fixed time difference for monthly and annual sampling

added documentation

toargridding/metadata.py

@@ -67,7 +67,7 @@ class TimeSample:
     def daterange_option(self) -> str:
         """Conversion of range to a string
 
-        Range is given as start<=incuded days < end
+        Range is given as [start, end)
         """
         end_with_padding = self.end + timedelta(1)
         return f"{self.start.isoformat()},{end_with_padding.isoformat()}"
@@ -84,9 +84,8 @@ class TimeSample:
         Calculates the duration in days relative to start time point.
         """
         
-        #TODO: could this be an issue for monthly sampling?
-        n_days = (self.end - self.start).days
-        return np.arange(n_days + 1)
+        tp = self.as_datetime_index()
+        return np.array([ (t - tp[0]).days for t in tp])
 
 
 @dataclass
@@ -121,8 +120,6 @@ class Metadata:
         """
 
         variable = TOARVariable.get(standart_name)
-
-
         return Metadata(variable, time, stat)
     
     @property
@@ -209,6 +206,7 @@ def get_cf_metadata(variable: Variables, metadata: Metadata | None)-> Dict:
     
     The resulting dictionary contains the required values for the netCDF files.
     """
+    
     match variable.name:
         case Variables.latitude.name:
             cf_metadata = {

toargridding/static_metadata.py

@@ -49,8 +49,14 @@ class TOARVariable:
     @classmethod
     def get(cls, standart_name: str) -> "TOARVariable":
         """searches the known variables for the requested variable
+        
+        Parameters:
+        ----------
+        standart_name:
+            name of the variable following the CF convention.
 
-        return: provides direct access to the meta data of the selected variable
+        return:
+            provides direct access to the meta data of the selected variable
         """
         for var in cls.vars:
             if var.standart_name == standart_name:

toargridding/toar_rest_client.py

@@ -380,7 +380,16 @@ class AnalysisServiceDownload(AnalysisService):
         self.sample_dir = sample_dir
         self.use_downloaded = use_downloaded
 
-    def get_timeseries_and_metadata(self, metadata: Metadata):
+    def get_timeseries_and_metadata(self, metadata: Metadata) -> tuple[pd.DataFrame, pd.DataFrame]:
+        """loading of cached data or requesting of data from the TOARDB
+        
+        Parameters:
+        ----------
+        metadata:
+            information on requested data
+        return:
+            tuple[timeseries, station coordinates]
+        """
         filename = self.sample_dir / self.get_sample_file_name(metadata)
         query_options = QueryOptions.from_metadata(metadata)
         needs_fresh_download = (not self.use_downloaded) or (not filename.is_file())