Struct MathEngine 

pub struct MathEngine { /* private fields */ }

Main mathematical engine for memory consolidation calculations

Implementations

impl MathEngine

pub fn new() -> Self

Create a new math engine with default configuration

pub fn with_config(config: MathEngineConfig) -> Self

Create a new math engine with custom configuration

pub fn config(&self) -> &MathEngineConfig

Get the current configuration

pub fn update_config(&mut self, config: MathEngineConfig)

Update the configuration

pub fn calculate_recall_probability( &self, params: &MemoryParameters, ) -> Result<RecallCalculationResult>

Calculate recall probability using the exact forgetting curve formula

Formula: p(t) = [1 - exp(-r * e^(-t/gn))] / (1 - e^(-1))

Arguments

• params - Memory parameters for calculation

Returns

• Result<RecallCalculationResult> - Calculation result or error

Performance

Target: <10ms per calculation

pub fn update_consolidation_strength( &self, current_strength: f64, recall_interval: PgInterval, ) -> Result<ConsolidationUpdateResult>

Update consolidation strength using the exact formula

Formula: gn = gn-1 + (1 - e^(-t)) / (1 + e^(-t))

Arguments

• current_strength - Current consolidation strength
• recall_interval - Time interval since last recall

Returns

• Result<ConsolidationUpdateResult> - Update result or error

pub fn calculate_decay_rate(&self, params: &MemoryParameters) -> Result<f64>

Calculate decay rate based on access patterns

This function calculates an adaptive decay rate based on access frequency, importance score, and memory age. More important and frequently accessed memories have lower decay rates.

Arguments

• params - Memory parameters for calculation

Returns

• Result<f64> - Calculated decay rate

pub fn batch_calculate_recall_probability( &self, memory_params: &[MemoryParameters], ) -> Result<BatchProcessingResult>

Batch process multiple memories for recall probability calculation

This function optimizes performance by processing multiple memories in a single operation, reducing overhead and improving throughput.

Arguments

• memory_params - Vector of memory parameters

Returns

• Result<BatchProcessingResult> - Batch processing results

pub fn should_migrate( &self, recall_probability: f64, current_tier: &str, ) -> bool

Determine if a memory should migrate to the next tier

Arguments

• recall_probability - Current recall probability
• current_tier - Current memory tier

Returns

• bool - True if memory should migrate

pub fn validate_accuracy(&self, expected: f64, actual: f64) -> Result<()>

Validate calculation accuracy against expected result

Arguments

• expected - Expected value
• actual - Actual calculated value

Returns

• Result<()> - Ok if within tolerance, error otherwise

Trait Implementations

impl Clone for MathEngine

fn clone(&self) -> MathEngine

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MathEngine

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

Formats the value using the given formatter.

impl Default for MathEngine

fn default() -> Self

Returns the “default value” for a type.