Update TippingPointMetrics enum with additional options

.gitignore

@@ -45,6 +45,7 @@ htmlcov/
 .cache
 nosetests.xml
 coverage.xml
+report.xml
 *.cover
 *.py,cover
 .hypothesis/

docs/api.py

@@ -20,7 +20,7 @@ def parse_content(
     parent: object = None,
     module: object = None,
 ):
-    """_summary_
+    """_summary_.
 
     Parameters
     ----------
@@ -79,7 +79,7 @@ def parse_section(
     builder: Builder,
     rel_dir: Path | str,
 ):
-    """_summary_
+    """_summary_.
 
     Parameters
     ----------
@@ -118,7 +118,7 @@ def parse_tree_section(
     content: list,
     sub: bool = False,
 ):
-    """_summary_
+    """_summary_.
 
     Parameters
     ----------
@@ -151,7 +151,7 @@ def create_tree(
     file: Path | str,
     filter: str = "*",
 ):
-    """_summary_
+    """_summary_.
 
     Parameters
     ----------

environment.yml

@@ -5,34 +5,10 @@ channels:
   - numba
 
 dependencies:
+  # Use conda to install pre-built binaries for geopandas and its C++ dependencies (GDAL, PROJ and fiona)
+  # Then `pip install .` to install the rest of the dependencies from the pyproj.toml that are on PyPI
+  - python=3.10
+  - geopandas
   - pip
   - pip:
-    - NDBC
-    - noaa-coops
-    - cht-tide
-    - cht-meteo
-    - cht-observations
-    - git+https://github.com/Deltares/hydromt_fiat.git
-    - git+https://github.com/Deltares/fiat_toolbox.git
-    - git+https://github.com/Deltares/hydromt_sfincs.git@FA_quadtree
-    - git+https://github.com/Deltares/cht_cyclones.git
-  - black
-  - typos
-  - ruff
-  - build
-  - geopandas
-  - mypy
-  - numpy
-  - pandas
-  - plotly
-  - pydantic
-  - pytest
-  - python=3.10
-  - tomli
-  - tomli-w
-  - twine
-  - census
-  - pre-commit
-  - numpy-financial
-  - pyogrio
-  - geojson
+    - .[dev]

flood_adapt/api/benefits.py

@@ -3,47 +3,47 @@
 import geopandas as gpd
 import pandas as pd
 
+from flood_adapt.dbs_controller import Database
 from flood_adapt.object_model.benefit import Benefit
 from flood_adapt.object_model.interface.benefits import IBenefit
-from flood_adapt.object_model.interface.database import IDatabase
 
 
-def get_benefits(database: IDatabase) -> dict[str, Any]:
+def get_benefits() -> dict[str, Any]:
     # sorting and filtering either with PyQt table or in the API
-    return database.benefits.list_objects()
+    return Database().benefits.list_objects()
 
 
-def get_benefit(name: str, database: IDatabase) -> IBenefit:
-    return database.benefits.get(name)
+def get_benefit(name: str) -> IBenefit:
+    return Database().benefits.get(name)
 
 
-def create_benefit(attrs: dict[str, Any], database: IDatabase) -> IBenefit:
-    return Benefit.load_dict(attrs, database.input_path)
+def create_benefit(attrs: dict[str, Any]) -> IBenefit:
+    return Benefit.load_dict(attrs, Database().input_path)
 
 
-def save_benefit(benefit: IBenefit, database: IDatabase) -> None:
-    database.benefits.save(benefit)
+def save_benefit(benefit: IBenefit) -> None:
+    Database().benefits.save(benefit)
 
 
-def edit_benefit(benefit: IBenefit, database: IDatabase) -> None:
-    database.benefits.edit(benefit)
+def edit_benefit(benefit: IBenefit) -> None:
+    Database().benefits.edit(benefit)
 
 
-def delete_benefit(name: str, database: IDatabase) -> None:
-    database.benefits.delete(name)
+def delete_benefit(name: str) -> None:
+    Database().benefits.delete(name)
 
 
-def check_benefit_scenarios(benefit: IBenefit, database: IDatabase) -> pd.DataFrame:
-    return database.check_benefit_scenarios(benefit)
+def check_benefit_scenarios(benefit: IBenefit) -> pd.DataFrame:
+    return Database().check_benefit_scenarios(benefit)
 
 
-def create_benefit_scenarios(benefit: IBenefit, database: IDatabase):
-    database.create_benefit_scenarios(benefit)
+def create_benefit_scenarios(benefit: IBenefit):
+    Database().create_benefit_scenarios(benefit)
 
 
-def run_benefit(name: Union[str, list[str]], database: IDatabase) -> None:
-    database.run_benefit(name)
+def run_benefit(name: Union[str, list[str]]) -> None:
+    Database().run_benefit(name)
 
