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server.R
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server.R
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# setup ----
# deployApp()
library(deSolve)
library(plyr)
library(grid)
library(compiler)
library(shinyTime)
library(lubridate)
library(TeachingDemos)
library(rmarkdown)
library(knitr)
library(DT)
library(rsconnect)
library(tidyverse)
default_dose_example_csv <- '"Date","Inf_st_Time","Inf_ed_Time","Dose"
"17.05.03","10:30","11:30","500"
"17.05.03","22:30","23:30","750"
"17.05.04","10:30","11:30","1000"
"17.05.04","22:30","23:30","1000"'
calculate_crcl <- function(age, weight, sex, scr){
crcl <- ((140-age) * weight * ifelse(sex == 'Female', 0.85, 1)) / (72*scr)
return(crcl)
}
# main ----
shiny::shinyServer(function(input, output) {
datasetInput <- reactive({
coln=c("Date","Inf_st_Time","Inf_ed_Time","Dose" )
dat1=c("17.05.03", "10:30", "11:30","500")
dat2=c("17.05.03", "22:30", "23:30","500")
dat3=c("17.05.04", "10:30", "11:30","1000")
dat4=c("17.05.04", "22:30", "23:30","1000")
suppl=data.frame (rbind(dat1,dat2,dat3,dat4))
colnames(suppl)<-coln
rownames(suppl)<-NULL
suppl
})
dose.data <- reactive({
inFile <- input$file1
if (is.null(inFile)) return(NULL)
a=read.csv(inFile$datapath, header=T, stringsAsFactors = T)
b=a[complete.cases(a), ]
b$paste=paste(b$Date,b$Time)
b
#Time calculation code is copyrighted
})
sim.data <- reactive({
obs1conc= input$obsc
obs1time=input$obst
obs1dat=input$obsd
obs11conc= input$obsc1
obs11time=input$obst1
obs11dat=input$obsd1
obs2conc= input$obsc2
obs2time=input$obst2
obs2dat=input$obsd2
inFile <- input$file1
WEIGHT <- input$weight
AGE<-input$age
SCR<-input$scr
CLCR <- calculate_crcl(AGE, WEIGHT, input$sex, SCR)
# Dose Data1 -------------------
input_file_text <- ifelse(is.null(input$file1),
yes = default_dose_example_csv,
no = input$file1$datapath)
rawdata <- read_csv(input_file_text, col_types = 'cccd') %>%
as.data.frame() %>%
print()
# 1. Dose Data1 ------------------------------
#rawdata=read.csv(inFile$datapath,header=T)
#rawdata
rawdata2=rawdata[complete.cases(rawdata), ]
rawdata2
infTime3=as.numeric(difftime(strptime(rawdata2[,3],"%H:%M"),strptime(rawdata2[,2],"%H:%M"),units="hours"))
infTime3
for(i in 1:length(infTime3)){
if(infTime3[i]<0){
infTime3[i]=24+infTime3[i]
}
}
RATE3=rawdata2[,4]/infTime3
RATE3
before=strptime(paste(rawdata[,1],rawdata[,2]), "%y.%m.%d %H:%M")
before
after=strptime(paste(rawdata[,1],rawdata[,3]), "%y.%m.%d %H:%M")
after
if (input$Observations=='1')
{
Observeddate=paste(input$obsDate, substr(input$obsTime, 12, 20))
pointtime=abs(as.numeric(difftime(before[1],Observeddate,units="hours"))) #pointtime
dose2 = input$newdose
# 2. population INFORM. ----------------------
CLPOP = 2.82 #Creatine Level Compartment1
CLPOP2 = 0.837 #Creatine Level Compartment2
V1POP = 31.7 #Volume Compartment1
QPOP = 11.8
