├── .Rbuildignore ├── .gitignore ├── .travis.yml ├── DESCRIPTION ├── LICENSE ├── NAMESPACE ├── R ├── export_app.R ├── list_apps.R ├── list_categories.R ├── list_keywords.R ├── markdown.R └── run_app.R ├── README.md ├── _pkgdown.yaml ├── appveyor.yml ├── docs ├── LICENSE-text.html ├── apple-touch-icon-120x120.png ├── apple-touch-icon-152x152.png ├── apple-touch-icon-180x180.png ├── apple-touch-icon-60x60.png ├── apple-touch-icon-76x76.png ├── apple-touch-icon.png ├── articles │ ├── index.html │ ├── z1_install.html │ ├── z2_usage.html │ └── z3_participate.html ├── authors.html ├── docsearch.css ├── docsearch.js ├── favicon-16x16.png ├── favicon-32x32.png ├── favicon.ico ├── index.html ├── link.svg ├── logo.svg ├── pkgdown.css ├── pkgdown.js ├── pkgdown.yml ├── reference │ ├── export_app.html │ ├── figures │ │ └── logo.png │ ├── index.html │ ├── list_apps.html │ ├── list_categories.html │ ├── list_keywords.html │ └── run_app.html └── sitemap.xml ├── index.Rmd ├── inst ├── apps │ ├── aggregation_segregation │ │ ├── global.R │ │ ├── info │ │ ├── server.R │ │ ├── ui.R │ │ └── www │ │ │ ├── actions.js │ │ │ ├── custom.css │ │ │ └── white-rstudio-logo.png │ ├── ant_collective_decision │ │ ├── global.R │ │ ├── info │ │ ├── server.R │ │ ├── ui.R │ │ └── www │ │ │ ├── actions.js │ │ │ ├── custom.css │ │ │ └── white-rstudio-logo.png │ ├── axelrod │ │ ├── info │ │ └── www │ │ │ ├── actions.js │ │ │ ├── custom.css │ │ │ └── white-rstudio-logo.png │ ├── bee_house_hunting │ │ ├── global.R │ │ ├── info │ │ ├── server.R │ │ ├── ui.R │ │ └── www │ │ │ ├── actions.js │ │ │ ├── custom.css │ │ │ └── white-rstudio-logo.png │ ├── opinion_dynamics │ │ ├── global.R │ │ ├── info │ │ ├── server.R │ │ ├── ui.R │ │ └── www │ │ │ ├── actions.js │ │ │ ├── custom.css │ │ │ └── white-rstudio-logo.png │ └── wisdom_of_crowds │ │ ├── global.R │ │ ├── info │ │ ├── server.R │ │ ├── ui.R │ │ └── www │ │ ├── actions.js │ │ ├── custom.css │ │ └── white-rstudio-logo.png └── html_templates │ └── template.html ├── logo.png ├── logo.svg ├── man ├── export_app.Rd ├── figures │ └── logo.png ├── list_apps.Rd ├── list_categories.Rd ├── list_keywords.Rd └── run_app.Rd ├── pkgdown └── favicon │ ├── apple-touch-icon-120x120.png │ ├── apple-touch-icon-152x152.png │ ├── apple-touch-icon-180x180.png │ ├── apple-touch-icon-60x60.png │ ├── apple-touch-icon-76x76.png │ ├── apple-touch-icon.png │ ├── favicon-16x16.png │ ├── favicon-32x32.png │ └── favicon.ico ├── teachR.Rproj └── vignettes ├── z1_install.R ├── z1_install.Rmd ├── z1_install.html ├── z2_usage.Rmd ├── z2_usage.html ├── z3_participate.Rmd └── z3_participate.html /.Rbuildignore: -------------------------------------------------------------------------------- 1 | ^.*\.Rproj$ 2 | ^\.Rproj\.user$ 3 | .travis.yml 4 | _pkgdown.yaml 5 | appveyor.yml 6 | index.Rmd 7 | logo.* 8 | LICENSE -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .Rproj.user 2 | .Rhistory 3 | .RData 4 | src/*.o 5 | src/*.so 6 | src/*.dll 7 | .DS_STORE -------------------------------------------------------------------------------- /.travis.yml: -------------------------------------------------------------------------------- 1 | language: R 2 | sudo: false 3 | cran: http://cran.rstudio.com 4 | cache: packages 5 | warnings_are_errors: false 6 | os: 7 | - linux 8 | - osx 9 | 10 | r_build_args: "--no-manual --no-build-vignettes" 11 | r_check_args: "--as-cran --ignore-vignettes --no-examples --install-args=--build" 12 | 13 | before_install: 14 | - fname=travis_helpers.sh 15 | - wget -O ${fname} http://bit.ly/travis_helpers 16 | - cat ${fname}; source ${fname}; rm ${fname} 17 | - cat DESCRIPTION 18 | - export PACKAGE_NAME=`package_name` 19 | - export RCHECK_DIR=${PACKAGE_NAME}.Rcheck 20 | 21 | after_success: 22 | - cat ${RCHECK_DIR}/00install.out 23 | - cat ${RCHECK_DIR}/00check.log 24 | 25 | after_failure: 26 | - cat ${RCHECK_DIR}/00install.out 27 | - cat ${RCHECK_DIR}/00check.log 28 | 29 | before_deploy: 30 | - if [ "$TRAVIS_OS_NAME" = "osx" ]; 31 | then 32 | PKG_TARBALL=$(ls -1t *.tgz | head -n 1); 33 | PKG_TARBALL_WITH_R=`echo $PKG_TARBALL | sed 's/.tgz/_'"R${rver}"'.tgz/'` ; 34 | mv ${PKG_TARBALL} ${PKG_TARBALL_WITH_R} ; 35 | echo "Built tarball is ${PKG_TARBALL_WITH_R}" ; 36 | fi 37 | - if [ "$TRAVIS_OS_NAME" = "linux" ]; 38 | then 39 | PKG_TARBALL=$(ls -1t *.tar.gz | head -n 1); 40 | PKG_TARBALL_WITH_R=`echo $PKG_TARBALL | sed 's/.tar.gz/_'"R${rver}"'.tar.gz/'` ; 41 | mv ${PKG_TARBALL} ${PKG_TARBALL_WITH_R} ; 42 | echo "Built tarball is ${PKG_TARBALL_WITH_R}" ; 43 | fi 44 | - if [[ "${TRAVIS_OS_NAME}" = "osx" ]]; 45 | then 46 | rm -f *.tar.gz; 47 | fi 48 | 49 | deploy: 50 | provider: releases 51 | skip_cleanup: true 52 | api_key: 53 | secure: 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 54 | file_glob: true 55 | file: ${PACKAGE_NAME}*.t*gz 56 | on: 57 | repo: swarm-lab/${PACKAGE_NAME} 58 | tags: true 59 | -------------------------------------------------------------------------------- /DESCRIPTION: -------------------------------------------------------------------------------- 1 | Package: teachR 2 | Type: Package 3 | Title: R Package For Distributing Web Applications For Educational Use 4 | Version: 0.2 5 | Authors@R: c( 6 | person("Simon", "Garnier", email = "garnier@njit.edu", role = c("aut", "cre"), 7 | comment = c(ORCID = "0000-0002-3886-3974")) 8 | ) 9 | Maintainer: Simon Garnier 10 | Description: teachR is a package for R that bundles several Shiny web 11 | applications for educational use. The goal of teachR is to provide teachers 12 | and educators with free, easy-to-use and interactive applications for 13 | complementing their courses with virtual demonstrations and/or experiments. 14 | License: GPL-3 15 | Imports: 16 | shiny (>= 1.2.0), 17 | pacman (>= 0.5.0), 18 | shinythemes (>= 1.1.2), 19 | dplyr (>= 0.7.8), 20 | markdown (>= 0.9), 21 | mime (>= 0.6) 22 | Suggests: 23 | knitr 24 | VignetteBuilder: knitr 25 | URL: https://swarm-lab.github.io/teachR/, https://github.com/swarm-lab/teachR 26 | BugReports: https://github.com/swarm-lab/teachR/issues 27 | RoxygenNote: 6.1.1 28 | Encoding: UTF-8 29 | -------------------------------------------------------------------------------- /NAMESPACE: -------------------------------------------------------------------------------- 1 | # Generated by roxygen2: do not edit by hand 2 | 3 | export(export_app) 4 | export(list_apps) 5 | export(list_categories) 6 | export(list_keywords) 7 | export(run_app) 8 | -------------------------------------------------------------------------------- /R/export_app.R: -------------------------------------------------------------------------------- 1 | #' @title Export \code{teachR} Apps 2 | #' 3 | #' @description This function exports a Shiny app provided by the 4 | #' \code{teachR} library to a local folder on 5 | #' a user's computer. Useful for modifying the app or running it on a Shiny 6 | #' Server instance for example. 7 | #' 8 | #' @param app The name of the app to export. 9 | #' 10 | #' @param dest The destination of the app folder on the user's computer. A folder 11 | #' with the name of the app will be created at this location. 12 | #' 13 | #' @return This function does not return anything. 14 | #' 15 | #' @author Simon Garnier, \email{garnier@@njit.edu} 16 | #' 17 | #' @examples 18 | #' \dontrun{ 19 | #' # Export app to the current working directory 20 | #' export_app("aggregation_segregation", ".") 21 | #' } 22 | #' 23 | #' @export 24 | export_app <- function(app, dest) { 25 | app_path <- paste0(find.package("teachR"), "/apps/", app) 26 | file.copy(from = app_path, to = dest, recursive = TRUE) 27 | } 28 | 29 | -------------------------------------------------------------------------------- /R/list_apps.R: -------------------------------------------------------------------------------- 1 | #' @title List \code{teachR} Apps 2 | #' 3 | #' @description This function generates a webpage listing all the apps available 4 | #' through the \code{teachR} library. The list can be filtered by category 5 | #' (type \code{list_categories()} for a list of existing categories) and 6 | #' keywords (type \code{list_keywords()} for a list of existing keywords). 7 | #' 8 | #' @param categories A character string or a vector of character strings 9 | #' corresponding to existing app categories (case insensitive). 10 | #' 11 | #' @param keywords A character string or a vector of character strings 12 | #' corresponding to existing app keywords (case insensitive). 13 | #' 14 | #' @return This function opens an html file. 15 | #' 16 | #' @author Simon Garnier, \email{garnier@@njit.edu} 17 | #' 18 | #' @details If called from RStudio, the list will open in the internal RStudio 19 | #' viewer. If called from a terminal, it will open in your default internet 20 | #' browser. 21 | #' 22 | #' @examples 23 | #' \dontrun{ 24 | #' list_apps(categories = c("biology", "social science")) 25 | #' } 26 | #' 27 | #' @export 28 | list_apps <- function(categories=NULL, keywords=NULL) { 29 | apps <- dir(paste0(find.package("teachR"), "/apps")) 30 | info_table <- data.frame() 31 | 32 | for (i in 1:length(apps)) { 33 | info <- utils::read.table(paste0(find.package("teachR"), "/apps/", apps[i], "/info"), sep = ":") 34 | info <- t(as.matrix(info)[, 2]) 35 | info_table <- rbind(info_table, info) 36 | } 37 | info_table[] <- lapply(info_table, as.character) 38 | names(info_table) <- c("Title", "Version", "Date", "Author", 39 | "Maintainer", "Description", "Category", 40 | "Keywords", "License", "Depends", "Command" ) 41 | 42 | md <- .make_list(info_table, categories, keywords) 43 | 44 | tmp_file <- tempfile(pattern = "file", fileext = ".html") 45 | out <- knitr::knit(text = md) 46 | markdown::markdownToHTML(text = out, output = tmp_file, options = c("toc"), 47 | title = "Apps available in teachR", 48 | template = paste0(find.package("teachR"), "/html_templates/template.html")) 49 | 50 | viewer <- getOption("viewer") 51 | if (!is.null(viewer)) 52 | viewer(tmp_file) 53 | else 54 | utils::browseURL(tmp_file) 55 | } 56 | 57 | 58 | .index <- function(x, pattern) { 59 | pattern <- paste(tolower(pattern), collapse = "|") 60 | x <- tolower(x) 61 | grepl(pattern, x) 62 | } 63 | 64 | 65 | .make_list <- function(info_table, categories = NULL, keywords = NULL) { 66 | if (!is.null(categories)) { 67 | info_table <- dplyr::filter(info_table, .index(Category, categories)) 68 | } 69 | if (!is.null(keywords)) { 70 | info_table <- dplyr::filter(info_table, .index(Keywords, keywords)) 71 | } 72 | 73 | if (nrow(info_table) > 0) { 74 | categories <- sort(unique(unlist(strsplit(info_table$Category, ",")))) 75 | md <- c("---") 76 | 77 | for (i in 1:length(categories)) { 78 | category <- sub(" ", "", categories[i]) 79 | md <- c(md, paste0("### ", category)) 80 | 81 | tmp <- dplyr::filter(info_table, .index(Category, categories[i])) 82 | 83 | for (j in 1:nrow(tmp)) { 84 | md <- c(md, "") 85 | 86 | md <- c(md, "") 87 | md <- c(md, paste0("")) 88 | md <- c(md, "") 89 | 90 | md <- c(md, "") 91 | md <- c(md, "") 92 | md <- c(md, paste0("")) 93 | md <- c(md, "") 94 | 95 | md <- c(md, "") 96 | md <- c(md, "") 97 | md <- c(md, paste0("")) 98 | md <- c(md, "") 99 | 100 | md <- c(md, "") 101 | md <- c(md, "") 102 | md <- c(md, paste0("")) 103 | md <- c(md, "") 104 | 105 | md <- c(md, "") 106 | md <- c(md, "") 107 | md <- c(md, paste0("")) 108 | md <- c(md, "") 109 | 110 | md <- c(md, "") 111 | md <- c(md, "") 112 | md <- c(md, paste0("")) 113 | md <- c(md, "") 114 | 115 | md <- c(md, "
", sub(" ", "", tmp$Title[j]), "
Command: ", "run_app(\"", sub(" ", "", tmp$Command[j]), "\")
Description: ", sub(" ", "", tmp$Description[j]), "
Keywords: ", sub(" ", "", tmp$Keywords[j]), "
Depends on: ", sub(" ", "", tmp$Depends[j]), "
Author: ", sub(" ", "", tmp$Author[j]), "
") 116 | } 117 | } 118 | } else { 119 | stop(paste0("There is no app matching these categories and/or keywords.")) 120 | } 121 | 122 | md 123 | } 124 | 125 | 126 | # .markdownToHTML <- function(file, output = NULL, text = NULL, 127 | # options = getOption("markdown.HTML.options"), 128 | # extensions = getOption("markdown.extensions"), title = "", 129 | # stylesheet = getOption("markdown.HTML.stylesheet"), 130 | # header = getOption("markdown.HTML.header"), 131 | # template = getOption("markdown.HTML.template"), fragment.only = FALSE, 132 | # encoding = getOption("encoding")) { 133 | # if (fragment.only) 134 | # options <- c(options, "fragment_only") 135 | # ret <- markdown::renderMarkdown(file, output = NULL, text, renderer = "HTML", 136 | # renderer.options = options, extensions = extensions, 137 | # encoding = encoding) 138 | # ret <- enc2native(ret) 139 | # if ("base64_images" %in% options) { 140 | # filedir <- if (!missing(file) && is.character(file) && 141 | # file.exists(file)) { 142 | # dirname(file) 143 | # } 144 | # else "." 145 | # ret <- local({ 146 | # oldwd <- setwd(filedir) 147 | # on.exit(setwd(oldwd)) 148 | # .b64EncodeImages(ret) 149 | # }) 150 | # } 151 | # if (!"fragment_only" %in% options) { 152 | # if (is.null(template)) 153 | # template <- system.file("resources", "markdown.html", 154 | # package = "markdown") 155 | # html <- paste(readLines(template), collapse = "\n") 156 | # html <- sub("#!html_output#", ret, html, fixed = TRUE) 157 | # if (is.character(stylesheet)) { 158 | # html <- sub("#!markdown_css#", option2char(stylesheet), 159 | # html, fixed = TRUE) 160 | # } 161 | # else { 162 | # warning("stylesheet must either be valid CSS or a file containing CSS!") 163 | # } 164 | # html <- sub("#!header#", option2char(header), html, fixed = TRUE) 165 | # if (!is.character(title) || title == "") { 166 | # m <- regexpr("<[Hh][1-6].*?>(.*)", 167 | # html, perl = TRUE) 168 | # if (m > -1) { 169 | # title <- regmatches(html, m) 170 | # title <- sub("<[Hh][1-6].*?>", "", title) 171 | # title <- sub("", "", title) 172 | # } 173 | # else { 174 | # title <- "" 175 | # } 176 | # } 177 | # html <- gsub("#!title#", title, html, fixed = TRUE) 178 | # if ("mathjax" %in% options && .requiresMathJax(html)) { 179 | # mathjax <- .mathJax(embed = "mathjax_embed" %in% 180 | # options) 181 | # } 182 | # else mathjax <- "" 183 | # html <- sub("#!mathjax#", mathjax, html, fixed = TRUE) 184 | # if ("highlight_code" %in% options && .requiresHighlighting(html)) { 185 | # highlight <- paste(readLines(system.file("resources", 186 | # "r_highlight.html", package = "markdown")), collapse = "\n") 187 | # } 188 | # else highlight <- "" 189 | # html <- sub("#!r_highlight#", highlight, html, fixed = TRUE) 190 | # ret <- html 191 | # } 192 | # if (is.character(output)) { 193 | # ret2 <- iconv(ret, to = "UTF-8") 194 | # if (any(is.na(ret2))) { 195 | # warning("failed to convert output to UTF-8; wrong input encoding or locale?") 196 | # } 197 | # else ret <- ret2 198 | # writeLines(ret, output, useBytes = TRUE) 199 | # ret <- NULL 200 | # } 201 | # invisible(ret) 202 | # } 203 | -------------------------------------------------------------------------------- /R/list_categories.R: -------------------------------------------------------------------------------- 1 | #' @title List Categories of All \code{teachR} Apps 2 | #' 3 | #' @description This function generates a listing of all the categories of apps 4 | #' available through the \code{teachR} library. 5 | #' 6 | #' @return A vector of character strings, each of them corresponding to a different 7 | #' category. 8 | #' 9 | #' @author Simon Garnier, \email{garnier@@njit.edu} 10 | #' 11 | #' @examples 12 | #' \dontrun{ 13 | #' list_categories() 14 | #' } 15 | #' 16 | #' @export 17 | list_categories <- function() { 18 | apps <- dir(paste0(find.package("teachR"), "/apps")) 19 | info_table <- data.frame() 20 | 21 | for (i in 1:length(apps)) { 22 | info <- utils::read.table(paste0(find.package("teachR"), "/apps/", apps[i], "/info"), sep = ":") 23 | info <- t(as.matrix(info)[, 2]) 24 | info_table <- rbind(info_table, info) 25 | } 26 | info_table[] <- lapply(info_table, as.character) 27 | names(info_table) <- c("Title", "Version", "Date", "Author", 28 | "Maintainer", "Description", "Category", 29 | "Keywords", "License", "Depends", "Command" ) 30 | 31 | categories <- strsplit(info_table$Category, ",") 32 | categories <- sort(unique(unlist(categories))) 33 | sub(" ", "", categories) 34 | } 35 | -------------------------------------------------------------------------------- /R/list_keywords.R: -------------------------------------------------------------------------------- 1 | #' @title List Keywords of All \code{teachR} Apps 2 | #' 3 | #' @description This function generates a listing of all the keywords of apps 4 | #' available through the \code{teachR} library. 5 | #' 6 | #' @return A vector of character strings, each of them corresponding to a different 7 | #' keyword. 8 | #' 9 | #' @author Simon Garnier, \email{garnier@@njit.edu} 10 | #' 11 | #' @examples 12 | #' \dontrun{ 13 | #' list_keywords() 14 | #' } 15 | #' 16 | #' @export 17 | list_keywords <- function() { 18 | apps <- dir(paste0(find.package("teachR"), "/apps")) 19 | info_table <- data.frame() 20 | 21 | for (i in 1:length(apps)) { 22 | info <- utils::read.table(paste0(find.package("teachR"), "/apps/", apps[i], "/info"), sep = ":") 23 | info <- t(as.matrix(info)[, 2]) 24 | info_table <- rbind(info_table, info) 25 | } 26 | info_table[] <- lapply(info_table, as.character) 27 | names(info_table) <- c("Title", "Version", "Date", "Author", 28 | "Maintainer", "Description", "Category", 29 | "Keywords", "License", "Depends", "Command" ) 30 | 31 | keywords <- strsplit(info_table$Keywords, ",") 32 | keywords <- sort(unique(unlist(keywords))) 33 | sub(" ", "", keywords) 34 | } 35 | 36 | 37 | 38 | 39 | -------------------------------------------------------------------------------- /R/markdown.R: -------------------------------------------------------------------------------- 1 | #' # Functions copied from the markdown package 2 | #' .mathJax <- local({ 3 | #' js <- NULL 4 | #' 5 | #' function(embed=FALSE, force=FALSE) { 6 | #' if (!embed) 7 | #' return(paste(readLines(system.file( 8 | #' 'resources', 'mathjax.html', package = 'markdown' 9 | #' )), collapse = '\n')) 10 | #' 11 | #' url <- 'https://cdn.bootcss.com/mathjax/2.7.0/MathJax.js?config=TeX-MML-AM_CHTML' 12 | #' 13 | #' # Insert or link to MathJax script? 14 | #' html <- c('', if (embed) { 15 | #' # Already in cache? 16 | #' if (force || is.null(js)) { 17 | #' js <<- readLines(url, warn = FALSE) 18 | #' } 19 | #' c('') 23 | #' 24 | #' paste(html, collapse = "\n") 25 | #' } 26 | #' }) 27 | #' 28 | #' 29 | #' .requiresMathJax <- function(html) { 30 | #' regs <- c("\\\\\\(([\\s\\S]+?)\\\\\\)", "\\\\\\[([\\s\\S]+?)\\\\\\]") 31 | #' for (i in regs) if (any(grepl(i, html, perl = TRUE))) 32 | #' return(TRUE) 33 | #' FALSE 34 | #' } 35 | #' 36 | #' .requiresHighlighting <- function(html) { 37 | #' any(grepl("

