numpy.spacing
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numpy.spacing(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'spacing'>
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Return the distance between x and the nearest adjacent number.
Parameters: x : array_like
Values to find the spacing of.
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 : array_like
The spacing of values of
x1
.Notes
It can be considered as a generalization of EPS:
spacing(np.float64(1)) == np.finfo(np.float64).eps
, and there should not be any representable number betweenx + spacing(x)
and x for any finite x.Spacing of +- inf and NaN is NaN.
Examples
>>> np.spacing(1) == np.finfo(np.float64).eps True
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.spacing.html