class PapasDisplay(Analyzer):
'''Plots a PAPAS event display
Example configuration:
from heppy.analyzers.PapasDisplay import PapasDisplay
papasdisplay = cfg.Analyzer(
PapasDisplay,
instance_label = 'papas',
detector = detector,
particles = 'papas_sim_particles',
clusters = ['ecal_clusters', 'hcal_clusters']
display = True
)
'''
def __init__(self, *args, **kwargs):
super(PapasDisplay, self).__init__(*args, **kwargs)
self.detector = self.cfg_ana.detector
self.is_display = self.cfg_ana.display
if self.is_display:
self.init_display()
def init_display(self):
self.display = Display(['xy', 'yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
def process(self, event):
particles = getattr(event, self.cfg_ana.particles)
if self.is_display:
self.display.clear()
self.display.register(GTrajectories(particles), layer=1)
for clustername in self.cfg_ana.clusters:
blobs = map(Blob, getattr(event, clustername).values())
self.display.register(blobs, layer=1, clearable=False)
from heppy.display.geometry import GDetector
from heppy.display.pfobjects import GTrajectories
display_on = True
detector = cms
logging.basicConfig(level='WARNING')
logger = logging.getLogger('Simulator')
logger.addHandler(logging.StreamHandler(sys.stdout))
for i in range(1):
if not i % 100:
print i
simulator = Simulator(detector, logger)
# particles = monojet([211, -211, 130, 22, 22, 22], math.pi/2., math.pi/2., 2, 50)
particles = [
# particle(211, math.pi/2., math.pi/2., 100),
particle(211, math.pi / 2 + 0.5, 0., 40.),
# particle(130, math.pi/2., math.pi/2.+0., 100.),
# particle(22, math.pi/2., math.pi/2.+0.0, 10.)
]
simulator.simulate(particles)
if display_on:
display = Display(['xy', 'yz', 'ECAL_thetaphi', 'HCAL_thetaphi'])
gdetector = GDetector(detector)
display.register(gdetector, 0)
gtrajectories = GTrajectories(simulator.ptcs)
display.register(gtrajectories, 1)
display.draw()
def init_display(self):
self.display = Display(['xy', 'yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
class PapasSim(Analyzer):
'''Runs PAPAS, the PArametrized Particle Simulation.
#This will need to redocumented once new papasdata structure arrives
Example configuration:
from heppy.analyzers.PapasSim import PapasSim
from heppy.papas.detectors.CMS import CMS
papas = cfg.Analyzer(
PapasSim,
instance_label = 'papas',
detector = CMS(),
gen_particles = 'gen_particles_stable',
sim_particles = 'sim_particles',
merged_ecals = 'ecal_clusters',
merged_hcals = 'hcal_clusters',
tracks = 'tracks',
#rec_particles = 'sim_rec_particles', # optional - will only do a simulation reconstruction if a name is provided
output_history = 'history_nodes',
display_filter_func = lambda ptc: ptc.e()>1.,
display = False,
verbose = True
)
detector: Detector model to be used.
gen_particles: Name of the input gen particle collection
sim_particles: Name extension for the output sim particle collection.
Note that the instance label is prepended to this name.
Therefore, in this particular case, the name of the output
sim particle collection is "papas_sim_particles".
merged_ecals: Name for the merged clusters created by simulator
merged_hcals: Name for the merged clusters created by simulator
tracks: Name for smeared tracks created by simulator
rec_particles: Optional. Name extension for the reconstructed particles created by simulator
This is retained for the time being to allow two reconstructions to be compared
Reconstruction will occur if this parameter or rec_particles_no_leptons is provided
Same comments as for the sim_particles parameter above.
rec_particles_no_leptons: Optional. Name extension for the reconstructed particles created by simulator
without electrons and muons
Reconstruction will occur if this parameter or rec_particles is provided
This is retained for the time being to allow two reconstructions to be compared
Same comments as for the sim_particles parameter above.
smeared: Name for smeared leptons
history: Optional name for the history nodes, set to None if not needed
display : Enable the event display
verbose : Enable the detailed printout.
