use different interp methods for cams

mlair/reference_models/reference_model_cams.py

@@ -11,7 +11,16 @@ import pandas as pd
 
 class CAMSforecast(AbstractReferenceModel):
 
-    def __init__(self, ref_name: str, ref_store_path: str = None, data_path: str = None):
+    def __init__(self, ref_name: str, ref_store_path: str = None, data_path: str = None, interp_method: str = None):
+        """
+        Use parameters `cams_data_path` to set `data_path` and `cams_interp_method` to set `interp_method` in MLAir
+        run script.
+
+        :param ref_name:
+        :param ref_store_path:
+        :param data_path:
+        :param interp_method:
+        """
 
         super().__init__()
         self.ref_name = ref_name
@@ -22,6 +31,7 @@ class CAMSforecast(AbstractReferenceModel):
             self.data_path = os.path.abspath(".")
         else:
             self.data_path = os.path.abspath(data_path)
+        self.interp_method = interp_method
         self.file_pattern = "forecasts_%s_test.nc"
         self.time_dim = "index"
         self.ahead_dim = "ahead"
@@ -36,7 +46,11 @@ class CAMSforecast(AbstractReferenceModel):
             darray = dataset.to_array().sortby(["longitude", "latitude"])
             for station, coords in missing_stations.items():
                 lon, lat = coords["lon"], coords["lat"]
-                station_data = darray.sel(longitude=lon, latitude=lat, method="nearest", drop=True).squeeze(drop=True)
+                if self.interp_method is None:
+                    station_data = darray.sel(longitude=lon, latitude=lat, method="nearest", drop=True).squeeze(drop=True)
+                else:
+                    station_data = darray.interp(**{"longitude": lon, "latitude": lat}, method=self.interp_method)
+                    station_data = station_data.drop_vars(["longitude", "latitude"]).squeeze(drop=True)
                 station_data = station_data.expand_dims(dim={self.type_dim: [self.ref_name]}).compute()
                 station_data.coords[self.time_dim] = station_data.coords[self.time_dim] - pd.Timedelta(days=1)
                 station_data.coords[self.ahead_dim] = station_data.coords[self.ahead_dim] + 1