Struct ReportInput 

pub struct ReportInput {

    pub model_path: String,
    pub family_name: String,
    pub model_class: String,
    pub formula: String,
    pub n_obs: Option<usize>,
    pub deviance: f64,
    pub reml_score: f64,
    pub iterations: usize,
    pub convergence_status: String,
    pub converged: bool,
    pub outer_gradient_norm: Option<f64>,
    pub criterion_certificate: Option<CriterionCertificateRow>,
    pub edf_total: f64,
    pub r_squared: Option<f64>,
    pub coefficients: Vec<CoefficientRow>,
    pub edf_blocks: Vec<EdfBlockRow>,
    pub continuous_order: Vec<ContinuousOrderRow>,
    pub anisotropic_scales: Vec<AnisotropicScalesRow>,
    pub measure_jet_spectra: Vec<MeasureJetSpectrumRow>,
    pub diagnostics: Option<DiagnosticsInput>,
    pub smooth_plots: Vec<SmoothPlotData>,
    pub alo: Option<AloData>,
    pub notes: Vec<String>,
}

Fields

model_path: String

family_name: String

model_class: String

formula: String

n_obs: Option<usize>

deviance: f64

reml_score: f64

iterations: usize

convergence_status: String

Human-readable P-IRLS / outer convergence status (e.g. “Converged”, “Max iterations reached”). Plain text so report.rs stays free of gam library types; main.rs supplies PirlsStatus::label().

converged: bool

Whether the fit cleanly converged. Drives the visual flag on the convergence line — any non-converged state is highlighted.

outer_gradient_norm: Option<f64>

Final outer-objective gradient norm at the recorded solution, when the outer loop measured it (None for cache-hit / gradient-free exits).

criterion_certificate: Option<CriterionCertificateRow>

First-order optimality certificate (#934), when the fit recorded one. Plain data so report.rs stays free of gam library types; main.rs maps the fit’s CriterionCertificate into this row.

edf_total: f64

r_squared: Option<f64>

coefficients: Vec<CoefficientRow>

edf_blocks: Vec<EdfBlockRow>

continuous_order: Vec<ContinuousOrderRow>

anisotropic_scales: Vec<AnisotropicScalesRow>

measure_jet_spectra: Vec<MeasureJetSpectrumRow>

diagnostics: Option<DiagnosticsInput>

smooth_plots: Vec<SmoothPlotData>

alo: Option<AloData>

notes: Vec<String>