From d9ac8a18c5131586e493f4aa9acad13ebf1a7b54 Mon Sep 17 00:00:00 2001 From: Qixin He Date: Fri, 11 Mar 2022 18:10:54 -0500 Subject: [PATCH] new v2 which splits up the parasite classes --- batchRuns/ODESImmunity_hqx.R | 2172 +++++++++++++++++++++++++++++++--- batchRuns/paramList.csv | 28 +- 2 files changed, 2008 insertions(+), 192 deletions(-) diff --git a/batchRuns/ODESImmunity_hqx.R b/batchRuns/ODESImmunity_hqx.R index f80c6bb..30692f9 100644 --- a/batchRuns/ODESImmunity_hqx.R +++ b/batchRuns/ODESImmunity_hqx.R @@ -1,180 +1,1998 @@ -require(deSolve) -library(tidyverse) -args <- commandArgs(trailingOnly = TRUE) -print(args) -paramFile<-args[1] -No<-as.integer(args[2]) -resultsFolder <-args[3] -#paramFile<-"paramList.csv" -#No<-2 -#resultsFolder<-"./" - -SEAI<-function(t,y,p){ - - with(as.list(c(y,p)),{ - # total host population size - N = NU+ND+SU+SD+AU+AD - # total parasite population size - P = PWU+PWD+PRU+PRD - - # parasite/host ratio - m = P/N - # prevalence - I = 1-exp(-m) - # converted cost of resistance considering competition - h = 1-(ResCost/(1+0.1*exp(-competition*(I-1)))) - #adjusted parasite population, transmissibility lower in PR - PADJ = PWU+PWD+(PRU+PRD)*h - - # pop size +1 is to prevent N = 0 for undefined scenario - fracN = P_acc_N/(NU+ND+1) - fracS = P_acc_S/(SU+SD+1) - fracA = P_acc_A/(AU+AD+1) - - # probability that the infected strain has not been seen by the adaptive immune system - infN = exp(-fracN/nstrains) - infS = exp(-fracS/nstrains) - infA = exp(-fracA/nstrains) - - #transmissibility is reduced to the number of infected hosts, - #receiving hosts needs to have open "resource room" for accepting new strains - B = b*(I/m)*(1-m/capacity) - - # per capita biting rate for hosts who are not treated - Bu = B*PADJ/N - # per capita biting rate for hosts who are drug treated - Bd = B*(PRU+PRD)*h/N - #print(B) - #eq b - infD = ND*infN+SD*infS+AD*infA - infU = NU*infN+SU*infS+AU*infA - #print(infD) - #print(infU) - - eq1 = B*h*(infU/N) - eq2 = B*h*(infD/N) - eq3 = B*(infU/N) - eq4 = B*(infD/N) - - # Parasite pop ODE - dPWU.dt = PWU*eq3 + PWD*eq3 - PWU*eq4 - muWU*PWU - dPWD.dt = PWD*eq4 + PWU*eq4 - PWD*eq3 - muWD*PWD - dPRU.dt = PRU*eq1 + PRD*eq1 - PRU*eq2 - muRU*PRU - dPRD.dt = PRD*eq2 + PRU*eq2 - PRD*eq1 - muRD*PRD - #sprintf("%.3f, %.3f,%.3f,%.3f",dPWU.dt,dPWD.dt,dPRU.dt,dPRD.dt) - - # Generalized immunity ODE - dNU.dt = birth + - (ND/Tau)- # drug loose effectiveness - (NU*Bu*infN*d1) - #naive class getting infected, and treated - (NU*Bu*rho1) - #naive class getting enough # of infections to move to S - (NU*Bu*muNU)- #naive class die from infections - (NU*att)#normal death rate - - - #print(dNU.dt) - - dND.dt = (NU*Bu*infN*d1) - #naive class getting infected, and treated - (ND/Tau) - # drug loose effectiveness - (ND*Bd*rho1) -#naive class getting enough # of infections to move to S - (ND*Bd*muND) -#naive class die from infections - (ND*att) #normal death rate - #print(dND.dt) - - dSU.dt = (NU*Bu*rho1) +#naive class getting enough # of infections to move to S - (SD/Tau)- # drug loose effectiveness - (SU*Bu*infS*d2)- #symptomatic class getting infected, show symptoms, and treated - (SU*Bu*rho2) -#symptomatic class getting enough # of infections to move to AS - (SU*att) #normal death rate - - dSD.dt = (ND*Bd*rho1)+ #naive class