Vulnerability method csv input

.gitignore

@@ -115,4 +115,5 @@ venv.bak/
 .mypy_cache/
 
 # dask
-dask-worker-space/
+dask-worker-space/
+/local_test_database

examples/fiat_flood.ini

@@ -1,8 +1,8 @@
 [global]
-artifact_data = True            						# use latest artifact data
+artifact_data = False								# use latest artifact data
 
 [setup_config]
-case = baseline                 						# name of case
+case = test_exposure                 						# name of case
 strategy = base									# name of strategy (optional)
 scenario = base									# name of scenario (optional)
 year = 2021									# case year (optional)
@@ -16,36 +16,30 @@ risk_output = True								# indicator that specifies whether a risk calculation
 map_output = True								# indicator that specifies whether the result maps should be included in the output (default is True)
 
 [setup_hazard1]
-map_fn = data/flood_hand/hand_050cm_rp02.tif    				# absolute or relative (with respect to the configuration.ini) path to the hazard file
+map_fn = max_depth				    				# absolute or relative (with respect to the configuration.ini) path to the hazard file
 map_type = water_depth								# description of the hazard file type
-rp = 2              								# hazard return period in years, required for a risk calculation (optional)
-crs = 3452									# coordinate reference system of the hazard file (optional)
+rp = None              								# hazard return period in years, required for a risk calculation (optional)
+crs = 4326									# coordinate reference system of the hazard file (optional)
 nodata = -9999									# value that is assigned as nodata (optional)
 var = None									# hazard variable name in NetCDF input files (optional)
 chunks = 100									# chunk sizes along each dimension used to load the hazard file into a dask array (default is 'auto') (optional)
 
-[setup_hazard2]
-map_fn = data/flood_hand/hand_150cm_rp50.tif    				# absolute or relative (with respect to the configuration.ini) path to the hazard file
-map_type = water_depth								# description of the hazard file type
-rp = 50										# hazard return period in years, required for a risk calculation (optional)
-crs = 3452									# coordinate reference system of the hazard file (optional)
-nodata = -9999									# value that is assigned as nodata (optional)
-var = None									# hazard variable name in NetCDF input files (optional)
-chunks = 100									# chunk sizes along each dimension used to load the hazard file into a dask array (default is 'auto') (optional)
+; [setup_exposure]  
+; asset_locations = NSI
+
+[setup_vulnerability]
 
-[setup_buildings_value]  
-bld_fn = guf_bld_2012           						# name tag of or absolute or relative (with respect to the configuration file) path to the building footprint file (default is 'wsf_bld_2015')
-pop_fn = ghs_pop_2015_54009     						# name tag of or absolute or relative (with respect to the configuration file) path to the population count file (default is 'ghs_pop_2015')
-chunks = 100									# chunk sizes along each dimension used to load the building footprint and population count files into a dask arrays (default is 'auto') (optional)
-function_fn = None								# absolute or relative (with respect to the configuration file or susceptibility_dp) path to the susceptibility file (default is the JCR continental susceptibilty function (https://publications.jrc.ec.europa.eu/repository/handle/JRC105688) related to the country parameter) (optional)
-scale_factor = 1								# scaling factor of the exposure values (default is 1) (optional)
-weight_factor = 1								# weight factor of the exposure values in the total damage and risk results (default is 1) (optional)
+vulnerability_source = AllDFF.xlsx [linking_exposure_vulnerability]
 
-# Alternatives to conduct a risk calculation (triggered by a multiple hazard input):
-# [setup_hazard]
-# map_fn = [hazard/RP_2.tif, hazard/RP_100.tif]					# TODO: Not properly working yet, input is '[.., ..]' instead of ['..', '..']
-# rp = [2, 100]									# TODO: Not properly working yet, input is not parseble.
+name1 = RES1-1SNB-SAzone
+BldgDmgFnID1 = 157
+Occupancy1 = RES1 
+Source1 = FIA
+Description1 = one floor, no basement, Structure, A-Zone
+exposure1 = RES1
 
