morphe-metrics: A Stateless Python Library for Morphogenetic Computing Evaluation

Morphe-metrics is the first open-source Python library for evaluating field-guided connectivity in morphogenetic neural networks — systems whose topology self-organises via bioelectric-analog voltage gradient signals. The primary metric is Edge-Field Concordance (EFC): the Pearson correlation between bioelectric field strength at candidate neighbour nodes and edge formation probability. EFC was introduced and first measured empirically in Maya-Morphe P3: Axon (DOI: 10.5281/zenodo.20102536), yielding EFC = -0.009 to -0.019 (exploratory regime) across 576 trials at 7 scales. The library provides 4 modules: EFCMetrics (compute_efc, interpret_efc, efc_summary), EFCTracker (epoch-level trajectory logging),…