R/render_rmd.R
In marinebon/infographiqR: Supporting R functions for creating intelligent interactive infographics, ie infographiq
Defines functions
rmd2html
render_figure
md_caption
insert_tooltip
infographiq_template
glossarize_md
get_modal_info
Documented in
get_modal_info
glossarize_md
infographiq_template
insert_tooltip
md_caption
render_figure
rmd2html
#' Generate the html for R markdown files
#'
#' Rmd files with interactive figures present a special problem in terms of rendering
#' them into html. The problem is that, if one uses the markdown library to
#' create the html, the figures will turn out fine but the glossary tooltip functionality
#' will be missing. This tooltip functionality is created by the function rmd2html,
#' described in this package. If one uses rmd2html to render a rmd file containing
#' interactive figures, the tooltips will turn out fine but the figures won't show
#' up. The problem with rmd2html is that the appropriate javascript libraries are
#' not loaded into the resulting <head> section of the final html. This function
#' solves the problem (thereby producing html with both working figures and tooltips)
#' by rendering the rmd using both the markdown and rmd2html approaches and then rewriting
#' the <head> section of the rmd2html version with the markdown version.
#'
#' @param target_rmd The R markdown file to be rendered
#' @param nms The NMS sanctuary, with only "cinms" currently doing anything.
#' @return The function outputs a html file that is the rendered version of the input rmd file.
#' @export
#' @examples \dontrun{
#' generate_html_4_rmd(here::here("modals/tar.Rmd"))
#' }
#'
generate_html_4_rmd <- function (target_rmd, nms = "cinms"){
# the following mini-function where_is_head has two simple purposes. When fed in a html file, which has already been brought in
# to R via readLines, the function will tell you the line number of the html file that contains "</html>" and
# the total number of lines in the file
where_is_head <-function(input_lines){
i<-1
while (!(input_lines[i]=="</head>")){
i <-i + 1
}
output_list <- list("total_lines" = length(input_lines), "head_line" = i)
return(output_list)
}
# Let's figure out where we are. In my local environment, I am in the directory for
# the sanctuary. In a docker container though, I won't be. So the following section of
# code attempts to put us in the right directory if we aren't there already.
location <- here::here()
start_point <- nchar(location) - nchar(nms) +1
if (!(substr(location, start_point, nchar(location)) == nms)){
location <- paste(location, nms, sep = "/")
}
modal_dir<- paste0(location,"/modals/")
# for a given rmd file, let's generate the html for it in two ways. Way 1 is via
# rmd2html which gives us the glossary tooltip working right (but where the interactive
# figures don't work). Way 2 is via render which gives us the interactive figures working
# right (but where the glossary tooltip doesn't work)
rmd2html(target_rmd)
rmarkdown::render(target_rmd, output_file = paste(modal_dir, "temp_file.html", sep ="/"))
# We want both the interactive figures and the glossary tooltip working in the html. The way to do
# that is to grab everything in the <head> section of the html produced by render and then
# to replace the <head> section of the html produced by rmd2html with that. The first step
# here is to read in the two html files
target_html <- gsub("Rmd", "html", target_rmd, ignore.case = TRUE)
target_lines <- readLines(target_html)
replacement_path <- paste0(modal_dir,"temp_file.html")
replacement_lines <- readLines(replacement_path)
# Next, let's figure out where the <head> section ends in each html file
target_location <- where_is_head(target_lines)
replacement_location <-where_is_head(replacement_lines)
# Now, let's replace the <head> section and save the new version of the html
output_file = c(replacement_lines[1:replacement_location$head_line],target_lines[(target_location$head_line+1):target_location$total_lines])
write(output_file, file = target_html)
# let's delete the temp html file that we created
file.remove(paste(modal_dir, "temp_file.html", sep ="/"))
}
#' Generate hyperlinked gray bar above figure
#'
#' The purpose of this function is to generate the hyperlinks for the monitoring program and data
#' associated with a figure and then to insert them into a gray bar above the figure in the modal window.
#'
#' @param figure_id The name of a row in the following google sheet cinms_content::info_figure_links
#' @return The output is a set of html tags to be inserted into a html file.
#' @export
#' @examples \dontrun{
#' get_figure_info("Figure App.E.11.8.")
