Struct CostModel 

pub struct CostModel { /* private fields */ }

A rolling empirical cost model for a single subsystem (agent / strategy).

Records (n, time) samples in a bounded ring buffer and fits c · f(n) over the candidate ComplexityClasses. Pure and dependency-free.

Implementations

impl CostModel

pub fn new(capacity: usize) -> Self

Creates a model that keeps the most recent capacity samples (min 1).

pub fn record(&mut self, n: f64, time_ms: f64)

Records one (n, time_ms) observation. Overwrites the oldest sample once the ring is full. Non-finite inputs are ignored.

pub fn len(&self) -> usize

Number of samples currently held.

pub fn is_empty(&self) -> bool

Whether no samples have been recorded.

pub fn best_fit(&self) -> Option<(ComplexityClass, f64)>

Fits each complexity class by least squares and returns the best (class, c) — the class with the smallest residual and the constant factor that scales its f(n) to the data.

Returns None until there are at least two samples with distinct n (a single workload size can’t distinguish the classes).

pub fn predict_ms(&self, n: f64) -> Option<f64>

Predicts the cost in milliseconds at workload size n from the best fit. None until best_fit is available.

pub fn latest_ms(&self) -> Option<f64>

The most recently recorded observation’s time in milliseconds, if any.

Fallback cost signal when predict_ms has no fit yet (a stable workload never produces two distinct n values, so the model can’t pick a complexity class — but the raw measurement is still the best available anchor).

Trait Implementations

impl Clone for CostModel

fn clone(&self) -> CostModel

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CostModel

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

Formats the value using the given formatter.