12 | 
13 | `teachR` is a package for [`R`](http://www.r-project.org) that bundles several 
14 | [`Shiny`](http://shiny.rstudio.com/) web applications for educational use. 
15 | 
16 | The goal of `teachR` is to provide teachers and educators with free, easy-to-use
17 | and interactive applications for complementing their courses with virtual 
18 | demonstrations and/or experiments. 
19 | 
20 | The [`Shiny`](http://shiny.rstudio.com/) applications in `teachR` can be launched 
21 | directly from within [`R`](http://www.r-project.org) or [`RStudio`](http://www.rstudio.com). 
22 | They can also be exported toward a local folder for later deployment 
23 | on [`shinyapp.io`](https://www.shinyapps.io/) or on a personal 
24 | [`Shiny Server`](http://www.rstudio.com/products/shiny/shiny-server/) instance. 
25 | 
26 | The `teachR` package is at a very early stage of development. It contains only a 
27 | few [`Shiny`](http://shiny.rstudio.com/) applications at the moment, but this 
28 | number is meant to grow with the help of [`Shiny`](http://shiny.rstudio.com/) 
29 | developers looking to make their educational web applications more easily 
30 | accessible. 
31 | 
32 | If you are a [`Shiny`](http://shiny.rstudio.com/) developer and want to 
33 | participate, just fork this repository, add your application(s) to the "inst/apps" 
34 | folder with a properly formatted "info" file (see other apps for examples), and 
35 | send me a pull request. 
36 | 
37 | ---
38 | 
39 | ## Quick start guides
40 | 
41 | 1. [Installing teachR](https://swarm-lab.github.io/teachR/articles/z1_install)
42 | 2. [Using teachR](https://swarm-lab.github.io/ROpenCVLite/articles/z2_usage.html)
43 | 3. [Adding new apps to teachR](https://swarm-lab.github.io/ROpenCVLite/articles/z3_participate.html)
44 | 
45 | ---
46 | 


--------------------------------------------------------------------------------
/_pkgdown.yaml:
--------------------------------------------------------------------------------
 1 | url: https://swarm-lab.github.io/teachR/
 2 | 
 3 | template:
 4 |   params:
 5 |     bootswatch: yeti
 6 | #    docsearch:
 7 | #      api_key: 3a2946bbe34c635ad2e2aae74a83374b
 8 | #      index_name: swarm-lab-swarm
 9 | 
10 | authors:
11 |   Simon Garnier:
12 |     href: http://www.theswarmlab.com
13 | 
14 | development:
15 |   mode: unreleased
16 | 


--------------------------------------------------------------------------------
/appveyor.yml:
--------------------------------------------------------------------------------
 1 | # DO NOT CHANGE
 2 | init:
 3 |   ps: |
 4 |     $ErrorActionPreference = "Stop"
 5 |     Invoke-WebRequest http://raw.github.com/krlmlr/r-appveyor/master/scripts/appveyor-tool.ps1 -OutFile "..\appveyor-tool.ps1"
 6 |     Import-Module '..\appveyor-tool.ps1'
 7 | 
 8 | install:
 9 |   ps: Bootstrap
10 | 
11 | cache:
12 |   - C:\RLibrary
13 | 
14 | 
15 | # Adapt as necessary starting from here
16 | environment:
17 |   global:
18 |     WARNINGS_ARE_ERRORS: 0.0
19 |     USE_RTOOLS: yes
20 |     R_CHECK_INSTALL_ARGS: --install-args=--build
21 | 
22 |   matrix:
23 |   - R_VERSION: stable
24 |     RTOOLS_VERSION: 34
25 |     CRAN: http://cran.rstudio.com
26 | 
27 | build_script:
28 |   - travis-tool.sh install_deps
29 | 
30 | test_script:
31 |   - travis-tool.sh run_tests
32 | 
33 | on_failure:
34 |   - 7z a failure.zip *.Rcheck\*
35 |   - appveyor PushArtifact failure.zip
36 | 
37 | artifacts:
38 |   - path: '*.Rcheck\**\*.log'
39 |     name: Logs
40 |   - path: '*.Rcheck\**\*.out'
41 |     name: Logs
42 |   - path: '*.Rcheck\**\*.fail'
43 |     name: Logs
44 |   - path: '*.Rcheck\**\*.Rout'
45 |     name: Logs
46 |   - path: '\*_*.tar.gz'
47 |     name: Bits
48 |   - path: '\*_*.zip'
49 |     name: Bits
50 | 
51 | deploy:
52 |   provider: GitHub
53 |   description: Windows Binary
54 |   auth_token:
55 |     secure: h+8/Q2kGkLoaoZ8OEtsplJGXuPFhS/VQbtE66cMJj7J3PeDgNAROVkV7368h3s+b
56 |   draft: no
57 |   prerelease: no
58 |   on:
59 |     APPVEYOR_REPO_TAG: true
60 | 


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1 - Installing teachR

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103 | 
This page describes the installation process of teachR.

104 | 
teachR has not been released on CRAN yet, but it can be easily installed from its GitHub repository with the following steps.

105 | 

106 | 
111 | 

112 | 

113 | 

114 | 1.1 - Before installing

115 | 
Before installing teachR, you will need to install the latest version of the devtools package. You can install devtools from CRAN as follows:

116 | 
if (!require(devtools))
117 |   install.packages("devtools")

118 | 

119 | 

120 | 

121 | 

122 | 1.2 - Installing teachR

123 | 
You can install teachR as follows:

124 | 
devtools::install_github("swarm-lab/teachR")

125 | 

126 | 

127 | 

128 | 

129 | 1.3 - Loading teachR

130 | 
library(teachR)

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This page describes how to add apps to teachR.

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131 |       
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132 |         
    Simon Garnier. Author, maintainer. ORCID
133 |         
    
134 |       
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135 |     

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 7 |       e.preventDefault();
 8 |       $("#search-input").focus();
 9 |     }
10 |   });
11 | 
12 |   $(document).ready(function() {
13 |     // do keyword highlighting
14 |     /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */
15 |     var mark = function() {
16 | 
17 |       var referrer = document.URL ;
18 |       var paramKey = "q" ;
19 | 
20 |       if (referrer.indexOf("?") !== -1) {
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22 |         var qs_noanchor = qs.split('#')[0];
23 |         var qsa = qs_noanchor.split('&');
24 |         var keyword = "";
25 | 
26 |         for (var i = 0; i < qsa.length; i++) {
27 |           var currentParam = qsa[i].split('=');
28 | 
29 |           if (currentParam.length !== 2) {
30 |             continue;
31 |           }
32 | 
33 |           if (currentParam[0] == paramKey) {
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36 |         }
37 | 
38 |         if (keyword !== "") {
39 |           $(".contents").unmark({
40 |             done: function() {
41 |               $(".contents").mark(keyword);
42 |             }
43 |           });
44 |         }
45 |       }
46 |     };
47 | 
48 |     mark();
49 |   });
50 | });
51 | 
52 | /* Search term highlighting ------------------------------*/
53 | 
54 | function matchedWords(hit) {
55 |   var words = [];
56 | 
57 |   var hierarchy = hit._highlightResult.hierarchy;
58 |   // loop to fetch from lvl0, lvl1, etc.
59 |   for (var idx in hierarchy) {
60 |     words = words.concat(hierarchy[idx].matchedWords);
61 |   }
62 | 
63 |   var content = hit._highlightResult.content;
64 |   if (content) {
65 |     words = words.concat(content.matchedWords);
66 |   }
67 | 
68 |   // return unique words
69 |   var words_uniq = [...new Set(words)];
70 |   return words_uniq;
71 | }
72 | 
73 | function updateHitURL(hit) {
74 | 
75 |   var words = matchedWords(hit);
76 |   var url = "";
77 | 
78 |   if (hit.anchor) {
79 |     url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor;
80 |   } else {
81 |     url = hit.url + '?q=' + escape(words.join(" "));
82 |   }
83 | 
84 |   return url;
85 | }
86 | 