#' }
#'
get_figure_info <- function (figure_id){
info_csv = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet=info_figure_links"
d <- readr::read_csv(info_csv) %>%
dplyr::filter(md_caption == figure_id)
if (nrow(d) == 0){
warning(paste("Need link in cinms_content:info_figure_links Google Sheet for", figure_id))
return("")
}
html <- NULL
no_ws <- c("before","after","outside","after-begin","before-end")
icons <- tibble::tribble(
~description_bkup , ~css, ~icon, ~fld_url, ~fld_description,
"Monitoring Program", "left", "clipboard-list", "url_monitoring", "title_monitoring",
"Data" , "right", "database" , "url_data", "title_data")
for (i in 1:nrow(icons)){ # i=1
h <- icons[i,]
url <- d[h$fld_url]
description <- d[h$fld_description]
if(!is.na(url) & substr(url,0,4) == "http"){
if (is.na(description)){
description <- h$description_bkup
} else {
description <- substr(stringr::str_trim(description), 0, 45)
}
html <- shiny::tagList(
html,
htmltools::div(
.noWS = no_ws,
style = glue::glue("text-align:{h$css}; display:table-cell;"),
htmltools::a(
.noWS = no_ws,
href = url, target = '_blank',
shiny::icon(h$icon), description)))
}
}
if (is.null(html))
return("")
shiny::tagList(
htmltools::div(
.noWS = no_ws,
style = "background:LightGrey; width:100%; display:table; font-size:120%; padding: 10px 10px 10px 10px; margin-bottom: 10px;",
htmltools::div(
.noWS = no_ws,
style = "display:table-row",
html)))
}
#' Generate introductory info for the html of a modal window
#'
#' This function generates the html tags for the top portion of a rmd modal window,
#' containing the introductory information about that window. This function only
#' will work within a rmd file to be knitted.
#'
#' @param rmd The name of an input file passed to knit().
#' @param info_modal_links_csv A hyperlink to the google sheet, in csv format, that contains the modal links info.
#' @return The function returns a string that is a set of html tags to be inserted into a html file.
#' @export
#' @examples \dontrun{
#' get_modal_info(info_modal_links_csv = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet=info_modal_links")
#' }
#'
get_modal_info <- function(rmd = knitr::current_input(), info_modal_links_csv){
modal_id <- basename(fs::path_ext_remove(rmd))
row <- readr::read_csv(info_modal_links_csv) %>%
dplyr::filter(modal == modal_id)
if (nrow(row) == 0) stop("Need link in cinms_content:info_modal_links Google Sheet!")
icons_html = NULL
if (!is.na(row$url_info)){
icons_html =
htmltools::a(shiny::icon("info-circle"), href=row$url_info, target='_blank')
}
if (!is.na(row$url_photo)){
icons_html = htmltools::tagList(
icons_html,
htmltools::a(shiny::icon("camera"), href=row$url_photo, target='_blank'))
}
htmltools::div(
htmltools::div(htmltools::tagList(icons_html), style = "margin-top: 10px;margin-bottom: 10px; margin-right: 10px; flex: 1;"), htmltools::div(
ifelse(!is.na(row$tagline), row$tagline, ""), style = "margin: 10px; font-style: italic; flex: 20; "), style="display: flex"
)
}
#' Insert html tags for glossary tooltips into md files
#'
#' The purpose of this function is to insert the html tags required for glossary
#' tooltip functionality into a given markdown file. The function glossarize_md
#' is used by the function rmd2html described in this package.
#'
#' @param md The markdown file where the tags are to be inserted.
#' @param md_out The markdown output file.
#' @return The output of this function is html tags inserted into a markdown file.
glossarize_md <- function(md, md_out = md){
# read the markdown file
tx <- readLines(md)
# only go forward with the glossarizing if the file contains more than "data to be added soon"
if (length(tx) > 12) {
# load in the glossary that will be used to create the tooltips. Reverse alphabetize the glossary, which will come in handy later
glossary_csv = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet=glossary"
glossary <- readr::read_csv(glossary_csv)
glossary <- glossary[order(glossary$term, decreasing = TRUE),]
# initialize the string variable that will hold the javascript tooltip
script_tooltip = ""
# go through each row of the glossary
for (q in 1:nrow(glossary)) {
# set a variable to zero that is used to keep track of whether a particular glossary word is in the modal window
flag = 0
# load in a specific glossary term
search_term = glossary$term[q]
# the css to be wrapped around any glossary word
span_definition = paste0('<span aria-describedby="tooltip', q, '" tabindex="0" style="border-bottom: 1px dashed #000000; font-size:100%" id="tooltip', q, '">')
# let's look to see if the glossary term is a subset of a longer glossary term (that is: "aragonite" and "aragonite saturation")
# if it is a subset, we want to identify the longer term (so that we don't put the tooltip for the
# shorter term with the longer term). Here is why the prior alphabetizing of the glossary matters
glossary_match = glossary$term[startsWith (glossary$term, search_term)]
if (length(glossary_match)>1){
longer_term = glossary_match[1]
