fix: some parts of new get_measurement data structure

app/lib/data_classes.dart

@@ -49,7 +49,7 @@ class SubDiv {
   double minThickness;
   double avgThickness;
   LatLng center;
-  double accuracy;
+  int accuracy;
   Color color;
   List<IceStats> iceStats;
 
@@ -69,12 +69,12 @@ class SubDiv {
       return SubDiv(
         sub_div_id: json['SubdivID'].toString(),
         groupID: json['GroupID'] ?? 0,
-        minThickness: json['MinThickness'] ?? 0,
-        avgThickness: json['AvgThickness'] ?? 0,
+        minThickness: json['MinThickness'].toDouble ?? 0,
+        avgThickness: json['AvgThickness'].toDouble ?? 0,
         center: json['CenLatitude'] != null && json['CenLongitude'] != null
             ? LatLng(json['CenLatitude'], json['CenLongitude'])
             : LatLng(0.0, 0.0),
-        accuracy: json['Accuracy'] ?? 0.0,
+        accuracy: json['Accuracy'] ?? 0,
         // Set grey as default color
         color: json['Color'] != null ? Color(json['Color']) : Colors.grey,
         iceStats: (json['IceStats'] as List<dynamic>?)

server/data_processing/process_lidar_data.py

@@ -29,6 +29,7 @@ def about_laz_file(path):
 
     return [las.header.version, las.header.point_count, las.header.scale, las.header.offset]
 
+
 def find_folder_files(direcory):
     files = []
     for root, _, fileNames in os.walk(direcory):
@@ -36,7 +37,7 @@ def find_folder_files(direcory):
             files.append(os.path.join(root, fileName))
     return files
 
-print(find_folder_files())
+
 
 # find the height of an area based on the coordinates of it's center
 # and it's affiliations (subId and groupId) (soon to be implemented
@@ -59,55 +60,57 @@ def calculate_area_data(center, body_of_water):
     # grid cell offset
     # NB: make these a global var
     grid_size = 4
-    #cell_x, cell_y = map_data['tile_width'], map_data['tile_height']
-    #cell_x, cell_y = (400*grid_size, 400*grid_size)
+    # cell_x, cell_y = map_data['tile_width'], map_data['tile_height']
+    # cell_x, cell_y = (400*grid_size, 400*grid_size)
     cell_x, cell_y = (2000, 1000)
 
     # convert the offset to meter
-    #cell_x = 111.320 * cell_x * 1000
-    #cell_y = (40075 * math.cos(cell_y) * 1000) / 360
+    # cell_x = 111.320 * cell_x * 1000
+    # cell_y = (40075 * math.cos(cell_y) * 1000) / 360
     cell_x = 111.320 * cell_x
-    cell_y = (111.320 * math.cos(60)*cell_y)
+    cell_y = (111.320 * math.cos(60) * cell_y)
 
     # set the limit of the area compared to local coordinates
     area_limit = calculate_corners(center[0], center[1], (cell_x, cell_y))
-    #area_limit = calculate_corners(sub_center[0], sub_center[1], (cell_x/4, cell_y/4))
+    # area_limit = calculate_corners(sub_center[0], sub_center[1], (cell_x/4, cell_y/4))
 
     # grid data
     map_data = map_data['features']
     map_zones = [area_limit[2], area_limit[0]]
-    map_data = list(filter(lambda point_position: inArea((point_position['properties']['sub_div_center'][0], point_position['properties']['sub_div_center'][1], 0.0), map_zones), map_data))
+    map_data = list(filter(lambda point_position: inArea(
+        (point_position['properties']['sub_div_center'][0], point_position['properties']['sub_div_center'][1], 0.0),
+        map_zones), map_data))
 
     # Refactor lidar data to a readable format
     iceOver = laspy.read(laz_data_paths[0])
     iceUnder = laspy.read(laz_data_paths[1])
 
     # add two files together temporary test data(soon to be removed)
-    ice_points = list(zip(iceOver.X,iceOver.Y,iceOver.Z)) + list(zip(iceUnder.X,iceUnder.Y,iceUnder.Z))
+    ice_points = list(zip(iceOver.X, iceOver.Y, iceOver.Z)) + list(zip(iceUnder.X, iceUnder.Y, iceUnder.Z))
     print(len(ice_points))
-    ice_points = list(filter(lambda point_position: inArea((point_position[0],point_position[1],0.0),[(-3300000, 4500000), (-3200000, 5000000)]), ice_points))
+    ice_points = list(filter(lambda point_position: inArea((point_position[0], point_position[1], 0.0),
+                                                           [(-3300000, 4500000), (-3200000, 5000000)]), ice_points))
     print(len(ice_points))
     # only for visualizating the testing data
-    #print("max",max(ice_points))
-    #print("min",min(ice_points))
+    # print("max",max(ice_points))
+    # print("min",min(ice_points))
 
-    #x = [points[0] for points in ice_points]
-    #y = [points[1] for points in ice_points]
+    # x = [points[0] for points in ice_points]
+    # y = [points[1] for points in ice_points]
 
