def prep_reco(TTree, host_file, name):
"""Create the "reco" (~AdSimple) TTree and fill buffer.
Parameters
----------
host_file : ROOT.TFile
The TFile that will hold the reco TTree
name : str
The name of this TTree
Returns
-------
(reco_ttree, buffer) : tuple
The TTree object and the buffer used to fill its TBranches
"""
buf = root_util.TreeBuffer()
buf.triggerType = root_util.unsigned_int_value()
buf.site = root_util.int_value()
buf.energy = root_util.float_value()
buf.x = root_util.float_value()
buf.y = root_util.float_value()
buf.z = root_util.float_value()
host_file.cd()
event_subdir = host_file.Get("Event")
if not bool(event_subdir):
event_subdir = host_file.mkdir("Event")
event_subdir.cd()
rec_subdir = event_subdir.Get("Rec")
if not bool(rec_subdir):
rec_subdir = event_subdir.mkdir("Rec")
rec_subdir.cd()
long_name = "Tree at /Event/Rec/{name} holding Rec_{name}".format(
name=name)
reco = TTree(name, long_name)
reco.Branch("context.mSite", buf.site, "context.mSite/I")
reco.Branch("triggerType", buf.triggerType, "triggerType/i")
reco.Branch("energy", buf.energy, "energy/F")
reco.Branch("x", buf.x, "x/F")
reco.Branch("y", buf.y, "y/F")
reco.Branch("z", buf.z, "z/F")
return reco, buf
def prep_truth(TTree, host_file):
"""Create the MC Truth TTree (named MCTruth) and fill buffer.
Parameters
----------
host_file : ROOT.TFile
The TFile that will hold the MC Truth TTree
Returns
-------
(mc_truth_ttree, buffer) : tuple
The TTree object and the buffer used to fill its TBranches
"""
buf = root_util.TreeBuffer()
buf.truth_index = root_util.unsigned_int_value()
host_file.cd()
name = "MCTruth"
long_name = "Monte Carlo Truth information for each entry"
mc_truth = TTree(name, long_name)
mc_truth.Branch("truth_index", buf.truth_index, "truth_index/i")
return mc_truth, buf
def prep_truth_lookup(TTree, host_file, event_types):
"""Create the MC Truth Lookup TTree (named MCTruthLookup) and fill buffer.
Each TBranch has a name which is either an integer, in which
case the value on that TBranch is an array of chars describing
the event subtype represented by that integer, or the converse:
a subtype name with an integer value. This way the expression
``MCTruthLookup->Show(0)`` will print out both directions of
lookup.
Parameters
----------
host_file : ROOT.TFile
The TFile that will hold the MC Truth Lookup TTree
event_types : list of :py:class:`EventType`
The list of EventType objects to add to the lookup table
Returns
-------
(mc_truth_lookup ttree, buffer) : tuple
The TTree object and the buffer used to fill its TBranches
"""
labels_by_number = []
numbers_by_label = []
for event_type in event_types:
event_labels = event_type.labels()
for number, label in event_labels.items():
if number is None or number < 0 or not isinstance(number, int):
raise InvalidLookupError(event_type.name, label, number)
numbers_by_label.append((label, number))
labels_by_number.append((number, label))
numbers_by_label.sort()
labels_by_number.sort()
max_label_length = max(len(x[0]) for x in numbers_by_label)
buf_size = max_label_length + 1
buf = root_util.TreeBuffer()
def new_singleton_array(value):
"""Return a simple singleton array with value of type
char*.
There's no root-util function for char arrays so I'm making my
own here. Further, python's built-in array.arrays are super
inconvenient for bytestrings/char arrays so I'm using
numpy.array instead. The "S{}" typecode means null-terminated
bytes array with max length of buf_size.
