, they must be broadcastable to a common shape (which becomes the shape of the output).
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 :None:None:`out`
array will be set to the ufunc result. Elsewhere, the :None:None:`out`
array will retain its original value. Note that if an uninitialized :None:None:`out`
array is created via the default out=None
, locations within it where the condition is False will remain uninitialized.
For other keyword-only arguments, see the ufunc docs <ufuncs.kwargs>
.
The remainder of the division of :None:None:`x1`
by :None:None:`x2`
. This is a scalar if both :None:None:`x1`
and :None:None:`x2`
are scalars.
This docstring was copied from numpy.fmod.
remainder
Equivalent to the Python %
operator.
>>> np.fmod([-3, -2, -1, 1, 2, 3], 2) # doctest: +SKIP array([-1, 0, -1, 1, 0, 1])This example is valid syntax, but we were not able to check execution
>>> np.remainder([-3, -2, -1, 1, 2, 3], 2) # doctest: +SKIP array([1, 0, 1, 1, 0, 1])This example is valid syntax, but we were not able to check execution
>>> np.fmod([5, 3], [2, 2.]) # doctest: +SKIP array([ 1., 1.])This example is valid syntax, but we were not able to check execution
>>> a = np.arange(-3, 3).reshape(3, 2) # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... a # doctest: +SKIP array([[-3, -2], [-1, 0], [ 1, 2]])
>>> np.fmod(a, [2,2]) # doctest: +SKIP array([[-1, 0], [-1, 0], [ 1, 0]])See :
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.ufunc.fmod
dask.array.ufunc.remainder
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