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server.R
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##################################################
#####
##### Age and Growth app - Server
##### Jonas Vasconcelos-Filho
##### 09/06/2019
##### v 1.0
#####
##################################################
# check.packages <- function(pkg){
# new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
# if (length(new.pkg))
# install.packages(new.pkg, dependencies = TRUE)
# sapply(pkg, require, character.only = TRUE)
# }
# # Usage example
# packages<-c("shiny", "FSA", "fishmethods", "AICcmodavg",
# "nlstools", "shinydashboard", "shinyWidgets",
# "ggplot2", "waiter","shinyalert")
#check.packages(packages)
library("shiny")
library("FSA")
library("fishmethods")
library("AICcmodavg")
library("nlstools")
library("shinydashboard")
library("shinyWidgets")
library("ggplot2")
library("waiter")
library("shinyalert")
library("rethinking")
library("tidyverse")
library("investr")
# if(!any(check.packages(packages)==F)){
shinyServer(function(session,input, output) {
###################################
#### Length-Weight Relationship (LWR)
# Data
lwrdata <- reactive({
file1 <- input$lwrfile
if(is.null(file1)) {return()}
read.table(file = file1$datapath,
sep = input$lwrsep,
header = input$lwrheader,
stringsAsFactors = input$lwrstringAsFactors)
})
# LWR - Variables
observe({
Vxlwr<-1:length(colnames(lwrdata()))
atr_listlwr<-list(names = colnames(lwrdata()))
attributes(Vxlwr)<-atr_listlwr
Faclwr<-!sapply(lwrdata(), is.factor)
Vxlwr<-Vxlwr[Faclwr]
updateSelectInput(session, "lwrx", "1. Select x-variable",
choices = Vxlwr)
})
observe({
Vylwr<-1:length(colnames(lwrdata()))
atr_listlwr<-list(names = colnames(lwrdata()))
attributes(Vylwr)<-atr_listlwr
Faclwr<-!sapply(lwrdata(), is.factor)
Vylwr<-Vylwr[Faclwr]
updateSelectInput(session, "lwry", "2. Select y-variable",
choices = Vylwr)
})
observe({
Vx<-1:length(colnames(lwrdata()))
atr_list<-list(names = colnames(lwrdata()))
attributes(Vx)<-atr_list
Fac<-!sapply(lwrdata(), is.factor)
Vx<-c("None", Vx[!Fac])
updateSelectInput(session, "lwrfactor", "3. Select factor-variable:",
choices = Vx, selected = "None")
})
## Table, summary, and structure
output$fileoblwr <- renderPrint({
if(is.null(input$lwrfile)) {return()}
str(lwrdata())
})
output$summlwr <- renderPrint({
if(is.null(input$lwrfile)) {return()}
summary(lwrdata())
})
output$tableuilwr <- renderUI({
dataoutlwr <- lwrdata()
output$dataoutlwr<-renderDataTable(dataoutlwr)
dataTableOutput("dataoutlwr")
})
output$lwrtb <- renderUI({
if(is.null(input$lwrfile)) {return()}
tabsetPanel(
tabPanel("Data",
uiOutput("tableuilwr")),
tabPanel("Structure",
verbatimTextOutput("fileoblwr")),
tabPanel("Summary",