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13 | 	teachR
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  3 | /**
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  5 |  * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
  6 |  *
  7 |  * .Site -> body > .container
  8 |  * .Site-content -> body > .container .row
  9 |  * .footer -> footer
 10 |  *
 11 |  * Key idea seems to be to ensure that .container and __all its parents__
 12 |  * have height set to 100%
 13 |  *
 14 |  */
 15 | 
 16 | html, body {
 17 |   height: 100%;
 18 | }
 19 | 
 20 | body > .container {
 21 |   display: flex;
 22 |   height: 100%;
 23 |   flex-direction: column;
 24 | 
 25 |   padding-top: 60px;
 26 | }
 27 | 
 28 | body > .container .row {
 29 |   flex: 1 0 auto;
 30 | }
 31 | 
 32 | footer {
 33 |   margin-top: 45px;
 34 |   padding: 35px 0 36px;
 35 |   border-top: 1px solid #e5e5e5;
 36 |   color: #666;
 37 |   display: flex;
 38 |   flex-shrink: 0;
 39 | }
 40 | footer p {
 41 |   margin-bottom: 0;
 42 | }
 43 | footer div {
 44 |   flex: 1;
 45 | }
 46 | footer .pkgdown {
 47 |   text-align: right;
 48 | }
 49 | footer p {
 50 |   margin-bottom: 0;
 51 | }
 52 | 
 53 | img.icon {
 54 |   float: right;
 55 | }
 56 | 
 57 | img {
 58 |   max-width: 100%;
 59 | }
 60 | 
 61 | /* Fix bug in bootstrap (only seen in firefox) */
 62 | summary {
 63 |   display: list-item;
 64 | }
 65 | 
 66 | /* Typographic tweaking ---------------------------------*/
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 68 | .contents .page-header {
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 70 | }
 71 | 
 72 | /* Section anchors ---------------------------------*/
 73 | 
 74 | a.anchor {
 75 |   margin-left: -30px;
 76 |   display:inline-block;
 77 |   width: 30px;
 78 |   height: 30px;
 79 |   visibility: hidden;
 80 | 
 81 |   background-image: url(./link.svg);
 82 |   background-repeat: no-repeat;
 83 |   background-size: 20px 20px;
 84 |   background-position: center center;
 85 | }
 86 | 
 87 | .hasAnchor:hover a.anchor {
 88 |   visibility: visible;
 89 | }
 90 | 
 91 | @media (max-width: 767px) {
 92 |   .hasAnchor:hover a.anchor {
 93 |     visibility: hidden;
 94 |   }
 95 | }
 96 | 
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 98 | /* Fixes for fixed navbar --------------------------*/
 99 | 
100 | .contents h1, .contents h2, .contents h3, .contents h4 {
101 |   padding-top: 60px;
102 |   margin-top: -40px;
103 | }
104 | 
105 | /* Static header placement on mobile devices */
106 | @media (max-width: 767px) {
107 |   .navbar-fixed-top {
108 |     position: absolute;
109 |   }
110 |   .navbar {
111 |     padding: 0;
112 |   }
113 | }
114 | 
115 | 
116 | /* Sidebar --------------------------*/
117 | 
118 | #sidebar {
119 |   margin-top: 30px;
120 | }
121 | #sidebar h2 {
122 |   font-size: 1.5em;
123 |   margin-top: 1em;
124 | }
125 | 
126 | #sidebar h2:first-child {
127 |   margin-top: 0;
128 | }
129 | 
130 | #sidebar .list-unstyled li {
131 |   margin-bottom: 0.5em;
132 | }
133 | 
134 | .orcid {
135 |   height: 16px;
136 |   vertical-align: middle;
137 | }
138 | 
139 | /* Reference index & topics ----------------------------------------------- */
140 | 
141 | .ref-index th {font-weight: normal;}
142 | 
143 | .ref-index td {vertical-align: top;}
144 | .ref-index .icon {width: 40px;}
145 | .ref-index .alias {width: 40%;}
146 | .ref-index-icons .alias {width: calc(40% - 40px);}
147 | .ref-index .title {width: 60%;}
148 | 
149 | .ref-arguments th {text-align: right; padding-right: 10px;}
150 | .ref-arguments th, .ref-arguments td {vertical-align: top;}
151 | .ref-arguments .name {width: 20%;}
152 | .ref-arguments .desc {width: 80%;}
153 | 
154 | /* Nice scrolling for wide elements --------------------------------------- */
155 | 
156 | table {
157 |   display: block;
158 |   overflow: auto;
159 | }
160 | 
161 | /* Syntax highlighting ---------------------------------------------------- */
162 | 
163 | pre {
164 |   word-wrap: normal;
165 |   word-break: normal;
166 |   border: 1px solid #eee;
167 | }
168 | 
169 | pre, code {
170 |   background-color: #f8f8f8;
171 |   color: #333;
172 | }
173 | 
174 | pre code {
175 |   overflow: auto;
176 |   word-wrap: normal;
177 |   white-space: pre;
178 | }
179 | 
180 | pre .img {
181 |   margin: 5px 0;
182 | }
183 | 
184 | pre .img img {
185 |   background-color: #fff;
186 |   display: block;
187 |   height: auto;
188 | }
189 | 
190 | code a, pre a {
191 |   color: #375f84;
192 | }
193 | 
194 | a.sourceLine:hover {
195 |   text-decoration: none;
196 | }
197 | 
198 | .fl      {color: #1514b5;}
199 | .fu      {color: #000000;} /* function */
200 | .ch,.st  {color: #036a07;} /* string */
201 | .kw      {color: #264D66;} /* keyword */
202 | .co      {color: #888888;} /* comment */
203 | 
204 | .message { color: black;   font-weight: bolder;}
205 | .error   { color: orange;  font-weight: bolder;}
206 | .warning { color: #6A0366; font-weight: bolder;}
207 | 
208 | /* Clipboard --------------------------*/
209 | 
210 | .hasCopyButton {
211 |   position: relative;
212 | }
213 | 
214 | .btn-copy-ex {
215 |   position: absolute;
216 |   right: 0;
217 |   top: 0;
218 |   visibility: hidden;
219 | }
220 | 
221 | .hasCopyButton:hover button.btn-copy-ex {
222 |   visibility: visible;
223 | }
224 | 
225 | /* mark.js ----------------------------*/
226 | 
227 | mark {
228 |   background-color: rgba(255, 255, 51, 0.5);
229 |   border-bottom: 2px solid rgba(255, 153, 51, 0.3);
230 |   padding: 1px;
231 | }
232 | 
233 | /* vertical spacing after htmlwidgets */
234 | .html-widget {
235 |   margin-bottom: 10px;
236 | }
237 | 


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  1 | /* http://gregfranko.com/blog/jquery-best-practices/ */
  2 | (function($) {
  3 |   $(function() {
  4 | 
  5 |     $("#sidebar")
  6 |       .stick_in_parent({offset_top: 40})
  7 |       .on('sticky_kit:bottom', function(e) {
  8 |         $(this).parent().css('position', 'static');
  9 |       })
 10 |       .on('sticky_kit:unbottom', function(e) {
 11 |         $(this).parent().css('position', 'relative');
 12 |       });
 13 | 
 14 |     $('body').scrollspy({
 15 |       target: '#sidebar',
 16 |       offset: 60
 17 |     });
 18 | 
 19 |     $('[data-toggle="tooltip"]').tooltip();
 20 | 
 21 |     var cur_path = paths(location.pathname);
 22 |     var links = $("#navbar ul li a");
 23 |     var max_length = -1;
 24 |     var pos = -1;
 25 |     for (var i = 0; i < links.length; i++) {
 26 |       if (links[i].getAttribute("href") === "#")
 27 |         continue;
 28 |       // Ignore external links
 29 |       if (links[i].host !== location.host)
 30 |         continue;
 31 | 
 32 |       var nav_path = paths(links[i].pathname);
 33 | 
 34 |       var length = prefix_length(nav_path, cur_path);
 35 |       if (length > max_length) {
 36 |         max_length = length;
 37 |         pos = i;
 38 |       }
 39 |     }
 40 | 
 41 |     // Add class to parent 
  • , and enclosing 
  •  if in dropdown
 42 |     if (pos >= 0) {
 43 |       var menu_anchor = $(links[pos]);
 44 |       menu_anchor.parent().addClass("active");
 45 |       menu_anchor.closest("li.dropdown").addClass("active");
 46 |     }
 47 |   });
 48 | 
 49 |   function paths(pathname) {
 50 |     var pieces = pathname.split("/");
 51 |     pieces.shift(); // always starts with /
 52 | 
 53 |     var end = pieces[pieces.length - 1];
 54 |     if (end === "index.html" || end === "")
 55 |       pieces.pop();
 56 |     return(pieces);
 57 |   }
 58 | 
 59 |   // Returns -1 if not found
 60 |   function prefix_length(needle, haystack) {
 61 |     if (needle.length > haystack.length)
 62 |       return(-1);
 63 | 
 64 |     // Special case for length-0 haystack, since for loop won't run
 65 |     if (haystack.length === 0) {
 66 |       return(needle.length === 0 ? 0 : -1);
 67 |     }
 68 | 
 69 |     for (var i = 0; i < haystack.length; i++) {
 70 |       if (needle[i] != haystack[i])
 71 |         return(i);
 72 |     }
 73 | 
 74 |     return(haystack.length);
 75 |   }
 76 | 
 77 |   /* Clipboard --------------------------*/
 78 | 
 79 |   function changeTooltipMessage(element, msg) {
 80 |     var tooltipOriginalTitle=element.getAttribute('data-original-title');
 81 |     element.setAttribute('data-original-title', msg);
 82 |     $(element).tooltip('show');
 83 |     element.setAttribute('data-original-title', tooltipOriginalTitle);
 84 |   }
 85 | 
 86 |   if(ClipboardJS.isSupported()) {
 87 |     $(document).ready(function() {
 88 |       var copyButton = "";
 89 | 
 90 |       $(".examples, div.sourceCode").addClass("hasCopyButton");
 91 | 
 92 |       // Insert copy buttons:
 93 |       $(copyButton).prependTo(".hasCopyButton");
 94 | 
 95 |       // Initialize tooltips:
 96 |       $('.btn-copy-ex').tooltip({container: 'body'});
 97 | 
 98 |       // Initialize clipboard:
 99 |       var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', {
100 |         text: function(trigger) {
101 |           return trigger.parentNode.textContent;
102 |         }
103 |       });
104 | 
105 |       clipboardBtnCopies.on('success', function(e) {
106 |         changeTooltipMessage(e.trigger, 'Copied!');
107 |         e.clearSelection();
108 |       });
109 | 
110 |       clipboardBtnCopies.on('error', function() {
111 |         changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy');
112 |       });
113 |     });
114 |   }
115 | })(window.jQuery || window.$)
116 | 


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 1 | pandoc: 1.19.2.1
 2 | pkgdown: 1.3.0
 3 | pkgdown_sha: ~
 4 | articles:
 5 |   z1_install: z1_install.html
 6 |   z2_usage: z2_usage.html
 7 |   z3_participate: z3_participate.html
 8 | urls:
 9 |   reference: https://swarm-lab.github.io/teachR//reference
10 |   article: https://swarm-lab.github.io/teachR//articles
11 | 
12 | 


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130 |   
    
131 |     
    
132 |     
    Export teachR Apps
    
133 |     Source: R/export_app.R
134 |     
135 |     
    
136 | 
137 |     
    
138 |     
139 |     
    This function exports a Shiny app provided by the 
140 |  teachR library to a local folder on 
141 |  a user's computer. Useful for modifying the app or running it on a Shiny 
142 |  Server instance for example.
    
143 |     
144 |     
    
145 | 
146 |     
    export_app(app, dest)
    
147 |     
148 |     
    Arguments
    
149 |     
150 |     
151 |     
152 |       
153 |       
154 |     
155 |     
156 |       
157 |       
159 |     
160 |     
    app
    The name of the app to export.
    dest
    The destination of the app folder on the user's computer. A folder
158 | with the name of the app will be created at this location.
    
161 |     
162 |     
    Value
    
163 | 
164 |     
    This function does not return anything.
    
165 |     
166 | 
167 |     
    Examples
    
168 |     
    # NOT RUN {
169 |  # Export app to the current working directory
170 |  export_app("aggregation_segregation", ".")
171 | # }
    
172 | 
    
173 |   
    
174 |   
187 | 
    
188 | 
189 |       
    
190 |       
    
191 |   
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192 | 
    
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195 |   
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196 | 
    
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127 |       
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128 |     
    
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132 |     133 |       
134 |       135 |       136 |     
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177 |     
    



    
141 |           
    All functions
    
142 |           
    
143 |         
    
148 |           
    export_app() 
    
149 |         
    Export teachR Apps
    
154 |           
    list_apps() 
    
155 |         
    List teachR Apps
    
160 |           
    list_categories() 
    
161 |         
    List Categories of All teachR Apps
    
166 |           
    list_keywords() 
    
167 |         
    List Keywords of All teachR Apps
    
172 |           
    run_app() 
    
173 |         
    Run teachR Apps
    
178 |   
    
179 | 
180 |   
186 | 
    
187 | 
188 |       
    
189 |       
    
190 |   
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191 | 
    
192 | 
193 | 
    
194 |   
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195 | 
    
196 |       
    
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  8 | 
  9 | List <code>teachR</code> Apps — list_apps • teachR
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130 |   
    
131 |     
    
132 |     
    List teachR Apps
    
133 |     Source: R/list_apps.R
134 |     
135 |     
    
136 | 
137 |     
    
138 |     
139 |     
    This function generates a webpage listing all the apps available 
140 |  through the teachR library. The list can be filtered by category 
141 |  (type list_categories() for a list of existing categories) and 
142 |  keywords (type list_keywords() for a list of existing keywords).
    
143 |     
144 |     
    
145 | 
146 |     
    list_apps(categories = NULL, keywords = NULL)
    
147 |     
148 |     
    Arguments
    
149 |     
150 |     
151 |     
152 |       
153 |       
155 |     
156 |     
157 |       
158 |       
160 |     
161 |     
    categories
    A character string or a vector of character strings 
154 | corresponding to existing app categories (case insensitive).
    keywords
    A character string or a vector of character strings 
159 | corresponding to existing app keywords (case insensitive).
    
162 |     
163 |     
    Value
    
164 | 
165 |     
    This function opens an html file.
    
166 |     
167 |     
    Details
    
168 | 
169 |     
    If called from RStudio, the list will open in the internal RStudio 
170 |  viewer. If called from a terminal, it will open in your default internet 
171 |  browser.
    
172 |     
173 | 
174 |     
    Examples
    
175 |     
    # NOT RUN {
176 |  list_apps(categories = c("biology", "social science"))
177 | # }
    
178 | 
    
179 |   
    
180 |   
195 | 
    
196 | 
197 |       
    
198 |       
    
199 |   
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200 | 
    
201 | 
202 | 
    
203 |   
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204 | 
    
205 |       
    
206 |    
    
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128 |   
    
129 |     
    
130 |     
    List Categories of All teachR Apps
    
131 |     Source: R/list_categories.R
132 |     
133 |     
    
134 | 
135 |     
    
136 |     
137 |     
    This function generates a listing  of all the categories of apps 
138 |  available through the teachR library.
    
139 |     
140 |     
    
141 | 
142 |     
    list_categories()
    
143 |         
144 |     
    Value
    
145 | 
146 |     
    A vector of character strings, each of them corresponding to a different
147 |  category.
    
148 |     
149 | 
150 |     
    Examples
    
151 |     
    # NOT RUN {
152 |  list_categories()
153 | # }
    
154 | 
    
155 |   
    
156 |   
168 | 
    
169 | 
170 |       
    
171 |       
    
172 |   
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173 | 
    
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175 | 
    
176 |   
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177 | 
    
178 |       
    
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128 |   
    
129 |     
    
130 |     
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131 |     Source: R/list_keywords.R
132 |     
133 |     
    
134 | 
135 |     
    
136 |     
137 |     
    This function generates a listing of all the keywords of apps 
138 |  available through the teachR library.
    
139 |     
140 |     
    
141 | 
142 |     
    list_keywords()
    
143 |         
144 |     
    Value
    
145 | 
146 |     
    A vector of character strings, each of them corresponding to a different
147 |  keyword.
    
148 |     
149 | 
150 |     
    Examples
    
151 |     
    # NOT RUN {
152 |  list_keywords()
153 | # }
    
154 | 
    
155 |   
    
156 |   
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169 | 
170 |       
    
171 |       
    
172 |   
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173 | 
    
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176 |   
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177 | 
    
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128 | 
    
129 |   
    
130 |     
    
131 |     
    Run teachR Apps
    
132 |     Source: R/run_app.R
133 |     
134 |     
    
135 | 
136 |     
    
137 |     
138 |     
    This function calls a Shiny app provided by the 
139 |  teachR library. The list of available Shiny apps can be obtained by 
140 |  typing list_apps() in your R terminal.
    
141 |     
142 |     
    
143 | 
144 |     
    run_app(app)
    
145 |     
146 |     
    Arguments
    
147 |     
148 |     
149 |     
150 |       
151 |       
152 |     
153 |     
    app
    The name of the app to run.
    
154 |     
155 |     
    Value
    
156 | 
157 |     
    This function does not return anything.
    
