Nothing
# Code for the plot
output$ecdf <- renderPlot({ # curly braces are for code blocks
# functions
func <- ecdf(df$values)
mirroredFunc <- function(x, a) {
func(-x + 2*a)
}
mdFunc <- function(x, a) {
func(x+a) - mirroredFunc(x+a, a)
}
if (correctMean()) {
meanGuess <- mean
} else {
meanGuess <- input$meanSlider
}
if (!correctRMSD()) {
fullRMSD(input$rmsdSlider)
}
if (!correctSMSD()) {
fullSMSD(input$smsdSlider)
}
if (!correctMD()) {
fullMD(input$mdSlider)
}
# max <- max(c(meanGuess + (meanGuess - absmin + 0.001), absmax)) # x value of meanGuess + maxDeviation
max <- max(c(meanGuess + (meanGuess - absmin), absmax)) # x value of meanGuess + maxDeviation
# maxDev <- max - meanGuess + 0.001 # the maximum deviation
maxDev <- max - meanGuess # the maximum deviation
p <- ggplot(df, aes(values)) +
geom_hline(
yintercept = 0,
color = 'black'
) +
geom_hline(
yintercept = 1,
color = 'black'
) +
scale_x_continuous(
n.breaks = 20
) +
scale_y_continuous(
n.break = 10
)
if (mode() == "Mean") {
source("server_src/plots/mean.R", local = TRUE)
} else if (mode() == "MD") {
source("server_src/plots/md.R", local = TRUE)
} else if (mode() == "SMSD") {
source("server_src/plots/smsd.R", local = TRUE)
} else if (mode() == "RMSD") {
source("server_src/plots/rmsd.R", local = TRUE)
} else if (mode() == "SD") {
source("server_src/plots/sd.R", local = TRUE)
}
p
})
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