VarianceUncertainty¶
- class astropy.nddata.VarianceUncertainty(array=None, copy=True, unit=None)[source]¶
Bases:
_VariancePropagationMixin,NDUncertaintyVariance uncertainty assuming first order Gaussian error propagation.
This class implements uncertainty propagation for
addition,subtraction,multiplicationanddivisionwith other instances ofVarianceUncertainty. The class can handle if the uncertainty has a unit that differs from (but is convertible to) the parentsNDDataunit. The unit of the resulting uncertainty will be the square of the unit of the resulting data. Also support for correlation is possible but requires the correlation as input. It cannot handle correlation determination itself.- Parameters:
- args, kwargs
see
NDUncertainty
Examples
Compare this example to that in
StdDevUncertainty; the uncertainties in the examples below are equivalent to the uncertainties inStdDevUncertainty.VarianceUncertaintyshould always be associated with anNDData-like instance, either by creating it during initialization:>>> from astropy.nddata import NDData, VarianceUncertainty >>> ndd = NDData([1,2,3], unit='m', ... uncertainty=VarianceUncertainty([0.01, 0.01, 0.01])) >>> ndd.uncertainty VarianceUncertainty([0.01, 0.01, 0.01])
or by setting it manually on the
NDDatainstance:>>> ndd.uncertainty = VarianceUncertainty([0.04], unit='m^2', copy=True) >>> ndd.uncertainty VarianceUncertainty([0.04])
the uncertainty
arraycan also be set directly:>>> ndd.uncertainty.array = 4 >>> ndd.uncertainty VarianceUncertainty(4)
Note
The unit will not be displayed.
Attributes Summary
True:VarianceUncertaintyallows to propagate correlated uncertainties."var":VarianceUncertaintyimplements variance.Attributes Documentation
True:VarianceUncertaintyallows to propagate correlated uncertainties.correlationmust be given, this class does not implement computing it by itself.
- uncertainty_type¶
"var":VarianceUncertaintyimplements variance.