dask.array.divide
dask.array.divide¶
- dask.array.divide(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'divide'>¶
This docstring was copied from numpy.divide.
Some inconsistencies with the Dask version may exist.
Divide arguments element-wise.
- Parameters
- x1array_like
Dividend array.
- x2array_like
Divisor array. If
x1.shape != x2.shape
, they must be broadcastable to a common shape (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 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.
- wherearray_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
- yndarray or scalar
The quotient
x1/x2
, element-wise. This is a scalar if both x1 and x2 are scalars.
See also
seterr
Set whether to raise or warn on overflow, underflow and division by zero.
Notes
Equivalent to
x1
/x2
in terms of array-broadcasting.The
true_divide(x1, x2)
function is an alias fordivide(x1, x2)
.Examples
>>> np.divide(2.0, 4.0) 0.5 >>> x1 = np.arange(9.0).reshape((3, 3)) >>> x2 = np.arange(3.0) >>> np.divide(x1, x2) array([[nan, 1. , 1. ], [inf, 4. , 2.5], [inf, 7. , 4. ]])
The
/
operator can be used as a shorthand fornp.divide
on ndarrays.>>> x1 = np.arange(9.0).reshape((3, 3)) >>> x2 = 2 * np.ones(3) >>> x1 / x2 array([[0. , 0.5, 1. ], [1.5, 2. , 2.5], [3. , 3.5, 4. ]])