feat(application): integrate measured-load ingestion training and planner source

services/netplan-v4/acceptance/forecast-src/model_isolation.py

@@ -0,0 +1,45 @@
+"""Forecast family fault isolation; no IO, fabricated samples or model switching."""
+from collections.abc import Mapping
+from math import isfinite
+from numbers import Real
+
+
+def collect_predictions(data, config, models, enabled):
+    """Return complete finite PV/load series independently for each requested model.
+
+    A model with insufficient history must not prevent other valid families being
+    published. It is omitted, not filled with zeros or replaced by another model.
+    Global raw-telemetry checks still run BEFORE this helper in run_forecast.
+    """
+    expected = tuple(data['df_fut'].index)
+    if not expected or len(set(expected)) != len(expected):
+        raise ValueError('Nonempty unique future interval index required')
+    expected_keys = set(expected)
+    predictions, errors = {}, {}
+    requested = 0
+    for variant, model in models.items():
+        predictions[variant] = {}
+        if not enabled(config, variant):
+            continue
+        requested += 1
+        try:
+            values = model.predict(data)
+            if not isinstance(values, Mapping) or set(values) != expected_keys:
+                raise ValueError('Missing, extra or non-matching forecast timestamps')
+            cleaned = {}
+            for at in expected:
+                value = values[at]
+                if isinstance(value, bool) or not isinstance(value, Real):
+                    raise ValueError('Non-numeric forecast power')
+                value = float(value)
+                if not isfinite(value) or value < 0:
+                    raise ValueError('Invalid nonnegative forecast power')
+                cleaned[at] = value
+            predictions[variant] = cleaned
+        except Exception as error:
+            # Expected data failures and unexpected model failures are visible,
+            # but model exception text may contain filesystem paths. Do not leak it.
+            errors[variant] = {'status': 'unavailable', 'errorType': type(error).__name__}
+    if requested and all(not p for p in predictions.values()):
+        raise ValueError('All requested PV/load models failed; no forecasts published')
+    return predictions, errors