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Adjust code to read dr for AP for both constant and uncertain modes #79

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Adjust code to read dr for AP for both constant and uncertain modes #79

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1d8d128
Adjust code to read dr for AP for both constant and uncertain modes
usr110 Oct 20, 2021
0d75a82
Initialize parameters only for uncertain run
usr110 Oct 20, 2021
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65 changes: 13 additions & 52 deletions R/ithim_setup_parameters.R
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Original file line number Diff line number Diff line change
Expand Up @@ -163,60 +163,21 @@ ithim_setup_parameters <- function(NSAMPLES = 1,
}

#### AP DOSE RESPONSE
AP_DOSE_RESPONSE_QUANTILE <<- AP_DOSE_RESPONSE_QUANTILE
## shortcut: use saved median values
if(!AP_DOSE_RESPONSE_QUANTILE){
global_path <- file.path(find.package('ithimr',lib.loc=.libPaths()), 'extdata/global/')
global_path <- paste0(global_path, "/")
DR_AP_LIST <<- readRDS(paste0(global_path,"dose_response/drap/dr_ap_list.Rds"))
}else{
if(AP_DOSE_RESPONSE_QUANTILE == T ) {
ap_diseases <- subset(DISEASE_INVENTORY, air_pollution==1)
dr_ap_list <- list()
ap_diseases <- subset(DISEASE_INVENTORY,air_pollution==1)
ap_parameters <- list()
for(disease in ap_diseases$ap_acronym){
for(letter in c('ALPHA_','BETA_','GAMMA_','TMREL_')){
if(AP_DOSE_RESPONSE_QUANTILE){
ap_parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_',letter,disease)]] <- runif(NSAMPLES,0,1)
parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_',letter,disease)]] <- ap_parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_',letter,disease)]]
} else {
ap_parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_',letter,disease)]] <- 0.5
}
}
dr_ap <- subset(DR_AP,cause_code==disease)
dr_ap_list[[disease]] <- list()
quant1 <- ap_parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_GAMMA_',disease)]]
quant2 <- ap_parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_BETA_',disease)]]
quant3 <- ap_parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_ALPHA_',disease)]]
quant4 <- ap_parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_TMREL_',disease)]]
for(age in unique(dr_ap$age_code)){
dr_ap_age <- subset(dr_ap,age_code==age)
#######################################
lbeta <- log(dr_ap_age$beta)
lgamma <- log(dr_ap_age$gamma)
gamma_val <- quantile(density(lgamma),quant1)
beta_val <- c()
for(i in 1:ifelse(AP_DOSE_RESPONSE_QUANTILE,NSAMPLES,1)){
den <- kde2d(lgamma,lbeta,n=c(1,100),h=0.2,lims=c(gamma_val[i],gamma_val[i],min(lbeta)-1,max(lbeta)+1))
beta_val[i] <- approx(x=cumsum(den$z)/sum(den$z),y=den$y,xout=quant2[i])$y
}
mod <- gam(log(alpha)~te(log(gamma),log(beta)),data=dr_ap_age)
pred_val <- predict(mod, newdata=data.frame(beta=exp(beta_val),gamma=exp(gamma_val)),se.fit=T)
alpha_val <- qnorm(quant3,pred_val$fit,sqrt(mod$sig2))
# generate a value for tmrel given alpha, beta and gamma
mod <- gam(log(tmrel)~ns(log(gamma),df=8)+ns(log(beta),df=8)+ns(log(alpha),df=8),data=dr_ap_age)
pred_val <- predict(mod, newdata=data.frame(alpha=exp(alpha_val),beta=exp(beta_val),gamma=exp(gamma_val)),se.fit=T)
tmrel_val <- qnorm(quant4,pred_val$fit,sqrt(mod$sig2))
dr_ap_list[[disease]][[age]] <- data.frame(alpha=exp(alpha_val),beta=exp(beta_val),gamma=exp(gamma_val),tmrel=exp(tmrel_val))
}
if(AP_DOSE_RESPONSE_QUANTILE){
# turn list inside out, so it's indexed first by sample
parameters$DR_AP_LIST <- lapply(1:NSAMPLES,function(x)lapply(dr_ap_list,function(y) lapply(y,function(z)z[x,])))
}else{
DR_AP_LIST <<- dr_ap_list
}
}

for(disease in ap_diseases$ap_acronym)
parameters[[paste0('AP_DOSE_RESPONSE_QUANTILE_',disease)]] <- runif(NSAMPLES,0,1)
}

# Read dr_ap_list.Rds which contains parameter values by diseases and ages, for both constant and uncertain mode
global_path <- file.path(find.package('ithimr',lib.loc=.libPaths()), 'extdata/global/')
global_path <- paste0(global_path, "/")
DR_AP_LIST <<- readRDS(paste0(global_path,"dose_response/drap/dr_ap_list.Rds"))

if(AP_DOSE_RESPONSE_QUANTILE)
parameters$DR_AP_LIST <- DR_AP_LIST

parameters
}

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