Currency conversion jrc (#434)

* add conversion jrc to us dollar (in progress)

* add parameter to convert jrc eur to us dollar

* replace None with False

hydromt_fiat/api/data_types.py

@@ -16,6 +16,7 @@ class Units(str, Enum):
 class Conversion(float, Enum):
     meters_to_feet = 3.28084
     feet_to_meters = 0.3048
+    eur_to_us_dollars = 1.327 #Average exchange rate in 2010
 
 
 class Currency(str, Enum):

hydromt_fiat/fiat.py

@@ -345,7 +345,8 @@ def setup_exposure_buildings(
         bf_conversion: bool = False,
         keep_unclassified: bool = True,
         dst_crs: Union[str, None] = None,
-        damage_translation_fn: Union[Path, str] = None
+        damage_translation_fn: Union[Path, str] = None,
+        eur_to_us_dollar: bool = False
     ) -> None:
         """Setup building exposure (vector) data for Delft-FIAT.
 
@@ -398,6 +399,8 @@ def setup_exposure_buildings(
             it is taken from the region attribute of `FiatModel`. By default None
         damage_translation_fn: Union[Path, str], optional
             The path to the translation function that can be used to relate user damage curves with user damages.
+        eur_to_us_dollar: bool
+            Convert JRC Damage Values (Euro 2010) into US-Dollars (2025)
         """
         # In case the unit is passed as a pydantic value get the string
         if hasattr(unit, "value"):
@@ -419,6 +422,7 @@ def setup_exposure_buildings(
                 ground_floor_height,
                 extraction_method,
                 ground_elevation=ground_elevation,
+                eur_to_us_dollar = eur_to_us_dollar
             )
 
         else:
@@ -440,7 +444,8 @@ def setup_exposure_buildings(
                 bf_conversion=bf_conversion,
                 keep_unclassified=keep_unclassified,
                 damage_translation_fn = damage_translation_fn,
-                gfh_attribute_name = gfh_attribute_name
+                gfh_attribute_name = gfh_attribute_name,
+                eur_to_us_dollar = eur_to_us_dollar
             )
 
         if (asset_locations != occupancy_type) and occupancy_object_type is not None:
@@ -586,6 +591,7 @@ def update_max_potential_damage(
         attribute_name: Union[str, List[str], None] = None,
         method_damages: Union[str, List[str], None] = "nearest",
         max_dist: float = 10,
+        eur_to_us_dollar: bool = False
     ):
         if self.exposure:
             self.exposure.setup_max_potential_damage(
@@ -595,6 +601,7 @@ def update_max_potential_damage(
                 attribute_name=attribute_name,
                 method_damages=method_damages,
                 max_dist=max_dist,
+                eur_to_us_dollar = eur_to_us_dollar
             )
 
     def update_ground_elevation(

hydromt_fiat/workflows/damage_values.py

@@ -1,6 +1,7 @@
 import pandas as pd
 from pathlib import Path
 from typing import Union
+from hydromt_fiat.api.data_types import Conversion
 
 default_jrc_max_damage_adjustment_values = {
     "construction_cost_vs_depreciated_value_res": 0.6,
@@ -21,6 +22,7 @@
 def preprocess_jrc_damage_values(
     jrc_base_damage_values: pd.DataFrame,
     country: str,
+    eur_to_us_dollar: bool = False,
     max_damage_adjustment_values: dict = default_jrc_max_damage_adjustment_values,
 ) -> dict:
     """Preprocess the JRC damage values data.
@@ -31,6 +33,8 @@ def preprocess_jrc_damage_values(
         The JRC damage values data.
     country : str
         The country to filter the data on.
+    eur_to_us_dollar: bool
+        Convert JRC Damage Values (Euro 2010) into US-Dollars (2025)
 
     Returns
     -------
@@ -81,7 +85,11 @@ def preprocess_jrc_damage_values(
                 + ((jrc_base_value * cc_vs_dv * (1 - up) * mu) * mdci)
             ),
         }
-
+
+    if eur_to_us_dollar:
+        for damage_types, occupancy_types in damage_values.items():
+            for occupancy_type in occupancy_types:
+                occupancy_types[occupancy_type] *= Conversion.eur_to_us_dollars.value
     return damage_values
 
 

hydromt_fiat/workflows/exposure_vector.py

@@ -150,6 +150,7 @@ def setup_buildings_from_single_source(
         gfh_unit: Units = None,
         ground_elevation: Union[int, float, str, Path, None] = None,
         grnd_elev_unit: Units = None,
+        eur_to_us_dollar: bool = False
     ) -> None:
         """Set up asset locations and other available data from a single source.
 
@@ -165,6 +166,10 @@ def setup_buildings_from_single_source(
             height to the assets.
         extraction_method : str
             The extract_method to be used for all of the assets.
+        extraction_method : str
+            The extract_method to be used for all of the assets.
+        eur_to_us_dollar: bool
+            Convert JRC Damage Values (Euro 2010) into US-Dollars (2025)
         """
         if str(source).upper() == "NSI":
             # The NSI data is selected, so get the assets from the NSI
@@ -339,6 +344,7 @@ def setup_buildings_from_multiple_sources(
         bf_conversion: bool = False,
         keep_unclassified: bool = True,
         damage_translation_fn: Union[Path, str] = None,
+        eur_to_us_dollar: bool = False, 
     ):
         """
         Set up the exposure data using multiple sources.
@@ -395,6 +401,8 @@ def setup_buildings_from_multiple_sources(
         damage_translation_fn : Path, str
             The path to the file that contains the translation of the damage types to
             the damage values. If None, the default translation file will be used.
+        eur_to_us_dollar: bool
+            Convert JRC Damage Values (Euro 2010) into US-Dollars (2025)
 
         Returns
         -------
@@ -408,7 +416,7 @@ def setup_buildings_from_multiple_sources(
             occupancy_source, occupancy_attr, keep_unclassified=keep_unclassified
         )
         self.setup_max_potential_damage(
-            max_potential_damage, damage_types, country=country, damage_translation_fn = damage_translation_fn
+            max_potential_damage, damage_types, country=country, damage_translation_fn = damage_translation_fn, eur_to_us_dollar = eur_to_us_dollar
         )
         if (
             any(
@@ -923,6 +931,7 @@ def setup_max_potential_damage(
         max_dist: float = 10,
         country: Union[str, None] = None,
         damage_translation_fn: Union[str, Path] = None,
+        eur_to_us_dollar: bool = False
     ) -> None:
         """Setup the max potential damage column of the exposure data in various ways.
 
@@ -942,6 +951,8 @@ def setup_max_potential_damage(
             _description_, by default 10
         damage_translation_fn: Union[Path, str], optional
             The path to the translation function that can be used to relate user damage curves with user damages.
+        eur_to_us_dollar: bool
+            Convert JRC Damage Values (Euro 2010) into US-Dollars (2025)
         """
         if damage_types is None:
             damage_types = ["total"]
@@ -1029,7 +1040,7 @@ def setup_max_potential_damage(
                         f"No country specified, using the '{country}' JRC damage values."
                     )
 
-                damage_values = preprocess_jrc_damage_values(damage_source, country)
+                damage_values = preprocess_jrc_damage_values(damage_source, country, eur_to_us_dollar)
 
             elif max_potential_damage == "hazus_max_potential_damages":
                 damage_source = self.data_catalog.get_dataframe(max_potential_damage)