v0.2.2 completed road & power network analysis

tomorrowcities/backend/engine.py

@@ -119,7 +119,29 @@ def compute_road_infra(buildings, household, individual,
                 idx = (household_w_node_id['commfacid'] == hospital_bld) & (household_w_node_id['node_id'] == node_with_hospital_access)
                 household_w_node_id.loc[idx, 'hospital_access'] = True
 
-    return gdf_edges['ds'], gdf_edges['is_damaged'], gdf_buildings['node_id'], gdf_buildings['hospital_access'], household_w_node_id['node_id'], household_w_node_id['hospital_access']
+    # Workplace/School (facility) connectivity analysis
+    # For each individual, find the closest road node (closest) of the
+    # household and the facility
+
+    individual_w_nodes = individual.merge(household_w_node_id[['hhid','node_id']],on='hhid',how='left')\
+                        .rename(columns={'node_id':'household_node_id'})\
+                        .merge(gdf_buildings[['bldid','node_id']],how='left',left_on='indivfacid',right_on='bldid')\
+                        .rename(columns={'node_id':'facility_node_id'})
+
+    # Calculate distances between all nodes in the damaged network
+    shortest_distance = nx.shortest_path_length(G_dmg)
+
+    # Create a dictionary to store all open connections
+    connection_dict = dict()
+    for source, targets in shortest_distance:
+        connection_dict[source] = dict()
+        for target, hop in targets.items():
+            connection_dict[source][target] = True
+
+    # Based on connectivity, fill-in facillity_access attribute in the individual layer
+    individual_w_nodes['facility_access'] = individual_w_nodes.apply(lambda x: x['facility_node_id'] in connection_dict[x['household_node_id']].keys(),axis=1)
+
+    return gdf_edges['ds'], gdf_edges['is_damaged'], gdf_buildings['node_id'], gdf_buildings['hospital_access'], household_w_node_id['node_id'], household_w_node_id['hospital_access'], individual_w_nodes['facility_access']
 
 def compute_power_infra(buildings, household, nodes,edges,intensity,fragility,hazard):
     print('Computing power infrastructure')
@@ -591,6 +613,8 @@ def calculate_metrics(gdf_buildings, df_household, df_individual, infra, hazard_
     metric1_index = df_workers['ds'] > thresholds['metric1']
     if 'power' in infra:
         metric1_index = (metric1_index) | (df_workers['has_power'] == False)
+    if 'road' in infra:
+        metric1_index = (metric1_index) | (df_workers['facility_access'] == False)
     df_workers_per_building = df_workers[metric1_index][['individ','hhid','ds']].merge(
         df_household[['hhid','bldid']],on='hhid',how='left').groupby(
             'bldid',as_index=False).agg({'individ':'count'})
@@ -605,6 +629,8 @@ def calculate_metrics(gdf_buildings, df_household, df_individual, infra, hazard_
     metric2_index = df_students['ds'] > thresholds['metric2']
     if 'power' in infra:
         metric2_index = (metric2_index) | (df_students['has_power'] == False)
+    if 'road' in infra:
+        metric2_index = (metric2_index) | (df_students['facility_access'] == False)
     df_students_per_building = df_students[metric2_index][['individ','hhid','ds']].merge(
         df_household[['hhid','bldid']],on='hhid',how='left').groupby(
             'bldid',as_index=False).agg({'individ':'count'})
@@ -673,6 +699,7 @@ def calculate_metrics(gdf_buildings, df_household, df_individual, infra, hazard_
                     (df_displaced_indiv['ds_hospital'] > thresholds['metric4']) 
     if 'road' in infra:
         metric7_index = (metric7_index) | (df_displaced_indiv['hospital_access'] == False)
+        metric7_index = (metric7_index) | (df_displaced_indiv['facility_access'] == False)
     if 'power' in infra:
         metric7_index = (metric7_index) | (df_displaced_indiv['hospital_has_power'] == False)
         metric7_index = (metric7_index) | (df_displaced_indiv['workplace_power'] == False)

tomorrowcities/content/articles/metrics.md

@@ -19,11 +19,21 @@ Their calculations heavily depend on the damage state of buildings and/or other
 infrastructural elements such as electrical power generators, roads or bridges. 
 
 ### Metric 1: Number of workers unemployed
-It denotes the number of invidivuals who lost their jobs either due to a damage at the workplace or lost access to a workplace. When the metrics is displayed on a building-level, it is the total number of such individuals living in that building.
+It denotes the number of invidivuals who lost their jobs based on any of the following conditions:
+
+* the associated workplace is damaged beyond a threshold
+* the associated workplace has lost electricity
+* the associated workplace can not be reached from the building that the individual lives in via
+transportation network.
 
 ### Metric 2: Number of children with no access to education
-Similar to the first metrics but individual here refers to a child who is associated with a school.
-The metric becomes active if the school is damaged or not accessible.
+Similar to the first metrics but individual here refers to individuals associated with a school.
+This metric takes place when any of the following conditions holds:
+
+* the school is damaged beyond a threshold
+* the school has lost electricity
+* the school can not be reached from the building that the individual lives in via
+transportation network.
 
