Implementing ggvis with shiny and circlize - r

Question

I'm trying to understand how ggvis works in the context of shiny and it's been a real headache. At this point I'm just trying to make something, anything interactive. Ideally I would like to be able to filter data points with sliders and be able to click on sectors and links to zoom and highlight respectively.
Ignoring the entire right bar, how would I be able to implement ggvis?
server.r
options(shiny.maxRequestSize=60*1024^2)
# Option to use scientific notation
options(scipen=999)
library(ggplot2)
library(ggvis)
shinyServer(function(input, output) {
inputData <- try(reactive({
inFile <- input$file1
if(is.null(inFile$datapath)){
return(iris)
}
newData <- read.csv(inFile$datapath, fill=TRUE)
newData
}))
output$choose_histVar <- renderUI({
newData <- inputData()
nameDataNew1<-c("ALL" ,"Earmarks", "Free-Cash")
if(class(nameDataNew1)!="try-error"){
selectInput("histVar", "1. Select Funding", as.list(nameDataNew1),
multiple = FALSE)
}
else{
selectInput("histVar", "1.Select Funding", NULL, multiple = FALSE)
}
})
# Use renderTable() function to render a table
output$summaryTable <- renderTable({ summary( try(inputData()) ) })
output$plot.hist <- renderPlot({
plotHistograms(data=try(inputData()), getCol=input$histVar,
getBin=input$bins)
})
output$plot.bar <- renderPlot({ plotcir(data)})
})
plotcir <- function(data) {
set.seed(999)
n = 1000
df = data.frame(factors = sample(letters[1:8], n, replace = TRUE),
x = rnorm(n), y = runif(n))
data.temp <- as.data.frame(df)
circos.par("track.height" = 0.1)
circos.initialize(factors = df$factors, x = df$x)
circos.track(factors = df$factors, y = df$y,
panel.fun = function(x, y) {
circos.text(CELL_META$xcenter, CELL_META$cell.ylim[2] + uy(5,
"mm"),
CELL_META$sector.index)
circos.axis(labels.cex = 0.6)
})
col = rep(c("#FF0000", "#00FF00"), 4)
circos.trackPoints(df$factors, df$x, df$y, col = col, pch = 16, cex = 0.5)
circos.text(-1, 0.5, "text", sector.index = "a", track.index = 1)
bgcol = rep(c("#EFEFEF", "#CCCCCC"), 4)
circos.trackHist(df$factors, df$x, bin.size = 0.2, bg.col = bgcol, col = NA)
circos.track(factors = df$factors, x = df$x, y = df$y,
panel.fun = function(x, y) {
ind = sample(length(x), 10)
x2 = x[ind]
y2 = y[ind]
od = order(x2)
circos.lines(x2[od], y2[od])
})
##vis <- reactive({})
circos.link("a", 0, "b", 0, h = 0.4)
circos.link("c", c(-0.5, 0.5), "d", c(-0.5,0.5), col = "red",
border = "blue", h = 0.2)
circos.link("e", 0, "g", c(-1,1), col = "green", border = "black", lwd = 2,
lty = 2)
}
ui.r
# Load libraries used in this Shiny App
library(shiny)
library(ggplot2)
library(circlize)
library(ggvis)
library(shinythemes)
shinyUI(fluidPage(
titlePanel(title = h2("The Wall", align="center")),
theme = shinytheme("cyborg"),
sidebarPanel(
fileInput('file1', 'The default dataset is df data. You may choose your own
CSV file'),
sliderInput('file1', 'Mission 1', value = 10, min = 0, max = 100, step = 1,
post = "%"),
sliderInput('file1', 'Mission 2', value = 0, min = 0, max = 100, step = 1,
post = "%"),
sliderInput('file1', 'Mission 3', value = 0, min = 0, max = 100, step = 1,
post = "%"),
sliderInput('file1', 'Mission 4', value = 0, min = 0, max = 100, step = 1,
post = "%"),
sliderInput('file1', 'Mission 5', value = 0, min = 0, max = 100, step = 1,
post = "%"),
uiOutput("choose_histVar"),
uiOutput("choose_xVar"),
uiOutput("choose_yVar"),
uiOutput("choose_cateVar"),
uiOutput("choose_barVar"),
p()
),
mainPanel(
h3('DOS - Augmented decisions'),
tabsetPanel(type="tab",
tabPanel( "Optimal",
plotOutput('plot.bar')
),
tabPanel("Histogram",
h4(checkboxInput("showHideHistograms", "Show/hide histograms",
value=FALSE)),
# Add a conditional panel to plot the histogram only when "Show
histogram" is checked
conditionalPanel(
condition = "input.showHideHistograms",
# Use plotOutput function to plot the output visualization
plotOutput('plot.hist')
)
)
),
p('')
)
))