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server.r
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library(shiny)
library(shinyLP)
library(shinyBS)
library(shinyjqui)
library(dplyr)
library(tools)
library(tidyverse)
library(lmtest)
library(lm.beta)
library(ggplot2)
library(RColorBrewer)
library(car)
library(data.table)
options(shiny.reactlog = TRUE)
options(shiny.usecairo=FALSE)
colMax <- function(data) sapply(data, max, na.rm = TRUE)
bx.stat <- function(inp){return(boxplot.stats(inp)$stats[c(1,5)])}
cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
fl_cl <- function(inp){return(c(floor(inp[1]),ceiling(inp[2])))}
splitVec <- function(vec){nvec <- c()
temp <- c()
while (length(vec) > 2) {
while (length(temp) < 3){
}
}
}
normRes <- function(vals){
m <- mean(vals)
res <- vals-m
shapiro.test(res)$p.value > 0.05
}
getColNames <- function(ct){
colLabs <- unlist(lapply(1:ncol(ct), function (i){
paste(
paste(rownames(ct)[ct[,i]>0], collapse=", "),
"vs.",
paste(rownames(ct)[ct[,i]<0], collapse=", ")
)
}))
return(colLabs)
}
doughnut <-
function (x0, edges = 200, labels=NULL, outer.radius = 1,
inner.radius=0.75, clockwise = FALSE,
init.angle = ifelse (clockwise, 90, 0), density = NULL,
angle = 45, col = NULL, border = FALSE, lty = NULL,
main = NULL, inside=NULL, ...){
if (!is.factor(x0)){stop("'x' values must be factors.")}
if (is.null(labels)){labels <- as.character(levels(x0))}
nas <- sum(is.na(x0))
x <- as.vector(table(x0[!is.na(x0)]))
col = colorRampPalette(brewer.pal(9,"Spectral"))(length(labels))
x <- c(0, cumsum(x)/sum(x))
dx <- diff(x)
nx <- length(dx)
par(mar=c(2,2,2,2))
plot.new()
pin <- par("pin")
xlim <- ylim <- c(-1, 1)
if (pin[1L] > pin[2L])
{xlim <- (pin[1L]/pin[2L]) * xlim}
else {ylim <- (pin[2L]/pin[1L]) * ylim}
plot.window(xlim, ylim, "", asp = 1)
twopi <- if (clockwise)
-2 * pi
else 2 * pi
t2xy <- function(t, radius) {
t2p <- twopi * t + init.angle * pi/180
list(x = radius * cos(t2p),
y = radius * sin(t2p))
}
for (i in 1L:nx) {
n <- max(2, floor(edges * dx[i]))
P <- t2xy(seq.int(x[i], x[i + 1], length.out = n),
outer.radius)
polygon(c(P$x, 0), c(P$y, 0), density = density[i],
angle = angle[i], border = border[i],
col = col[i], lty = lty[i])
Pout <- t2xy(mean(x[i + 0:1]), outer.radius)
lab <- as.character(labels[i])
if (!is.na(lab) && nzchar(lab)) {
text(1.3 * Pout$x, 1.3 * Pout$y, labels[i], family="serif",
xpd = TRUE, adj = ifelse(Pout$x < 0, 1, 0),
...)
}
## Add white disc
Pin <- t2xy(seq.int(0, 1, length.out = n*nx),
inner.radius)
polygon(Pin$x, Pin$y, density = density[i],
angle = angle[i], border = border[i],
col = "white", lty = lty[i])
if (nas > 0)
text(0,0,paste(nas, ifelse(nas>1,"\nNAs", "\nNA")), family="serif", cex=1.25)
}
title(main = main, ...)
