# -*- coding: utf-8 -*-
__author__ = 'lenovo'
from util.tripFlow.base import getFormatGID
from util.tripFlow.base import getDirection
from util.tripFlow.extractGridEdges import ExtractGridEdges
tPoint = [161.12, 40.35]
fPoint = [161.57, 39.79]
PROP = {
'index': 9,
'delta': -1,
'IDIRECTORY': '/datahouse',
'ODIRECTORY': '/datahouse',
'suffix': 1
}
task = ExtractGridEdges(PROP)
direction = getDirection(fPoint, tPoint)
fromGid = getFormatGID(fPoint)['gid']
toGid = getFormatGID(tPoint)['gid']
print(direction)
speed = 2.3
task.updateResByLine(fPoint, tPoint, fromGid, toGid, direction, speed)
print(task.resByCate['from'])
print(task.resByCate['to'])
#证明from和to的方向是一样的
def processTask(x, eps, K, delta, stdindir, stdoutdir):
subfix = "%.2f" % (delta)
PROP = {
'index': x,
'delta': delta,
'IDIRECTORY': stdindir,
'ODIRECTORY': stdoutdir,
'subfix': subfix
}
task = ExtractGridEdges(PROP)
res = task.run()
count = res['count']
min_samples = int(count / K) if count > K else 1
resByDir = res['res']['resByDir']
resByCate = res['res']['resByCate']
dataType = 'angle' # 确定是按照方向聚类还是角度聚�?direction, category
EPS_INTERVAL = 0.001 if dataType == 'direction' else 0.4
clusterofilename = ''
iterationTimes = 0
while (True):
if (iterationTimes == 50):
eps -= EPS_INTERVAL*50
min_samples -= 5
iterationTimes = 0
clusterPROP = {
'index': x,
'ODIRECTORY': stdoutdir,
'resByDir': resByDir,
'resByCate': resByCate,
'resByAng': resByCate,
'dataType': dataType,
'eps': eps,
'min_samples': min_samples,
'subfix': subfix
}
print '''
=== Cluster Parameters ===
index = %d
stdindir = %s
stdoutdir = %s
eps = %f
min_samples = %d
=== Cluster Parameters ===
''' % (x, stdindir, stdoutdir, eps, min_samples)
# 角度聚类单独处理
if dataType == 'angle':
clusterTask = LineTFIntersections(clusterPROP)
noiseRate, clusterofilename = clusterTask.run()
break
clusterTask = DBScanTFIntersections(clusterPROP)
noiseRate, clusterofilename = clusterTask.run()
if noiseRate <= 0.5:
break
else:
eps += EPS_INTERVAL
iterationTimes += 1
mergePROP = {
'index': x,
'IDIRECTORY': stdindir,
'ODIRECTORY': stdoutdir,
'dataType': dataType,
'subfix': subfix
}
mergeTask = MergeClusterEdges(mergePROP)
mergeTask.run()
def processTask(x, eps, K, delta, stdindir, stdoutdir, locs, city, LngSPLIT,
LatSPLIT):
suffix = "%.2f" % (delta)
PROP = {
'index': x,
'delta': delta,
'IDIRECTORY': stdindir,
'ODIRECTORY': stdoutdir,
'suffix': suffix,
'locs': locs,
'city': city,
'LngSPLIT': LngSPLIT,
'LatSPLIT': LatSPLIT
}
extractionStartTime = time.time()
task = ExtractGridEdges(PROP)
res = task.run()
extractionEndTime = time.time()
print "Extraction seconds: %f" % (extractionEndTime - extractionStartTime)
count = res['count']
#min_samples = int(count / K) if count > K else 1
min_samples = 2
resByDir = res['res']['resByDir']
resByCate = res['res']['resByCate']
dataType = 'angle' # 确定是按照方向聚类还是角度聚�?direction, category
#EPS_INTERVAL = 0.001 if dataType == 'direction' else 0.4
EPS_INTERVAL = 0.001 if dataType == 'direction' else 0.4
iterationTimes = 0
while (True):
if (iterationTimes == 50):
eps -= EPS_INTERVAL * 50
min_samples -= 5
iterationTimes = 0
clusterPROP = {
'index': x,
'ODIRECTORY': stdoutdir,
'resByDir': resByDir,
'resByCate': resByCate,
'resByAng': resByCate,
'dataType': dataType,
'eps': eps,
'min_samples': min_samples,
'suffix': suffix,
'locs': locs,
'city': city,
'LngSPLIT': LngSPLIT,
'LatSPLIT': LatSPLIT
}
print '''
=== Cluster Parameters ===
index = %d
stdindir = %s
stdoutdir = %s
eps = %f
min_samples = %d
=== Cluster Parameters ===
''' % (x, stdindir, stdoutdir, eps, min_samples)
# 角度聚类单独处理
if dataType == 'angle':
clusteringStartTime = time.time()
clusterTask = LineTFIntersections(clusterPROP)
noiseRate, clusterofilename = clusterTask.run()
clusteringEndTime = time.time()
print "Clustering seconds: %f" % (clusteringEndTime -
clusteringStartTime)
break
clusterTask = DBScanTFIntersections(clusterPROP)
noiseRate, clusterofilename = clusterTask.run()
if noiseRate <= 0.5:
print(iterationTimes)
break
else:
eps += EPS_INTERVAL
iterationTimes += 1
mergePROP = {
'index': x,
'IDIRECTORY': stdindir,
'ODIRECTORY': stdoutdir,
'dataType': dataType,
'suffix': suffix,
'city': city
}
mergeTask = MergeClusterEdges(mergePROP)
mergeTask.run()