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Support this project and keep always updated about recent software releases, bug fixes and major improvements by [following on github](https://github.com/dpscience?tab=followers).
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Copyright (c) 2020-2021 Danny Petschke (danny.petschke@uni-wuerzburg.de). All rights reserved.<br><br>
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Copyright (c) 2020-2022 Dr. Danny Petschke (danny.petschke@uni-wuerzburg.de). All rights reserved.<br><br>
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<b>pyDCONTINPALS</b> - A program in Python for running the historical FORTRAN code CONTIN-PALS initially provided by [Provencher (1982)](https://www.sciencedirect.com/science/article/abs/pii/0010465582901746) and [Gregory et al. (1990/](https://www.sciencedirect.com/science/article/abs/pii/016890029090358D)[1991)](https://www.sciencedirect.com/science/article/abs/pii/016890029190367Y). CONTIN-PALS program solves Fredholm integral equations with convoluted exponential decays as kernels of the type that occur in the analysis of Positron Annihilation Lifetime Spectra (PALS).<br>
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```python
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__demoMode =True# disable if running from real data
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#NOTE: spectrum and IRF (or mono-exponential decay spectrum) data vectors require equal length!
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#NOTE: SPECTRUM and IRF (or mono-exponential decay spectrum) data vectors require equal length!
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__roi_start =0
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__roi_end =7400
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__roi_end =7400# Note: number of channels is internally limited by CONTIN to <= 4000, so adjust the '__binFactor' in order to fit the given number of channels into this range
# define the number of rows, which should be skipped during the import (e.g. for ignoring the header entries):
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# define the number of rows to be skipped during the import of the data (e.g. for ignoring the header entries):
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__skipRows =5;
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# fixed mono-decay component in units of picoseconds [ps] (1/lambda = tau):
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# Note: set to something like 1E-6 if you provide numerical IRF data as input
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__tau_monoDecaySpec_in_ps =182. #[ps]
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# Note: set to values below 1E-6 if you are providing numerical IRF data as input otherwise the decay rate in [ps]:
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__tau_monoDecaySpec_in_ps =182. # [ps]
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# used to simulate the IRF in case of '__demoMode' == True:
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__t_zero =2000# channel number
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__irf_fwhm = [270.04,498.63] # [ps]
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__irf_intensity = [0.9382,0.0618] # [ps]
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__irf_t0 = [0.,6.6] # [ps]
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# grid of characteristic lifetimes with equally distributed grid points defining the resulting intensity spectrum
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# grid of characteristic lifetimes with equally distributed grid points defining the resulting intensity spectrum to be expected as output:
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__gridTau_start =10.0# [ps]
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__gridTau_stop =3000.0# [ps]
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__gridPoints =100# 10 ... 100 Note: this value is internally limited to 100 by CONTIN
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__gridPoints =100# 10 ... 100 Note: this value is internally limited by CONTIN
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# channel/bin resolution [ps]:
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__channelResolutionInPs =10. # >= 10 ... Note: this value is internally limited by CONTIN. If lower, increase '__binFactor' to fit into this range
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__binFactor =2# Note: number of channels is internally limited by CONTIN to <= 4000, so adjust the '__binFactor' in order to fit the given number of channels into this range
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# channel/bin resolution [ps]
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__channelResolutionInPs =5. # >= 10 ... Note: this value is internally limited by CONTIN
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__binFactor =1
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# background estimation/calculation region:
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# background estimation:
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__bkgrd_startIndex =6500;
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__bkgrd_count =900; # number of channels with respect to the 'startIndex'
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__bkgrd_count =900; # number of channels with respect to the 'startIndex''
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```
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* <b>execute</b> `pyDCONTINPALS.py`<br>
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