pub struct FitStat<Model: FitModelErrors + LevMarModel> {
pub report: MinimizationReport<Model::Scalar>,
pub reduced_chi2: Model::Scalar,
pub errors: Model::OwnedModel,
pub covariance_matrix: GenericMatrix<Model::Scalar, Model::ParamCount, Model::ParamCount>,
}Expand description
Result of fit_stat.
Fields§
§report: MinimizationReport<Model::Scalar>Report resulted from the fit
reduced_chi2: Model::Scalar$\chi^{2}/\test{dof}$ criteria. Should be about 1 for correct fit.
errors: Model::OwnedModelType defined by model, containing parameter errors.
This will usually be the model type itself, but there may be exceptions.
covariance_matrix: GenericMatrix<Model::Scalar, Model::ParamCount, Model::ParamCount>A parameter covariance matrix. If you don’t know what this is, you can safely ignore it.
Trait Implementations§
Source§impl<Model: Debug + FitModelErrors + LevMarModel> Debug for FitStat<Model>
impl<Model: Debug + FitModelErrors + LevMarModel> Debug for FitStat<Model>
Auto Trait Implementations§
impl<Model> Freeze for FitStat<Model>where
<Model as LevMarModel>::RealScalar: Freeze,
<Model as FitModelErrors>::OwnedModel: Freeze,
<<<Model as FitModel>::ParamCount as Conv>::TNum as ArrayLength>::ArrayType<GenericArray<<Model as LevMarModel>::RealScalar, <<Model as FitModel>::ParamCount as Conv>::TNum>>: Freeze,
impl<Model> RefUnwindSafe for FitStat<Model>where
<Model as LevMarModel>::RealScalar: RefUnwindSafe,
<Model as FitModelErrors>::OwnedModel: RefUnwindSafe,
<<<Model as FitModel>::ParamCount as Conv>::TNum as ArrayLength>::ArrayType<GenericArray<<Model as LevMarModel>::RealScalar, <<Model as FitModel>::ParamCount as Conv>::TNum>>: RefUnwindSafe,
<<Model as FitModel>::ParamCount as Conv>::Nalg: RefUnwindSafe,
impl<Model> Send for FitStat<Model>
impl<Model> Sync for FitStat<Model>
impl<Model> Unpin for FitStat<Model>where
<Model as LevMarModel>::RealScalar: Unpin,
<Model as FitModelErrors>::OwnedModel: Unpin,
<<<Model as FitModel>::ParamCount as Conv>::TNum as ArrayLength>::ArrayType<GenericArray<<Model as LevMarModel>::RealScalar, <<Model as FitModel>::ParamCount as Conv>::TNum>>: Unpin,
<<Model as FitModel>::ParamCount as Conv>::Nalg: Unpin,
impl<Model> UnwindSafe for FitStat<Model>where
<Model as LevMarModel>::RealScalar: UnwindSafe,
<Model as FitModelErrors>::OwnedModel: UnwindSafe,
<<<Model as FitModel>::ParamCount as Conv>::TNum as ArrayLength>::ArrayType<GenericArray<<Model as LevMarModel>::RealScalar, <<Model as FitModel>::ParamCount as Conv>::TNum>>: UnwindSafe,
<<Model as FitModel>::ParamCount as Conv>::Nalg: UnwindSafe,
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
Source§impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
Source§fn to_subset(&self) -> Option<SS>
fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct
self from the equivalent element of its
superset. Read moreSource§fn is_in_subset(&self) -> bool
fn is_in_subset(&self) -> bool
Checks if
self is actually part of its subset T (and can be converted to it).Source§fn to_subset_unchecked(&self) -> SS
fn to_subset_unchecked(&self) -> SS
Use with care! Same as
self.to_subset but without any property checks. Always succeeds.Source§fn from_subset(element: &SS) -> SP
fn from_subset(element: &SS) -> SP
The inclusion map: converts
self to the equivalent element of its superset.