class lpcAnalyser(object):
def __init__(self, filename):
'''
Constructor
'''
self._parser = lpcAnalysisParser(filename)
self._initReader()
self._initResiduals()
self._initPruner()
self._setOutputFilename()
self._initPurity()
def _initReader(self):
run_parameters = self._parser.getReadParameters()
if run_parameters['type'] == 'lpcAnalysisPickleReader':
self._reader = lpcAnalysisPickleReader(**run_parameters['params'])
else:
raise ValueError, 'Specified type of reader is not recognised'
def _initResiduals(self):
residual_parameters = self._parser.getResidualsParameters()
if residual_parameters['type'] == 'LPCResiduals':
tau_range = residual_parameters['params'].pop('tau_range')
self._residuals = LPCResiduals(**residual_parameters['params'])
self._residuals_runner = LPCResidualsRunner(self._residuals, tau_range)
else:
raise ValueError, 'Specified type of residuals calculator is not recognised'
def _initPruner(self):
pruner_parameters = self._parser.getPrunerParameters()
if pruner_parameters['type'] == 'lpcCurvePruner':
self._pruner = lpcCurvePruner(self._residuals_runner, **pruner_parameters['params'])
else:
raise ValueError, 'Specified type of residuals calculator is not recognised'
def _setOutputFilename(self):
misc = self._parser.getMiscParameters()
self._output_filename = misc['params']['output_filename']
def _initPurity(self):
self._purity = LPCPurityCalculator(self._residuals_runner)
def runAnalyser(self):
out_data = []
while 1:
try:
evt = self._reader.getNextEvent()
self._residuals.setDataPoints(evt[0]['Xi'])
self._residuals_runner.setLpcCurves(evt[0]['lpc_curve'])
self._residuals_runner.calculateResiduals(calc_residuals = False, calc_containment_matrix = False)
remaining_curves = self._pruner.pruneCurves()
#muon_proton_hits = truth_evt.getParticleHits([13, 2212])
#eff = LPCEfficiencyCalculator(remaining_curves, evt['data_range'], muon_proton_hits, tau) TODO - move from examples/toytracks
voxel_to_pdg_dictionary = evt[1].getParticlesInVoxelDict()
pur = self._purity.calculatePurity(remaining_curves, evt[0]['data_range'], voxel_to_pdg_dictionary)
out_data.append({'voxel_dict': voxel_to_pdg_dictionary, 'pur': pur})
except EOFError:
break
#TODO - factor this out into a class which enters the analysis configuration file
outfile = open(self._output_filename, 'w')
cPickle.dump(out_data, outfile, -1)
def LPCEfficiencyCalculator(curves, data_range, particle_hits, tau):
#first rescale the curves then calculate the proton and muon efficiency
if data_range is None:
data_range = 1.0
muon_hits = array([[h[0][0], h[0][1], h[0][2]] for h in particle_hits[13]]) / data_range
proton_hits = array([[h[0][0], h[0][1], h[0][2]] for h in particle_hits[2212]]) / data_range
residuals_calc = LPCResiduals(muon_hits, tube_radius = 0.12)
residuals_runner = LPCResidualsRunner(curves, residuals_calc)
residuals_runner.setTauRange([tau])
muon_residuals = residuals_runner.calculateResiduals(True, False, False)
muon_coverage = max([len(muon_residuals['curve_residuals'][i]['coverage_indices'][tau]) for i in range(len(curves))])
muon_efficiency = float(muon_coverage) / len(muon_hits)
residuals_calc.setDataPoints(proton_hits)
proton_residuals = residuals_runner.calculateResiduals(True, False, False)
proton_coverage = max([len(proton_residuals['curve_residuals'][i]['coverage_indices'][tau]) for i in range(len(curves))])
proton_efficiency = float(proton_coverage) / len(proton_hits)
print 'residuals'
