Building classification and further exposure indicators are assigned to each...

Building classification and further exposure indicators are assigned to each building and written to the Exposure table

exposurecoquimbo/saradata.py

@@ -5,6 +5,8 @@ import csv
 from shapely import wkt
 import geopandas
 from pygeotile.tile import Tile
+import numpy
+
 
 COQUIMBO_LONGITUDE = [-71.5, -71.0]
 COQUIMBO_LATITUDE = [-30.25, -29.25]
@@ -59,8 +61,8 @@ def create_sara_database(database_filepath):
                     NAME  TEXT);''')
     sql_statement = "SELECT AddGeometryColumn('LOCATIONS', 'geometry', 4326, 'POINT', 'XY');"
     conn.execute(sql_statement)
-    sql_statement = "SELECT AddGeometryColumn('LOCATIONS', 'voronoi', 4326, 'POLYGON', 'XY');"
-    conn.execute(sql_statement)
+    # sql_statement = "SELECT AddGeometryColumn('LOCATIONS', 'voronoi', 4326, 'POLYGON', 'XY');"
+    # conn.execute(sql_statement)
     print("Table LOCATIONS created")
 
 
@@ -181,6 +183,7 @@ def add_buildings(conn, building_filepath):
     cur = conn.cursor()
     # Create the Buildings table
     sql = 'CREATE TABLE Buildings ('
+    sql += 'IDX   INTEGER PRIMARY KEY AUTOINCREMENT,'
     sql += 'loc_id INTEGER,'
     sql += 'quadkey TEXT);'
     cur.execute(sql)
@@ -216,12 +219,70 @@ def add_buildings(conn, building_filepath):
         conn.commit()
 
 
+def classify_buildings(conn):
+
+    # Create building classification table
+    cur = conn.cursor()
+    # Create the Buildings table
+    # sql = 'CREATE TABLE Exposure ('
+    # sql += 'building_id INTEGER, '
+    # sql += 'taxonomy TEXT, '
+    # sql += 'NUMBER   REAL, '
+    # sql += 'STRUCTURAL  REAL, '
+    # sql += 'NIGHT       REAL);'
+    # cur.execute(sql)
+    # print("Table Exposure created")
+
+    # Simple version
+    # Loop over all exposure-data locations (Voronoi cells)
+    sql_statement = "SELECT idx FROM Locations;"
+    print(sql_statement)
+    cur.execute(sql_statement)
+    rows = cur.fetchall()
+    for row in rows:
+        print("Location: " + str(row[0]))
+        sql_statement = "SELECT Taxonomy, Number, Structural, Night FROM Assets WHERE Location = %d" % row[0]
+        cur.execute(sql_statement)
+        assets = cur.fetchall()
+        for asset in assets:
+            print("Asset: %s, %f, %f, %f" % (asset[0], asset[1], asset[2], asset[3]))
+        taxonomies = numpy.array(assets)[:, 0]
+        print(taxonomies)
+        a = numpy.asarray(assets)[:, 1:].astype(numpy.float)
+        print(a)
+        sum = a.sum(axis=0)
+        print(sum)
+        proportions = a/sum[None, :]
+        print(proportions)
+        proportions[numpy.isnan(proportions)] = 0
+        print(proportions)
+        # Select all buildings in the Voronoi cell
+        sql_statement = "SELECT idx FROM Buildings WHERE loc_id = %d" % row[0]
+        print(sql_statement)
+        cur.execute(sql_statement)
+        buildings = cur.fetchall()
+        for building_index in buildings:
+            # Write exposure data for the building
+            print(building_index[0])
+            for counter in range(taxonomies.shape[0]):
+                print(taxonomies[counter])
+                print(proportions[counter,:])
+
+                sql_statement = "INSERT INTO Exposure (building_id, taxonomy, number, structural, night) VALUES (%d, %s, %f, %f, %f)" % (building_index[0], taxonomies[counter], proportions[counter,0], proportions[counter,0], proportions[counter,0])
+                cur.execute(sql_statement)
+        conn.commit()
+
+
+
+
 def main():
-    conn = create_sara_database('../skr/testdb.sqlite')
-    # conn = start_sara_database('../skr/testdb.sqlite')
-    read_sara_exposure_into_database(conn, '../data/Exposure_Res_Chile.csv')
-    add_voronoi_cells(conn)
-    add_buildings(conn, '../data/obm.building.gpkg')
+    # conn = create_sara_database('../skr/testdb.sqlite')
+    conn = start_sara_database('../skr/testdb.sqlite')
+    # read_sara_exposure_into_database(conn, '../data/Exposure_Ind_Chile.csv')
+    # add_voronoi_cells(conn)
+    # add_buildings(conn, '../data/obm.building.small.gpkg')
+    classify_buildings(conn)
+
 
 
 main()