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Replace returned STATE_UNKNOWN by None (#60324)

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Thomas Dietrich 2021-11-25 12:09:30 +01:00 • committed by GitHub
parent 62bf42e421
commit fd8b43320d
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GPG key ID: 4AEE18F83AFDEB23
1 changed files with 19 additions and 19 deletions
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38
homeassistant/components/statistics/sensor.py
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@ -481,7 +481,7 @@ class StatisticsSensor(SensorEntity):
)
age_range_seconds = (self.ages[-1] - self.ages[0]).total_seconds()
return area / age_range_seconds
return STATE_UNKNOWN
return None
def _stat_average_step(self):
if len(self.states) >= 2:
@ -493,7 +493,7 @@ class StatisticsSensor(SensorEntity):
)
age_range_seconds = (self.ages[-1] - self.ages[0]).total_seconds()
return area / age_range_seconds
return STATE_UNKNOWN
return None
def _stat_average_timeless(self):
return self._stat_mean()
@ -501,19 +501,19 @@ class StatisticsSensor(SensorEntity):
def _stat_change(self):
if len(self.states) > 0:
return self.states[-1] - self.states[0]
return STATE_UNKNOWN
return None
def _stat_change_sample(self):
if len(self.states) > 1:
return (self.states[-1] - self.states[0]) / (len(self.states) - 1)
return STATE_UNKNOWN
return None
def _stat_change_second(self):
if len(self.states) > 1:
age_range_seconds = (self.ages[-1] - self.ages[0]).total_seconds()
if age_range_seconds > 0:
return (self.states[-1] - self.states[0]) / age_range_seconds
return STATE_UNKNOWN
return None
def _stat_count(self):
return len(self.states)
@ -521,37 +521,37 @@ class StatisticsSensor(SensorEntity):
def _stat_datetime_newest(self):
if len(self.states) > 0:
return self.ages[-1]
return STATE_UNKNOWN
return None
def _stat_datetime_oldest(self):
if len(self.states) > 0:
return self.ages[0]
return STATE_UNKNOWN
return None
def _stat_distance_95_percent_of_values(self):
if len(self.states) >= 2:
return 2 * 1.96 * self._stat_standard_deviation()
return STATE_UNKNOWN
return None
def _stat_distance_99_percent_of_values(self):
if len(self.states) >= 2:
return 2 * 2.58 * self._stat_standard_deviation()
return STATE_UNKNOWN
return None
def _stat_distance_absolute(self):
if len(self.states) > 0:
return max(self.states) - min(self.states)
return STATE_UNKNOWN
return None
def _stat_mean(self):
if len(self.states) > 0:
return statistics.mean(self.states)
return STATE_UNKNOWN
return None
def _stat_median(self):
if len(self.states) > 0:
return statistics.median(self.states)
return STATE_UNKNOWN
return None
def _stat_noisiness(self):
if len(self.states) >= 2:
@ -559,7 +559,7 @@ class StatisticsSensor(SensorEntity):
abs(j - i) for i, j in zip(list(self.states), list(self.states)[1:])
)
return diff_sum / (len(self.states) - 1)
return STATE_UNKNOWN
return None
def _stat_quantiles(self):
if len(self.states) > self._quantile_intervals:
@ -571,29 +571,29 @@ class StatisticsSensor(SensorEntity):
method=self._quantile_method,
)
]
return STATE_UNKNOWN
return None
def _stat_standard_deviation(self):
if len(self.states) >= 2:
return statistics.stdev(self.states)
return STATE_UNKNOWN
return None
def _stat_total(self):
if len(self.states) > 0:
return sum(self.states)
return STATE_UNKNOWN
return None
def _stat_value_max(self):
if len(self.states) > 0:
return max(self.states)
return STATE_UNKNOWN
return None
def _stat_value_min(self):
if len(self.states) > 0:
return min(self.states)
return STATE_UNKNOWN
return None
def _stat_variance(self):
if len(self.states) >= 2:
return statistics.variance(self.states)
return STATE_UNKNOWN
return None