invisible(NULL)
}
effPlot <-
function (eff, type, boundary=2, edges = 100, labels=NULL, outer.radius = 1,
inner.radius=0.75,
init.angle = 0, density = NULL,
angle = 45, col = NULL, border = FALSE, lty = NULL,
main = NULL, inside=NULL, ...){
if (!all(is.numeric(c(eff, boundary)))){stop("'x' values must be factors.")}
if (is.null(labels)){labels <- c("", "")}
effb <- eff
eff <- min(abs(eff), 2)
x <- abs(c(0, (boundary-eff)/boundary, 1))
rat <- abs(0.5*eff/boundary)
efcol <- hsv(max(0.5-rat, 0),1,1)
col <- c("grey90", efcol)
dx <- diff(x)
nx <- length(dx)
par(mar=c(0,2,1,2))
plot.new()
pin <- par("pin")
xlim <- c(-1, 1)
ylim <- c(0,1)
if (pin[1L] > pin[2L])
{xlim <- (pin[1L]/pin[2L]) * xlim
} else {ylim <- (pin[2L]/pin[1L]) * ylim}
plot.window(xlim, ylim, "", asp = 1)
t2xy <- function(t, radius) {
t2p <- pi * t + init.angle * pi/180
list(x = radius * cos(t2p),
y = radius * sin(t2p))
}
for (i in 1L:nx) {
n <- max(50, floor(edges * dx[i]))
P <- t2xy(seq.int(x[i], x[i + 1], length.out = n),
outer.radius)
polygon(c(P$x, 0), c(P$y, 0), density = density[i],
angle = angle[i], border = border[i],
col = col[i], lty = lty[i])
Pout <- t2xy(mean(x[i + 0:1]), outer.radius)
lab <- as.character(labels[i])
if (!is.na(lab) && nzchar(lab)) {
text(1.1 * Pout$x, 1.1 * Pout$y, labels[i], family="serif",
xpd = TRUE, adj = ifelse(Pout$x < 0, 1, 0))
}
}
## Add white disc
Pin <- t2xy(seq.int(0, 1, length.out = n*nx),
inner.radius)
polygon(Pin$x, Pin$y, density = density[i],
angle = angle[i], border = border[i],
col = "white", lty = lty[i])
text(0,0.2,paste(type, ": ", abs(round(effb, 2)), sep=""), family="serif", cex=1.25)
text(-1,-0.2, "Weak", family="serif", cex=1.25)
text(1,-0.2,"Strong", family="serif", cex=1.25)
title(main = main, ...)
invisible(NULL)
}
corPlot <-
function (eff, type="spearman", boundary=1, edges = 100, labels=NULL, outer.radius = 1,
inner.radius=0.75,
init.angle = 0, density = NULL,
angle = 45, col = NULL, border = FALSE, lty = NULL,
main = NULL, inside=NULL, ...){
if (type == "spearman") {type <- "Spearman's rho"} else {type <- "Pearson's r"}
if (!all(is.numeric(c(eff, boundary)))){stop("'x' values must be factors.")}
if (is.null(labels)){labels <- c("", "")}
effb <- eff
#eff <- min(abs(eff), 2)
x <- c(-1, max(eff-0.02,-1), min(eff+0.02,1), 1)
x <- (x/-2)+0.5
rat <- abs(0.4*eff)
efcol <- hsv(max(rat, 0),1,1)
col <- c("grey90", efcol, "grey90")
dx <- diff(x)
print(dx)
nx <- length(dx)
par(mar=c(0,2,1,2))
plot.new()
pin <- par("pin")
xlim <- c(-1, 1)
ylim <- c(0,1)
if (pin[1L] > pin[2L])
{xlim <- (pin[1L]/pin[2L]) * xlim
} else {ylim <- (pin[2L]/pin[1L]) * ylim}
plot.window(xlim, ylim, "", asp = 1)
t2xy <- function(t, radius) {
t2p <- pi * t + init.angle * pi/180
list(x = radius * cos(t2p),
y = radius * sin(t2p))
}
for (i in 1L:nx) {
n <- max(50, floor(edges * dx[i]))
P <- t2xy(seq.int(x[i], x[i + 1], length.out = n),
outer.radius)
polygon(c(P$x, 0), c(P$y, 0), density = density[i],
angle = angle[i], border = border[i],
col = col[i], lty = lty[i])
Pout <- t2xy(mean(x[i + 0:1]), outer.radius)
lab <- as.character(labels[i])
if (!is.na(lab) && nzchar(lab)) {
text(1.1 * Pout$x, 1.1 * Pout$y, labels[i], family="serif",
xpd = TRUE, adj = ifelse(Pout$x < 0, 1, 0))
}
}
## Add white disc
Pin <- t2xy(seq.int(0, 1, length.out = n*nx),
inner.radius)
polygon(Pin$x, Pin$y, density = density[i],
angle = angle[i], border = border[i],
col = "white", lty = lty[i])
text(0,0.2,paste(type, ": ", abs(round(effb, 2)), sep=""), family="serif", cex=1.25)
text(-1,-0.2, "Strong negative", family="serif", cex=1.25)
text(1,-0.2,"Strong positive", family="serif", cex=1.25)
title(main = main, ...)
