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# $Id: CakePenalties.R 216 2011-07-05 14:35:03Z nelr $
# The CAKE R modules are based on mkin
# CAKE (6245), by Tessella, for Syngenta: Copyright (C) 2011 Syngenta
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.”
# Penalty function for fits that should not be accepted
CakePenalties<-function(params, modelled, obs, penalty.scale = 10, ...){
# Because the model cost is roughly proportional to points,
# make the penalties scale that way too for consistent behaviour
# with many or few data points
sum(CakePenaltiesLong(params, modelled, obs, penalty.scale, ...)$value) * dim(obs)[[1]]
}
CakePenaltiesLong<-function(params, modelled, obs, penalty.scale = 10, ...){
r<-data.frame(name=character(0), value=numeric(0))
# Flow fractions > 1
#-------------------------------
fails<-CakePenaltiesFF(params);
if(dim(fails)[[1]] > 0){
#print("Penalty failures:")
#print(fails)
# Add a failure record for each flow fraction that missed
names(fails)<-c('name', 'value')
fails$value = 100*(fails$value - 1)
fails$name = lapply(fails$name, function(x) paste("FF_", x, sep=""))
r <- rbind(r, fails)
#totalPenalties <- totalPenalties + 100*sum(fails$x - 1) # Penalty for failure
}
r$value <- r$value * penalty.scale
return(r)
}
CakePenaltiesFF<-function(params){
ff.values<-params["f_"==substr(names(params), 0, 2)] # Flow fractions
if(length(ff.values) > 0){
ffs<-data.frame(t(sapply(strsplit(names(ff.values), '_'), FUN=function(x){ x[c(2,4)] }))) # Split into source/dest
names(ffs)<-c('source', 'dest')
ffs['value'] <- ff.values # Add values
sums<-aggregate(ffs$value, list(s=ffs$source), sum) # Sum of flows from each source
fails<-sums[sums$x>1.00001,] # All compartments > 1
} else { fails<-data.frame(s=character(0), x=numeric(0)) }
return(fails)
}
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