Merge branch 'main' of https://github.com/Deltares-research/FloodAdapt …

…into fiat_adapter

.github/workflows/publish-to-pypi.yml

@@ -18,15 +18,16 @@ name: release
 #  1. In github settings:
 #     - Create an environment called `release`
 #     - Setup the permissions (https://github.com/<ORGANIZATION>/<REPO_NAME>/settings/environments)
-#     - Add the following variables:
-#        - PACKAGE_NAME: the name of your package on pypi
-#        - PYTHON_VERSION: the version of Python you want to use
 
 #  2. On PyPi:
 #      - Create the project and add a trusted publisher (https://pypi.org/manage/project/<PACKAGE_NAME>/settings/publishing/ or https://pypi.org/manage/account/publishing if the project is not on pypi yet)
 #      - Ensure the publisher is configured to use:
 #          - the filename of this workflow yml (in this case: publish-to-pypi.yml)
 
+# 3. In this file:
+#     - Add the following variables to the `env` section:
+#        - PACKAGE_NAME: the name of your package on pypi
+#        - PYTHON_VERSION: the version of Python you want to use
 #     - In the `setup_and_build` job:
 #        - Update the the shell commands to install your package
 
@@ -36,6 +37,11 @@ on:
       - v[0-9]+\.[0-9]+\.[0-9]+
       # https://peps.python.org/pep-0440/
 
+
+env:
+  PACKAGE_NAME: "flood-adapt"
+  PYTHON_VERSION: "3.10"
+
 jobs:
   details:
     runs-on: ubuntu-latest
@@ -95,10 +101,13 @@ jobs:
       - uses: conda-incubator/setup-miniconda@v3
         with:
           auto-update-conda: true
-          activate-environment: publish
-          python-version: ${{ env.PYTHON_VERSION }}
           channels: conda-forge
 
+      - name: Create environment
+        shell: bash -el {0}
+        run: |
+          conda create -n publish python=${{ env.PYTHON_VERSION }}
+
       - name: Install Build tools
         shell: bash -el {0}
         run: |
@@ -107,6 +116,7 @@ jobs:
       - name: Install dependencies
         shell: bash -el {0}
         run: |
+          conda install -n publish gdal basemap cftime fiona netCDF4 pygeos pyproj rasterio rtree shapely --channel conda-forge
           conda run -n publish pip install .
 
       - name: Build source and wheel distribution

.vscode/settings.json

@@ -1,8 +1,8 @@
 {
     // Python settings
-    "python.analysis.typeEvaluation.strictDictionaryInference": true,
-    "python.analysis.typeEvaluation.strictListInference": true,
-    "python.analysis.typeEvaluation.strictSetInference": true,
+    "python.analysis.typeEvaluation.strictDictionaryInference": false,
+    "python.analysis.typeEvaluation.strictListInference": false,
+    "python.analysis.typeEvaluation.strictSetInference": false,
     "python.missingPackage.severity": "Error",
 
     "debug.console.closeOnEnd": true,

docs/_quarto.yml

@@ -54,7 +54,6 @@ quartodoc:
         - name: object_model.benefit.Benefit
         - name: adapter.impacts_integrator.Impacts
         - name: object_model.scenario.Scenario
-        - name: object_model.interface.site.Site
         - name: object_model.strategy.Strategy
         - name: misc.log.FloodAdaptLogging
         - name: misc.config.Settings

flood_adapt/adapter/fiat_adapter.py

@@ -422,9 +422,9 @@ def apply_economic_growth(
         ]
 
         # Get objects that are buildings (using site info)
-        buildings_rows = ~self._model.exposure.exposure_db["Primary Object Type"].isin(
-            self._site.attrs.fiat.non_building_names
-        )
+        buildings_rows = ~self.fiat_model.exposure.exposure_db[
+            "Primary Object Type"
+        ].isin(self.site.attrs.fiat.config.non_building_names)
 
         # If ids are given use that as an additional filter
         if ids:
@@ -466,9 +466,9 @@ def apply_population_growth_existing(
         ]
 
         # Get objects that are buildings (using site info)
-        buildings_rows = ~self._model.exposure.exposure_db["Primary Object Type"].isin(
-            self._site.attrs.fiat.non_building_names
-        )
+        buildings_rows = ~self.fiat_model.exposure.exposure_db[
+            "Primary Object Type"
+        ].isin(self.site.attrs.fiat.config.non_building_names)
 
