def make_plots(configurations):
'''
For each configuration in the given list, overlays the graphs of
scale versus pt for all sets of measurements specified.
These measurements are either from the true or the PHOSPHOR fit.
'''
for cfg in configurations[:]:
## Only check EE 2011AB
#if (not 'EE_lowR9' in cfg.name) or (not 'AB' in cfg.name):
#continue
### Only check 2011AB
#if not 'AB' in cfg.name:
#continue
## MC, EB, 2011A+B, 1 of 4 statistically independent tests
plotter = FitResultPlotter(cfg.sources[0], cfg.getters[0], cfg.xtitle,
cfg.ytitle, title = cfg.titles[0],
name=cfg.name, yasymmerrors=True)
for isources, igetters, ititle in zip(cfg.sources,
cfg.getters,
cfg.titles):
plotter.sources = isources
plotter.getters = igetters
plotter.title = ititle
plotter.getdata()
plotter.makegraph()
canvases.next('c_' + cfg.name).SetGrid()
## Check if there is a problem with the ranges
yrange = 'auto'
for graph in plotter.graphs:
if (graph.GetHistogram().GetMaximum() -
graph.GetHistogram().GetMinimum()) < 0.1:
print cfg.name, graph.GetTitle(), 'min:', graph.GetMaximum(),
print ', max:', graph.GetMaximum
yrange = (-5, 10)
plotter.plotall(title = cfg.title,
xrange = (5, 55),
yrange = yrange,
legend_position = 'topright')
#plotter.graphs[0].Draw('p')
canvases.canvases[-1].Modified()
canvases.canvases[-1].Update()
canvases.update()
plotters.append(plotter)
def plot_xy(xname, yname, filemask, xtype='var', ytype='var'):
filename = filemask % ptbinedges[0]
## Mass scale vs photon scale
frp = FitResultPlotter(
sources = sources(filename, wsname),
getters = xygetters(xname, yname, xtype, ytype),
xtitle = axistitles[xname],
ytitle = axistitles[yname],
title = 'Dummy Legend Entry',
)
for ptrange in ptbinedges:
filename = filemask % ptrange
frp.sources = sources(filename, wsname)
frp.title = 'E_{T}^{#gamma} #in [%d, %d] GeV' % ptrange
frp.getdata()
frp.makegraph()
canvases.next(yname + '_vs_' + xname).SetGrid()
frp.plotall(title = ptitle)
frps.append(frp)
def make_plots(configurations):
"""
For each configuration in the given list, overlays the graphs of
scale versus pt for all sets of measurements specified.
These measurements are either from the true or the PHOSPHOR fit.
"""
for cfg in configurations[:]:
## Only check EE 2011AB
# if (not 'EE_lowR9' in cfg.name) or (not 'AB' in cfg.name):
# continue
### Only check 2011AB
# if not 'AB' in cfg.name:
# continue
## MC, EB, 2011A+B, 1 of 4 statistically independent tests
plotter = FitResultPlotter(
cfg.sources[0],
cfg.getters[0],
cfg.xtitle,
cfg.ytitle,
title=cfg.titles[0],
name=cfg.name,
xasymmerrors=True,
yasymmerrors=True,
colors=[ROOT.kBlack],
)
for isources, igetters, ititle in zip(cfg.sources, cfg.getters, cfg.titles):
plotter.sources = isources
plotter.getters = igetters
plotter.title = ititle
plotter.getdata()
plotter.makegraph()
plotter.graph.Fit("pol1")
canvases.next("c_" + cfg.name).SetGrid()
plotter.graph.Draw("ap")
plotter.graph.GetXaxis().SetTitle(cfg.xtitle)
plotter.graph.GetYaxis().SetTitle(cfg.ytitle)
# if 'EE_highR9' in cfg.name:
# plotter.plotall(title = cfg.title,
##xrange = (0, 10),
##yrange = (0, 10),
# legend_position = 'topright')
# else:
# plotter.plotall(title = cfg.title,
##xrange = (5, 55),
# legend_position = 'topright')
# plotter.graphs[0].Draw('p')
canvases.canvases[-1].Modified()
canvases.canvases[-1].Update()
canvases.update()
plotters.append(plotter)
def make_plots(configurations):
'''
For each configuration in the given list, overlays the graphs of
scale versus pt for all sets of measurements specified.
