inst/example/plot_associations.R

K.true  <- 2   # no. of latent subclasses in actual simulation. 
               # If eta = c(1,0), effectively, it is K.true=1
J       <- 5   # no. of pathogens.
N       <- 500 # no. of cases/controls.

col_seq_cause <-  c("#DB9D85","#A2B367","#47BEA2",
"#70B3DA","#CD99D8")#colorspace::rainbow_hcl(5, start = 30, end = 300)

subclass_mix_seq <- seq(0,1,by=0.05)
res      <- array(NA,c(J,J,length(subclass_mix_seq)))
res_cond <- array(NA,c(J,J,length(subclass_mix_seq),J))

it <- layout(matrix(1:J^2,nrow=J,ncol=J,byrow=TRUE),
            heights = rep(3,J),
            widths  = rep(3,J)) 

oldpar <- par(oma=c(8,10,8,3));  

pch_seq_cause <- LETTERS[1:J]
lty_seq_cause <- 1+(1:J)
pch_pos_seq   <- c(0.01); gap = 0.15
adj_seq <- c(0.15,0.5,0.85) # for roman numerals:
cex1       <- 2
cex_label1 <- 1
cex2       <- 2
cex_label2 <- 2
cex_margin_marks <- 2

for (scn in c(1,2,3)){
 for (iter in seq_along(subclass_mix_seq)){
   curr_mix <- subclass_mix_seq[iter]
   lambda <- c(curr_mix,1-curr_mix)
   eta    <- c(curr_mix,1-curr_mix) 
   # if it is c(1,0),then it is conditional independence model, and
   # only the first column of parameters in PsiBS, ThetaBS matter!
   
   seed_start <- 20150923
   
   # set fixed simulation sequence:
   set.seed(seed_start)
   
   if (scn == 3){
     ThetaBS_withNA <- cbind(c(0.95,0.9,0.1,0.5,0.5),
                             c(0.95,0.1,0.9,0.5,0.5))
     PsiBS_withNA   <- cbind(c(0.4,0.4,0.05,0.2,0.2),
                             c(0.05,0.05,0.4,0.05,0.05))
   }
   
   if (scn == 2){
     ThetaBS_withNA <- cbind(c(0.95,0.5,0.5,0.5,0.5),
                             c(0.95,0.5,0.5,0.5,0.5))
     PsiBS_withNA   <- cbind(c(0.4,0.4,0.05,0.2,0.2),
                             c(0.05,0.05,0.4,0.05,0.05))
   }
   
   if (scn == 1){
     ThetaBS_withNA <- cbind(c(0.95,0.5,0.5,0.5,0.5),
                             c(0.95,0.5,0.5,0.5,0.5))
     PsiBS_withNA   <- cbind(c(0.3,0.3,0.15,0.2,0.2),
                             c(0.15,0.15,0.3,0.05,0.05))
   }
   
   # the following paramter names are set using names in the 'baker' package:
   set_parameter0 <- list(
     cause_list      = c(LETTERS[1:J]),
     etiology        = c(0.5,0.2,0.15,0.1,0.05), #same length as cause_list
     #etiology        = rep(0.2,J), #same length as cause_list
     pathogen_BrS    = LETTERS[1:J],
     meas_nm         = list(MBS = c("MBS1")),
     Lambda          = lambda,              #ctrl mix
     Eta             = t(replicate(J,eta)), #case mix, row number equal to Jcause.
     PsiBS           = PsiBS_withNA,
     ThetaBS         = ThetaBS_withNA,
     Nu      =     N, # control size.
     Nd      =     N  # case size.
   )
   
   res[,,iter] <- round(compute_logOR_single_cause(set_parameter0),2)
   
   for (pick in 1:J){
     set_parameter <- set_parameter0
     set_parameter$ThetaBS <- set_parameter0$PsiBS
     set_parameter$ThetaBS[pick,] <- set_parameter0$ThetaBS[pick,]
     set_parameter$etiology <- rep(0,J); set_parameter$etiology[pick] <- 1
     res_cond[,,iter,pick] <- round(compute_logOR_single_cause(set_parameter),2)
   }
 }
 
 ind <- sapply(c(0,0.5,1),function(x) which(subclass_mix_seq==x))
 logOR_lim <- c(-2.15,2.15)
 col_seq <- c("dodgerblue2","orange")
 logOR_seq <- log(c(0.25,0.5,1,2,4))
 pick_one <- 3

 print(paste0("==Shading pairs of ",pch_seq_cause[pick_one]," and others.==="))
 for (j in 1:J){
   for (l in 1:J){
     