         # If ids are given use that as an additional filter
         if ids:
@@ -614,9 +614,9 @@ def buyout_properties(self, buyout: Buyout, ids: Optional[list[str]] = []):
         ]
 
         # Get objects that are buildings (using site info)
-        buildings_rows = ~self._model.exposure.exposure_db["Primary Object Type"].isin(
-            self._site.attrs.fiat.non_building_names
-        )
+        buildings_rows = ~self.fiat_model.exposure.exposure_db[
+            "Primary Object Type"
+        ].isin(self.site.attrs.fiat.config.non_building_names)
 
         # Get rows that are affected
         objectids = get_object_ids(buyout, self._model)
@@ -671,7 +671,7 @@ def get_buildings(self) -> gpd.GeoDataFrame:
             )
         return self._model.exposure.select_objects(
             primary_object_type="ALL",
-            non_building_names=self._site.attrs.fiat.non_building_names,
+            non_building_names=self.site.attrs.fiat.config.non_building_names,
             return_gdf=True,
         )
 
@@ -686,7 +686,7 @@ def get_property_types(self) -> list:
             raise ValueError("No property types found in the FIAT model.")
         types.append("all")  # Add "all" type for using as identifier
 
-        names = self._site.attrs.fiat.non_building_names
+        names = self.site.attrs.fiat.config.non_building_names
         if names:
             for name in names:
                 if name in types:
@@ -725,7 +725,7 @@ def get_object_ids(
         ids = self._model.exposure.get_object_ids(
             selection_type=measure.attrs.selection_type,
             property_type=measure.attrs.property_type,
-            non_building_names=self._site.attrs.fiat.non_building_names,
+            non_building_names=self.site.attrs.fiat.config.non_building_names,
             aggregation=measure.attrs.aggregation_area_type,
             aggregation_area_name=measure.attrs.aggregation_area_name,
             polygon_file=str(polygon_file),

flood_adapt/adapter/impacts_integrator.py

@@ -169,19 +169,19 @@ def preprocess_fiat(self):
                     dem = (
                         self.database.static_path
                         / "dem"
-                        / self.site_info.attrs.dem.filename
+                        / self.site_info.attrs.sfincs.dem.filename
                     )
                     aggregation_areas = [
                         self.database.static_path / aggr.file
-                        for aggr in self.site_info.attrs.fiat.aggregation
+                        for aggr in self.site_info.attrs.fiat.config.aggregation
                     ]
                     attribute_names = [
                         aggr.field_name
-                        for aggr in self.site_info.attrs.fiat.aggregation
+                        for aggr in self.site_info.attrs.fiat.config.aggregation
                     ]
                     label_names = [
                         f"Aggregation Label: {aggr.name}"
-                        for aggr in self.site_info.attrs.fiat.aggregation
+                        for aggr in self.site_info.attrs.fiat.config.aggregation
                     ]
 
                     fa.apply_population_growth_new(

flood_adapt/adapter/sfincs_adapter.py

@@ -69,6 +69,7 @@
     GreenInfrastructure,
 )
 from flood_adapt.object_model.hazard.measure.pump import Pump
+from flood_adapt.object_model.interface.config.site import Site
 from flood_adapt.object_model.interface.measures import IMeasure
 from flood_adapt.object_model.interface.path_builder import (
     ObjectDir,
@@ -80,7 +81,6 @@
     PhysicalProjectionModel,
 )
 from flood_adapt.object_model.interface.scenarios import IScenario
-from flood_adapt.object_model.interface.site import Site
 from flood_adapt.object_model.io import unit_system as us
 from flood_adapt.object_model.utils import cd, resolve_filepath
 
@@ -500,7 +500,9 @@ def write_floodmap_geotiff(
     ):
         results_path = self._get_result_path(scenario)
         sim_path = sim_path or self._get_simulation_paths(scenario)[0]
-        demfile = self.database.static_path / "dem" / self.site.attrs.dem.filename
+        demfile = (
+            self.database.static_path / "dem" / self.site.attrs.sfincs.dem.filename
+        )
 
         # read SFINCS model
         with SfincsAdapter(model_root=sim_path) as model:
@@ -568,7 +570,7 @@ def plot_wl_obs(
         with SfincsAdapter(model_root=sim_path) as model:
             df, gdf = model._get_zs_points()
 