}
# let's go through every line of the markdown file looking for glossary words. We are skipping the first several
# lines in order to avoid putting any tooltips in the modal window description
for (i in 12:length(tx)) {
# We want to avoid putting in tooltips in several situations that would cause the window to break.
# 1. No tooltips on tabs (that is what the searching for "#" takes care of)
# 2. No tooltips in the gray bar above the image (that is what the searching for the "</i>" and "</div> tags
# take care of)
# 3. No tooltips on lines where there is a link for a data download
# 4. No tooltips on lines that create interactive graphs (no line starting with "<script")
if (substr(tx[i],1,1) != "#" && stringr::str_sub(tx[i],-4) != "</i>" && stringr::str_sub(tx[i],-5) != "</div>" && substr(tx[i], 1, 24) != "Download timeseries data" && substr(tx[i], 1, 7) != "<script"){
# We also want to avoid inserting tooltips into the path of the image file, which is what the following
# image_start is looking for. If a line does contain an image path, we want to separate that from the rest of
# the line, do a glossary word replace on the image-less line, and then - later in this code - paste the image back on to the line
image_start = regexpr(pattern = "/img/cinms_cr", text = tx[i])[1] - 4
if (image_start > 1) {
line_content = substr(tx[i], 1, image_start)
image_link = stringr::str_sub(tx[i], -(nchar(tx[i])-image_start))
}
else {
line_content = tx[i]
}
# here is where we keep track of whether a glossary word shows up in the modal window - this will be used later
if (grepl(pattern = search_term, x = line_content, ignore.case = TRUE) ==TRUE){
flag = 1
}
# If the text contains a glossary term that is a shorter subset of another glossary term, we first
# split the text by the longer glossary term and separately save the longer glossary terms (to preserve
# the pattern of capitalization). We then run the split text through the tooltip function to add the required
# span tags around the glossary terms and then paste the split text back together
if (length(glossary_match)>1){
split_text_longer <- stringr::str_split(line_content, stringr::regex(longer_term, ignore_case = TRUE))[[1]]
save_glossary_terms_longer <- c(stringr::str_extract_all(line_content, stringr::regex(longer_term, ignore_case = TRUE))[[1]],"")
for (s in 1:length(split_text_longer)){
split_text_longer[s] <- insert_tooltip(split_text_longer[s], search_term, span_definition)
}
line_content<- paste0(split_text_longer, save_glossary_terms_longer, collapse="")
}
else {
# In the case that the glossary term is not a shorter subset, life is much easier. We just run the line of content
# through the insert tooltip function
line_content <- insert_tooltip(line_content, search_term, span_definition)
}
# if we separated the image path, let's paste it back on
if (image_start > 1) {
tx[i] = paste0(line_content, image_link)
}
else {
tx[i] = line_content
}
}
}
#if a glossary word was found in a modal window, let's add the javascript for that tooltip in
if (flag == 1){
script_tooltip = paste0(script_tooltip, '<script>tippy ("#tooltip', q, '",{content: "', glossary$definition[q], '"});</script>\r\n')
}
}
# let's replace the markdown file with the modified version of the markdown file that contains all of the tooltip stuff
# (if any)
writeLines(tx, con=md_out)
# if any glossary words are found, let's add in the javascript needed to make this all go
if (script_tooltip != ""){
load_script=' <script src="https://unpkg.com/@popperjs/core@2"></script><script src="https://unpkg.com/tippy.js@6"></script>\r\n'
write( load_script, file=md_out, append=TRUE)
write(script_tooltip, file=md_out, append=TRUE)
}
}
}
#' Create new site from template
#'
#' This function creates a new website from a template stored within the package.
#'
#' @param path The directory path where the new site should be located.
#' @return The output is a directory containing the template version of a site.
#' @export
#' @examples \dontrun{
#' infographiq_template("test_location")
#' }
#'
infographiq_template <- function(path){
if (dir.exists(path)){
stop(paste("Error: the directory -", path, "- already exists."))
