getDDneutronEnergy)
from utilities.ionStopping import ionStopping
argParser = argparse.ArgumentParser()
argParser.add_argument('-run', choices=[0, 1, 2, 3], default=0, type=int)
parsedArgs = argParser.parse_args()
runNumber = parsedArgs.run
standoff = {
0: distances.tunlSSA_CsI.standoffMid,
1: distances.tunlSSA_CsI.standoffClose,
2: distances.tunlSSA_CsI.standoffClose,
3: distances.tunlSSA_CsI.standoffFar
}
standoffName = {0: 'mid', 1: 'close', 2: 'close', 3: 'far'}
tofWindowSettings = tofWindows()
##############
# vars for binning of TOF
# this range covers each of the 4 multi-standoff runs
#tof_nBins = 120
#tof_minRange = 130.0
#tof_maxRange = 250.0
tof_nBins = tofWindowSettings.nBins[standoffName[runNumber]]
tof_minRange = tofWindowSettings.minRange[standoffName[runNumber]]
tof_maxRange = tofWindowSettings.maxRange[standoffName[runNumber]]
tof_range = (tof_minRange, tof_maxRange)
eD_bins = 150
eD_minRange = 200.0
eD_maxRange = 1700.0
eD_range = (eD_minRange, eD_maxRange)
def __init__(self,
chainFilename,
nSamplesFromTOF,
nBins_eD=100,
nBins_x=20,
nRuns=4):
"""Create a PPC tools object - reads in chain from file"""
self.chain, self.probs, self.nParams, self.nWalkers, self.nSteps = readChainFromFile(
chainFilename)
self.nRuns = nRuns
self.eD_bins = nBins_eD
self.eD_minRange = 200.0
self.eD_maxRange = 1200.0
self.eD_range = (self.eD_minRange, self.eD_maxRange)
self.eD_binSize = (self.eD_maxRange - self.eD_minRange) / self.eD_bins
self.eD_binCenters = np.linspace(
self.eD_minRange + self.eD_binSize / 2,
self.eD_maxRange - self.eD_binSize / 2, self.eD_bins)
self.eD_binMax = self.eD_bins - 1
self.x_bins = nBins_x
self.x_minRange = 0.0
self.x_maxRange = distances.tunlSSA_CsI.cellLength
self.x_range = (self.x_minRange, self.x_maxRange)
self.x_binSize = (self.x_maxRange - self.x_minRange) / self.x_bins
self.x_binCenters = np.linspace(self.x_minRange + self.x_binSize / 2,
self.x_maxRange - self.x_binSize / 2,
self.x_bins)
# parameters for making the fake data...
self.nEvPerLoop = nSamplesFromTOF
self.nSamplesFromTOF = nSamplesFromTOF
self.data_x = np.repeat(self.x_binCenters, self.nEvPerLoop)
self.ddnXSinstance = ddnXSinterpolator()
self.beamTiming = beamTimingShape()
self.zeroDegTimeSpreader = zeroDegreeTimingSpread()
# stopping power model and parameters
stoppingMedia_Z = 1
stoppingMedia_A = 2
stoppingMedia_rho = 8.565e-5 # from red notebook, p 157
incidentIon_charge = 1
stoppingMedia_meanExcitation = 19.2 * 1e-3
dgas_materialDef = [
stoppingMedia_Z, stoppingMedia_A, stoppingMedia_rho,
stoppingMedia_meanExcitation
]
#stoppingModel = ionStopping.simpleBethe( stoppingModelParams )
self.stoppingModel = ionStopping.simpleBethe([incidentIon_charge])
self.stoppingModel.addMaterial(dgas_materialDef)
self.eN_binCenters = getDDneutronEnergy(self.eD_binCenters)
tofWindowSettings = tofWindows()
tof_nBins = tofWindowSettings.nBins
self.tof_minRange = [
tofWindowSettings.minRange['mid'],
tofWindowSettings.minRange['close'],
tofWindowSettings.minRange['close'],
tofWindowSettings.minRange['far'],
tofWindowSettings.minRange['production']
]
self.tof_maxRange = [
tofWindowSettings.maxRange['mid'],
tofWindowSettings.maxRange['close'],
tofWindowSettings.maxRange['close'],
tofWindowSettings.maxRange['far'],
tofWindowSettings.maxRange['production']
]
self.tof_range = []
for minR, maxR in zip(self.tof_minRange, self.tof_maxRange):
self.tof_range.append((minR, maxR))
self.tofRunBins = [
tof_nBins['mid'], tof_nBins['close'], tof_nBins['close'],
tof_nBins['far'], tof_nBins['production']
]
self.standoffs = [
distances.tunlSSA_CsI.standoffMid,
distances.tunlSSA_CsI.standoffClose,
distances.tunlSSA_CsI.standoffClose,
distances.tunlSSA_CsI.standoffFar,
distances.tunlSSA_CsI.standoff_TUNLruns
]
self.tofData = None
self.neutronSpectra = None
self.paramNames = [
'$E_0$', '$f_1$', '$f_2$', '$f_3$', '$N_1$', '$N_2$', '$N_3$',
'$N_4$', '$N_5$'
]