invisible(NULL)
}
bend <-
function (nas, tot, edges = 100, labels=NULL, outer.radius = 1,
inner.radius=0.75,
init.angle = 0, density = NULL,
angle = 45, col = NULL, border = FALSE, lty = NULL,
main = NULL, inside=NULL, ...){
if (!all(is.numeric(c(nas, tot)))){stop("'x' values must be factors.")}
if (is.null(labels)){labels <- c("", "")}
col <- c("grey90", "red")
x <- c(0, (tot-nas)/tot, 1)
dx <- diff(x)
nx <- length(dx)
par(mar=c(0,2,1,2))
plot.new()
pin <- par("pin")
xlim <- c(-1, 1)
ylim <- c(0,1)
if (pin[1L] > pin[2L])
{xlim <- (pin[1L]/pin[2L]) * xlim
} else {ylim <- (pin[2L]/pin[1L]) * ylim}
plot.window(xlim, ylim, "", asp = 1)
t2xy <- function(t, radius) {
t2p <- pi * t + init.angle * pi/180
list(x = radius * cos(t2p),
y = radius * sin(t2p))
}
for (i in 1L:nx) {
n <- max(50, floor(edges * dx[i]))
P <- t2xy(seq.int(x[i], x[i + 1], length.out = n),
outer.radius)
polygon(c(P$x, 0), c(P$y, 0), density = density[i],
angle = angle[i], border = border[i],
col = col[i], lty = lty[i])
Pout <- t2xy(mean(x[i + 0:1]), outer.radius)
lab <- as.character(labels[i])
if (!is.na(lab) && nzchar(lab)) {
text(1.1 * Pout$x, 1.1 * Pout$y, labels[i], family="serif",
xpd = TRUE, adj = ifelse(Pout$x < 0, 1, 0))
}
}
## Add white disc
Pin <- t2xy(seq.int(0, 1, length.out = n*nx),
inner.radius)
polygon(Pin$x, Pin$y, density = density[i],
angle = angle[i], border = border[i],
col = "white", lty = lty[i])
text(0,0.2,paste(round((1-x[2])*100, 1), "% missing", sep=""), family="serif", cex=1.25)
title(main = main, ...)
invisible(NULL)
}
getna <- function(cc) {
cc[ sample(c(TRUE, NA), prob = c(0.95, 0.05), size = length(cc), replace = TRUE) ]
}
getEffLab <- function(eff) {
eff <- abs(eff)
if (eff <0.8){
if (eff < 0.2) {return("very small")}
else if (eff < 0.5) {return("small")}
else {return("medium")}
}
else {
if (eff < 1.2) {return("large")}
else if (eff < 2) {return("very large")}
else {return("huge")}
}
}
getCorLab <- function(eff, rel = T) {
eff <- abs(eff)
if (rel == T){if (eff <0.5){
if (eff < 0.1) {return("very weak")}
else if (eff < 0.3) {return("weak")}
else {return("medium")}
}
else {
return("strong")
}
}
else {
if (eff <0.5){
if (eff < 0.1) {return("at all")}
else if (eff < 0.3) {return("to a limited degree")}
else {return("reasonably well")}
}
else {
return("well")
}
}
}
randdata <- function(){
seed0 <- round(rnorm(100, 100, 25))
rd <- data.frame(
gender=c(sample(c(rep("female",10),rep("male",8)), 50, replace=T),
sample(c(rep("female",8),rep("male",10)), 50, replace=T)),
age=c(round(runif(50,min=10,max=30),0), round(runif(50,min=20,max=45),0)),
education=c(sample(c(rep("3_university",7),rep("2_high",5),rep("1_elementary",2),rep("4_doctorate",10)),50,replace=T),
sample(c(rep("3_university",5),rep("2_high",7),rep("1_elementary",10),rep("4_doctorate",2)),50,replace=T)),
residence=c(sample(c(rep("East",7),rep("Mid",5),rep("West",1)),50,replace=T),
sample(c(rep("East",2),rep("Mid",7),rep("West",10)),50,replace=T)),
birthplace=c(sample(c(rep("East",5),rep("Mid",4),rep("West",1)),50,replace=T),
sample(c(rep("East",3),rep("Mid",8),rep("West",15)),50,replace=T)),
rhoticity=c(abs(round(rnorm(50,0.2, 0.1),2)),abs(round(rnorm(50,0.5, 0.1),2))),
glottalisation=c(sample(c(rep("2_preconsonantal",7), rep("3_preconsonantal+initial",1), rep("1_none",10)),50,replace=T),
sample(c(rep("2_preconsonantal",7), rep("3_preconsonantal+initial",3), rep("1_none",1)),50,replace=T)),
before_class=seed0,
mid_class=seed0+rnorm(100,10,26),
after_class=seed0+rnorm(100,20,25)
)
# rd <- as.data.frame(lapply(rd, getna))
return(rd)
}
getExp <- function (cdata) {
expDat <- data.frame()
for (i in 1:length(rowSums(cdata))){
for (j in 1:length(colSums(cdata))) {
expDat[i,j] <- (sum(cdata[i,]) * sum(cdata[,j])) / sum(cdata)
expDat[i,j] <- (sum(cdata[i,]) * sum(cdata[,j])) / sum(cdata)
}
}
colnames(expDat) <- colnames(cdata)
return(expDat)
}
renderCatPlots <- function(cats, dats, input, output) {
for (i in cats) {
local({
ii <- i
# need i evaluated here
output[[sprintf('%s_%s', "plot", ii)]] <- renderPlot({
doughnut(dats[[ii]])
})
})
}
}
renderNumPlots <- function(nums, dats, input, output) {
for (i in nums) {
