tdcrpy package
This section provides documentation for the modules and classes in the project.
Submodules
tdcrpy.TDCRPy module
Created on Mon Jan 23 16:01:49 2023
A Monte-Carlo code to calculate detection efficiency in TDCR measurements
@author: Romain Coulon, Jialin Hu Bureau International des Poids et Mesures
- tdcrpy.TDCRPy.TDCRPy(L, TD, TAB, TBC, TAC, Rad, pmf_1, N, kB, V, mode, mode2, Display=False, barp=True)
This is the main function of the TDCRPy package running the Monte-Carlo Triple-to-Double Coincidence Ratio model. The computation is made for a given solution containing a radionuclide (or a mixture of radionuclides), a given volume of scintillator V and a given Birks constant kB.
It can operates in two modes:
–> In mode=”eff”, it calculates the efficiency of the TDCR system as a function of a value (triplet) of free parameter(s) L, the measurement data is not used;
—> In mode=”res”, it calculates the residual of the TDCR model parametrized by a value (or triplet) of free parameter(s) L and the measurement data TD, TAB, TBC, TAC.
also, two configuration can be set:
–> mode2=”sym”, where symmetry is considered between the 3 photomultiplier tubes - here L is a scalar and only the global TDCR value TD is used as measurement data.
—> mode2=”asym”, where an asymmetry between the 3 photomultiplier tubes is possible - here L is a triplet and only the specific TDCR values TAB, TBC, TAC are used as measurement data.
The parmeter N sets the number of Monte-Carlo trails used for the estimation. Each MC trial corresponds to a simulated radiactive decay. TDCRPY() used a set of fonctions from the tdcrpy.TDCR_model_lib module.
Advanced settings can be configured in the config.toml file.
–> By default Y = True so that the analytical model is applied for solution containing only pure beta emitting radionuclides. If you would like to apply the MC calculation also for these nuclides, set Y = False.
—> If you would like to change the number of bins nE to discretize the linear energy space for quenching calculation, you can change nE_electron and nE_alpha parameters for respectively electrons and alpha particles.
–> By default the calculation is set for Ultima-Gold cocktail mixed with a small amount of aqueous solution. You can adapt for a specific scintillator by changing the density, the mean charge number Z and the mean mass number A of the scintillator.
Parameters
- LFloat (if mode2=”sym”) or a tuple (if mode2=”asym”)
Free parameter in keV-1.
- TDfloat
triple-to-double coincidence ratio. Not consider if mode2=”asym”. Not consider if mode2=”asym”.
- TABfloat
triple-to-double coincidence ratio (coincidences between channel A and B). Not consider if mode2=”sym”.
- TBCfloat
triple-to-double coincidence ratio (coincidences between channel B and C). Not consider if mode2=”sym”.
- TACfloat
triple-to-double coincidence ratio (coincidences between channel A and C). Not consider if mode2=”sym”.
- Radstring
List of radionuclides (eg. “H-3, Co-60”).
- pmf_1string
list of probability of each radionuclide (eg. “0.8, 0.2”).
- Ninteger
Number of Monte-Carlo trials. recommanded N>10000 (see JCGM 101). Not applied in the case of pure beta emitting radionuclides.
- kBfloat
Birks constant in cm/keV.
- Vfloat
volume of the scintillator in ml. run only for 10 ml
- modestring
“res” to return the residual, “eff” to return efficiencies.
- mode2string
“sym” for symetrical model, “asym” for symetrical model.
- DisplayBoolean, optional
“True” to display details on the decay sampling. The default is False.
- barpBoolean, optional
“True” to display the calculation progress. The default is True.