event must contain
todo once history is implemented
event will gain
ecal_clusters:- smeared merged clusters from simulation
hcal_clusters:- smeared merged clusters from simulation
tracks: - tracks from simulation
baseline_particles:- simulated particles (excluding electrons and muons)
sim_particles - simulated particles including electrons and muons
'''
def __init__(self, *args, **kwargs):
super(PapasSim, self).__init__(*args, **kwargs)
self.detector = self.cfg_ana.detector
self.simulator = Simulator(self.detector, self.mainLogger)
self.simname = '_'.join(
[self.instance_label, self.cfg_ana.sim_particles])
self.tracksname = self.cfg_ana.tracks
self.mergedecalsname = self.cfg_ana.merged_ecals
self.mergedhcalsname = self.cfg_ana.merged_hcals
self.historyname = self.cfg_ana.output_history
self.is_display = self.cfg_ana.display
if self.is_display:
self.init_display()
def init_display(self):
self.display = Display(['xy', 'yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
def process(self, event):
event.simulator = self
if self.is_display:
self.display.clear()
pfsim_particles = []
gen_particles = getattr(event, self.cfg_ana.gen_particles)
try:
self.simulator.simulate(gen_particles)
except (PropagationError, SimulationError) as err:
self.mainLogger.error(str(err) + ' -> Event discarded')
return False
pfsim_particles = self.simulator.ptcs
if self.is_display:
self.display.register(GTrajectories(pfsim_particles), layer=1)
#these are the particles before simulation
simparticles = sorted(pfsim_particles,
key=lambda ptc: ptc.e(),
reverse=True)
setattr(event, self.simname, simparticles)
#extract the tracks and clusters (extraction is prior to Colins merging step)
event.tracks = dict()
event.ecal_clusters = dict()
event.hcal_clusters = dict()
if "tracker" in self.simulator.pfinput.elements:
for element in self.simulator.pfinput.elements["tracker"]:
event.tracks[element.uniqueid] = element
if "ecal_in" in self.simulator.pfinput.elements:
for element in self.simulator.pfinput.elements["ecal_in"]:
event.ecal_clusters[element.uniqueid] = element
if "hcal_in" in self.simulator.pfinput.elements:
for element in self.simulator.pfinput.elements["hcal_in"]:
event.hcal_clusters[element.uniqueid] = element
ruler = Distance()
#create history node
#note eventually history will be created by the simulator and passed in
# as an argument and this will no longer be needed
uniqueids = list(event.tracks.keys()) + list(
event.ecal_clusters.keys()) + list(event.hcal_clusters.keys())
history = dict((idt, Node(idt)) for idt in uniqueids)
#Now merge the simulated clusters and tracks as a separate pre-stage (prior to new reconstruction)
# and set the event to point to the merged cluster
pfevent = PFEvent(event, 'tracks', 'ecal_clusters', 'hcal_clusters')
merged_ecals = MergedClusterBuilder(pfevent.ecal_clusters, ruler,
history)
setattr(event, self.mergedecalsname, merged_ecals.merged)
merged_hcals = MergedClusterBuilder(pfevent.hcal_clusters, ruler,
merged_ecals.history_nodes)
setattr(event, self.mergedhcalsname, merged_hcals.merged)
setattr(event, self.historyname, merged_hcals.history_nodes)
from heppy.display.geometry import GDetector
from heppy.display.pfobjects import GTrajectories
display_on = True
detector = cms
logging.basicConfig(level="WARNING")
logger = logging.getLogger("Simulator")
logger.addHandler(logging.StreamHandler(sys.stdout))
for i in range(1):
if not i % 100:
print i
simulator = Simulator(detector, logger)
# particles = monojet([211, -211, 130, 22, 22, 22], math.pi/2., math.pi/2., 2, 50)
particles = [
# particle(211, math.pi/2., math.pi/2., 100),
particle(211, math.pi / 2 + 0.5, 0.0, 40.0),
# particle(130, math.pi/2., math.pi/2.+0., 100.),
# particle(22, math.pi/2., math.pi/2.+0.0, 10.)
]
simulator.simulate(particles)
if display_on:
display = Display(["xy", "yz", "ECAL_thetaphi", "HCAL_thetaphi"])
gdetector = GDetector(detector)
display.register(gdetector, 0)
gtrajectories = GTrajectories(simulator.ptcs)
display.register(gtrajectories, 1)
display.draw()
class PapasDisplay(Analyzer):
'''Plots a PAPAS event display
Can be used to produce a single event plot or a comparative event plot.