-# Alternative to derive rp from filename:
-# [setup_hazard1]
-# map_fn = hazard/RP_*.tif
+name2 = COM1blabla
+occupancy2 = COM1 
+source2 = FIA
+description2 = choose
+exposure2 = COM1

hydromt_fiat/data/vulnerability_test_file_input.csv

@@ -0,0 +1,12 @@
+Name,Link,ID,Occupancy,Source,Description
+My vulnerability function 1,APT,105,RES1,FIA,"one floor, no basement, Structure, A-Zone"
+My vulnerability function 2,APT2,105,RES1,FIA,"one floor, no basement, Structure, A-Zone"
+My vulnerability function 3,APT3,105,RES1,FIA,"one floor, no basement, Structure, A-Zone"
+My vulnerability function 4,HOUS,693,RES3A,BCAR - Jan 2011,"1to2 Stories, Elevated (Obstr)+6ft - no basement, Coastal A or V Zone"
+My vulnerability function 5,SHOP,228,COM1,USACE - Galveston,"Drug Store, structure"
+My vulnerability function 6,SHOP2,358,COM2,USACE - Galveston,"T.V. Repair, structure"
+My vulnerability function 7,MALL,459,COM4,USACE - New Orleans,"Utility Company, structure, salt water, short duration"
+My vulnerability function 8,MALL2,459,COM4,USACE - New Orleans,"Utility Company, structure, salt water, short duration"
+My vulnerability function 9,OFFI,550,IND1,USACE - Galveston,"Fabrication Shop, structure"
+My vulnerability function 10,HOUS2,699,RES3A,BCAR - Jan 2011,"1to2 Stories, Elevated (Obstr)+10ft - no basement, Coastal A or V Zone"
+My vulnerability function 11,HOUS3,699,RES3A,BCAR - Jan 2011,"1to2 Stories, Elevated (Obstr)+10ft - no basement, Coastal A or V Zone"

hydromt_fiat/fiat.py

@@ -1,9 +1,10 @@
 """Implement fiat model class"""
 
+import logging
 from hydromt.models.model_api import Model
 from hydromt_fiat.reader import Reader
 from hydromt_fiat.writer import Writer
-import logging
+from hydromt_fiat.workflows.vulnerability import Vulnerability
 
 
 from . import DATADIR
@@ -54,8 +55,9 @@ def setup_exposure_vector(self, region, **kwargs):
     def setup_exposure_raster(self):
         NotImplemented
 
-    def setup_vulnerability(self):
-        NotImplemented
+    def setup_vulnerability(self, vulnerability_source, vulnerability_identifiers_and_linking):
+        vul = Vulnerability(self.data_catalog)
+        vul.get_vulnerability_function(vulnerability_source, vulnerability_identifiers_and_linking)
 
     def setup_hazard(self):
         NotImplemented

hydromt_fiat/vulnerability_test_file_output.csv

@@ -0,0 +1,10 @@
+#UNIT=meter
+water depth,RES1,RES2,COM1
+-1,0,0,0
+0,0.2,0,0.2
+1,0.3,0.2,0.3
+2,0.4,0.5,0.4
+3,0.6,0.7,0.6
+4,1,0.9,1
+5,1,1,1
+6,1,1,1

hydromt_fiat/workflows/vulnerability.py

@@ -1,27 +1,72 @@
 import pandas as pd
+import numpy as np
 from pathlib import Path
+from hydromt.data_catalog import DataCatalog
+import re
 
 ### TO BE UPDATED ###
 class Vulnerability:
-    def get_susceptibility_function(self):
+    def __init__(self, data_catalog: DataCatalog):
+        self.data_catalog = data_catalog
+
+    def get_vulnerability_function(self, vulnerability_source, vulnerability_identifiers_and_linking):
+        # TODO: @Luis: this function needs to be changed. Now it looks up a damage function
+        # according to country that is chosen but we want the user to choose their
+        # damage functions per category (res, com, etc.). So our function will be
+        # quite different.
         """Return the susceptibility function id and the maximum damage number."""
 
