def __init__(self, data_dir, run_number, config):
Converter.__init__(self, data_dir, run_number, config)
# DIRECTORIES
self.EUDAQDir = self.SoftDir.joinpath(self.Config.get('SOFTWARE', 'eudaq2'))
self.ProteusSoftDir = self.SoftDir.joinpath(self.Config.get('SOFTWARE', 'proteus'))
self.ProteusDataDir = self.DataDir.joinpath('proteus')
# FILENAMES
self.ROOTFileName = join(self.SaveDir, 'run{:06d}.root'.format(self.RunNumber))
self.AlignSteps = self.get_align_steps()
self.TrackFileName = join(self.ProteusDataDir, 'track-{:04d}-data.root'.format(self.RunNumber))
self.MatchFileName = join(self.ProteusDataDir, 'match-{:04d}-trees.root'.format(self.RunNumber))
self.FinalFileName = join(self.SaveDir, 'run{:04d}.hdf5'.format(self.RunNumber))
self.FileNames = [self.ROOTFileName] + self.get_align_files() + [self.TrackFileName, self.MatchFileName, self.FinalFileName]
self.NSteps = len(self.FileNames)
self.NTelPlanes = self.Config.getint('TELESCOPE', 'planes')
self.NDUTPlanes = self.Config.getint('DUT', 'planes')
# FILES
self.F = None
self.TrackFile = TFile()
self.MatchFile = TFile()
self.Draw = Draw()
def __init__(self, filename, plane, config, save_dir=None, first_run=None):
Converter.__init__(self, filename, config)
self.SaveDir = save_dir
self.CalibrationDir = join(self.SaveDir, 'calibrations')
self.RunNumber = basename(filename).strip('.root').split('_')[-1]
self.FirstRun = first_run if first_run is not None else self.RunNumber
self.OldFile = read_root_file(filename)
self.OldTree = self.OldFile.Get('Plane{}'.format(6 +
plane)).Get('Hits')
self.EventTree = self.OldFile.Get('Event')
self.NewFile = self.create_new_file(filename, save_dir)
self.NewTree = self.OldTree.CloneTree(0)
# New Branches
self.ScalarBranches = OrderedDict([('NCluster', array([0], 'u2')),
('TimeStamp', array([0], 'f8'))])
self.VectorBranches = OrderedDict([('VCal', vector('float')()),
('ClusterSize',
vector('unsigned short')()),
('ClusterX', vector('float')()),
('ClusterY', vector('float')()),
('ClusterVcal', vector('float')())])
# Charge Fits
self.FitParameters = zeros((52, 80, 4))
self.Fit = TF1('ErFit', '[3] * (TMath::Erf((x - [0]) / [1]) + [2])',
-500, 255 * 7)
self.get_fits()
# Vars
self.Hits = []
self.ClusteredHits = []
self.Clusters = []
self.ProgressBar = None