158 |     
159 |     
    Details
    
160 | 
161 |     
    If called from RStudio, the app will open in the internal RStudio 
162 |  internet browser. If called from a terminal, it will open in your default 
163 |  internet browser. All apps should work without any problem with the internal 
164 |  RStudio internet browser, as well as with recent versions of most internet 
165 |  browsers. It is likely to break with older versions.
    
166 |     
167 | 
168 |     
    Examples
    
169 |     
    # NOT RUN {
170 |  run_app("aggregation_segregation")
171 | # }
    
172 | 
    
173 |   
    
174 |   
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190 | 
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193 |   
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194 | 
    
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197 |   
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198 | 
    
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 2 | 
 3 |   
 4 |     https://swarm-lab.github.io/teachR//index.html
 5 |   
 6 |   
 7 |     https://swarm-lab.github.io/teachR//reference/export_app.html
 8 |   
 9 |   
10 |     https://swarm-lab.github.io/teachR//reference/list_apps.html
11 |   
12 |   
13 |     https://swarm-lab.github.io/teachR//reference/list_categories.html
14 |   
15 |   
16 |     https://swarm-lab.github.io/teachR//reference/list_keywords.html
17 |   
18 |   
19 |     https://swarm-lab.github.io/teachR//reference/run_app.html
20 |   
21 |   
22 |     https://swarm-lab.github.io/teachR//articles/z1_install.html
23 |   
24 |   
25 |     https://swarm-lab.github.io/teachR//articles/z2_usage.html
26 |   
27 |   
28 |     https://swarm-lab.github.io/teachR//articles/z3_participate.html
29 |   
30 | 
31 | 


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/index.Rmd:
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 1 | ---
 2 | output: github_document
 3 | ---
 4 | 
 5 | # teachR - R package for distributing web applications for educational use 
 6 | 
 7 | [![Travis-CI Build Status](https://travis-ci.org/swarm-lab/teachR.svg?branch=master)](https://travis-ci.org/swarm-lab/teachR)
 8 | [![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/swarm-lab/teachR?branch=master&svg=true)](https://ci.appveyor.com/project/swarm-lab/teachR)
 9 | 
10 | **Please submit all suggestions and bug reports 
11 | [here](https://github.com/swarm-lab/teachR/issues). Thanks!**
12 | 
13 | ---
14 | 
15 | ## Description 
16 | 
17 | `teachR` is a package for [`R`](http://www.r-project.org) that bundles several 
18 | [`Shiny`](http://shiny.rstudio.com/) web applications for educational use. 
19 | 
20 | The goal of `teachR` is to provide teachers and educators with free, easy-to-use
21 | and interactive applications for complementing their courses with virtual 
22 | demonstrations and/or experiments. 
23 | 
24 | The [`Shiny`](http://shiny.rstudio.com/) applications in `teachR` can be launched 
25 | directly from within [`R`](http://www.r-project.org) or [`RStudio`](http://www.rstudio.com). 
26 | They can also be exported toward a local folder for later deployment 
27 | on [`shinyapp.io`](https://www.shinyapps.io/) or on a personal 
28 | [`Shiny Server`](http://www.rstudio.com/products/shiny/shiny-server/) instance. 
29 | 
30 | The `teachR` package is at a very early stage of development. It contains only a 
31 | few [`Shiny`](http://shiny.rstudio.com/) applications at the moment, but this 
32 | number is meant to grow with the help of [`Shiny`](http://shiny.rstudio.com/) 
33 | developers looking to make their educational web applications more easily 
34 | accessible. 
35 | 
36 | If you are a [`Shiny`](http://shiny.rstudio.com/) developer and want to 
37 | participate, just fork this repository, add your application(s) to the "inst/apps" 
38 | folder with a properly formatted "info" file (see other apps for examples), and 
39 | send me a pull request. 
40 | 
41 | ---
42 | 
43 | ## Quick start guides
44 | 
45 | 1. [Installing teachR](https://swarm-lab.github.io/teachR/articles/z1_install)
46 | 2. [Using teachR](https://swarm-lab.github.io/ROpenCVLite/articles/z2_usage.html)
47 | 3. [Adding new apps to teachR](https://swarm-lab.github.io/ROpenCVLite/articles/z3_participate.html)
48 | 
49 | ---
50 | 


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/inst/apps/aggregation_segregation/global.R:
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  1 | #### LOAD LIBRARIES #### 
  2 | pacman::p_load(shiny, shinythemes, dplyr, ggvis)
  3 | 
  4 | 
  5 | #### DEFINE CUSTOM FUNCTIONS ####
  6 | #' @title Random Walk
  7 | #' 
  8 | #' @description This function computes the next step of a random walk. 
  9 | #' 
 10 | #' @param df A data frame containing at least the following columns: x (x 
 11 | #'  coordinates of each individual), y (y coordinates of each individual), h 
 12 | #'  (heading in radians of each individual), s (the speed of each individual).
 13 | #' 
 14 | #' @return A data frame of the same dimensions as \code{df}.
 15 | #' 
 16 | #' @author Simon Garnier: \email{garnier@@njit.edu}, 
 17 | #'  \link[https://twitter.com/sjmgarnier]{@@sjmgarnier}
 18 | #' 
 19 | rw <- function(df) {
 20 |   n <- nrow(df)
 21 |   
 22 |   within(df, {
 23 |     h <- h + rnorm(n, sd = pi / 6)
 24 |     x <- x + s * cos(h)
 25 |     y <- y + s * sin(h)
 26 |     
 27 |     h[x < -1] <- 0
 28 |     h[x > 1] <- pi
 29 |     h[y < -1] <- pi / 2
 30 |     h[y > 1] <- -pi / 2
 31 |   })
 32 | }
 33 | 
 34 | 
 35 | #' @title Sigmoid Curve
 36 | #' 
 37 | #' @description This function computes a fully customizable sigmoid function. 
 38 | #' 
 39 | #' @param x The x coordinates at which to compute the sigmoid values.
 40 | #' @param a The sigmoid minimum value.
 41 | #' @param k The sigmoid maximum value. 
 42 | #' @param b The growth rate of the sigmoid. 
 43 | #' @param m The position of the inflection point of the sigmoid. 
 44 | #' 
 45 | #' @return A vector of the same length as \code{x}.
 46 | #' 
 47 | #' @author Simon Garnier: \email{garnier@@njit.edu}, 
 48 | #'  \link[https://twitter.com/sjmgarnier]{@@sjmgarnier}
 49 | #'
 50 | sigmoid <- function(x, a = 0, k = 1, b = 0.1, m = 100) {
 51 |   a + (k - a) / ((1 + exp(-b * (x - m))))
 52 | }
 53 | 
 54 | 
 55 | #' @title Pairwise Distances
 56 | #' 
 57 | #' @description This function computes the pairwise distances between two series
 58 | #'  of points. 
 59 | #' 
 60 | #' @param A A matrix for which the number of rows corresponds to the number of 
 61 | #'  points and the number of colums corresponds to the number of dimensions in 
 62 | #'  which these points are defined.
 63 | #' @param B Same as \code{A}. In addition \code{B} must have the same number of 
 64 | #'  columns as \code{A}.
 65 | #' 
 66 | #' @return A matrix of the pairwise distances between the points in A (along the 
 67 | #'  rows) and B (along the columns).
 68 | #' 
 69 | #' @author Simon Garnier: \email{garnier@@njit.edu}, 
 70 | #'  \link[https://twitter.com/sjmgarnier]{@@sjmgarnier}
 71 | #'
 72 | pdist <- function(A, B) {
 73 |   if (ncol(A) != ncol(B)) {
 74 |     stop("A and B should have the same number of columns.")
 75 |   }
 76 |   
 77 |   an = apply(A, 1, function(rvec) crossprod(rvec,rvec))
 78 |   bn = apply(B, 1, function(rvec) crossprod(rvec,rvec))
 79 |   
 80 |   m = nrow(A)
 81 |   n = nrow(B)
 82 |   
 83 |   tmp = matrix(rep(an, n), nrow = m) 
 84 |   tmp = tmp +  matrix(rep(bn, m), nrow = m, byrow = TRUE)
 85 |   sqrt( tmp - 2 * tcrossprod(A,B) )
 86 | }
 87 | 
 88 | 
 89 | #' @title Speed Adjustment 
 90 | #' 
 91 | #' @description This function adjusts the speed of individuals based on the 
 92 | #'  local neighborhood. 
 93 | #' 
 94 | #' @param df A data frame containing at least the following columns: x (x 
 95 | #'  coordinates of each individual), y (y coordinates of each individual), h 
 96 | #'  (heading in radians of each individual), s (the speed of each individual).
 97 | #' @param affinSame The degree of affinity of an individual for other 
 98 | #'  individuals of the same class (-1: repulsion; 1: attraction).
 99 | #' @param affinOther The degree of affinity of an individual for other 
100 | #'  individuals of a different class (-1: repulsion; 1: attraction). 
101 | #' 
102 | #' @return A data frame of the same dimensions as \code{df}.
103 | #' 
104 | #' @author Simon Garnier: \email{garnier@@njit.edu}, 
105 | #'  \link[https://twitter.com/sjmgarnier]{@@sjmgarnier}
106 | #'
107 | sp <- function(df, affinSame = 0, affinOther = 0) {
108 |   dist <- pdist(as.matrix(df[, 1:2]), as.matrix(df[, 1:2]))
109 |   neighbor <- dist < 0.125
110 |   b_neighbor <- apply(df$col == "#107AB6" & neighbor, 2, sum) - (df$col == "#107AB6")
111 |   r_neighbor <- apply(df$col == "#D86810" & neighbor, 2, sum) - (df$col == "#D86810")
112 |   
113 |   nb <- (df$col == "#107AB6") * affinSame * b_neighbor + 
114 |     (df$col == "#D86810") * affinSame * r_neighbor + 
115 |     (df$col == "#107AB6") * affinOther * r_neighbor + 
116 |     (df$col == "#D86810") * affinOther * b_neighbor
117 |   
118 |   df$s <- sigmoid(nb, k = 0.1, m = 4, b = -1)
119 |   df
120 | }
121 | 
122 | 
123 | ### DEFINE GLOBAL VARIABLES ###
124 | pop <- NULL
125 | run <- FALSE
126 | 


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/inst/apps/aggregation_segregation/info:
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 1 | Title: Self-organized aggregation and segregation
 2 | Version: 0.1
 3 | Date: 2015-05-13
 4 | Author: Simon Garnier
 5 | Maintainer: Simon Garnier 
 6 | Description: This app illustrates the principle of self-organized aggregation and segregation.
 7 | Category: Biology, Social Science
 8 | Keywords: Aggregation, Segregation, Self-Organization
 9 | License: GPL (>= 3)
10 | Depends: dplyr (>= 0.4.1), ggvis (>= 0.4.3)
11 | Command: aggregation_segregation


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/inst/apps/aggregation_segregation/server.R:
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 1 | shinyServer(function(input, output, session) {
 2 |   
 3 |   react <- reactiveValues(count = 0)
 4 |   
 5 |   observe({
 6 |     input$reset
 7 |     isolate({
 8 |       pop <<- data.frame(x = runif(input$nIndiv, min = -1, max = 1),
 9 |                          y = runif(input$nIndiv, min = -1, max = 1),
10 |                          h = runif(input$nIndiv, min = -pi, max = pi),
11 |                          s = 0.01, 
12 |                          col = sample(c("#107AB6", "#D86810"), input$nIndiv, replace = TRUE))
13 |     })
14 |     react$count <- 0
15 |   })
16 |   
17 |   locs <- reactive({
18 |     invalidateLater(60, NULL)
19 |     
20 |     if (is.null(pop)) {
21 |       return()
22 |     }
23 |     
24 |     if (run) {
25 |       isolate({
26 |         pop <<- sp(pop, input$affinSame, input$affinOther)
27 |         pop <<- rw(pop)
28 |         react$count <- react$count + 1
29 |       })
30 |     }
31 |     
32 |     pop
33 |   })
34 |   
35 |   observe({
36 |     if (input$start > 0) {
37 |       run <<- TRUE
38 |     }
39 |   })
40 |   
41 |   observe({
42 |     if (input$stop > 0) {
43 |       run <<- FALSE
44 |     }
45 |   })
46 |   
47 |   output$count <- renderText({
48 |     react$count
49 |   })
50 |   
51 |   observe({
52 |     if (is.null(locs)) {
53 |       return()
54 |     } 
55 |     
56 |     locs %>%
57 |       ggvis(x = ~x, y = ~y) %>%
58 |       layer_points(fill := ~col) %>%
59 |       scale_numeric("x", domain = c(-1, 1)) %>%
60 |       scale_numeric("y", domain = c(-1, 1)) %>%
61 |       add_axis("x", title = "", properties = axis_props(labels = list(fontSize = 0))) %>%
62 |       add_axis("x", title = "", properties = axis_props(labels = list(fontSize = 0)), orient = "top") %>%
63 |       add_axis("y", title = "", properties = axis_props(labels = list(fontSize = 0))) %>%
64 |       add_axis("y", title = "", properties = axis_props(labels = list(fontSize = 0)), orient = "right") %>%
65 |       set_options(width = "auto", height = "100%", resizable = FALSE, 
66 |                   duration = 30) %>%
67 |       bind_shiny("display")
68 |   })
69 | })
70 | 
71 | 