-        gui_units = us.UnitTypesLength(self.site.attrs.gui.default_length_units)
+        gui_units = us.UnitTypesLength(self.site.attrs.gui.units.default_length_units)
         conversion_factor = us.UnitfulLength(
             value=1.0, units=us.UnitTypesLength("meters")
         ).convert(gui_units)
@@ -577,21 +579,21 @@ def plot_wl_obs(
             # Plot actual thing
             fig = px.line(
                 df[col] * conversion_factor
-                + self.site.attrs.water_level.localdatum.height.convert(
+                + self.site.attrs.sfincs.water_level.localdatum.height.convert(
                     gui_units
                 )  # convert to reference datum for plotting
             )
 
             # plot reference water levels
             fig.add_hline(
-                y=self.site.attrs.water_level.msl.height.convert(gui_units),
+                y=self.site.attrs.sfincs.water_level.msl.height.convert(gui_units),
                 line_dash="dash",
                 line_color="#000000",
-                annotation_text=self.site.attrs.water_level.msl.name,
+                annotation_text=self.site.attrs.sfincs.water_level.msl.name,
                 annotation_position="bottom right",
             )
-            if self.site.attrs.water_level.other:
-                for wl_ref in self.site.attrs.water_level.other:
+            if self.site.attrs.sfincs.water_level.other:
+                for wl_ref in self.site.attrs.sfincs.water_level.other:
                     fig.add_hline(
                         y=wl_ref.height.convert(gui_units),
                         line_dash="dash",
@@ -621,10 +623,10 @@ def plot_wl_obs(
 
             # check if event is historic
             if isinstance(event, HistoricalEvent):
-                if self.site.attrs.tide_gauge is None:
+                if self.site.attrs.sfincs.tide_gauge is None:
                     continue
                 df_gauge = TideGauge(
-                    attrs=self.site.attrs.tide_gauge
+                    attrs=self.site.attrs.sfincs.tide_gauge
                 ).get_waterlevels_in_time_frame(
                     time=TimeModel(
                         start_time=event.attrs.time.start_time,
@@ -636,7 +638,7 @@ def plot_wl_obs(
                 if df_gauge is not None:
                     waterlevel = df_gauge.iloc[
                         :, 0
-                    ] + self.site.attrs.water_level.msl.height.convert(gui_units)
+                    ] + self.site.attrs.sfincs.water_level.msl.height.convert(gui_units)
 
                     # If data is available, add to plot
                     fig.add_trace(
@@ -657,10 +659,10 @@ def plot_wl_obs(
 
     def add_obs_points(self):
         """Add observation points provided in the site toml to SFINCS model."""
-        if self.site.attrs.obs_point is not None:
+        if self.site.attrs.sfincs.obs_point is not None:
             self.logger.info("Adding observation points to the overland flood model...")
 
-            obs_points = self.site.attrs.obs_point
+            obs_points = self.site.attrs.sfincs.obs_point
             names = []
             lat = []
             lon = []
@@ -716,7 +718,7 @@ def calculate_rp_floodmaps(self, scenario: IScenario):
 
         phys_proj = scenario.projection.get_physical_projection()
 
-        floodmap_rp = self.site.attrs.risk.return_periods
+        floodmap_rp = self.site.attrs.fiat.risk.return_periods
         frequencies = scenario.event.attrs.frequency
 
         # adjust storm frequency for hurricane events
@@ -816,7 +818,9 @@ def calculate_rp_floodmaps(self, scenario: IScenario):
 
             # write geotiff
             # dem file for high resolution flood depth map
-            demfile = self.database.static_path / "dem" / self.site.attrs.dem.filename
+            demfile = (
+                self.database.static_path / "dem" / self.site.attrs.sfincs.dem.filename
+            )
 
