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/tags/0.6.3/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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