getting enough # of infections to move to S - (SU*Bu*infS*d2)- #symptomatic class getting infected, show symptoms, and treated - (SD/Tau) - # drug loose effectiveness - (SD*Bd*rho2)- #symptomatic class getting enough # of infections to move to AS - (SD*att) #normal death rate - - dAU.dt = (SU*Bu*rho2)+ #symptomatic class getting enough # of infections to move to AS - (AD/Tau)- # drug loose effectiveness - (AU*Bu*infA*omega*d3)- #asymptomatic class getting infected, show symptoms, and treated - (AU*att) #normal death rate - - dAD.dt = (SD*Bd*rho2) + #symptomatic class getting enough # of infections to move to AS - (AU*Bu*infA*omega*d3)- #asymptomatic class getting infected, show symptoms, and treated - (AD/Tau)- # drug loose effectiveness - (AD*att) #normal death rate - - #sprintf("%.0f, %.0f,%.0f,%.0f,%.0f,%.0f",dNU.dt,dND.dt,dSU.dt,dSD.dt,dAU.dt,dAD.dt) - - # track the mean number of times infected per immunity class - dP_acc_N.dt = NU*Bu + ND*Bd - # total number of infection received - (NU*(Bu*muNU+att))*P_acc_N/(NU+ND+1)- #when naive U class die how many infections deducted - (ND*(Bd*muND+att))*P_acc_N/(NU+ND+1)- #when naive D class die many infections deducted - ((NU*Bu*rho1)+(ND*Bd*rho1))*P_acc_N/(NU+ND+1) #when naive class leave to S - - dP_acc_S.dt = ((NU*Bu*rho1)+(ND*Bd*rho1))*P_acc_N/(NU+ND+1)+ #when naive class leave to S - SU*Bu + SD*Bd- #total number of new infections - (SU+SD)*att*P_acc_S/(SU+SD+1)- # normal death - ((SD*Bd*rho2)+ (SU*Bu*rho2))*P_acc_S/(SU+SD+1) #Symptomatic move to Asymptomatic - - dP_acc_A.dt = ((SD*Bd*rho2)+ (SU*Bu*rho2))*P_acc_S/(SU+SD+1)+ #Symptomatic move to Asymptomatic - AU*Bu + AD*Bd- #total number of new infections - (AU+AD)*att*P_acc_A/(AU+AD+1) # normal death - - a <- 365/(2*pi) - db.dt = bavgnull * seasonality / a *(1- dryWidth *cos(phase+t/a))*sin(phase+t/a-dryWidth*sin(phase+t/a)) - #db.dt =0 - #sprintf("%.0f, %.0f,%.0f,%.0f",dP_acc_N.dt,dP_acc_S.dt,dP_acc_A.dt,dbeta.dt) - - return(list(c(dPWU.dt,dPWD.dt,dPRU.dt,dPRD.dt,dNU.dt,dND.dt,dSU.dt,dSD.dt,dAU.dt,dAD.dt,dP_acc_N.dt, dP_acc_S.dt, dP_acc_A.dt, db.dt))) - }) -} - -allPara<-read.csv(paramFile,sep=",",header=T) - -currentPara<-allPara[allPara$No==No,] - -t2 = seq(from=0,to=30*365,by=1) -N0 = c(PWU=100,PWD=0,PRU=2,PRD=0, - NU=1000,ND=0,SU=0,SD=0,AU=0,AD=0, - P_acc_N=0,P_acc_S=0,P_acc_A=0, - b=currentPara$bavgnull*(1-currentPara$seasonality)) - -out2 = ode(y=N0,times=t2,func=SEAI,parms=currentPara) -out2<-as_tibble(out2) -sumOut2<-out2%>%mutate(year = floor(time/365),P = PWU+PWD+PRU+PRD, N = NU+ND+SU+SD+AU+AD)%>% - group_by(year)%>%summarise(meanP=mean(P),meanN=mean(N)) - -while((abs(sumOut2[20,"meanP"]-sumOut2[30,"meanP"])/sumOut2[30,"meanP"]>0.001 )| - (abs(sumOut2[20,"meanN"]-sumOut2[30,"meanN"])/sumOut2[30,"meanN"]>0.001)){ - print(out2[30*365,2:15]) - t2<-t2+30*365 - N0 = as.numeric(out2[30*365,2:15]) - names(N0)<-colnames(out2[,2:15]) - out2 = ode(y=N0,times=t2,func=SEAI,parms=currentPara) - out2<-as_tibble(out2) - sumOut2<-out2%>%mutate(year = floor(time/365),P = PWU+PWD+PRU+PRD, N = NU+ND+SU+SD+AU+AD)%>% - group_by(year)%>%summarise(meanP=mean(P),meanN=mean(N)) -} -out2<-as.data.frame(out2) -out2<-out2%>%mutate(m_N = P_acc_N/(NU+ND),m_S =P_acc_S/(SU+SD), m_A = P_acc_A/(AU+AD), - P = PWU+PWD+PRU+PRD, N = NU+ND+SU+SD+AU+AD, prev = 1-exp(-P/N)) - -##you can check the output through this graph -#out2.melt<-reshape2::melt(out2%>%filter(time%%10==0), id.vars=1) -#ggplot(out2.melt, aes(time,value ))+geom_line()+ylim(0,NA)+ -# facet_wrap(.