__init__.py 11 KB

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  1. #!/usr/bin/env python3
  2. # -*- coding: utf-8 -*-
  3. from common.BigDataCenterAPI import *
  4. from models import *
  5. from sqlalchemy import text
  6. from sqlalchemy import func
  7. from shapely.geometry import Polygon, MultiPolygon
  8. from shapely.ops import unary_union
  9. import json
  10. def convert_to_polygon(points):
  11. # 将点的列表转换为POLYGON格式的字符串
  12. polygon_str = "POLYGON(("
  13. for point in points:
  14. # 假设点的顺序是经度(x),纬度(y)
  15. polygon_str += f"{point['y']} {point['x']}, "
  16. # 移除最后一个逗号和空格,然后添加闭合点和结束括号
  17. polygon_str = polygon_str.rstrip(", ") + f", {points[0]['y']} {points[0]['x']}))"
  18. return polygon_str
  19. def get_town_list2(location_list:list,db):
  20. resutl = []
  21. for location in location_list:
  22. location = convert_to_polygon(location) #,geometry
  23. sql = text(f"""SELECT DISTINCT `name`,properties,pac FROM tp_geojson_data_zj WHERE ST_Intersects(geometry,ST_PolygonFromText( '{location}', 4326 ))""")
  24. # print(sql)
  25. resutl+=db.execute(sql).all()
  26. return resutl
  27. def get_village_list(location_list:list,db,pac=''):
  28. resutl = []
  29. for location in location_list:
  30. location = convert_to_polygon(location) #geometry,
  31. sql = text(f"""SELECT DISTINCT `name`,properties,pac,populationSize,GDP FROM (select * from tp_geojson_data_cj_sq {pac})A WHERE ST_Intersects(geometry,ST_PolygonFromText( '{location}', 4326 )) """)
  32. # print(sql)
  33. resutl+=db.execute(sql).all()
  34. return resutl
  35. def get_town_list(locations,):
  36. # 初始化一个空的MultiPolygon来容纳所有多边形
  37. multi_polygon = MultiPolygon()
  38. # 遍历每个位置,创建多边形并添加到multi_polygon中
  39. for location in locations:
  40. # 将边界列表转换为Polygon
  41. polygon = Polygon([(item['x'], item['y']) for item in location])
  42. multi_polygon = multi_polygon.union(polygon)
  43. # 将GeoJSON数据转换为字典
  44. with open('/home/python3/zj_geojson.json', 'r', encoding='utf-8') as file:
  45. geojson = json.load(file)
  46. # 假设GeoJSON数据是一个FeatureCollection
  47. features = geojson.get('features', [])
  48. # 初始化一个空列表来存储结果
  49. intersected_names_and_pacs = []
  50. # 遍历GeoJSON中的每个Feature,计算交集
  51. for feature in features:
  52. geom = feature['geometry']
  53. if 'coordinates' in geom:
  54. # 将GeoJSON Polygon转换为shapely Polygon
  55. if geom['type'] == 'Polygon':
  56. polygon = Polygon(geom['coordinates'][0])
  57. intersection = polygon.intersection(multi_polygon)
  58. elif geom['type'] == 'MultiPolygon':
  59. multi_polygon_feature = MultiPolygon([Polygon(coords[0]) for coords in geom['coordinates']])
  60. intersection = multi_polygon_feature.intersection(multi_polygon)
  61. else:
  62. continue # 跳过非Polygon和非MultiPolygon类型的几何对象
  63. if not intersection.is_empty:
  64. properties = feature['properties']
  65. intersected_names_and_pacs.append({
  66. "townName": properties.get('NAME', ''),
  67. "code": properties.get('PAC', ''),
  68. "populationSize": 0, # 假设值,需要从数据中获取
  69. "areaSize": round(intersection.area, 2), # 交集区域的面积
  70. "GDP": 0 # 假设值,需要从数据中获取
  71. })
  72. return intersected_names_and_pacs, len(intersected_names_and_pacs)
  73. def get_town_village_list(locations,db):
  74. # 初始化一个空的MultiPolygon来容纳所有多边形
  75. # multi_polygon = MultiPolygon()
  76. #
  77. # # 遍历每个位置,创建多边形并添加到multi_polygon中
  78. # for location in locations:
  79. # # 将边界列表转换为Polygon
  80. # polygon = Polygon([(item['x'], item['y']) for item in location])
