Small Model updates

docs/changelog.rst

@@ -28,6 +28,7 @@ Added
 - Added documentation for how to start your own plugin (PR #446)
 - New raster method ``to_slippy_tiles``: tiling of a raster dataset according to the slippy tile structure for e.g., webviewers (PR #440).
 - Support for http and other *filesystems* in path of data source (PR #515).
+- ``set_forcing`` can now add pandas.DataFrame object to frocing. (PR #534)
 
 Changed
 -------
@@ -43,6 +44,7 @@ Fixed
 -----
 - when a model component (eg maps, forcing, grid) is updated using the set_ methods, it will first be read to avoid loosing data. (PR #460)
 - open_geodataset with driver vector also works for other geometry type than points. (PR #509)
+- overwrite model in update mode. (PR #534)
 
 Deprecated
 ----------

hydromt/models/model_api.py

@@ -299,7 +299,10 @@ def update(
                     '"model_out" directory required when updating in "read-only" mode'
                 )
             self.read()
-            self.set_root(model_out, mode="w")
+            if forceful_overwrite:
+                self.set_root(model_out, mode="w+")
+            else:
+                self.set_root(model_out, mode="w")
 
         # check if model has a region
         if self.region is None:
@@ -1335,21 +1338,28 @@ def forcing(self) -> Dict[str, Union[xr.Dataset, xr.DataArray]]:
 
     def set_forcing(
         self,
-        data: Union[xr.DataArray, xr.Dataset],
+        data: Union[xr.DataArray, xr.Dataset, pd.DataFrame],
         name: Optional[str] = None,
         split_dataset: Optional[bool] = True,
     ):
         """Add data to forcing attribute.
 
+        Data can be xarray.DataArray, xarray.Dataset or pandas.DataFrame.
+        If pandas.DataFrame, indices should be the DataFrame index and the columns
+        the variable names. the DataFrame will then be converted to xr.Dataset using
+        :py:meth:`pandas.DataFrame.to_xarray` method.
+
         Arguments
         ---------
-        data: xarray.Dataset or xarray.DataArray
+        data: xarray.Dataset or xarray.DataArray or pd.DataFrame
             New forcing data to add
         name: str, optional
             Results name, required if data is xarray.Dataset is and split_dataset=False.
         split_dataset: bool, optional
             If True (default), split a Dataset to store each variable as a DataArray.
         """
+        if isinstance(data, pd.DataFrame):
+            data = data.to_xarray()
         data_dict = _check_data(data, name, split_dataset)
         for name in data_dict:
             if name in self.forcing:  # trigger init / read

tests/test_model.py

@@ -226,6 +226,9 @@ def test_model_append(demda, df, tmpdir):
     assert "dem" in mod1.maps
     mod1.set_forcing(demda, name="dem1")
     assert "dem" in mod1.forcing
+    mod1.set_forcing(df, name="df1", split_dataset=False)
+    assert "df1" in mod1.forcing
+    assert isinstance(mod1.forcing["df1"], xr.Dataset)
     mod1.set_states(demda, name="dem1")
     assert "dem" in mod1.states
     mod1.set_geoms(demda.raster.box, name="dem1")