dendro: adjust grouper function

level1/do_dendro_calculation.py

@@ -25,16 +25,21 @@ def filter(data, flags):
     return data[data.columns[data.columns.str.match(".*dendro(?!.*r)")]]
 
 
-def grouper(n, df, fillvalue=None):
-    # the customized grouper function split a dataframe, so that the output is a n columns long dataframe
-    # in the dendro calculation, one tree correspond to one dendrometer
-    # this consist of 3 columns: the calculated value, the manually read value and the flag
+def grouper(df, n, fillvalue=None):
+    """
+    This grouper function splits a pd.DataFrame into pd.DataFrames with `n` columns.
+
+    Background: Every dendrometer (i.e one tree) is represented by three columns:
+    1. calculated value
+    2. manually read value
+    3. quality flag
+    """
     args = [iter(df)] * n
     return zip_longest(fillvalue=fillvalue, *args)
 
 
 def fillNa(df):
-    for bhd_value, bhd_manu, flag in grouper(3, df):
+    for bhd_value, bhd_manu, flag in grouper(df, n=3):
         # setting 91 flag on all values, where calculated value is nan
         df.loc[df[bhd_value].isna(), flag] = 91
         df[bhd_value] = df[bhd_value].fillna(df[bhd_manu])
@@ -177,7 +182,7 @@ def main(station, device, start_date, end_date, debug):
 
         # corrections in index Order and not setted flags
         final = final.sort_index()
-        for a, b, c in grouper(3, final):
+        for a, b, c in grouper(final, n=3):
             final = final.fillna({a: NODATA, b: NODATA, c: 92})
 
         writeData(final, device)