Add a generic named-feature learner for the zone models

Electrical heat, ventilation, wind and inter-zone exchange each need
their own coefficient next to the existing loss/heat/bias, and each must
stay physically bounded and not claim precision it does not have.

learning.py adds FeatureLearner: exponentially weighted RLS over named
features with per-feature bounds, priors at 0 for new effects, the same
covariance windup bound as the base model, and a linked bound that keeps
the directional wind term from cancelling more than the isotropic one.
Each prior is sized as "worth N typical samples" (20 for new effects,
200 for zone coupling, which is weakly identifiable). Confidence is the
share of a coefficient's information that comes from data; the standard
error uses a bias-corrected running noise estimate. Saved models are
matched by feature name, so adding a heat source, window or neighbour
retrains only that coefficient and keeps the covariance of the rest.

The existing 3-parameter learner now uses the same RLS step, covariance
bound and positive-definiteness check (behavior unchanged; all existing
tests pass).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/test_physics.py

@@ -1,14 +1,15 @@
 """Offline tests: run python -m unittest discover -s tests -v."""
-import importlib.util
 import unittest
 from pathlib import Path
 
-path = Path(__file__).resolve().parents[1] / 'custom_components' / 'heating_mpc' / 'physics.py'
-spec = importlib.util.spec_from_file_location('heating_mpc_physics', path)
-m = importlib.util.module_from_spec(spec)
 import sys
-sys.modules[spec.name] = m
-spec.loader.exec_module(m)
+import types
+
+COMPONENTS = Path(__file__).resolve().parents[1] / 'custom_components' / 'heating_mpc'
+# Fake only the package container, to avoid importing Home Assistant from __init__.
+sys.modules.setdefault('heating_mpc', types.ModuleType('heating_mpc'))
+sys.modules['heating_mpc'].__path__ = [str(COMPONENTS)]
+from heating_mpc import physics as m  # noqa: E402
 
 
 class ModelTests(unittest.TestCase):