V2POP = 75.9 #Volume Compartment1
# 3. calculation ------------
nd1=sum(cumprod(rawdata2[,4]>0)) #ndoses=number of dosing
nd=sum(cumprod(rawdata2[,4]>0))*2 #ndoses=number of dosing
B1T=0 #Time of first dosing
nd2=nd*3
newtau=ceiling(as.numeric(difftime(Observeddate,before[nd1],units="hours"))) #time duration
result222=c()
for (i in 1:nd1){
result222[i]=abs(as.numeric(difftime(before[i],before[1],units="hours")))
#print(result222)
}
tau=result222
maxtime=c(max(tau)+newtau) #nd*tau
maxtime
i=c()
v = RATE3
result=c()
for(i in 1:(nd)){
print(i)
result[i] = list(append(c(v[i]),0))
#print(result)
if(i==nd)break;
}
result = c(do.call("cbind",result))
result
RATEinf<-result #RATE by point
RATEinf
flag<-complete.cases(RATEinf)
RATEinf=RATEinf[flag]
RATEinf
resultf=c()
result2=c()
result22=c()
a=append(tau,c(outer(max(tau),c(abs(newtau)*(1:nd1)),"+")))
a
i=c()
num=1
b=infTime3
for (i in 1:(nd+1)){
result22[i]=a[i]
#cat("i=",i,"num=",num,"\n")
#print(result22[i])
resultf[num]=result22[i]
if(i==nd+1)break;
num=num+1
result2[num]=a[i]+b[i]
#cat("i=",i,"num=",num,"\n")
#print(result2[num])
resultf[num]=result2[num]
i=i+1
num=num+1
}
TIMEinf=resultf
TIMEinf
flag<-complete.cases(TIMEinf)
TIMEinf=TIMEinf[flag]
TIMEinf
Cstepdoseinf <- approxfun(TIMEinf, RATEinf, method = "const")
Cstepdoseinf(0:max(TIMEinf))
length(Cstepdoseinf(0:max(TIMEinf)))
n=1
ID = seq(from = 1, to = n, by = 1)
TVCL=CLPOP*(CLCR/72)**CLPOP2
TVV2 <- V2POP*(WEIGHT/60)
TVV1 <- V1POP
Q <- QPOP
B1T=0
TIME <- seq(from = 0, to = pointtime, by =0.1)
TIME <- sort(unique(c(TIME,B1T)))
TIMElast <- max(TIME)
}
if (input$Observations=='2')
{
Observeddate1=paste(input$obsd1, substr(input$obst1, 12, 20))
Observeddate2=paste(input$obsd2, substr(input$obst2, 12, 20))
pointtime1=abs(as.numeric(difftime(before[1],Observeddate1,units="hours"))) #pointtime
pointtime2=abs(as.numeric(difftime(before[1],Observeddate2,units="hours"))) #pointtime
dose2 = input$newdose
###### 4. population INFORM. ----------
CLPOP = 2.82 #Creatine Level Compartment1
CLPOP2 = 0.837 #Creatine Level Compartment2
V1POP = 31.7 #Volume Compartment1
QPOP = 11.8
V2POP = 75.9 #Volume Compartment1
# calculation -----
nd1=sum(cumprod(rawdata2[,4]>0)) #ndoses=number of dosing
nd=sum(cumprod(rawdata2[,4]>0))*2 #ndoses=number of dosing
B1T=0 #Time of first dosing
vec=c(Observeddate1,Observeddate2)
vec[1]<vec[2]
Observeddatef=c()
fun.obsdate<-function(vec){
if(vec[1]>vec[2]) Observeddatef=vec[1]
if(vec[1]<vec[2]) Observeddatef=vec[2]
return(Observeddatef)
}
fun.obsdate(vec)
pointtime3=abs(as.numeric(difftime(before[1],fun.obsdate(vec),units="hours"))) #pointtime
newtau=ceiling(as.numeric(difftime(fun.obsdate(vec),before[nd1],units="hours")))
result222=c()
for (i in 1:nd1){
result222[i]=abs(as.numeric(difftime(before[i],before[1],units="hours")))
#print(result222)
}
tau=result222
maxtime=max(tau)+newtau #nd*tau
maxtime
i=c()
