integrate WRF for datahandler

mlair/data_handler/data_handler_wrf_chem.py

@@ -12,10 +12,12 @@ import os
 from mlair.helpers.geofunctions import haversine_dist
 from mlair.helpers.helpers import convert2xrda, remove_items
 from mlair.helpers import TimeTrackingWrapper
-from typing import Tuple, Union, List, Dict
 
-from mlair.data_handler.abstract_data_handler import AbstractDataHandler
+
 from mlair.data_handler.data_handler_single_station import DataHandlerSingleStation
+from mlair.data_handler import DefaultDataHandler
+
+from typing import Tuple, Union, List, Dict
 import logging
 import cartopy.crs as ccrs
 
@@ -170,6 +172,8 @@ class SingleGridColumnWrfChemDataLoader(BaseWrfChemDataLoader):
         self.external_coords_file = external_coords_file
 
         self.open_data()
+
+        if self.physical_t_coord_name != self.time_dim_name:
             self.assign_coords(
                 {self.physical_t_coord_name: (self.time_dim_name, self._data[self.physical_t_coord_name].values)})
 
@@ -194,7 +198,7 @@ class SingleGridColumnWrfChemDataLoader(BaseWrfChemDataLoader):
             raise SyntaxError(f"`coords' must have length=2 (lat, lon), but has length={len(coords)}")
         if isinstance(coords, tuple):
             self.__coords = dict(lat=coords[0], lon=coords[1])
-            print(f"self.__coords={self.__coords}")
+            logging.debug(f"{self.__class__.__name__}.__coords is set to {self.__coords}")
         elif isinstance(coords, dict):
             if (coords.keys() == __set_coords.keys()):
                 self.__coords = coords
@@ -263,13 +267,19 @@ class DataHandlerSingleGridColumn2(DataHandlerSingleStation):
         lat, lon = self.str2coords(station)
         sgc_loader = SingleGridColumnWrfChemDataLoader((lat, lon),
                                                        data_path=path,
-                                                       rechunk_values={'Time': 1, 'bottom_top': 2},
                                                        external_coords_file=self.external_coords_file,
+                                                       time_dim_name=self.time_dim
                                                        )
 
+        # select defined variables at grid box or grid coloumn based on nearest icoords
         data = sgc_loader.data.isel(sgc_loader.get_nearest_icoords()).squeeze()[self.variables]
-        data = data.expand_dims({self.iter_dim: station}).to_array()
-        data = data.transpose(self.iter_dim, self.time_dim, 'variable', sgc_loader.logical_z_coord_name)
+        # expand dimesion for iterdim
+        data = data.expand_dims({self.iter_dim: station}).to_array(self.target_dim)
+        # transpose dataarray: set first three fixed and keep remaining as is
+        data = data.transpose(self.iter_dim, self.time_dim, self.target_dim, ...)
+        data = self._slice_prep(data, start=start, end=end)
+        # data = self.check_for_negative_concentrations(data)
+
         # ToDo
         # data should somehow look like this:
         # < xarray.DataArray(Stations: 1, datetime: 7670, variables: 9) (From DataHandlerSingleStation)
@@ -311,6 +321,14 @@ class DataHandlerSingleGridColumn2(DataHandlerSingleStation):
     #     raise NotImplementedError
 
 
+class DataHandlerWRF(DefaultDataHandler):
+    """Data handler using CDC."""
+    data_handler = DataHandlerSingleGridColumn2
+    data_handler_transformation = DataHandlerSingleGridColumn2
+    _requirements = data_handler.requirements()
+
+
+
 if __name__ == '__main__':
 
     def plot_map_proj(data, xlim=None, ylim=None, filename=None, point=None):