def test():
env = Graphenv()
env.init()
name1='JJCEX.ACS.PH.03.OAT'
name2= 'JJCEX.ACS.PH.04.OAT'
name3 = 'JJCEX.ACS.PH.03.COOLING.VLV'
name4 = 'JJCEX.ACS.PH.03.STEAM.VLV.2'
L =[(name1,env.getSensorId(name1)),\
(name2,env.getSensorId(name2))]
gr = Graph()
#print a[0].head()
expr = "{0};{1};{t}.hour"
a = gr.getXY(L,'',expr)
#a = gr.getPredict(L,'x.month == 7',expr,'SVM',4,30,'ada1',True)
#b = gr.getPredict(L,'x.month == 9','','Ada Boost',4,0,'svm1',False)
print a
#a = gr.getCorrelations(L,expr)
#ex = gr.getMSTF(L,expr)
#ex = gr.getExpression(L,expr,a,True)
#print a
return a
def graph(type,h,dtfilter,req,expression,mtype,maw,pct,mname,learn):
keys= [(n,int(x)) for n,x in h]
g = Graph()
j0=g.getRequest(req,dtfilter)
if type =='Moving Std':
print "type",type
j = g.getMSTF(keys,dtfilter,expression)
ctype='StockChart'
elif type =='Time Series':
print type,keys
j = g.getRegular(keys,dtfilter,expression,False)
ctype='StockChart'
elif type =='XY':
print type,keys
j = g.getXY(keys,dtfilter,expression)
ctype='scatter'
elif type =='Correl':
print type,keys
j = g.getCorrelations(keys,dtfilter,expression)
ctype='StockChart'
elif type =='Frequencies':
print type,keys
j = g.getFreq(keys,dtfilter,expression)
ctype='Histogram'
elif type =='Learn':
print type,keys,mtype,maw
j = g.getPredict(keys,dtfilter,expression,mtype,maw,float(pct),mname,learn)
ctype='StockChart'
elif type =='Table':
print type,keys
j = g.getRegular(keys,dtfilter,expression,False)
ctype='Table'
else:
return {}
if not isinstance(j, str):
j.extend(j0)
return json.dumps(j),ctype