v = RATE3
result=c()
for(i in 1:(nd)){
print(i)
result[i] = list(append(c(v[i]),0))
#print(result)
if(i==nd)break;
}
result = c(do.call("cbind",result))
result
RATEinf<-result #RATE by point
RATEinf
flag<-complete.cases(RATEinf)
RATEinf=RATEinf[flag]
RATEinf
cat("RATEinf:",RATEinf,length(RATEinf))
resultf=c()
result2=c()
result22=c()
a=append(tau,c(outer(max(tau),c(abs(newtau)*(1:nd1)),"+")))
a
i=c()
num=1
b=infTime3
for (i in 1:(nd+1)){
result22[i]=a[i]
#cat("i=",i,"num=",num,"\n")
#print(result22[i])
resultf[num]=result22[i]
if(i==nd+1)break;
num=num+1
result2[num]=a[i]+b[i]
#cat("i=",i,"num=",num,"\n")
#print(result2[num])
resultf[num]=result2[num]
i=i+1
num=num+1
}
TIMEinf=resultf
TIMEinf
flag<-complete.cases(TIMEinf)
TIMEinf=TIMEinf[flag]
TIMEinf
cat("TIMEinf:",TIMEinf,length(TIMEinf))
Cstepdoseinf <- approxfun(TIMEinf, RATEinf, method = "const")
Cstepdoseinf(0:max(TIMEinf))
length(Cstepdoseinf(0:max(TIMEinf)))
n=1
ID = seq(from = 1, to = n, by = 1)
TVCL=CLPOP*(CLCR/72)**CLPOP2
TVV2 <- V2POP*(WEIGHT/60)
TVV1 <- V1POP
Q <- QPOP
B1T=0
TIME <- seq(from = 0, to = pointtime3, by =0.1)
TIME <- sort(unique(c(TIME,B1T)))
TIMElast <- max(TIME)
}
#Cstepdoseinf(T) function : please refer to http://onlinelibrary.wiley.com/doi/10.1002/psp4.21/full#footer-support-info
DOSEdata <- data.frame(var = rep(1, times = nd1),
time = tau, #seq(0,TIMElast-tau,tau),
value = rep(0, times = nd1),
method = rep("add", times = nd1))
EPS1SD <- 1.00E-04 #Additive residual error
EPS2SD <- 0.253 #Proportional residual error
EPS2SDsq=(EPS2SD)^2
ETA1SD <- 0.257 # Clearance eta
ETA2SD <- 0.959 # Volume eta
TVCL=CLPOP*(CLCR/72) ** CLPOP2
TVV2 <- V2POP*(WEIGHT/60)
TVV1 <- V1POP
Q <- QPOP
## ltv2mat copy right:: Prof. BAE
cmat=function(vec){
LENGTH=length(vec)
DIM=as.integer(round((sqrt(8*LENGTH+1)-1)/2,0))
if(DIM*(DIM+1)/2!=LENGTH) return(NULL)
mat=matrix(nrow=DIM, ncol=DIM)
mat[upper.tri(mat, diag=TRUE)]=vec
mat[lower.tri(mat)] = t(mat)[lower.tri(mat)]
return(mat)
}
omega <- cmat(c(ETA1SD ,0,ETA2SD)) #c(Clearance eta,0,volume eta)
omega.inv <- solve(omega)
omega.inv
# model
model <- function(T,A,eta){
RateC <-Cstepdoseinf(T)
K1=QPOP/V1POP
K2=QPOP/(TVV2*exp(eta[2]))
K3=(TVCL*exp(eta[1])) / TVV1
dA <- vector(length = 2)
dA[1] = (RateC) - (K1*A[1]) + (K2*A[2]) - (K3*A[1]) #Central compartment
dA[2] = (K1*A[1]) - (K2*A[2]) #Peripheral compartment
list(dA)
}
mod.cmp =cmpfun(model)
A_0 <- c(A1 = 0, A2 = 0)
if (input$Observations=='1')
{
y=c(obs1conc)
mapb2 <- function(eta){
etamat=matrix(unlist(eta))
out <- lsoda(c(A1=0 ,A2=0), TIME, model, eta, events=list(data=DOSEdata))
out <- cbind(out, DV=out[,"A1"]/TVV1)
head(out)
eta=c(eta[1],eta[2])
eta_m=unlist(matrix(eta,nrow = 2))
sig2=EPS2SDsq
sig2j <- subset(out[,4],out[,1]==pointtime)^2*sig2
sqwres <- log(sig2j) + (1/sig2j)*(y[1]-subset(out[,4],out[,1]==pointtime))^2
nOn <- diag(t(eta_m) %*% omega.inv %*% eta_m)
