class Core:
pre = EdgeMatchObjectDetector()
cam = WebCamera()
pipeline = PipeLine()
pipeline.addCamera(cam)
pipeline.addPreProcessor(pre)
pipeline.executePipeLine()
def experimentsS(deviceID, writeID):
time_start = time.time()
nowTime = time.strftime("%Y_%m_%d_%H_%M_%S", time.localtime())
resultWritter = ResultWritter("../result/" + nowTime)
mlpPos = [0, 1, 2]
nclasses = [2, 6, 21]
for dataName in ["com-lj"]:
# for dataName in ["com-orkut"]:
for i in range(5):#5
args = {}
for k in [0, 1, 2]:#3
for j in range(3):#3
args['numLayer'] = mlpPos[j] + k + 1
args['mlpPos'] = [mlpPos[j] + k]
args['nclasses'] = [nclasses[j]]
if writeID == 4:
args['baseModel'] = "GatedGIN"
args['useKTupleFeature'] = True
elif writeID == 5:
args['baseModel'] = "GIN"
args['useKTupleFeature'] = False
elif writeID == 6:
args['baseModel'] = "GCN"
args['useKTupleFeature'] = False
args['numIterator'] = 200
args['use3Feature'] = False
args['useRandomFeature'] = False
args['layerNorm'] = False
args['learningRate'] = 0.001
args['weightDecay'] = 0
args['useDropout'] = True
args['keepProb'] = 0.5
args['useBatchNorm'] = True
args['detach'] = False
args['aggregator'] = "mean"
if writeID == 5:
args['aggregator'] = "sum"
pipeLine = PipeLine(resultWritter = resultWritter, args = args, deviceID = deviceID, writeInfo = deviceID)
pipeLine.trainSynGraph(["../newData/" + dataName])
valData = ["../newData/" + dataName + ".edges"]
model = PipeLine(resultWritter = resultWritter, args = args, deviceID = deviceID, writeInfo = deviceID)
model.LoadModel("../model/real1/realBest.ckpt" + model.writeInfo)
model.inferRealGraph(valData, needLabel = True)
time_end = time.time()
print("time cost",time_end - time_start,'s')
resultWritter.writeResult('summary.txt', "time cost" + str(time_end - time_start) + 's')
def runTransferExperiments(deviceID):
writeID = deviceID
time_start = time.time()
nowTime = time.strftime("%Y_%m_%d_%H_%M_%S", time.localtime())
resultWritter = ResultWritter("../result/" + nowTime)
# for dataName in ["com-lj", "com-orkut"]:
# for dataName in ["artist_edges"]:
# for dataName in ["com-lj"]:
for dataName in ["com-orkut"]:
for i in range(5):#5
args = {}
args['numLayer'] = 3
args['mlpPos'] = [0, 1, 2]
for j in range(1):#3
args['baseModel'] = "GatedGIN"
args['useKTupleFeature'] = True
args['numIterator'] = 200
args['nclasses'] = [2, 6, 21]
args['use3Feature'] = False
args['useRandomFeature'] = False
args['layerNorm'] = False
args['learningRate'] = 0.001
args['weightDecay'] = 0
args['useDropout'] = True
args['keepProb'] = 0.5
args['useBatchNorm'] = True
args['detach'] = False
args['aggregator'] = "mean"
pipeLine = PipeLine(resultWritter = resultWritter, args = args, deviceID = deviceID, writeInfo = writeID)
pipeLine.trainSynGraph(["../newData/" + dataName])
for testName in ["artist_edges", "web-BerkStan", "com-lj", "com-orkut"]:
valData = ["../newData/" + testName + ".edges"]
model = PipeLine(resultWritter = resultWritter, args = args, deviceID = deviceID, writeInfo = writeID)
model.LoadModel("../model/real1/realBest.ckpt" + model.writeInfo)
model.inferRealGraph(valData, needLabel = True)
time_end = time.time()
print("time cost",time_end - time_start,'s')
resultWritter.writeResult('summary.txt', "time cost" + str(time_end - time_start) + 's')
resultWritter.writeResult('summary.txt', dataName)
args['numLayer'] += 1
args['mlpPos'][0] += 1
args['mlpPos'][1] += 1
args['mlpPos'][2] += 1
mainwin.setContent(info_win)
from FutureTab import FutureTab
sh_ftab = FutureTab()
sh_ftab.setContentWindow(info_win)
dl_ftab = FutureTab()
dl_ftab.setContentWindow(info_win)
mainwin.setSHTab(sh_ftab)
mainwin.setDLTab(dl_ftab)
from FutureSpider import InfoParser
from PipeLine import PipeLine
# 创建管道类
pipe = PipeLine()
# 互相绑定
pipe.set_SH_FutureTab(sh_ftab)
pipe.set_DL_FutureTab(dl_ftab)
# sh_ftab.setPipeLine(pipe)
mainwin.setPipeLine(pipe)
pipe.setMainWindow(mainwin)
# 初始化爬虫类
spider = InfoParser(pipe)
# 调用爬虫爬虫方法
spider.SH_getPageLink(sh_url)
spider.DL_getPageLink(dl_url)
mainwin.setSpider(spider)
def timecompare(self, cmp_time_str, iday):
#今天时间
today = datetime.date.today()
str_today = time.strftime("%Y-%m-%d", today.timetuple())
# 用今天日期减掉时间差，参数为1天，获得昨天的日期
yesterday = today - datetime.timedelta(days=iday)
str_yesterday = time.strftime("%Y-%m-%d", yesterday.timetuple())
# print("今天是%s, 昨天是%s" % (str_today, str_yesterday))
yesterdayArray = time.strptime(str_yesterday, "%Y-%m-%d")
yesterdayTimeStamp = int(time.mktime(yesterdayArray))
cmp_Time_Array = time.strptime(cmp_time_str, "%Y-%m-%d")
cmpTimeTimeStamp = int(time.mktime(cmp_Time_Array))
if (cmpTimeTimeStamp >= yesterdayTimeStamp):
return True
else:
return False
if __name__ == '__main__':
sh_url = "http://www.shfe.com.cn/news/notice/"
dl_url = "http://www.dce.com.cn/dalianshangpin/yw/fw/jystz/ywtz/index.html"
pl = PipeLine()
spider = InfoParser(pl)
# spider.SH_getPageLink(sh_url)
spider.DL_getPageLink(dl_url)