Struct SelfOptimizingAlgorithm 

pub struct SelfOptimizingAlgorithm { /* private fields */ }

Self-optimizing spatial algorithm

Experimental

This type is gated behind the experimental cargo feature. Its hardware-counter-guided runtime code generation and adaptive memory optimization are research-stage and not yet implemented; calling SelfOptimizingAlgorithm::auto_optimize_and_execute returns an honest SpatialError::NotImplementedError instead of fabricating speedup metrics.

Implementations

impl SelfOptimizingAlgorithm

pub fn new(_algorithmtype: &str) -> Self

Create new self-optimizing algorithm

pub fn with_hardware_counter_feedback(self, enabled: bool) -> Self

Enable hardware performance counter feedback

pub fn with_runtime_code_generation(self, enabled: bool) -> Self

Enable runtime code generation

pub fn with_adaptive_memory_patterns(self, enabled: bool) -> Self

Enable adaptive memory patterns

pub async fn auto_optimize_and_execute( &mut self, data: &ArrayView2<'_, f64>, ) -> SpatialResult<Array1<usize>>

Auto-optimize and execute the configured algorithm.

Status

Not implemented. The runtime self-optimization pipeline (hardware performance-counter feedback, just-in-time code generation, and adaptive memory-pattern selection) is research-stage and has no working backend.

Earlier revisions of this method returned a fixed i % 2 two-cluster labelling together with fabricated before/after performance metrics (e.g. a hard-coded “10x speedup”). That fabricated success has been removed: the method now returns an honest SpatialError::NotImplementedError. Callers that need real clustering should use the algorithms in the cluster family directly.

The data argument is validated for shape so that the error message can report the problem size, but no optimization or clustering is performed.

Trait Implementations

impl Debug for SelfOptimizingAlgorithm

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

Formats the value using the given formatter.