     par(mar=c(0,0,0,0)); 
     if (j==J){
       par(mar=c(0,0,0,0))
     }
     if (l%%J==0){
       par(mar=c(0,0,0,1)) 
     }
     if (l%%J==1){
       par(mar=c(0,1,0,0))
     }
     if (!(j==l)){
       plot(res[j,l,],type="l",xlab="",ylab="",
            ylim=logOR_lim, lwd=5,
            xaxt="n",
            yaxt="n",
            col=col_seq[1+(l>j)],
            #lty=c(2,1)[1+(l>j)],
            lty=1,
            bty="n"
       )
       box(col="lightgray")
       abline(h=0,col="lightgray",lwd=3,lty=3)
       
       if (j<l){
         matplot(res_cond[j,l,,],type="l",add=TRUE,pch=LETTERS[1:J],lwd=2,lty=2,
                 col=col_seq_cause)
       }
       lab_ord <- c(j,l); if (j>l){lab_ord <- rev(lab_ord)}
       mtext(paste0("(",set_parameter$pathogen_BrS[lab_ord[1]],",", 
                    set_parameter$pathogen_BrS[lab_ord[2]],")"), 
             side=3, adj=0.1,line=-2)
       
       if (l%%J==1){
         axis(2,at = logOR_seq, 
              labels = round(exp(logOR_seq),1),
              las=2,cex.axis=cex1)
       }
       
       if (l%%J==0){
         axis(4,at = logOR_seq, 
              labels = round(exp(logOR_seq),1),
              las=2,cex.axis=cex1)
       }
       
       if (j==J){
         axis(1,at=seq_along(subclass_mix_seq)[ind],
         labels=rep("",length(ind)),cex.axis = cex1,las=1)
         axis(1,at=seq_along(subclass_mix_seq)[ind]+c(1,rep(0,length(ind)-2),-1),
         labels=subclass_mix_seq[ind],cex.axis = cex1,las=1,tick=FALSE)
       }
       if (j==1){
         axis(3,at=seq_along(subclass_mix_seq)[ind],
         labels=rep("",length(ind)),cex.axis = cex1,las=1)
         axis(3,at=seq_along(subclass_mix_seq)[ind]+c(1,rep(0,length(ind)-2),-1),
         labels=subclass_mix_seq[ind],cex.axis = cex1,las=1,tick=FALSE)
       }
       if (j==5 & l==1){
         mtext(expression(atop("Odds Ratio","(log-scale)")), side = 2, line = 4, 
               cex=cex_label1, las=2)
       }
       if (j==5){
         mtext(expression(lambda[o]),side=1,line=4,cex=cex_label1)
       }
       
       if ((j<l) && (l==pick_one | j==pick_one )){
         # add shading cells for oen picked pathogen among cases:
         color <- rgb(190, 190, 190, alpha=80, maxColorValue=255)
         rect(par("usr")[1], par("usr")[3], par("usr")[2], 
              par("usr")[4], density = 100, col = color)
         
         matplot(res_cond[j,l,,],type="l",add=TRUE,lwd=2,col=col_seq_cause,lty=lty_seq_cause)
         for (ell in 1:J){
           where_add_letter <- quantile(seq_along(subclass_mix_seq),pch_pos_seq+gap*ell)
           points(where_add_letter, res_cond[j,l,where_add_letter,ell], pch=pch_seq_cause[ell])
         }
         mtext(paste0("(",set_parameter$pathogen_BrS[lab_ord[1]],",", 
                      set_parameter$pathogen_BrS[lab_ord[2]],")"), 
               side=3, adj=0.1,line=-2)
       }
       
     }else{
       
       plot(1, type="n", axes=FALSE, xlab="", ylab="", bty="n",
            xlim=c(0,1),ylim=c(0,1))
       
       
       if (j==3){
         text(labels=expression(CASES%up%""),x=.7,
              y=0.55,srt=-49,col=col_seq[2],cex=1.8,adj=0.5,font=4)
         text(labels=expression(CONTROLS%down%""),x=.42,
              y=0.38,srt=-49,col=col_seq[1],cex=1.8,adj=0.5,font=4)
       }
       if (j!=1 & j!=J){
         dg <- par("usr") 
         segments(dg[1],dg[4],dg[2],dg[3], col='lightgray',lwd=3)
       }
       if (j==J){
         legend("top",LETTERS[1:J],lty=2,col=col_seq_cause,cex = 1.5,lwd=2,
                bty="n",horiz=FALSE)
       }
     }
   }
 }
}
par(oldpar)
zhenkewu/baker documentation built on March 17, 2022, 9:54 p.m.