 ### Metric 3: Number of households with no access to hospital
 The number of households who lost its access to its associated hospital.
@@ -34,7 +44,13 @@ Access is lost when any of the following conditions hold:
 * the associated hospital has no electricity
 
 ### Metric 4: Number of individuals with no access to hospital
-It is derived from metric 3 by counting the individuals in the corresponding households.
+This metric is very similar to metric 3 except individual-hospital association
+is used. In this metric, individual-hospital association is built upon household-hospital association.
+An individual is said to lost his/her access to hospital when any of the conditions hold:
+
+* the damage state of the associated hospital is beyond a threshold
+* the associated hospital is inaccessible via transportation network
+* the associated hospital has no electricity
 
 ### Metric 5: Number of households displaced
 It is direct result of building damage state. If a building is damaged, then the households in it are also
@@ -44,4 +60,9 @@ damaged.
 It is derived from metric 5.
 
 ### Metric 7: Population displacement
-An individual is assumed to be displaced if the associated household is damaged, or he/she lost access to workplace, schoold or hospital. 
+An individual is assumed to be displaced when any of the following condition holds:
+
+* the associated household is damaged
+* the individual's workplace, school, or associated hospital is damaged
+* the individual can not reach to workplace, school, or associated hospital via transportation network
+* the individual's workplace, school, or associated hospital has no electricity

tomorrowcities/content/articles/power.md

@@ -13,4 +13,60 @@ category:
 
 [TOC]
 
-## Power Infrastructure Analysis
+## Power Infrastructure Analysis
+
+
+### Data
+**Power Nodes**
+
+node_id|pwr_plant|n_bldgs|eq_vuln|geometry|
+|-------|---------|-------|-------|--------|
+|1      |1        |None   |None   |POINT (36.80602 -1.31293)|
+|2      |0        |0      |ESS1   |POINT (36.80302 -1.36646)|
+|3      |0        |3      |ESS2   |POINT (36.80302 -1.36646)|
+
+**node_id** is a unique identifier for electrical power node.
+**pwr_plant** indicates that the power node is a generator/power source
+when it is set to 1 or True.
+**n_bldgs** is used for the nodes which distributes electricity to the
+neighboring building. If this attribute is a positive value then it will used
+to distribute power to the neighbors. Such nodes are called *server* nodes.
+**eq_vuln** is the taxonomy string used for the structural power node building.
+When not specified, the node is assumed to be immune to hazards. Finally comes
+the geometry column which is simple a point coordinate in WGS84 coordinate
+reference system.
+
+**Power Edges**
+The minimum required attributes of the edges is shown below:
+
+|edge_id|from_node|to_node|geometry|
+|---------|-------|-------|--------|
+|1        |2      |1   |LINESTRING (82.61515 27.80731, ...|
+|2        |3      |1   |LINESTRING (82.72634 27.68782, ...|
+|3        |1      |2   |LINESTRING (82.06824 27.80731, ...|
+
+where **edge_id** is the unique identifier of the transmission line between any two nodes.
+**from/to_node** attributes define the starting and ending nodes of the transmission line.
+Finally comes the geometry as a line string. For transmission lines, no taxonomy information
+is required.
+
+**Power Fragility**
+The fragility functions for the power node structures are defined as a tabular tabular data whose
+attributes are shown below.
+
+| vuln_string  |med_Slight | med_Moderate | med_Extensive | med_Complete | beta_Slight | beta_Moderate | beta_Extensive | beta_Complete |                                       description|
+|--------------|-----------|--------------|---------------|--------------|-------------|---------------|----------------|---------------|--------------------------------------------------|
+|       ESS1   |    0.15   |       0.29   |        0.45   |       0.90   |      0.70   |        0.55   |         0.45   |        0.45   | Low Voltage (115 KV) Substation (Anchored/Seis...|
+|       ESS2   |    0.13   |       0.26   |       0.34    |      0.74    |     0.65    |       0.50    |        0.40    |       0.40    | Low Voltage (115 KV) Substation (Unanchored/St...|
+|       ESS3   |    0.15   |       0.25   |       0.35    |      0.70    |     0.60    |       0.50    |        0.40    |       0.40    | Medium Voltage (230 KV) Substation (Anchored/S...|
+
+**vuln_string** of the fragility curves should match **eq_vuln** field of the power nodes. Median and beta values of four fragility curves (slight, moderate, extensive and complete) are defined
+in the same row. It is optional to add a description message.
+
+### Additional Auxillary Attributes
+As soon as the power network analysis is conducted, 
+the engine creates internal attributes tagged to building and household layers
+which will be visible in LayerDisplayer. The name of the additional attribute is
+*has_power* which is a boolean variable. When used in the building layer, it indicates
+if a building has power or not. The same attribute is also used in household layer
+which indicates the associated building has power.

tomorrowcities/content/articles/welcome.md

@@ -18,7 +18,18 @@ TCDSE is a web application designed to conduct computational tasks to generate i
 