Example configuration::
#(single event plot)
from heppy.analyzers.PapasDisplay import PapasDisplay
papasdisplay = cfg.Analyzer(
PapaDisplay,
projections = ['xy', 'yz'],
screennames = ["simulated"],
particles_type_and_subtypes = ['ps'],
clusters_type_and_subtypes = [['es', 'hs']],
detector = detector,
save = True,
display = True
)
#(comparative event plot)
from heppy.analyzers.PapasDisplay import PapasDisplay
papasdisplay = cfg.Analyzer(
PapaDisplay,
projections = ['xy', 'yz'],
screennames = ["simulated", "reconstructed"],
particles_type_and_subtypes = ['ps', 'pr'],
clusters_type_and_subtypes = [['es', 'hs'],['em', 'hm']],
detector = detector,
save = True,
display = True
)
@param projections: list of projections eg ['xy', 'yz', 'xz' ,'ECAL_thetaphi', 'HCAL_thetaphi']
these will be separate windows
@param subscreens: list of names of panels within each window eg subscreens=["simulated", "reconstructed"]
each of the projection windows will contain all of the subscreens
the subscreens can be used to show different aspects of an event, eg simulated particles and reconstructed particles
@param particles_type_and_subtypes: list of type_and_subtypes of particles (eg ['ps', 'pr']).
List must be same length as subscreens. Each element of list says which particles to plot on the corresponding subscreen.
@param clusters_type_and_subtypes: list of type_and_subtypes of clusters (eg [['es', 'hs'],['em', 'hm']]).
The list must be same length as subscreens, and each element should itself be a list.
Each element of the list says which clusters to plot on the corresponding subscreen.
More than one cluster type may be plotted on a single screen.
@param detector: the detector to be plotted
@param save: boolean, if True will save graph to png file.
@param display: boolean, if True will plot graph to screen.
'''
def __init__(self, *args, **kwargs):
super(PapasDisplay, self).__init__(*args, **kwargs)
self.compare = False
nscreens = len(self.cfg_ana.screennames)
if nscreens == 2:
self.compare = True
if (len(self.cfg_ana.particles_type_and_subtypes) != nscreens or
len(self.cfg_ana.clusters_type_and_subtypes) != nscreens):
raise Exception("Inconsistent display options: screennames, particles_type_and_subtypes and clusters_type_and_subtypes argument lists must have same length")
if self.cfg_ana.do_display:
self.init_display()
def init_display(self):
'''Set up the display'''
self.display = Display(self.cfg_ana.projections, self.cfg_ana.screennames)
self.gdetector = GDetector(self.cfg_ana.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
def process(self, event):
'''Selects the required particles and clusters and registers them on the display
@param event: event that must contain a papasevent'''
if not self.cfg_ana.do_display:
return
self.display.clear()
for i in range(len(self.cfg_ana.screennames)):
particles_collection = event.papasevent.get_collection(self.cfg_ana.particles_type_and_subtypes[i])
if particles_collection:
self.register_particles(particles_collection.values(), i)
for type_and_subtype in self.cfg_ana.clusters_type_and_subtypes[i]:
cluster_collection = event.papasevent.get_collection(type_and_subtype)
if cluster_collection:
self.register_clusters(cluster_collection.values(), i)
def register_particles(self, particles, side=0):
'''
Adds list of particles into the display
@param particles: list of particles to append to display
@param side: 0 = left, 1 = right
'''
self.display.register(GTrajectories(particles), layer=2, sides=[side])
if self.compare:
otherside = (side + 1)%2 #opposite side
self.display.register(GTrajectories(particles, is_grey=True), layer=1, sides=[otherside])
def register_clusters(self, clusters, side=0):
'''Adds list of clusters into the display
@param clusters: list of clusters to append to display
@param side: 0 = left, 1 = right'''
blobs = map(Blob, clusters)
self.display.register(blobs, layer=2, clearable=True, sides=[side])
if self.compare:
otherside = (side + 1)%2
mapfunc = partial(Blob, grey=True)
blobs = map(mapfunc, clusters)
self.display.register(blobs, layer=1, clearable=True, sides=[otherside])
def init_display(self):
'''Set up the display'''
self.display = Display(self.cfg_ana.projections, self.cfg_ana.screennames)
self.gdetector = GDetector(self.cfg_ana.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
pass
else:
raise ValueError('implement drawing for projection ' + projection )
class GDetector(object):
def __init__(self, description):
self.desc = description
elems = sorted(self.desc.elements.values(), key= lambda x : x.volume.outer.rad, reverse = True)
self.elements = [GDetectorElement(elem) for elem in elems]
#self.elements = [GDetectorElement(elem) for elem in self.desc.elements.values()]
def draw(self, projection):
for elem in self.elements:
elem.draw(projection)
if __name__ == '__main__':
from ROOT import TCanvas, TH2F
from heppy.papas.detectors.CMS import CMS
from heppy.display.core import Display
cms = CMS()
gcms = GDetector(cms)
display = Display()
display.register(gcms, 0)
display.draw()
def init_display(self):
self.display = Display(['xy','yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
class PapasSim(Analyzer):
'''Runs PAPAS, the PArametrized Particle Simulation.