~variable,scales="free_y") - -outFile<-paste(resultsFolder,"/",strsplit(paramFile,split="[.]")[[1]][1],"_results.csv",sep="") -if(file.exists(outFile)){ - write.table(as.data.frame(cbind(currentPara,out2[30*365,])), - file = outFile, row.names=F, col.names=F,sep=",", - quote=F,append=T) -}else{ - write.csv(as.data.frame(cbind(currentPara,out2[30*365,])), - file = outFile, row.names=F, - quote=F) - 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require(deSolve)
library(tidyverse)
args <- commandArgs(trailingOnly = TRUE)
print(args)
paramFile<-args[1]
No<-as.integer(args[2])
resultsFolder <-args[3]
#paramFile<-"paramList.csv"
#No<-2
#resultsFolder<-"./"
+
SEAI<-function(t,y,p){
+
with(as.list(c(y,p)),{
# total host population size
N = NU+ND+SU+SD+AU+AD
# total parasite population size
P = PWU+PWD+PRU+PRD
# parasite/host ratio
m = P/N
# prevalence
I = 1-exp(-m)
# converted cost of resistance considering competition
h = 1-(ResCost/(1+0.1*exp(-competition*(I-1))))
#adjusted parasite population, transmissibility lower in PR
PADJ = PWU+PWD+(PRU+PRD)*h
# pop size +1 is to prevent N = 0 for undefined scenario
fracN = P_acc_N/(NU+ND+1)
fracS = P_acc_S/(SU+SD+1)
fracA = P_acc_A/(AU+AD+1)
# probability that the infected strain has not been seen by the adaptive immune system
infN = exp(-fracN/nstrains)
infS = exp(-fracS/nstrains)
infA = exp(-fracA/nstrains)
+
#transmissibility is reduced to the number of infected hosts,
#receiving hosts needs to have open "resource room" for accepting new strains
B = b*(I/m)*(1-m/capacity)
# per capita biting rate for hosts who are not treated
Bu = B*PADJ/N
# per capita biting rate for hosts who are drug treated
Bd = B*(PRU+PRD)*h/N
#print(B)
#eq b
infD = ND*infN+SD*infS+AD*infA
infU = NU*infN+SU*infS+AU*infA
#print(infD)
#print(infU)
eq1 = B*h*(infU/N)
eq2 = B*h*(infD/N)
eq3 = B*(infU/N)
eq4 = B*(infD/N)
# Parasite pop ODE
dPWU.dt = PWU*eq3 + PWD*eq3 - PWU*eq4 - muWU*PWU
dPWD.dt = PWD*eq4 + PWU*eq4 - PWD*eq3 - muWD*PWD
dPRU.dt = PRU*eq1 + PRD*eq1 - PRU*eq2 - muRU*PRU
dPRD.dt = PRD*eq2 + PRU*eq2 - PRD*eq1 - muRD*PRD
#sprintf("%.3f, %.3f,%.3f,%.3f",dPWU.dt,dPWD.dt,dPRU.dt,dPRD.dt)
+
# Generalized immunity ODE
dNU.dt = birth +
(ND/Tau)- # drug loose effectiveness
(NU*Bu*infN*d1) - #naive class getting infected, and treated
(NU*Bu*rho1) - #naive class getting enough # of infections to move to S
(NU*Bu*muNU)- #naive class die from infections
(NU*att)#normal death rate
+
#print(dNU.dt)
dND.dt = (NU*Bu*infN*d1) - #naive class getting infected, and treated
(ND/Tau) - # drug loose effectiveness
(ND*Bd*rho1) -#naive class getting enough # of infections to move to S
(ND*Bd*muND) -#naive class die from infections
(ND*att) #normal death rate
#print(dND.dt)
dSU.dt = (NU*Bu*rho1) +#naive class getting enough # of infections to move to S
(SD/Tau)- # drug loose effectiveness
(SU*Bu*infS*d2)- #symptomatic class getting infected, show symptoms, and treated
(SU*Bu*rho2) -#symptomatic class getting enough # of infections to move to AS
(SU*att) #normal death rate
dSD.dt = (ND*Bd*rho1)+ #naive class getting enough # of infections to move to S
