Python nllm3 예제들

예제 #1

파일: res_m3_EB.py 프로젝트: janveverka/JPsi

def drawLatex(x, y, text):
    latexLabel.SetText(x, y, text)
    latexLabels.append(latexLabel.DrawClone())

yurii.applySelection(selection)
    
iteration = 1
xvar = []
nll = []
dx = (xMax - xMin) / (numScanSteps - 1)
#print "Begin iteration %d: scanning over [%.2g, %.2g]" % \
    #(iteration, xMin, xMax)
## Scan the NLL
for istep in range(numScanSteps):
    xvar.append(xMin + dx * istep)
    nll.append( yurii.nllm3(scale, res=xvar[-1]) )
## Make a graph
x = array.array("d", xvar)
y = array.array("d", nll)
gr = TGraph(len(xvar), x, y)
## Draw the graph
c1 =  TCanvas("iter%d" % iteration, "Iteration %d" % iteration)
canvases.append(c1)
c1.SetGridx()
c1.SetGridy()
#gr.Draw("ap")
gr.GetXaxis().SetTitle("Photon Surplus Energy Resolution (%)")
gr.GetYaxis().SetTitle("- log L")
gr.SetNameTitle("gr%d" % iteration, "Iteration %d" % iteration)
gr.Draw("ap")
graphs.append(gr)

예제 #2

파일: es_m3.py 프로젝트: janveverka/JPsi

def drawLatex(x, y, text):
    latexLabel.SetText(x, y, text)
    latexLabels.append(latexLabel.DrawClone())

yurii.applySelection(selection)
    
iteration = 1
xvar = []
nll = []
dx = (xMax - xMin) / (numScanSteps - 1)
#print "Begin iteration %d: scanning over [%.2g, %.2g]" % \
    #(iteration, xMin, xMax)
## Scan the NLL
for istep in range(numScanSteps):
    xvar.append(xMin + dx * istep)
    nll.append( yurii.nllm3(scale=xvar[-1], res=0.) )
## Make a graph
x = array.array("d", xvar)
y = array.array("d", nll)
gr = TGraph(len(xvar), x, y)
## Draw the graph
c1 =  TCanvas("iter%d" % iteration, "Iteration %d" % iteration)
canvases.append(c1)
c1.SetGridx()
c1.SetGridy()
#gr.Draw("ap")
gr.GetXaxis().SetTitle("Photon Energy Scale (%)")
gr.GetYaxis().SetTitle("- log L")
gr.SetNameTitle("gr%d" % iteration, "Iteration %d" % iteration)
gr.Draw("ap")
graphs.append(gr)

예제 #3

파일: escale.py 프로젝트: janveverka/JPsi

    latexLabels.append(latexLabel.DrawClone())

yurii.applySelection(selection)

iteration = 1
xvar = []
nll = []
dx = (xMax - xMin) / (numScanSteps - 1)
#print "Begin iteration %d: scanning over [%.2g, %.2g]" % \
    #(iteration, xMin, xMax)
## Scan the NLL
for istep in range(numScanSteps):
    xvar.append(xMin + dx * istep)
    nll.append( yurii.nllm3( scale=xvar[-1],
                             res=0.,
                             m3min=87.2,
                             m3max=95.2,
                             nbinsMC=30 ) )
## Make a graph
x = array.array("d", xvar)
y = array.array("d", nll)
gr = TGraph(len(xvar), x, y)
## Draw the graph
c1 =  TCanvas("iter%d" % iteration, "Iteration %d" % iteration)
canvases.append(c1)
c1.SetGridx()
c1.SetGridy()
#gr.Draw("ap")
gr.GetXaxis().SetTitle("Photon Energy Scale (%)")
gr.GetYaxis().SetTitle("- log L")
gr.SetNameTitle("gr%d" % iteration, "Iteration %d" % iteration)

예제 #4

파일: es_m3_EE_scan.py 프로젝트: janveverka/JPsi

for im3 in range(numM3ScanSteps):
    xvar = []
    nll = []
    dx = (xMax - xMin) / (numScanSteps - 1)
    dm3 = m3WindowSizeScanRange[0] + \
          (m3WindowSizeScanRange[1] -  m3WindowSizeScanRange[0]) * \
          im3 / (numM3ScanSteps - 1)
    dm3 *= 0.5
    m3min = m3Center - dm3
    m3max = m3Center + dm3
    print "Begin iteration %d: scanning over [%f, %f]" % \
        (im3, m3min, m3max)
    ## Scan the NLL
    for istep in range(numScanSteps):
        xvar.append(xMin + dx * istep)
        nll.append( yurii.nllm3(scale=xvar[-1], res=0., m3min=m3min, m3max=m3max) )
    ## Make a graph
    x = array.array("d", xvar)
    y = array.array("d", nll)
    gr = TGraph(len(xvar), x, y)
    ## Draw the graph
    c1 =  TCanvas("iter%d" % im3, "Iteration %d" % im3)
    canvases.append(c1)
    c1.SetGridx()
    c1.SetGridy()
    #gr.Draw("ap")
    gr.GetXaxis().SetTitle("Photon Energy Scale (%)")
    gr.GetYaxis().SetTitle("- log L")
    gr.SetNameTitle("gr%d" % iteration, "Iteration %d" % iteration)
    gr.Draw("ap")
    graphs.append(gr)

예제 #5

파일: es_m3_EE.py 프로젝트: janveverka/JPsi

def drawLatex(x, y, text):
    latexLabel.SetText(x, y, text)
    latexLabels.append(latexLabel.DrawClone())

yurii.applySelection(selection)

iteration = 1
xvar = []
nll = []
dx = (xMax - xMin) / (numScanSteps - 1)
#print "Begin iteration %d: scanning over [%.2g, %.2g]" % \
    #(iteration, xMin, xMax)
## Scan the NLL
for istep in range(numScanSteps):
    xvar.append(xMin + dx * istep)
    nll.append( yurii.nllm3(scale=xvar[-1], res=0., m3min=84, m3max=96, nbinsMC=60) )
## Make a graph
x = array.array("d", xvar)
y = array.array("d", nll)
gr = TGraph(len(xvar), x, y)
## Draw the graph
c1 =  TCanvas("iter%d" % iteration, "Iteration %d" % iteration)
canvases.append(c1)
c1.SetGridx()
c1.SetGridy()
#gr.Draw("ap")
gr.GetXaxis().SetTitle("Photon Energy Scale (%)")
gr.GetYaxis().SetTitle("- log L")
gr.SetNameTitle("gr%d" % iteration, "Iteration %d" % iteration)
gr.Draw("ap")
graphs.append(gr)