Struct LossFunctionEvaluation 

pub struct LossFunctionEvaluation {
    pub value: f64,
    pub lindhard_evaluations: u64,
    pub unconverged_cells: u64,
    pub unconverged_error: f64,
    pub largest_interval_rules: u64,
}

One evaluation of the full Penn loss function Im[-1/ε(q, ω)] (FullPenn::loss_function_evaluation): the value, the work of its adaptive ω_p integral, and whether every cell of that integral met its tolerance.

The bisection of each knot interval of the ω_p integral has a budget of rule applications (#298; the rule and the budget are documented on the weighted quadrature in quadrature.rs and in the module docs). A cell that did not meet its tolerance (budget spent, maximum depth reached, or midpoint no longer representable) keeps its estimate, is counted in unconverged_cells, and contributes its error estimate to unconverged_error; Self::converged is then false.

Fields

value: f64

Im[-1/ε(q, ω)] (dimensionless), as FullPenn::loss_function.

lindhard_evaluations: u64

Evaluations of the Lindhard continuum loss function in the ω_p integral: the work, a deterministic count.

unconverged_cells: u64

Cells of the ω_p integral accepted without meeting their tolerance.

unconverged_error: f64

The sum of the error estimates of those cells, in the units of value (zero when the integral converged).

largest_interval_rules: u64

The most rule applications (of 5 evaluations each) that the bisection of any one knot interval used, at most OMEGA_P_INTERVAL_BUDGET.

Implementations

impl LossFunctionEvaluation

pub fn converged(&self) -> bool

Whether every cell of the ω_p integral met its tolerance.

Trait Implementations

impl Clone for LossFunctionEvaluation

fn clone(&self) -> LossFunctionEvaluation

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Copy for LossFunctionEvaluation

impl Debug for LossFunctionEvaluation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for LossFunctionEvaluation

fn eq(&self, other: &LossFunctionEvaluation) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl StructuralPartialEq for LossFunctionEvaluation