(SU*Bu*infS*d2)- #symptomatic class getting infected, show symptoms, and treated
(SD/Tau) - # drug loose effectiveness
(SD*Bd*rho2)- #symptomatic class getting enough # of infections to move to AS
(SD*att) #normal death rate
dAU.dt = (SU*Bu*rho2)+ #symptomatic class getting enough # of infections to move to AS
(AD/Tau)- # drug loose effectiveness
(AU*Bu*infA*omega*d3)- #asymptomatic class getting infected, show symptoms, and treated
(AU*att) #normal death rate
dAD.dt = (SD*Bd*rho2) + #symptomatic class getting enough # of infections to move to AS
(AU*Bu*infA*omega*d3)- #asymptomatic class getting infected, show symptoms, and treated
(AD/Tau)- # drug loose effectiveness
(AD*att) #normal death rate
#sprintf("%.0f, %.0f,%.0f,%.0f,%.0f,%.0f",dNU.dt,dND.dt,dSU.dt,dSD.dt,dAU.dt,dAD.dt)
# track the mean number of times infected per immunity class
dP_acc_N.dt = NU*Bu + ND*Bd - # total number of infection received
(NU*(Bu*muNU+att))*P_acc_N/(NU+ND+1)- #when naive U class die how many infections deducted
(ND*(Bd*muND+att))*P_acc_N/(NU+ND+1)- #when naive D class die many infections deducted
((NU*Bu*rho1)+(ND*Bd*rho1))*P_acc_N/(NU+ND+1) #when naive class leave to S
dP_acc_S.dt = ((NU*Bu*rho1)+(ND*Bd*rho1))*P_acc_N/(NU+ND+1)+ #when naive class leave to S
SU*Bu + SD*Bd- #total number of new infections
(SU+SD)*att*P_acc_S/(SU+SD+1)- # normal death
((SD*Bd*rho2)+ (SU*Bu*rho2))*P_acc_S/(SU+SD+1) #Symptomatic move to Asymptomatic
dP_acc_A.dt = ((SD*Bd*rho2)+ (SU*Bu*rho2))*P_acc_S/(SU+SD+1)+ #Symptomatic move to Asymptomatic
AU*Bu + AD*Bd- #total number of new infections
(AU+AD)*att*P_acc_A/(AU+AD+1) # normal death
a <- 365/(2*pi)
db.dt = bavgnull * seasonality / a *(1- dryWidth *cos(phase+t/a))*sin(phase+t/a-dryWidth*sin(phase+t/a))
#db.dt =0
#sprintf("%.0f, %.0f,%.0f,%.0f",dP_acc_N.dt,dP_acc_S.dt,dP_acc_A.dt,dbeta.dt)
+
return(list(c(dPWU.dt,dPWD.dt,dPRU.dt,dPRD.dt,dNU.dt,dND.dt,dSU.dt,dSD.dt,dAU.dt,dAD.dt,dP_acc_N.dt, dP_acc_S.dt, dP_acc_A.dt, db.dt)))
})
}
+
allPara<-read.csv(paramFile,sep=",",header=T)
+
currentPara<-allPara[allPara$No==No,]
+
t2 = seq(from=0,to=30*365,by=1)
N0 = c(PWU=100,PWD=0,PRU=2,PRD=0,
NU=1000,ND=0,SU=0,SD=0,AU=0,AD=0,
P_acc_N=0,P_acc_S=0,P_acc_A=0,
b=currentPara$bavgnull*(1-currentPara$seasonality))
+
out2 = ode(y=N0,times=t2,func=SEAI,parms=currentPara)
out2<-as_tibble(out2)
sumOut2<-out2%>%mutate(year = floor(time/365),P = PWU+PWD+PRU+PRD, N = NU+ND+SU+SD+AU+AD)%>%
group_by(year)%>%summarise(meanP=mean(P),meanN=mean(N))
+
while((abs(sumOut2[20,"meanP"]-sumOut2[30,"meanP"])/sumOut2[30,"meanP"]>0.001 )|
(abs(sumOut2[20,"meanN"]-sumOut2[30,"meanN"])/sumOut2[30,"meanN"]>0.001)){
print(out2[30*365,2:15])
t2<-t2+30*365
N0 = as.numeric(out2[30*365,2:15])
names(N0)<-colnames(out2[,2:15])
out2 = ode(y=N0,times=t2,func=SEAI,parms=currentPara)
out2<-as_tibble(out2)
sumOut2<-out2%>%mutate(year = floor(time/365),P = PWU+PWD+PRU+PRD, N = NU+ND+SU+SD+AU+AD)%>%
group_by(year)%>%summarise(meanP=mean(P),meanN=mean(N))
}
out2<-as.data.frame(out2)
out2<-out2%>%mutate(m_N = P_acc_N/(NU+ND),m_S =P_acc_S/(SU+SD), m_A = P_acc_A/(AU+AD),
P = PWU+PWD+PRU+PRD, N = NU+ND+SU+SD+AU+AD, prev = 1-exp(-P/N))
+
##you can check the output through this graph
#out2.melt<-reshape2::melt(out2%>%filter(time%%10==0), id.vars=1)
#ggplot(out2.melt, aes(time,value ))+geom_line()+ylim(0,NA)+
