import rCodeGen, utility
import attribute
import aGenForE
parser = argparse.ArgumentParser(description='This program will get results for all the subexperiments. \n' , formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('-td', required=True,help='Training directory')
parser.add_argument('-dt',required=True,help='Number of days after start training day specified . Defaults to 1 ')
parser.add_argument('-run', required=True,help='dry (only show dont execute) or real (show and execute)')
parser.add_argument('-sequence', required=True,help='lp (Local parallel) / dp (Distributed parallel) / serial')
parser.add_argument('-nComputers',required=True,help="Number of computers at which task has to be run present in the data set")
parser.add_argument('-iT',required=False,help='Instrument name')
parser.add_argument('-sP',required=False,help='Strike price of instrument')
parser.add_argument('-oT',required=False,help='Options Type')
args = parser.parse_args()
attribute.initializeInstDetails(args.iT,args.sP,args.oT)
if(args.sequence == "dp"):
import dp
allDataDirectories = attribute.getListOfTrainingDirectoriesNames( int(args.dt) , args.td ,args.iT)
commandList = []
for directories in allDataDirectories:
#src/removeDuplicatesFromOrderBook.py -d ob/data/ro/nsefut/20141126/ -iT SBIN -oT 0 -sP -1
commandList.append(["removeDuplicatesFromOrderBook.py", "-d", directories, "-iT", args.iT, "-oT", args.oT, "-sP", args.sP])
for chunkNum in range(0,len(commandList),int(args.nComputers)):
lSubGenList = commandList[chunkNum:chunkNum+int(args.nComputers)]
utility.runCommandList(lSubGenList,args)
print dp.printGroupStatus()
lListOfTrainPredictDirectories = lListOfTrainingDirectories
if args.pd is None:
predictionDirectory = attribute.getListOfTrainingDirectoriesNames(2,lListOfTrainPredictDirectories[-1],args.iT)[-1]
else:
predictionDirectory = args.pd
lListOfTrainPredictDirectories.append(predictionDirectory)
if(args.sequence == "dp"):
experimentFolder = args.e
dataFolder = args.td
generatorsFolder = args.g
commandList = []
for directories in lListOfTrainPredictDirectories:
commandList.append(["aGenForE.py","-e",experimentFolder,"-d",directories,"-g",args.g,"-run",args.run,"-sequence",args.sequence,'-tickSize',args.tickSize,"-iT",args.iT,"-oT",args.oT,"-sP",args.sP])
utility.runCommandList( commandList ,args)
print dp.printGroupStatus()
else:
if args.sequence == 'lp':
# to run it in local parallel mode
pool = multiprocessing.Pool() # this will return the number of CPU's
results = map(scriptWrapperForFeatureGeneration,lListOfTrainPredictDirectories)
else:
results = map(scriptWrapperForFeatureGeneration,lListOfTrainPredictDirectories)
utility.runCommand(["rGenForE.py","-e",args.e,"-a",algo,"-sequence",args.sequence,"-targetClass",args.targetClass,"-skipM",args.skipM,\
'-dt',args.dt,'-pd',predictionDirectory,"-td",args.td,"-skipP",args.skipP, '-wt' , args.wt,"-iT",args.iT,"-oT",args.oT,"-sP",args.sP],args.run,args.sequence)
utility.runCommand(["runAllRScriptsForE.py","-td",args.td,"-pd",predictionDirectory,"-dt",args.dt,"-e",args.e,"-a",algo,"-run",args.run,\
'-wt' , args.wt,"-iT",args.iT,"-oT",args.oT,"-sP",args.sP,"-sequence",args.sequence],args.run,args.sequence)
if args.targetClass == "multinomial" :
utility.runCommand(["cMatrixGen.py","-d",predictionDirectory,"-e",args.e,"-a",algo],args.run,args.sequence)
if args.dt == None:
args.dt = "1"
if args.wt == None:
args.wt = "default"
if args.pd == None:
args.pd = args.td
if args.pdt == None:
args.pdt = args.nDays
if args.g == None:
args.g = "ob/generators/"
if args.targetClass == None:
args.targetClass = "binomial"
if args.iT is not None and args.sP is None and args.oT is None:
args.sP = "-1"
args.oT = "0"
if "/nsecur/" in args.td:
if args.t == None:
args.t = "0.000015"
if args.tickSize == None:
args.tickSize = "25000"
elif "/nsefut/" in args.td:
if args.t == None:
args.t = "0.00015"
if args.tickSize == None:
args.tickSize = "5"
dp.printGroupStatus()