return kwargs from adapter.to_file funtions

hydromt/data_adapter/dataframe.py

@@ -152,6 +152,8 @@ def to_file(
         driver : str
             Name of the driver used to read the data.
             See :py:func:`~hydromt.data_catalog.DataCatalog.get_geodataset`.
+        kwargs: dict
+            The additional keyword arguments that were passed in.
 
 
         """
@@ -162,20 +164,21 @@ def to_file(
             )
         except IndexError as err:  # out of bounds for time
             logger.warning(str(err))
-            return None, None
+            return None, None, None
 
         if driver is None or driver == "csv":
             # always write as CSV
             driver = "csv"
             fn_out = join(data_root, f"{data_name}.csv")
             obj.to_csv(fn_out, **kwargs)
+            kwargs["index_col"] = obj.index.name
         elif driver == "excel":
             fn_out = join(data_root, f"{data_name}.xlsx")
             obj.to_excel(fn_out, **kwargs)
         else:
             raise ValueError(f"DataFrame: Driver {driver} is unknown.")
 
-        return fn_out, driver
+        return fn_out, driver, kwargs
 
     def get_data(
         self,

hydromt/data_adapter/geodataframe.py

@@ -166,7 +166,7 @@ def to_file(
         kwargs.pop("time_tuple", None)
         gdf = self.get_data(bbox=bbox, variables=variables, logger=logger)
         if gdf.index.size == 0:
-            return None, None
+            return None, None, None
 
         if driver is None:
             _lst = ["csv", "xls", "xlsx", "xy", "vector_table"]
@@ -190,7 +190,7 @@ def to_file(
             gdf.to_file(fn_out, driver=driver, **kwargs)
             driver = "vector"
 
-        return fn_out, driver
+        return fn_out, driver, kwargs
 
     def get_data(
         self,

hydromt/data_adapter/geodataset.py

@@ -182,7 +182,7 @@ def to_file(
             single_var_as_array=variables is None,
         )
         if obj.vector.index.size == 0 or ("time" in obj.coords and obj.time.size == 0):
-            return None, None
+            return None, None, None
 
         # much better for mem/storage/processing if dtypes are set correctly
         for name, coord in obj.coords.items():
@@ -218,7 +218,7 @@ def to_file(
         else:
             raise ValueError(f"GeoDataset: Driver {driver} unknown.")
 
-        return fn_out, driver
+        return fn_out, driver, kwargs
 
     def get_data(
         self,

hydromt/data_adapter/rasterdataset.py

@@ -179,6 +179,8 @@ def to_file(
         driver: str
             Name of driver to read data with, see
             :py:func:`~hydromt.data_catalog.DataCatalog.get_rasterdataset`
+        kwargs: dict
+            the additional kwyeord arguments that were passed to `to_netcdf`
         """
         try:
             obj = self.get_data(
@@ -190,7 +192,7 @@ def to_file(
             )
         except IndexError as err:  # out of bounds
             logger.warning(str(err))
-            return None, None
+            return None, None, None
 
         if driver is None:
             # by default write 2D raster data to GeoTiff and 3D raster data to netcdf
@@ -228,7 +230,7 @@ def to_file(
                 )
             driver = "raster"
 
-        return fn_out, driver
+        return fn_out, driver, kwargs
 
     def get_data(
         self,

hydromt/data_catalog.py

@@ -867,7 +867,7 @@ def export_data(
                             unit_add = source.unit_add
                             source.unit_mult = {}
                             source.unit_add = {}
-                        fn_out, driver = source.to_file(
+                        fn_out, driver, source_kwargs = source.to_file(
                             data_root=data_root,
                             data_name=key,
                             variables=source_vars.get(key, None),

hydromt/stats/extremes.py

@@ -898,7 +898,7 @@ def get_lmom(x, nmom=4):
         vector of (nmom) L-moments
     """
     n = len(x)
-    xs = np.msort(x)
+    xs = np.sort(x, axis=0)
     bb = np.zeros(nmom - 1)
     ll = np.zeros(nmom - 1)
     b0 = xs.mean(axis=0)