Example configuration:
from heppy.analyzers.PapasSim import PapasSim
from heppy.papas.detectors.CMS import CMS
papas = cfg.Analyzer(
PapasSim,
instance_label = 'papas',
detector = CMS(),
gen_particles = 'gen_particles_stable',
sim_particles = 'sim_particles',
rec_particles = 'rec_particles',
display = False,
verbose = False
)
detector: Detector model to be used.
gen_particles: Name of the input gen particle collection
sim_particles: Name extension for the output sim particle collection.
Note that the instance label is prepended to this name.
Therefore, in this particular case, the name of the output
sim particle collection is "papas_sim_particles".
rec_particles: Name extension for the output reconstructed particle collection.
Same comments as for the sim_particles parameter above.
display : Enable the event display
verbose : Enable the detailed printout.
'''
def __init__(self, *args, **kwargs):
super(PapasSim, self).__init__(*args, **kwargs)
self.detector = self.cfg_ana.detector
self.simulator = Simulator(self.detector,
self.mainLogger)
self.simname = '_'.join([self.instance_label, self.cfg_ana.sim_particles])
self.recname = '_'.join([self.instance_label, self.cfg_ana.rec_particles])
self.is_display = self.cfg_ana.display
if self.is_display:
self.init_display()
def init_display(self):
self.display = Display(['xy','yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
def process(self, event):
event.simulator = self
if self.is_display:
self.display.clear()
pfsim_particles = []
gen_particles = getattr(event, self.cfg_ana.gen_particles)
self.simulator.simulate( gen_particles )
pfsim_particles = self.simulator.ptcs
if self.is_display:
self.display.register( GTrajectories(pfsim_particles),
layer=1)
simparticles = sorted( pfsim_particles,
key = lambda ptc: ptc.e(), reverse=True)
particles = sorted( self.simulator.particles,
key = lambda ptc: ptc.e(), reverse=True)
setattr(event, self.simname, simparticles)
pfinput = PFInput(simparticles)
event.tracks = dict()
event.ECALclusters = dict()
event.HCALclusters = dict()
for label, element in pfinput.elements.iteritems():
if label == 'tracker':
event.tracks[0,id(element)]=element
elif label == 'ecal_in':
event.ECALclusters[1,id(element)]=element
elif label == 'hcal_in':
event.HCALclusters[2,id(element)]=element
else:
print label
assert(False)
setattr(event, self.recname, particles)
class Papas(Analyzer):
'''Runs PAPAS, the PArametrized Particle Simulation.
Papas reads a list of stable generated particles,
and creates a list of reconstruted particles.
First, the particles are extrapolated in the magnetic field
through the tracker and to the calorimeters,
and the particle deposits are simulated using a parametrized simulation.
Then, a particle flow algorithm is used to connect the simulated tracks
and calorimeter energy deposits, and to identify and reconstruct
final state particles.
Example:
from heppy.analyzers.Papas import Papas
from heppy.papas.detectors.CMS import CMS
papas = cfg.Analyzer(
Papas,
instance_label = 'papas',
detector = CMS(),
gen_particles = 'gen_particles_stable',
sim_particles = 'sim_particles',
rec_particles = 'particles',
display = False,
verbose = True
)
detector: Detector model to be used, here CMS.
gen_particles: Name of the input gen particle collection
sim_particles: Name for the output sim particle collection.
rec_particles: Name for the output reconstructed particle collection.
display : Enable the event display
verbose : Enable the detailed printout.
