__init__.py 13 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. if len(location_list) ==0:
  22. return []
  23. query = []
  24. for location in location_list:
  25. location = convert_to_polygon(location) #,geometry
  26. query.append(f"ST_Intersects(geometry,ST_PolygonFromText( '{location}', 4326 ))")
  27. query=' or '.join(query)
  28. sql = text(f"""SELECT DISTINCT `name`,properties,pac FROM tp_geojson_data_zj WHERE {query}""")
  29. # print(sql)
  30. resutl=db.execute(sql).all()
  31. return resutl
  32. def get_village_list(location_list:list,db,pac=''):
  33. if len(location_list) ==0:
  34. return []
  35. resutl = []
  36. query = []
  37. for location in location_list:
  38. location = convert_to_polygon(location) #geometry,
  39. query.append(f"ST_Intersects(geometry,ST_PolygonFromText( '{location}', 4326 ))")
  40. query=' or '.join(query)
  41. sql = text(f"""SELECT DISTINCT `name`,properties,pac,populationSize,GDP FROM (select * from tp_geojson_data_cj_sq {pac})A WHERE {query} """)
  42. # print(sql)
  43. resutl=db.execute(sql).all()
  44. return resutl
  45. def get_town_list(locations,):
  46. # 初始化一个空的MultiPolygon来容纳所有多边形
  47. multi_polygon = MultiPolygon()
  48. # 遍历每个位置,创建多边形并添加到multi_polygon中
  49. for location in locations:
  50. # 将边界列表转换为Polygon
  51. polygon = Polygon([(item['x'], item['y']) for item in location])
  52. multi_polygon = multi_polygon.union(polygon)
  53. # 将GeoJSON数据转换为字典
  54. with open('/home/python3/zj_geojson.json', 'r', encoding='utf-8') as file:
  55. geojson = json.load(file)
  56. # 假设GeoJSON数据是一个FeatureCollection
  57. features = geojson.get('features', [])
  58. # 初始化一个空列表来存储结果
  59. intersected_names_and_pacs = []
  60. # 遍历GeoJSON中的每个Feature,计算交集
  61. for feature in features:
  62. geom = feature['geometry']
  63. if 'coordinates' in geom:
  64. # 将GeoJSON Polygon转换为shapely Polygon
  65. if geom['type'] == 'Polygon':
  66. polygon = Polygon(geom['coordinates'][0])
  67. intersection = polygon.intersection(multi_polygon)
  68. elif geom['type'] == 'MultiPolygon':
  69. multi_polygon_feature = MultiPolygon([Polygon(coords[0]) for coords in geom['coordinates']])
  70. intersection = multi_polygon_feature.intersection(multi_polygon)
  71. else:
  72. continue # 跳过非Polygon和非MultiPolygon类型的几何对象
  73. if not intersection.is_empty:
  74. properties = feature['properties']
  75. intersected_names_and_pacs.append({
  76. "townName": properties.get('NAME', ''),
  77. "code": properties.get('PAC', ''),
  78. "populationSize": 0, # 假设值,需要从数据中获取
  79. "areaSize": round(intersection.area, 2), # 交集区域的面积
  80. "GDP": 0 # 假设值,需要从数据中获取
  81. })
  82. return intersected_names_and_pacs, len(intersected_names_and_pacs)
  83. def get_bqw_yj_quyu_data(area_code,db):
  84. sql = text(
  85. """SELECT ifnull(populationSize,0) as populationSize,
  86. ifnull(populationSize_unit,'') as populationSize_unit,
  87. ifnull(areaSize,0) as areaSize,
  88. ifnull(areaSize_unit,'')as areaSize_unit,ifnull(GDP,0) as GDP,ifnull(GDP_unit,'') as GDP_unit FROM sharedb.`bqw_yj_quyu_data` where `area_code`like :code order by area_code,year desc """).bindparams(
  89. code=f'%{area_code}%')
  90. # 执行查询
  91. result = db.execute(sql).fetchone()
  92. # 处理结果
  93. if result:
  94. return dict(result)
  95. else:
  96. return {"populationSize":0,"populationSize_unit":"","areaSize":0,"areaSize_unit":"","GDP":0,"GDP_unit":""}
  97. def get_town_village_list(locations,db):
  98. # 初始化一个空的MultiPolygon来容纳所有多边形
  99. intersected_towns = get_town_list2(locations,db)
  100. # 初始化一个空列表来存储结果
  101. intersected_names_and_pacs = []