return(sum(sqwres)+ nOn)
}
}
if (input$Observations=='2')
{
y=c(input$obsc1,input$obsc2)
mapb2 <- function(eta){
etamat=matrix(unlist(eta))
out <- lsoda(c(A1=0 ,A2=0), TIME, model, eta, events=list(data=DOSEdata))
out <- cbind(out, DV=out[,"A1"]/TVV1)
head(out)
eta=c(eta[1],eta[2])
eta_m=unlist(matrix(eta,nrow = 2))
sig2=EPS2SDsq
sig2j <- subset(out[,4],out[,1]==pointtime1)^2*sig2
sqwres <- log(sig2j) + (1/sig2j)*(y[1]-subset(out[,4],out[,1]==pointtime1))^2 + (1/sig2j)*(y[2]-subset(out[,4],out[,1]==pointtime2))^2
nOn <- diag(t(eta_m) %*% omega.inv %*% eta_m)
return(sum(sqwres)+ nOn)
}
}
mapb2.cmp =cmpfun(mapb2)
ini=c(0.1,0.1)
withProgress(message = 'minimization in progress', min = 0, max = 100,value = 99,
{
FIT=optim(ini, mapb2.cmp, control = list(trace=1,REPORT=1),method="L-BFGS-B")
FIT$par
}
)
# cat("FIT$par=",FIT$par)
# cat("omega.inv=",omega.inv)
out <- lsoda(c(A1=0, A2=0), TIME, mod.cmp, FIT$par,events = list(data = DOSEdata ))
out <- cbind(out, DV=out[,"A1"]/TVV1)
outs<-data.frame(out)
# outs$DV=outs[,"A1"]/TVV1
outs$maxtime=maxtime
if (input$Observations=='1'){
outs$pointtime=pointtime
outs$Observeddate=Observeddate
outs$predictedConc=subset(outs[,4],outs[,1]==pointtime)
outs$observedConc=obs1conc
}
if(input$Observations=='2'){
outs$observedConc1=obs11conc
outs$observedConc2=obs2conc
outs$pointtime1=pointtime1
outs$pointtime2=pointtime2
outs$Observeddate=fun.obsdate(vec)
outs$predictedConc1=subset(outs[,4],outs[,1]==pointtime1)
outs$predictedConc2=subset(outs[,4],outs[,1]==pointtime2)
}
outs$TIME=TIME
outs$CL <- TVCL*(exp(FIT$par[1])) #predicted CL
outs$V2 <- TVV2*(exp(FIT$par[2])) #predicted V2
outs$V1 <- V1POP #predicted V1
#
# if (input$Observations=='1')
# {
#
# }
# if (input$Observations=='2')
# {
# outs$obs1=obs11conc
# outs$obs2=obs2conc
# }
outs2=merge(x=outs,y=DOSEdata, by="time",all.x=TRUE)
outs2
}
)
output$downloadData <- downloadHandler(
filename = function() { paste("dose_example", '.csv', sep='') },
content = function(file) {
write.csv(datasetInput(), file, row.names = F)
}
)
output$dosing_history_contents <- renderTable({
if (is.null(input$file1)) return(read_csv(default_dose_example_csv, col_types='cccn'))
return(read_csv(input$file1$datapath, col_types='cccn'))
})
# crcl: https://www.mdcalc.com/creatinine-clearance-cockcroft-gault-equation
output$creatinine_clearance <- renderText({
return(calculate_crcl(input$age, input$weight, input$sex, input$scr) %>% round(digits = 2))
})
output$output_table1_time_predicted_concentration <- renderTable({
prt1 <- sim.data()
prt2 <- prt1[complete.cases(prt1),]
if (input$Observations=='1') {
prtx_predicted_concentration <- prt2 %>%
slice(2) %>%
select(pointtime,
`observed conc.`=observedConc,
`predicted conc.`=predictedConc)
}
if (input$Observations=='2') {
prtx_predicted_concentration <- prt2 %>%
slice(2) %>%
select(pointtime1,
observedConc1,
predictedConc1)
}
