Merge pull request #387 from NannyML/feat/value-limit-defaults-summar…

…y-stats Replace `np.NaN` values for value limits in summary statistics
NannyML · May 15, 2024 · 9f046be · 9f046be
2 parents a213cd3 + aa60aeb
commit 9f046be
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Showing 5 changed files with 9 additions and 9 deletions.
diff --git a/nannyml/stats/avg/calculator.py b/nannyml/stats/avg/calculator.py
@@ -97,8 +97,8 @@ def __init__(
         self._upper_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
         self._lower_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
 
-        self.lower_threshold_value_limit: float = np.nan
-        self.upper_threshold_value_limit: float = np.nan
+        self.lower_threshold_value_limit: Optional[float] = None
+        self.upper_threshold_value_limit: Optional[float] = None
         self.simple_stats_metric = 'values_avg'
 
     @log_usage(UsageEvent.STATS_AVG_FIT)

diff --git a/nannyml/stats/count/calculator.py b/nannyml/stats/count/calculator.py
@@ -75,8 +75,8 @@ def __init__(
         self._upper_alert_threshold: Optional[float] = 0
         self._lower_alert_threshold: Optional[float] = 0
 
-        self.lower_threshold_value_limit: float = 0
-        self.upper_threshold_value_limit: float = np.nan
+        self.lower_threshold_value_limit: Optional[float] = 0
+        self.upper_threshold_value_limit: Optional[float] = None
         self.simple_stats_metric = 'rows_count'
 
     def _calculate_count_value_stats(self, data: pd.DataFrame):

diff --git a/nannyml/stats/median/calculator.py b/nannyml/stats/median/calculator.py
@@ -101,8 +101,8 @@ def __init__(
         self._upper_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
         self._lower_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
 
-        self.lower_threshold_value_limit: float = np.nan
-        self.upper_threshold_value_limit: float = np.nan
+        self.lower_threshold_value_limit: Optional[float] = None
+        self.upper_threshold_value_limit: Optional[float] = None
         self.simple_stats_metric = 'values_median'
 
     @log_usage(UsageEvent.STATS_MEDIAN_FIT)

diff --git a/nannyml/stats/std/calculator.py b/nannyml/stats/std/calculator.py
@@ -102,7 +102,7 @@ def __init__(
         self._upper_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
         self._lower_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
 
-        self.lower_threshold_value_limit: float = 0
+        self.lower_threshold_value_limit: Optional[float] = 0
         self.upper_threshold_value_limit: Optional[float] = None
         self.simple_stats_metric = 'values_std'
 

diff --git a/nannyml/stats/sum/calculator.py b/nannyml/stats/sum/calculator.py
@@ -96,8 +96,8 @@ def __init__(
         self._upper_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
         self._lower_alert_thresholds: Dict[str, Optional[float]] = {column_name: 0 for column_name in self.column_names}
 
-        self.lower_threshold_value_limit: float = np.nan
-        self.upper_threshold_value_limit: float = np.nan
+        self.lower_threshold_value_limit: Optional[float] = None
+        self.upper_threshold_value_limit: Optional[float] = None
         self.simple_stats_metric = 'values_sum'
 
     @log_usage(UsageEvent.STATS_SUM_FIT)