jjallaire

library(shiny)
library(datasets)

# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {
  
  # Return the requested dataset
  datasetInput <- reactive({
    switch(input$dataset,
           "rock" = rock,

jjallaire

library(shiny)

# Define server logic for slider examples
shinyServer(function(input, output) {
  
  # Reactive expression to compose a data frame containing all of the values
  sliderValues <- reactive({
    
    # Compose data frame
    data.frame(

jjallaire

library(shiny)
library(datasets)

# We tweak the "am" field to have nicer factor labels. Since this doesn't
# rely on any user inputs we can do this once at startup and then use the
# value throughout the lifetime of the application
mpgData <- mtcars
mpgData$am <- factor(mpgData$am, labels = c("Automatic", "Manual"))

jjallaire

library(shiny)
library(datasets)

# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {

  # By declaring databaseInput as a reactive expression we ensure that:
  #
  #  1) It is only called when the inputs it depends on changes
  #  2) The computation and result are shared by all the callers (it 

jjallaire

library(shiny)
library(datasets)

# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {
  
  # Return the requested dataset
  datasetInput <- reactive({
    switch(input$dataset,
           "rock" = rock,

jjallaire

loadedPackageRequiresUpdate <- function(pkgs) {
  if (any(pkgs %in% loadedNamespaces())) {
    return(TRUE)
  }
  else {
    # compute dependent packages
    avail <- available.packages()
    if (getRversion() >= "2.15")
      deps <- tools:::package_dependencies(pkgs, db = avail, recursive = TRUE)
    else

jjallaire

loadedPackageUpdateRequired <- function(pkgs) {
  
  if (any(pkgs %in% loadedNamespaces())) {
    return(TRUE)
  }
  else {
    # compute dependent packages
    avail <- available.packages()
    if (getRversion() >= "2.15")
      deps <- tools:::package_dependencies(pkgs, db = avail, recursive = TRUE)

jjallaire

library(Rcpp)
library(microbenchmark)

cppFunction('
  IntegerVector table1(const CharacterVector x) {
    std::map<std::string, int> counts;
    std::vector<std::string> vec = as<std::vector<std::string> >(x);
  
    int n = x.length();
      for (int i = 0; i < n; i++) {

jjallaire

IntegerVector table1(const CharacterVector x) {
  std::map<char*, int> counts;

  int n = x.length();
  for (int i = 0; i < n; i++) {
    counts[x[i]]++;
  }

  // Loop through each element of map and output into named vector
  IntegerVector out(counts.size());

jjallaire

// [[Rcpp::depends(RcppArmadillo)]]

#include <Rcpp.h>

#include <RcppArmadillo.h>



using namespace Rcpp;