Add ema calculation class, calculate an emo temperature, use the ema_temperature in auto_window dectection
This commit is contained in:
@@ -109,10 +109,13 @@ from .const import (
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PRESET_AC_SUFFIX,
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PRESET_AC_SUFFIX,
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)
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)
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from .commons import get_tz
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from .underlyings import UnderlyingEntity
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from .underlyings import UnderlyingEntity
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from .prop_algorithm import PropAlgorithm
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from .prop_algorithm import PropAlgorithm
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from .open_window_algorithm import WindowOpenDetectionAlgorithm
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from .open_window_algorithm import WindowOpenDetectionAlgorithm
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from .ema import EstimatedMobileAverage
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_LOGGER = logging.getLogger(__name__)
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_LOGGER = logging.getLogger(__name__)
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@@ -246,6 +249,8 @@ class BaseThermostat(ClimateEntity, RestoreEntity):
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self._underlyings = []
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self._underlyings = []
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self._smooth_temp = None
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self._ema_algo = None
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self.post_init(entry_infos)
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self.post_init(entry_infos)
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def post_init(self, entry_infos):
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def post_init(self, entry_infos):
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@@ -450,6 +455,13 @@ class BaseThermostat(ClimateEntity, RestoreEntity):
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self._total_energy = 0
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self._total_energy = 0
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self._ema_algo = EstimatedMobileAverage(
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self.name,
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self._cycle_min * 60,
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# Needed for time calculation
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get_tz(self._hass),
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)
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_LOGGER.debug(
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_LOGGER.debug(
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"%s - Creation of a new VersatileThermostat entity: unique_id=%s",
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"%s - Creation of a new VersatileThermostat entity: unique_id=%s",
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self,
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self,
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@@ -1476,6 +1488,11 @@ class BaseThermostat(ClimateEntity, RestoreEntity):
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self._last_temperature_mesure = self.get_state_date_or_now(state)
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self._last_temperature_mesure = self.get_state_date_or_now(state)
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# calculate the smooth_temperature with EMA calculation
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self._ema_temp = self._ema_algo.calculate_ema(
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self._cur_temp, self._last_temperature_mesure
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)
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_LOGGER.debug(
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_LOGGER.debug(
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"%s - After setting _last_temperature_mesure %s , state.last_changed.replace=%s",
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"%s - After setting _last_temperature_mesure %s , state.last_changed.replace=%s",
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self,
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self,
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@@ -1679,7 +1696,7 @@ class BaseThermostat(ClimateEntity, RestoreEntity):
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return
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return
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slope = self._window_auto_algo.add_temp_measurement(
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slope = self._window_auto_algo.add_temp_measurement(
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temperature=self._cur_temp, datetime_measure=self._last_temperature_mesure
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temperature=self._ema_temp, datetime_measure=self._last_temperature_mesure
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)
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)
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_LOGGER.debug(
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_LOGGER.debug(
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"%s - Window auto is on, check the alert. last slope is %.3f",
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"%s - Window auto is on, check the alert. last slope is %.3f",
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@@ -2155,6 +2172,7 @@ class BaseThermostat(ClimateEntity, RestoreEntity):
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"max_power_sensor_entity_id": self._max_power_sensor_entity_id,
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"max_power_sensor_entity_id": self._max_power_sensor_entity_id,
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"temperature_unit": self.temperature_unit,
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"temperature_unit": self.temperature_unit,
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"is_device_active": self.is_device_active,
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"is_device_active": self.is_device_active,
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"ema_temp": self._ema_temp,
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}
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}
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@callback
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@callback
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80
custom_components/versatile_thermostat/ema.py
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80
custom_components/versatile_thermostat/ema.py
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@@ -0,0 +1,80 @@
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# pylint: disable=line-too-long
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"""The Estimated Mobile Average calculation used for temperature slope
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and maybe some others feature"""
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import logging
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import math
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from datetime import datetime, tzinfo
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_LOGGER = logging.getLogger(__name__)
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MIN_TIME_DECAY_SEC = 5
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# As for the EMA calculation of irregular time series, I've seen that it might be useful to
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# have an upper limit for alpha in case the last measurement was too long ago.
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# For example when using a half life of 10 minutes a measurement that is 60 minutes ago
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# (if there's nothing inbetween) would contribute to the smoothed value with 1,5%,
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# giving the current measurement 98,5% relevance. It could be wise to limit the alpha to e.g. 4x the half life (=0.9375).
