Description Usage Arguments Value See Also Examples
Computes HCP response and relative efficiency/RBE using compound Poison processes and successive convolutions (CPP_SC, the SPIFF algorithm)
1 2 3 4 5  | AT.run.CPPSC.method(E.MeV.u, particle.no, fluence.cm2.or.dose.Gy,
 material.no, stopping.power.source.no, 
	rdd.model, rdd.parameters, er.model, gamma.model, gamma.parameters, 
	N2, fluence.factor, write.output, shrink.tails, shrink.tails.under, 
	adjust.N2, lethal.events.mode)
 | 
E.MeV.u | 
  particle energy for each component in the mixed particle
field [MeV/u] (array of size   | 
particle.no | 
  particle type for each component in the mixed particle
field (array of size   | 
fluence.cm2.or.dose.Gy | 
  if positive, particle fluence for each
component in the mixed particle field [1/cm2]; if negative, particle dose for
each component in the mixed particle field [Gy] (array of size
  | 
material.no | 
  index number for detector material (see also
  | 
stopping.power.source.no | 
  TODO (see also
  | 
rdd.model | 
  index number for chosen radial dose distribution (see also
  | 
rdd.parameters | 
 parameters for chosen radial dose distribution (array of size 4).  | 
er.model | 
  index number for chosen electron-range model (see also
  | 
gamma.model | 
 index number for chosen gamma response.  | 
gamma.parameters | 
 parameters for chosen gamma response (array of size 9).  | 
N2 | 
 number of bins per factor of two for the dose scale of local dose histogram.  | 
fluence.factor | 
  factor to scale the fluences / doses given in
  | 
write.output | 
 if true, a log-file is written to SuccessiveConvolutions.txt in the working directory.  | 
shrink.tails | 
 if true, tails of the local dose distribution, contributing less than shrink.tails.under are cut.  | 
shrink.tails.under | 
 limit for tail cutting in local dose distribution.  | 
adjust.N2 | 
 if true, N2 will be increase if necessary at high fluence to ensure sufficient local dose histogram resolution.  | 
lethal.events.mode | 
 if true, computations are done for dependent subtargets.  | 
N2 | 
 number of bins per factor of two for the dose scale of local dose histogram  | 
relative.efficiency | 
 particle response at dose D / gamma response at dose D  | 
d.check | 
 sanity check: total dose (in Gy) as returned by the algorithm  | 
S.HCP | 
 absolute particle response  | 
S.gamma | 
 absolute gamma response  | 
mean.number.of.tracks.contrib | 
 mean number of tracks contributing to representative point  | 
start.number.of.tracks.contrib | 
 low fluence approximation for mean number of tracks contributing to representative point (start value for successive convolutions)  | 
n.convolutions | 
 number of convolutions performed to reach requested dose/fluence  | 
lower.Jensen.bound | 
 lower bound for Jensen's inequity  | 
upper.Jensen.bound | 
 upper bound for Jensen's inequity  | 
View the C source code here: http://sourceforge.net/apps/trac/libamtrack/browser/trunk/src/AT_Algorithms_CPP.c#L34
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40  | # Compute the relative efficiency of an Alanine detector in a mixed
# carbon / proton field
AT.run.CPPSC.method( particle.no                          = c(6012, 1001,
 1001),         # namely carbon, protons, and protons with
                     E.MeV.u                              = c(270, 270, 5),   
           
# 270 MeV/u (primary Carbon, 270 MeV/u and 5 MeV/u (fast and slow proton
# component) 
                     fluence.cm2.or.dose.Gy               = c(1e8, 1e9, 1e7), 
           # and their corresponding fluences
                     material.no                          = 5,                
           # i.e. Alanine
                     rdd.model                            = 3,                
           # simple 'Geiss' parametrization of radial dose distribution
                     rdd.parameter                        = 50e-9,            
           # with 50 nm core radius
                     er.model                             = 4,                
           # M. Scholz' parametrization of track radius
                     gamma.model                          = 2,                
           # General hit/target X ray response, but
                     gamma.parameters                     = c(1,500,1,1,0),   
           
# as simple single exponential saturation (one hit, one target), saturation
# dose 500 Gy
                     N2                                   = 10,               
           # ten bins per factor 2 for internal local dose histogramming
                     fluence.factor                       = 1.0,              
           # can be used to easily scale total fluence (historical)
                     write.output                         = TRUE,             
           # write a log file
                     shrink.tails                         = TRUE,             
           # cut tails of local dose distribution, if...
                     shrink.tails.under                   = 1e-30,            
           # ... they contribute less then 1e-30 to first moment of histogram
                     adjust.N2                            = TRUE,             
           # perform rebinning if local dose distribution becomes too narrow
                     lethal.events.mode                   = FALSE,            
           # use independent subtargets
                     stopping.power.source.no             = 2)                
      
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