Merge pull request #104 from TomorrowsCities/feature_policy_8

tomorrowcities/backend/engine.py

@@ -443,6 +443,7 @@ def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensit
             earthquake_intensity_unit = 'm/s2',
             cdf_median_increase_in_percent = 0.20,
             flood_depth_reduction = 0.20,
+            damage_curve_suppress_factor = 0.9,
             ):
 
     print('cdf_median_increase_in_percent',cdf_median_increase_in_percent)
@@ -567,13 +568,6 @@ def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensit
             idx = (gdf_building_intensity['rnd'] < 0.70) & (gdf_building_intensity['occupancy'] == 'Res')
             gdf_building_intensity.loc[idx,'occupancy'] = 'Agri'
 
-    if 8 in policies:
-        if hazard_type == HAZARD_FLOOD or hazard_type == HAZARD_DEBRIS:
-            max_height = gdf_building_intensity['height'].max()
-            idx = gdf_building_intensity['specialfac'] == 0
-            gdf_building_intensity.loc[idx, 'height'] = gdf_building_intensity[idx]['height'].apply(lambda h: min(max_height, h+4))
-            gdf_building_intensity['storeys'] = gdf_building_intensity['height'].apply(lambda h: str(h)+'s')
-
     if 9 in policies:
         if hazard_type == HAZARD_FLOOD or hazard_type == HAZARD_DEBRIS:
             max_height = gdf_building_intensity['height'].max()
@@ -669,12 +663,16 @@ def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensit
                 # Increase medians *cdf_median_increase_in_percent* percent for residential buildings
                 applied_to = (bld_eq['occupancy'] == 'Res') & ((bld_eq['freqincome'] == 'lowIncomeA') | (bld_eq['freqincome'] == 'lowIncomeB'))
                 bld_eq.loc[applied_to, med_cols] = bld_eq.loc[applied_to, med_cols] * \
-                        ( 1 + cdf_median_increase_in_percent )
+                        ( 1 + cdf_median_increase_in_percent ) 
             if 6 in policies:
                 # Increase medians *cdf_median_increase_in_percent* percent for residential buildings
                 applied_to = bld_eq['occupancy']=='Res'
                 bld_eq.loc[applied_to, med_cols] = bld_eq.loc[applied_to, med_cols] * \
                         ( 1 + cdf_median_increase_in_percent )
+            if 8 in policies:
+                applied_to = bld_eq['occupancy'] == 'Res'
+                bld_eq.loc[applied_to, med_cols] = bld_eq.loc[applied_to, med_cols] * \
+                         ( 1 + cdf_median_increase_in_percent )
                 
             # Intensity measure calculation
             sa_list = np.array([float(x.split()[-1]) for x in bld_eq.columns if x.startswith('sa ')])
@@ -731,7 +729,11 @@ def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensit
                 applied_to = bld_eq['occupancy'] == 'Res'
                 bld_eq.loc[applied_to, imt_cols] = bld_eq.loc[applied_to, imt_cols] * \
                         ( 1 - cdf_median_increase_in_percent )
-                
+            if 8 in policies:
+                applied_to = bld_eq['occupancy'] == 'Res'
+                bld_eq.loc[applied_to, imt_cols] = bld_eq.loc[applied_to, imt_cols] * \
+                        ( 1 - cdf_median_increase_in_percent )
+                                
             def computer_damage_state(row):
                 intensity_in_g = row[row['imt_2']] / earthquake_intensity_normalization_factor
                 prob_ds1 = np.interp(intensity_in_g, row['imls'], row['slight'])
@@ -758,7 +760,7 @@ def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensit
 
     elif hazard_type == HAZARD_FLOOD:
         bld_flood = gdf_building_intensity.merge(df_hazard, on='expstr', how='left')
-
+        damage_curve_cols = ['hw0','hw0_5','hw1','hw1_5','hw2','hw3','hw4','hw5','hw6']
         # reduce flood depth *flood_depth_reduction* cm
         # Effect of policies are stacked
         if 1 in policies:
@@ -771,6 +773,9 @@ def compute(gdf_landuse, gdf_buildings, df_household, df_individual,gdf_intensit
         if 6 in policies:
             applied_to = bld_flood['occupancy'] == 'Res'
             bld_flood.loc[applied_to, 'im'] = bld_flood.loc[applied_to, 'im'] - flood_depth_reduction
+        if 8 in policies:
+            applied_to = bld_flood['occupancy'] == 'Res'
+            bld_flood.loc[applied_to, damage_curve_cols] = bld_flood.loc[applied_to, damage_curve_cols] * damage_curve_suppress_factor
         bld_flood.loc[bld_flood['im'] < 0, 'im'] = 0
 
         x = np.array([0,0.5,1,1.5,2,3,4,5,6])