# facet_wrap(.~variable,scales="free_y")
+
outFile<-paste(resultsFolder,"/",strsplit(paramFile,split="[.]")[[1]][1],"_results.csv",sep="")
if(file.exists(outFile)){
write.table(as.data.frame(cbind(currentPara,out2[30*365,])),
file = outFile, row.names=F, col.names=F,sep=",",
quote=F,append=T)
}else{
write.csv(as.data.frame(cbind(currentPara,out2[30*365,])),
file = outFile, row.names=F,
quote=F)
}
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+ + + You can’t perform that action at this time. +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/batchRuns/paramList.csv b/batchRuns/paramList.csv index 37b3bf3..97e41b4 100644 --- a/batchRuns/paramList.csv +++ b/batchRuns/paramList.csv @@ -1,15 +1,13 @@ -No,birth,att,muND,muNU,nstrains,rho1,rho2,omega,ResCost,capacity,muWU,muWD,muRD,muRU,Tau,d1,d2,d3,bavgnull,seasonality,dryWidth,phase,competition,modelType -1,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.1,0,1,0,12,oneLocus_nonSeasonal -2,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.1,0.6,1,0,12,oneLocus_nonSeasonal -3,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.01,0,1,0,12,oneLocus_nonSeasonal -4,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.02,0,1,0,12,oneLocus_nonSeasonal -5,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.03,0,1,0,12,oneLocus_nonSeasonal -6,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.04,0,1,0,12,oneLocus_nonSeasonal -7,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.05,0,1,0,12,oneLocus_nonSeasonal -8,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.06,0,1,0,12,oneLocus_nonSeasonal -9,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.07,0,1,0,12,oneLocus_nonSeasonal -10,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.08,0,1,0,12,oneLocus_nonSeasonal -11,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.09,0,1,0,12,oneLocus_nonSeasonal -12,1,9.13242E-05,0.1,0.1,20,0.5,0.05,0.01,0.6,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.1,0,1,0,12,oneLocus_nonSeasonal - - +No,birth,att,muND,muNU,nstrains,rho1,rho2,omega,cloneCost,mixCost,ImmLost,capacity,muWU,muWD,muRD,muRU,Tau,d1,d2,d3,bavgnull,seasonality,dryWidth,phase,modelType +1,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.1,0,1,0,oneLocus_nonSeasonal +2,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.1,0.6,1,0,oneLocus_nonSeasonal +3,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.01,0,1,0,oneLocus_nonSeasonal +4,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.02,0,1,0,oneLocus_nonSeasonal +5,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.03,0,1,0,oneLocus_nonSeasonal +6,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.04,0,1,0,oneLocus_nonSeasonal +7,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.05,0,1,0,oneLocus_nonSeasonal +8,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.06,0,1,0,oneLocus_nonSeasonal +9,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.07,0,1,0,oneLocus_nonSeasonal +10,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.08,0,1,0,oneLocus_nonSeasonal +11,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.09,0,1,0,oneLocus_nonSeasonal +12,1,9.13E-05,0.1,0.1,20,0.5,0.05,0.01,0.1,0.9,0.000273973,10,0.006666667,0.99,0.006666667,0.006666667,20,1,1,1,0.1,0,1,0,oneLocus_nonSeasonal \ No newline at end of file