Nothing
#Server functions for module 4 step 1
c(
######### Set variables #########
# Set hidden variables
output$Mod4Step1_hidden <- renderUI({
list(
numericInput("Mod4Step1_Tmax", "", Modules_VAR$Tmax$max),
numericInput("Mod4Step1_NI", "", 10),
numericInput("Mod4Step1_NT", "", 2),
numericInput("Mod4Step1_NR", "", 10),
shinyMatrix::matrixInput("Mod4Step1_Ve", value = matrix(c(input$Mod4Step1_Ve1, input$Mod4Step1_Corr_e,
input$Mod4Step1_Corr_e, input$Mod4Step1_Ve2), 2), class = "numeric")
)
}),
outputOptions(output, "Mod4Step1_hidden", suspendWhenHidden = FALSE),
######### Run simulation #########
# Run simulation and return results
Mod4Step1_output <- reactive({
if (input$Mod4Step1_Run == 0) # if Run button is pressed
return(NULL)
isolate({
updateCheckboxInput(session, "isRunning", value = TRUE)
# Call app main function
data <- squid::squidR(input, module = "Mod4Step1")
dt <- as.data.table(data$sampled_data)
dt <- dt[ , .(Time, Individual, Trait, Phenotype)]
dt[ , Trait := paste0("Phenotype_", Trait)]
dt <- dcast(dt, Time + Individual ~ Trait, value.var = "Phenotype")
updateCheckboxInput(session, "isRunning", value = FALSE)
return(dt)
})
}),
output$Mod4Step1_correlationplot <- renderPlot({
data <- Mod4Step1_output()
if (!is.null(data)) {
dt <- copy(data)
ggplot2::ggplot(dt, ggplot2::aes(x = Phenotype_1, Phenotype_2, fill = as.factor(Individual), colour = as.factor(Individual))) +
ggplot2::geom_point() +
ggplot2::xlab("Phenotype of trait y") +
ggplot2::ylab("Phenotype of trait z") +
ggplotCustomTheme()
}else{
defaultPlot()
}
}),
# Display results (Matrix)
output$Mod4Step1_Covariance_Matrix <- renderUI({
cov <- round(input$Mod4Step1_Corr_e * sqrt(input$Mod4Step1_Ve1 * input$Mod4Step1_Ve2),3)
myMatrix <- paste0(
"$$ \\Omega_{",NOT$error,"}=
\\begin{pmatrix}
",input$Mod4Step1_Ve1," & ",cov," \\\\
",cov," & ",input$Mod4Step1_Ve2," \\\\
\\end{pmatrix}
$$")
return(withMathJax(myMatrix))
})
) # End return
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