Returns
- resfloat
Residuals of the model compared the measurement data for (a) given free parmeters L. (only in mode=”res”)
- mean_efficiency_Sfloat
Estimation of the efficiency of single counting events. (only in mode=”eff”)
- std_efficiency_Sfloat
Standard uncertainty from calculation associated with the estimation of the efficiency of single counting events. (only in mode=”eff”)
- mean_efficiency_Dfloat
Estimation of the efficiency of logic sum of double coincidences. (only in mode=”eff”)
- std_efficiency_Dfloat
Standard uncertainty from calculation associated with the estimation of the efficiency of logic sum of double coincidences. (only in mode=”eff”)
- mean_efficiency_Tfloat
Estimation of the efficiency of triple coincidences. (only in mode=”eff”)
- std_efficiency_Tfloat
Standard uncertainty from calculation associated with the estimation of the efficiency of triple coincidences. (only in mode=”eff”)
tdcrpy.TDCR_model_lib module
Created on Mon Jan 23 16:04:46 2023
Library of function of the TDCRpy code
@author: Romain Coulon, Jialin Hu Bureau International des Poids et Mesures
- tdcrpy.TDCR_model_lib.E_quench_a(e, kB, nE)
This function calculate the quenched energy alpha particles according to the Birks model of scintillation quenching
Parameters
- efloat
energy of the alpha particle in keV.
- kBfloat
Birks constant in cm/keV.
Returns
- float
Quenched energy in keV.
- tdcrpy.TDCR_model_lib.E_quench_e(e, kB, nE)
This function calculate the quenched energy of electrons according to the Birks model of scintillation quenching
Parameters
- efloat
energy of the electron in eV.
- kBfloat
Birks constant in cm/MeV.
Returns
- float
Quenched energy in eV.
- tdcrpy.TDCR_model_lib.TicTocGenerator()
Generator that returns time differences
- tdcrpy.TDCR_model_lib.clear_terminal()
Function to clear the terminal screen
- tdcrpy.TDCR_model_lib.display_header()
Function to display the header.
- tdcrpy.TDCR_model_lib.energie_dep_beta(e_inci, *, matrice10_1=array([[1.0, 2.0, 3.0, ..., 198.0, 199.0, 200.0], [0.0, 0.0, 0.0, ..., 5.1e-05, 4.7e-05, 5.7e-05], [0.0, 2e-06, 2e-06, ..., 7.7e-05, 7.4e-05, 7e-05], ..., [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0]]), matrice10_2=array([[200.0, 202.0, 204.0, ..., 1996.0, 1998.0, 2000.0], [5.7e-05, 4.9e-05, 5.6e-05, ..., 0.001795, 0.001826, 0.00181], [0.000494, 0.000489, 0.000492, ..., 0.000912, 0.000912, 0.000913], ..., [0.0, 0.0, 0.0, ..., 0.48222, 6.8e-05, 7e-05], [0.0, 0.0, 0.0, ..., 5e-06, 0.481935, 6.6e-05], [0.0, 0.0, 0.0, ..., 3e-06, 6e-06, 0.481512]]), matrice10_3=array([[2000.0, 2010.0, 2020.0, ..., 9980.0, 9990.0, 10000.0], [0.00181, 0.001776, 0.001775, ..., 0.012191, 0.012222, 0.012252], [0.004217, 0.004213, 0.004184, ..., 0.004783, 0.004785, 0.004751], ..., [0.0, 0.0, 0.0, ..., 0.000646, 1.4e-05, 1.5e-05], [0.0, 0.0, 0.0, ..., 1e-06, 0.000645, 1.5e-05], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.00065]]), ed=array([[0.0, 0.0, 0.0], [0.0002008, 0.001999, 0.009991], [0.0004016, 0.003998, 0.019982], ..., [0.2006, 1.997, 9.981], [0.2008, 1.999, 9.991], [0.201, 2.001, 10.001]]))
This function samples the energy deposited by an electron in the scintillator using response calculated by the Monte-Carlo code MCNP6.
Parameters
- e_incifloat
energy of the electron in keV.
- matrice10_1list[list], optional
response matrix for electrons in the range [1-200] keV and for a scintillator volume of 10 ml.
- matrice10_2list[list], optional
response matrix for electrons in the range [200-2000] keV and for a scintillator volume of 10 ml.