These measurements are either from the true or the PHOSPHOR fit.
'''
for cfg in configurations[:]:
## Only check EE 2011AB
#if (not 'EE_lowR9' in cfg.name) or (not 'AB' in cfg.name):
#continue
### Only check 2011AB
#if not 'AB' in cfg.name:
#continue
## MC, EB, 2011A+B, 1 of 4 statistically independent tests
plotter = FitResultPlotter(cfg.sources[0], cfg.getters[0], cfg.xtitle,
cfg.ytitle, title = cfg.titles[0],
name=cfg.name)
for isources, igetters, ititle in zip(cfg.sources,
cfg.getters,
cfg.titles):
plotter.sources = isources
plotter.getters = igetters
plotter.title = ititle
plotter.getdata()
plotter.makegraph()
canvases.next('c_' + cfg.name).SetGrid()
plotter.plotall(title = cfg.title,
xrange = (5, 55),
legend_position = 'topright')
#plotter.graphs[0].Draw('p')
canvases.canvases[-1].Modified()
canvases.canvases[-1].Update()
canvases.update()
plotters.append(plotter)
]
oplus = lambda x, y: sqrt(x * x + y * y)
for cfg in cfgs:
#------------------------------------------------------------------------------
## Scale Comparison
## PDF Morph: m translation for photon scale
frp = FitResultPlotter(
sources=zip(cfg.filenames, cfg.wsnames, cfg.strue_snapshots),
getters=(
lambda ws, i=iter(bincenters): i.next(), # x
lambda ws, i=iter(ktransmc[cfg.name]['sreco']): (
ws.var('#Deltas').getVal() + i.next() # y
),
lambda ws, i=iter(binhalfwidths): i.next(), # ex
lambda ws, i=iter(ktransmc[cfg.name]['esreco']):
(oplus(ws.var('#Deltas').getError(), i.next())), # ey
),
xtitle='E_{T}^{#gamma} (GeV)',
ytitle='s_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)',
title='PDF Morph',
)
frp.getdata()
frp.makegraph()
## New Baseline
frp.sources = zip(cfg.filenames, cfg.wsnames, cfg.sreco_snapshots)
frp.getters = var_vs_pt('#Deltas')
frp.title = 'Baseline'
frp.getdata()
"""Returns functions that take a workspaces ws and return
x, y, ex, ey where y and ey correspond to workspace
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
)
categories = [c.name for c in cats]
workspaces = ['ws1'] * n
snapshot = 'sFit_strue_mc_Nominal{f}_mmMass80_{c}_PhoEt{l}-{h}_bifurGauss'
plotter = FitResultPlotter(None, None)
for etar9 in cats:
frp = FitResultPlotter(
sources='dummy',
getters=var_vs_pt('#Deltas'),
xtitle='E_{T}^{#gamma} (GeV)',
ytitle='s_{gen} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1 (%)',
)
for fitrange, title in zip(['FitRange' + x for x in '65 68 71'.split()],
'-3% Nominal +3%'.split()):
filenames = [os.path.join(path, 'strue_%s.root' % fitrange)] * n
snapshots = [
snapshot.format(f=fitrange, c=etar9.name, l=lo, h=hi)
for lo, hi in binedges
]
frp.sources = zip(filenames, workspaces, snapshots)
sgen_snapshots = ['sFit_sgen_mc_mmMass80_EB_lowR9_cbShape_PhoEt%d-%d_iter0' % (lo, hi)
for lo, hi in binedges]
def var_vs_pt(name):
"""Returns functions that take a workspaces ws and return
x, y, ex, ey where y and ey correspond to workspace
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()
def make_resolution_plots():
'''
Makes canvases with resolution plots.
