def queryClusterPointInfo():
"""
根据聚类点id查询聚类点信息：id、客户名称、人数、站点名称、经纬度
"""
res = ResMsg()
try:
logger.info("begin queryClusterPointInfo!")
aiBusModel = AiBusModel()
userInfo = session.get("userInfo")
data = request.get_json()
clusterId = data["id"]
clusterPoint = aiBusModel.selectClusterPointById(clusterId)
siteIdList = clusterPoint["siteSet"].split(",")
siteInfo = aiBusModel.selectClientNameByIds(siteIdList)
res.update(code=ResponseCode.Success, data=siteInfo)
return res.data
except Exception as e:
logger.error("queryClusterPointInfo exception:{}".format(str(e)))
res.update(code=ResponseCode.Fail, msg="查询聚类点信息报错！")
return res.data
def queryClusterResult():
res = ResMsg()
try:
logger.info("begin queryClusterResult!")
aiBusModel = AiBusModel()
userInfo = session.get("userInfo")
data = request.get_json()
fileId = data["fileId"]
clusterOutPoints = []
clusterCorePoints = []
clusterAroundPoints = []
#1)先查询聚类参数
clusterParams = aiBusModel.selectClusterParams((fileId))
if not clusterParams:
clusterParams = aiBusModel.selectClusterParamsBySiteFileId(
(fileId))
if not clusterParams:
res.update(code=ResponseCode.Success)
return res.data
fileId = clusterParams["id"]
#2)查询聚类结果
clusterResut = aiBusModel.selectClusterResult((1, fileId))
for item in clusterResut:
if item["relativeProperty"] == 1:
siteProperty = "固定"
elif item["relativeProperty"] == 0:
siteProperty = "临时"
else:
siteProperty = "自定义"
#根据site id查询网点信息
clientNames = []
users = []
if item["siteSet"] != '':
users = item["siteSet"].split(",")
siteInfo = aiBusModel.selectClientNameByIds(users)
for site in siteInfo:
clientNames.append(site["clientName"])
row={"id":item["id"],"siteName":item["clusterName"],"siteProperty":siteProperty,\
"longitude":item["longitude"],"latitude":item["latitude"],"number":item["number"],\
"users":users,"userNames":clientNames}
if item["clusterProperty"] == 1:
clusterCorePoints.append(row)
elif item["clusterProperty"] == 2:
clusterAroundPoints.append(row)
else:
clusterOutPoints.append(row)
res.update(code=ResponseCode.Success,
data={
"epsRadius": clusterParams["clusterRadius"],
"minSamples": clusterParams["clusterMinSamples"],
"clusterCorePoints": clusterCorePoints,
"clusterAroundPoints": clusterAroundPoints,
"clusterOutPoints": clusterOutPoints
})
return res.data
except Exception as e:
logger.error("generateClusterPoints exception:{}".format(str(e)))
res.update(code=ResponseCode.Fail, msg="查询聚类结果报错！")
return res.data
def generateClusterPoints():
"""
根据网点文件id生成聚类点
"""
res = ResMsg()
try:
logger.info("begin generateClusterPoints!")
aiBusModel = AiBusModel()
userInfo = session.get("userInfo")
data = request.get_json()
fileId = data["fileId"]
epsRadius = float(data["epsRadius"])
minSamples = data["minSamples"]
#先判断网点文件是否有效
fileProperty = aiBusModel.selectSiteFileStatus(fileId)
if fileProperty["fileStatus"] == 0:
res.update(code=ResponseCode.Fail, msg="该文件已经失效!")
return res.data
#根据网点文件查询网点list
#先判断是该文件是聚类文件还是网点文件
if fileProperty["clusterStatus"] == 1:
siteFileId = fileProperty["siteFileId"]
else:
siteFileId = fileId
#对网点文件的临时聚类结果进行失效
aiBusModel.updateClusterResultByFileId(
(0, userInfo["userName"], fileId), [2])
siteGeoList = aiBusModel.selectSiteGeoListByFileId(siteFileId)
if not siteGeoList:
res.update(code=ResponseCode.Fail, msg="网点为空！")
return res.data
#{"noiseList":[ids],"aroundList":[ids],"clusterDict":{"id":[ids],"id":[ids]}}
clusterInfo = clusterByAdaptiveDbscan(siteGeoList, epsRadius,
minSamples)
#将聚类结果保存至表中
insertVals = []
siteGeoDict = {}
for site in siteGeoList:
siteGeoDict[str(site["id"])] = site
clusterOutPoints = []
clusterCorePoints = []
clusterAroundPoints = []
#1)处理异常点fileId,siteId,clusterName,clusterProperty,clusterStatus,longitude,latitude,number,siteSet
for id in clusterInfo["noiseList"]:
relativeId = "site_" + str(id)
site = siteGeoDict[str(id)]
insertVals.append(
(fileId, relativeId, site["siteName"], site["siteProperty"], 0,
2, site["lng"], site["lat"], site["number"], str(id),
userInfo["userName"], userInfo["userName"]))
#clusterOutPoints.append({"id":relativeId,"siteName":site["siteName"],"siteProperty":site["siteProperty"],"number":site["number"],"longitude":site["lng"],"latitude":site["lat"]})
#2)处理聚类点
for key in clusterInfo["clusterDict"].keys():
clusterSet = clusterInfo["clusterDict"][key]
#处理聚类核心点
clusterNumber = 0
site = siteGeoDict[str(key)]
for id in clusterSet:
sitePoint = siteGeoDict[str(id)]
clusterNumber += int(sitePoint["number"])
clusterIdStr = ",".join(map(str, clusterSet))
insertVals.append((fileId, "site_" + str(key), site["siteName"],
site["siteProperty"], 1, 2, site["lng"],
site["lat"], clusterNumber, clusterIdStr,
userInfo["userName"], userInfo["userName"]))
#处理边界点
for id in clusterInfo["aroundList"]:
relativeId = "site_" + str(id)
aroundSite = siteGeoDict[str(id)]
insertVals.append(
(fileId, relativeId, aroundSite["siteName"],
aroundSite["siteProperty"], 2, 2,
aroundSite["lng"], aroundSite["lat"], aroundSite["number"],
str(id), userInfo["userName"], userInfo["userName"]))
#3)插入聚类点并返回
aiBusModel.batchClusterSites(insertVals)
#4)返回聚类结果
clusterResut = aiBusModel.selectClusterResult((2, fileId))
for item in clusterResut:
if item["relativeProperty"] == 1:
siteProperty = "固定"
elif item["relativeProperty"] == 0:
siteProperty = "临时"
else:
siteProperty = "自定义"
#根据site id查询网点信息
siteInfo = aiBusModel.selectClientNameByIds(
item["siteSet"].split(","))
clientNames = []
for site in siteInfo:
clientNames.append(site["clientName"])
row={"id":item["id"],"siteName":item["clusterName"],"siteProperty":siteProperty,\
"longitude":item["longitude"],"latitude":item["latitude"],"number":item["number"],\
"users":item["siteSet"].split(","),"userNames":clientNames}
if item["clusterProperty"] == 1:
clusterCorePoints.append(row)
elif item["clusterProperty"] == 2:
clusterAroundPoints.append(row)
else:
clusterOutPoints.append(row)
res.update(code=ResponseCode.Success,
data={
"clusterCorePoints": clusterCorePoints,
"clusterAroundPoints": clusterAroundPoints,
"clusterOutPoints": clusterOutPoints
})
return res.data
except Exception as e:
logger.error("generateClusterPoints exception:{}".format(str(e)))
res.update(code=ResponseCode.Fail, msg=str(e))
return res.data