verbatimTextOutput("summlwr"))
)
})
# Graphical parameters
lwrx <- reactive({
as.numeric(input$lwrx)
})
lwry <- reactive({
as.numeric(input$lwry)
})
lwrpch<-reactive({
as.numeric(input$lwrpch)
})
lwrcolpt<-reactive({
as.numeric(input$lwrcolpt)
})
lwrA <- reactive({
as.numeric(input$lwrA)
})
lwrB <- reactive({
as.numeric(input$lwrB)
})
lwrptsize <- reactive({
as.numeric(input$lwrptsize)
})
lwrptalpha <- reactive({
as.numeric(input$lwrptalpha)
})
lwrICalpha <- reactive({
as.numeric(input$lwrICalpha)
})
lwrfactor<-reactive({
as.numeric(input$lwrfactor)
})
widthlwr <- reactive({
as.numeric(input$widthlwr)
})
heightlwr <- reactive({
as.numeric(input$heightlwr)
})
reslwr <- reactive({
as.numeric(input$reslwr)
})
##############################
## Models
modLWRnls2<-reactive({
mods$lwr_Lm_Ancova_H1 <- FALSE
H0 <- 3
if(!is.na(lwrfactor())){
dados<-data.frame(x = lwrdata()[, lwrx()],
y = lwrdata()[, lwry()],
factor = lwrdata()[, lwrfactor()])
a <- lwrA()
b <- lwrB()
ancova <- glm(y ~ x + factor, data = dados)
AOV <- summary(aov(ancova))
AOV <- AOV[[1]]
pvalue <- AOV$`Pr(>F)`[2]
if(pvalue < (1-lwrICalpha())){
mods$lwr_Lm_Ancova_H1 <- TRUE
N <- levels(dados$factor)
DF <- as.data.frame(matrix(NA, nrow = (2*length(N)), ncol = 8))
Linha <- seq(1, (2*length(N))-1, 2)
for(i in 1:length(N)){
subdata <- subset(dados, dados$factor == N[i])
mod <- nls(y ~ a * x^b,
data= subdata,
start = list(a = a,
b = b))
S<-summary(mod)
DF[Linha[i]:(Linha[i]+1), 1] <- N[i]
DF[Linha[i]:(Linha[i]+1), 2] <- c('intercept', "slope")
DF[Linha[i]:(Linha[i]+1), 3:4] <- round(S$coefficients[ ,1:2], 4)
DF[Linha[i]:(Linha[i]+1), 5] <- round(abs(H0 - DF[Linha[i]:(Linha[i]+1), 3]) /
DF[Linha[i]:(Linha[i]+1), 4], 4)
DF[Linha[i]:(Linha[i]+1), 6] <- S$df[2]
DF[Linha[i]:(Linha[i]+1), 7] <- round(pt(DF[Linha[i]:(Linha[i]+1), 5],
DF[Linha[i]:(Linha[i]+1), 6], lower.tail = F), 4)
}
for(j in 1:nrow(DF)){
if(DF[j, 7] < (1 - lwrICalpha())){
if(DF[j, 3] > H0){
DF[j, 8] <- "Positive allometric"
} else
DF[j, 8] <- "Negative allometric"
} else{
DF[j, 8] <- "Isometric"
}
}
colnames(DF)<-c("Group",
"Parameter",
"Estimate",
"Std. Error",
"t value",
'df',
"Pr(>|t|)",
'Status')
mods$lwr_Lm_fits<-DF #[seq(2, length(N)*2,2), ]
} else {
DF <- as.data.frame(matrix(NA, nrow = 2, ncol = 7))
mod <- nls(y ~ a * x^b,
data= dados,
start = list(a = a,
b = b))
S<-summary(mod)
DF[, 1] <- "Polled"
DF[, 2] <- c('intercept', "slope")
DF[, 3:4] <- round(S$coefficients[ ,1:2], 4)
DF[2, 5] <- round(abs(H0 - DF[2, 3]) /
DF[2, 4], 4)
DF[2, 6] <- S$df[2]
DF[2, 7] <- round(pt(DF[2, 5], DF[2, 6], lower.tail = F), 4)
if(DF[2, 7] < (1 - lwrICalpha())){
if(DF[2, 3] > H0){
DF[2, 8] <- "Positive allometric"
} else {
DF[2, 8] <- "Negative allometric"
}
} else{
