Struct JointResolutionModel 

pub struct JointResolutionModel { /* private fields */ }

A sample and its calibrant, sharing one Gaussian resolution.

FitModel::evaluate returns the sample’s predictions followed by the calibrant’s, so the caller fits against the two spectra concatenated in that order.

Implementations

impl JointResolutionModel

pub fn new( sample: SpectrumSpec, calibrant: SpectrumSpec, flight_path_m: f64, delta_t_sq_index: usize, delta_l_sq_index: usize, ) -> Result<Self, FittingError>

Build the joint model.

delta_t_sq_index / delta_l_sq_index are the shared slots holding the squared widths. Everything else about each arm, including whether its densities and temperature are fitted, is in its SpectrumSpec — the calibrant’s being known is what makes it a calibrant.

Errors

FittingError::InvalidConfig when a spectrum’s grid is empty, when its density count does not match its isotope count, or when two parameters share a slot.

pub fn sample_len(&self) -> usize

Number of data points the sample contributes, i.e. where the calibrant’s predictions start in FitModel::evaluate’s output.

pub fn len(&self) -> usize

Total length of the concatenated prediction.

pub fn is_empty(&self) -> bool

Whether the joint prediction is empty. Never true: both grids are checked non-empty at construction.

Trait Implementations

impl FitModel for JointResolutionModel

fn evaluate(&self, params: &[f64]) -> Result<Vec<f64>, FittingError>

Evaluate the model for the given parameters.

fn analytical_jacobian( &self, _params: &[f64], _free_param_indices: &[usize], _y_current: &[f64], ) -> Option<FlatMatrix>

Optionally provide an analytical Jacobian.