local({
ii <- i
nas <- sum(is.na(dats[[ii]]))
# need i evaluated here
output[[sprintf('%s_%s', "plot", ii)]] <- renderPlot({
ggplot(dats[!is.na(dats[[ii]]),], aes_string(ii))+
geom_histogram(aes(fill=..count..), bins=10) +
theme_minimal() + xlab("") + ylab("") +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position="none") +
scale_y_continuous(labels=c()) +
scale_fill_distiller(palette="Oranges")+
annotate("text", Inf, Inf, label = ifelse(nas>0, paste(nas, ifelse(nas>1,"NAs", "NA")), ""), hjust = 1, vjust = 1, size=6, family="serif")
})
})
}
}
getSummary <- function(dt.i){
smr <- lapply(levels(dt.i[,2]), function(i){
m <- mean(dt.i[dt.i[,2]==i,1], na.rm=T)
s <- sd(dt.i[dt.i[,2]==i,1], na.rm=T)/sqrt(length(dt.i[dt.i[,2]==i,1]))
return(c(i, m,s))
})
smr <- do.call("rbind",smr)
colnames(smr) <- c("l", "m", "s")
smr <- as.data.frame(smr)
smr$m <- as.numeric(as.character(smr$m))
smr$s <- as.numeric(as.character(smr$s))
return(smr)
}
shinyServer(function(input, output, session) {
cookedData <- reactiveValues(cats=NULL, nums=NULL, cooked=NULL)
plotType <- reactiveValues(current=NULL)
importSettings <- reactiveValues(header=TRUE, sep="\t", quoter='"', dec=".")
testSet <- reactiveValues(settings=NULL, vals=NULL, manConts=NULL)
settings <- reactiveValues(na.ignore="ignore", mod="real", cols="b&w", serif="serif")
summaryVals <- reactiveValues(freqs=NULL)
anovaGroups <- reactiveValues(level=NULL, finished=FALSE, results=NULL)
observeEvent(input$upFile, {
settings$mod <- "real"
showModal(
modalDialog(size="s",
fileInput(inputId='file1', label='Choose a CSV file',
accept=c('text/csv',
'text/comma-separated-values',
'text/plain',
'text/tab-separated-values',
'csv',
'tsv')),
hr(),
p(a("Download sample data", href="https://onedrive.live.com/download?cid=8BF09AD1C8343122&resid=8BF09AD1C8343122%21258985&authkey=ACWhDNRScGBzKwk"), style='text-align:center'),
easyClose = TRUE
)
)
})
observeEvent(input$saveSettings, {
settings$na.ignore <- input$naSetting
settings$cols <- input$plotCol
settings$serif <- input$serif
})
observeEvent(input$startDemo, {
settings$mod <- "demo"
session$sendCustomMessage('activeNavs', 'Check')
updateNavbarPage(session, 'mainnavbar', selected = 'Check')
})
observeEvent(input$file1, {
if (is.null(rawData())){
showModal(modalDialog(
size="s",
title="Invalid file",
h4("This file is not supported", style="color: #ff0000; font-face: bold"),
fileInput(inputId='file1', label='Choose a CSV file',
accept=c('text/csv',
'text/comma-separated-values',
'text/plain',
'text/tab-separated-values',
'csv'
)
),
hr(),
p(a("Download sample data", href="https://onedrive.live.com/download?cid=8BF09AD1C8343122&resid=8BF09AD1C8343122%21258985&authkey=ACWhDNRScGBzKwk"), style='text-align:center'),
easyClose = TRUE,
fade=FALSE))
}
else {removeModal()}
})
rawData <- reactive({
if (settings$mod == "demo"){randdata()}
else {
inFile <- input$file1
if (is.null(inFile))
return(NULL)
if (file_ext(inFile$name) %in% c(
'text/csv',
'text/comma-separated-values',
'text/tab-separated-values',
'text/plain',
'csv',
'tsv')) {read.csv(inFile$datapath, header=importSettings$header, sep=importSettings$sep, quote=importSettings$quoter, dec=importSettings$dec)}
else {return(NULL)}}
})
cookData <- function() {
req(rawData())
cookedData$cooked <- rawData()
for (label in colnames(rawData())) {
if (label %in% cookedData$cats) {
if (!is.factor(cookedData$cooked[[label]])){cookedData$cooked[[label]] <- as.factor(cookedData$cooked[[label]])}
}
if (label %in% cookedData$nums) {
if (is.factor(cookedData$cooked[[label]])){cookedData$cooked[[label]] <- as.numeric(cookedData$cooked[[label]])}
}
}
# colnames(cookedData$cooked) <- gsub("_", " ", colnames(cookedData$cooked))
# names(cookedData$cats) <- gsub("_", " ", names(cookedData$cats))
# names(cookedData$nums) <- gsub("_", " ", names(cookedData$nums))
}
# Observer waiting for the upload of a file --> once its done the page Data check is activated and selected
observe({
if (is.null(rawData()) == FALSE) {
session$sendCustomMessage('activeNavs', 'Check')
updateNavbarPage(session, 'mainnavbar', selected = 'Check')
}
})
observeEvent(input$bigFriendlyButton, {