DF[2, 8] <- "Isometric"
}
colnames(DF)<-c("Group",
"Parameter",
"Estimate",
"Std. Error",
"t value",
'df',
"Pr(>|t|)",
"Status")
mods$lwr_Lm_fits<-DF #[2, ]
}
mods$lwr_Lm_AOV<-AOV
} else {
dados<-data.frame(x = lwrdata()[, lwrx()],
y = lwrdata()[, lwry()])
a <- lwrA()
b <- lwrB()
mod <- nls(y ~ a * x^b,
data= dados,
start = list(a = a,
b = b))
AOV <- summary(mod)
mods$lwr_Lm_AOV<-AOV
DF <- as.data.frame(matrix(NA, nrow = 2, ncol = 8))
S<-summary(mod)
DF[1:2, 1] <- "Polled"
DF[1:2, 2] <- c('intercept', "slope")
DF[1:2, 3:4] <- round(S$coefficients[, 1:2], 4)
DF[2, 5] <- round(abs(H0 - DF[2, 3])/
DF[2, 4],4)
DF[2, 6] <- S$df[2]
DF[2, 7] <- pt(DF[2, 5],
DF[2, 6], lower.tail = F)
if(DF[2, 7] < (1- lwrICalpha())){
if(DF[2, 3] > H0){
DF[2, 8] <- "Positive allometric"
} else
DF[2, 8] <- "Negative allometric"
} else{
DF[2, 8] <- "Isometric"
}
colnames(DF)<-c("Group",
"Parameter",
"Estimate",
"Std. Error",
"t value",
'df',
"Pr(>|t|)",
'Status')
mods$lwr_Lm_fits<-DF
}
return(mods$lwr_Lm_fits)
})
modLWRlm<-reactive({
mods$lwr_Lm_Ancova_H1 <- FALSE
if(!is.na(lwrfactor())){
dados<-data.frame(x = lwrdata()[, lwrx()],
y = lwrdata()[, lwry()],
factor = lwrdata()[, lwrfactor()])
dados<-subset(dados, dados$x > 0 & dados$y > 0)
dados$x<-log(dados$x)
dados$y<-log(dados$y)
a <- lwrA()
b <- lwrB()
fitlm <- lm(y ~ factor + x + factor:x, data = dados)
AOV <- anova(fitlm)
pvalue <- AOV$`Pr(>F)`[1]
if(pvalue < (1-lwrICalpha())){
mods$lwr_Lm_Ancova_H1 <- TRUE
N <- levels(dados$factor)
DF <- as.data.frame(matrix(NA, nrow = (2*length(N)), ncol = 8))
Linha <- seq(1, (2*length(N))-1, 2)
for(i in 1:length(N)){
subdata <- subset(dados, dados$factor == N[i])
mod <- lm(y ~ x, data= subdata)
S<-summary(mod)
DF[Linha[i]:(Linha[i]+1), 1] <- N[i] # adaptar a nova tabela de allometria para sair somente o slope pra factor
DF[Linha[i]:(Linha[i]+1), 2] <- c('intercept', "slope")
DF[Linha[i]:(Linha[i]+1), 3:4] <- round(S$coefficients[,-4],4)
B0 <- 1
DF[(Linha[i]+1), 5] <- round(abs(B0 - DF[(Linha[i]+1), 3]) / DF[(Linha[i]+1), 4],4)
DF[Linha[i]:(Linha[i]+1), 6] <- S$df[2]
DF[(Linha[i]+1), 7] <- round(pt(DF[(Linha[i]+1), 5],
DF[(Linha[i]+1), 6], lower.tail = F), 4)
if(DF[(Linha[i]+1), 7] < (1-lwrICalpha())){
if(DF[(Linha[i]+1), 3] > B0){
DF[(Linha[i]+1), 8] <- "Positive allometric"
} else
DF[(Linha[i]+1), 8] <- "Negative allometric"
} else{
DF[(Linha[i]+1), 8] <- "Isometric"
}
}
colnames(DF)<-c("Group",
"Parameter",
"Estimate",
"Std. Error",
"t value",
'df',
"Pr(>|t|)",
'Body Growth Behavior')
DF <- DF[seq(2, length(N)*2, 2),]
mods$lwr_Lm_fits<-DF
} else {
DF <- as.data.frame(matrix(NA, nrow = 2, ncol = 8))
mod <- lm(y ~ x, data= dados)
S<-summary(mod)
DF[1, 1] <- "Polled"
DF[1, 2] <- "slope"
DF[1, 3:4] <- round(S$coefficients[2, 1:2],4)
