Gabriele Cosmo
78 lines
1.8 KiB
Python
78 lines
1.8 KiB
Python
hm.selectStore("xrayfluo.his")
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histoGamDet = hm.load1D(1)
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# prepare to fit the histo h1
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# creating a vector from a histogram
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v1=vm.from1D(histoGamDet)
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vm.list()
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# create a new fitter:
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fit=Fitter()
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# perform fit using the histogram
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fit.setData(v1)
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v1.toAscii("EnergyDep.dat")
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# set the model to "gaussian"
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fit.setModel("G")
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# define (and init) parameters for fit function
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fit.setParameter("amp" ,653.)
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amp = fit.fitParameter ("amp")
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amp.setStart(653.)
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amp.setStep(1.)
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amp.setBounds(500.,700.)
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# ... for these the order is relevant
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fit.setParameter("mean" ,1.72)
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mean = fit.fitParameter ("mean")
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mean.setStart(1.72)
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mean.setStep(0.01)
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mean.setBounds(1.62,1.82)
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# ... as there is no "intelligent parsing" possible :-(
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fit.setParameter("sigma",.1)
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sigma = fit.fitParameter ("sigma")
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sigma.setStart(0.1)
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sigma.setStep(0.005)
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sigma.setBounds(0.01,0.3)
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# perform fit using the histogram
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fit.chiSquareFit()
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fit.printResult()
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# get vector wiht fitted function for overlay
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vfit=fit.fittedVector(vm)
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# comment this if you want to have a look at the resource file for NAG
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shell("rm -f e04ucc.r")
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#pl.zoneOption("mirrorAxis","yes")
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pl.xAxisOption("title","energy release in the detector")
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pl.yAxisOption("label","counts")
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# set error bars (full version)
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#pl.dataOption("Representation","Error")
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# plot data with overlayed fit-result
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pl.textStyle("fontsize","10.")
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pl.dataStyle("linecolor", "green")
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pl.dataOption("legend","fit")
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#pl.dataStyle("lineshape","dashdot")
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pl.plot(vfit)
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wait()
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pl.psPrint("fitEnegyDep.ps")
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pl.reset()
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pl.textStyle("fontsize","10.")
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pl.dataStyle("linecolor", "red")
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pl.dataOption("legend","energyDeposit")
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pl.plot(v1)
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wait()
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pl.dataStyle("linecolor", "green")
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pl.dataOption("legend","fit")
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pl.dataStyle("lineshape","dashdot")
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pl.overlay(vfit)
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pl.psPrint("fitEnegyOverl.ps")
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pl.reset()
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del fit
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