-        # Read the global exposure configuration.
-        df_config = pd.read_excel(
-            Path(self._DATADIR).joinpath("global_configuration.xlsx"),
-            sheet_name="Buildings",
-        )
-
-        # Get the function id.
-        sf_id = df_config.loc[
-            df_config["Alpha-3"] == self.config["country"],
-            f"Damage_Function_ID_{self.config['hazard_type'].capitalize()}",
-        ].values[0]
-
-        # Get the maximum damage value.
-        max_damage = df_config.loc[
-            df_config["Alpha-3"] == self.config["country"],
-            f"Max_Damage_{self.config['hazard_type']. capitalize()}",
-        ].values[0]
-
-        return sf_id, max_damage
+        # Save the source vulnerabilities and input vulnerability identifiers and linking as data frames.
+        df_source = self.data_catalog.get_dataframe(vulnerability_source)
+
+        # USER INPUT, read csv generated via gui or manually inputted
+        df_identifiers_linking = pd.read_csv(vulnerability_identifiers_and_linking)
+
+        # Identify the unique combinations of values from the identifiers and linking data frame that will be used to select subsets of values from the source data frame.
+        # unique_combinations = df_identifiers_linking.groupby(['ID', 'Occupancy', 'Source', 'Description']).nunique().reset_index()
+
+        # Initialize an empty list to hold the subsets
+        subsets = []
+
+        # Loop over the unique combinations of values
+        for i in range(len(df_identifiers_linking)):
+            # Use the unique combination of values to select the corresponding subset of values
+            # from the first data frame using boolean indexing
+            subset = df_source.loc[(df_source['BldgDmgFnID'] == df_identifiers_linking.loc[i, 'ID']) &
+                            (df_source['Occupancy'] == df_identifiers_linking.loc[i, 'Occupancy']) &
+                            (df_source['Source'] == df_identifiers_linking.loc[i, 'Source']) &
+                            (df_source['Description'] == df_identifiers_linking.loc[i, 'Description'])]
+
+            # # Check if the subset is empty
+            # if subset.empty:
+            #     print(f"No values found for unique combination {df_identifiers_linking.loc[i]}")
+            # else:
+            #     print(f"Values found for unique combination {df_identifiers_linking.loc[i]}")
+
+            # Append the subset of values to the list of subsets
+            subsets.append(subset)
+
+        # Concatenate all of the necessary vulnerability curves info into a single data frame using pd.concat()
+        combined_df = pd.concat(subsets, ignore_index=True)
+
+        # Get vulnerability factors and apply FIAT format.
+        vf_values_only = combined_df.values.T[4:-1] /100
+
+        vf_water_depths_numbers = np.arange(-4,25)
+        vf_water_depths = np.array(vf_water_depths_numbers.reshape(-1,1))
+        vf_raw = np.hstack([vf_water_depths,vf_values_only])
+
+        top_header_array = np.full((1, vf_names_header.shape[0]), fill_value="", dtype='<U100')
+        top_header_array[0, 0] = "#UNIT=feet"
+
+        vf_names = df_identifiers_linking['Name'].values
+        vf_names_header = np.append('water depth', vf_names).reshape(top_header_array.shape)
+
+        vf_fiat_format = np.concatenate([top_header_array, vf_names_header, vf_raw])
+
+        # Create a dataframe out of the previous array.
+        v_dataframe = pd.DataFrame(vf_fiat_format)
+
+        # Export the dataframe to a csv.
+        v_dataframe.to_csv('vulnerability_test_file_output.csv', index=False, header=False)
+

tests/test_vulnerability.py

@@ -1,9 +1,30 @@
-from hydromt_fiat.workflows.vulnerability import Vulnerability
+from hydromt_fiat.fiat import FiatModel
+from hydromt.config import configread
 from pathlib import Path
+import pytest
 
-EXAMPLEDIR = Path().absolute() / "examples"
+EXAMPLEDIR = Path().absolute() / "local_test_database"
 