B0 <- 1
DF[1, 5] <- round(abs(B0 - DF[1, 3]) / DF[1, 4],4)
DF[1, 6] <- S$df[2]
DF[1, 7] <- round(pt(DF[1, 6], DF[1, 5],lower.tail = F),4)
if(DF[1, 7] < (1-lwrICalpha())){
if(DF[1, 3] > B0){
DF[1, 8] <- "Positive allometric"
} else
DF[1, 8] <- "Negative allometric"
} else{
DF[1, 8] <- "Isometric"
}
colnames(DF)<-c("Group",
"Parameter",
"Estimate",
"Std. Error",
"t value",
'df',
"Pr(>|t|)",
'Body Growth Behavior')
mods$lwr_Lm_fits<-DF
}
rownames(AOV) <- c(colnames(lwrdata())[lwrfactor()],
colnames(lwrdata())[lwrx()],
paste("",colnames(lwrdata())[lwrfactor()],
":",colnames(lwrdata())[lwrx()], sep = ""),
"Residuals")
attributes(AOV)$heading[2]<-paste('Response:', colnames(lwrdata())[lwry()])
mods$lwr_Lm_AOV<-AOV
} else {
dados<-data.frame(x = lwrdata()[, lwrx()],
y = lwrdata()[, lwry()])
dados<-subset(dados, dados$x > 0 & dados$y > 0)
dados$x<-log(dados$x)
dados$y<-log(dados$y)
a <- lwrA()
b <- lwrB()
fitlm <- lm(y ~ x, data = dados)
AOV <- anova(fitlm)
rownames(AOV) <- c(colnames(lwrdata())[lwrx()],
"Residuals")
attributes(AOV)$heading[2]<-paste('Response:', colnames(lwrdata())[lwry()])
mods$lwr_Lm_AOV<-AOV
DF <- as.data.frame(matrix(NA, nrow = 1, ncol = 8))
S<-summary(fitlm)
DF[1, 1] <- "Polled"
DF[1, 2] <- "slope"
DF[1, 3:4] <- round(S$coefficients[2, 1:2],4)
B0 <- 1
DF[1, 5] <- round(abs(B0 - DF[1, 3]) / DF[1, 4],4)
DF[1, 6] <- S$df[2]
DF[1, 7] <- round(pt(DF[1, 6], DF[1, 5],lower.tail = F),4)
if(DF[1, 7] < (1-lwrICalpha())){
if(DF[1, 3] > B0){
DF[1, 8] <- "Positive allometric"
} else
DF[1, 8] <- "Negative allometric"
} else{
DF[1, 8] <- "Isometric"
}
colnames(DF)<-c("Group",
"Parameter",
"Estimate",
"Std. Error",
"t value",
'df',
"Pr(>|t|)",
'Body Growth Behavior')
mods$lwr_Lm_fits<-DF
}
mods$fitLWRlm<-fitlm
return(fitlm)
})
lwrANCOVA <- reactive({
if(input$lwrmodel==1){
bH0 <- "LWR are equals"
bH1 <- "LWR are not equals"
S <- summary(mods$fitnlsANCOVA)
nlsH1<-mods$nlsH1
if(nlsH1){
whoIsDifferent <- rownames(S$coefficients)[2+which(S$coefficients[3:nrow(S$coefficients),4]<lwrICalpha())]
DF <- as.data.frame(t(as.matrix(S$coefficients[2+which(S$coefficients[3:nrow(S$coefficients),4]<lwrICalpha()),])))
Status <- paste("Null hypothesis (H0) rejected. LWR of", whoIsDifferent, " is different", sep = "")
} else{
whoIsDifferent <- rownames(S$coefficients)[2+which(S$coefficients[3:nrow(S$coefficients),4]<lwrICalpha())]
DF <- as.data.frame(t(as.matrix(S$coefficients[2+which(S$coefficients[3:nrow(S$coefficients),4]<lwrICalpha()),])))
Status <- paste("Null hypothesis (H0) accepted. LWR curves are equals", sep = "")
}
DF$bH0<-bH0
DF$bH1<-bH1
DF$Status <- Status
DF<-DF[,c(5,6,1:4,7)]
return(DF)
}
})
{
lwrallometric <- reactive({ # Porque a saida so funciona se essa porra tiver ativa?
