Struct BsdeSolution 

pub struct BsdeSolution<const N: usize> {
    pub coefficients: Vec<Vec<f64>>,
    pub basis_type: BasisFunctionType,
    pub dt: f64,
    pub steps: usize,
    pub x_init: [f64; N],
    pub feature_scale: Vec<f64>,
    pub clamp_range: Option<(f64, f64)>,
    pub gradient_steps: [f64; N],
    pub v0: f64,
    pub control_t0: ControlOutput<N>,
}

Complete BSDE solution storing regression coefficients for all time steps.

Enables point evaluation of the value function and optimal controls at any (time_index, state) pair without re-running the solver.

Fields

coefficients: Vec<Vec<f64>>

Regression coefficients at each backward time step. coefficients[t] contains the basis weights at time index t.

basis_type: BasisFunctionType

Basis function configuration.

dt: f64

Time step size.

steps: usize

Number of backward time steps.

x_init: [f64; N]

Initial state used for centering.

feature_scale: Vec<f64>

Feature scaling per dimension.

clamp_range: Option<(f64, f64)>

Clamping range for basis inputs.

gradient_steps: [f64; N]

Gradient step sizes per dimension.

v0: f64

Value function at t=0 and x_init.

control_t0: ControlOutput<N>

Optimal control at t=0 and x_init.

Implementations

impl<const N: usize> BsdeSolution<N>

pub fn evaluate(&self, time_index: usize, state: &[f64; N]) -> f64

Evaluate the value function at a given time index and state.

time_index ranges from 0 (start) to self.steps (terminal).

pub fn evaluate_control<M: Model<N>>( &self, time_index: usize, state: &[f64; N], model: &M, ) -> ControlOutput<N>

Evaluate optimal control at a given time index and state.

pub fn evaluate_spread_trajectory<M: Model<N>>( &self, state: &[f64; N], model: &M, a: f64, kappa: f64, ) -> Vec<(f64, f64)>

Evaluate optimal spreads across all time steps for a given state.

Returns vectors of (bid_spread, ask_spread) for each time step from 0 to steps-1.

pub fn time_to_index(&self, t: f64) -> usize

Convert a time value to the nearest time index. t is time elapsed from 0 (start of horizon).