'''
global plotters
#==========================================================================
for cfg in get_resolution_configs()[:]:
## MC, EB, 2011A+B, 1 of 4 statistically independent tests
xtitle = 'E_{T}^{#gamma} (GeV)'
ytitle = 'E^{#gamma} Resolution (%)'
plotter = FitResultPlotter(cfg.sources1, cfg.getters1, xtitle, ytitle,
title = 'MC Truth')
plotter.getdata()
plotter.makegraph()
plotter.sources = cfg.sources2
plotter.getters = cfg.getters2
plotter.title = 'MC Fit'
plotter.getdata()
plotter.makegraph()
plotter.sources = cfg.sources3
plotter.getters = cfg.getters3
plotter.title = 'Data Fit'
plotter.getdata()
plotter.makegraph()
canvases.next('c_' + cfg.name).SetGrid()
plotter.plotall(title = cfg.title,
styles = [20, 25, 26],
colors = [ROOT.kBlack, ROOT.kBlue, ROOT.kRed])
plotters.append(plotter)
% (lo, hi) for lo, hi in binedges],
## MC truth scale
strue_snapshots = ['sFit_strue_mc_bifurGauss_mmMass90_EE_highR9_'
'PhoEt%d-%d' % (lo, hi) for lo, hi in binedges],
),
]
for cfg in cfgs:
#------------------------------------------------------------------------------
## Scale Comparison
## Baseline v2
frp = FitResultPlotter(
sources = zip(cfg.filenames1, cfg.wsnames, cfg.sreco_snapshots1),
getters = var_vs_pt('#Deltas'),
xtitle = 'E_{T}^{#gamma} (GeV)',
ytitle = 's_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)',
title = 'Baseline v2',
)
frp.getdata()
frp.makegraph()
## Proposal 2
frp.sources = zip(cfg.filenames2, cfg.wsnames, cfg.sreco_snapshots2)
frp.getters = var_vs_pt('#Deltas')
frp.title = 'm_{#mu#mu} < 90 GeV'
frp.getdata()
frp.makegraph()
## True
frp.sources = zip(cfg.filenames2, cfg.wsnames, cfg.strue_snapshots)
def var_vs_pt(name):
"""Returns functions that take a workspaces ws and return
x, y, ex, ey where y and ey correspond to workspace
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()
def var_vs_pt(name):
"""Returns functions that take a workspaces ws and return
x, y, ex, ey where y and ey correspond to workspace
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
)
categories = [c.name for c in cats]
workspaces = ['ws1'] * n
snapshot = 'sFit_strue_mc_Nominal{f}_mmMass80_{c}_PhoEt{l}-{h}_bifurGauss'
plotter = FitResultPlotter(None, None)
for etar9 in cats:
frp = FitResultPlotter(
sources = 'dummy',
getters = var_vs_pt('#Deltas'),
xtitle = 'E_{T}^{#gamma} (GeV)',
ytitle = 's_{gen} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1 (%)',
)
for fitrange, title in zip(['FitRange' + x for x in '65 68 71'.split()],
'-3% Nominal +3%'.split()):
filenames = [os.path.join(path, 'strue_%s.root' % fitrange)] * n
snapshots = [snapshot.format(f=fitrange, c=etar9.name, l=lo, h=hi)
for lo, hi in binedges]
frp.sources = zip(filenames, workspaces, snapshots)
frp.getters = var_vs_pt('#Deltas')
frp.title = title
lambda ws: ws.var(name).getVal(), # y
lambda ws, i = iter(binhalfwidths): i.next(), # ex