 
-def get_aggregation_benefits(name: str, database: IDatabase) -> dict[gpd.GeoDataFrame]:
-    return database.get_aggregation_benefits(name)
+def get_aggregation_benefits(name: str) -> dict[gpd.GeoDataFrame]:
+    return Database().get_aggregation_benefits(name)

flood_adapt/api/events.py

@@ -5,7 +5,7 @@
 import pandas as pd
 from cht_cyclones.tropical_cyclone import TropicalCyclone
 
-from flood_adapt.dbs_controller import IDatabase
+from flood_adapt.dbs_controller import Database
 from flood_adapt.object_model.hazard.event.event import Event
 from flood_adapt.object_model.hazard.event.event_factory import EventFactory
 from flood_adapt.object_model.hazard.event.historical_nearshore import (
@@ -21,22 +21,22 @@
 from flood_adapt.object_model.io.unitfulvalue import UnitTypesLength
 
 
-def get_events(database: IDatabase) -> dict[str, Any]:
+def get_events() -> dict[str, Any]:
     # use PyQt table / sorting and filtering either with PyQt table or in the API
-    return database.events.list_objects()
+    return Database().events.list_objects()
 
 
-def get_event(name: str, database: IDatabase) -> IEvent:
-    return database.events.get(name)
+def get_event(name: str) -> IEvent:
+    return Database().events.get(name)
 
 
-def get_event_mode(name: str, database: IDatabase) -> str:
-    filename = database.input_path / "events" / f"{name}" / f"{name}.toml"
+def get_event_mode(name: str) -> str:
+    filename = Database().input_path / "events" / f"{name}" / f"{name}.toml"
     return Event.get_mode(filename)
 
 
 def create_synthetic_event(attrs: dict[str, Any]) -> ISynthetic:
-    """Create a synthetic event object from a dictionary of attributes
+    """Create a synthetic event object from a dictionary of attributes.
 
     Parameters
     ----------
@@ -52,7 +52,7 @@ def create_synthetic_event(attrs: dict[str, Any]) -> ISynthetic:
 
 
 def create_historical_nearshore_event(attrs: dict[str, Any]) -> IHistoricalNearshore:
-    """Create a historical nearshore event object from a dictionary of attributes
+    """Create a historical nearshore event object from a dictionary of attributes.
 
     Parameters
     ----------
@@ -68,7 +68,7 @@ def create_historical_nearshore_event(attrs: dict[str, Any]) -> IHistoricalNears
 
 
 def create_historical_offshore_event(attrs: dict[str, Any]) -> IHistoricalOffshore:
-    """Create a historical offshore event object from a dictionary of attributes
+    """Create a historical offshore event object from a dictionary of attributes.
 
     Parameters
     ----------
@@ -84,7 +84,7 @@ def create_historical_offshore_event(attrs: dict[str, Any]) -> IHistoricalOffsho
 
 
 def create_historical_hurricane_event(attrs: dict[str, Any]) -> IHistoricalHurricane:
-    """Create a historical hurricane event object from a dictionary of attributes
+    """Create a historical hurricane event object from a dictionary of attributes.
 
     Parameters
     ----------
@@ -99,28 +99,24 @@ def create_historical_hurricane_event(attrs: dict[str, Any]) -> IHistoricalHurri
     return EventFactory.get_event("Historical_hurricane").load_dict(attrs)
 
 
-def save_event_toml(event: IEvent, database: IDatabase) -> None:
-    database.events.save(event)
+def save_event_toml(event: IEvent) -> None:
+    Database().events.save(event)
 
 
-def save_timeseries_csv(
-    name: str, event: IEvent, df: pd.DataFrame, database: IDatabase
-) -> None:
-    database.write_to_csv(name, event, df)
+def save_timeseries_csv(name: str, event: IEvent, df: pd.DataFrame) -> None:
+    Database().write_to_csv(name, event, df)
 
 
-def edit_event(event: IEvent, database: IDatabase) -> None:
-    database.events.edit(event)
+def edit_event(event: IEvent) -> None:
+    Database().events.edit(event)
 
 
-def delete_event(name: str, database: IDatabase) -> None:
-    database.events.delete(name)
+def delete_event(name: str) -> None:
+    Database().events.delete(name)
 
 
-def copy_event(
-    old_name: str, database: IDatabase, new_name: str, new_description: str
-) -> None:
-    database.events.copy(old_name, new_name, new_description)
+def copy_event(old_name: str, new_name: str, new_description: str) -> None:
+    Database().events.copy(old_name, new_name, new_description)
 
 
 def download_wl_data(
@@ -135,31 +131,24 @@ def read_csv(csvpath: Union[str, os.PathLike]) -> pd.DataFrame:
     return Event.read_csv(csvpath)
 
