numpy.divide — NumPy v1.15 Manual (original) (raw)
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 theufunc docs. |
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| 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])