     # Plot the points
-    #plt.plot(x, y, 'bo')  # 'bo' specifies blue color and circle markers
-    #plt.xlabel('X axis')
-    #plt.ylabel('Y axis')
-    #plt.title('Plotting Points')
-    #plt.grid(True)  # Add grid
-    #plt.show()
+    # plt.plot(x, y, 'bo')  # 'bo' specifies blue color and circle markers
+    # plt.xlabel('X axis')
+    # plt.ylabel('Y axis')
+    # plt.title('Plotting Points')
+    # plt.grid(True)  # Add grid
+    # plt.show()
 
     max_point = max(ice_points)
     min_point = min(ice_points)
 
-
     # define all the sub-areas within the area, local coordinates
-    grid_sub_area = define_gridareas(center[0], center[1], (cell_x, cell_y),grid_size)
+    grid_sub_area = define_gridareas(center[0], center[1], (cell_x, cell_y), grid_size)
     # define all the sub-areas within the area, lidar coordinates
     grid_area_lidar_heights = define_grid_lidardata((min_point, max_point), grid_size, ice_points)
 
@@ -122,23 +125,25 @@ def calculate_area_data(center, body_of_water):
             start = (sub_area[0][2])
             end = (sub_area[0][0])
 
-            #test data
+            # test data
             # zone coordinates sett to be relative to the lidar data's point cloud
-            #print("l1 = ", min_point, " l2 = ", max_point)
-            #print("p1 = ", start, " p2 = ", end)
-            #print("center_lim = ", center)
-            #print("max_lim = ", area_limit)
-            #areazone = position_relative_to_pointcloud(min_point, max_point, start, end, center, area_limit)
-            #print("area",areazone)
+            # print("l1 = ", min_point, " l2 = ", max_point)
+            # print("p1 = ", start, " p2 = ", end)
+            # print("center_lim = ", center)
+            # print("max_lim = ", area_limit)
+            # areazone = position_relative_to_pointcloud(min_point, max_point, start, end, center, area_limit)
+            # print("area",areazone)
             # calculate map zones height
             ys, xs = start
             ye, xe = end
-            sub_center = ((xs + xe)/2, (ys + ye)/2)
+            sub_center = ((xs + xe) / 2, (ys + ye) / 2)
             # check if area is part of water body
-            part_of_subarea_of_waterbody = list(filter(lambda pos: inArea((pos['properties']['sub_div_center'][0], pos['properties']['sub_div_center'][1], 0.0), [start,end]), map_data))
+            part_of_subarea_of_waterbody = list(filter(lambda pos: inArea(
+                (pos['properties']['sub_div_center'][0], pos['properties']['sub_div_center'][1], 0.0), [start, end]),
+                                                       map_data))
             print('sub_area: ', sub_area)
             print('part_of_subarea_of_waterbody: ', part_of_subarea_of_waterbody)
-            if(len(part_of_subarea_of_waterbody) > 0):
+            if (len(part_of_subarea_of_waterbody) > 0):
                 current_map_zone = closest_points(sub_center, part_of_subarea_of_waterbody, taken_coords)
                 sub_center = current_map_zone['properties']['sub_div_center']
                 taken_coords.append(sub_center)
@@ -150,16 +155,15 @@ def calculate_area_data(center, body_of_water):
             current_zone_id = current_map_zone['properties']['sub_div_id']
 
             # filter data within sub-area zones
-            #print(areazone[0][0]," < ",ice_points[0][0]," < ",areazone[1][0])
-            #print(areazone[0][1]," > ",ice_points[0][1]," > ",areazone[1][1])
-            #points_in_area = list(filter(lambda point_position: inArea(point_position, areazone), ice_points))
+            # print(areazone[0][0]," < ",ice_points[0][0]," < ",areazone[1][0])
+            # print(areazone[0][1]," > ",ice_points[0][1]," > ",areazone[1][1])
+            # points_in_area = list(filter(lambda point_position: inArea(point_position, areazone), ice_points))
 
             if current_map_zone is not None:
                 #                     sub_id        center         heights
                 area_heights.append((current_zone_id, sub_center, sub_area[1]))
         return area_heights
     else:
-        return [] # return [0] if no data collected from lidar
-
+        return []  # return [0] if no data collected from lidar
 
-#print(calculate_area_data((61, 11), 'mj\u00f8sa'))
+# print(calculate_area_data((61, 11), 'mj\u00f8sa'))

server/map_handler/get_measurements.py

@@ -32,20 +32,24 @@ def get_measurements(self, lake_name):
             # Iterate over all fetched rows
             for measurement in lidar_data:
                 processed_subdivs = []
-                # Create new measurement object
+
+                # Create new measurement object with embedded sensor object
                 new_measurement = {
                     'MeasurementID': measurement['MeasurementID'],
                     'TimeMeasured': str(datetime.now()),
                     'CenterLat': measurement['CenterLat'],
                     'CenterLon': measurement['CenterLon'],
-                    'Sensor': measurement['Sensor'],
-                    'Subdivisions': [],
+                    'Sensor': {
+                        'SensorID': measurement['Sensor']['SensorID'],
+                        'SensorType': measurement['Sensor']['SensorType'],
+                        'Active': measurement['Sensor']['Active'],
+                    },
+                    'Subdivisions': None,
                 }
                 for sub_division in measurement['Subdivisions']:
                     subdiv_id = sub_division['SubdivID']
                     center_lat = sub_division['CenLatitude']
                     center_lng = sub_division['CenLongitude']
-                    thicknesses = sub_division['Heights']
 