if(input$lwrmodel==1){
mod <- modLWRnls2()
S <- summary(mod)
B0<- 3
Bh1<-coef(mod)[2]
epBh1<-S$coefficients[2,2]
t <- abs(B0 - Bh1)/epBh1
p <- pt(t, S$df[2], lower.tail = F)
} else{
mod <- modLWRlm()
S <- summary(mod)
B0<- 1
Bh1<-coef(mod)[2]
epBh1<-S$coefficients[2,2]
t <- abs(B0 - Bh1)/epBh1
p <- pt(t, S$df[2], lower.tail = F)
}
if(p < 0.05){
if(Bh1 > B0){
Status <- "Positive allometric"
} else
Status <- "Negative allometric"
} else{
Status <- "Isometric"
}
# return(data.frame(bH0 = B0, bH1 = Bh1,
# t = t, df = S$df[2],
# 'p-value' = ifelse(p<0.000001, "<2e-16",p),
# status = Status))
return(mods$lwr_Lm_fits)
})
}
output$plotlwr <- renderPlot({
if(!is.na(lwrfactor())){
dados<-data.frame(x = lwrdata()[, lwrx()],
y = lwrdata()[, lwry()],
factor = lwrdata()[, lwrfactor()])
} else {
dados<-data.frame(x = lwrdata()[, lwrx()],
y = lwrdata()[, lwry()])
}
dados<-na.omit(dados)
a <- lwrA()
b <- lwrB()
if(input$lwrmodel==1){
parameters <- mods$lwr_Lm_fits
finalData <- dados[1,]
finalData$fit<-NA
finalData$lwr<-NA
finalData$upr<-NA
if(mods$lwr_Lm_Ancova_H1){
listFactors <- levels(dados$factor)
for(j in 1:length(listFactors)){
subData <- subset(dados, dados$factor == listFactors[j])
mod <- nls(y ~ a * x ^ b,
data= subData,
start = list(a = a,
b = b))
subData <- cbind(subData,
as_tibble(predFit(mod,
newdata = subData,
interval = "confidence",
level= lwrICalpha())))
finalData<-rbind(finalData, subData)
}
dados<-finalData[-1,]
gg <- ggplot(data = dados,
aes(x = x, y = y, color=factor)) +
theme_bw(base_size = 14) +
xlab(input$xlablwr) + ylab(input$ylablwr) +
theme(axis.text = element_text(size=15,
face = "bold", color = "black"),
axis.title = element_text(size=15,
face = "bold", color = "black"),
strip.text = element_text(size=15,
face = "bold", color = "black")) +
geom_point(shape = lwrpch(),
alpha = lwrptalpha(),
size = lwrptsize())+
geom_line(aes(x= x, y = fit, color=factor), size=1.25)
if(input$lwrIC) {
gg <- gg + geom_ribbon(aes(x = x,
ymin = lwr,
ymax = upr,
fill = factor),
alpha=0.2,
linetype = 0)
}
} else {
mod <- nls(y ~ a * x ^ b,
data= dados,
start = list(a = a,
b = b))
dados <- cbind(dados,
as_tibble(predFit(mod,
newdata = dados,
interval = "confidence",
level= lwrICalpha())))
gg <- ggplot(data = dados,
aes(x = x, y = y)) +
theme_bw(base_size = 14) +
xlab(input$xlablwr) + ylab(input$ylablwr) +
theme(axis.text = element_text(size=15,
face = "bold", color = "black"),
axis.title = element_text(size=15,
face = "bold", color = "black"),
strip.text = element_text(size=15,
face = "bold", color = "black")) +
geom_point(shape = lwrpch(),
alpha = lwrptalpha(),
size = lwrptsize())+
geom_line(aes(x= x, y = fit))
if(input$lwrIC) {
gg <- gg + geom_ribbon(aes(x = x, ymin = lwr, ymax = upr),
alpha=0.2)
}
}
}
else{
dados<-subset(dados, dados$x > 0 & dados$y > 0)
dados$x<-log(dados$x)
dados$y<-log(dados$y)
gg <- ggplot(data = dados,
aes(x = x, y = y)) +
theme_bw(base_size = 14) +
xlab(input$xlablwr) + ylab(input$ylablwr) +
theme(axis.text = element_text(size=15,
face = "bold", color = "black"),
axis.title = element_text(size=15,
face = "bold", color = "black"),
strip.text = element_text(size=15,
face = "bold", color = "black")) +
geom_point(shape = lwrpch(),
alpha = lwrptalpha(),
size = lwrptsize())
if(mods$lwr_Lm_Ancova_H1){
