import sendemail as se
name = os.path.basename(__file__)
se.send(name, message)
if cfg.plotcut:
allcounts = cc.run(reconstructdata, rowcount, int(cfg.mincount))
sys.path.append('/d6/rstein/Hamburg-Cosmic-Rays/BDT')
import BDT
BDT.run(reconstructdata, rowcount, int(cfg.mincount), allcounts)
llcuts = oz.run(reconstructdata + "_BDT", rowcount, int(cfg.mincount), cfg.graph, allcounts)
print llcuts
pl.run(reconstructdata+ "_BDT", rowcount, int(cfg.mincount), cfg.graph, llcuts, allcounts)
pz.run(reconstructdata+ "_BDT", rowcount, int(cfg.mincount), cfg.graph, llcuts, allcounts)
pp.run(reconstructdata+ "_BDT", rowcount, int(cfg.mincount), cfg.graph, llcuts)
pe.run(reconstructdata+ "_BDT", rowcount, int(cfg.mincount), cfg.graph, llcuts)
ph.run(reconstructdata+ "_BDT", rowcount, int(cfg.mincount), cfg.graph, llcuts)
if cfg.plot:
pz.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph, defaultcuts)
pp.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph, defaultcuts)
pe.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph, defaultcuts)
ph.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph, defaultcuts)
#~ if cfg.plotangle:
#~ pa.run(cfg.reconstructdata, rowcount, int(cfg.mincount), cfg.graph)
if cfg.radiusstatistics:
rs.run(cfg.graph)
if cfg.plotcut:
allcounts = cc.run(reconstructdata, rowcount, int(cfg.mincount))
sys.path.append('/d6/rstein/Hamburg-Cosmic-Rays/BDT')
import BDT
BDT.run(reconstructdata, rowcount, int(cfg.mincount), allcounts)
llcuts = oz.run(reconstructdata + "_BDT", rowcount, int(cfg.mincount),
cfg.graph, allcounts)
print llcuts
pl.run(reconstructdata + "_BDT", rowcount, int(cfg.mincount), cfg.graph,
llcuts, allcounts)
pz.run(reconstructdata + "_BDT", rowcount, int(cfg.mincount), cfg.graph,
llcuts, allcounts)
pp.run(reconstructdata + "_BDT", rowcount, int(cfg.mincount), cfg.graph,
llcuts)
pe.run(reconstructdata + "_BDT", rowcount, int(cfg.mincount), cfg.graph,
llcuts)
ph.run(reconstructdata + "_BDT", rowcount, int(cfg.mincount), cfg.graph,
llcuts)
if cfg.plot:
pz.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph,
defaultcuts)
pp.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph,
defaultcuts)
pe.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph,
defaultcuts)
ph.run(reconstructdata, rowcount, int(cfg.mincount), cfg.graph,
defaultcuts)
pl.run(reconstructdata + "_BDT",
rowcount,
int(mincount),
graph=False,
cuts=llcuts,
allcounts=allcounts)
pz.run(reconstructdata + "_BDT",
rowcount,
int(mincount),
graph=False,
cuts=llcuts,
allcounts=allcounts)
pp.run(reconstructdata + "_BDT",
rowcount,
int(mincount),
graph=False,
cuts=llcuts,
allcounts=allcounts)
pe.run(reconstructdata + "_BDT",
rowcount,
int(mincount),
graph=False,
cuts=llcuts,
allcounts=allcounts)
ph.run(reconstructdata + "_BDT",
rowcount,
int(mincount),
graph=False,
cuts=llcuts,
allcounts=allcounts)
import categorycounts as cc
import initialise as i
orientation = "ideal"
mincount = 5
sys.path.append("/d6/rstein/Hamburg-Cosmic-Rays/BDT")
import BDT
with open(afspath + "/orientations/" + orientation + ".csv", "rb") as csvfile:
reader = csv.reader(csvfile, delimiter=",", quotechar="|")
rowcount = 0
for row in reader:
rowcount += 1
allcounts = cc.run(reconstructdata, rowcount, int(mincount))
print allcounts
BDT.run(reconstructdata, rowcount, int(mincount), allcounts)
llcuts = oz.run(reconstructdata + "_BDT", rowcount, int(mincount), graph=False, allcounts=allcounts)
print llcuts
pz.run(reconstructdata + "_BDT", rowcount, int(mincount), graph=False, cuts=None, allcounts=allcounts)
pl.run(reconstructdata + "_BDT", rowcount, int(mincount), graph=False, cuts=llcuts, allcounts=allcounts)
pz.run(reconstructdata + "_BDT", rowcount, int(mincount), graph=False, cuts=llcuts, allcounts=allcounts)
pp.run(reconstructdata + "_BDT", rowcount, int(mincount), graph=False, cuts=llcuts, allcounts=allcounts)
pe.run(reconstructdata + "_BDT", rowcount, int(mincount), graph=False, cuts=llcuts, allcounts=allcounts)
ph.run(reconstructdata + "_BDT", rowcount, int(mincount), graph=False, cuts=llcuts, allcounts=allcounts)
totaln = n*5000 print time.asctime(time.localtime()),"Cosmic Ray Iron Flux is", flux, "Simulated Area is", area, "Field of View is", solidangle, "Detected Flux is", detectedflux print time.asctime(time.localtime()),"Rate per hour", rateperhour, "Simulated Hours", numberofhours, "Simulated Events", n print time.asctime(time.localtime()),"Simulated 500 events, equal to", totalhours, "Simulated Hours. Simulated Events", totaln pickle_dir = "/nfs/astrop/d6/rstein/chargereconstructionpickle/combined/" statsdata = pickle_dir + "stats.p" traindata = pickle_dir + "trainingset.p" plpd.run(statsdata) BDT.run(traindata, statsdata, int(mincount)) pd.run(statsdata, int(mincount), cuts=[0.0, 0.0]) llcuts = oz.run(statsdata, int(mincount)) pem.run(statsdata, int(mincount), cuts=llcuts) pb.run(statsdata, int(mincount), cuts=llcuts) print "Log Likelihood Cuts", llcuts pz.run(statsdata, int(mincount), cuts=None) pe.run(statsdata, int(mincount), cuts=None) pd.run(statsdata, int(mincount), cuts=None) ph.run(statsdata, int(mincount), cuts=None) pp.run(statsdata, int(mincount), cuts=None) pz.run(statsdata, int(mincount), cuts=llcuts) pl.run(statsdata, int(mincount), cuts=llcuts) pp.run(statsdata, int(mincount), cuts=llcuts) pd.run(statsdata, int(mincount), cuts=[0.0, 0.0]) pe.run(statsdata, int(mincount), cuts=llcuts) ph.run(statsdata, int(mincount), cuts=llcuts)