'''
def __init__(self, *args, **kwargs):
super(Papas, self).__init__(*args, **kwargs)
self.detector = self.cfg_ana.detector
self.simulator = Simulator(self.detector,
self.mainLogger)
self.is_display = self.cfg_ana.display
if self.is_display:
self.init_display()
def init_display(self):
self.display = Display(['xy','yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
def process(self, event):
event.simulator = self
if self.is_display:
self.display.clear()
pfsim_particles = []
gen_particles = getattr(event, self.cfg_ana.gen_particles)
self.simulator.simulate( gen_particles )
pfsim_particles = self.simulator.ptcs
if self.is_display:
particles_for_display = pfsim_particles
if hasattr(self.cfg_ana, 'display_filter_func'):
particles_for_display = [ ptc for ptc in pfsim_particles if
self.cfg_ana.display_filter_func(ptc) ]
self.display.register( GTrajectories(particles_for_display),
layer=1)
simparticles = sorted( pfsim_particles,
key = lambda ptc: ptc.e(), reverse=True)
particles = sorted( self.simulator.particles,
key = lambda ptc: ptc.e(), reverse=True)
setattr(event, self.cfg_ana.sim_particles, simparticles)
setattr(event, self.cfg_ana.rec_particles, particles)
class PapasDisplay(Analyzer):
'''Plots a PAPAS event display
Can be used to produce a single event plot or a comparative event plot.
Example configuration::
#(single event plot)
from heppy.analyzers.PapasDisplay import PapasDisplay
papasdisplay = cfg.Analyzer(
PapaDisplay,
projections = ['xy', 'yz'],
screennames = ["simulated"],
particles_type_and_subtypes = ['ps'],
clusters_type_and_subtypes = [['es', 'hs']],
detector = detector,
save = True,
display = True
)
#(comparative event plot)
from heppy.analyzers.PapasDisplay import PapasDisplay
papasdisplay = cfg.Analyzer(
PapaDisplay,
projections = ['xy', 'yz'],
screennames = ["simulated", "reconstructed"],
particles_type_and_subtypes = ['ps', 'pr'],
clusters_type_and_subtypes = [['es', 'hs'],['em', 'hm']],
detector = detector,
save = True,
display = True
)
@param projections: list of projections eg ['xy', 'yz', 'xz' ,'ECAL_thetaphi', 'HCAL_thetaphi']
these will be separate windows
@param subscreens: list of names of panels within each window eg subscreens=["simulated", "reconstructed"]
each of the projection windows will contain all of the subscreens
the subscreens can be used to show different aspects of an event, eg simulated particles and reconstructed particles
@param particles_type_and_subtypes: list of type_and_subtypes of particles (eg ['ps', 'pr']).
List must be same length as subscreens. Each element of list says which particles to plot on the corresponding subscreen.
@param clusters_type_and_subtypes: list of type_and_subtypes of clusters (eg [['es', 'hs'],['em', 'hm']]).
The list must be same length as subscreens, and each element should itself be a list.
Each element of the list says which clusters to plot on the corresponding subscreen.
More than one cluster type may be plotted on a single screen.
@param detector: the detector to be plotted
@param save: boolean, if True will save graph to png file.
@param display: boolean, if True will plot graph to screen.
'''
def __init__(self, *args, **kwargs):
super(PapasDisplay, self).__init__(*args, **kwargs)
self.compare = False
nscreens = len(self.cfg_ana.screennames)
if nscreens == 2:
self.compare = True
if (len(self.cfg_ana.particles_type_and_subtypes) != nscreens or
len(self.cfg_ana.clusters_type_and_subtypes) != nscreens):
raise Exception("Inconsistent display options: screennames, particles_type_and_subtypes and clusters_type_and_subtypes argument lists must have same length")
if self.cfg_ana.do_display:
self.init_display()
def init_display(self):
'''Set up the display'''
self.display = Display(self.cfg_ana.projections, self.cfg_ana.screennames)
self.gdetector = GDetector(self.cfg_ana.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
def process(self, event):
'''Selects the required particles and clusters and registers them on the display
@param event: event that must contain a papasevent'''
if not self.cfg_ana.do_display:
return
self.display.clear()
for i in range(len(self.cfg_ana.screennames)):
particles_collection = event.papasevent.get_collection(self.cfg_ana.particles_type_and_subtypes[i])
if particles_collection:
self.register_particles(particles_collection.values(), i)
for type_and_subtype in self.cfg_ana.clusters_type_and_subtypes[i]:
clusters = event.papasevent.get_collection(type_and_subtype)
if clusters:
self.register_clusters(clusters.values(), i)
def register_particles(self, particles, side=0):
'''
Adds list of particles into the display
@param particles: list of particles to append to display
@param side: 0 = left, 1 = right
'''
self.display.register(GTrajectories(particles), layer=2, sides=[side])
if self.compare:
otherside = (side + 1)%2 #opposite side
self.display.register(GTrajectories(particles, is_grey=True), layer=1, sides=[otherside])
def register_clusters(self, clusters, side=0):
'''Adds list of clusters into the display
@param clusters: list of clusters to append to display
@param side: 0 = left, 1 = right'''
blobs = map(Blob, clusters)
self.display.register(blobs, layer=2, clearable=True, sides=[side])
if self.compare:
otherside = (side + 1)%2
mapfunc = partial(Blob, grey=True)
blobs = map(mapfunc, clusters)
self.display.register(blobs, layer=1, clearable=True, sides=[otherside])
def init_display(self):
'''Set up the display'''
self.display = Display(self.cfg_ana.projections, self.cfg_ana.screennames)
self.gdetector = GDetector(self.cfg_ana.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
class PapasSim(Analyzer):
'''Runs PAPAS, the PArametrized Particle Simulation.