return(prtx_predicted_concentration)
})
output$outputtable2 <- renderTable({
prt1=sim.data()
prt2=prt1[complete.cases(prt1),]
if (input$Observations=='1')
{
prtx=prt2[2,c("CL","V1","V2")]
}
if (input$Observations=='2')
{
prtx=prt2[2,c("pointtime2","observedConc2","predictedConc2")]
}
prtx
})
output$outputtable3 <- renderTable({
prt1=sim.data()
prt2=prt1[complete.cases(prt1),]
if(input$Observations=='1'){
}
if (input$Observations=='2')
{
prtx=prt2[2,c("CL","V1","V2")]
prtx
}
})
output$plotCONC <- renderPlot({
data1=sim.data()
plot(data1$TIME,data1$DV,ylab="concentration", xlab="time",type="l", pch=4,main="Concentration Curve of Vancomycin",col="#009ACD", ylim=c(0,50),xlim=c(0,data1$maxtime[1]))
if (input$Observations=='1'){
points(data1$pointtime,data1$observedConc, col="red", pch=6,cex=1.0) #y point
points(data1$pointtime[1],subset(data1$DV,data1$time==data1$pointtime), col="green", pch=6,cex=1.0) #predicted DV point
legend(data1$maxtime[1]-11,50,legend=c("observed conc.","predicted conc."),col=c("red","green"),pch=6:6, cex=0.8)
}
if(input$Observations=='2'){
points(data1$pointtime1,data1$observedConc1, col="red", pch=6,cex=1.0) #y point
points(data1$pointtime1[1],subset(data1$DV,data1$time==data1$pointtime1), col="green", pch=6,cex=1.0) #predicted DV point
points(data1$pointtime2,data1$observedConc2, col="blue", pch=1,cex=1.0) #y2 point
points(data1$pointtime2[1],subset(data1$DV,data1$time==data1$pointtime2), col="black", pch=1,cex=1.0) #predicted DV point 1
legend(data1$maxtime[1]-11,50,legend=c("observed conc.","predicted conc."),col=c("red","green"),pch=6:6, cex=0.8)
}
})
sim2.data <- reactive({
obs1conc= input$obsc
obs1time=input$obst
obs1dat=input$obsd
obs11conc= input$obsc1
obs11time=input$obst1
obs11dat=input$obsd1
obs2conc= input$obsc2
obs2time=input$obst2
obs2dat=input$obsd2
inFile <- input$file1
WEIGHT <- input$weight
AGE<-input$age
SCR<-input$scr
CLCR <- calculate_crcl(AGE, WEIGHT, input$sex, SCR)
# Dose Data1 -------------------
input_file_text <- ifelse(is.null(input$file1),
yes = default_dose_example_csv,
no = input$file1$datapath)
rawdata <- read_csv(input_file_text, col_types = 'cccd') %>%
as.data.frame() %>%
print()
#rawdata=read.csv(inFile$datapath,header=T)
#rawdata
rawdata2=rawdata[complete.cases(rawdata), ]
rawdata2
infTime3=as.numeric(difftime(strptime(rawdata2[,3],"%H:%M"),strptime(rawdata2[,2],"%H:%M"),units="hours"))
infTime3
for(i in 1:length(infTime3)){
if(infTime3[i]<0){
infTime3[i]=24+infTime3[i]
}
}
RATE3=rawdata2[,4]/infTime3
RATE3
cat("RATE3:",RATE3,"\n")
before=strptime(paste(rawdata[,1],rawdata[,2]), "%y.%m.%d %H:%M")
before
after=strptime(paste(rawdata[,1],rawdata[,3]), "%y.%m.%d %H:%M")
after
if (input$Observations=='1')
{
Observeddate=paste(input$obsDate, substr(input$obsTime, 12, 20))
pointtime=abs(as.numeric(difftime(before[1],Observeddate,units="hours"))) #pointtime
dose2 = input$newdose
