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added option for bfe from table when elevating #130

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Sep 13, 2023
Merged

added option for bfe from table when elevating #130

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91 changes: 56 additions & 35 deletions hydromt_fiat/workflows/exposure_vector.py
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Original file line number Diff line number Diff line change
Expand Up @@ -457,8 +457,10 @@ def setup_max_potential_damage(
)
]
except KeyError as e:
self.logger.warning(f"Not found in the {max_potential_damage} damage "
f"value data: {e}")
self.logger.warning(
f"Not found in the {max_potential_damage} damage "
f"value data: {e}"
)

def update_max_potential_damage(
self, updated_max_potential_damages: pd.DataFrame
Expand Down Expand Up @@ -550,7 +552,7 @@ def raise_ground_floor_height(
"Ground Floor Height",
].iloc[idx, :] = raise_by

elif height_reference.lower() == "geom":
elif height_reference.lower() in ["geom", "table"]:
# Elevate the objects relative to the surface water elevation map that the
# user submitted.
self.logger.info(
Expand All @@ -564,6 +566,7 @@ def raise_ground_floor_height(
self.exposure_db.iloc[idx, :] = self.set_height_relative_to_reference(
self.exposure_db.iloc[idx, :],
self.exposure_geoms[0].iloc[idx, :],
height_reference,
path_ref,
attr_ref,
raise_by,
Expand All @@ -574,10 +577,6 @@ def raise_ground_floor_height(
"original exposure data."
)

elif height_reference.lower() == "table":
# Input a CSV with Object IDs and elevations
NotImplemented

else:
self.logger.warning(
"The height reference of the Ground Floor Height is set to "
Expand Down Expand Up @@ -836,6 +835,7 @@ def setup_new_composite_areas(
new_objects = self.set_height_relative_to_reference(
new_objects,
_new_exposure_geoms,
elevation_reference,
path_ref,
attr_ref,
ground_floor_height,
Expand Down Expand Up @@ -1064,6 +1064,7 @@ def set_height_relative_to_reference(
self,
exposure_to_modify: pd.DataFrame,
exposure_geoms: gpd.GeoDataFrame,
height_reference: str,
path_ref: str,
attr_ref: str,
raise_by: Union[int, float],
Expand All @@ -1077,6 +1078,8 @@ def set_height_relative_to_reference(
_description_
exposure_geoms : gpd.GeoDataFrame
_description_
height_reference : str
_description_
path_ref : str
_description_
attr_ref : str
Expand All @@ -1095,36 +1098,54 @@ def set_height_relative_to_reference(
the same as that of the exposure data
"""
# Add the different options of input data: vector, raster, table
reference_shp = gpd.read_file(path_ref, engine="pyogrio") # Vector

# Reproject the input flood map if necessary
if reference_shp.crs != CRS.from_user_input(out_crs):
reference_shp = reference_shp.to_crs(
out_crs
) # TODO: make sure that the exposure_geoms file is projected in the out_crs (this doesn't happen now)

# Spatially join the data
modified_objects_gdf = gpd.sjoin(
exposure_geoms,
reference_shp[[attr_ref, "geometry"]],
how="left",
)
if height_reference == "geom":
reference_shp = gpd.read_file(path_ref, engine="pyogrio") # Vector

# Reproject the input flood map if necessary
if reference_shp.crs != CRS.from_user_input(out_crs):
reference_shp = reference_shp.to_crs(
out_crs
) # TODO: make sure that the exposure_geoms file is projected in the out_crs (this doesn't happen now)

# Spatially join the data
modified_objects_gdf = gpd.sjoin(
exposure_geoms,
reference_shp[[attr_ref, "geometry"]],
how="left",
)

# Sort and add the elevation to the shp values, append to the exposure dataframe
# To be able to append the values from the GeoDataFrame to the DataFrame, it
# must be sorted on the Object ID.
identifier = (
"Object ID" if "Object ID" in modified_objects_gdf.columns else "object_id"
)
# Sort and add the elevation to the shp values, append to the exposure dataframe
# To be able to append the values from the GeoDataFrame to the DataFrame, it
# must be sorted on the Object ID.
identifier = (
"Object ID"
if "Object ID" in modified_objects_gdf.columns
else "object_id"
)

# Group by the identifier and take the maximum value of the attribute reference
# to avoid duplicates in the case of overlapping polygons in the data used
# as reference.
modified_objects_gdf = (
modified_objects_gdf.groupby(identifier)
.max(attr_ref)
.sort_values(by=[identifier])
)

elif height_reference == "table":
# Add table
reference_table = pd.read_csv(path_ref) # Vector
# Join the data based on "Object ID"
modified_objects_gdf = pd.merge(
exposure_geoms,
reference_table[["Object ID", attr_ref]],
on="Object ID",
how="left",
)
modified_objects_gdf = modified_objects_gdf.sort_values(
by=["Object ID"]
).set_index("Object ID", drop=False)

# Group by the identifier and take the maximum value of the attribute reference
# to avoid duplicates in the case of overlapping polygons in the data used
# as reference.
modified_objects_gdf = (
modified_objects_gdf.groupby(identifier)
.max(attr_ref)
.sort_values(by=[identifier])
)
exposure_to_modify = exposure_to_modify.sort_values(by=["Object ID"]).set_index(
"Object ID", drop=False
)
Expand Down