 
-def plot_wl(
-    event: IEvent, database: IDatabase, input_wl_df: pd.DataFrame = None
-) -> str:
-    return database.plot_wl(event, input_wl_df)
+def plot_wl(event: IEvent, input_wl_df: pd.DataFrame = None) -> str:
+    return Database().plot_wl(event, input_wl_df)
 
 
 def plot_river(
     event: IEvent,
-    database: IDatabase,
     input_river_df: list[pd.DataFrame],
 ) -> str:
-    return database.plot_river(event, input_river_df)
+    return Database().plot_river(event, input_river_df)
 
 
-def plot_rainfall(
-    event: IEvent, database: IDatabase, input_rainfall_df: pd.DataFrame = None
-) -> str:
-    return database.plot_rainfall(event, input_rainfall_df)
+def plot_rainfall(event: IEvent, input_rainfall_df: pd.DataFrame = None) -> str:
+    return Database().plot_rainfall(event, input_rainfall_df)
 
 
-def plot_wind(
-    event: IEvent, database: IDatabase, input_wind_df: pd.DataFrame = None
-) -> str:
-    return database.plot_wind(event, input_wind_df)
+def plot_wind(event: IEvent, input_wind_df: pd.DataFrame = None) -> str:
+    return Database().plot_wind(event, input_wind_df)
 
 
-def save_cyclone_track(event: IEvent, track: TropicalCyclone, database: IDatabase):
-    database.write_cyc(event, track)
+def save_cyclone_track(event: IEvent, track: TropicalCyclone):
+    Database().write_cyc(event, track)

flood_adapt/api/measures.py

@@ -3,6 +3,7 @@
 import geopandas as gpd
 import pandas as pd
 
+from flood_adapt.dbs_controller import Database
 from flood_adapt.object_model.direct_impact.measure.buyout import Buyout
 from flood_adapt.object_model.direct_impact.measure.elevate import Elevate
 from flood_adapt.object_model.direct_impact.measure.floodproof import FloodProof
@@ -11,24 +12,21 @@
     GreenInfrastructure,
 )
 from flood_adapt.object_model.hazard.measure.pump import Pump
-from flood_adapt.object_model.interface.database import IDatabase
 from flood_adapt.object_model.interface.measures import (
     IMeasure,
 )
 from flood_adapt.object_model.interface.site import ISite
 
 
-def get_measures(database: IDatabase) -> dict[str, Any]:
-    return database.measures.list_objects()
+def get_measures() -> dict[str, Any]:
+    return Database().measures.list_objects()
 
 
-def get_measure(name: str, database: IDatabase) -> IMeasure:
-    return database.measures.get(name)
+def get_measure(name: str) -> IMeasure:
+    return Database().measures.get(name)
 
 
-def create_measure(
-    attrs: dict[str, Any], type: str, database: IDatabase = None
-) -> IMeasure:
+def create_measure(attrs: dict[str, Any], type: str = None) -> IMeasure:
     """Create a measure from a dictionary of attributes and a type string.
 
     Parameters
@@ -45,9 +43,8 @@ def create_measure(
     IMeasure
         Measure object.
     """
-
     # If a database is provided, use it to set the input path for the measure. Otherwise, set it to None.
-    database_path = database.input_path if database else None
+    database_path = Database().input_path
 
     if type == "elevate_properties":
         return Elevate.load_dict(attrs, database_path)
@@ -63,22 +60,20 @@ def create_measure(
         return GreenInfrastructure.load_dict(attrs, database_path)
 
 
-def save_measure(measure: IMeasure, database: IDatabase) -> None:
-    database.measures.save(measure)
+def save_measure(measure: IMeasure) -> None:
+    Database().measures.save(measure)
 
 
-def edit_measure(measure: IMeasure, database: IDatabase) -> None:
-    database.measures.edit(measure)
+def edit_measure(measure: IMeasure) -> None:
+    Database().measures.edit(measure)
 
 
-def delete_measure(name: str, database: IDatabase) -> None:
-    database.measures.delete(name)
+def delete_measure(name: str) -> None:
+    Database().measures.delete(name)
 
 
-def copy_measure(
-    old_name: str, database: IDatabase, new_name: str, new_description: str
-) -> None:
-    database.measures.copy(old_name, new_name, new_description)
+def copy_measure(old_name: str, new_name: str, new_description: str) -> None:
+    Database().measures.copy(old_name, new_name, new_description)
 
 
 # Green infrastructure
@@ -94,5 +89,5 @@ def calculate_volume(
     )
 
 
-def get_green_infra_table(database: IDatabase, measure_type: str) -> pd.DataFrame:
-    return database.get_green_infra_table(measure_type)
+def get_green_infra_table(measure_type: str) -> pd.DataFrame:
+    return Database().static.get_green_infra_table(measure_type)