- matrice10_3list[list], optional
response matrix for electrons in the range [2000-10000] keV and for a scintillator volume of 10 ml.
- edlist[list], optional
matrix of input energies. column 0: [1-200] keV; column 1: [200-2000] keV; column 2: [2000-10000] keV
Returns
- resultfloat
deposited energy in keV.
- tdcrpy.TDCR_model_lib.energie_dep_gamma(e_inci, v, matrice10_1=array([[1.0, 2.0, 3.0, ..., 198.0, 199.0, 200.0], [0.0, 0.0, 0.0, ..., 1e-06, 2e-06, 2e-06], [0.0, 0.001795, 0.005885, ..., 0.873706, 0.87388, 0.87406], ..., [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0]]), matrice10_2=array([[200.0, 202.0, 204.0, ..., 1996.0, 1998.0, 2000.0], [2e-06, 1e-06, 0.0, ..., 4.5e-05, 4.2e-05, 4.8e-05], [0.877508, 0.877865, 0.878157, ..., 0.951362, 0.951381, 0.951434], ..., [0.0, 0.0, 0.0, ..., 3e-06, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 4e-06, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 4e-06]]), matrice10_3=array([[2000.0, 2010.0, 2020.0, ..., 9980.0, 9990.0, 10000.0], [6e-05, 3e-05, 8e-05, ..., 0.00017, 0.00019, 0.00015], [0.95212, 0.95221, 0.95236, ..., 0.97913, 0.97918, 0.97918], ..., [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0]]), matrice16_1=array([[1.0, 2.0, 3.0, ..., 198.0, 199.0, 200.0], [0.0, 0.0, 0.0, ..., 2e-06, 1e-06, 3e-06], [0.0, 0.001533, 0.005069, ..., 0.855719, 0.855893, 0.856118], ..., [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0]]), matrice16_2=array([[200.0, 202.0, 204.0, ..., 1996.0, 1998.0, 2000.0], [3e-06, 1e-06, 0.0, ..., 3.8e-05, 4.8e-05, 4.1e-05], [0.859989, 0.860337, 0.860676, ..., 0.943906, 0.943951, 0.944006], ..., [0.0, 0.0, 0.0, ..., 3e-06, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 4e-06, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 4e-06]]), matrice16_3=array([[2000.0, 2010.0, 2020.0, ..., 9980.0, 9990.0, 10000.0], [4.1e-05, 3.1e-05, 4.4e-05, ..., 0.000194, 0.00019, 0.000205], [0.944572, 0.944712, 0.944892, ..., 0.975521, 0.975553, 0.975526], ..., [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, ..., 0.0, 0.0, 0.0]]), ed=array([[0.0, 0.0, 0.0], [0.0002008, 0.001999, 0.009991], [0.0004016, 0.003998, 0.019982], ..., [0.2006, 1.997, 9.981], [0.2008, 1.999, 9.991], [0.201, 2.001, 10.001]]))
This function samples the energy deposited by a x or gamma rays in the scintillator using response calculated by the Monte-Carlo code MCNP6.
Parameters
- e_incifloat
energy of the photon in keV.
- vfloat
volume of the scintillator in ml.
- matrice10_1list[list], optional
response matrix for photons in the range [1-200] keV and for a scintillator volume of 10 ml.
- matrice10_2list[list], optional
response matrix for photons in the range [200-2000] keV and for a scintillator volume of 10 ml.
- matrice10_3list[list], optional
response matrix for photons in the range [2000-10000] keV and for a scintillator volume of 10 ml.
- edlist[list], optional
matrix of input energies. column 0: [1-200] keV; column 1: [200-2000] keV; column 2: [2000-10000] keV
Returns
- resultfloat
deposited energy in keV.
- tdcrpy.TDCR_model_lib.modelAnalytical(L, TD, TAB, TBC, TAC, rad, kB, V, mode, mode2, ne)
TDCR analytical model that is used for pure beta emitting radionuclides
Parameters
- Lfloat or tuple
free parameter(s).