 ## What is New?
 
-**v0.2.1**
+**Changelog: v0.2.2**
+
+* Power and Road network analysis is completed.
+* Electrical power loss information is propagated to household and individual layers.
+* All seven impact metrics are updated to reflect electrical power-loss.
+* All seven impact metrics are updated to reflect damage in road network.
+* Documentation in the engine is extended.
+* New version of the engine is redeployed to [HuggingFace](https://huggingface.co/spaces/hkayabilisim/app-engine).
+* Reorganized the folders in the [Sample Dataset](https://drive.google.com/file/d/1BGPZQ2IKJHY9ExOCCHcNNrCTioYZ8D1y/view?usp=sharing).
+* Building layer can now be exported as CSV also.
+
+**Changelog: v0.2.1**
 
 * [27dd195](https://github.com/TomorrowsCities/tomorrowcities/commit/27dd195a240cbb97a97d124fc9b132ee2ea1f5e9) Integrated road network analysis into metric3
 * [de6fbca](https://github.com/TomorrowsCities/tomorrowcities/commit/de6fbca8d8b03d350096190ae35646f47a9a0414) Changed engine layout to be more compact 
@@ -27,7 +38,7 @@ TCDSE is a web application designed to conduct computational tasks to generate i
 * Extended documentation in welcome, data, metrics, and road pages.
 * Added [a demonstration video](https://github.com/TomorrowsCities/tomorrowcities/assets/2515171/ec2dc36d-fe76-42fb-b9be-47a1690374de) to GitHub discussion page[discussion](https://github.com/TomorrowsCities/tomorrowcities/discussions/6).
 
-**v0.2**
+**Changelog: v0.2**
 
 * Transportation network analysis for flood and earthquake damage assessment
 * Building and household-level loss of hospital access information

tomorrowcities/pages/engine.py

@@ -73,7 +73,7 @@ layers = solara.reactive({
             'force_render': solara.reactive(False),
             'visible': solara.reactive(False),
             'pre_processing': identity_preprocess,
-            'extra_cols': {},
+            'extra_cols': {'facility_access':True},
             'attributes_required': set(['individ', 'hhid', 'gender', 'age', 'eduattstat', 'head', 'indivfacid']),
             'attributes': set(['individ', 'hhid', 'gender', 'age', 'eduattstat', 'head', 'indivfacid'])},
         'intensity': {
@@ -848,9 +848,12 @@ def LayerDisplayer():
                 #solara.CrossFilterDataFrame(df=data)
                 solara.DataFrame(data, items_per_page=5)
             if selected == "building":
-                file_object = data.to_json()
-                with solara.FileDownload(file_object, "building_export.geojson", mime_type="application/geo+json"):
-                    solara.Button("Download GeoJSON", icon_name="mdi-cloud-download-outline", color="primary")
+                with solara.Row():
+                    file_object = data.to_json()
+                    with solara.FileDownload(file_object, "building_export.geojson", mime_type="application/geo+json"):
+                        solara.Button("Download GeoJSON", icon_name="mdi-cloud-download-outline", color="primary")
+                    with solara.FileDownload(data.to_csv(), "building_export.csv", mime_type="text/csv"):
+                        solara.Button("Download CSV", icon_name="mdi-cloud-download-outline", color="primary")
         if selected == 'gem_vulnerability':
             VulnerabiliyDisplayer(data)
 
@@ -978,7 +981,9 @@ def ExecutePanel():
             buildings['hospital_access'] = False
             household['node_id'] = None
             household['hospital_access'] = False
-            ds, is_damaged, building_node_id, building_hospital_acess, household_node_id, household_hospital_access  = \
+            individual['facility_access'] = True
+            ds, is_damaged, building_node_id, building_hospital_acess, household_node_id, \
+                    household_hospital_access, individual_facility_access  = \
                 compute_road_infra(buildings, household, individual, nodes, edges, intensity, 
                 fragility, hazard,road_water_height_threshold)
             
@@ -988,11 +993,12 @@ def ExecutePanel():
             buildings['hospital_access'] = list(building_hospital_acess)
             household['node_id'] = list(household_node_id)   
             household['hospital_access'] = list(household_hospital_access)
+            individual['facility_access'] = list(individual_facility_access)
   
             print(buildings.head())
             print('number of damaged roads/bridges',len(edges[edges['is_damaged']]))
 
-            return edges, buildings, household
+            return edges, buildings, household, individual
 
         def execute_power():
             buildings = layers.value['layers']['building']['data'].value
@@ -1089,10 +1095,11 @@ def ExecutePanel():
                 layers.value['layers']['building']['data'].set(buildings)
                 layers.value['layers']['household']['data'].set(household)
             if 'road' in layers.value['infra'].value:
-                edges, buildings, household = execute_road()
+                edges, buildings, household, individual = execute_road()
                 layers.value['layers']['road edges']['data'].set(edges)
                 layers.value['layers']['building']['data'].set(buildings)
                 layers.value['layers']['household']['data'].set(household)
+                layers.value['layers']['individual']['data'].set(individual)
             if 'building' in layers.value['infra'].value:
                 buildings = execute_building()
                 layers.value['layers']['building']['data'].set(buildings)