                     # Create new subdivision object
                     sub_division = {
@@ -68,7 +72,7 @@ def get_measurements(self, lake_name):
                     processed_subdivs.append(sub_division)
 
                 # Append processed measurement and subdivisions
-                new_measurement['Subdivisions'].append(processed_subdivs)
+                new_measurement['Subdivisions'] = processed_subdivs
                 measurements.append(new_measurement)
 
         # Populate remaining non-processed subdivisions and create "invalid" or "proxy" measurement to store them

server/map_handler/input_new_data.py

@@ -3,6 +3,7 @@ import os
 from datetime import datetime
 from server.data_processing.process_lidar_data import calculate_area_data, about_laz_file
 
+
 # input_new_Lidar_data send new data gathered from the lidar and send it to the database (from the drone, most likely)
 def input_new_Lidar_data(self, cursor, sensorId, bodyOfWater):
     """
@@ -14,7 +15,7 @@ def input_new_Lidar_data(self, cursor, sensorId, bodyOfWater):
     :return:
     """
     try:
-        print("name=",bodyOfWater)
+        print("name=", bodyOfWater)
         # hard coded coordinates
         latitude = 60.816848
         longitude = 10.723823
@@ -54,7 +55,7 @@ def input_new_Lidar_data(self, cursor, sensorId, bodyOfWater):
             }
         }
 
-        if(areas_data):
+        if (areas_data):
             # store lidar data in jason formate
             # calculate data for each zone within the area
             for area in areas_data:
@@ -63,8 +64,8 @@ def input_new_Lidar_data(self, cursor, sensorId, bodyOfWater):
                 map_lat, map_lng = area[1]
                 heights = area[2]
 
-                if(len(heights) != 0 or sum(heights) == 0):
-                    average = sum(heights)/len(heights)
+                if (len(heights) != 0 or sum(heights) == 0):
+                    average = sum(heights) / len(heights)
                     minimum_thickness = min(heights)
                 else:
                     average = 0
@@ -75,7 +76,9 @@ def input_new_Lidar_data(self, cursor, sensorId, bodyOfWater):
                 cursor.execute('''
                 INSERT INTO SubdivisionMeasurementData(MeasurementID, TimeMeasured, SubdivID, WaterBodyName, MinimumThickness, AverageThickness, CalculatedSafety, Accuracy) VALUES
                     (?,?,?,?,?,?,?,?);
-                ''', (measurement_id, time_measured, subId, bodyOfWater, float(minimum_thickness), float(average), float(0.0), scale_factor))
+                ''', (
+                measurement_id, time_measured, subId, bodyOfWater, float(minimum_thickness), float(average), float(0.0),
+                scale_factor))
                 sub_center = (map_lat, map_lng)
                 # set up json formate
                 lidar_read = {
@@ -105,7 +108,7 @@ def input_new_Lidar_data(self, cursor, sensorId, bodyOfWater):
         self.send_response(200)
         self.send_header('Content-type', "application/json")
         self.end_headers()
-        file_path = "./server/map_handler/lake_relations/"+bodyOfWater+"_lidar_data.json"
+        file_path = "./server/map_handler/lake_relations/" + bodyOfWater + "_lidar_data.json"
         content = None
 
         current_directory = os.getcwd()
@@ -123,7 +126,6 @@ def input_new_Lidar_data(self, cursor, sensorId, bodyOfWater):
             print('No data found, line 101')
             content = json.dumps([])
 
-
         # Write content data to response object
         self.wfile.write(content.encode('utf-8'))
 

server/map_handler/lake_relations/mjøsa_lidar_data.json

@@ -13,7 +13,7 @@
       {
         "SubdivID": 36,
         "MinThickness": -1.0,
-        "AvgThickness": 1,
+        "AvgThickness": 1.0,
         "CenLatitude": 60.841532,
         "CenLongitude": 10.717878,
         "Accuracy": 2
@@ -21,7 +21,7 @@
       {
         "SubdivID": 83,
         "MinThickness": -1.0,
-        "AvgThickness": 14,
+        "AvgThickness": 14.0,
         "CenLatitude": 60.828326,
         "CenLongitude": 10.982563,
         "Accuracy": 2
@@ -29,7 +29,7 @@
       {
         "SubdivID": 33,
         "MinThickness": -1.0,
-        "AvgThickness": 1,
+        "AvgThickness": 1.0,
         "CenLatitude": 60.771059,
         "CenLongitude": 10.698341,
         "Accuracy": 2
@@ -37,7 +37,7 @@
       {
         "SubdivID": 136,
         "MinThickness": -1.0,
-        "AvgThickness": 9,
+        "AvgThickness": 9.0,
         "CenLatitude": 60.396856,
         "CenLongitude": 11.220933,
         "Accuracy": 2