true_divide(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Unlike 'floor division', true division adjusts the output type to present the best answer, regardless of input types.
In Python, //
is the floor division operator and /
the true division operator. The true_divide(x1, x2)
function is equivalent to true division in Python.
Dividend array.
Divisor array. If x1.shape != x2.shape
, they must be broadcastable to a common shape (which becomes the shape of the output).
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.
This condition is broadcast over the input. At locations where the condition is True, the :None:None:`out` array will be set to the ufunc result. Elsewhere, the :None:None:`out` array will retain its original value. Note that if an uninitialized :None:None:`out` array is created via the default out=None
, locations within it where the condition is False will remain uninitialized.
For other keyword-only arguments, see the ufunc docs <ufuncs.kwargs>
.
Returns a true division of the inputs, element-wise.
>>> x = np.arange(5)This example is valid syntax, but we were not able to check execution
... np.true_divide(x, 4) array([ 0. , 0.25, 0.5 , 0.75, 1. ])
>>> x/4 array([ 0. , 0.25, 0.5 , 0.75, 1. ])This example is valid syntax, but we were not able to check execution
>>> x//4 array([0, 0, 0, 0, 1])
The /
operator can be used as a shorthand for np.true_divide
on ndarrays.
>>> x = np.arange(5)See :
... x / 4 array([0. , 0.25, 0.5 , 0.75, 1. ])
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