Show learning activity with Learning Progress and Last Sample sensors

During a first test the Status entity only said "learning" for the
first half hour (the radiator-lag wait after a restart), and the
attributes explaining why were hard to find. Add two sensors:

- Learning Progress (%): for the least trained room, the mean of its
  three readiness requirements (200 samples, 30 ON, 30 OFF), each capped
  at 100 %; 100 % means ready. Attributes show the counts.
- Last Sample: an enum of the last poll's learning outcome, with English
  and Romanian state names (e.g. "Waiting for radiators to settle"). Its
  history shows when learning happens.

Polls blocked by missing shared inputs now report waiting_for_inputs.
Readiness thresholds move to const.py.

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

custom_components/heating_mpc/sensor.py

@@ -2,16 +2,19 @@
 from __future__ import annotations
 
 from homeassistant.components.sensor import SensorDeviceClass, SensorEntity, SensorStateClass
-from homeassistant.const import UnitOfTemperature
+from homeassistant.const import PERCENTAGE, UnitOfTemperature
 from homeassistant.helpers.update_coordinator import CoordinatorEntity
 
-from .const import DOMAIN
+from .const import (
+    DOMAIN, READY_OFF_SAMPLES, READY_ON_SAMPLES, READY_SAMPLES, SAMPLE_RESULTS,
+)
 from .evaluation import HORIZONS, WINDOW_DAYS
 
 
 async def async_setup_entry(hass, entry, async_add_entities) -> None:
     coordinator = hass.data[DOMAIN][entry.entry_id]
-    entities = [MPCStatus(coordinator, entry.entry_id), MPCWeightedTemp(coordinator, entry.entry_id), MPCOutdoorTemperature(coordinator, entry.entry_id)]
+    entities = [MPCStatus(coordinator, entry.entry_id), MPCWeightedTemp(coordinator, entry.entry_id), MPCOutdoorTemperature(coordinator, entry.entry_id),
+                MPCLearningProgress(coordinator, entry.entry_id), MPCLastSample(coordinator, entry.entry_id)]
     entities += [MPCRoomPrediction(coordinator, entry.entry_id, room) for room in coordinator.rooms]
     entities += [MPCForecastError(coordinator, entry.entry_id, horizon) for horizon in HORIZONS]
     async_add_entities(entities)
@@ -147,3 +150,55 @@ class MPCForecastError(CoordinatorEntity, SensorEntity):
             "basis": ("thermal model replayed with the actual relay history; outdoor "
                       "temperature held at the start value"),
         }
+
+
+class MPCLearningProgress(CoordinatorEntity, SensorEntity):
+    """How close the least trained room is to being used for forecasts."""
+    _attr_has_entity_name = True
+    _attr_name = "Heating MPC Learning Progress"
+    _attr_native_unit_of_measurement = PERCENTAGE
+    _attr_state_class = SensorStateClass.MEASUREMENT
+    _attr_suggested_display_precision = 0
+    _attr_icon = "mdi:school-outline"
+
+    def __init__(self, coordinator, entry_id):
+        super().__init__(coordinator)
+        self._attr_unique_id = f"{entry_id}_learning_progress"
+
+    @property
+    def native_value(self):
+        return self.coordinator.data.get("learning_progress")
+
+    @property
+    def extra_state_attributes(self):
+        data = self.coordinator.data
+        return {
+            "samples": data.get("samples"),
+            "on_samples": data.get("on_samples"),
+            "off_samples": data.get("off_samples"),
+            "required": {"samples": READY_SAMPLES, "on_samples": READY_ON_SAMPLES,
+                         "off_samples": READY_OFF_SAMPLES},
+        }
+
+
+class MPCLastSample(CoordinatorEntity, SensorEntity):
+    """What the last poll did for learning; its history shows when learning happens."""
+    _attr_has_entity_name = True
+    _attr_name = "Heating MPC Last Sample"
+    _attr_translation_key = "last_sample"  # translated state names
+    _attr_device_class = SensorDeviceClass.ENUM
+    _attr_options = list(SAMPLE_RESULTS)
+    _attr_icon = "mdi:clipboard-pulse-outline"
+    _unrecorded_attributes = frozenset({"counts_since_start"})
+
+    def __init__(self, coordinator, entry_id):
+        super().__init__(coordinator)
+        self._attr_unique_id = f"{entry_id}_last_sample"
+
+    @property
+    def native_value(self):
+        return self.coordinator.data.get("sample_result")
+
+    @property
+    def extra_state_attributes(self):
+        return {"counts_since_start": self.coordinator.data.get("sample_results_since_start", {})}