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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, element-wise.

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 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

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 keyword-only 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 with from __future__ import division.

In Python 3.0, // is the floor division operator and / the true division operator. The true_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])