maya-metrics: A Stateless Python Library for Affective Neuromorphic Evaluation in Continual Learning SNNs

Maya-metrics is the first open-source Python library for evaluating internal affective and neuromodulatory dynamics in neuromorphic spiking neural networks (SNNs) engaged in class-incremental continual learning (CIL). Six stateless modules: AffectiveMetrics, CrossDimensional, ComplexityMetrics, MaturationIndex, CrossSubstrate, and CLCorrector. Validated against 11 published preprints across two substrates (SNN + LLM) and one embodied PiCar-X deployment. 16/16 unit tests pass. Confirms two series constants programmatically: Bhaya Quiescence Law and Buddhi S-curve determinism. KARMA_DECAY_RATE = 0.002315.