session$sendCustomMessage('activeNavs', 'Summarize')
session$sendCustomMessage('activeNavs', 'Explore')
session$sendCustomMessage('activeNavs', 'Analyze')
cookedData$cats <- if(!is.null(input$cats_order)){input$cats_order} else {TRUE}
cookedData$nums <- if(!is.null(input$nums_order)){input$nums_order} else {TRUE}
cookData()
req(cookedData$cooked)
renderCatPlots(cookedData$cats, cookedData$cooked, input, output)
renderNumPlots(cookedData$nums, cookedData$cooked, input, output)
updateNavbarPage(session, 'mainnavbar', selected = 'Summarize')
})
plotinput <- eventReactive(input$doPlot, {
if (length(input$outcome_order)!=1|length(input$pred_order)>2) {
showModal(
modalDialog(
title="ERROR",
"You need one outcome and 0-2 predictors",
footer=NULL,
easyClose=TRUE
)
)
}
list(outcome=input$outcome_order, pred=input$pred_order)
})
observeEvent(input$bigUnfriendlyButton, {
showModal(
modalDialog(
title="Tell us more about your data",
tagList(
#FOR SOME REASON, THIS DOES NOT WORK WITH T/F AND NEEDS THIS KIND OF WORKAROUND
selectInput(inputId='header', label='Header',
c("Header row in the data"="h",
"No header in the data"="nh"),
ifelse(importSettings$header, "h", "nh")),
selectInput(inputId='sep', label='Separator',
c(Comma=',',
Semicolon=';',
Tab='\t'),
importSettings$sep),
selectInput(inputId='dec', label='Decimal sign',
c("Point"='.',
'Comma'=','),
importSettings$dec),
selectInput(inputId='quoter', label='Quote sign',
c(None='',
'Double Quote'='"',
'Single Quote'="'"),
importSettings$quoter)
),
footer= actionButton("ok", "OK")
)
)
})
observeEvent(input$ok, {
importSettings$header <- ifelse(input$header=="h", T, F)
importSettings$quoter <- input$quoter
importSettings$sep <- input$sep
importSettings$dec <- input$dec
removeModal()
})
observeEvent(input$compSel, {
showModal(
modalDialog(
wellPanel(
h4("Columns"),
p("Take several columns from your data and compare them to each other"),
actionButton("colComp", "Proceed", class="btn btn-secondary")
),
wellPanel(
h4("Groups"),
p("Take one column from your data and compare several groups in it"),
actionButton("grComp", "Proceed", class="btn btn-secondary")
)
)
)
})
observeEvent(input$colComp, {
updateNavbarPage(session, 'mainnavbar', selected = 'Columns ')
testSet$settings <- "colComp"
req(cookedData$cooked, cookedData$cats, cookedData$nums)
anovaGroups$finished <- FALSE
showModal(
modalDialog(
title="Select columns",
orderInput('sels', 'Columns to compare', items=c(),
as_source = FALSE, connect = c('ns', 'cs'), width="100%", item_class="success", placeholder="Select two or more columns to compare"),
orderInput('ns', 'Numbers', items = cookedData$nums,
as_source = FALSE, connect = c('cs', 'sels'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cookedData$cats,
as_source = FALSE, connect = c('ns', 'sels'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_cols", "OK"), fade = FALSE
)
)
})
observeEvent(input$colCChange, {
updateNavbarPage(session, 'mainnavbar', selected = 'Columns ')
testSet$settings <- "colComp"
req(cookedData$cooked, cookedData$cats, cookedData$nums)
labs <- colnames(testSet$vals)
labs <- labs[labs %in% c(cookedData$cats, cookedData$nums)]
cats <- cookedData$cats[!(cookedData$cats %in% labs)]
nums <- cookedData$nums[!(cookedData$nums %in% labs)]
showModal(
modalDialog(
title="Select columns",
orderInput('sels', 'Columns to compare', items=labs,
as_source = FALSE, connect = c('ns', 'cs'), width="100%", item_class="success", placeholder="Select two or more columns to compare"),
orderInput('ns', 'Numbers', items = nums,
as_source = FALSE, connect = c('cs', 'sels'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cats,
as_source = FALSE, connect = c('ns', 'sels'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_cols", "OK"), fade = FALSE
)
)
})
observeEvent(input$grComp, {
showModal(
modalDialog(
title="Select columns",
orderInput('ind', 'Column to evaluate', items=c(),
as_source = FALSE, connect = c('ns', 'pred', 'cs'), width="100%", item_class="success", placeholder="Select the measured variable"),
orderInput('pred', 'Column with groups', items=c(),