gg <- gg +
geom_point(data = dados,
aes(x = x, y = y, color = factor),
shape = lwrpch(),
alpha = lwrptalpha(),
size = lwrptsize())+
geom_smooth(data = dados,
aes(x = x, y = y, color=factor),
method = "lm", se = input$lwrIC,
level = lwrICalpha())+
labs(color = colnames(lwrdata())[lwrfactor()])
} else {
gg <- gg +
geom_point(data = dados,
aes(x = x, y = y),
shape = lwrpch(),
alpha = lwrptalpha(),
size = lwrptsize()) +
geom_smooth(data = dados,
aes(x = x, y = y), color = "black",
method = "lm", se = input$lwrIC,
level = lwrICalpha())
}
}
graphs$basiclwr <- gg
print(gg)
})
output$downLWRstat <- downloadHandler(
filename = "LWR stats.txt",
content = function(file) {
if(input$lwrmodel==1){
sink(file)
print(modLWRnls2())
print(lwrallometric())
sink()
} else {
sink(file)
print(summary(modLWRlm()))
print(lwrallometric())
sink()
}
})
output$plotlwrstat <- renderPrint({
print(mods$lwr_Lm_AOV)
cat("\n\n")
print(summary(mods$fitLWRlm))
cat("\n\n")
cat("Body Growth Behavior \n")
print(lwrallometric(), row.names = FALSE)
})
output$downLWRplot <- downloadHandler(
filename = function(){
paste("LWR", input$downloadfilelwr, sep = ".")
},
content = function(file){
if(input$downloadfilelwr=="tiff")
tiff(file, width = widthlwr(), height = heightlwr(), res= reslwr())
else
jpeg(file, width = widthlwr(), height = heightlwr(), res= reslwr())
print(graphs$basiclwr)
dev.off()
}
)
########################################
########################################
########################################
# Age Input
agedata <- reactive({
file1 <- input$agefile
if(is.null(file1)) {return()}
read.table(file = file1$datapath,
sep = input$agesep,
header = input$ageheader,
stringsAsFactors = input$agestringAsFactors)
})
# Age - Variables and Graphical parameters
observe(
{
Vx<-1:length(colnames(agedata()))
atr_list<-list(names = colnames(agedata()))
attributes(Vx)<-atr_list
Fac<-!sapply(agedata(), is.factor)
Vx<-Vx[Fac]
updateSelectInput(session, "agex", "1. Select x-variable",
choices = Vx)
})
observe(
{
Vy<-1:length(colnames(agedata()))
atr_list<-list(names = colnames(agedata()))
attributes(Vy)<-atr_list
Fac<-!sapply(agedata(), is.factor)
Vy<-Vy[Fac]
updateSelectInput(session, "agey", "2. Select y-variable",
choices = Vy)
})
x <- reactive({
as.numeric(input$agex)
})
y <- reactive({
as.numeric(input$agey)
})
output$plot <- renderPlot({
dados<-data.frame(x = agedata()[, x()],
y = agedata()[, y()])
dados<-na.omit(dados)
gg <- ggplot() +
geom_point(data = dados, aes(x = x, y = y),
colour = agecolpt(), shape = agepch())+
theme_bw(base_size = 14) +
xlab(input$xlab) + ylab(input$ylab) +
theme(axis.text=element_text(size=15, face = "bold", color = "black"),
axis.title=element_text(size=15, face = "bold", color = "black"),
strip.text = element_text(size=15, face = "bold", color = "black"))
graphs$basic<-gg
print(gg)
})
agepch<-reactive({
as.numeric(input$agepch)
})
agecolpt<-reactive({
as.numeric(input$agecolpt)
})
# Growth models
plotInput <- reactive({
dados<-na.omit(agedata())
x<-dados[, x()]
y<-dados[, y()]
x<-seq(min(x, na.rm = T), max(x, na.rm = T), 0.1)
dataY<-data.frame(x = x,
VBGF = NA,
Gomp = NA,
Log = NA)
base<-graphs$basic
if(input$modelsvbgf == T){
dataY$VBGF <- Linfvbgf() * (1 - exp(-K() * (x - t0())))
base <- base+
