pub struct PdfSet { /* private fields */ }
Expand description
Class for PDF set metadata and manipulation.
Implementations§
source§impl PdfSet
impl PdfSet
sourcepub fn new(setname: &str) -> Result<Self>
pub fn new(setname: &str) -> Result<Self>
Constructor from a set name.
Errors
If the PDF set with the specified name was not found an error is returned.
sourcepub fn error_type(&self) -> String
pub fn error_type(&self) -> String
Get the type of PDF errors in this set (replicas, symmhessian, hessian, custom, etc.).
sourcepub fn uncertainty(
&self,
values: &[f64],
cl: f64,
alternative: bool
) -> Result<PdfUncertainty>
pub fn uncertainty( &self, values: &[f64], cl: f64, alternative: bool ) -> Result<PdfUncertainty>
Calculate central value and error from vector values with appropriate formulae for this set.
Warning: The values vector corresponds to the members of this PDF set and must be ordered accordingly.
In the Hessian approach, the central value is the best-fit “values[0]” and the uncertainty is given by either the symmetric or asymmetric formula using eigenvector PDF sets.
If the PDF set is given in the form of replicas, by default, the central value is given by the mean and is not necessarily “values[0]" for quantities with a non-linear dependence on PDFs, while the uncertainty is given by the standard deviation.
The argument cl
is used to rescale uncertainties to a particular confidence level (in
percent); a negative number will rescale to the default CL for this set. The default value
in LHAPDF is 100*erf(1/sqrt(2))=68.268949213709
, corresponding to 1-sigma uncertainties.
If the PDF set is given in the form of replicas, then the argument alternative
equal to
true
(default in LHAPDF: false
) will construct a confidence interval from the
probability distribution of replicas, with the central value given by the median.
For a combined set, a breakdown of the separate PDF and parameter variation uncertainties
is available. The parameter variation uncertainties are computed from the last 2*n
members of the set, with n
the number of parameters.