Example configuration:
from heppy.analyzers.PapasSim import PapasSim
from heppy.papas.detectors.CMS import CMS
papas = cfg.Analyzer(
PapasSim,
instance_label = 'papas',
detector = CMS(),
gen_particles = 'gen_particles_stable',
sim_particles = 'sim_particles',
merged_ecals = 'ecal_clusters',
merged_hcals = 'hcal_clusters',
tracks = 'tracks',
#rec_particles = 'sim_rec_particles', # optional - will only do a simulation reconstruction if a name is provided
output_history = 'history_nodes',
display_filter_func = lambda ptc: ptc.e()>1.,
display = False,
verbose = True
)
detector: Detector model to be used.
gen_particles: Name of the input gen particle collection
sim_particles: Name extension for the output sim particle collection.
Note that the instance label is prepended to this name.
Therefore, in this particular case, the name of the output
sim particle collection is "papas_sim_particles".
merged_ecals: Name for the merged clusters created by simulator
merged_hcals: Name for the merged clusters created by simulator
tracks: Name for smeared tracks created by simulator
rec_particles: Optional. Name extension for the reconstructed particles created by simulator
This is retained for the time being to allow two reconstructions to be compared
Reconstruction will occur if this parameter or rec_particles_no_leptons is provided
Same comments as for the sim_particles parameter above.
rec_particles_no_leptons: Optional. Name extension for the reconstructed particles created by simulator
without electrons and muons
Reconstruction will occur if this parameter or rec_particles is provided
This is retained for the time being to allow two reconstructions to be compared
Same comments as for the sim_particles parameter above.
smeared: Name for smeared leptons
history: Optional name for the history nodes, set to None if not needed
display : Enable the event display
verbose : Enable the detailed printout.
'''
def __init__(self, *args, **kwargs):
super(PapasSim, self).__init__(*args, **kwargs)
self.detector = self.cfg_ana.detector
self.simulator = Simulator(self.detector, self.mainLogger)
self.simname = '_'.join([self.instance_label, self.cfg_ana.sim_particles])
self.tracksname = self.cfg_ana.tracks
self.mergedecalsname = self.cfg_ana.merged_ecals
self.mergedhcalsname = self.cfg_ana.merged_hcals
self.historyname = self.cfg_ana.output_history
#decide if reconstruction is needed
self.do_reconstruct = False
if hasattr(self.cfg_ana, 'rec_particles') :
self.do_reconstruct = True
self.recname = '_'.join([self.instance_label, self.cfg_ana.rec_particles])
#if hasattr(self.cfg_ana, 'rec_particles_no_leptons') :
# self.do_reconstruct = True
# self.rec_noleptonsname = '_'.join([self.instance_label, self.cfg_ana.rec_particles_no_leptons])
self.is_display = self.cfg_ana.display
if self.is_display:
self.init_display()
def init_display(self):
self.display = Display(['xy','yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
def process(self, event):
'''
event must contain the
event will gain
ecal_clusters:- smeared merged clusters from simulation
hcal_clusters:- smeared merged clusters from simulation
tracks: - tracks from simulation
baseline_particles:- simulated particles (excluding electrons and muons)
sim_particles - simulated particles including electrons and muons
'''
event.simulator = self
if self.is_display:
self.display.clear()
pfsim_particles = []
gen_particles = getattr(event, self.cfg_ana.gen_particles)
self.simulator.simulate( gen_particles, self.do_reconstruct)
pfsim_particles = self.simulator.ptcs
if self.is_display:
self.display.register( GTrajectories(pfsim_particles),
layer=1)
#these are the particles before simulation
simparticles = sorted( pfsim_particles,
key = lambda ptc: ptc.e(), reverse=True)
setattr(event, self.simname, simparticles)
if self.do_reconstruct: # used for verification/ comparison of reconstruction methods
#these are the reconstructed (via simulation) particles including electrons and muons
particles = sorted( self.simulator.particles,
key = lambda ptc: ptc.e(), reverse=True)
#these are the reconstructed (via simulation) particles excluding muons and electrons