infTime2=input$newinf #infTime2=1 #infusion time
infTime2
# population INFORM. --------------------------------
CLPOP = 2.82 #Creatine Level Compartment1
CLPOP2 = 0.837 #Creatine Level Compartment2
V1POP = 31.7 #Volume Compartment1
QPOP = 11.8
V2POP = 75.9 #Volume Compartment1
# calculation --------------------------------------
nd1=sum(cumprod(rawdata2[,4]>0))
B1T=0 #Time of first dosing
RATE2=dose2/infTime2 #dose by 1 time
nd2=nd1*6
newtau2=input$newtau
result222=c()
for (i in 1:nd1){
result222[i]=abs(as.numeric(difftime(before[i],before[1],units="hours")))
# print(result222)
}
tau=result222
maxtime2=max(tau)+newtau2 #nd*tau
maxtime2
# cat("maxtime2:",maxtime2)
i=c()
v = RATE3
result=c()
for(i in 1:nd1){
# print(i)
result[i] = list(append(c(v[i]),0))
#print(result)
if(i==nd1)break;
}
result = c(do.call("cbind",result))
result
cat("result:", result,"\n")
RATEinf<-append(result,0) #RATE by point
RATEinf
flag<-complete.cases(RATEinf)
RATEinf=RATEinf[flag]
resultf=c()
result2=c()
result22=c()
i=c()
num=1
a=append(tau,c(outer(max(tau),c(abs(newtau2)*(1:nd1)),"+")))
b=infTime3
cat("result:",result,"\n")
cat("a:",a)
for (i in 1:(nd1+1)){
result22[i]=a[i]
#cat("i=",i,"num=",num,"\n")
#print(result22[i])
resultf[num]=result22[i]
if(i==nd1+1)break;
num=num+1
result2[num]=a[i]+b[i]
#cat("i=",i,"num=",num,"\n")
#print(result2[num])
resultf[num]=result2[num]
i=i+1
num=num+1
}
TIMEinf=resultf
flag<-complete.cases(TIMEinf)
TIMEinf=TIMEinf[flag]
TIMEinf
TIMEinf2<-append(TIMEinf,outer(c(maxtime2+infTime2,maxtime2+newtau2), newtau2 * 0:ceiling((nd2/2)-1),"+")[-(length(outer(c(maxtime2+infTime2,maxtime2+newtau2), newtau2 * 0:ceiling((nd2/2)-1),"+")))])
TIMEinf2
RATEinf2<-append(c(rep(c(RATE2,0),nd2/2)),result,0) #RATE by point
RATEinf2
flag<-complete.cases(RATEinf2)
RATEinf2=RATEinf2[flag]
length(TIMEinf2)
length(RATEinf2)
cat("a:",a,"\n")
cat("newtau2:",newtau2,"\n")
cat("TIMEinf2:",TIMEinf2,length(TIMEinf),"\n")
cat("RATEinf2:",RATEinf2,length(RATEinf),"\n")
cat("infTime3:",infTime3,length(infTime3),"\n")
Cstepdoseinf <- approxfun(TIMEinf, RATEinf, method = "const")
Cstepdoseinf(0:max(TIMEinf))
length(Cstepdoseinf(0:max(TIMEinf)))
Cstepdoseinf2 <- approxfun(TIMEinf2, RATEinf2, method = "const")
Cstepdoseinf2(0:max(TIMEinf2))
length(Cstepdoseinf2(0:max(TIMEinf2)))
n=1
ID = seq(from = 1, to = n, by = 1)
TVCL=CLPOP*(CLCR/72)**CLPOP2
TVV2 <- V2POP*(WEIGHT/60)
TVV1 <- V1POP
Q <- QPOP
B1T=0
TIME <- seq(from = 0, to = maxtime2, by =0.1)
TIME <- sort(unique(c(TIME,B1T)))
TIMElast <- max(TIME)
TIME3 <- seq(from = 0, to = max(TIMEinf2), by =0.1)
ndoses=TIMElast/tau
}
RATE3=rawdata2[,4]/infTime3
RATE3
if (input$Observations=='2')
{
infTime2=input$newinf
Observeddate1=paste(input$obsd1, substr(input$obst1, 12, 20))
Observeddate2=paste(input$obsd2, substr(input$obst2, 12, 20))
pointtime1=abs(as.numeric(difftime(before[1],Observeddate1,units="hours"))) #pointtime
