numpy.spacing#

numpy.spacing(x,/,out=None,*,where=True,casting='same_kind',order='K',dtype=None,subok=True[,signature])=<ufunc'spacing'>#

Return the distance between x and the nearest adjacent number.

Parameters:
xarray_like

Values to find the spacing of.

outndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must havea shape that the inputs broadcast to. If not provided or None,a freshly-allocated array is returned. A tuple (possible only as akeyword argument) must have length equal to the number of outputs.

wherearray_like, optional

This condition is broadcast over the input. At locations where thecondition is True, theout array will be set to the ufunc result.Elsewhere, theout array will retain its original value.Note that if an uninitializedout array is created via the defaultout=None, locations within it where the condition is False willremain uninitialized.

**kwargs

For other keyword-only arguments, see theufunc docs.

Returns:
outndarray or scalar

The spacing of values ofx.This is a scalar ifx is a scalar.

Notes

It can be considered as a generalization of EPS:spacing(np.float64(1))==np.finfo(np.float64).eps, and thereshould not be any representable number betweenx+spacing(x) andx for any finite x.

Spacing of +- inf and NaN is NaN.

Examples

>>>importnumpyasnp>>>np.spacing(1)==np.finfo(np.float64).epsTrue
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