change methods and docstrings to use lower case h for hour

jarq6c · Feb 9, 2024 · 3f39564 · 3f39564
1 parent 1e8c0bb
commit 3f39564
Showing 1 changed file with 8 additions and 8 deletions.
diff --git a/python/events/src/hydrotools/events/event_detection/decomposition.py b/python/events/src/hydrotools/events/event_detection/decomposition.py
@@ -212,8 +212,8 @@ def mark_event_flows(
     series: pd.Series,
     halflife: Union[float, str, pd.Timedelta],
     window: Union[int, pd.tseries.offsets.DateOffset, pd.Index],
-    minimum_event_duration: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0H',
-    start_radius: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0H'
+    minimum_event_duration: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0h',
+    start_radius: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0h'
     ) -> pd.Series:
     """Model the trend in a streamflow time series by taking the max
         of two rolling minimum filters applied in a forward and 
@@ -236,10 +236,10 @@ def mark_event_flows(
         window: int, offset, or BaseIndexer subclass, required
             Size of the moving window for `pandas.Series.rolling.min`.
             This filter is used to model the trend in `series`.
-        minimum_event_duration: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0H'
+        minimum_event_duration: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0h'
             Enforce a minimum event duration. This should generally be set equal to 
             halflife to reduce the number of false positives flagged as events.
-        start_radius: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0H'
+        start_radius: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0h'
             Shift event starts to a local minimum. Phase shifts imparted on the 
             original signal may advance or delay event start times depending upon how 
             much smoothing is required to eliminate noise.
@@ -293,8 +293,8 @@ def list_events(
     series: pd.Series,
     halflife: Union[float, str, pd.Timedelta],
     window: Union[int, pd.tseries.offsets.DateOffset, pd.Index],
-    minimum_event_duration: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0H',
-    start_radius: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0H'
+    minimum_event_duration: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0h',
+    start_radius: Union[pd.Timedelta, datetime.timedelta, np.timedelta64, str, int] = '0h'
     ) -> pd.DataFrame:
     """Apply time series decomposition to mark event values in a streamflow
         time series. Discretize continuous event values into indiviual events.
@@ -312,10 +312,10 @@ def list_events(
         window: int, offset, or BaseIndexer subclass, required
             Size of the moving window for `pandas.Series.rolling.min`.
             This filter is used to model the trend in `series`.
-        minimum_event_duration: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0H'
+        minimum_event_duration: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0h'
             Enforce a minimum event duration. This should generally be set equal to 
             halflife to reduce the number of false positives flagged as events.
-        start_radius: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0H'
+        start_radius: pandas.Timedelta, datetime.timedelta, numpy.timedelta64, str, int, optional, default '0h'
             Shift event starts to a local minimum. Phase shifts imparted on the 
             original signal may advance or delay event start times depending upon how 
             much smoothing is required to eliminate noise.