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/inst/apps/aggregation_segregation/ui.R:
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  1 | shinyUI(
  2 |   navbarPage(
  3 |     title = "Aggregation, segregation",
  4 |     theme = shinytheme("cosmo"),
  5 |     fluid = FALSE,
  6 |     collapsible = TRUE,
  7 |     
  8 |     tabPanel("Model",
  9 |              
 10 |              includeCSS("www/custom.css"),
 11 |              
 12 |              # Sidebar
 13 |              sidebarLayout(
 14 |                sidebarPanel(
 15 |                  width = 3, 
 16 |                  
 17 |                  sliderInput("nIndiv", "Number of individuals", 
 18 |                              min = 2, max = 500, value = 200), 
 19 |                  
 20 |                  tags$hr(),
 21 |                  
 22 |                  sliderInput("affinSame", "Affinity with same color", 
 23 |                              min = -1, max = 1, value = 0, step = 0.1),
 24 |                  
 25 |                  tags$hr(),
 26 |                  
 27 |                  sliderInput("affinOther", "Affinity with different color", 
 28 |                              min = -1, max = 1, value = 0, step = 0.1),
 29 |                  
 30 |                  tags$hr(),
 31 |                  
 32 |                  actionButton("start", "Start", style = "border: 2px solid; border-color: green; background-color: green;"),
 33 |                  actionButton("stop", "Stop", style = "border: 2px solid; border-color: red; background-color: red;"),
 34 |                  actionButton("reset", "Reset", style = "border: 2px solid; border-color: black;"),
 35 |                  
 36 |                  tags$hr(),
 37 |                  
 38 |                  tags$p("Step:", textOutput("count", inline = TRUE)),
 39 |                  
 40 |                  tags$hr()
 41 |                  
 42 |                ),
 43 |                
 44 |                # Main panel
 45 |                mainPanel(
 46 |                  fluidRow(
 47 |                    ggvisOutput("display")
 48 |                  )
 49 |                )
 50 |              )
 51 |     ),
 52 |     
 53 |     tabPanel("Instructions",
 54 |              
 55 |              fluidRow(
 56 |                tags$hr(),
 57 |                
 58 |                h2("Goal"),
 59 |                
 60 |                p("This webapp simulates a simple aggregation mechanism."),
 61 |                
 62 |                p("In the absence of interaction, each individual particle moves 
 63 |                  randomly at maximum speed. When two particles move close to 
 64 |                  each other, they slow down if they have a positive affinity for 
 65 |                  each other, or accelerate if they have a negative affinity for 
 66 |                  each other. The amount of deceleration (resp. acceleration)
 67 |                  depends on the strength of the affinity and the number of 
 68 |                  particles within the interaction range of each particle."),
 69 |                
 70 |                tags$hr(),
 71 |                
 72 |                h2("Parameters"),
 73 |                
 74 |                p("This simulation takes 3 parameters that you can modify using 
 75 |                  the sliders in the 'Model' tab."),
 76 |                
 77 |                tags$ol(
 78 |                  tags$li(tags$b("Number of individuals: "), "this sets the number 
 79 |                          of particles in the simulation. Change this value to 
 80 |                          observe the effect of the particles' density on their 
 81 |                          aggregation behavior. The new value will not be taken 
 82 |                          into account unless you hit the 'Reset' button."), 
 83 |                  tags$li(tags$b("Affinity with same color: "), "this determines 
 84 |                          the level of affinity between particles of the same
 85 |                          color. This parameter can be changed while the 
 86 |                          simulation is running."), 
 87 |                  tags$li(tags$b("Affinity with different color: "), "this determines 
 88 |                          the level of affinity between particles of different
 89 |                          colors. This parameter can be changed while the 
 90 |                          simulation is running.")
 91 |                  ),
 92 |                
 93 |                p("Use the 'Start' and 'Stop' buttons to run or pause the 
 94 |                  simulation. The 'Reset' button will disperse the particles 
 95 |                  randomly and update their number - if the corresponding 
 96 |                  parameter has been modified."),
 97 |                
 98 |                tags$hr(),
 99 |                
100 |                h2("Outputs"),
101 |                
102 |                p("This simulation returns an animated graph representing the XY 
103 |                  positions of the particles."),
104 |                
105 |                tags$hr()
106 |              )
107 |     ),
108 |     
109 |     tabPanel("About",
110 |              
111 |              fluidRow(
112 |                tags$hr(),
113 |                
114 |                p(strong("Author:"), " Simon Garnier (", a("New Jersey Institute of Technology",
115 |                                                           href = "http://www.njit.edu",
116 |                                                           target = "_blank"), ")"),
117 |                
118 |                p(strong("Twitter:"), a("@sjmgarnier", 
119 |                                        href = "https://twitter.com/sjmgarnier",
120 |                                        target = "_blank")),
121 |                
122 |                p(strong("Website:"), a("http://www.theswarmlab.com", 
123 |                                        href = "http://www.theswarmlab.com",
124 |                                        target = "_blank")),
125 |                
126 |                p(strong("Source code:"), 
127 |                  a("GitHub",
128 |                    href = "https://github.com/swarm-lab/teachR/tree/master/inst/apps/aggregation_segregation",
129 |                    target = "_blank")),
130 |                
131 |                p(strong("Created with:"), 
132 |                  a("RStudio",
133 |                    href = "http://www.rstudio.com/",
134 |                    target = "_blank"), 
135 |                  " and ",
136 |                  a("Shiny.",
137 |                    href = "http://shiny.rstudio.com",
138 |                    target = "_blank")),
139 |                
140 |                p(strong("License:"), 
141 |                  a("GPL v3",
142 |                    href = "http://www.gnu.org/copyleft/gpl.html",
143 |                    target = "_blank")),
144 |                
145 |                tags$hr()
146 |              )
147 |     ),
148 |     
149 |     tabPanel(tagList(tags$html("Powered by"),
150 |                      tags$img(src = "white-rstudio-logo.png",
151 |                               height = "20")),
152 |              value = "RStudio",
153 |              tags$head(tags$script(src = "actions.js"))
154 |     )    
155 |   )
156 | )
157 | 
158 | 


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/inst/apps/aggregation_segregation/www/actions.js:
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 1 | $(document).ready(function() {
 2 |   
 3 |   jQuery(function($){
 4 |     $("a[data-value='RStudio']").attr("href", "http://www.rstudio.com");
 5 |     $("a[data-value='RStudio']").attr("data-toggle", "");
 6 |   });
 7 |   
 8 | });
 9 | 
10 | 
11 | 
12 | 
13 | 
14 | 


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/inst/apps/aggregation_segregation/www/custom.css:
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/inst/apps/aggregation_segregation/www/white-rstudio-logo.png:
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/inst/apps/ant_collective_decision/global.R:
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 1 | #### LOAD LIBRARIES #### 
 2 | pacman::p_load(shiny, shinythemes, deSolve, dplyr, plotly)
 3 | 
 4 | 
 5 | #### DEFINE CUSTOM FUNCTIONS ####
 6 | #' @title ODE System
 7 | #' 
 8 | #' @description This function represents the ODE system to simulate the 
 9 | #'  collective selection of a food source by ant colonies.  
10 | #' 
11 | #' @param t The time step to compute the ODE at.
12 | #' @param y The values of the state variables of the ODE at the time step: 
13 | #'  number of ants at the nest (N) and at each food source (S1...Sn), quantity 
14 | #'  of pheromone on the routes to each food source (Q1...Qn).
15 | #' @param parms Parameters of the ODE system:
16 | #'  \itemize{
17 | #'   \item l: Distance to each food source in seconds.
18 | #'   \item q: Quantity of pheromone deposited by the ants on the way back from 
19 | #'    each food source.
20 | #'   \item qe: Quantity of pheromone deposited by the ants on the way to the 
21 | #'    food sources.
22 | #'   \item alpha, beta, gamma, eta: Regulates recruitment at the nest as a 
23 | #'    function of the quantity of pheromone at the nest entrance.
24 | #'   \item psi: Probability for an ant to leave the food source.
25 | #'   \item rho: Rate of evaporation of the pheromone.
26 | #'   \item k: Intrinsic attractiveness of each route.
27 | #'   \item n: Degree of nonlinearity.
28 | #'  }
29 | #' 
30 | #' @return A list of the changes in \code{y} suitable for \code{\link{dede}} 
31 | #'  function. 
32 | #' 
33 | #' @author Simon Garnier: \email{garnier@@njit.edu}, 
34 | #'  \link[https://twitter.com/sjmgarnier]{@@sjmgarnier}
35 | #' 
36 | ode_sys <- function(t, y, parms) {
37 |   nS <- length(parms$l)
38 |   
39 |   Q <- sum(y[(nS + 2):(2 * nS + 1)])
40 |   phi <- (parms$alpha * (parms$beta + Q) ^ parms$eta) / ((parms$beta + Q) ^ parms$eta + parms$gamma)
41 |   
42 |   dN <- -phi*y[1]
43 |   dS <- rep(0,nS)
44 |   dQ <- rep(0,nS)
45 |   
46 |   ylag <- {}
47 |   
48 |   for (i in 1:nS) {
49 |     if (t < parms$l[i]) {
50 |       ylag <- c(parms$iniN, parms$iniS, parms$iniQ)
51 |       Qlag <- 0
52 |       philag <- 0
53 |     } else {
54 |       ylag <- lagvalue(t - parms$l[i])
55 |       Qlag <- sum(ylag[(nS + 2):(2 * nS + 1)])
56 |       philag <- (parms$alpha * (parms$beta + Qlag) ^ parms$eta) / ((parms$beta + Qlag) ^ parms$eta + parms$gamma)
57 |     }
58 |     
59 |     P <- ((parms$k[i] + y[i + nS + 1]) ^ parms$n) / sum((parms$k + y[(nS + 2):(2 * nS + 1)]) ^ parms$n)
60 |     Plag <- ((parms$k[i] + ylag[i + nS + 1]) ^ parms$n) / sum((parms$k + ylag[(nS + 2):(2 * nS + 1)]) ^ parms$n)
61 |     
62 |     dN <- dN + parms$psi*ylag[i + 1]
63 |     
64 |     dS[i] <- -parms$psi*y[i + 1] + philag * ylag[1] * Plag
65 |     
66 |     dQ[i] <- parms$qe * P * phi * y[1] + parms$q[i] * parms$psi * ylag[i + 1] - parms$rho * y[i + nS + 1]
67 |     
68 |   }
69 |   
70 |   return(list(c(dN, dS, dQ)))
71 | }
72 | 


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/inst/apps/ant_collective_decision/info:
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 1 | Title: Collective food source selection in ants. 
 2 | Version: 0.1
 3 | Date: 2015-05-13
 4 | Author: Simon Garnier
 5 | Maintainer: Simon Garnier 
 6 | Description: This app illustrates the principle of collective decision-making in ants.
 7 | Category: Biology
 8 | Keywords: Ants, Decision-making, Self-Organization
 9 | License: GPL (>= 3)
10 | Depends: dplyr (>= 0.4.1), plotly (>= 4.5.6), deSolve (>= 1.11)
11 | Command: ant_collective_decision


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/inst/apps/ant_collective_decision/server.R:
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 1 | shinyServer(function(input, output) {
 2 |   
 3 |   res <- reactive({
 4 |     parms <- list(iniN = input$N, 
 5 |                   iniS = rep(0,2), 
 6 |                   iniQ = rep(0,2), 
 7 |                   l = c(input$l1, input$l2), 
 8 |                   q = c(input$q1, input$q2), 
 9 |                   qe = 0, 
10 |                   alpha = 0.01, 
11 |                   beta = 5, 
12 |                   gamma = 1200, 
13 |                   eta = 2, 
14 |                   psi = 0.05, 
15 |                   rho = 0.01, 
16 |                   k = c(100 - input$k1 + 1, 100 - input$k2 + 1), 
17 |                   n = 2)
18 |     
19 |     out <- dede(c(N = parms$iniN, S = parms$iniS, Q = parms$iniQ), 
20 |                 seq(0, 3600, length.out = 360), 
21 |                 ode_sys, 
22 |                 parms)
23 |     
24 |     data.frame(time = rep(out[, 1], 2), 
25 |                S = c(rep("Source 1", nrow(out)), rep("Source 2", nrow(out))),
26 |                val = c(out[, 3], out[, 4]))
27 |   })
28 |   
29 |   output$the_display <- renderPlotly({
30 |     g <- ggplot(data = res(), aes(x = time, y = val, color = S)) +
31 |       geom_path(size = 0.75) +
32 |       theme_minimal(base_size = 16) +
33 |       theme(legend.title = element_blank()) +
34 |       xlab("Time") + ylab("Number of ants") +
35 |       scale_color_manual(values = c("#2678B2", "#FD7F28"))
36 |     
37 |     ggplotly(g) %>%
38 |       layout(legend = list(x = 0.5, y = 1.1, orientation = "h", xanchor = "center"),
39 |              hovermode = "x")
40 |   })
41 |   
42 | })
43 | 


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/inst/apps/ant_collective_decision/ui.R:
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  1 | shinyUI(
  2 |   navbarPage(
  3 |     title = "Collective food source selection in ants",
  4 |     theme = shinytheme("cosmo"),
  5 |     fluid = FALSE,
  6 |     collapsible = TRUE,
  7 |     
  8 |     tabPanel("Model",
  9 |              
 10 |              includeCSS("www/custom.css"),
 11 |              
 12 |              # Sidebar
 13 |              sidebarLayout(
 14 |                sidebarPanel(
 15 |                  width = 3, 
 16 |                  
 17 |                  h4(tags$b("Source #1")),
 18 |                  sliderInput('l1', 'Distance:', ticks = FALSE,
 19 |                              min = 0, max = 100, value = 20, step = 1, width = "100%"),
 20 |                  sliderInput('q1', 'Quality:', ticks = FALSE,
 21 |                              min = 0, max = 2, value = 1, step = 0.01, width = "100%"),
 22 |                  sliderInput('k1', 'Light intensity:', ticks = FALSE,
 23 |                              min = 0, max = 100, value = 20, step = 1, width = "100%"),
 24 |                  
 25 |                  hr(),
 26 |                  
 27 |                  h4(tags$b("Source #2")),
 28 |                  sliderInput('l2', 'Distance:', ticks = FALSE,
 29 |                              min = 0, max = 100, value = 25, step = 1, width = "100%"),
 30 |                  sliderInput('q2', 'Quality:', ticks = FALSE,
 31 |                              min = 0, max = 2, value = 1, step = 0.01, width = "100%"),
 32 |                  sliderInput('k2', 'Light intensity:', ticks = FALSE,
 33 |                              min = 0, max = 100, value = 20, step = 1, width = "100%")
 34 |                ),
 35 |                
 36 |                # Main panel
 37 |                mainPanel(
 38 |                  fluidRow(
 39 |                    id = "the_display_row",
 40 |                    column(12, plotlyOutput("the_display", height = "100%"))
 41 |                  ),
 42 |                  
 43 |                  fluidRow(
 44 |                    column(12, 
 45 |                           sliderInput('N', 'Number of ants in the colony:', 
 46 |                                       min = 0, max = 5000, value = 1000, step = 10, width = "100%")
 47 |                    )
 48 |                  )
 49 |                )
 50 |              )
 51 |     ),
 52 |     
 53 |     tabPanel("Instructions",
 54 |              
 55 |              fluidRow(
 56 |                tags$hr(),
 57 |                
 58 |                h2("Goal"),
 59 |                
 60 |                p("This webapp simulates the collective decision-making mechanism
 61 |                  of mass-recruiting ant colonies."),
 62 |                
 63 |                p("The underlying model is a system of differential equations 
 64 |                  directly inspired from the work of Jean-Louis Deneubourg and 
 65 |                  his collaborators during the 1980's and 1990's. Hereafter are a 
 66 |                  couple relevant publications regarding the equations that served 
 67 |                  as a basis for this simulation:"),
 68 |                
 69 |                tags$ol(
 70 |                  tags$li(
 71 |                    tags$a(href = "http://doi.org/10.1007/BF00462870",
 72 |                           "Goss, S., Aron, S., Deneubourg, J. L., & Pasteels, 
 73 |                           J. M. (1989). Self-organized shortcuts in the Argentine 
 74 |                           ant. Die Naturwissenschaften, 76(12), 579–581.")), 
 75 |                  tags$li(
 76 |                    tags$a(href = "http://doi.org/10.1007/BF02224053",
 77 |                           "Beckers, R., Deneubourg, J.-L., Goss, S., & Pasteels, 
 78 |                           J. M. (1990). Collective decision making through food 
 79 |                           recruitment. Insectes Sociaux, 37(3), 258–267."))
 80 |                ),
 81 |                
 82 |                tags$hr(),
 83 |                
 84 |                h2("Parameters"),
 85 |                
 86 |                p("This simulation takes 4 parameters that you can modify using 
 87 |                  the sliders in the 'Model' tab."),
 88 |                
 89 |                tags$ol(
 90 |                  tags$li(tags$b("Number of ants in the colony: "), "this sets the 
 91 |                          total number of ants in the colony. Change this value to
 92 |                          observe the effect of colony size on the speed and
 93 |                          strength of the collective decision."), 
 94 |                  tags$li(tags$b("Distance: "), "this determines the distance in 
 95 |                          centimeters of the corresponding food source to the nest. 
 96 |                          The larger this value, the longer it will take ants to 
 97 |                          reach the food source and come back to the nest, and 
 98 |                          hence the longer it will take them to reinforce the 
 99 |                          pheromeone trail in between."), 
100 |                  tags$li(tags$b("Quality: "), "this determines the sugar 
101 |                          concentration in molar of the corresponding food source.
102 |                          Larger values indicates a more beneficial food source. 
103 |                          Ants lay more pheromone on their trails when coming 
104 |                          back from rich food sources than from poor ones."),
105 |                  tags$li(tags$b("Light intensity: "), "this determines how 
106 |                          exposed to light is the path between the nest and a food
107 |                          source. Light is repellent for ants that prefer to walk
108 |                          along less exposed paths (most likely to reduce risks 
109 |                          of predation or dessication). Higher values of this 
110 |                          parameter indicate a more exposed path, and therefore a
111 |                          less attractive path.")
112 |                ),
113 |                
114 |                tags$hr(),
115 |                
116 |                h2("Outputs"),
117 |                
118 |                p("This simulation returns a graph representing the number of ants
119 |                  at each food source (blue: source 1; orange: source 2) as a 
120 |                  function of time (total time: 1 hour)."),
121 |                
122 |                tags$hr()
123 |              )
124 |     ),
125 |     
126 |     tabPanel("About",
127 |              
128 |              fluidRow(
129 |                tags$hr(),
130 |                
131 |                p(strong("Author:"), " Simon Garnier (", a("New Jersey Institute of Technology",
132 |                                                           href = "http://www.njit.edu",
133 |                                                           target = "_blank"), ")"),
134 |                
135 |                p(strong("Twitter:"), a("@sjmgarnier", 
136 |                                        href = "https://twitter.com/sjmgarnier",
137 |                                        target = "_blank")),
138 |                
139 |                p(strong("Website:"), a("http://www.theswarmlab.com", 
140 |                                        href = "http://www.theswarmlab.com",
141 |                                        target = "_blank")),
142 |                
143 |                p(strong("Source code:"), 
144 |                  a("GitHub",
145 |                    href = "https://github.com/swarm-lab/teachR/tree/master/inst/apps/ant_collective_decision",
146 |                    target = "_blank")),
147 |                
148 |                p(strong("Created with:"), 
149 |                  a("RStudio",
150 |                    href = "http://www.rstudio.com/",
151 |                    target = "_blank"), 
152 |                  " and ",
153 |                  a("Shiny.",
154 |                    href = "http://shiny.rstudio.com",
155 |                    target = "_blank")),
156 |                
157 |                p(strong("License:"), 
158 |                  a("GPL v3",
159 |                    href = "http://www.gnu.org/copyleft/gpl.html",
160 |                    target = "_blank")),
161 |                
162 |                tags$hr()
163 |              )
164 |     ),
165 |     
166 |     tabPanel(tagList(tags$html("Powered by"),
167 |                      tags$img(src = "white-rstudio-logo.png",
168 |                               height = "20")),
169 |              value = "RStudio",
170 |              tags$head(tags$script(src = "actions.js"))
171 |     )    
172 |   )
173 | )
174 | 
175 | 
176 | 