pointtime2=abs(as.numeric(difftime(before[1],Observeddate2,units="hours"))) #pointtime
dose2 = input$newdose
##################################
###### population INFORM ----
##################################
CLPOP = 2.82 #Creatine Level Compartment1
CLPOP2 = 0.837 #Creatine Level Compartment2
V1POP = 31.7 #Volume Compartment1
QPOP = 11.8
V2POP = 75.9 #Volume Compartment1
# calculation ----
nd1=sum(cumprod(rawdata2[,4]>0)) #ndoses=number of dosing
# nd=sum(cumprod(rawdata2[,4]>0))*2 #ndoses=number of dosing
RATE2=dose2/infTime2 #dose by 1 time
B1T=0 #Time of first dosing
nd2=nd1*6
vec=c(Observeddate1,Observeddate2)
Observeddatef=c()
fun.obsdate<-function(vec){
if(vec[1]>vec[2]) Observeddatef=vec[1]
if(vec[1]<vec[2]) Observeddatef=vec[2]
return(Observeddatef)
}
fun.obsdate(vec)
pointtime3=abs(as.numeric(difftime(before[1],fun.obsdate(vec),units="hours"))) #pointtime
#newtau2=ceiling(as.numeric(difftime(fun.obsdate(vec),before[nd1],units="hours")))
newtau2=input$newtau
result222=c()
for (i in 1:nd1){
result222[i]=abs(as.numeric(difftime(before[i],before[1],units="hours")))
#print(result222)
}
tau=result222
maxtime2=max(tau)+newtau2 #nd*tau
maxtime2
cat("maxtau=",max(tau))
cat("maxtime2=",maxtime2)
i=c()
v = RATE3
result=c()
for(i in 1:nd1){
print(i)
result[i] = list(append(c(v[i]),0))
print(result)
if(i==nd1)break;
}
result = c(do.call("cbind",result))
result
RATEinf<-append(result,0) #RATE by point
RATEinf
flag<-complete.cases(RATEinf)
RATEinf=RATEinf[flag]
RATEinf
resultf=c()
result2=c()
result22=c()
a=append(tau,c(outer(max(tau),c(abs(newtau2)*(1:nd1)),"+")))
a
i=c()
num=1
b=infTime3
for (i in 1:(nd1+1)){
result22[i]=a[i]
#cat("i=",i,"num=",num,"\n")
#print(result22[i])
resultf[num]=result22[i]
if(i==nd1+1)break;
num=num+1
result2[num]=a[i]+b[i]
#cat("i=",i,"num=",num,"\n")
#print(result2[num])
resultf[num]=result2[num]
i=i+1
num=num+1
}
TIMEinf=resultf
flag<-complete.cases(TIMEinf)
TIMEinf=TIMEinf[flag]
TIMEinf
TIMEinf2<-append(TIMEinf,outer(c(maxtime2+infTime2,maxtime2+newtau2), newtau2 * 0:ceiling((nd2/2)-1),"+")[-(length(outer(c(maxtime2+infTime2,maxtime2+newtau2), newtau2 * 0:ceiling((nd2/2)-1),"+")))])
TIMEinf2
cat("nd2=",nd2,"\n")
cat("maxtime2=", maxtime2,"\n")
RATEinf2<-append(c(rep(c(RATE2,0),nd2/2)),result,0) #RATE by point
RATEinf2
flag<-complete.cases(RATEinf2)
RATEinf2=RATEinf2[flag]
length(TIMEinf2)
length(RATEinf2)
cat("newtau2:",newtau2,length(newtau2),"\n")
cat("TIMEinf2:",TIMEinf2,length(TIMEinf2),"\n")
cat("RATEinf2:",RATEinf2,length(RATEinf2),"\n")
cat("infTime32:",infTime3,length(infTime3),"\n")
cat("TIMEinf:",TIMEinf,length(TIMEinf),"\n")
cat("RATEinf:",RATEinf,length(RATEinf),"\n")
Cstepdoseinf <- approxfun(TIMEinf, RATEinf, method = "const")
Cstepdoseinf(0:max(TIMEinf))
length(Cstepdoseinf(0:max(TIMEinf)))
Cstepdoseinf2 <- approxfun(TIMEinf2, RATEinf2, method = "const")
Cstepdoseinf2(0:max(TIMEinf2))