+_cases = {
+    "vulnerability": {
+        "data_catalogue": EXAMPLEDIR / "fiat_catalog.yml",
+        "dir": "test_vulnerability",
+        "ini": EXAMPLEDIR / "test_vulnerability.ini",
+    },
+}
 
-def test_vulnerability_class_initialization():
+@pytest.mark.parametrize("case", list(_cases.keys()))
+def test_vulnerability_class_initialization(case):
     # Read model in examples folder.
-    Vulnerability()
+    root = EXAMPLEDIR.joinpath(_cases[case]["dir"])
+    data_catalog_yml = str(_cases[case]["data_catalogue"])
+
+    fm = FiatModel(
+        root=root,
+        mode="w",
+        data_libs=[data_catalog_yml],
+    )
+
+    opt = configread(_cases[case]["ini"])
+    fm.build(opt=opt)
+

vulnerability_test_file_output.csv

@@ -0,0 +1,31 @@
+#UNIT=feet,,,,,,,,,,,
+water depth,My vulnerability function 1,My vulnerability function 2,My vulnerability function 3,My vulnerability function 4,My vulnerability function 5,My vulnerability function 6,My vulnerability function 7,My vulnerability function 8,My vulnerability function 9,My vulnerability function 10,My vulnerability function 11
+-4,0,0,0,0.08,0,0,0,0,0,0.38,0.38
+-3,0,0,0,0.17,0,0,0,0,0,0.78,0.78
+-2,0,0,0,0.53,0,0,0,0,0,1,1
+-1,0,0,0,0.93,0,0,0,0,0,1,1
+0,0.18,0.18,0.18,1,0,0,0,0,0,1,1
+1,0.22,0.22,0.22,1,0.01,0.02,0.72,0.72,0.02,1,1
+2,0.25,0.25,0.25,1,0.05,0.06,0.72,0.72,0.05,1,1
+3,0.28,0.28,0.28,1,0.05,0.12,1,1,0.1,1,1
+4,0.3,0.3,0.3,1,0.05,0.15,1,1,0.15,1,1
+5,0.31,0.31,0.31,1,0.07,0.2,1,1,0.2,1,1
+6,0.4,0.4,0.4,1,0.08,0.25,1,1,0.25,1,1
+7,0.43,0.43,0.43,1,0.11,0.32,1,1,0.3,1,1
+8,0.43,0.43,0.43,1,0.14,0.41,1,1,0.35,1,1
+9,0.45,0.45,0.45,1,0.18,0.5,1,1,0.4,1,1
+10,0.46,0.46,0.46,1,0.22,0.57,1,1,0.5,1,1
+11,0.47,0.47,0.47,1,0.27,0.61,1,1,0.75,1,1
+12,0.47,0.47,0.47,1,0.33,0.66,1,1,0.75,1,1
+13,0.49,0.49,0.49,1,0.38,0.69,1,1,0.75,1,1
+14,0.5,0.5,0.5,1,0.45,0.72,1,1,0.75,1,1
+15,0.5,0.5,0.5,1,0.51,0.75,1,1,0.75,1,1
+16,0.5,0.5,0.5,1,0.57,0.77,1,1,0.75,1,1
+17,0.51,0.51,0.51,1,0.63,0.8,1,1,0.75,1,1
+18,0.51,0.51,0.51,1,0.68,0.82,1,1,0.75,1,1
+19,0.52,0.52,0.52,1,0.73,0.84,1,1,0.75,1,1
+20,0.52,0.52,0.52,1,0.78,0.86,1,1,0.75,1,1
+21,0.53,0.53,0.53,1,0.83,0.88,1,1,0.75,1,1
+22,0.53,0.53,0.53,1,0.88,0.9,1,1,0.75,1,1
+23,0.54,0.54,0.54,1,0.93,0.92,1,1,0.75,1,1
+24,0.54,0.54,0.54,1,0.98,0.94,1,1,0.75,1,1