  81. # multi_polygon = multi_polygon.union(polygon)
  82. # intersected_towns = db.query(TpZjGeoJSONData).filter(
  83. # func.ST_Intersects(TpZjGeoJSONData.geometry, multi_polygon) == True
  84. # ).all()
  85. intersected_towns = get_town_list2(locations,db)
  86. # 初始化一个空列表来存储结果
  87. intersected_names_and_pacs = []
  88. town_count = len(intersected_towns)
  89. village_count = 0
  90. for town in intersected_towns:
  91. # town_count+=1
  92. town_pac = town.pac
  93. properties = json.loads(town.properties)
  94. town_data = {
  95. "townName": town.name,
  96. "code": town.pac,
  97. "populationSize": 0, # 假设值,需要从数据中获取
  98. "areaSize": properties['GEO_AREA'], # 交集区域的面积
  99. "GDP": 0 # 假设值,需要从数据中获取
  100. }
  101. # intersected_villages = db.query(TpCjSqGeoJSONData).filter(
  102. # func.ST_Intersects(TpCjSqGeoJSONData.geometry, multi_polygon) == True
  103. # ).filter(TpCjSqGeoJSONData.pac.like(f'{town_pac}%')).all()
  104. intersected_villages = get_village_list(locations,db,pac=f""" where pac like '{town_pac}%'""")
  105. intersected_villages_names_and_pacs = []
  106. for village in intersected_villages:
  107. town_data['populationSize']+=village.populationSize
  108. town_data['GDP']+=village.GDP
  109. # properties = json.loads(village.properties)
  110. village_data = {
  111. "villageName": village.name,
  112. "code": village.pac,
  113. "populationSize": village.populationSize, # 假设值,需要从数据中获取
  114. "areaSize": properties['GEO_AREA'], # 交集区域的面积 0,#
  115. "GDP": village.GDP # 假设值,需要从数据中获取
  116. }
  117. intersected_villages_names_and_pacs.append(village_data)
  118. villageCount= len(intersected_villages_names_and_pacs)
  119. if villageCount>0:
  120. town_data['children']=intersected_villages_names_and_pacs
  121. town_data['villageCount'] =villageCount
  122. village_count += villageCount
  123. intersected_names_and_pacs.append(town_data)
  124. return intersected_names_and_pacs, town_count,village_count
  125. # import geopandas as gpd
  126. # from shapely.geometry import Polygon
  127. #
  128. #
  129. #
  130. # def get_town_list(locations):
  131. # # 读取GeoJSON文件为GeoDataFrame
  132. # gdf = gpd.read_file('zj_geojson.json')
  133. # gdf = gdf.set_crs("EPSG:4326", allow_override=True)
  134. #
  135. # # 初始化一个空的GeoDataFrame来容纳所有多边形
  136. # multi_polygon_gdf = gpd.GeoDataFrame(crs=gdf.crs)
  137. #
  138. # # 遍历每个位置,创建多边形并添加到multi_polygon_gdf中
  139. # for location in locations:
  140. # # 将边界列表转换为Polygon
  141. # polygon = Polygon([(item['x'], item['y']) for item in location])
  142. # # 将多边形添加到multi_polygon_gdf中
  143. # multi_polygon_gdf = multi_polygon_gdf.append(gpd.GeoDataFrame([1], geometry=[polygon], crs=gdf.crs))
  144. #
  145. # # 使用overlay函数来找出相交的区域
  146. # intersected = gpd.overlay(gdf, multi_polygon_gdf, how='intersection')
  147. #
  148. # # 获取相交区域的名称和PAC
  149. # intersected_names_and_pacs = [{"name": row['NAME'], "pac": row['PAC'],"populationSize":0,"areaSize":0,"GDP":0} for index, row in intersected.iterrows() if 'NAME' in row and 'PAC' in row]
  150. #
  151. # return intersected_names_and_pacs,len(intersected_names_and_pacs)
  152. def count_town_village(location_list:list,db):
  153. town_count = 0
  154. town_list = []
  155. village_count = 0
  156. village_list = []
  157. result = []
  158. url = 'https://19.15.75.180:8581/GatewayMsg/http/api/proxy/invoke'
  159. service_code= 'YZT1685418808667'
  160. service_info = db.query(OneShareApiEntity).filter(OneShareApiEntity.servercode == service_code).first()
