def doTracking(delay=0):
for i in xrange(200):
cm.go(1)
m = cm.video_source.getOutputColorMat()
for j in xrange(tm.getFoundSubtreeCount()):
tm.displayFoundSubtreeBorders(j, m, False, 2, 0)
if write_video:
video_writer.write(m)
if delay != -1:
cm.wk(delay)
import common as common
for x in common.razorModules:
x = str(x)
exec(compile("common." + x + " = " + x, "<retards>", "exec"))
common.go(Player.Position.X + 1, Player.Position.Y + 1) # insula bank
for l in ["M", "L"]:
wimport(w, r.RooPoisson("pois_%s" % l, "pois_%s" % l, w.var("n_%s" % l), w.function("mean_%s" % l)))
w.factory("PROD::model(pois_L,pois_M)")
w.defineSet("obs", common.argSet(w, ["n_L", "n_M"]))
dataset = common.dataset(w.set("obs"))
#w.Print()
return common.fit_result(w, w.pdf("model"), "r", dataset, pl=True)
if __name__ == "__main__":
common.setup()
__L2M = {"yRange": (0.0, 0.35),
"yTitle": "CSVL to CSVM",
"data": data_CSV_L2M,
"tags": ["1tag;", "2tag;"]}
common.go(pdf="L2M_fit.pdf", func=fit_two_terms, **__L2M)
common.go(pdf="L2M_arithmetic.pdf", func=arithmetic, **__L2M)
__R2T = {"yRange": (0.0, 1.0),
"yTitle": "relaxed to tight",
"data": data_SS_relaxed_to_tight,
"tags": ["1;", "2;"]}
common.go(pdf="R2T_fit.pdf", func=fit_two_terms, **__R2T)
common.go(pdf="R2T_arithmetic.pdf", func=arithmetic, **__R2T)
def doTracking(delay=0):
for i in xrange(200):
cm.go(1)
m = cm.video_source.getOutputColorMat()
for j in xrange(tm.getFoundSubtreeCount()):
tm.displayFoundSubtreeBorders(j, m, False, 2, 0)
m = cm.video_source.getOutputColorMat()
for j in xrange(tm.getFoundSubtreeCount()):
tm.displayFoundSubtreeBorders(j, m, False, 2, 0)
if write_video:
video_writer.write(m)
if delay != -1:
cm.wk(delay)
cm.the_callback = callback
n = cm.network
if isTraining:
cm.go(3200)
n.save("ot.dst")
else:
n.load("ot.dst")
# cm.network.save("ot.dst")
tm = cm.pd.DestinTreeManager(n, 1)
print "size of winning tree is: " + str(tm.getWinningCentroidTreeSize())
cm.freezeTraining()
for i in xrange(100):
cm.go(1)
tm.addTree()
support = 10
print "mining..."
found = tm.mine(support)
w.defineSet("obs", common.argSet(w, ["n_L", "n_M"]))
dataset = common.dataset(w.set("obs"))
#w.Print()
return common.fit_result(w, w.pdf("model"), "r", dataset, pl=True)
if __name__ == "__main__":
common.setup()
__L2M = {
"yRange": (0.0, 0.35),
"yTitle": "CSVL to CSVM",
"data": data_CSV_L2M,
"tags": ["1tag;", "2tag;"]
}
common.go(pdf="L2M_fit.pdf", func=fit_two_terms, **__L2M)
common.go(pdf="L2M_arithmetic.pdf", func=arithmetic, **__L2M)
__R2T = {
"yRange": (0.0, 1.0),
"yTitle": "relaxed to tight",
"data": data_SS_relaxed_to_tight,
"tags": ["1;", "2;"]
}
common.go(pdf="R2T_fit.pdf", func=fit_two_terms, **__R2T)
common.go(pdf="R2T_arithmetic.pdf", func=arithmetic, **__R2T)
def doTracking(delay=0):
for i in xrange(200):
cm.go(1)
m = cm.video_source.getOutputColorMat()
for j in xrange(tm.getFoundSubtreeCount()):
tm.displayFoundSubtreeBorders(j, m, False, 2, 0)
def doTracking(delay=0):
for i in xrange(200):
cm.go(1)
m = cm.video_source.getOutputColorMat()
for j in xrange(tm.getFoundSubtreeCount()):
tm.displayFoundSubtreeBorders(j, m, False, 2, 0)
#cm.wk(delay)
cm.the_callback = callback
n = cm.network
if isTraining:
cm.go(3200)
n.save("ot.dst")
else:
n.load("ot.dst")
#cm.network.save("ot.dst")
tm = cm.pd.DestinTreeManager(n, 1)
print "size of winning tree is: " + str(tm.getWinningCentroidTreeSize())
cm.freezeTraining()
for i in xrange(100):
cm.go(1)
tm.addTree()
support = 10
print "mining..."