- TDfloat
triple-to-double coincidence ratio that was measured (logic sum).
- TABfloat
triple-to-double coincidence ratio that was measured (channels A and B).
- TBCflat
triple-to-double coincidence ratio that was measured (channels B and C).
- TACfloat
triple-to-double coincidence ratio that was measured (channels A and C).
- radstring
radionuclide (eg. “Na-22”).
- kBfloat
Birks constant in cm/keV.
- Vfloat
volume of the scintillator in ml. run only for 10 ml
- modestring
“res” to return the residual, “eff” to return efficiencies.
- mode2string
“sym” for symetrical model, “asym” for symetrical model.
- nEinteger
Number of bins for the quenching function.
Returns
- resfloat
Residuals of the model compared the measurement data for (a) given free parmeters L. (only in mode=”res”)
- mean_efficiency_Sfloat
Estimation of the efficiency of single counting events. (only in mode=”eff”)
- mean_efficiency_Dfloat
Estimation of the efficiency of logic sum of double coincidences. (only in mode=”eff”)
- mean_efficiency_Tfloat
Estimation of the efficiency of triple coincidences. (only in mode=”eff”)
- tdcrpy.TDCR_model_lib.normalise(p_x)
This function is used to ensure that the sum of probability is equal to 1.
Parameters
- p_xlist
vector of probabilities.
Returns
- plist
normalized probability vector.
- tdcrpy.TDCR_model_lib.readBetaShape(rad, mode, level, z=<zipfile.ZipFile filename='C:\\Users\\romain.coulon\\Anaconda3\\lib\\site-packages\\tdcrpy\\decayData\\All-nuclides_BetaShape.zip' mode='r'>)
This funcion reads the beta spectra calculated by the code BetaShape and published in the DDEP web page.
refs:
Parameters
- radstring
identifier of the radionuclide. e.g. ‘Na-22’
- modestring
identifier of the decay mode. ‘beta-’ or ‘beta+’
- levelint or string
level of the daughter after decay. 0,1,2,3 …. or ‘tot’ in case of pure beta emitting radionuclides
Returns
- elist
the energy vector in keV.
- dNdxlist
the probability density in keV-1.
- tdcrpy.TDCR_model_lib.readEShape(rad, *, z=<zipfile.ZipFile filename='C:\\Users\\romain.coulon\\Anaconda3\\lib\\site-packages\\tdcrpy\\decayData\\All-nuclides_Ensdf.zip' mode='r'>)
This function reads the ENSDF zip files and format the data to be processed by TDCRPy.
Parameters
- radstring
name of the radionuclide such as ‘Ag-108’.
- zZipFile object
zip ENSDF file.
Returns
- daug_namelist
daughter nucleus of the decay
- Energylist
comprise all transition energies of the daughter nucleus.
- Problist
comprise all transtion probabilities of the daughter nucleus.
- Typelist
comprise all type of transition of the daughter nucleus.
- tdcrpy.TDCR_model_lib.readPenNuc2(rad, z1=<zipfile.ZipFile filename='C:\\Users\\romain.coulon\\Anaconda3\\lib\\site-packages\\tdcrpy\\decayData\\All-nuclides_PenNuc.zip' mode='r'>)
This function is used to read PenNuc files to format the decay data in lists readable by TDCRPy.
Parameters
- radstring
name of the radionculide (for example: “Am-241”).
Returns
- daughterlist
list of the daughter nucleus – indice 0.
- prob_dauglist
list of probabilities to produce daugter nuclei – indice 1.
- energy_Qlist
list of Q value for each transition to a given daughter nucleus – indice 2.
- desin_type_totlist[list]
list of type of decay branch / emitted particules – indice 3. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- desin_energy_totlist[list]
list of the energies of decay transition or the emitted particles – indice 4. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- desin_prob_totlist[list]
list of the prabability of decay transition or the emitted particles – indice 5. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- desin_level_totlist[list]
list of energy level that the daughter nucleus can have just after the decay of the mother nucleus – indice 6. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- prob_branch_totlist
list of branch probabilities – indice 7. It contains a sub-list for all possible branches of a given daughter nucleus.