lambda ws: ws.var(name).getError(), # ey
)
plotters = []
#------------------------------------------------------------------------------
## Scale Comparison
## Lyon
frp = FitResultPlotter(
sources = zip(filenames, wsnames, sreco_snapshots),
getters = (
lambda ws, i = iter(bincenters): i.next(), # x
lambda ws, i = iter(sreco_lyon): i.next(), # y
lambda ws, i = iter(binhalfwidths): i.next(), # ex
lambda ws, i = iter(esreco_lyon): i.next(), # ey
),
xtitle = 'E_{T}^{#gamma} (GeV)',
ytitle = 's_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)',
title = 'Lyon',
)
frp.getdata()
frp.makegraph()
## Caltech
frp.getters = var_vs_pt('#Deltas')
frp.title = 'Caltech'
frp.getdata()
frp.makegraph()
## Compare Caltech and Lyon scale
sgen_snapshots = ['sFit_sgen_mc_mmMass80_EB_lowR9_cbShape_PhoEt%d-%d_iter0' % (lo, hi)
for lo, hi in binedges]
def var_vs_pt(name):
"""Returns functions that take a workspaces ws and return
x, y, ex, ey where y and ey correspond to workspace
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),
lambda ws, i=iter(binhalfwidths): i.next(), # ex
lambda ws: ws.var(name).getError(), # ey
)
plotters = []
#------------------------------------------------------------------------------
## Scale Comparison
## Lyon
frp = FitResultPlotter(
sources=zip(filenames, wsnames, sreco_snapshots),
getters=(
lambda ws, i=iter(bincenters): i.next(), # x
lambda ws, i=iter(sreco_lyon): i.next(), # y
lambda ws, i=iter(binhalfwidths): i.next(), # ex
lambda ws, i=iter(esreco_lyon): i.next(), # ey
),
xtitle='E_{T}^{#gamma} (GeV)',
ytitle='s_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)',
title='Lyon',
)
frp.getdata()
frp.makegraph()
## Caltech
frp.getters = var_vs_pt('#Deltas')
frp.title = 'Caltech'
frp.getdata()
frp.makegraph()
## Compare Caltech and Lyon scale
'sFit_strue_mc_bifurGauss_mmMass80_EE_highR9_'
'PhoEt%d-%d' % (lo, hi) for lo, hi in binedges
],
),
]
for cfg in cfgs:
#------------------------------------------------------------------------------
## Scale Comparison
## Lyon
frp = FitResultPlotter(
sources=zip(cfg.filenames, cfg.wsnames, cfg.sreco_snapshots),
getters=(
lambda ws, i=iter(bincenters): i.next(), # x
lambda ws, i=iter(lyonmc[cfg.name]['sreco']): i.next(), # y
lambda ws, i=iter(binhalfwidths): i.next(), # ex
lambda ws, i=iter(lyonmc[cfg.name]['esreco']): i.next(), # ey
),
xtitle='E_{T}^{#gamma} (GeV)',
ytitle='s_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)',
title='Lyon',
)
frp.getdata()
frp.makegraph()
## Caltech
frp.getters = var_vs_pt('#Deltas')
frp.title = 'Caltech'
frp.getdata()
frp.makegraph()
## True
def make_resolution_plots(configurations):
'''
For each configuration in the given list, overlays the graphs of
resolution versus pt for all sets of measurements specified.
These measurements are either from the true or the PHOSPHOR fit.
