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
def graphit(sensorname,sensorid):
g = Graph()
j,t = g.getMSTF(sensorname,sensorid)
return t