#origparticles = sorted( self.simulator.pfsequence.pfreco.particles,
# key = lambda ptc: ptc.e(), reverse=True)
if hasattr(self, 'recname') :
setattr(event, self.recname, particles)
#if hasattr(self, 'rec_noleptonsname') :
# setattr(event, self.rec_noleptonsname, origparticles)
#extract the tracks and clusters (extraction is prior to Colins merging step)
event.tracks = dict()
event.ecal_clusters = dict()
event.hcal_clusters = dict()
if "tracker" in self.simulator.pfinput.elements :
for element in self.simulator.pfinput.elements["tracker"]:
event.tracks[element.uniqueid] = element
if "ecal_in" in self.simulator.pfinput.elements :
for element in self.simulator.pfinput.elements["ecal_in"]:
event.ecal_clusters[element.uniqueid] = element
if "hcal_in" in self.simulator.pfinput.elements :
for element in self.simulator.pfinput.elements["hcal_in"]:
event.hcal_clusters[element.uniqueid] = element
ruler = Distance()
#create history node
#note eventually history will be created by the simulator and passed in
# as an argument and this will no longer be needed
uniqueids = list(event.tracks.keys()) + list(event.ecal_clusters.keys()) + list(event.hcal_clusters.keys())
history = dict( (idt, Node(idt)) for idt in uniqueids )
#Now merge the simulated clusters and tracks as a separate pre-stage (prior to new reconstruction)
# and set the event to point to the merged cluster
pfevent = PFEvent(event, 'tracks', 'ecal_clusters', 'hcal_clusters')
merged_ecals = MergedClusterBuilder(pfevent.ecal_clusters, ruler, history)
setattr(event, self.mergedecalsname, merged_ecals.merged)
merged_hcals = MergedClusterBuilder(pfevent.hcal_clusters, ruler, merged_ecals.history_nodes)
setattr(event, self.mergedhcalsname, merged_hcals.merged)
setattr(event, self.historyname, merged_hcals.history_nodes)
####if uncommented this will use the original reconstructions to provide the ready merged tracks and clusters
#event.ecal_clusters = dict()
#event.hcal_clusters = dict()
#for element in self.simulator.pfsequence.elements :
#elif element.__class__.__name__ == 'SmearedCluster' and element.layer == 'ecal_in':
#event.ecal_clusters[element.uniqueid] = element
#elif element.__class__.__name__ == 'SmearedCluster' and element.layer == 'hcal_in':
#event.hcal_clusters[element.uniqueid] = element
#else :
#print element.__class__.__name__
#assert(False)
###if uncommented will check that cluster merging is OK (compare new merging module with Colins merging)
#event.origecal_clusters = dict()
#event.orighcal_clusters = dict()
#for element in self.simulator.pfsequence.elements :
#if element.__class__.__name__ == 'SmearedCluster' and element.layer == 'ecal_in':
#event.origecal_clusters[element.uniqueid] = element
#elif element.__class__.__name__ == 'SmearedCluster' and element.layer == 'hcal_in':
#event.orighcal_clusters[element.uniqueid] = element
#ClusterComparer(event.origecal_clusters,event.ecal_clusters)
#ClusterComparer(event.orighcal_clusters,event.hcal_clusters)
#event.othertracks = dict()
#for element in self.simulator.pfsequence.elements :
#if element.__class__.__name__ == 'SmearedTrack':
#event.othertracks[element.uniqueid] = element
#assert (len(event.tracks) == len(event.othertracks))
pass
class PapasSim(Analyzer):
'''Runs PAPAS, the PArametrized Particle Simulation.
#This will need to redocumented once new papasdata structure arrives
Example configuration:
from heppy.analyzers.PapasSim import PapasSim
from heppy.papas.detectors.CMS import CMS
papas = cfg.Analyzer(
PapasSim,
instance_label = 'papas',
detector = CMS(),
gen_particles = 'gen_particles_stable',
sim_particles = 'sim_particles',
merged_ecals = 'ecal_clusters',
merged_hcals = 'hcal_clusters',
tracks = 'tracks',
#rec_particles = 'sim_rec_particles', # optional - will only do a simulation reconstruction if a name is provided
output_history = 'history_nodes',
display_filter_func = lambda ptc: ptc.e()>1.,
display = False,
verbose = True
)
detector: Detector model to be used.
gen_particles: Name of the input gen particle collection
sim_particles: Name extension for the output sim particle collection.