as_source = FALSE, connect = c('ns', 'cs', 'ind'), width="100%", item_class="success", placeholder="Select the column defining the groups"),
orderInput('ns', 'Numbers', items = cookedData$nums,
as_source = FALSE, connect = c('cs', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cookedData$cats,
as_source = FALSE, connect = c('ns', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_grs", "OK"), fade = FALSE
)
)
})
observeEvent (input$ok_grs, {
req(input$ind_order, input$pred_order)
testSet$manConts <- NULL
if (length(input$ind_order) == 1 & length(input$pred_order)==1 & input$pred_order[1] %in% cookedData$cats){
testSet$settings <- "grComp"
c1 <- input$ind_order
c2 <- input$pred_order
testSet$vals <- cookedData$cooked[,c(input$ind_order, input$pred_order)]
updateNavbarPage(session, 'mainnavbar', selected = 'Groups ')
removeModal()
}
else {
if (input$pred_order[1] %in% cookedData$nums){
showModal(
modalDialog(
title="ERROR",
p("The grouping variable must be a category, not a number",style="font-face: bold; color: red"),
orderInput('ind', 'Column to evaluate', items=input$ind_order,
as_source = FALSE, connect = c('ns', 'cs', 'pred'), width="100%", item_class="success", placeholder="Select the measured variable"),
orderInput('pred', 'Column with groups', items=c(),
as_source = FALSE, connect = c('ns', 'cs', 'ind'), width="100%", item_class="success", placeholder="Select the column defining the groups"),
orderInput('ns', 'Numbers', items = cookedData$nums,
as_source = FALSE, connect = c('cs', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cookedData$cats,
as_source = FALSE, connect = c('ns', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_grs", "OK"), fade = FALSE
)
)
}
else{
showModal(
modalDialog(
title="ERROR",
p("One measured variable and one grouping variable needed",style="font-face: bold; color: red"),
orderInput('ind', 'Column to evaluate', items=c(),
as_source = FALSE, connect = c('ns', 'cs', 'pred'), width="100%", item_class="success", placeholder="Select the measured variable"),
orderInput('pred', 'Column with groups', items=c(),
as_source = FALSE, connect = c('ns', 'cs', 'ind'), width="100%", item_class="success", placeholder="Select the column defining the groups"),
orderInput('ns', 'Numbers', items = cookedData$nums,
as_source = FALSE, connect = c('cs', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cookedData$cats,
as_source = FALSE, connect = c('ns', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_grs", "OK"), fade = FALSE
)
)
}
}
})
observeEvent(input$grCChange, {
req(cookedData$cooked, cookedData$cats, cookedData$nums)
outp <- input$ind_order
preds <- input$pred_order
labs <- unique(c(outp, preds))
cats <- cookedData$cats[(!cookedData$cats %in% labs)]
nums <- cookedData$nums[(!cookedData$nums %in% labs)]
showModal(
modalDialog(
title="Select columns",
orderInput('ind', 'Column to evaluate', items=input$ind_order,
as_source = FALSE, connect = c('ns', 'pred', 'cs'), width="100%", item_class="success", placeholder="Select the measured variable"),
orderInput('pred', 'Column with groups', items=input$pred_order,
as_source = FALSE, connect = c('ns', 'cs', 'ind'), width="100%", item_class="success", placeholder="Select the column defining the groups"),
orderInput('ns', 'Numbers', items = nums,
as_source = FALSE, connect = c('cs', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cats,
as_source = FALSE, connect = c('ns', 'pred', 'ind'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_grs", "OK"), fade = FALSE
)
)
})
observeEvent(input$modSet, {
updateNavbarPage(session, 'mainnavbar', selected = 'Model data')
testSet$settings <- "mod"
req(cookedData$cooked, cookedData$cats, cookedData$nums)
showModal(
modalDialog(
title="Select columns",
orderInput('outp', 'Column to predict', items=c(),
as_source = FALSE, connect = c('ns', 'cs', 'pred'), width="100%", item_class="success", placeholder="Select the column to predict"),
orderInput('pred', 'Columns with predictors', items=c(),
as_source = FALSE, connect = c('ns', 'cs', 'outp'), width="100%", item_class="success", placeholder="Select one or more columns as predictors"),