  102. town_count = len(intersected_towns)
  103. village_count = 0
  104. populationSize = 0
  105. areaSize = 0
  106. GDP = 0
  107. for town in intersected_towns:
  108. # town_count+=1
  109. town_pac = town.pac
  110. properties = json.loads(town.properties)
  111. quyu_data = get_bqw_yj_quyu_data(town.pac,db)
  112. town_data = {
  113. "townName": town.name,
  114. "code": town.pac,
  115. "populationSize": f"{quyu_data['populationSize']}{quyu_data['populationSize_unit']}",
  116. "areaSize": f"{quyu_data['areaSize']}{quyu_data['areaSize_unit']}",
  117. "GDP": f"{quyu_data['GDP']}{quyu_data['GDP_unit']}" # 假设值,需要从数据中获取
  118. }
  119. populationSize += quyu_data['populationSize']
  120. areaSize += quyu_data['areaSize']
  121. GDP += quyu_data['GDP']
  122. # intersected_villages = db.query(TpCjSqGeoJSONData).filter(
  123. # func.ST_Intersects(TpCjSqGeoJSONData.geometry, multi_polygon) == True
  124. # ).filter(TpCjSqGeoJSONData.pac.like(f'{town_pac}%')).all()
  125. intersected_villages = get_village_list(locations,db,pac=f""" where pac like '{town_pac}%'""")
  126. intersected_villages_names_and_pacs = []
  127. for village in intersected_villages:
  128. quyu_data = get_bqw_yj_quyu_data(village.pac, db)
  129. # town_data['populationSize']+=village.populationSize
  130. # town_data['GDP']+=village.GDP
  131. # properties = json.loads(village.properties)
  132. village_data = {
  133. "villageName": village.name,
  134. "code": village.pac,
  135. "populationSize": f"{quyu_data['populationSize']}{quyu_data['populationSize_unit']}",#village.populationSize, # 假设值,需要从数据中获取
  136. "areaSize": f"{quyu_data['areaSize']}{quyu_data['areaSize_unit']}",#properties['GEO_AREA'], # 交集区域的面积 0,#
  137. "GDP": f"{quyu_data['GDP']}{quyu_data['GDP_unit']}"#village.GDP # 假设值,需要从数据中获取
  138. }
  139. intersected_villages_names_and_pacs.append(village_data)
  140. villageCount= len(intersected_villages_names_and_pacs)
  141. if villageCount>0:
  142. town_data['children']=intersected_villages_names_and_pacs
  143. town_data['villageCount'] =villageCount
  144. village_count += villageCount
  145. intersected_names_and_pacs.append(town_data)
  146. return intersected_names_and_pacs, town_count,village_count,populationSize,areaSize,GDP
  147. # import geopandas as gpd
  148. # from shapely.geometry import Polygon
  149. #
  150. #
  151. #
  152. # def get_town_list(locations):
  153. # # 读取GeoJSON文件为GeoDataFrame
  154. # gdf = gpd.read_file('zj_geojson.json')
  155. # gdf = gdf.set_crs("EPSG:4326", allow_override=True)
  156. #
  157. # # 初始化一个空的GeoDataFrame来容纳所有多边形
  158. # multi_polygon_gdf = gpd.GeoDataFrame(crs=gdf.crs)
  159. #
  160. # # 遍历每个位置,创建多边形并添加到multi_polygon_gdf中
  161. # for location in locations:
  162. # # 将边界列表转换为Polygon
  163. # polygon = Polygon([(item['x'], item['y']) for item in location])
  164. # # 将多边形添加到multi_polygon_gdf中
  165. # multi_polygon_gdf = multi_polygon_gdf.append(gpd.GeoDataFrame([1], geometry=[polygon], crs=gdf.crs))
  166. #
  167. # # 使用overlay函数来找出相交的区域
  168. # intersected = gpd.overlay(gdf, multi_polygon_gdf, how='intersection')
  169. #
  170. # # 获取相交区域的名称和PAC
  171. # 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]
  172. #
  173. # return intersected_names_and_pacs,len(intersected_names_and_pacs)
  174. def count_town_village(location_list:list,db):
  175. town_count = 0
  176. town_list = []
  177. village_count = 0
  178. village_list = []
  179. result = []
  180. url = 'https://19.15.75.180:8581/GatewayMsg/http/api/proxy/invoke'
  181. service_code= 'YZT1685418808667'