             # writing the geotiff to the scenario results folder
             with SfincsAdapter(model_root=sim_paths[0]) as dummymodel:
@@ -1021,13 +1025,13 @@ def _add_forcing_waterlevels(self, forcing: IWaterlevel):
             df_ts *= conversion
             self._set_waterlevel_forcing(df_ts)
         elif isinstance(forcing, WaterlevelGauged):
-            if self.site.attrs.tide_gauge is None:
+            if self.site.attrs.sfincs.tide_gauge is None:
                 raise ValueError("No tide gauge defined for this site.")
-            df_ts = TideGauge(self.site.attrs.tide_gauge).get_waterlevels_in_time_frame(
-                time=time_frame
-            )
+            df_ts = TideGauge(
+                self.site.attrs.sfincs.tide_gauge
+            ).get_waterlevels_in_time_frame(time=time_frame)
             conversion = us.UnitfulLength(
-                value=1.0, units=self.site.attrs.tide_gauge.units
+                value=1.0, units=self.site.attrs.sfincs.tide_gauge.units
             ).convert(us.UnitTypesLength.meters)
             df_ts *= conversion
             self._set_waterlevel_forcing(df_ts)
@@ -1097,7 +1101,7 @@ def _add_measure_floodwall(self, floodwall: FloodWall):
                 float(
                     us.UnitfulLength(
                         value=float(height),
-                        units=self.site.attrs.gui.default_length_units,
+                        units=self.site.attrs.gui.units.default_length_units,
                     ).convert(us.UnitTypesLength("meters"))
                 )
                 for height in gdf_floodwall["z"]
@@ -1363,7 +1367,7 @@ def _get_simulation_paths(self, scenario: IScenario) -> List[Path]:
         base_path = (
             self._get_result_path(scenario)
             / "simulations"
-            / self.site.attrs.sfincs.overland_model
+            / self.site.attrs.sfincs.config.overland_model
         )
 
         if isinstance(scenario.event, EventSet):
@@ -1383,7 +1387,7 @@ def _get_simulation_path_offshore(self, scenario: IScenario) -> List[Path]:
         base_path = (
             self._get_result_path(scenario)
             / "simulations"
-            / self.site.attrs.sfincs.offshore_model
+            / self.site.attrs.sfincs.config.offshore_model
         )
         if isinstance(scenario.event, EventSet):
             return [
@@ -1430,8 +1434,8 @@ def _get_zs_points(self):
         names = []
         descriptions = []
         # get station names from site.toml
-        if self.site.attrs.obs_point is not None:
-            obs_points = self.site.attrs.obs_point
+        if self.site.attrs.sfincs.obs_point is not None:
+            obs_points = self.site.attrs.sfincs.obs_point
             for pt in obs_points:
                 names.append(pt.name)
                 descriptions.append(pt.description)
@@ -1447,11 +1451,12 @@ def _get_zs_points(self):
     # @gundula do we keep this func, its not used anywhere?
     def _downscale_hmax(self, zsmax, demfile: Path):
         # read DEM and convert units to metric units used by SFINCS
-        demfile_units = self.site.attrs.dem.units
+        demfile_units = self.site.attrs.sfincs.dem.units
         dem_conversion = us.UnitfulLength(value=1.0, units=demfile_units).convert(
             us.UnitTypesLength("meters")
         )
         dem = dem_conversion * self._model.data_catalog.get_rasterdataset(demfile)
+        dem = dem.rio.reproject(self.sf_model.crs)
 
         # determine conversion factor for output floodmap
         floodmap_units = self.site.attrs.sfincs.floodmap_units

flood_adapt/api/events.py

@@ -28,6 +28,7 @@
     CSVTimeseries,
     SyntheticTimeseriesModel,
 )
+from flood_adapt.object_model.hazard.forcing.waterlevels import SurgeModel, TideModel
 from flood_adapt.object_model.hazard.interface.events import (
     IEvent,
     IEventModel,
@@ -45,6 +46,7 @@
     ShapeType,
 )
 from flood_adapt.object_model.hazard.interface.models import TimeModel
+from flood_adapt.object_model.interface.config.sfincs import RiverModel
 from flood_adapt.object_model.io import unit_system as us
 
 # Ensure all objects are imported and available for use if this module is imported
@@ -78,6 +80,9 @@
     "CSVTimeseries",
     "SyntheticTimeseriesModel",
     "DischargeConstant",
+    "RiverModel",
+    "SurgeModel",
+    "TideModel",
 ]
 
 
@@ -148,10 +153,6 @@ def create_event(attrs: dict[str, Any] | IEventModel) -> IEvent | EventSet:
     return EventFactory.load_dict(attrs)
 
 
-def list_forcing_types() -> list[str]:
-    return ForcingFactory.list_forcing_types()
-
-
 def list_forcings() -> list[Type[IForcing]]:
     return ForcingFactory.list_forcings()