orderInput('ns', 'Numbers', items = cookedData$nums,
as_source = FALSE, connect = c('cs', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cookedData$cats,
as_source = FALSE, connect = c('ns', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_mod", "OK"), fade = FALSE
)
)
})
observeEvent(input$modChange, {
updateNavbarPage(session, 'mainnavbar', selected = 'Model data')
testSet$settings <- "mod"
req(cookedData$cooked, cookedData$cats, cookedData$nums)
outp <- input$outp_order
preds <- input$pred_order
labs <- unique(c(outp, preds))
cats <- cookedData$cats[(!cookedData$cats %in% labs)]
nums <- cookedData$nums[(!cookedData$nums %in% labs)]
showModal(
modalDialog(
title="Select columns",
orderInput('outp', 'Column to predict', items=outp,
as_source = FALSE, connect = c('ns', 'cs', 'pred'), width="100%", item_class="success", placeholder="Select the column to predict"),
orderInput('pred', 'Columns with predictors', items=preds,
as_source = FALSE, connect = c('ns', 'cs', 'outp'), width="100%", item_class="info", placeholder="Select one or more columns as predictors"),
orderInput('ns', 'Numbers', items = nums,
as_source = FALSE, connect = c('cs', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cats,
as_source = FALSE, connect = c('ns', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_mod", "OK"), fade = FALSE
)
)
})
observeEvent(input$ok_cols, {
if (length(input$sels_order)>1 & (all(input$sels_order %in% cookedData$cats)|all(input$sels_order %in% cookedData$nums))) {
testSet$vals <- cookedData$cooked[,input$sels_order]
testSet$vals <- testSet$vals[!is.null(testSet$vals)]
testSet$manConts <- NULL
testSet$twoCol <- NULL
if (length(input$sels_order) == 2 & all(colnames(testSet$vals) %in% cookedData$nums)) {
showModal(modalDialog(
title="Test type",
h4("Decide what to do with these columns"),
p("Compare distribution - e.g. for counts from a corpus, where each row is a different option"),
actionButton("compCount", "Proceed"),
p("Compare means - e.g. for measurements, where each row is one participant"),
actionButton("compMeans", "Proceed"),
p("Compare values - to determine the strength of relationship between two numeric variables"),
actionButton("correlate", "Proceed"),
fade=FALSE,
easyClose=FALSE
))
}
else {removeModal()}
}
else if (length(input$sels_order)<2) {testSet$vals <- NULL
showModal(modalDialog(
title="ERROR",
h4("Not enough data - select two or more columns", style="font-face: bold; color: red"),
orderInput('sels', 'Columns to compare', items=c(),
as_source = FALSE, connect = c('ns', 'cs'), width="100%", item_class="primary", placeholder="Select two or more columns to compare"),
orderInput('ns', 'Numbers', items = cookedData$nums,
as_source = FALSE, connect = c('cs', 'sels'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cookedData$cats,
as_source = FALSE, connect = c('ns', 'sels'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_cols", "OK")
))
}
else {testSet$vals <- NULL
showModal(modalDialog(
title="ERROR",
h4("Can't compare numbers to categories", style="font-face: bold; color: red"),
orderInput('sels', 'Columns to compare', items=c(),
as_source = FALSE, connect = c('ns', 'cs'), width="100%", item_class="primary", placeholder="Select two or more columns to compare"),
orderInput('ns', 'Numbers', items = cookedData$nums,
as_source = FALSE, connect = c('cs', 'sels'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cookedData$cats,
as_source = FALSE, connect = c('ns', 'sels'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_cols", "OK")
))
}
})
observeEvent(input$compCount, {
testSet$twoCol <- "compCount"
showModal(modalDialog(
title="Set rownames",
p("Select the column which contains the names of the categories that the counts represent"),
selectInput("namesCol", label="Columns with labels",
choices=c(cookedData$cats),
),
actionButton("ok_namesCol", "OK"),
fade=FALSE,
easyClose=FALSE
))
})
observeEvent(input$ok_namesCol, {
testSet$namesCol <- input$namesCol
removeModal()
})
observeEvent(input$compMeans, {
testSet$twoCol <- "compMeans"
removeModal()
})
observeEvent(input$correlate, {
testSet$twoCol <- "correlate"
removeModal()
})