- tran_type_totlist[list]
list of all possible transitions – indice 8. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- tran_energy_totlist[list]
list of energy associated with transitions – indice 9. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- tran_prob_totlist[list]
list of probability associated with transitions – indice 10. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- tran_level_totlist[list]
list of corresponding branch levels – indice 11. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to the level before the transition.
- tran_level_end_totlist[list]
list of level following given transitions – indice 12. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to the level after the transition.
- level_energy_totlist[list]
list of energy levels – indice 13. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- prob_tran_totlist[list]
list of sum of transition of each branches – indice 14. It contains a sub-list for all possible branches of a given daughter nucleus and a sub-sub list related to possible decay mode of each branch.
- tdcrpy.TDCR_model_lib.read_matrice(path, niveau)
This function read the response matrix calculated by MCNP6 simulation.
Parameters
- pathstring
path to the response matrix.
- niveauinteger or string
energy range of the response matrix. 0: [1-200] keV; 1: [200-2000] keV; 2: [2000-10000] keV. “e” for the input energy matrix.
Returns
- matricelist[list]
formatted response matrix.
- tdcrpy.TDCR_model_lib.relaxation_atom(daugther, rad, lacune='defaut')
This function simulates the atomic rearangement following a missing electron an inner shell of the daughter atom.
Parameters
- daugtherstring
The daughter nucleus (for example NB95,PD110 etc.)
- radstring
The mother nucleus (for exemple Am-241, C-11 etc.)
- lacunestring
The shell where the electron is missing (for example ‘Atom_K’,’Atom_L’ etc.)
Returns
Type : type of transition Auger L or K, or X Ray. Energy : corresponding energy in keV.
- tdcrpy.TDCR_model_lib.sampling(p_x)
This function aims to sample in a pdf or a pmf
Parameters
- p_xfloat vector
Probability Density (or mass) Function (PDF or PMF) of the random variable x.
Returns
- iinteger
index in x pointing the sampled value of the random variable X.
- tdcrpy.TDCR_model_lib.stoppingpower(e, rho=0.96, Z=5.2, A=11.04, emin=0, file=array([0.0, 0.7, 1.4, ..., 12.491336, 12.490668, 8.98619049e-43]))
The stopping power of electrons between 20 keV and 1000 keV is a mixture of a radiative loss model [1], and a collision model [2] that has been validated agaisnt the NIST model ESTAR [3] recommanded by the ICRU Report 37 [4]. At low energy - between 10 eV and 20 keV - the model from Tan and Xia [5] is implemented.
Refs:
[1] https://doi.org/10.1016/0020-708x(82)90244-7
[3] https://dx.doi.org/10.18434/T4NC7P
[4] ICRU Report 37, Stopping Powers for Electrons and Positrons
Parameters
- efloat
Energy of the electron in eV.
- rhofloat, optional
density of the source in g.cm-3. The default is 0.96.
- Zfloat, optional
mean charge number of the source. The default is 5.2.
- Afloat, optional
mean mass number of the source. The default is 11.04.
- eminfloat, optional
the minimal energy to consider. The default is 0.
- filelist, optional
tabulated data form the Tan and Xia model. The default is data_TanXia_f.
Returns
- dEdxfloat
Calculated stopping power in MeV.cm-1.