tomorrowcities/pages/engine.py

@@ -53,6 +53,7 @@ def create_new_app_state():
     'cdf_median_increase_in_percent': solara.reactive(0.2),
     'threshold_increase_culvert_water_height': solara.reactive(0.2),
     'threshold_increase_road_water_height': solara.reactive(0.2),
+    'damage_curve_suppress_factor': solara.reactive(0.9),
     'flood_depth_reduction': solara.reactive(0.2),
     'dialog_message_to_be_shown': solara.reactive(None),
     'seed': solara.reactive(42),
@@ -245,15 +246,15 @@ def create_new_app_state():
     'selected_policies': solara.reactive([]),
     'policies': {
         '1': {'id':1, 'label': 'P1', 'description': 'Land and tenure security program', 'applied': solara.reactive(False)},
-        '2': {'id':2, 'label': 'P2', 'description': 'State-led upgrading/retrofitting of low-income/informal housing', 'applied': solara.reactive(False)},
-        '3': {'id':3, 'label': 'P3', 'description': 'Robust investment in WASH (water, sanitation and hygiene) and flood-control infrastructure', 'applied': solara.reactive(False)},
-        '4': {'id':4, 'label': 'P4', 'description': 'Investments in road networks and public spaces through conventional paving', 'applied': solara.reactive(False)},
-        '5': {'id':5, 'label': 'P5', 'description': 'Shelter Law - All low-income and informal settlements should have physical and free access to community centres and shelters', 'applied': solara.reactive(False)},
-        '6': {'id':6, 'label': 'P6', 'description': 'Funding community-based networks in low-income areas (holistic approaches)', 'applied': solara.reactive(False)},
-        '7': {'id':7, 'label': 'P7', 'description': 'Urban farming programs', 'applied': solara.reactive(False)},
-        '8': {'id':8, 'label': 'P8', 'description': 'Emergency cash transfers to vulnerable households', 'applied': solara.reactive(False)},
-        '9': {'id':9, 'label': 'P9', 'description': 'Waste collection and rivers cleaning program ', 'applied': solara.reactive(False)},
-        '10': {'id':10, 'label': 'P10', 'description': 'Enforcement of environmental protection zones', 'applied': solara.reactive(False)},
+        '2': {'id':2, 'label': 'P2', 'description': 'Housing retrofitting', 'applied': solara.reactive(False)},
+        '3': {'id':3, 'label': 'P3', 'description': 'Investment in water and sanitation', 'applied': solara.reactive(False)},
+        '4': {'id':4, 'label': 'P4', 'description': 'Investments in road networks', 'applied': solara.reactive(False)},
+        '5': {'id':5, 'label': 'P5', 'description': 'Access to more shelters', 'applied': solara.reactive(False)},
+        '6': {'id':6, 'label': 'P6', 'description': 'Funding community networks', 'applied': solara.reactive(False)},
+        '7': {'id':7, 'label': 'P7', 'description': 'Support for local livelihoods', 'applied': solara.reactive(False)},
+        '8': {'id':8, 'label': 'P8', 'description': 'Cash transfers to vulnerable groups', 'applied': solara.reactive(False)},
+        '9': {'id':9, 'label': 'P9', 'description': 'Waste collection and river cleaning program', 'applied': solara.reactive(False)},
+        '10': {'id':10, 'label': 'P10', 'description': 'Environmental protection zones', 'applied': solara.reactive(False)},
         #'11': {'id':11, 'label': 'I1', 'description': 'DRR-oriented zoning and urban transformation', 'applied': solara.reactive(False)},
         #'12': {'id':12, 'label': 'I2', 'description': 'Increased monitoring and supervision on new constructions in terms of disaster-resilience', 'applied': solara.reactive(False)},
         #'13': {'id':13, 'label': 'I3', 'description': 'Taking social equality into consideration in the making of urbanisation and DRR policies', 'applied': solara.reactive(False)},
@@ -1381,6 +1382,7 @@ def ExecutePanel():
             earthquake_intensity_unit = layers.value['earthquake_intensity_unit'].value
             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
 
 
             policies = [p['id'] for _, p in layers.value['policies'].items() if f"{p['label']}/{p['description']}" in layers.value['selected_policies'].value]
@@ -1410,6 +1412,7 @@ def ExecutePanel():
                     earthquake_intensity_unit=earthquake_intensity_unit,
                     cdf_median_increase_in_percent=cdf_median_increase_in_percent,
                     flood_depth_reduction=flood_depth_reduction,
+                    damage_curve_suppress_factor=damage_curve_suppress_factor
                     )
             else:
                 if fragility is None:
@@ -1427,6 +1430,7 @@ def ExecutePanel():
                     earthquake_intensity_unit=earthquake_intensity_unit,
                     cdf_median_increase_in_percent=cdf_median_increase_in_percent,
                     flood_depth_reduction=flood_depth_reduction,
+                    damage_curve_suppress_factor=damage_curve_suppress_factor,
                     )
             buildings['ds'] = list(df_bld_hazard['ds'])
             buildings['casualty'] = list(df_bld_hazard['casualty'])
@@ -1537,8 +1541,8 @@ def ExecutePanel():
     if len(policies) > 0:
         with solara.Column(gap="30px"):
             # if at least one of the policies is selected
-            if bool(set({1,2,4,6}).intersection(set(policies))):
-                with solara.Tooltip('Effects policies 1,2,4,6. Code-level upgrade of residential buildings (percentage increase in median value of the CDF default: 0.2)'):
+            if bool(set({1,2,4,6,8}).intersection(set(policies))):
+                with solara.Tooltip('Effects policies 1,2,4,6,8. Code-level upgrade of residential buildings (percentage increase in median value of the CDF default: 0.2)'):
                     solara.InputFloat(label='cdf_median_increase_in_percent',  value=layers.value['cdf_median_increase_in_percent'],
                                     continuous_update=True)
             if bool(set({1,2,3,6}).intersection(set(policies))):
@@ -1553,7 +1557,10 @@ def ExecutePanel():
                 with solara.Tooltip('Effects policies 4. Increasing water-depth threshold for roads'):
                     solara.InputFloat(label='threshold_increase_road_water_height',  value=layers.value['threshold_increase_road_water_height'],
                                     continuous_update=True)
-
+            if bool(set({8}).intersection(set(policies))):
+                with solara.Tooltip('Effects policies 8. Suppress damage curves via multiplying this factor'):
+                    solara.InputFloat(label='damage_curve_suppress_factor',  value=layers.value['damage_curve_suppress_factor'],
+                                    continuous_update=True)
     # The statements in this block are passed several times during thread execution
     if result.error is not None:
         execute_error.set(execute_error.value + str(result.error))