def runANNZ():
exitStatus = runOneANNZ()
if exitStatus == 0: return
# if ANNZ failed during training, try again with a different random seed and randomized MLM options
# --------------------------------------------------------------------------------------------------
if glob.annz["doTrain"]:
# set random seed if not already set
setSeed = (not glob.annz.has_key("initSeedRnd"))
if not setSeed: setSeed = (glob.annz["initSeedRnd"] < 1)
if setSeed: glob.annz["initSeedRnd"] = 198876
# remove all userMLMopts so that a random set is generated
glob.annz["userMLMopts"] = ""
if glob.annz["doBinnedCls"]:
for nRndOptNow in range(glob.annz["binCls_nTries"]): glob.annz.pop("userMLMopts_"+str(nRndOptNow),None)
nTries = 0
for nTryNow in range(nTries):
glob.annz["initSeedRnd"] += 1
log.warning(whtOnRed(" - runANNZ failed !!! Will try again ("+str(nTryNow+1)+"/"+str(nTries)+") with initSeedRnd = ")+yellowOnRed(str(glob.annz["initSeedRnd"])))
exitStatus = runOneANNZ()
if exitStatus == 0: break
Assert("runANNZ failed !!!",(exitStatus == 0))
return
def initParse():
parser = argparse.ArgumentParser(description="Command line parser:")
parser.add_argument("--make", action='store_true')
parser.add_argument("--clean", action='store_true')
parser.add_argument("--train", action='store_true')
parser.add_argument("--optimize", action='store_true')
parser.add_argument("--verify", action='store_true')
parser.add_argument("--evaluate", action='store_true')
parser.add_argument("--qsub", action='store_true')
parser.add_argument("--genInputTrees", action='store_true')
parser.add_argument("--singleRegression", action='store_true')
parser.add_argument("--randomRegression", action='store_true')
parser.add_argument("--binnedClassification", action='store_true')
parser.add_argument("--singleClassification", action='store_true')
parser.add_argument("--randomClassification", action='store_true')
parser.add_argument("--onlyKnnErr", action='store_true')
parser.add_argument("--inTrainFlag", action='store_true')
parser.add_argument("--truncateLog", action='store_true')
parser.add_argument("--isBatch", action='store_true')
parser.add_argument("--fitsToAscii", action='store_true')
parser.add_argument("--asciiToFits", action='store_true')
parser.add_argument("--logFileName", type=str, default="")
parser.add_argument("--logLevel", type=str, default="INFO")
parser.add_argument("--generalOptS", type=str, default="NULL")
parser.add_argument("--makeOpt", type=str, default="NULL")
parser.add_argument("--maxNobj", type=float, default=0)
parser.add_argument("--trainIndex", type=int, default=-1)
parser.add_argument("--generalOptI", type=int, default=-1)
glob.pars = vars(parser.parse_args())
initLogger()
# sanity check of user options
# --------------------------------------------------------------------------------------------------
hasMake = (glob.pars["make"] or glob.pars["clean"])
nModes = 0 ; nSetups = 0
# if glob.pars["genInputTrees"]: nSetups += 1
if glob.pars["singleClassification"]: nSetups += 1
if glob.pars["randomClassification"]: nSetups += 1
if glob.pars["singleRegression"]: nSetups += 1
if glob.pars["randomRegression"]: nSetups += 1
if glob.pars["binnedClassification"]: nSetups += 1
if glob.pars["onlyKnnErr"]: nSetups += 1
if glob.pars["inTrainFlag"]: nSetups += 1
if glob.pars["fitsToAscii"]: nSetups += 1
if glob.pars["asciiToFits"]: nSetups += 1
if not ((nSetups == 1) or (nSetups == 0 and (glob.pars["genInputTrees"] or hasMake or glob.pars["qsub"]))):
log.warning("Possibly missing/conflicting job-options... Did you define: --singleClassification" \
+ " --randomClassification , --singleRegression --randomRegression, --binnedClassification, " \
+"--onlyKnnErr, --inTrainFlag, --fitsToAscii, --asciiToFits .... ?")
if nSetups == 1:
if glob.pars["genInputTrees"]: nModes += 1
if glob.pars["train"]: nModes += 1
if glob.pars["optimize"]: nModes += 1
if glob.pars["verify"]: nModes += 1
if glob.pars["evaluate"]: nModes += 1
if glob.pars["onlyKnnErr"]: nModes += 1
if glob.pars["inTrainFlag"]: nModes += 1
if glob.pars["fitsToAscii"]: nModes += 1
if glob.pars["asciiToFits"]: nModes += 1
if not (nModes == 1 or hasMake):
log.warning("Should define exactly one of --genInputTrees --train , --optimize --verify, --evaluate, --onlyKnnErr, --inTrainFlag, --fitsToAscii, --asciiToFits !")
glob.pars["onlyMake"] = (((nSetups == 0) or (nModes == 0)) and hasMake and (not glob.pars["genInputTrees"]))
# add make option, e.g., "-j4"
glob.makeOpt = glob.pars["makeOpt"] if glob.pars["makeOpt"] is not "NULL" else ""
# set basic values for operational flags
# --------------------------------------------------------------------------------------------------
glob.annz["doGenInputTrees"] = glob.pars["genInputTrees"]
glob.annz["doSingleReg"] = glob.pars["singleRegression"]
glob.annz["doRandomReg"] = glob.pars["randomRegression"]
glob.annz["doBinnedCls"] = glob.pars["binnedClassification"]
glob.annz["doSingleCls"] = glob.pars["singleClassification"]
glob.annz["doRandomCls"] = glob.pars["randomClassification"]
glob.annz["doTrain"] = glob.pars["train"]
glob.annz["doOptim"] = glob.pars["optimize"]
glob.annz["doVerif"] = glob.pars["verify"]
glob.annz["doEval"] = glob.pars["evaluate"]
glob.annz["doOnlyKnnErr"] = glob.pars["onlyKnnErr"]
glob.annz["doInTrainFlag"] = glob.pars["inTrainFlag"]
glob.annz["doRegression"] = glob.annz["doSingleReg"] or glob.annz["doRandomReg"] or glob.annz["doBinnedCls"]
glob.annz["doClassification"] = glob.annz["doSingleCls"] or glob.annz["doRandomCls"]
glob.annz["maxNobj"] = int(floor(glob.pars["maxNobj"])) # limit number of used objects - used for debugging
glob.annz["trainIndex"] = glob.pars["trainIndex"] # used for python batch-job submision
glob.annz["doFitsToAscii"] = glob.pars["fitsToAscii"]
glob.annz["doAsciiToFits"] = glob.pars["asciiToFits"]
# general-use options for developers
glob.annz["generalOptS"] = glob.pars["generalOptS"]
glob.annz["generalOptI"] = glob.pars["generalOptI"]
# default values for options which should be overridden in generalSettings()
# --------------------------------------------------------------------------------------------------
glob.annz["isBatch"] = (glob.pars["logFileName"] != "" or glob.pars["isBatch"])
glob.annz["useCoutCol"] = glob.annz["doPlots"] = True
glob.annz["printPlotExtension"] = "pdf"