- tdcrpy.TDCR_model_lib.stoppingpowerA(e, rho=0.96, energy_alpha=[1.0, 1.5, 2.0, 2.5, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 12.5, 15.0, 17.5, 20.0, 22.5, 25.0, 27.5, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0, 125.0, 150.0, 175.0, 200.0, 225.0, 250.0, 275.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0, 650.0, 700.0, 750.0, 800.0, 850.0, 900.0, 950.0, 1000.0, 1250.0, 1500.0, 1750.0, 2000.0, 2250.0, 2500.0, 2750.0, 3000.0, 3500.0, 4000.0, 4500.0, 5000.0, 5500.0, 6000.0, 6500.0, 7000.0, 7500.0, 8000.0], dEdx_alpha=[426600.0, 442500.0, 456000.0, 468700.0, 480800.0, 504300.0, 526800.0, 548500.0, 569400.0, 589600.0, 609100.0, 628100.0, 673000.0, 715000.0, 754500.0, 791900.0, 827400.0, 861200.0, 893600.0, 924700.0, 983500.0, 1038000.0, 1090000.0, 1139000.0, 1185000.0, 1229000.0, 1271000.0, 1311000.0, 1350000.0, 1387000.0, 1423000.0, 1457000.0, 1490000.0, 1522000.0, 1668000.0, 1792000.0, 1900000.0, 1993000.0, 2074000.0, 2145000.0, 2206000.0, 2258000.0, 2340000.0, 2398000.0, 2436000.0, 2457000.0, 2465000.0, 2463000.0, 2453000.0, 2436000.0, 2415000.0, 2389000.0, 2361000.0, 2331000.0, 2299000.0, 2267000.0, 2111000.0, 1962000.0, 1819000.0, 1684000.0, 1561000.0, 1457000.0, 1369000.0, 1292000.0, 1164000.0, 1061000.0, 977400.0, 907300.0, 847700.0, 796300.0, 751400.0, 711800.0, 676600.0, 645000.0])
Estimation of the stopping power of alpha particles using tabulated values form the ASTAR code
ref:
Parameters
- efloat
energy of the alpha particle in keV.
- rhofloat, optional
density of the source in g.cm-3. The default is 0.96.
- energy_alphalist, optional
the list of energy (in keV) for which the stopping power was calculated with ASTAR. The default is energy_alph.
- dEdx_alphalist, optional
the list of stopping powers (in keV.cm2/g) associated with the energy vector. The default is dEdx_alph.
Returns
- float
Interpolated ASTAR estimation of the stopping power.
- tdcrpy.TDCR_model_lib.tic()
Records a time in TicToc, marks the beginning of a time interval
- tdcrpy.TDCR_model_lib.toc(tempBool=True)
Prints the time difference yielded by generator instance TicToc
tdcrpy.TDCRoptimize module
Created on Wed Jul 5 10:04:53 2023
@author: romain.coulon, jialin.hu
- tdcrpy.TDCRoptimize.eff(TD, TAB, TBC, TAC, Rad, pmf_1, kB, V, mode2, N=1000, L=1)
Caclulation of the efficiency of a TDCR system based on the model TDCRPy.
Parameters
- TDfloat
triple-to-double coincidence ratio. Not consider if mode2=”asym”. Not consider if mode2=”asym”.
- TABfloat
triple-to-double coincidence ratio (coincidences between channel A and B). Not consider if mode2=”sym”.
- TBCfloat
triple-to-double coincidence ratio (coincidences between channel B and C). Not consider if mode2=”sym”.
- TACfloat
triple-to-double coincidence ratio (coincidences between channel A and C). Not consider if mode2=”sym”.
- Radstring
List of radionuclides.
- pmf_1string
list of probability of each radionuclide..
- kBfloat
Birks constant.
- Vfloat
volume of the scintillator in ml. run only for 10 ml
- mode2string
“sym” for symetrical model, “asym” for symetrical model.
- Ninterger, optional
number of Monte-Carlo trials. The default is 1000.
- Lfloat, optional
free parameter(s) as initial guess. The default is 1.
Returns
- L0float
global free parameter.
- Ltuple
free parameters (relevant for the asymetric model).
- eff_Sfloat
counting efficiency of single events.
- u_eff_Sfloat
standard uncertainty of eff_S.
- eff_Dfloat
counting efficiency of double coincidences.
- u_eff_Dfloat
standard uncertainty of eff_D.
- eff_Tfloat
counting efficiency of triple coincidences.
- u_eff_Tfloat
standard uncertainty of eff_T.