numpy.divide¶

numpy.
divide
(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'true_divide'>¶ Returns a true division of the inputs, elementwise.
Instead of the Python traditional ‘floor division’, this returns a true division. True division adjusts the output type to present the best answer, regardless of input types.
Parameters:  x1 : array_like
Dividend array.
 x2 : array_like
Divisor array.
 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 freshlyallocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
 where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
 **kwargs
For other keywordonly arguments, see the ufunc docs.
Returns:  out : ndarray or scalar
This is a scalar if both x1 and x2 are scalars.
Notes
The floor division operator
//
was added in Python 2.2 making//
and/
equivalent operators. The default floor division operation of/
can be replaced by true division withfrom __future__ import division
.In Python 3.0,
//
is the floor division operator and/
the true division operator. Thetrue_divide(x1, x2)
function is equivalent to true division in Python.Examples
>>> x = np.arange(5) >>> np.true_divide(x, 4) array([ 0. , 0.25, 0.5 , 0.75, 1. ])
>>> x/4 array([0, 0, 0, 0, 1]) >>> x//4 array([0, 0, 0, 0, 1])
>>> from __future__ import division >>> x/4 array([ 0. , 0.25, 0.5 , 0.75, 1. ]) >>> x//4 array([0, 0, 0, 0, 1])