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/inst/apps/ant_collective_decision/www/actions.js:
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 1 | $(document).ready(function() {
 2 |   
 3 |   jQuery(function($){
 4 |     $("a[data-value='RStudio']").attr("href", "http://www.rstudio.com");
 5 |     $("a[data-value='RStudio']").attr("data-toggle", "");
 6 |   });
 7 |   
 8 | });
 9 | 
10 | 
11 | 
12 | 
13 | 
14 | 


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/inst/apps/ant_collective_decision/www/custom.css:
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/inst/apps/axelrod/info:
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 1 | Title: Opinion dynamics. 
 2 | Version: 0.1
 3 | Date: 2015-05-13
 4 | Author: Simon Garnier
 5 | Maintainer: Simon Garnier 
 6 | Description: This app illustrates the spreading of two competing opinions in an originally uniform population.
 7 | Category: Biology, Social Science
 8 | Keywords: Opinion dynamics
 9 | License: GPL (>= 3)
10 | Depends: ggplot2 (>= 1.0.1), grid (>= 3.2.1), gridExtra (>= 2.0.0), dplyr (>= 0.4.2), scales (>= 0.2.5), simecol (>= 0.8-6), grip
11 | Command: opinion_dynamics


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/inst/apps/axelrod/www/actions.js:
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 1 | $(document).ready(function() {
 2 |   
 3 |   jQuery(function($){
 4 |     $("a[data-value='RStudio']").attr("href", "http://www.rstudio.com");
 5 |     $("a[data-value='RStudio']").attr("data-toggle", "");
 6 |   });
 7 |   
 8 | });
 9 | 
10 | 
11 | 
12 | 
13 | 
14 | 


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/inst/apps/bee_house_hunting/global.R:
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 1 | #### LOAD LIBRARIES #### 
 2 | pacman::p_load(shiny, shinythemes, deSolve, plotly, dplyr)
 3 | 
 4 | 
 5 | #### DEFINE CUSTOM FUNCTIONS ####
 6 | #' @title ODE System
 7 | #' 
 8 | #' @description This function represents the ODE system to simulate the 
 9 | #'  collective selection of a nest by honeybee colonies.  
10 | #' 
11 | #' @param t The time step to compute the ODE at.
12 | #' @param y The values of the state variables of the ODE at the time step.
13 | #' @param parms Parameters of the ODE system.
14 | #' 
15 | #' @return A list of the changes in \code{y} suitable for \code{\link{dede}} 
16 | #'  function. 
17 | #' 
18 | #' @author Simon Garnier: \email{garnier@@njit.edu}, 
19 | #'  \link[https://twitter.com/sjmgarnier]{@@sjmgarnier}
20 | #' 
21 | ode_sys <- function(t, y, parms) {
22 |   yu <- 1 - sum(y)
23 |   
24 |   dy <- rep(0, 3)
25 |   
26 |   for (i in 1:3) {
27 |     if (i == 3 & t < parms$theta) {
28 |       dy[i] <- 0
29 |     } else {
30 |       idx <- which(1:length(dy) != i)
31 |       
32 |       dy[i] <-  yu * parms$gamma[i] + 
33 |         y[i] * yu * parms$rho[i] - 
34 |         y[i] * parms$alpha[i] - 
35 |         y[i] * sum(parms$sigma[idx] * y[idx])
36 |     }
37 |   }
38 |   
39 |   list(dy)
40 | }
41 | 


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/inst/apps/bee_house_hunting/info:
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 1 | Title: "House hunting" in honeybees. 
 2 | Version: 0.1
 3 | Date: 2015-05-13
 4 | Author: Simon Garnier
 5 | Maintainer: Simon Garnier 
 6 | Description: This app illustrates the principle of collective nest selection in honeybees.
 7 | Category: Biology
 8 | Keywords: Honeybees, Decision-making, Self-Organization
 9 | License: GPL (>= 3)
10 | Depends: dplyr (>= 0.4.1), plotly (>= 4.5.6), deSolve (>= 1.11)
11 | Command: bee_house_hunting


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/inst/apps/bee_house_hunting/server.R:
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 1 | shinyServer(function(input, output) {
 2 |   
 3 |   res <- reactive({
 4 |     parms <- list(gamma = c(input$gamma1, input$gamma2, input$gamma3),  # discovery rate
 5 |                   alpha = c(input$alpha1, input$alpha2, input$alpha3),  # spontaneous uncommitment 
 6 |                   rho = c(input$rho1, input$rho2, input$rho3),          # recruitment rate 
 7 |                   sigma = c(input$sigma1, input$sigma2, input$sigma3),  # conversion rate
 8 |                   theta = input$theta)                                  # time at which 3rd nest is introduced
 9 |     
10 |     tmp <- lsoda(c(0, 0, 0), seq(0, input$duration, 0.05), ode_sys, parms)
11 |     tmp[, 2:4] <- tmp[, 2:4] * input$scouts
12 |     out <- data.frame(time = rep(tmp[, 1], 3),
13 |                       nest = rep(c("Nest 1", "Nest 2", "Nest 3"), each = nrow(tmp)),
14 |                       val = c(tmp[, 2], tmp[, 3], tmp[, 4]))
15 |     out
16 |   })
17 |   
18 |   output$the_display <- renderPlotly({
19 |     g <- ggplot(data = res(), aes(x = time, y = val, color = nest)) +
20 |       geom_path(size = 0.75) +
21 |       geom_hline(yintercept = input$quorum, size = 0.5, linetype = 2) +
22 |       theme_minimal(base_size = 16) +
23 |       theme(legend.title = element_blank()) +
24 |       xlab("Time") + ylab("Number of committed scouts") +
25 |       scale_color_manual(values = c("#2678B2", "#FD7F28", "#339734"))
26 |     
27 |     ggplotly(g) %>%
28 |       layout(legend = list(x = 0.5, y = 1.1, orientation = "h", xanchor = "center"),
29 |              hovermode = "x")
30 |   })
31 |   
32 | })
33 | 


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/inst/apps/bee_house_hunting/ui.R:
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  1 | shinyUI(
  2 |   navbarPage(
  3 |     title = "\"House hunting\" in honeybees",
  4 |     theme = shinytheme("cosmo"),
  5 |     fluid = FALSE,
  6 |     collapsible = TRUE,
  7 |     
  8 |     tabPanel("Model",
  9 |              
 10 |              includeCSS("www/custom.css"),
 11 |              
 12 |              # Sidebar
 13 |              sidebarLayout(
 14 |                sidebarPanel(
 15 |                  width = 3, 
 16 |                  
 17 |                  sliderInput("duration", "Duration of the trial:",
 18 |                              min = 1, max = 200, value = 200, width = "100%"),
 19 |                  sliderInput("scouts", "Number of scouts:",
 20 |                              min = 1, max = 200, value = 100, width = "100%"),
 21 |                  sliderInput("quorum", "Quorum number:",
 22 |                              min = 1, max = 200, value = 25, width = "100%"),
 23 |                  sliderInput("theta", "Time to introduce a 3rd nest:",
 24 |                              min = 1, max = 200, value = 100, width = "100%")
 25 |                ),
 26 |                
 27 |                # Main panel
 28 |                mainPanel(
 29 |                  fluidRow(
 30 |                    id = "the_display_row",
 31 |                    column(12, plotlyOutput("the_display", height = "100%"))
 32 |                  ),
 33 |                  
 34 |                  fluidRow(
 35 |                    column(4,
 36 |                           wellPanel(h5("Nest #1"),
 37 |                                     sliderInput("gamma1", "Discovery rate:",
 38 |                                                 min = 0, max = 10, value = 1.5, step = 0.1),
 39 |                                     sliderInput("alpha1", "Desertion rate:",
 40 |                                                 min = 0, max = 10, value = 1, step = 0.1),
 41 |                                     sliderInput("rho1", "Recruitment rate:",
 42 |                                                 min = 0, max = 10, value = 2, step = 0.1),
 43 |                                     sliderInput("sigma1", "Deconversion rate:",
 44 |                                                 min = 0, max = 10, value = 2, step = 0.1))
 45 |                    ),
 46 |                    column(4,
 47 |                           wellPanel(h5("Nest #2"),
 48 |                                     sliderInput("gamma2", "Discovery rate:",
 49 |                                                 min = 0, max = 10, value = 2, step = 0.1),
 50 |                                     sliderInput("alpha2", "Desertion rate:",
 51 |                                                 min = 0, max = 10, value = 1.5, step = 0.1),
 52 |                                     sliderInput("rho2", "Recruitment rate:",
 53 |                                                 min = 0, max = 10, value = 2, step = 0.1),
 54 |                                     sliderInput("sigma2", "Deconversion rate:",
 55 |                                                 min = 0, max = 10, value = 2, step = 0.1))
 56 |                    ),
 57 |                    column(4,
 58 |                           wellPanel(h5("Nest #3"),
 59 |                                     sliderInput("gamma3", "Discovery rate:",
 60 |                                                 min = 0, max = 10, value = 2, step = 0.1),
 61 |                                     sliderInput("alpha3", "Desertion rate:",
 62 |                                                 min = 0, max = 10, value = 1, step = 0.1),
 63 |                                     sliderInput("rho3", "Recruitment rate:",
 64 |                                                 min = 0, max = 10, value = 2, step = 0.1),
 65 |                                     sliderInput("sigma3", "Deconversion rate:",
 66 |                                                 min = 0, max = 10, value = 2, step = 0.1))
 67 |                    )
 68 |                  )
 69 |                )
 70 |              )
 71 |     ),
 72 |     
 73 |     tabPanel("Instructions"),
 74 |     
 75 |     tabPanel("About",
 76 |              
 77 |              fluidRow(
 78 |                tags$hr(),
 79 |                
 80 |                p(strong("Author:"), " Simon Garnier (", a("New Jersey Institute of Technology",
 81 |                                                           href = "http://www.njit.edu",
 82 |                                                           target = "_blank"), ")"),
 83 |                
 84 |                p(strong("Twitter:"), a("@sjmgarnier", 
 85 |                                        href = "https://twitter.com/sjmgarnier",
 86 |                                        target = "_blank")),
 87 |                
 88 |                p(strong("Website:"), a("http://www.theswarmlab.com", 
 89 |                                        href = "http://www.theswarmlab.com",
 90 |                                        target = "_blank")),
 91 |                
 92 |                p(strong("Source code:"), 
 93 |                  a("GitHub",
 94 |                    href = "https://github.com/swarm-lab/teachR/tree/master/inst/apps/bee_house_hunting",
 95 |                    target = "_blank")),
 96 |                
 97 |                p(strong("Created with:"), 
 98 |                  a("RStudio",
 99 |                    href = "http://www.rstudio.com/",
100 |                    target = "_blank"), 
101 |                  " and ",
102 |                  a("Shiny.",
103 |                    href = "http://shiny.rstudio.com",
104 |                    target = "_blank")),
105 |                
106 |                p(strong("License:"), 
107 |                  a("GPL v3",
108 |                    href = "http://www.gnu.org/copyleft/gpl.html",
109 |                    target = "_blank")),
110 |                
111 |                tags$hr()
112 |              )
113 |     ),
114 |     
115 |     tabPanel(tagList(tags$html("Powered by"),
116 |                      tags$img(src = "white-rstudio-logo.png",
117 |                               height="20")),
118 |              value = "RStudio",
119 |              tags$head(tags$script(src = "actions.js"))
120 |     )    
121 |   )
122 | )
123 | 


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/inst/apps/bee_house_hunting/www/actions.js:
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 1 | $(document).ready(function() {
 2 |   
 3 |   jQuery(function($){
 4 |     $("a[data-value='RStudio']").attr("href", "http://www.rstudio.com");
 5 |     $("a[data-value='RStudio']").attr("data-toggle", "");
 6 |   });
 7 |   
 8 | });
 9 | 
10 | 
11 | 
12 | 
13 | 
14 | 


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/inst/apps/bee_house_hunting/www/custom.css:
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/inst/apps/bee_house_hunting/www/white-rstudio-logo.png:
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https://raw.githubusercontent.com/swarm-lab/teachR/07583fc5cb9e2d6dcb9ba2b13ab6099e7292ea1d/inst/apps/bee_house_hunting/www/white-rstudio-logo.png


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/inst/apps/opinion_dynamics/global.R:
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 1 | pacman::p_load(shiny, shinythemes, simecol, ggvis, dplyr)
 2 | 
 3 | grid_sys <- function(time, init, parms) {
 4 |   o1 <- init
 5 |   o1[o1 < 0] <- 0
 6 |   
 7 |   o2 <- init
 8 |   o2[o2 > 0] <- 0
 9 |   
10 |   p1 <- eightneighbors(o1) / 8
11 |   p2 <- p1 - eightneighbors(o2) / 8
12 |   
13 |   r <- runif(nrow(init) * ncol(init))
14 |   
15 |   idx1 <- r <= p1
16 |   idx2 <- r <= p2 & r > p1
17 |   
18 |   init[idx1] <- 1 * parms$w1
19 |   init[idx2] <- -1 * parms$w2
20 |   
21 |   init
22 | }
23 | 


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/inst/apps/opinion_dynamics/info:
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 1 | Title: Opinion dynamics. 
 2 | Version: 0.1
 3 | Date: 2015-05-13
 4 | Author: Simon Garnier
 5 | Maintainer: Simon Garnier 
 6 | Description: This app illustrates the spreading of two competing opinions in an originally uniform population.
 7 | Category: Biology, Social Science
 8 | Keywords: Opinion dynamics
 9 | License: GPL (>= 3)
10 | Depends: dplyr (>= 0.4.2), simecol (>= 0.8-6), ggvis (>= 0.4.3)
11 | Command: opinion_dynamics