  161. signTime = str(GetTime() // 1000)
  162. nonce = GetNonce(5)
  163. sign = GetSign(signTime, nonce, service_info.passtoken)
  164. headers = {
  165. # 'Content-Type': 'application/json',
  166. 'x-tif-signature': sign,
  167. 'x-tif-timestamp': signTime,
  168. 'x-tif-nonce': nonce,
  169. 'x-tif-paasid': service_info.passid,
  170. 'x-tif-serviceId': service_code
  171. }
  172. response = requests.post(url=url, headers=headers, json=location_list, verify=False)
  173. if response.status_code==200:
  174. data_list = response.json()['data']
  175. for data in data_list:
  176. township = data['townshipCode']
  177. if township not in town_list:
  178. town_count+=1
  179. town_list.append(township)
  180. # result.append({'township':data['township'],"townshipCode":data['townshipCode'],"villages":[]})
  181. result.append({'township':data['township'],"townshipCode":data['townshipCode'],"village":'-',"villageCode":'-',"populationSize":0,"areaSize":0,"GDP":0})
  182. village = data['villageCode']
  183. if village not in village_list:
  184. village_count+=1
  185. village_list.append(village)
  186. # for town in result:
  187. # if town['townshipCode']==data['townshipCode']:
  188. # town["villages"].append({'village': data['village'], "villageCode": data['villageCode']})
  189. result.append({'township':data['township'],"townshipCode":data['townshipCode'],'village': data['village'], "villageCode": data['villageCode'],"populationSize":0,"areaSize":0,"GDP":0})
  190. return result,town_count,village_count
  191. def count_emergency_expert(location_list:list,db):
  192. location = convert_to_polygon(location_list)
  193. sql = text(f"""SELECT * FROM emergency_expert WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', latitude, ' ', longitude, ')'), 4326))""")
  194. return len(db.execute(sql).all())
  195. def count_emergency_management(location_list: list, db):
  196. location = convert_to_polygon(location_list)
  197. sql = text(f"""SELECT DISTINCT management_unit FROM `rescue_materia` WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', latitude, ' ', longitude, ')'), 4326))""")
  198. return len(db.execute(sql).all())
  199. def get_hospital_list(location_list:list,db):
  200. resutl = []
  201. for location in location_list:
  202. location = convert_to_polygon(location)
  203. sql = text(f"""SELECT hospital_name as `name`,longitude,latitude,6 AS `dataType` FROM mid_hospital WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', latitude, ' ', longitude, ')'), 4326))""")
  204. resutl+=db.execute(sql).all()
  205. return resutl
  206. def get_emergency_shelter_list(location_list:list,db):
  207. resutl = []
  208. for location in location_list:
  209. location = convert_to_polygon(location)
  210. sql = text(f"""SELECT shelter_name as `name`,lng as longitude,lat as latitude,3 AS `dataType` FROM mid_emergency_shelter WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', lat, ' ', lng, ')'), 4326))""")
  211. resutl+=db.execute(sql).all()
  212. return resutl
  213. def get_waterlogged_roads_list(location_list:list,db):
  214. resutl = []
  215. for location in location_list:
  216. location = convert_to_polygon(location)
  217. sql = text(f"""SELECT flood_name as `name`,lng as longitude,lat as latitude,4 AS `dataType` FROM mid_waterlogged_roads WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', lat, ' ', lng, ')'), 4326))""")
  218. resutl+=db.execute(sql).all()
  219. return resutl