xorbits.numpy.divmod#
- xorbits.numpy.divmod = <function wrap_fallback_module_method.<locals>._wrapped>#
divmod(x1, x2[, out1, out2], / [, out=(None, None)], *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj])
Return element-wise quotient and remainder simultaneously.
New in version 1.13.0(numpy).
np.divmod(x, y)
is equivalent to(x // y, x % y)
, but faster because it avoids redundant work. It is used to implement the Python built-in functiondivmod
on NumPy arrays.- Parameters
x1 (array_like) – Dividend array.
x2 (array_like) – Divisor array. If
x1.shape != x2.shape
, they must be broadcastable to a common shape (which becomes the shape of the output).out (ndarray, None, or tuple of ndarray and None, 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 (array_like, 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
out1 (ndarray) – Element-wise quotient resulting from floor division. This is a scalar if both x1 and x2 are scalars.
out2 (ndarray) – Element-wise remainder from floor division. This is a scalar if both x1 and x2 are scalars.
See also
floor_divide
Equivalent to Python’s
//
operator.remainder
Equivalent to Python’s
%
operator.modf
Equivalent to
divmod(x, 1)
for positivex
with the return values switched.
Examples
>>> np.divmod(np.arange(5), 3) (array([0, 0, 0, 1, 1]), array([0, 1, 2, 0, 1]))
The divmod function can be used as a shorthand for
np.divmod
on ndarrays.>>> x = np.arange(5) >>> divmod(x, 3) (array([0, 0, 0, 1, 1]), array([0, 1, 2, 0, 1]))
Warning
This method has not been implemented yet. Xorbits will try to execute it with numpy.
This docstring was copied from numpy.