observeEvent(input$ok_mod, {
anovaGroups$finished <- NULL
if (length(input$outp_order)==1 & length(input$pred_order)>0) {
testSet$vals <- cookedData$cooked[,c(input$outp_order, input$pred_order)]
testSet$manConts <- NULL
removeModal()
}
else if (length(input$outp_order)!=1) {testSet$vals <- NULL
if (length(input$outp_order)!=0 | length(input$outp_order)!=0){
outp <- input$outp_order
preds <- input$pred_order
labs <- unique(c(outp, preds))
cats <- cookedData$cats[(!cookedData$cats %in% labs)]
nums <- cookedData$nums[(!cookedData$nums %in% labs)]
}
else {
if(length(input$outp_order)==0) {outp <- c()} else {outp <- input$outp_order}
if(length(input$pred_order)==0) {preds <- c()} else {preds <- input$pred_order}
labs <- unique(c(outp, preds))
cats <- cookedData$cats[(!cookedData$cats %in% labs)]
nums <- cookedData$nums[(!cookedData$nums %in% labs)]
}
showModal(modalDialog(
title="ERROR",
h4("Select one column to be predicted", style="font-face: bold; color: red"),
orderInput('outp', 'Column to predict', items=outp,
as_source = FALSE, connect = c('ns', 'cs', 'pred'), width="100%", item_class="success", placeholder="Select the column to predict"),
orderInput('pred', 'Columns with predictors', items=preds,
as_source = FALSE, connect = c('ns', 'cs', 'outp'), width="100%", item_class="info", placeholder="Select one or more columns as predictors"),
orderInput('ns', 'Numbers', items = nums,
as_source = FALSE, connect = c('cs', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cats,
as_source = FALSE, connect = c('ns', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_mod", "OK")
))
}
else {testSet$vals <- NULL
if (length(input$outp_order)!=0 | length(input$outp_order)!=0){
outp <- input$outp_order
preds <- input$pred_order
labs <- unique(c(outp, preds))
cats <- cookedData$cats[(!cookedData$cats %in% labs)]
nums <- cookedData$nums[(!cookedData$nums %in% labs)]
}
else {
if(length(input$outp_order)==0) {outp <- c()} else {outp <- input$outp_order}
if(length(input$pred_order)==0) {preds <- c()} else {preds <- input$pred_order}
labs <- unique(c(outp, preds))
cats <- cookedData$cats[(!cookedData$cats %in% labs)]
nums <- cookedData$nums[(!cookedData$nums %in% labs)]
}
showModal(modalDialog(
title="ERROR",
h4("Select some predictors", style="font-face: bold; color: red"),
orderInput('outp', 'Column to predict', items=outp,
as_source = FALSE, connect = c('ns', 'cs', 'pred'), width="100%", item_class="success", placeholder="Select the column to predict"),
orderInput('pred', 'Columns with predictors', items=preds,
as_source = FALSE, connect = c('ns', 'cs', 'outp'), width="100%", item_class="info", placeholder="Select one or more columns as predictors"),
orderInput('ns', 'Numbers', items = nums,
as_source = FALSE, connect = c('cs', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Numeric variables"),
orderInput('cs', 'Categories', items = cats,
as_source = FALSE, connect = c('ns', 'outp', 'pred'), width="100%", item_class="primary", placeholder="Categoric variables"),
footer=actionButton("ok_mod", "OK")
))
}
})
output$fulltab <- renderDataTable({
req(cookedData$cooked, input$selGrs)
cookedData$cooked
})
observeEvent(input$handleNAs, {
req(cookedData$cooked, settings)
showModal(
modalDialog(
title="Handle NAs",
p("Choose what to do with the missing values. Some tests will not work if they are kept."),
selectInput("naAction", label="",
c("Ignore missing values"="ignore",
"Keep missing values"="keep"
), settings$na.ignore),
footer=actionButton("ok_nas", "OK"),
easyClose=T
)
)
})
observeEvent(input$ok_nas, {
settings$na.ignore <- input$naAction
removeModal()
})
observeEvent(input$setContsCol,{
req(testSet$vals)
anovaGroups$finished <- NULL
if (testSet$settings=="colComp") {
dat0 <- testSet$vals
ids <- colnames(dat0)
dat <- data.frame(values__=c(), id__=c())
for (i in ids) {
dat <- rbind(dat, data.frame(values__=dat0[, i], id__=rep(i, length(dat0[, i]))))
}
dat$id__ <- factor(dat$id__)
if (settings$na.ignore=="ignore"){dat <- dat[rowSums(is.na(dat))==0,]}
groups <- levels(dat[,2])
}
else if (testSet$settings=="grComp"){
dat <- testSet$vals
colnames(dat) <- c("values__", "id__")