Note that the instance label is prepended to this name.
Therefore, in this particular case, the name of the output
sim particle collection is "papas_sim_particles".
merged_ecals: Name for the merged clusters created by simulator
merged_hcals: Name for the merged clusters created by simulator
tracks: Name for smeared tracks created by simulator
rec_particles: Optional. Name extension for the reconstructed particles created by simulator
This is retained for the time being to allow two reconstructions to be compared
Reconstruction will occur if this parameter or rec_particles_no_leptons is provided
Same comments as for the sim_particles parameter above.
rec_particles_no_leptons: Optional. Name extension for the reconstructed particles created by simulator
without electrons and muons
Reconstruction will occur if this parameter or rec_particles is provided
This is retained for the time being to allow two reconstructions to be compared
Same comments as for the sim_particles parameter above.
smeared: Name for smeared leptons
history: Optional name for the history nodes, set to None if not needed
display : Enable the event display
verbose : Enable the detailed printout.
event must contain
todo once history is implemented
event will gain
ecal_clusters:- smeared merged clusters from simulation
hcal_clusters:- smeared merged clusters from simulation
tracks: - tracks from simulation
baseline_particles:- simulated particles (excluding electrons and muons)
sim_particles - simulated particles including electrons and muons
'''
def __init__(self, *args, **kwargs):
super(PapasSim, self).__init__(*args, **kwargs)
self.detector = self.cfg_ana.detector
self.simulator = Simulator(self.detector, self.mainLogger)
self.simname = '_'.join([self.instance_label, self.cfg_ana.sim_particles])
self.tracksname = self.cfg_ana.tracks
self.mergedecalsname = self.cfg_ana.merged_ecals
self.mergedhcalsname = self.cfg_ana.merged_hcals
self.historyname = self.cfg_ana.output_history
self.is_display = self.cfg_ana.display
if self.is_display:
self.init_display()
def init_display(self):
self.display = Display(['xy', 'yz'])
self.gdetector = GDetector(self.detector)
self.display.register(self.gdetector, layer=0, clearable=False)
self.is_display = True
def process(self, event):
event.simulator = self
if self.is_display:
self.display.clear()
pfsim_particles = []
gen_particles = getattr(event, self.cfg_ana.gen_particles)
try:
self.simulator.simulate(gen_particles)
except (PropagationError, SimulationError) as err:
self.mainLogger.error(str(err) + ' -> Event discarded')
return False
pfsim_particles = self.simulator.ptcs
if self.is_display :
self.display.register(GTrajectories(pfsim_particles),
layer=1)
#these are the particles before simulation
simparticles = sorted(pfsim_particles,
key=lambda ptc: ptc.e(), reverse=True)
setattr(event, self.simname, simparticles)
#extract the tracks and clusters (extraction is prior to Colins merging step)
event.tracks = dict()
event.ecal_clusters = dict()
event.hcal_clusters = dict()
if "tracker" in self.simulator.pfinput.elements :
for element in self.simulator.pfinput.elements["tracker"]:
event.tracks[element.uniqueid] = element
if "ecal_in" in self.simulator.pfinput.elements :
for element in self.simulator.pfinput.elements["ecal_in"]:
event.ecal_clusters[element.uniqueid] = element
if "hcal_in" in self.simulator.pfinput.elements :
for element in self.simulator.pfinput.elements["hcal_in"]:
event.hcal_clusters[element.uniqueid] = element
ruler = Distance()
#create history node
#note eventually history will be created by the simulator and passed in
# as an argument and this will no longer be needed
uniqueids = list(event.tracks.keys()) + list(event.ecal_clusters.keys()) + list(event.hcal_clusters.keys())
history = dict((idt, Node(idt)) for idt in uniqueids)
#Now merge the simulated clusters and tracks as a separate pre-stage (prior to new reconstruction)
# and set the event to point to the merged cluster
pfevent = PFEvent(event, 'tracks', 'ecal_clusters', 'hcal_clusters')
merged_ecals = MergedClusterBuilder(pfevent.ecal_clusters, ruler, history)
setattr(event, self.mergedecalsname, merged_ecals.merged)
merged_hcals = MergedClusterBuilder(pfevent.hcal_clusters, ruler, merged_ecals.history_nodes)
setattr(event, self.mergedhcalsname, merged_hcals.merged)
setattr(event, self.historyname, merged_hcals.history_nodes)