Struct SolverConfig 

#[non_exhaustive]
pub struct SolverConfig {
    pub max_iterations: u32,
    pub learning_rate: f32,
    pub momentum: f32,
    pub discretize_threshold: f32,
}

Configuration parameters for the CLS solver.

These parameters control the behavior of the continuous local search algorithm:

• max_iterations: Maximum number of gradient descent iterations
• learning_rate: Step size for gradient updates
• momentum: Momentum coefficient for velocity accumulation
• discretize_threshold: Threshold for converting continuous values to boolean

Default Values

use xlog_solve::SolverConfig;

let config = SolverConfig::default();
assert_eq!(config.max_iterations, 10000);
assert_eq!(config.learning_rate, 0.1);
assert_eq!(config.momentum, 0.9);
assert_eq!(config.discretize_threshold, 0.5);

Example

use xlog_solve::SolverConfig;

let mut config = SolverConfig::default();
config.max_iterations = 5000;
config.learning_rate = 0.05;
config.momentum = 0.95;
config.discretize_threshold = 0.5;

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

max_iterations: u32

Maximum number of iterations before giving up.

The solver will terminate and return the best-effort result if this limit is reached without finding a satisfying assignment.

learning_rate: f32

Learning rate for gradient descent updates.

Controls the step size when updating variable assignments. Larger values lead to faster convergence but may overshoot. Typical values are in the range [0.01, 0.5].

momentum: f32

Momentum coefficient for velocity accumulation.

Controls how much of the previous velocity is retained. Helps escape local minima and smooths the optimization trajectory. Values close to 1.0 give more weight to history. Typical values are in the range [0.8, 0.99].

discretize_threshold: f32

Threshold for discretizing continuous values to boolean.

Values >= threshold become true, values < threshold become false. The standard value is 0.5 for symmetric treatment.

Implementations

impl SolverConfig

pub const fn new( max_iterations: u32, learning_rate: f32, momentum: f32, discretize_threshold: f32, ) -> Self

Creates a new configuration with specified parameters.

Arguments

• max_iterations - Maximum number of iterations
• learning_rate - Step size for gradient updates
• momentum - Momentum coefficient
• discretize_threshold - Threshold for boolean conversion

pub const fn fast() -> Self

Creates a configuration optimized for fast convergence on small instances.

Uses higher learning rate and fewer iterations.

pub const fn thorough() -> Self

Creates a configuration optimized for thorough search on hard instances.

Uses more iterations and lower learning rate for better exploration.

pub const fn with_max_iterations(self, max_iterations: u32) -> Self

Sets the maximum iterations, consuming and returning self.

pub const fn with_learning_rate(self, learning_rate: f32) -> Self

Sets the learning rate, consuming and returning self.

pub const fn with_momentum(self, momentum: f32) -> Self

Sets the momentum, consuming and returning self.

pub const fn with_discretize_threshold(self, threshold: f32) -> Self

Sets the discretize threshold, consuming and returning self.

Trait Implementations

impl Clone for SolverConfig

fn clone(&self) -> SolverConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SolverConfig

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

Formats the value using the given formatter.

impl Default for SolverConfig

fn default() -> Self

Returns the “default value” for a type.

impl PartialEq for SolverConfig

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

Tests for self and other values to be equal, and is used by ==.

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

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for SolverConfig

impl StructuralPartialEq for SolverConfig