def make_uuplot(ux, uy):
plot = ux.uniform_var.frame()
ux.data.plotOn(plot, roo.LineColor(ux.color), roo.MarkerColor(ux.color))
ux.uniform_pdf.plotOn(plot, roo.LineColor(ux.color), roo.Range(0, 1))
uy.uniform_pdf.plotOn(plot, roo.LineColor(uy.color), roo.Range(0, 1),
roo.LineStyle(ROOT.kDashed))
uy.data.plotOn(plot, roo.LineColor(uy.color), roo.MarkerColor(uy.color),
roo.MarkerStyle(4))
canvases.next('uu')
plot.Draw()
return plot
def make_fixed_range_log_plot(self):
c1 = canvases.next(self.name + '_log_fixedrange')
c1.SetGrid()
c1.SetLogy()
self.canvases.append(c1)
## Use the ModalInterval class to display the shortest range containing
## 100% of all the entries.
mi = self.modal_interval
mi.setFraction(1)
fullrange = (mi.lowerBound(), mi.upperBound())
plot = self.deltaE.frame(roo.Range(*self.fixed_range_log))
plot.SetTitle(', '.join(self.labels))
self.fit_data.plotOn(plot, roo.MarkerColor(self.color_data),
roo.MarkerStyle(self.marker_style),
roo.LineColor(self.color_data))
self.model.plotOn(plot, roo.LineColor(self.color_model))
if fullrange[0] + fullrange[1] > 0:
layout = (0.6, 0.9, 0.87)
else:
layout = (0.2, 0.5, 0.87)
self.model.paramOn(plot, roo.Format("NEU", roo.AutoPrecision(2)),
roo.Layout(*layout))
## Fine tune the y-axis range so that we see all the events.
plot.SetMinimum(0.5)
## Add a larger top margin to the y-axis range
plot.SetMaximum(pow(plot.GetMaximum(), 1.1))
plot.Draw()
self.plots.append(plot)
def make_fixed_range_zoom_plot(self):
c1 = canvases.next(self.name + '_lin_fixedrange')
c1.SetGrid()
self.canvases.append(c1)
plot = self.deltaE.frame(roo.Range(*self.fixed_range_zoom))
plot.SetTitle(', '.join(self.labels))
self.fit_data.plotOn(plot, roo.MarkerColor(self.color_data),
roo.MarkerStyle(self.marker_style),
roo.LineColor(self.color_data))
self.model.plotOn(plot, roo.LineColor(self.color_model))
self.model.paramOn(plot, roo.Format("NEU", roo.AutoPrecision(2)),
roo.Layout(0.2, 0.52, 0.87))
plot.Draw()
self.plots.append(plot)
def plot_uniform(self):
'''
Create a canvas with transformed x data overlayed with a uniform pdf.
'''
self.uplot = self.uniform_var.frame()
self.data.plotOn(self.uplot, roo.LineColor(self.color),
roo.MarkerColor(self.color))
self.uniform_pdf.plotOn(self.uplot, roo.Range(0, 1),
roo.LineColor(self.color))
cname = '_'.join(
[self.uniform_var.GetName(), 'of',
self.xvar.GetName()])
canvases.next(cname).SetGrid()
self.uplot.SetTitle('')
self.uplot.Draw()
def run(self):
## Set the range of deltaE to cover all the date plus a small margin.
mi = self.modal_interval
mi.setFraction(1.)
self.deltaE.setRange(mi.lowerBound() - 1, mi.upperBound() + 1)
self.model = ParameterizedKeysPdf(self.name + '_model',
self.name + '_model',
self.deltaE,
self.mode,
self.effsigma,
self.train_data,
rho=2)
mit = self.modal_interval_training
mit.setFraction(0.99)
fitrange = roo.Range(mit.lowerBound(), mit.upperBound())
self.fit_result = self.model.fitTo(self.fit_data, roo.NumCPU(8),
roo.Save(), fitrange)
self.fit_result.SetName(self.name + '_fit_result')
self.make_log_plot()
self.make_zoom_plot()
self.make_fixed_range_log_plot()
self.make_fixed_range_zoom_plot()
canvases.update()
xyplot = w.var('x').frame()
xyplot.SetTitle('')
xyplot.GetYaxis().SetTitle('y')
yvar.plotOn(xyplot)
canvases.next('exp_of_x').SetGrid()
xyplot.Draw()
yxplot = w.var('y').frame()
yxplot.SetTitle('')
yxplot.GetYaxis().SetTitle('x')
xvar.plotOn(yxplot)
canvases.next('log_of_y').SetGrid()
yxplot.Draw()
yplot = w.var('y').frame(roo.Range(0, 5))
yplot.SetTitle('')
data.plotOn(yplot)
fY.plotOn(yplot)
canvases.next('fY').SetGrid()
yplot.Draw()
xuplot = w.var('x').frame()
xuplot.SetTitle('')
xuplot.GetYaxis().SetTitle('u')
uvar.plotOn(xuplot)
canvases.next('cdf_of_x').SetGrid()
xuplot.Draw()
uplot = w.var('u').frame()
yplot.SetTitle('')
data = fX.generate(ROOT.RooArgSet(w.var('x')), 10000)
data.addColumn(FX)
xplot = w.var('x').frame()
xplot.SetTitle('')
data.plotOn(xplot)
fX.plotOn(xplot)
canvases.next('fX').SetGrid()
xplot.Draw()
xuplot = w.var('x').frame()
xuplot.SetTitle('')
xuplot.GetYaxis().SetTitle('u')
FX.plotOn(xuplot)
canvases.next('FX').SetGrid()
xuplot.Draw()
uplot = w.var('u').frame()
uplot.SetTitle('')
data.plotOn(uplot)
fU.plotOn(uplot, roo.Range(0, 1))
canvases.next('fU').SetGrid()
uplot.Draw()
canvases.update()
if __name__ == '__main__':
import user