numpy.spacing(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'spacing'>
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 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. |
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Returns: |
out : array_like The spacing of values of |
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 between x + spacing(x)
and x for any finite x.
Spacing of +- inf and NaN is NaN.
>>> np.spacing(1) == np.finfo(np.float64).eps True
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.spacing.html