def getGridIntersection(self, fPoint, tPoint, fromGid, toGid, direction):
"""
计算交叉点，所有点格式均为 [lng, lat]
:param self:
:param fPoint: 来源�?
:param tPoint: 到达�?
:param fromGid: 来源 gid
:param toGid: 到达 gid
:param direction: 方向
"""
fGIPoint, tGIPoint = [], []
fromLat = float(fPoint[1])
fromLng = float(fPoint[0])
toLat = float(tPoint[1])
toLng = float(tPoint[0])
# 处理 from/to
toDirection = {
'n': 's',
's': 'n',
'w': 'e',
'e': 'w'
}
pfRes = parseFormatGID(fromGid, direction, self.LngSPLIT, self.LatSPLIT, self.locs)
ptRes = parseFormatGID(toGid, toDirection[direction], self.LngSPLIT, self.LatSPLIT, self.locs)
fGidLine = pfRes['dlinePoint']
tGidLine = ptRes['dlinePoint']
fLng = pfRes['lng']
fLat = pfRes['lat']
tLng = ptRes['lng']
tLat = ptRes['lat']
# 计算网格方边交点
if direction in ['n', 's']: # 与纬度线相交
k = (toLng - fromLng) / (toLat - fromLat)
b1, b2 = fLng, tLng
fIlng = b1 + (fGidLine - fromLat) * k
fGIPoint = [fIlng, fGidLine]
tIlng = b2 + (tGidLine - fromLat) * k
tGIPoint = [tIlng, tGidLine]
else: # 与经度线相交
k = (toLat - fromLat) / (toLng - fromLng)
b1, b2 = fLat, tLat
fIlat = b1 + (fGidLine - fromLng) * k
fGIPoint = [fGidLine, fIlat]
tIlat = b2 + (tGidLine - fromLng) * k
tGIPoint = [tGidLine,tIlat]
return fGIPoint, tGIPoint
def iterateResByDirection(self):
# 四个方向分别聚类
for x in xrange(0, self.typeNum):
currentDir = -1
for line in self.resByDir[x]:
linelist = line.split(',')
lng = float(linelist[0])
lat = float(linelist[1])
gid = int(linelist[2])
gdirStr = linelist[3]
speed = linelist[4]
direction = linelist[5]
gidInfo = parseFormatGID(gid, 'e', self.LngSPLIT,
self.LatSPLIT, self.locs)
gLat = gidInfo['lat']
gLng = gidInfo['lng']
if currentDir == -1:
currentDir = direction
self.dbInput[x].append([lng, lat])
subprops = "%s,%s,%s" % (gdirStr, speed, direction)
self.subInfo[x].append([gid, gLng, gLat, subprops])
print "Direction: %s - process completed. Total %d records." % (
currentDir, len(self.resByDir[x]))
def iterateRes(self):
cateKeys = {0: 'from', 1: 'to'}
for x in xrange(0, self.typeNum):
accumulator = 0
totalNum, noiseNum = 0, 0
for gid, tripsArray in self.resByAng[cateKeys[x]].iteritems():
tripsLen = len(tripsArray)
totalNum += tripsLen
tmpLngLat, tmpAngle, tmpSubInfo = [], [], []
for index in xrange(0, tripsLen):
linelist = tripsArray[index].split(',')
# lng = float(linelist[0])
# lat = float(linelist[1])
gid = int(linelist[2])
gdirStr = linelist[3]
speed = linelist[4]
direction = linelist[5]
angle = int(float(linelist[6]))
gidInfo = parseFormatGID(gid, 'e')
gLat = gidInfo['lat']
gLng = gidInfo['lng']
strength = float(linelist[7])
tmpLngLat.append(linelist[0] + ',' + linelist[1])
tmpAngle.append([angle, strength])
subprops = "%s,%s,%s" % (gdirStr, speed, direction)
tmpSubInfo.append("%d,%.6f,%.6f,%s" %
(gid, gLng, gLat, subprops))
# DBScan result
dbres = self.lineCLusterCalculation(tmpAngle)
if not dbres:
continue
noiseNum += dbres['noiseNum']
self.dbLabel[x] += dbres['labels']
self.dbInput[x] += tmpLngLat
self.subInfo[x] += tmpSubInfo
accumulator += 1
noiseRate = float(noiseNum) / totalNum
print '''
=== Angle Cluster Info ===
Number of dbscan clusters in all: %d
Grid ID number: %d
Records(total): %d
Noise Rate: %f
=== Angle Cluster Info ===
''' % (self.dbscanBaseNum, accumulator, totalNum, noiseRate)
return noiseRate
def iterateResByCategory(self):