"""
type_format = "S{}".format(buf_size)
return np.array([value], type_format)
# Create and initialize the TreeBuffer buffers to the only
# values they'll ever take
for label, number in numbers_by_label:
setattr(buf, label, root_util.unsigned_int_value())
root_util.assign_value(getattr(buf, label), number)
for number, label in labels_by_number:
setattr(buf, "_{}".format(number), new_singleton_array(label))
host_file.cd()
name = "MCTruthLookup"
long_name = "Monte Carlo Truth lookup table"
mc_truth = TTree(name, long_name)
for label, number in numbers_by_label:
mc_truth.Branch(label, getattr(buf, label), "{}/i".format(label))
for number, label in labels_by_number:
name = "_{}".format(number)
mc_truth.Branch(name, getattr(buf, name),
"{}[{}]/C".format(name, buf_size))
mc_truth.Fill()
return mc_truth, buf
def create_computed_TTree(name, host_file, selection_name, title=None):
from ROOT import TTree
git_description = git_describe()
if title is None:
title = ('Computed quantities by Sam Kohn (git: %s)' %
git_description)
else:
try:
title = title % git_description
except:
pass
host_file.cd()
outdata = TTree(name, title)
# Initialize the "buffer" used to fill values into the TTree
buffer_depth = 20
fill_buf = TreeBuffer()
fill_buf.loopIndex = unsigned_int_value(buffer_depth)
fill_buf.multiplicity = unsigned_int_value()
fill_buf.timestamp = long_value(buffer_depth)
fill_buf.timestamp_seconds = int_value(buffer_depth)
fill_buf.timestamp_nanoseconds = int_value(buffer_depth)
fill_buf.detector = int_value(buffer_depth)
fill_buf.dt_to_prompt = long_value(buffer_depth)
fill_buf.dr_to_prompt = float_value(buffer_depth)
fill_buf.dt_cluster_to_prev_ADevent = long_value()
fill_buf.site = int_value()
fill_buf.run = unsigned_int_value()
fill_buf.fileno = unsigned_int_value()
fill_buf.triggerNumber = int_value(buffer_depth)
fill_buf.triggerType = unsigned_int_value(buffer_depth)
fill_buf.nHit = int_value(buffer_depth)
fill_buf.charge = float_value(buffer_depth)
fill_buf.fQuad = float_value(buffer_depth)
fill_buf.fMax = float_value(buffer_depth)
fill_buf.fPSD_t1 = float_value(buffer_depth)
fill_buf.fPSD_t2 = float_value(buffer_depth)
fill_buf.f2inch_maxQ = float_value(buffer_depth)
fill_buf.Q1 = float_value(buffer_depth)
fill_buf.Q2 = float_value(buffer_depth)
fill_buf.energy = float_value(buffer_depth)
fill_buf.x = float_value(buffer_depth)
fill_buf.y = float_value(buffer_depth)
fill_buf.z = float_value(buffer_depth)
fill_buf.fID = float_value(buffer_depth)
fill_buf.fPSD = float_value(buffer_depth)
fill_buf.dt_previous_WSMuon = long_value(buffer_depth)
fill_buf.dt_previous_ADMuon = long_value(buffer_depth)
fill_buf.dt_previous_ShowerMuon = long_value(buffer_depth)
def branch_multiple(name, typecode):
outdata.Branch(name, getattr(fill_buf, name), '{}[multiplicity]/{}'.format(
name, typecode))
return
def branch(name, typecode):
outdata.Branch(name, getattr(fill_buf, name), '{}/{}'.format(name,
typecode))
return
# Initialize the new TTree so that each TBranch reads from the
# appropriate TreeBuffer attribute
branch('multiplicity', 'i')
branch_multiple('loopIndex', 'i')
branch_multiple('timestamp', 'L')
branch_multiple('timestamp_seconds', 'I')
branch_multiple('timestamp_nanoseconds', 'I')
branch_multiple('detector', 'I')
branch_multiple('dt_to_prompt', 'L')
branch_multiple('dr_to_prompt', 'F')
branch('dt_cluster_to_prev_ADevent', 'L')
branch('site', 'I')
branch('run', 'i')
branch('fileno', 'i')
branch_multiple('triggerNumber', 'I')
branch_multiple('triggerType', 'I')
branch_multiple('nHit', 'I')
branch_multiple('charge', 'F')
branch_multiple('fQuad', 'F')
branch_multiple('fMax', 'F')
branch_multiple('fPSD_t1', 'F')
branch_multiple('fPSD_t2', 'F')
branch_multiple('f2inch_maxQ', 'F')
branch_multiple('Q1', 'F')
branch_multiple('Q2', 'F')
branch_multiple('energy', 'F')
branch_multiple('x', 'F')
branch_multiple('y', 'F')
branch_multiple('z', 'F')
branch_multiple('dt_previous_WSMuon', 'L')
branch_multiple('dt_previous_ADMuon', 'L')
branch_multiple('dt_previous_ShowerMuon', 'L')
return outdata, fill_buf