variable of a given name and x and ex are pt bins."""
return (
lambda ws, i = iter(bincenters): i.next(), # x
lambda ws: ws.var(name).getVal(), # y
lambda ws, i = iter(binhalfwidths): i.next(), # ex
lambda ws: ws.var(name).getError(), # ey
)
frp = FitResultPlotter(
sources = zip(filenames, wsnames, strue_snapshots),
getters = var_vs_pt('#Deltas'),
xtitle = 'E_{T}^{#gamma} (GeV)',
ytitle = 's_{true} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1 (%)'
)
canvases.next()
frp.main()
print frp.ytitle
frp.dump()
print
## MC truth resolution
# canvases.next()
# frp.main(getters = var_vs_pt('#sigma'),
# ytitle = '#sigma(E^{#gamma}_{reco}/E^{#gamma}_{gen})')
# frp.dump()
## Scale from mmg
canvases.next()
frp.main(sources = zip(filenames, wsnames, sreco_snapshots),
getters = var_vs_pt('#Deltas'),
ytitle = 's_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)')
variable of a given name and x and ex are pt bins."""
return (
lambda ws, i = iter(bincenters): i.next(), # x
lambda ws: ws.var(name).getVal(), # y
lambda ws, i = iter(binhalfwidths): i.next(), # ex
lambda ws: ws.var(name).getError(), # ey
)
frp = FitResultPlotter(
sources = zip(filenames, wsnames, strue_snapshots),
getters = var_vs_pt('#Deltas'),
xtitle = 'E_{T}^{#gamma} (GeV)',
ytitle = 's_{true} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1 (%)'
)
canvases.next()
frp.main()
## MC truth resolution
# canvases.next()
# frp.main(getters = var_vs_pt('#sigma'),
# ytitle = '#sigma(E^{#gamma}_{reco}/E^{#gamma}_{gen})')
# frp.dump()
## Scale from mmg
canvases.next()
frp.main(sources = zip(filenames, wsnames, sreco_snapshots),
getters = var_vs_pt('#Deltas'),
ytitle = 's_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)')
## Lyon's scale from mmg
canvases.next()
return (
lambda ws, i=iter(bincenters): i.next(), # x
lambda ws: ws.var(name).getVal(), # y
lambda ws, i=iter(binhalfwidths): i.next(), # ex
lambda ws: ws.var(name).getError(), # ey
)
frp = FitResultPlotter(
sources=zip(filenames, wsnames, strue_snapshots),
getters=var_vs_pt('#Deltas'),
xtitle='E_{T}^{#gamma} (GeV)',
ytitle='s_{true} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1 (%)')
canvases.next()
frp.main()
print frp.ytitle
frp.dump()
print
## MC truth resolution
# canvases.next()
# frp.main(getters = var_vs_pt('#sigma'),
# ytitle = '#sigma(E^{#gamma}_{reco}/E^{#gamma}_{gen})')
# frp.dump()
## Scale from mmg
canvases.next()
frp.main(sources=zip(filenames, wsnames, sreco_snapshots),
getters=var_vs_pt('#Deltas'),
ytitle='s_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)')
return (
lambda ws, i=iter(bincenters): i.next(), # x
lambda ws: ws.var(name).getVal(), # y
lambda ws, i=iter(binhalfwidths): i.next(), # ex
lambda ws: ws.var(name).getError(), # ey
)
frp = FitResultPlotter(
sources=zip(filenames, wsnames, strue_snapshots),
getters=var_vs_pt('#Deltas'),
xtitle='E_{T}^{#gamma} (GeV)',
ytitle='s_{true} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1 (%)')
canvases.next()
frp.main()
## MC truth resolution
# canvases.next()
# frp.main(getters = var_vs_pt('#sigma'),
# ytitle = '#sigma(E^{#gamma}_{reco}/E^{#gamma}_{gen})')
# frp.dump()
## Scale from mmg
canvases.next()
frp.main(sources=zip(filenames, wsnames, sreco_snapshots),
getters=var_vs_pt('#Deltas'),
ytitle='s_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)')
## Lyon's scale from mmg
canvases.next()