# 暂时只拿 from 的数据进行聚类，所以所有结果存在 index=0 的元素中
# noiseRate 只会返回最后一个计算的结果，如果 from/to 均计算过，只有一个结果被保留
noiseRate = 0
cateKeys = {0: 'from', 1: 'to'}
for x in xrange(0, self.typeNum):
accumulator = 0
totalNum, noiseNum = 0, 0
for gid, tripsArray in self.resByCate[cateKeys[x]].iteritems():
tripsLen = len(tripsArray)
totalNum += tripsLen
tmpInput, tmpSubInfo = [], []
for index in xrange(0, tripsLen):
linelist = tripsArray[index].split(',')
lng = float(linelist[0])
lat = float(linelist[1])
gid = int(linelist[2])
gdirStr = linelist[3]
speed = linelist[4]
direction = linelist[5]
gidInfo = parseFormatGID(gid, 'e', self.LngSPLIT,
self.LatSPLIT, self.locs)
gLat = gidInfo['lat']
gLng = gidInfo['lng']
tmpInput.append([lng, lat])
subprops = "%s,%s,%s" % (gdirStr, speed, direction)
tmpSubInfo.append([gid, gLng, gLat, subprops])
self.dbInput[x] += tmpInput
self.subInfo[x] += tmpSubInfo
# DBScan result
dbres = self.dbscanCalByCategory(tmpInput)
noiseNum += dbres['noiseNum']
self.dbLabel[x] += dbres['labels']
accumulator += 1
noiseRate = float(noiseNum) / totalNum
print '''
=== DBScan Info ===
Number of dbscan clusters in all: %d
Grid ID number: %d
Records(total): %d
Noise Rate: %f
=== DBScan Info ===
''' % (self.dbscanBaseNum, accumulator, totalNum, noiseRate)
return noiseRate
def iterateResWithoutFromTo(self):
cateKeys = {0: 'from', 1: 'to'}
self.resByAng['all'] = {}
# merge from and to
if 'from' in self.resByAng.keys():
for gid, tripsArray in self.resByAng['from'].iteritems():
self.resByAng['all'][gid] = tripsArray
if 'to' in self.resByAng.keys():
for gid, tripsArray in self.resByAng['to'].iteritems():
if self.resByAng['all'].has_key(gid):
self.resByAng['all'][gid].extend(tripsArray)
else:
self.resByAng['all'][gid] = tripsArray
accumulator, clusterNum = 0, 0
totalNum, noiseNum = 0, 0
for gid, tripsArray in self.resByAng['all'].iteritems():
tripsLen = len(tripsArray)
totalNum += tripsLen
tmpLngLat, tmpSubInfo, tmpLngLatAngle, labels = [], [], [], []
mapLngLatAngle = {}
for index in xrange(0, tripsLen):
linelist = tripsArray[index].split(',')
startLng = float(linelist[0])
startLat = float(linelist[1])
gid = int(linelist[2])
gdirStr = linelist[3]
speed = linelist[4]
direction = linelist[5]
angle = float(linelist[6])
gidInfo = parseFormatGID(gid, 'e', self.LngSPLIT, self.LatSPLIT, self.locs)
gLat = gidInfo['lat']
gLng = gidInfo['lng']
tmpLngLat.append("%.6f,%.6f" % (startLng, startLat))
subprops = "%s,%s,%s,%.1f" % (gdirStr, speed, direction, angle)
tmpSubInfo.append("%d,%.6f,%.6f,%s" % (gid, gLng, gLat, subprops))
clusterKey = "%.6f,%.6f,%.1f" % (startLng, startLat, angle)
tmpLngLatAngle.append(clusterKey)
if clusterKey in mapLngLatAngle.keys():
mapLngLatAngle[clusterKey] = mapLngLatAngle[clusterKey] + 1
else:
mapLngLatAngle[clusterKey] = 1
# Aggregation by tmpLngLatAngle
clusterIndex = 0
clusterMap = {}
for clusterKey in mapLngLatAngle.keys():
if mapLngLatAngle[clusterKey] >= self.min_samples:
clusterMap[clusterKey] = clusterIndex
clusterIndex = clusterIndex + 1
clusterNum = clusterNum + 1
else:
clusterMap[clusterKey] = -1
noiseNum += mapLngLatAngle[clusterKey]
for index in xrange(0, tripsLen):
labels.append(clusterMap[tmpLngLatAngle[index]])
self.dbLabel[0] += labels
self.dbInput[0] += tmpLngLat
self.subInfo[0] += tmpSubInfo
accumulator += 1
noiseRate = float(noiseNum) / totalNum
print '''