geom_line(data = dataY, aes(x = x, y = VBGF),
color="black", size=1.25)
}
#gomp
if(input$modelsgomp == T){
dataY$Gomp <- Linfgom() * exp( - exp(-gi() * (x - ti())))
base <- base+
geom_line(data = dataY, aes(x = x, y = Gomp),
color="red", size=1.25)
}
#log
if(input$modelslog == T){
dataY$Log <- Linflog()/(1 + exp(-ginf() * (x - tilog())))
base <- base+
geom_line(data = dataY, aes(x = x, y = Log),
color="blue", size=1.25)
}
graphs$inputs<-base
})
output$plot2 <- renderPlot({
plotInput()
base<-graphs$inputs
print(base)
})
output$plot3 <- renderPlot({
plotInput()
base<-graphs$inputs
print(base)
})
output$plot4 <- renderPlot({
plotInput()
base<-graphs$inputs
print(base)
})
output$plot5 <- renderPlot({
plotInput()
base<-graphs$inputs
print(base)
})
observeEvent(input$modelsvbgf, {
if(input$modelsvbgf == F){
shinyjs::disable("vbgfL")
shinyjs::disable("vbgfK")
shinyjs::disable("vbgft0")
} else {
shinyjs::enable("vbgfL")
shinyjs::enable("vbgfK")
shinyjs::enable("vbgft0")
}
})
observeEvent(input$modelsgomp, {
if(input$modelsgomp == F){
shinyjs::disable("gompL")
shinyjs::disable("gompgi")
shinyjs::disable("gompti")
} else {
shinyjs::enable("gompL")
shinyjs::enable("gompgi")
shinyjs::enable("gompti")
}
})
observeEvent(input$modelslog, {
if(input$modelslog == F){
shinyjs::disable("logL")
shinyjs::disable("logginf")
shinyjs::disable("logti")
} else {
shinyjs::enable("logL")
shinyjs::enable("logginf")
shinyjs::enable("logti")
}
})
observeEvent(input$boot, {
if(input$boot == F){
shinyjs::disable("nboot")
} else {
shinyjs::enable("nboot")
}
})
# VBGF seed values
Linfvbgf<-reactive({
as.numeric(input$vbgfL)
})
K<-reactive({
as.numeric(input$vbgfK)
})
t0<-reactive({
as.numeric(input$vbgft0)
})
# Gompertz seed values
Linfgom<-reactive({
as.numeric(input$gompL)
})
gi<-reactive({
as.numeric(input$gompgi)
})
ti<-reactive({
as.numeric(input$gompti)
})
# Log seed values
Linflog<-reactive({
as.numeric(input$logL)
})
ginf<-reactive({
as.numeric(input$logginf)
})
tilog<-reactive({
as.numeric(input$logti)
})
observe({
if(input$modelsvbgf == F){return()}
else{
dados<-na.omit(agedata())
dados<-data.frame(age = dados[, x()],
Y = dados[, y()])
Seeds<-vbStarts(Y~age, data = dados, type = "typical")
updateSliderInput(session, "vbgfL",
value = Seeds$Linf,
min = round(Seeds$Linf/5),
max = round(Seeds$Linf*5),
step = 1)
}
})
observe({
if(input$modelsvbgf == F){return()}
else{
dados<-na.omit(agedata())
dados<-data.frame(age = dados[, x()],
Y = dados[, y()])
Seeds<-vbStarts(Y ~ age, data = dados,
type = "typical")
updateSliderInput(session, "vbgfK",
value = Seeds$K,
min = 0.001,
max = round(Seeds$K*5,2),
step = 0.001)
}
})
observe({
if(input$modelsvbgf == F){return()}
else{
dados<-na.omit(agedata())
dados<-data.frame(age = dados[, x()],
Y = dados[, y()])
Seeds<-vbStarts(Y ~ age, data = dados, type = "typical")
updateSliderInput(session, "vbgft0",
value = Seeds$t0,
min = -abs(round(Seeds$t0*5,2)),
max = abs(round(Seeds$t0*5,2)),
step = 0.001)
}
})
observe({
if(input$modelsgomp == F){return()}
else{
dados <- na.omit(agedata())
dados<-data.frame(age = dados[, x()],
Y = dados[, y()])
Seeds<-vbStarts(Y ~ age, data = dados, type = "typical")
updateSliderInput(session, "gompL",
value = Seeds$Linf,
min = round(Seeds$Linf/5),
max = round(Seeds$Linf*5),
step = 1)
}