numpy.subtract

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numpy.floor_divide

# numpy.true_divide¶

`numpy.``true_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. 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])
```