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/inst/apps/opinion_dynamics/server.R:
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 1 | shinyServer(function(input, output, session) {  
 2 |   data <- reactiveValues()
 3 |   
 4 |   observe({
 5 |     input$rerun
 6 |     
 7 |     mat <- matrix(0, nrow = 25, ncol = 25)
 8 |     mat[sample(1:(25 * 25), 2, FALSE)] <- c(1, -1)
 9 |     
10 |     m1 <- new("gridModel", main = grid_sys, parms = list(w1 = input$w1, w2 = input$w2),
11 |               times = 0:input$max.time, init = mat, solver = "iteration")
12 |     
13 |     data$steps <- out(sim(m1))
14 |     
15 |     data$summary <- data.frame(time = 0:input$max.time,
16 |                                s1 = sapply(data$steps, function(x) sum(x > 0)),
17 |                                s2 = sapply(data$steps, function(x) sum(x < 0)))
18 |   })    
19 |   
20 |   output$timeline <- renderUI({
21 |     sliderInput("time", "Timeline (move cursor or click on play button)", 
22 |                 min = 0, max = input$max.time, value = 0, step = 1, width = "100%", 
23 |                 animate = animationOptions(interval = 250, loop = FALSE,
24 |                                            playButton = tag("span", list(class = "glyphicon glyphicon-play")),
25 |                                            pauseButton = tag("span", list(class = "glyphicon glyphicon-pause"))))
26 |   })
27 |   
28 |   observe({
29 |     if (is.null(input$time)) {
30 |       return()
31 |     } 
32 |     
33 |     data.frame(expand.grid(x = 1:25, y = 1:25),
34 |                z = sign(as.vector(data$steps[[input$time + 1]])) + 2) %>%
35 |       mutate(color = c("#1E90FF", "#FFFFFF", "#FF6347")[z]) %>%
36 |       ggvis(x = ~factor(x), y = ~factor(y), fill := ~color) %>%
37 |       layer_rects(width = band(), height = band(), strokeWidth := 0.1) %>%
38 |       hide_axis("x") %>%
39 |       hide_axis("y") %>%
40 |       hide_legend("fill") %>%
41 |       set_options(width = "auto", height = "100%", resizable = FALSE, duration = 30) %>%
42 |       bind_shiny("display1")
43 |     
44 |     filter(data$summary, time <= (input$time + 1)) %>%
45 |       ggvis(x = ~time) %>%
46 |       layer_paths(y = ~100 * (25 * 25 - s1 - s2) / 625, stroke := "black", strokeWidth := 2) %>%
47 |       layer_paths(y = ~100 * s1 / 625, stroke := "tomato", strokeWidth := 2) %>%
48 |       layer_paths(y = ~100 * s2 / 625, stroke := "dodgerblue", strokeWidth := 2) %>%
49 |       scale_numeric("x", domain = c(0, input$max.time), nice = FALSE) %>%
50 |       add_axis("x", title = "Time") %>%
51 |       add_axis("y", title = "% population") %>%
52 |       set_options(width = "auto", height = "100%", resizable = FALSE, duration = 30) %>%
53 |       bind_shiny("display2")
54 |   })
55 | })
56 | 
57 | 
58 | 


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/inst/apps/opinion_dynamics/ui.R:
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 1 | shinyUI(
 2 |   navbarPage(
 3 |     title = "Opinion dynamics",
 4 |     theme = shinytheme("cosmo"),
 5 |     fluid = FALSE,
 6 |     collapsible = TRUE,
 7 |     
 8 |     tabPanel("Model",
 9 |              
10 |              includeCSS("www/custom.css"),
11 |              
12 |              # Sidebar
13 |              sidebarLayout(
14 |                sidebarPanel(
15 |                  width = 3, 
16 |                  sliderInput("max.time", "Duration of the trial:",
17 |                              min = 1, max = 500, value = 200, width = "100%"),
18 |                  sliderInput("w1", "Strength of opinion 1:",
19 |                              min = 0, max = 1, value = 0.25, step = 0.01, width = "100%"),
20 |                  sliderInput("w2", "Strength of opinion 2:",
21 |                              min = 0, max = 1, value = 0.25, step = 0.01, width = "100%"),
22 |                  p(align = 'center',
23 |                    actionButton("rerun", "Rerun"))
24 |                ),
25 |                
26 |                # Main panel
27 |                mainPanel(
28 |                  fluidRow(
29 |                    column(6, 
30 |                           tags$div(class = "box", 
31 |                                    tags$div(class = "content", 
32 |                                             ggvisOutput("display1")))
33 |                           # plotOutput("plot", height = "500px")
34 |                  ),
35 |                  column(6, 
36 |                         tags$div(class = "box", 
37 |                                  tags$div(class = "content", 
38 |                                           ggvisOutput("display2")))
39 |                         # plotOutput("plot", height = "500px")
40 |                  ),
41 |                  uiOutput("timeline"))
42 |                )
43 |              )
44 |     ),
45 |     
46 |     tabPanel("Instructions"),
47 |     
48 |     tabPanel("About",
49 |              
50 |              fluidRow(
51 |                tags$hr(),
52 |                
53 |                p(strong("Author:"), " Simon Garnier (", a("New Jersey Institute of Technology",
54 |                                                           href = "http://www.njit.edu",
55 |                                                           target = "_blank"), ")"),
56 |                
57 |                p(strong("Twitter:"), a("@sjmgarnier", 
58 |                                        href = "https://twitter.com/sjmgarnier",
59 |                                        target = "_blank")),
60 |                
61 |                p(strong("Website:"), a("http://www.theswarmlab.com", 
62 |                                        href = "http://www.theswarmlab.com",
63 |                                        target = "_blank")),
64 |                
65 |                p(strong("Source code:"), 
66 |                  a("GitHub",
67 |                    href = "https://github.com/swarm-lab/teachR/tree/master/inst/apps/opinion_dynamics",
68 |                    target = "_blank")),
69 |                
70 |                p(strong("Created with:"), 
71 |                  a("RStudio",
72 |                    href = "http://www.rstudio.com/",
73 |                    target = "_blank"), 
74 |                  " and ",
75 |                  a("Shiny.",
76 |                    href = "http://shiny.rstudio.com",
77 |                    target = "_blank")),
78 |                
79 |                p(strong("License:"), 
80 |                  a("GPL v3",
81 |                    href = "http://www.gnu.org/copyleft/gpl.html",
82 |                    target = "_blank")),
83 |                
84 |                tags$hr()
85 |              )
86 |     ),
87 |     
88 |     tabPanel(tagList(tags$html("Powered by"),
89 |                      tags$img(src = "white-rstudio-logo.png",
90 |                               height = "20")),
91 |              value = "RStudio",
92 |              tags$head(tags$script(src = "actions.js"))
93 |     )    
94 |   )
95 | )
96 | 


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/inst/apps/opinion_dynamics/www/actions.js:
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 1 | $(document).ready(function() {
 2 |   
 3 |   jQuery(function($){
 4 |     $("a[data-value='RStudio']").attr("href", "http://www.rstudio.com");
 5 |     $("a[data-value='RStudio']").attr("data-toggle", "");
 6 |   });
 7 |   
 8 | });
 9 | 
10 | 
11 | 
12 | 
13 | 
14 | 


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/inst/apps/opinion_dynamics/www/custom.css:
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 1 | .box{
 2 | 	position: relative;
 3 | 	width: 100%;		/* desired width */
 4 | }
 5 | 
 6 | .box:before{
 7 | 	content: "";
 8 | 	display: block;
 9 | 	padding-top: 100%; 	/* initial ratio of 1:1*/
10 | }
11 | 
12 | .content {
13 |   position:  absolute;
14 | 	top: 0;
15 | 	left: 0;
16 | 	bottom: 0;
17 | 	right: 0;
18 | }
19 | 


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/inst/apps/opinion_dynamics/www/white-rstudio-logo.png:
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/inst/apps/wisdom_of_crowds/global.R:
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 1 | pacman::p_load(shiny, shinythemes, dplyr, plotly, compiler, memoise, msm)
 2 | 
 3 | enableJIT(3)
 4 | 
 5 | memoise(sigmoid <- function(x, a = 0, k = 1, b = 0.1, m = 100, v = 1, q = 1) {
 6 |   s <- a + (k - a) / ((1 + q * exp(-b * (x - m))) ^ (1 / v))
 7 |   s0 <- a + (k - a) / ((1 + q * exp(-b * (0 - m))) ^ (1 / v))
 8 |   (s - s0) / diff(c(s0, 1)) * diff(c(0, 1))
 9 | })
10 | 
11 | memoise(woc <- function(n = 100, val = 200, error = 0.1, soc = 1) {
12 |   res <- rtnorm(n, mean = val, sd = val * error, lower = 0)
13 |   soc <- sigmoid(0:n, m = (1 - soc) * n, b = 0.5)
14 |   
15 |   for (i in 2:n) {
16 |     res[i] <- res[i] * (1 - soc[i]) + mean(res[1:(i - 1)]) * soc[i]
17 |   }
18 |   
19 |   res
20 | })
21 | 


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/inst/apps/wisdom_of_crowds/info:
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 1 | Title: The Wisdom of Crowds. 
 2 | Version: 0.1
 3 | Date: 2016-02-10
 4 | Author: Simon Garnier
 5 | Maintainer: Simon Garnier 
 6 | Description: This app illustrates the 'Wisdom of Crowds' effect and what happens when social interactions are allowed to happen between the actors.
 7 | Category: Biology, Social Science
 8 | Keywords: Opinion dynamics
 9 | License: GPL (>= 3)
10 | Depends: plotly, dplyr, compiler, memoise, msm
11 | Command: wisdom_of_crowds


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/inst/apps/wisdom_of_crowds/server.R:
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 1 | shinyServer(function(input, output, session) {
 2 |   
 3 |   react <- reactiveValues(tab = {}, count = -1)
 4 |   
 5 |   observe({
 6 |     if (react$count != input$goButton) {
 7 |       react$count <- input$goButton
 8 |       
 9 |       withProgress(message = paste0("Simulating ", input$rep, " experiments"), {
10 |         m1 <- replicate(input$rep, woc(n = input$n, 
11 |                                val = 200,
12 |                                error = input$error / 100,
13 |                                soc = 0))
14 |         tmp1 <- abs(m1 - 200) 
15 |         tmp2 <- abs(matrix(apply(m1, 2, mean), nrow = input$n, ncol = input$rep, byrow = TRUE) - 200)
16 |         r1 <- apply(tmp2 < tmp1, 2, sum)
17 |         
18 |         m2 <- replicate(input$rep, woc(n = input$n, 
19 |                                val = 200,
20 |                                error = input$error / 100,
21 |                                soc = input$soc))
22 |         tmp1 <- abs(m2 - 200) 
23 |         tmp2 <- abs(matrix(apply(m2, 2, mean), nrow = input$n, ncol = input$rep, byrow = TRUE) - 200)
24 |         r2 <- apply(tmp2 < tmp1, 2, sum)
25 |         
26 |         react$tab <- data.frame(
27 |           SOC = as.factor(rep(c("Control", "Experimental"), each = input$rep * 2)),
28 |           TYPE = rep(c("mean", "sd", "mean", "sd"), each = input$rep),
29 |           VAL = c(apply(m1, 2, mean), # 100 * (r1 / input$n),
30 |                   apply(m1, 2, sd),
31 |                   apply(m2, 2, mean), # 100 * (r2 / input$n),
32 |                   apply(m2, 2, sd)))
33 |       }) 
34 |     }
35 |   })
36 |   
37 |   output$IBM.plot1 <- renderPlotly({
38 |     sub_dat <- filter(react$tab, TYPE == "mean")
39 |     r <- c(min(sub_dat$VAL), max(sub_dat$VAL))
40 |     plot_ly(sub_dat, type = "histogram", alpha = 0.6, 
41 |             x = ~VAL, color = ~SOC, colors = c("tomato3", "dodgerblue3"),
42 |             xbins = list(start = r[1], end = r[2], size = diff(r) / 40), 
43 |             autobinx = FALSE) %>%
44 |       layout(barmode = "overlay", hovermode = "x",
45 |              xaxis = list(title = "Group average"),
46 |              yaxis = list(title = "Count"),
47 |              font = list(size = 14),
48 |              legend = list(x = 0.5, y = 1.1, orientation = "h", xanchor = "center"))
49 |   })
50 |   
51 |   output$IBM.plot2 <- renderPlotly({
52 |     sub_dat <- filter(react$tab, TYPE == "sd")
53 |     r <- c(min(sub_dat$VAL), max(sub_dat$VAL))
54 |     plot_ly(sub_dat, type = "histogram", alpha = 0.6, 
55 |             x = ~VAL, color = ~SOC, colors = c("tomato3", "dodgerblue3"),
56 |             xbins = list(start = r[1], end = r[2], size = diff(r) / 40), 
57 |             autobinx = FALSE) %>%
58 |       layout(barmode = "overlay", hovermode = "x",
59 |              xaxis = list(title = "Group standard deviation"),
60 |              yaxis = list(title = "Count"),
61 |              font = list(size = 14),
62 |              legend = list(x = 0.5, y = 1.1, orientation = "h", xanchor = "center"))
63 |   })
64 | })
65 | 


