| """ | |
| K5 — Freshness per-cell (R8 fix v3). | |
| """ | |
| import math | |
| import numpy as np | |
| DECAY_LAMBDA = 0.001 | |
| ABS_THRESHOLD = 0.5 # below this magnitude = not "significant" | |
| def compute_k5_percell(cells, current_step): | |
| out = {} | |
| for c in cells: | |
| last = getattr(c, "last_significant_step", None) | |
| if last is None: | |
| last = 0 | |
| age = min(500, max(0, current_step - last)) | |
| out[c.cell_id] = math.exp(-DECAY_LAMBDA * age) | |
| return out | |
| def update_significance(cell, activations, current_step, | |
| abs_threshold=ABS_THRESHOLD): | |
| """ | |
| Cell is 'significant' if its mean |activation| > abs_threshold. | |
| Simple, interpretable, produces real variance across cells. | |
| """ | |
| a = np.abs(activations) | |
| if a.size == 0: | |
| return False | |
| m = float(a.mean()) | |
| cell._last_mag = m # for debugging | |
| if m > abs_threshold: | |
| cell.last_significant_step = current_step | |
| return True | |
| return False |