Merge pull request #113 from TomorrowsCities/feature_multi_class_flood

tomorrowcities/backend/engine.py

@@ -117,10 +117,10 @@ def compute_road_infra(buildings, household, individual,
             flooded_roads = (non_bridges) & (gdf_edges['im'] > road_water_height_threshold)
             flooded_culverts = (culverts) & (gdf_edges['im'] > culvert_water_height_threshold)
 
-            gdf_edges.loc[flooded_roads, 'ds'] = 1
+            gdf_edges.loc[flooded_roads, 'ds'] = DS_COMPLETE
             gdf_edges.loc[flooded_roads, 'is_damaged'] = True
 
-            gdf_edges.loc[flooded_culverts, 'ds'] = 1
+            gdf_edges.loc[flooded_culverts, 'ds'] = DS_COMPLETE
             gdf_edges.loc[flooded_culverts, 'is_damaged'] = True
     elif hazard == 'earthquake':
         fragility = fragility.rename(columns={"med_slight": "med_ds1", 
@@ -242,6 +242,7 @@ def compute_power_infra(buildings, household, nodes,edges,intensity,fragility,ha
                         threshold_flood, threshold_flood_distance, preserve_edge_directions,
                         earthquake_intensity_unit = 'm/s2',
                         ):
+    print('threshold_flood', threshold_flood)
     earthquake_intensity_normalization_factor = 1
     if earthquake_intensity_unit == 'm/s2':
         earthquake_intensity_normalization_factor = 9.81
@@ -355,8 +356,8 @@ def compute_power_infra(buildings, household, nodes,edges,intensity,fragility,ha
         flood_mapping = interp1d(x,y,axis=1,kind='linear',bounds_error=False, fill_value=(0,1))
         # TODO: find another way for vectorized interpolate
         gdf_nodes['fl_prob'] = np.diag(flood_mapping(xnew))
-        gdf_nodes['ds'] = 0
-        gdf_nodes.loc[gdf_nodes['fl_prob'] > threshold_flood,'ds'] = 1
+        ds2_threshold, ds3_threshold, ds4_threshold = threshold_flood
+        gdf_nodes['ds'] = gdf_nodes['fl_prob'].map(lambda x: DS_COMPLETE if x > ds4_threshold else DS_EXTENSIVE if x > ds3_threshold else DS_MODERATE if x > ds2_threshold else DS_SLIGHT if x > 0 else DS_NO )
         
     # All Nodes
     all_nodes = set(gdf_nodes['node_id'])
@@ -439,13 +440,13 @@ def compute_power_infra(buildings, household, nodes,edges,intensity,fragility,ha
            gdf_buildings['has_power'], household_w_node_id['has_power'],hospitals['has_power'] 
 
 def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensity, df_hazard, hazard_type, policies=[],
-            threshold_flood = 0.2, threshold_flood_distance = 10,
+            threshold_flood = [0.05, 0.2, 0.5], threshold_flood_distance = 10,
             earthquake_intensity_unit = 'm/s2',
             cdf_median_increase_in_percent = 0.20,
             flood_depth_reduction = 0.20,
             damage_curve_suppress_factor = 0.9,
             ):
-
+    print('threshold_flood', threshold_flood)
     print('cdf_median_increase_in_percent',cdf_median_increase_in_percent)
     print('flood_depth_reduction', flood_depth_reduction)
     print('policies', policies)
@@ -778,9 +779,9 @@ def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensit
         flood_mapping = interp1d(x,y,axis=1,kind='linear',bounds_error=False, fill_value=(0,1))
         # TODO: find another way for vectorized interpolate
         bld_flood['fl_prob'] = np.diag(flood_mapping(xnew))
-        bld_flood['fl_ds'] = 0
-        flooded_buildings = bld_flood['fl_prob'] > threshold_flood
-        bld_flood.loc[flooded_buildings, 'fl_ds'] = 1
+        ds2_threshold, ds3_threshold, ds4_threshold = threshold_flood
+        bld_flood['fl_ds'] = bld_flood['fl_prob'].map(lambda x: DS_COLLAPSED if x > ds4_threshold else DS_EXTENSIZE if x > ds3_threshold else DS_MODERATE if x > ds2_threshold else DS_SLIGHT if x > 0 else DS_NO )
+        flooded_buildings = bld_flood['fl_ds'] > DS_SLIGHT
 
         casualty_rates = np.array([[0,0,0,0.000976715,0.0105355,0.052184493,0.160744982,0.373769339,0.743830881]])
         y_casualty = np.repeat(casualty_rates, len(bld_flood),axis=0)
@@ -844,13 +845,12 @@ def generate_metrics(t, t_full, hazard_type, population_displacement_consensus):
     HAZARD_FLOOD = "flood"
     HAZARD_DEBRIS = "debris"
 