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/inst/apps/wisdom_of_crowds/ui.R:
--------------------------------------------------------------------------------
  1 | shinyUI(
  2 |   navbarPage(
  3 |     title = "The Wisdom of Crowds",
  4 |     theme = shinytheme("cosmo"),
  5 |     fluid = FALSE,
  6 |     collapsible = TRUE,
  7 |     
  8 |     tabPanel("Model",
  9 |              
 10 |              includeCSS("www/custom.css"),
 11 |              
 12 |              # Sidebar
 13 |              sidebarLayout(
 14 |                sidebarPanel(
 15 |                  width = 3, 
 16 |                  
 17 |                  sliderInput("n", "Number of individuals in the group", 
 18 |                              min = 50, max = 500, value = 100, step = 1, width = "100%"), hr(),
 19 |                  
 20 |                  sliderInput("error", "% error of individual guesses", 
 21 |                              min = 0, max = 100, value = 20, width = "100%"), hr(),
 22 |                  
 23 |                  sliderInput("soc", "Intensity of social influence", 
 24 |                              min = 0, max = 1, value = 0, width = "100%"), hr(),
 25 |                  
 26 |                  sliderInput("rep", "Number of replicates", 
 27 |                              min = 0, max = 1000, value = 500, width = "100%"), hr(),
 28 |                  
 29 |                  div(style = "text-align: center;",
 30 |                      actionButton("goButton", "Rerun", icon = icon("refresh"))
 31 |                  )
 32 |                  
 33 |                ),
 34 |                
 35 |                # Main panel
 36 |                mainPanel(
 37 |                  fluidRow(
 38 |                    column(6,
 39 |                           plotlyOutput("IBM.plot1", height = "100%")),
 40 |                    
 41 |                    column(6,
 42 |                           plotlyOutput("IBM.plot2", height = "100%"))
 43 |                  ),
 44 |                  
 45 |                  tags$hr(),
 46 |                  
 47 |                  p(tags$b("Control"), " = no social influence"),
 48 |                  p(tags$b("Experimental"), " = social influence set to slider value"),
 49 |                  p(tags$b("Number of gumballs"), " = 200")
 50 |                )
 51 |              )
 52 |     ),
 53 |     
 54 |     tabPanel("Instructions", 
 55 |              
 56 |              fluidRow(
 57 |                tags$hr(),
 58 |                
 59 |                h2("Goal"),
 60 |                
 61 |                p("This webapp simulates a classical experiment in the social 
 62 |                  sciences that aims at demonstrating the so-called 'Wisdom of 
 63 |                  Crowds'."), 
 64 |                
 65 |                p("In this experiment, a number of people (set by the user) are 
 66 |                  asked to guess the number of gumballs placed in a jar. Each 
 67 |                  guess is likely to be off the true number of gumballs in the 
 68 |                  jar. However, if all the guesses are made independently and in
 69 |                  the absence of general perceptual or cognitive bias to 
 70 |                  systematically under- or overestimate this number, the average
 71 |                  guess of the group will be close to the exact number of 
 72 |                  gumballs. This observation, ", a("made originally by Sir Francis 
 73 |                  Galton in 1906", 
 74 |                  href = "https://en.wikipedia.org/wiki/Francis_Galton#Variance_and_standard_deviation"),
 75 |                  ", is at the origin of concept of 'Wisdom of Crowds', where the
 76 |                  crowd as a whole is better than any of the people who compose 
 77 |                  it"),
 78 |                
 79 |                p("However, if the guesses are not made independently (e.g. if 
 80 |                  each person knows about previous guesses), then things can get
 81 |                  quickly out of hands, and the 'Wisdom of Crowds' disappear. 
 82 |                  The goal of this simulation if to help you understand how 
 83 |                  social feedback (i.e. knowledge of other people's guesses in 
 84 |                  this case) can undermine the ability of a group to act as a 
 85 |                  reliable collective estimator."),
 86 |                
 87 |                tags$hr(),
 88 |                
 89 |                h2("Parameters"),
 90 |                
 91 |                p("This simulation takes 3 parameters that you can modify using 
 92 |                  the sliders in the 'Model' tab."),
 93 |                
 94 |                tags$ol(
 95 |                  tags$li(tags$b("Number of individuals in the group: "), "this 
 96 |                          sets the number of people who are asked to guess in 
 97 |                          each replicate of the virtual experiment."), 
 98 |                  tags$li(tags$b("% error of individual guesses: "), "this sets
 99 |                          the average error of each person's guess. For instance,
100 |                          if sets to 20%, this means that people make guesses 
101 |                          that in average 20% off the real number of gumballs in 
102 |                          the jar (above or below this number)."), 
103 |                  tags$li(tags$b("Intensity of social influence: "), "this 
104 |                          determines how much each individual cares about the 
105 |                          guesses made by previous individuals. If set to 0, it 
106 |                          means that they ignore them completely before making a 
107 |                          guess (independent guesses).")
108 |                ),
109 |                
110 |                p("Every time you re-run the experiment with a different set of 
111 |                  parameters, the software simulates 1,000 replicates."),
112 |                
113 |                tags$hr(),
114 |                
115 |                h2("Outputs"),
116 |                
117 |                p("This simulation returns 2 graphs."),
118 |                
119 |                tags$ol(
120 |                  tags$li("The left represents the percentage of individuals in 
121 |                          each replicate that made a worse guess that the group's
122 |                          average in that replicate. Higher values indicates that
123 |                          the group performs better than most of its members."), 
124 |                  tags$li("The right graph represents the distribution of the 
125 |                          groups' standard deviations. Smaller values indicates
126 |                          that individual opinions are more similar to each other.")
127 |                ),
128 |                
129 |                tags$hr()
130 |              )
131 |     ),
132 |     
133 |     tabPanel("About",
134 |              
135 |              fluidRow(
136 |                tags$hr(),
137 |                
138 |                p(strong("Author:"), " Simon Garnier (", a("New Jersey Institute of Technology",
139 |                                                           href = "http://www.njit.edu",
140 |                                                           target = "_blank"), ")"),
141 |                
142 |                p(strong("Twitter:"), a("@sjmgarnier", 
143 |                                        href = "https://twitter.com/sjmgarnier",
144 |                                        target = "_blank")),
145 |                
146 |                p(strong("Website:"), a("http://www.theswarmlab.com", 
147 |                                        href = "http://www.theswarmlab.com",
148 |                                        target = "_blank")),
149 |                
150 |                p(strong("Source code:"), 
151 |                  a("GitHub",
152 |                    href = "https://github.com/swarm-lab/Shiny/tree/master/wisdom_of_crowds/model",
153 |                    target = "_blank")),
154 |                
155 |                p(strong("Created with:"), 
156 |                  a("RStudio",
157 |                    href = "http://www.rstudio.com/",
158 |                    target = "_blank"), 
159 |                  " and ",
160 |                  a("Shiny.",
161 |                    href = "http://shiny.rstudio.com",
162 |                    target = "_blank")),
163 |                
164 |                p(strong("License:"), 
165 |                  a("GPL v3",
166 |                    href = "http://www.gnu.org/copyleft/gpl.html",
167 |                    target = "_blank")),
168 |                
169 |                tags$hr()
170 |              )
171 |     ),
172 |     
173 |     tabPanel(tagList(tags$html("Powered by"),
174 |                      tags$img(src = "white-rstudio-logo.png",
175 |                               height = "20")),
176 |              value = "RStudio",
177 |              tags$head(tags$script(src = "actions.js"))
178 |     )    
179 |   )
180 | )
181 | 
182 | 


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/inst/apps/wisdom_of_crowds/www/actions.js:
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 1 | $(document).ready(function() {
 2 |   
 3 |   jQuery(function($){
 4 |     $("a[data-value='RStudio']").attr("href", "http://www.rstudio.com");
 5 |     $("a[data-value='RStudio']").attr("data-toggle", "");
 6 |   });
 7 |   
 8 | });
 9 | 
10 | 
11 | 
12 | 
13 | 
14 | 


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 1 | 
 2 | 
 3 | 
 4 | 
 5 | 
 6 | Apps available in teachR
 7 | 
 8 | 
19 | 
20 | #!r_highlight#
21 | 
22 | #!mathjax#
23 | 
24 | 
47 | 
48 | 
49 | 
50 | #!header#
51 | 
52 | 
53 | 
54 | 
55 | 
    #!title#
    
56 | 
    
57 | #!html_output#
58 | 
59 | 
60 | 
61 | 


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 1 | 
 2 | 
 3 | 
 5 | 
11 | 
12 | 	
13 | 	teachR
14 | 
15 | 
16 | 	
22 | 
23 | 
24 | 


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/man/export_app.Rd:
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 1 | % Generated by roxygen2: do not edit by hand
 2 | % Please edit documentation in R/export_app.R
 3 | \name{export_app}
 4 | \alias{export_app}
 5 | \title{Export \code{teachR} Apps}
 6 | \usage{
 7 | export_app(app, dest)
 8 | }
 9 | \arguments{
10 | \item{app}{The name of the app to export.}
11 | 
12 | \item{dest}{The destination of the app folder on the user's computer. A folder
13 | with the name of the app will be created at this location.}
14 | }
15 | \value{
16 | This function does not return anything.
17 | }
18 | \description{
19 | This function exports a Shiny app provided by the 
20 |  \code{teachR} library to a local folder on 
21 |  a user's computer. Useful for modifying the app or running it on a Shiny 
22 |  Server instance for example.
23 | }
24 | \examples{
25 | \dontrun{
26 |  # Export app to the current working directory
27 |  export_app("aggregation_segregation", ".")
28 | }
29 | 
30 | }
31 | \author{
32 | Simon Garnier, \email{garnier@njit.edu}
33 | }
34 | 


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 1 | % Generated by roxygen2: do not edit by hand
 2 | % Please edit documentation in R/list_apps.R
 3 | \name{list_apps}
 4 | \alias{list_apps}
 5 | \title{List \code{teachR} Apps}
 6 | \usage{
 7 | list_apps(categories = NULL, keywords = NULL)
 8 | }
 9 | \arguments{
10 | \item{categories}{A character string or a vector of character strings 
11 | corresponding to existing app categories (case insensitive).}
12 | 
13 | \item{keywords}{A character string or a vector of character strings 
14 | corresponding to existing app keywords (case insensitive).}
15 | }
16 | \value{
17 | This function opens an html file.
18 | }
19 | \description{
20 | This function generates a webpage listing all the apps available 
21 |  through the \code{teachR} library. The list can be filtered by category 
22 |  (type \code{list_categories()} for a list of existing categories) and 
23 |  keywords (type \code{list_keywords()} for a list of existing keywords).
24 | }
25 | \details{
26 | If called from RStudio, the list will open in the internal RStudio 
27 |  viewer. If called from a terminal, it will open in your default internet 
28 |  browser.
29 | }
30 | \examples{
31 | \dontrun{
32 |  list_apps(categories = c("biology", "social science"))
33 | }
34 | 
35 | }
36 | \author{
37 | Simon Garnier, \email{garnier@njit.edu}
38 | }
39 | 


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/man/list_categories.Rd:
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 1 | % Generated by roxygen2: do not edit by hand
 2 | % Please edit documentation in R/list_categories.R
 3 | \name{list_categories}
 4 | \alias{list_categories}
 5 | \title{List Categories of All \code{teachR} Apps}
 6 | \usage{
 7 | list_categories()
 8 | }
 9 | \value{
10 | A vector of character strings, each of them corresponding to a different
11 |  category.
12 | }
13 | \description{
14 | This function generates a listing  of all the categories of apps 
15 |  available through the \code{teachR} library.
16 | }
17 | \examples{
18 | \dontrun{
19 |  list_categories()
20 | }
21 | 
22 | }
23 | \author{
24 | Simon Garnier, \email{garnier@njit.edu}
25 | }
26 | 


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 1 | % Generated by roxygen2: do not edit by hand
 2 | % Please edit documentation in R/list_keywords.R
 3 | \name{list_keywords}
 4 | \alias{list_keywords}
 5 | \title{List Keywords of All \code{teachR} Apps}
 6 | \usage{
 7 | list_keywords()
 8 | }
 9 | \value{
10 | A vector of character strings, each of them corresponding to a different
11 |  keyword.
12 | }
13 | \description{
14 | This function generates a listing of all the keywords of apps 
15 |  available through the \code{teachR} library.
16 | }
17 | \examples{
18 | \dontrun{
19 |  list_keywords()
20 | }
21 | 
22 | }
23 | \author{
24 | Simon Garnier, \email{garnier@njit.edu}
25 | }
26 | 


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/man/run_app.Rd:
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 1 | % Generated by roxygen2: do not edit by hand
 2 | % Please edit documentation in R/run_app.R
 3 | \name{run_app}
 4 | \alias{run_app}
 5 | \title{Run \code{teachR} Apps}
 6 | \usage{
 7 | run_app(app)
 8 | }
 9 | \arguments{
10 | \item{app}{The name of the app to run.}
11 | }
12 | \value{
13 | This function does not return anything.
14 | }
15 | \description{
16 | This function calls a Shiny app provided by the 
17 |  \code{teachR} library. The list of available Shiny apps can be obtained by 
18 |  typing \code{list_apps()} in your R terminal.
19 | }
20 | \details{
21 | If called from RStudio, the app will open in the internal RStudio 
22 |  internet browser. If called from a terminal, it will open in your default 
23 |  internet browser. All apps should work without any problem with the internal 
24 |  RStudio internet browser, as well as with recent versions of most internet 
25 |  browsers. It is likely to break with older versions.
26 | }
27 | \examples{
28 | \dontrun{
29 |  run_app("aggregation_segregation")
30 | }
31 | 
32 | }
33 | \author{
34 | Simon Garnier, \email{garnier@njit.edu}
35 | }
36 | 


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/teachR.Rproj:
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 1 | Version: 1.0
 2 | 
 3 | RestoreWorkspace: Default
 4 | SaveWorkspace: Default
 5 | AlwaysSaveHistory: Default
 6 | 
 7 | EnableCodeIndexing: Yes
 8 | UseSpacesForTab: Yes
 9 | NumSpacesForTab: 2
10 | Encoding: UTF-8
11 | 
12 | RnwWeave: Sweave
13 | LaTeX: pdfLaTeX
14 | 
15 | BuildType: Package
16 | PackageUseDevtools: Yes
17 | PackageInstallArgs: --no-multiarch --with-keep.source
18 | PackageRoxygenize: rd,collate,namespace,vignette
19 | 


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/vignettes/z1_install.R:
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 1 | ## ---- message=FALSE, eval=FALSE------------------------------------------
 2 | #  if (!require(devtools))
 3 | #    install.packages("devtools")
 4 | 
 5 | ## ---- message=FALSE, eval=FALSE------------------------------------------
 6 | #  devtools::install_github("swarm-lab/teachR")
 7 | 
 8 | ## ---- message=FALSE, eval=FALSE------------------------------------------
 9 | #  library(teachR)
10 | 
11 | 


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/vignettes/z1_install.Rmd:
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 1 | ---
 2 | title: "1 - Installing teachR"
 3 | output: rmarkdown::html_vignette
 4 | vignette: >
 5 |   %\VignetteIndexEntry{pkgdown}
 6 |   %\VignetteEngine{knitr::rmarkdown}
 7 |   %\VignetteEncoding{UTF-8}
 8 | ---
 9 | 
10 | __This page describes the installation process of [`teachR`](https://github.com/swarm-lab/teachR).__ 
11 | 
12 | `teachR` has not been released on [CRAN](https://cran.r-project.org/) yet, but it 
13 | can be easily installed from its [GitHub repository](https://github.com/swarm-lab/teachR)
14 | with the following steps. 
15 | 
16 | ---
17 | 
18 | + [1.1 - Before installing ](#before-installing)
19 | + [1.2 - Installing teachR](#installing-teachr)
20 | + [1.3 - Loading teachR](#loading-teachr)
21 |   
22 | ---
23 | 
24 | ## 1.1 - Before installing
25 | 
26 | Before installing `teachR`, you will need to install the latest version of the [`devtools`](https://CRAN.R-project.org/package=devtools) package. You can install [`devtools`](https://CRAN.R-project.org/package=devtools)  from 
27 | [`CRAN`](https://cran.r-project.org) as follows: 
28 | 
29 | ```{r, message=FALSE, eval=FALSE}
30 | if (!require(devtools))
31 |   install.packages("devtools")
32 | ```
33 | 
34 | ---
35 | 
36 | ## 1.2 - Installing teachR
37 | 
38 | You can install `teachR` as follows:
39 | 
40 | ```{r, message=FALSE, eval=FALSE}
41 | devtools::install_github("swarm-lab/teachR")
42 | ```
43 | 
44 | ---
45 | 
46 | ## 1.3 - Loading teachR
47 | 
48 | ```{r, message=FALSE, eval=FALSE}
49 | library(teachR)
50 | ```
51 | 


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/vignettes/z2_usage.Rmd:
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 1 | ---
 2 | title: "1 - Installing teachR"
 3 | output: rmarkdown::html_vignette
 4 | vignette: >
 5 |   %\VignetteIndexEntry{pkgdown}
 6 |   %\VignetteEngine{knitr::rmarkdown}
 7 |   %\VignetteEncoding{UTF-8}
 8 | ---
 9 | 
10 | __This page describes how to use [`teachR`](https://github.com/swarm-lab/teachR).__ 
11 | 


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 1 | 
 2 | 
 3 | 
 4 | 
 5 | 
 6 | 
 7 | 
 8 | 
 9 | 
10 | 
11 | 
12 | 
13 | 
14 | 
15 | 1 - Installing teachR
16 | 
17 | 
18 | 
19 | 
20 | 
21 | 
22 | 
23 | 
24 | 
25 | 
26 | 
27 | 
28 | 
29 | 
30 | 
31 | 
    1 - Installing teachR
    
32 | 
33 | 
34 | 
35 | 
    This page describes how to use teachR.
    
36 | 
37 | 
38 | 
39 | 
40 | 
48 | 
49 | 
50 | 
51 | 


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 1 | ---
 2 | title: "1 - Installing teachR"
 3 | output: rmarkdown::html_vignette
 4 | vignette: >
 5 |   %\VignetteIndexEntry{pkgdown}
 6 |   %\VignetteEngine{knitr::rmarkdown}
 7 |   %\VignetteEncoding{UTF-8}
 8 | ---
 9 | 
10 | __This page describes how to add apps to [`teachR`](https://github.com/swarm-lab/teachR).__ 
11 | 


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 2 | 
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10 | 
11 | 
12 | 
13 | 
14 | 
15 | 1 - Installing teachR
16 | 
17 | 
18 | 
19 | 
20 | 
21 | 
22 | 
23 | 
24 | 
25 | 
26 | 
27 | 
28 | 
29 | 
30 | 
31 | 
    1 - Installing teachR
    
32 | 
33 | 
34 | 
35 | 
    This page describes how to add apps to teachR.
    
36 | 
37 | 
38 | 
39 | 
40 | 
48 | 
49 | 
50 | 
51 | 


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