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MAX_ALPHA = 0.9375
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class EstimatedMobileAverage:
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"""A class that will do the Estimated Mobile Average calculation"""
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def __init__(self, vterm_name: str, halflife: float, timezone: tzinfo):
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"""The halflife is the duration in secondes of a normal cycle"""
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self._halflife: float = halflife
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self._timezone = timezone
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self._current_ema: float = None
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self._last_timestamp: datetime = datetime.now(self._timezone)
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self._name = vterm_name
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def __str__(self) -> str:
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return f"EMA-{self._name}"
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def calculate_ema(self, measurement: float, timestamp: datetime) -> float | None:
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"""Calculate the new EMA from a new measurement measured at timestamp
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Return the EMA or None if all parameters are not initialized now
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"""
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if measurement is None or timestamp is None:
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_LOGGER.warning(
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"%s - Cannot calculate EMA: measurement and timestamp are mandatory. This message can be normal at startup but should not persist",
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self,
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)
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return measurement
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if self._current_ema is None:
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_LOGGER.debug(
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"%s - First init of the EMA",
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self,
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)
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self._current_ema = measurement
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self._last_timestamp = timestamp
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return self._current_ema
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time_decay = (timestamp - self._last_timestamp).total_seconds()
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if time_decay < MIN_TIME_DECAY_SEC:
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_LOGGER.debug(
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"%s - time_decay %s is too small (< %s). Forget the measurement",
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self,
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time_decay,
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MIN_TIME_DECAY_SEC,
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)
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return self._current_ema
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alpha = 1 - math.exp(math.log(0.5) * time_decay / self._halflife)
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# capping alpha to avoid gap if last measurement was long time ago
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alpha = min(alpha, 0.9375)
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new_ema = round(alpha * measurement + (1 - alpha) * self._current_ema, 1)
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self._last_timestamp = timestamp
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self._current_ema = new_ema
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_LOGGER.debug(
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"%s - alpha=%.2f new_ema=%.2f last_timestamp=%s",
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self,
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alpha,
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self._current_ema,
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self._last_timestamp,
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)
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return self._current_ema
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@@ -49,6 +49,7 @@ class PITemperatureRegulator:
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self.target_temp = target_temp
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self.target_temp = target_temp
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# Do not reset the accumulated error
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# Do not reset the accumulated error
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# Discussion #191. After a target change we should reset the accumulated error which is certainly wrong now.
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# Discussion #191. After a target change we should reset the accumulated error which is certainly wrong now.
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if self.accumulated_error < 0:
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self.accumulated_error = 0
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self.accumulated_error = 0
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def calculate_regulated_temperature(
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def calculate_regulated_temperature(
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53
tests/test_ema.py
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53
tests/test_ema.py
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@@ -0,0 +1,53 @@
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# pylint: disable=line-too-long
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""" Tests de EMA calculation"""
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from datetime import datetime, timedelta
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from homeassistant.core import HomeAssistant
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from custom_components.versatile_thermostat.ema import EstimatedMobileAverage
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from .commons import get_tz
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def test_ema_basics(hass: HomeAssistant):
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"""Test the EMA calculation with basic features"""
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tz = get_tz(hass) # pylint: disable=invalid-name
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now: datetime = datetime.now(tz=tz)
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the_ema = EstimatedMobileAverage(
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"test",
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# 5 minutes
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300,
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# Needed for time calculation
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get_tz(hass),
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)
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assert the_ema
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current_timestamp = now
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# First initialization
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assert the_ema.calculate_ema(20, current_timestamp) == 20
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current_timestamp = current_timestamp + timedelta(minutes=1)
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# One minute later, same temperature. EMA temperature should not have change
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assert the_ema.calculate_ema(20, current_timestamp) == 20
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# Too short measurement should be ignored
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assert the_ema.calculate_ema(2000, current_timestamp) == 20
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current_timestamp = current_timestamp + timedelta(seconds=4)
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assert the_ema.calculate_ema(20, current_timestamp) == 20
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# a new normal measurement 5 minutes later
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current_timestamp = current_timestamp + timedelta(minutes=5)
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ema = the_ema.calculate_ema(25, current_timestamp)
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assert ema > 20
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assert ema == 22.5
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# a big change in a short time does have a limited effect
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current_timestamp = current_timestamp + timedelta(seconds=5)
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ema = the_ema.calculate_ema(30, current_timestamp)
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assert ema > 22.5
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assert ema < 23
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assert ema == 22.6
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