'''
for cfg in configurations[:]:
### Only check 2011AB
#if not 'AB' in cfg.name:
#continue
## MC, EB, 2011A+B, 1 of 4 statistically independent tests
plotter = FitResultPlotter(cfg.sources[1], cfg.getters_true[1], cfg.xtitle,
cfg.ytitle, title = 'MC Truth 1', name=cfg.name)
for i in range(1,5):
plotter.sources = cfg.sources[i]
plotter.getters = cfg.getters_true[i]
plotter.title = 'MC Truth %d' % i
plotter.getdata()
plotter.makegraph()
for i in range(1,5):
plotter.sources = cfg.sources[i]
plotter.getters = cfg.getters_fit[i]
plotter.title = 'MC Fit %d' % i
plotter.getdata()
plotter.makegraph()
canvases.next('c_' + cfg.name).SetGrid()
plotter.plotall(title = cfg.title,
xrange = (0, 80),
legend_position = 'topright')
plotter.graphs[0].Draw('p')
canvases.canvases[-1].Modified()
canvases.canvases[-1].Update()
canvases.update()
plotters.append(plotter)
sources3 = make_list_of_sources(jobname_template3),
getters1 = var_vs_pt_getter_factory('phoResTrue'),
getters2 = var_vs_pt_getter_factory('phoRes'),
getters3 = var_vs_pt_fitresult_getter_factory(fitresult,
'phoRes'),
)
resolution_configurations.append(cfg)
## End of loop categories
plotters = []
#==============================================================================
for cfg in scale_configurations[:]:
## MC, EB, 2011A+B, 1 of 4 statistically independent tests
plotter = FitResultPlotter(cfg.sources1, cfg.getters1, cfg.xtitle,
cfg.ytitle, title = 'MC Truth')
plotter.getdata()
plotter.makegraph()
plotter.sources = cfg.sources2
plotter.getters = cfg.getters2
plotter.title = 'MC Fit'
plotter.getdata()
plotter.makegraph()
plotter.sources = cfg.sources3
plotter.getters = cfg.getters3
plotter.title = 'Data Fit'
plotter.getdata()
plotter.makegraph()
sources3 = make_list_of_sources(jobname_template3),
getters1 = var_vs_pt_getter_factory('phoScaleTrue'),
getters2 = var_vs_pt_getter_factory('#Deltas'),
getters3 = var_vs_pt_getter_factory('phoScale'),
)
scale_configurations.append(cfg)
## End of loop categories
plotters = []
#==============================================================================
for cfg in scale_configurations[:]:
## MC, EB, 2011A+B, 1 of 4 statistically independent tests
xtitle = 'E_{T}^{#gamma} (GeV)'
ytitle = 'E^{#gamma} Scale (%)'
plotter = FitResultPlotter(cfg.sources1, cfg.getters1, xtitle, ytitle,
title = 'MC Truth')
plotter.getdata()
plotter.makegraph()
plotter.sources = cfg.sources2
plotter.getters = cfg.getters2
plotter.title = '2011 Baseline'
plotter.getdata()
plotter.makegraph()
plotter.sources = cfg.sources3
plotter.getters = cfg.getters3
plotter.title = 'PHOSPHOR'
plotter.getdata()
plotter.makegraph()
def var_vs_pt(name):
"""Returns functions that take a workspaces ws and return
x, y, ex, ey where y and ey correspond to workspace
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),
]
oplus = lambda x, y: sqrt(x*x + y*y)
for cfg in cfgs:
#------------------------------------------------------------------------------
## Scale Comparison
## PDF Morph: m translation for photon scale
frp = FitResultPlotter(
sources = zip(cfg.filenames, cfg.wsnames, cfg.strue_snapshots),
getters = (
lambda ws, i = iter(bincenters): i.next(), # x
lambda ws, i = iter(ktransmc[cfg.name]['sreco']): (
ws.var('#Deltas').getVal() + i.next() # y
),
lambda ws, i = iter(binhalfwidths): i.next(), # ex
lambda ws, i = iter(ktransmc[cfg.name]['esreco']): (
oplus(ws.var('#Deltas').getError(), i.next())
), # ey
),
xtitle = 'E_{T}^{#gamma} (GeV)',
ytitle = 's_{reco} = E^{#gamma}_{reco}/E^{kin}_{reco} - 1 (%)',
title = 'PDF Morph',
)
frp.getdata()
frp.makegraph()
## New Baseline
frp.sources = zip(cfg.filenames, cfg.wsnames, cfg.sreco_snapshots)
frp.getters = var_vs_pt('#Deltas')
frp.title = 'Baseline'
frp.getdata()