=== Angle Cluster Info ===
Number of clusters in total: %d
Grid ID number: %d
Records(total): %d
Noise Rate: %f
=== Angle Cluster Info ===
''' % (clusterNum, accumulator, totalNum, noiseRate)
return noiseRate
lng = linelist[4]
gid = getFormatGID([lng, lat])['gid']
devId = int(linelist[1])
if devIdDict.has_key(gid):
if devId not in devIdDict[gid]:
devIdDict[gid].append(devId)
res[gid] += 1
else:
devIdDict[gid] = [devId]
res[gid] += 1
#res[gid] += 1
f.close()
# 写入文件
preline=[[] for j in xrange(len(res))];
ofile = os.path.join(OUTPUT_PATH, ofilename)
with open(ofile, 'wb') as output:
for index in xrange(len(res)):
dirDict = parseFormatGID(index);
preline[index].append(int(index));
preline[index].append(float(dirDict['lng']));
preline[index].append(float(dirDict['lat']));
preline[index].append(int(res[index]));
output.write(str(index)+","+str(dirDict['lng'])+","+str(dirDict['lat'])+","+str(res[index])+"\n");
output.close()
ojsonFile = os.path.join(OUTPUT_PATH, ofilename+".json")
with open(ojsonFile, 'wb') as foutput:
foutput.write(json.dumps(preline));
foutput.close()
def getNextGIDs(self, point, direction):
"""
获取方向后续的前 N 个交点
:param self:
:param point: [lng, lat, gid]
:param direction:
"""
res = []
[x, y] = direction
fromLat = point[1]
fromLng = point[0]
fromGID = point[2]
parsedObj = parseFormatGID(fromGID)
baseLatCenter = parsedObj['lat']
baseLngCenter = parsedObj['lng']
latDir = 1 if y > 0 else -1
lngDir = 1 if x > 0 else -1
# 存储所有交点数据
jumpPoints = []
# 计算网格方边交点
if y != 0: # 与平行纬度线相交
k = x / y
for i in xrange(0, self.custom_params['jump_length']):
incrementLat = baseLatCenter + self.custom_params[
'LatSPLIT'] * (0.5 + i) * latDir - fromLat
iLng = fromLng + incrementLat * k
iLat = incrementLat + fromLat
# key = '0,%d' % (i)
jumpPoints.append([iLng, iLat, 0, i])
if x != 0: # 与平行经度线相交
k = y / x
for i in xrange(0, self.custom_params['jump_length']):
incrementLng = baseLngCenter + self.custom_params[
'LngSPLIT'] * (0.5 + i) * lngDir - fromLng
iLat = fromLat + incrementLng * k
iLng = incrementLng + fromLng
# key = '%d,0' % (i)
jumpPoints.append([iLng, iLat, i, 0])
if x != 0 and y != 0:
# 根据纬度从小到大排前三
for i in xrange(self.custom_params['jump_length'],
self.custom_params['jump_length'] * 2):
currentIndex = -1
currentMax = jumpPoints[i][0]
for jumpIndex in xrange(0, self.custom_params['jump_length']):
if (jumpPoints[jumpIndex][0] * lngDir) > (currentMax *
lngDir):
currentIndex = jumpIndex
currentMax = jumpPoints[jumpIndex][0]
if currentIndex != -1:
jumpPoints[currentIndex] = jumpPoints[i][:]
# 确定该方向离圆心最小的交点
minLng = jumpPoints[0][0]
minLat = jumpPoints[0][1]
originGid = 0
if x != 0 and y != 0:
for i in xrange(1, self.custom_params['jump_length']):
if minLng * lngDir > jumpPoints[i][0] * lngDir:
minLng = jumpPoints[i][0]
minLat = jumpPoints[i][1]
# 只取三个交点
updateOriginGid = False
for i in xrange(0, self.custom_params['jump_length']):
ilng = jumpPoints[i][0]
ilat = jumpPoints[i][1]
# if ilng == minLng and ilat == minLat:
# updateOriginGid = True
if jumpPoints[i][2] == 0:
ilat += 0.002 * latDir # 0.002 为一小点偏量，使交点在对应网格内而不至于只卡在边界上
else:
ilng += 0.002 * lngDir
point = getFormatGID([ilng, ilat])
gid = point['gid']
# if updateOriginGid:
# updateOriginGid = False
# originGid = gid
res.append([ilng, ilat, gid])
return {
'res': res,
'endPoints': [minLng, minLat]
# 'originGid': originGid
}