found = tm.mine(support)
wimport(w, r.RooRealVar("qcd", "qcd", qcdIni, 0.0, 3.0 * max(1.0, qcdIni)))
for l in ["M", "SSL", "SST"]:
wimport(w, r.RooRealVar("ewk_%s" % l, "ewk_%s" % l, getattr(y, "ewk_%s" % l)))
wimport(w, r.RooRealVar("n_%s" % l, "n_%s" % l, getattr(y, "n_%s" % l)))
wimport(w, r.RooFormulaVar("mean_SSL", "(@0)+(@1)", r.RooArgList(w.var("ewk_SSL"), w.var("qcd_SSL"))))
wimport(w, r.RooFormulaVar("mean_SST", "(@0)+((@1)*(@2))", r.RooArgList(w.var("ewk_SST"), w.var("qcd_SSL"), w.var("r"))))
wimport(w, r.RooFormulaVar("mean_M", "(@0)+((@1)/(@2))", r.RooArgList(w.var("ewk_M"), w.var("qcd"), w.var("r"))))
for l in ["M", "SSL", "SST"]:
wimport(w, r.RooPoisson("pois_%s" % l, "pois_%s" % l, w.var("n_%s" % l), w.function("mean_%s" % l)))
w.factory("PROD::model(pois_M,pois_SSL,pois_SST)")
w.defineSet("obs", common.argSet(w, ["n_M", "n_SSL", "n_SST"]))
dataset = common.dataset(w.set("obs"))
#w.Print()
return common.fit_result(w, w.pdf("model"), "qcd", dataset, pl=True)
if __name__ == "__main__":
common.setup()
__qcd = {"data": data, "yTitle": "QCD yield estimate"}
common.go(pdf="QCD_arithmetic1.pdf", func=arithmetic, tags=["1;"], yRange=(0.0, 50.0), **__qcd)
common.go(pdf="QCD_arithmetic2.pdf", func=arithmetic, tags=["2;"], yRange=(0.0, 15.0), **__qcd)
common.go(pdf="QCD_fit1.pdf", func=fit_qcd, tags=["1;"], yRange=(0.0, 50.0), **__qcd)
common.go(pdf="QCD_fit2.pdf", func=fit_qcd, tags=["2;"], yRange=(0.0, 15.0), **__qcd)
if not Misc.CurrentScriptDirectory() in sys.path:
sys.path.append(Misc.CurrentScriptDirectory())
#
import System
import common as common
import hoboconstants as hobo
for x in common.razorModules:
x = str(x)
exec(compile("common." + x + " = " + x, "<retards>", "exec"))
startX = Player.Position.X
startY = Player.Position.Y
positions = {
1: [15, 15],
2: [-15, 15],
3: [-15, 0],
4: [15, 0],
5: [-15, -0],
6: [1, 1]
}
#Recal To Luna Moongate
while not Player.IsGhost:
for pos in positions:
Misc.SendMessage(positions[pos][1])
common.go(startX + positions[pos][0], startY + positions[pos][1])
Misc.Pause(6000)