#model for source DWTP 
model {
   mu_10 ~ dnorm(-2.6,0.3)
   tau ~ dgamma(0.1,0.1)
   mu <- mu_10 *log(10)
   sigma <- 1/tau
   sigma_10 <- sigma/(log(10)*log(10))

for (i in 1:n) {
     u[i] ~ dlnorm(mu,tau)
     loss[i] ~ dbeta(50.75,5.25)
     inhib[i] ~ dbeta(5.17,1.48) 
     u_liter[i] <- (u[i]*(1/v)*f*(1/(1-inhib[i]))*(1/(1-loss[i])))/pcr[i,13]

     p_1[i] <- 1-exp(-1*u[i])
     p_0.2[i] <- 1-exp(-0.2*u[i])
     p_0.1[i] <- 1-exp(-0.1*u[i])
     p_0.04[i] <- 1-exp(-0.04*u[i])
     p_0.03[i] <- 1-exp(-0.03125*u[i])
     p_0.02[i] <- 1-exp(-0.02*u[i])
   
     #likelihoods for Conc.
     pcr[i,1] ~ dbin(p_1[i],pcr[i,7])
     pcr[i,2] ~ dbin(p_0.2[i],pcr[i,8])
     pcr[i,3] ~ dbin(p_0.1[i],pcr[i,9])
     pcr[i,4] ~ dbin(p_0.04[i],pcr[i,10])
     pcr[i,5] ~ dbin(p_0.03[i],pcr[i,11])
     pcr[i,6] ~ dbin(p_0.02[i],pcr[i,12])
   }

}
list(pcr=structure(.Data=c(
#3s oct
0,2,NA,NA,4,NA,2,2,5,5,5,5,207.7,
0,6,NA,3,NA,NA,2,7,5,5,5,5,207.7,
2,7,7,1,1,NA,2,7,10,5,5,5,207.7,
2,2,5,5,1,0,2,2,5,5,5,5,207.7,
0,3,0,NA,NA,NA,2,7,5,5,5,5,207.7,

#4s oct
2,2,4,NA,NA,NA,2,2,5,5,5,5,200.2,
0,5,4,NA,NA,NA,2,7,5,5,5,5,200.2,
2,2,4,3,NA,NA,2,2,5,5,5,5,200.2,
0,7,5,4,NA,3,2,7,5,5,5,5,200.2,
0,4,NA,NA,NA,NA,2,7,5,5,5,5,200.2,

#10s jan
#corrected number of reps fm 12 to 7
2,1,NA,NA,NA,NA,7,7,5,5,5,5,57.1,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,57.1,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,57.1,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,57.1,
0,1,NA,NA,NA,NA,2,7,5,5,5,5,57.1,

#11s march
0,2,NA,NA,NA,NA,2,7,5,5,5,5,81.3,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,81.3,
0,4,NA,NA,NA,NA,2,7,5,5,5,5,81.3,
0,2,NA,2,NA,NA,7,2,5,5,5,5,81.3,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,81.3,

#22S nov
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,144.4,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,144.4,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,144.4,
0,2,NA,NA,NA,NA,2,7,5,5,5,5,144.4,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,144.4,

#23S aug
1,4,NA,NA,NA,NA,2,7,5,5,5,5,200.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,

#24s dec
2,0,NA,NA,NA,NA,7,2,5,5,5,5,1999.7,
0,2,NA,NA,NA,NA,7,7,5,5,5,5,1999.7,
2,0,NA,NA,NA,NA,7,2,5,5,5,5,1999.7,
0,1,NA,NA,NA,NA,2,7,5,5,5,5,1999.7,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,1999.7,

#25s oct
0,0,NA,1,NA,NA,2,2,5,5,5,5,88.5,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,88.5,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,88.5,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,88.5,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,88.5,

#26s jan
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,206.5,
0,7,NA,9,4,3,2,7,5,10,5,5,206.5,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,206.5,
0,3,NA,NA,NA,NA,2,7,5,5,5,5,206.5,
0,1,NA,0,NA,NA,2,7,5,5,5,5,206.5,

#27s feb
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,
0,5,NA,3,NA,NA,2,5,5,5,5,5,200.0
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,200.0,
),
.Dim=c(26,13)),n=26,v=0.005,f=3)


#model for treated DWTP 
model {
   mu_10 ~ dnorm(-2.6,0.3)
   tau ~ dgamma(0.1,0.1)
   mu <- mu_10 *log(10)
   sigma <- 1/tau
   sigma_10 <- sigma/(log(10)*log(10))
for (i in 1:n) {
     u[i] ~ dlnorm(mu,tau)
     inhib[i] ~ dbeta(18.88,8.81)
     loss[i] ~ dbeta(50.75,5.25)
     u_liter[i] <- (u[i]*(1/v)*f*(1/(1-inhib[i]))*(1/(1-loss[i])))/pcr[i,13]

     p_1[i] <- 1-exp(-1*u[i])
     p_0.2[i] <- 1-exp(-0.2*u[i])
     p_0.1[i] <- 1-exp(-0.1*u[i])
     p_0.04[i] <- 1-exp(-0.04*u[i])
     p_0.03[i] <- 1-exp(-0.03125*u[i])
     p_0.02[i] <- 1-exp(-0.02*u[i])
   
     #likelihoods for Conc.
     pcr[i,1] ~ dbin(p_1[i],pcr[i,7])
     pcr[i,2] ~ dbin(p_0.2[i],pcr[i,8])
     pcr[i,3] ~ dbin(p_0.1[i],pcr[i,9])
     pcr[i,4] ~ dbin(p_0.04[i],pcr[i,10])
     pcr[i,5] ~ dbin(p_0.03[i],pcr[i,11])
     pcr[i,6] ~ dbin(p_0.02[i],pcr[i,12])
   }
}
list(pcr=structure(.Data=c(
#3t oct
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2004.7,
0,3,NA,0,NA,NA,7,7,5,5,5,5,2004.7,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2004.7,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2004.7,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2004.7,

#20t jan
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2003.7,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2003.7,
1,0,NA,NA,NA,NA,7,2,5,5,5,5,2003.7,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2003.7,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2003.7,

#23t aug
2,2,1,NA,NA,NA,2,2,5,5,5,5,2000.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2000.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2000.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2000.0,
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,2000.0,

#25t oct
5,1,NA,NA,NA,NA,7,7,5,5,5,5,673.5,
2,0,NA,NA,NA,NA,7,7,5,5,5,5,673.5,
1,4,1,NA,NA,NA,2,7,5,5,5,5,673.5,
2,3,1,NA,NA,NA,2,7,5,5,5,5,673.5
#0,0,NA,NA,NA,NA,2,2,5,5,5,5,673.5
),
#accounts for per ml(ie, v) and fraction of org floc used (ie f)
.Dim=c(7,13)),n=7,v=0.005,f=3)