Take Maia feedbacks on the algo.

custom_components/versatile_thermostat/base_thermostat.py

@@ -113,7 +113,7 @@ from .underlyings import UnderlyingEntity
 
 from .prop_algorithm import PropAlgorithm
 from .open_window_algorithm import WindowOpenDetectionAlgorithm
-from .ema import EstimatedMobileAverage
+from .ema import ExponentialMovingAverage
 
 _LOGGER = logging.getLogger(__name__)
 
@@ -459,11 +459,13 @@ class BaseThermostat(ClimateEntity, RestoreEntity):
 
         self._total_energy = 0
 
-        self._ema_algo = EstimatedMobileAverage(
+        self._ema_algo = ExponentialMovingAverage(
             self.name,
             self._cycle_min * 60,
             # Needed for time calculation
             get_tz(self._hass),
+            # one digit after the coma for temperature
+            1,
         )
 
         _LOGGER.debug(

custom_components/versatile_thermostat/ema.py

@@ -8,7 +8,7 @@ from datetime import datetime, tzinfo
 
 _LOGGER = logging.getLogger(__name__)
 
-MIN_TIME_DECAY_SEC = 5
+MIN_TIME_DECAY_SEC = 0
 # As for the EMA calculation of irregular time series, I've seen that it might be useful to
 # have an upper limit for alpha in case the last measurement was too long ago.
 # For example when using a half life of 10 minutes a measurement that is 60 minutes ago
@@ -17,16 +17,19 @@ MIN_TIME_DECAY_SEC = 5
 MAX_ALPHA = 0.9375
 
 
-class EstimatedMobileAverage:
+class ExponentialMovingAverage:
     """A class that will do the Estimated Mobile Average calculation"""
 
-    def __init__(self, vterm_name: str, halflife: float, timezone: tzinfo):
+    def __init__(
+        self, vterm_name: str, halflife: float, timezone: tzinfo, precision: int = 3
+    ):
         """The halflife is the duration in secondes of a normal cycle"""
         self._halflife: float = halflife
         self._timezone = timezone
         self._current_ema: float = None
         self._last_timestamp: datetime = datetime.now(self._timezone)
         self._name = vterm_name
+        self._precision = precision
 
     def __str__(self) -> str:
         return f"EMA-{self._name}"
@@ -64,8 +67,8 @@ class EstimatedMobileAverage:
 
         alpha = 1 - math.exp(math.log(0.5) * time_decay / self._halflife)
         # capping alpha to avoid gap if last measurement was long time ago
-        alpha = min(alpha, 0.9375)
-        new_ema = round(alpha * measurement + (1 - alpha) * self._current_ema, 1)
+        alpha = min(alpha, MAX_ALPHA)
+        new_ema = alpha * measurement + (1 - alpha) * self._current_ema
 
         self._last_timestamp = timestamp
         self._current_ema = new_ema
@@ -77,4 +80,4 @@ class EstimatedMobileAverage:
             self._last_timestamp,
         )
 
-        return self._current_ema
+        return round(self._current_ema, self._precision)

tests/test_ema.py

@@ -4,7 +4,7 @@ from datetime import datetime, timedelta
 
 from homeassistant.core import HomeAssistant
 
-from custom_components.versatile_thermostat.ema import EstimatedMobileAverage
+from custom_components.versatile_thermostat.ema import ExponentialMovingAverage
 
 from .commons import get_tz
 
@@ -15,12 +15,13 @@ def test_ema_basics(hass: HomeAssistant):
     tz = get_tz(hass)  # pylint: disable=invalid-name
     now: datetime = datetime.now(tz=tz)
 
-    the_ema = EstimatedMobileAverage(
+    the_ema = ExponentialMovingAverage(
         "test",
         # 5 minutes
         300,
         # Needed for time calculation
         get_tz(hass),
+        1,
     )
 
     assert the_ema