-    if hazard_type == HAZARD_EARTHQUAKE:
+    if hazard_type == HAZARD_EARTHQUAKE or hazard_type == HAZARD_FLOOD:
     # Effect of policies on thresholds
     # First get the global threshold
         thresholds = {f'metric{id}': DS_SLIGHT for id in range(8)}
     else:
-        # Default thresholds for flood and debris
-        # For flood, there are only two states: 0 or 1.
+        # For debris, there are only two states: 0 or 1.
         # So threshold is set to 0.
         thresholds = {f'metric{id}': DS_NO for id in range(8)}
 

tomorrowcities/pages/engine.py

@@ -23,7 +23,7 @@ import pickle
 import datetime
 from . import storage, user, session_storage, store_in_session_storage, read_from_session_storage
 from .settings import landslide_max_trials
-from .settings import threshold_flood, threshold_flood_distance, threshold_road_water_height, threshold_culvert_water_height, preserve_edge_directions,\
+from .settings import threshold_flood_ds2, threshold_flood_ds3, threshold_flood_ds4, threshold_flood_distance, threshold_road_water_height, threshold_culvert_water_height, preserve_edge_directions,\
                       population_displacement_consensus
 from ..backend.engine import compute, compute_power_infra, compute_road_infra, calculate_metrics, generate_exposure, \
     create_tally, generate_metrics
@@ -1357,6 +1357,7 @@ def ExecutePanel():
             fragility = layers.value['layers']['power fragility']['data'].value
             hazard = layers.value['hazard'].value
             earthquake_intensity_unit = layers.value['earthquake_intensity_unit'].value
+            threshold_flood = [threshold_flood_ds2.value, threshold_flood_ds3.value, threshold_flood_ds4.value]
 
             if layers.value['hazard'].value == 'landslide':
                 fragility = layers.value['layers']['landslide fragility']['data'].value
@@ -1373,7 +1374,7 @@ def ExecutePanel():
                                     edges,
                                     intensity,
                                     fragility,
-                                    hazard, threshold_flood.value, threshold_flood_distance.value,
+                                    hazard, threshold_flood, threshold_flood_distance.value,
                                     preserve_edge_directions.value,
                                     earthquake_intensity_unit=earthquake_intensity_unit,
                                     )
@@ -1400,7 +1401,7 @@ def ExecutePanel():
             flood_depth_reduction = layers.value['flood_depth_reduction'].value
             cdf_median_increase_in_percent = layers.value['cdf_median_increase_in_percent'].value
             damage_curve_suppress_factor = layers.value['damage_curve_suppress_factor'].value
-
+            threshold_flood = [threshold_flood_ds2.value, threshold_flood_ds3.value, threshold_flood_ds4.value]
 
             policies = [p['id'] for _, p in layers.value['policies'].items() if f"{p['description']} ({p['label']})" in layers.value['selected_policies'].value]
 
@@ -1424,7 +1425,7 @@ def ExecutePanel():
                     fragility[['expstr','susceptibility',trigger_level]].rename(columns={trigger_level:'collapse_probability'}),
                     layers.value['hazard'].value,
                     policies=policies,
-                    threshold_flood = threshold_flood.value,
+                    threshold_flood = threshold_flood,
                     threshold_flood_distance = threshold_flood_distance.value,
                     earthquake_intensity_unit=earthquake_intensity_unit,
                     cdf_median_increase_in_percent=cdf_median_increase_in_percent,
@@ -1442,7 +1443,7 @@ def ExecutePanel():
                     intensity,
                     fragility if layers.value['hazard'].value == "earthquake" else vulnerability,
                     layers.value['hazard'].value, policies=policies,
-                    threshold_flood = threshold_flood.value,
+                    threshold_flood = threshold_flood,
                     threshold_flood_distance = threshold_flood_distance.value,
                     earthquake_intensity_unit=earthquake_intensity_unit,
                     cdf_median_increase_in_percent=cdf_median_increase_in_percent,

tomorrowcities/pages/settings.py

@@ -6,7 +6,10 @@ import os
 from . import user, config
 
 landslide_max_trials = solara.reactive(5)
-threshold_flood = solara.reactive(0.2) 
+threshold_flood_ds2 = solara.reactive(0.05)
+threshold_flood_ds3 = solara.reactive(0.20)
+threshold_flood_ds4 = solara.reactive(0.50)
+
 threshold_flood_distance = solara.reactive(10)
 threshold_road_water_height = solara.reactive(0.3) 
 threshold_culvert_water_height = solara.reactive(1.5)
@@ -31,7 +34,9 @@ def Page(name: Optional[str] = None, page: int = 0, page_size=100):
                         If the relative damage obtained from the vulnerability curve is beyond 
                         the flood threshold, the structure is assumed to flooded.
                         After resetting the value, please execute the simulation again to see its effect.''')
-        solara.SliderFloat(label='Flood Threshold (relative damage)', value=threshold_flood, min=0,max=1, step=0.1)
+        solara.SliderFloat(label='Flood Threshold for DS2', value=threshold_flood_ds2, min=0.05,max=1, step=0.05)
+        solara.SliderFloat(label='Flood Threshold for DS3', value=threshold_flood_ds3, min=0.05,max=1, step=0.05)
+        solara.SliderFloat(label='Flood Threshold for DS4', value=threshold_flood_ds4, min=0.05,max=1, step=0.05)
         solara.Markdown(md_text='''
                         If the distance from a structure to the nearest flood intensity measure
                         is greater than Flood Distance, then the structure is assumed to be