sql first refactor

backend/tests/test_planning_charge_slot_selection.py

@@ -1,10 +1,7 @@
-"""`_select_charge_slots`: pre-selection nabíjecích slotů (anti-micro-cycling).
+"""Pre-selection nabíjecích slotů (anti-micro-cycling) – referenční Python.
 
-Ověřuje novou logiku podle varianty B:
-  - PV-surplus sloty jsou vždy zahrnuty.
-  - Zbytek rozpočtu doplnit nejlevnějšími sloty podle `buy_price` (ne `sell_price`).
-  - Žádné sloty nesmí být vyloučeny kvůli tomu, že nemají PV-surplus, když
-    `charge_slot_buffer` > 0 a ještě chybí energie do `soc_max`.
+Logika je v DB: ems.fn_load_planning_slots_full. Tento soubor drží kopii algoritmu
+pro rychlé unit testy bez PostgreSQL.
 """
 
 from __future__ import annotations
@@ -13,7 +10,50 @@ import unittest
 from datetime import datetime, timezone
 from types import SimpleNamespace
 
-from services.planning_engine import INTERVAL_H, PlanningSlot, _select_charge_slots
+from services.planning_engine import INTERVAL_H, PlanningSlot
+
+
+def _select_charge_slots(
+    slots: list[PlanningSlot],
+    battery: SimpleNamespace,
+    current_soc_wh: float,
+) -> set[int]:
+    """Kopie logiky z ems.fn_load_planning_slots_full (charge mask)."""
+    charge_buf = float(getattr(battery, "charge_slot_buffer", 0) or 0)
+    if charge_buf <= 0:
+        return set(range(len(slots)))
+
+    energy_to_fill = float(battery.soc_max_wh) - float(current_soc_wh)
+    if energy_to_fill <= 0:
+        return set()
+
+    eta = float(getattr(battery, "charge_efficiency", 1.0) or 1.0)
+    max_p_w = float(getattr(battery, "max_charge_power_w", 0.0) or 0.0)
+    per_slot_full_wh = max_p_w * eta * INTERVAL_H
+
+    selected: set[int] = set()
+    for t, s in enumerate(slots):
+        pv_surplus_w = max(0, s.pv_a_forecast_w + s.pv_b_forecast_w - s.load_baseline_w)
+        if pv_surplus_w > 0:
+            selected.add(t)
+
+    grid_target_wh = energy_to_fill * charge_buf
+    if grid_target_wh <= 0 or per_slot_full_wh <= 0:
+        return selected
+
+    grid_candidates = [
+        (t, float(s.buy_price)) for t, s in enumerate(slots) if t not in selected
+    ]
+    grid_candidates.sort(key=lambda x: x[1])
+
+    cumulative = 0.0
+    for t, _price in grid_candidates:
+        if cumulative >= grid_target_wh:
+            break
+        selected.add(t)
+        cumulative += per_slot_full_wh
+
+    return selected
 
 
 def _slot(*, buy: float, sell: float = 1.0, pv: int = 0, load: int = 2_000) -> PlanningSlot: