jcheng5

jpeg_dimensions <- function(filename, bytes = 1024) {
  bytes <- readBin(filename, "raw", n = bytes)
  
  if (length(bytes) < 2 || bytes[[1]] != 0xFF || bytes[[2]] != 0xD8) {
    stop("Couldn't decode jpeg")
  }
  
  ff <- which(bytes == 0xFF)
  c0 <- which(bytes == 0xC0)
  

jcheng5

```{js echo=FALSE}
function enshadowGtTable(tableEl) {
  var containerEl = tableEl.parentElement;
  var styleEl = containerEl.previousElementSibling;
  if (containerEl.tagName !== "DIV" || styleEl.tagName !== "STYLE") {
    throw new Error("Unexpected document structure");
  }
  var shadowDiv = document.createElement("div");
  shadowDiv.classList.add("gt-shadow-container");
  containerEl.parentElement.insertBefore(shadowDiv, styleEl);

jcheng5

As far as CRAN is concerned, there are two flavors of R on Solaris: one that is built using the Solaris Studio compiler, and one that is built using the GNU/gcc toolchain. The latter is far more up-to-date, but if your package requires it, then your DESCRIPTION file must declare that with the line SystemRequirements: GNU make.

These instructions are for configuring, building, and installing R-devel using the GNU/gcc toolchain (only).

You'll need VMWare Fusion on Mac, or VMWare Workstation (?) on Windows/Linux.

Get Solaris VM

Download the Solaris VM provided by Jeroen Ooms: https://github.com/jeroen/solarisvm

jcheng5

  590  pkgutil -i wget
  603  pkgutil -i gcc5gfortran
  609  pkgutil -i -y libiconv_dev
  613  pkgutil -i -y zlib_dev
  615  pkgutil -i -y libz_dev
  620  pkgutil -i -y liblzma_dev
  622  pkgutil -i -y libpcre_dev
  624  pkgutil -i -y libcurl_dev
  634  pkgutil -i -y libcurl4_dev
  647  pkgutil -y -i gmake

jcheng5

library(shiny)

ui <- fluidPage(
  numericInput("temp_c", "Celsius", NA),
  numericInput("temp_f", "Fahrenheit", NA)
)

server <- function(input, output, session) {
  c_to_f <- function(c, decimals = 1) {
    round((c * 9 / 5) + 32, decimals)

jcheng5

# BE SURE TO set your Mapbox access token with:
# options(mapbox.accessToken = "...")

library(htmltools)
library(leaflet)

mapboxgl_deps <- list(
  htmlDependency(
    "mapbox-gl-js", "0.53.0", c(href = "https://api.mapbox.com/mapbox-gl-js/v0.53.0/"),
    script = "mapbox-gl.js",

jcheng5

num_suffix <- function(x, base = 1000, suffixes = c("K", "M", "B", "T")) {
  
  if (length(suffixes) == 0) {
    tibble(
      scale_by = rep_len(1, length(x)),
      suffix = rep_len("", length(x))
    )
  }
  
  i <- floor(log(abs(x), base = base))

jcheng5

library(shiny)
library(leaflet)

#' Add a tile layer whose source is an R function
#'
#' @param tileFunc A function(x, y, z) that returns a 256x256 image object
#'   suitable for passing to `png::writePNG`.
#' @seealso [leaflet::addTiles()] for other parameters
addDynamicTiles <- function(map, tileFunc,
  layerId = paste0("leafletRaster", sample.int(9999999, 1)),

jcheng5

library(ggplot2)
library(shiny)

ui <- fluidPage(
  varSelectInput("color_by", "Color by:", diamonds, selected = "cut"),
  plotOutput("plot")
)

server <- function(input, output, session) {
  output$plot <- renderPlot({

jcheng5

# Examples:
# shiny              # Launch the Shiny app in the current directory
# shiny path/to/app  # Launch the Shiny app at the specified path
# shiny . launch.browser=F,port=8000   # Launch Shiny in the current dir with given options
function shiny {
  R --vanilla -q -e "shiny::runApp(\"${1:-.}\", launch.browser=TRUE, $2)"
}