  182. service_info = db.query(OneShareApiEntity).filter(OneShareApiEntity.servercode == service_code).first()
  183. signTime = str(GetTime() // 1000)
  184. nonce = GetNonce(5)
  185. sign = GetSign(signTime, nonce, service_info.passtoken)
  186. headers = {
  187. # 'Content-Type': 'application/json',
  188. 'x-tif-signature': sign,
  189. 'x-tif-timestamp': signTime,
  190. 'x-tif-nonce': nonce,
  191. 'x-tif-paasid': service_info.passid,
  192. 'x-tif-serviceId': service_code
  193. }
  194. response = requests.post(url=url, headers=headers, json=location_list, verify=False)
  195. if response.status_code==200:
  196. data_list = response.json()['data']
  197. for data in data_list:
  198. township = data['townshipCode']
  199. if township not in town_list:
  200. town_count+=1
  201. town_list.append(township)
  202. # result.append({'township':data['township'],"townshipCode":data['townshipCode'],"villages":[]})
  203. result.append({'township':data['township'],"townshipCode":data['townshipCode'],"village":'-',"villageCode":'-',"populationSize":0,"areaSize":0,"GDP":0})
  204. village = data['villageCode']
  205. if village not in village_list:
  206. village_count+=1
  207. village_list.append(village)
  208. # for town in result:
  209. # if town['townshipCode']==data['townshipCode']:
  210. # town["villages"].append({'village': data['village'], "villageCode": data['villageCode']})
  211. result.append({'township':data['township'],"townshipCode":data['townshipCode'],'village': data['village'], "villageCode": data['villageCode'],"populationSize":0,"areaSize":0,"GDP":0})
  212. return result,town_count,village_count
  213. def count_emergency_expert(location_list:list,db):
  214. location = convert_to_polygon(location_list)
  215. sql = text(f"""SELECT * FROM emergency_expert WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', latitude, ' ', longitude, ')'), 4326))""")
  216. return len(db.execute(sql).all())
  217. def count_emergency_management(location_list: list, db):
  218. location = convert_to_polygon(location_list)
  219. sql = text(f"""SELECT DISTINCT management_unit FROM `rescue_materia` WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', latitude, ' ', longitude, ')'), 4326))""")
  220. return len(db.execute(sql).all())
  221. def get_hospital_list(location_list:list,db):
  222. resutl = []
  223. for location in location_list:
  224. location = convert_to_polygon(location)
  225. 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))""")
  226. resutl+=db.execute(sql).all()
  227. return resutl
  228. def get_emergency_shelter_list(location_list:list,db):
  229. resutl = []
  230. for location in location_list:
  231. location = convert_to_polygon(location)
  232. 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))""")
  233. resutl+=db.execute(sql).all()
  234. return resutl
  235. def get_waterlogged_roads_list(location_list:list,db):
  236. resutl = []
  237. for location in location_list:
  238. location = convert_to_polygon(location)
  239. 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))""")
  240. resutl+=db.execute(sql).all()
  241. return resutl
  242. def get_point_list(location_list:list,db):
  243. resutl = []
  244. for location in location_list:
  245. location = convert_to_polygon(location)
  246. sql = text(f"""SELECT `id` ,`name`, longitude, latitude, `dataType` FROM point_data WHERE ST_Contains(ST_PolygonFromText( '{location}', 4326 ),ST_PointFromText(CONCAT('POINT(', latitude, ' ', longitude, ')'), 4326))""")
  247. resutl+=db.execute(sql).all()
  248. return resutl