}
dir_template <- system.file("template_website", package = "infographiqR")
file.copy(dir_template, dirname(path), recursive = T)
dir_tmp <- file.path(dirname(path), basename(dir_template))
file.rename(dir_tmp, path)
}
#' Insert tooltips into text.
#'
#' The purpose of the following function is, for a provided section of text, to
#' insert the required tooltip css around a provided glossary term. The function
#' preserves the pattern of capitalization of the glossary term that already exists.
#' This function is used by the function glossarize_md also described in this
#' package.
#'
#' @param text The section of text where tooltips are to be added.
#' @param glossary_term The glossary term to be looked for.
#' @param span_css The css tags to add before the glossary term.
#' @return The function outputs a string containing the text section with html tags inserted.
#
insert_tooltip<- function(text, glossary_term, span_css){
# We start by splitting the text by the glossary term and then separately saving the glossary terms. This is done
# so that we can preserve the pattern of capitalization of the glossary term
split_text <- stringr::str_split(text, stringr::regex(glossary_term, ignore_case = TRUE))[[1]]
save_glossary_terms <- c(stringr::str_extract_all(text, stringr::regex(glossary_term, ignore_case = TRUE))[[1]],"")
# Let's go through every section of the split text and add the required css tags
for (q in 1:length(split_text)){
if (q>1){
split_text[q] = paste0("</span>", split_text[q])
}
if (q<length(split_text)){
split_text[q] = paste0(split_text[q], span_css)
}
}
# put the split text and the glossary terms back together again and then return that as the output
return (paste0(split_text, save_glossary_terms, collapse=""))
}
#' Generate the caption for a figure
#'
#' This function generates either a short or expanded caption for a given figure.
#'
#' @param title The name of a figure.
#' @param md The md file containing the list of captions.
#' @param get_details A Boolean variable indicating whether a short or expanded caption is required.
#' @param fig_in_report A Boolean variable indicating whether the figure described in the caption is present in the condition report.
#' @return A string containing the caption, with html tags inserted.
#' @export
#' @examples \dontrun{
#' md_caption("Figure Ux.Ocean.SST.ERD.map.", get_details = T)
#' }
#'
md_caption <- function(title, md = here::here("modals/_captions.md"), get_details = F, fig_in_report = T){
stopifnot(file.exists(md))
tbl <- tibble::tibble(
# read lines of markdown in _captions.md
ln = readLines(md) %>% stringr::str_trim()) %>%
# detect header with title, set rest to NA
dplyr::mutate(
is_hdr = stringr::str_detect(
ln,
glue::glue('^## {stringr::str_replace_all(title, stringr::fixed("."), "\\\\.")}'))
%>% dplyr::na_if(FALSE)) %>%
# fill down so capturing all starting with title header
tidyr::fill(is_hdr) %>%
# filter for title header down, removing previous lines
dplyr::filter(is_hdr) %>%
# remove title header
dplyr::slice(-1) %>%
# detect subsequent headers
dplyr::mutate(
is_hdr = stringr::str_detect(ln, "^## ") %>% dplyr::na_if(F)) %>%
# fill down
tidyr::fill(is_hdr) %>%
dplyr::mutate(
is_hdr = tidyr::replace_na(is_hdr, FALSE)) %>%
# filter for not header down, removing subsequent lines outside caption
dplyr::filter(!is_hdr) %>%
# replace links in markdown with html to open in new tab
dplyr::mutate(
ln = stringr::str_replace_all(ln, "\\[(.*?)\\]\\((.*?)\\)", "<a href='\\2' target='_blank'>\\1</a>")) %>%
# details
dplyr::mutate(
is_details = stringr::str_detect(ln, "^### Details") %>% dplyr::na_if(F)) %>%
# fill down
tidyr::fill(is_details)
simple_md <- tbl %>%
dplyr::filter(is.na(is_details)) %>%
dplyr::filter(ln != "") %>%
dplyr::pull(ln) %>%
paste0(collapse = "\n") %>%
stringr::str_trim()
# Remove spaces around figure title.
title <- stringr::str_trim(title)
# If the last character of the figure title is a period, delete it. This will
# improve how the title looks when embedded into the text.
if (substring(title, nchar(title))=="."){
title<- substring(title,0,nchar(title)-1)
}
# If figure is in condition report, append figure title (like App.F.13.2) to the
# end of expanded figure caption and add link to condition report
if (fig_in_report == T) {
expanded_caption = paste('<details>\n <summary>Click for Details</summary>\n\\1 For more information, consult', title,
'in the [CINMS 2016 Condition Report](https://nmssanctuaries.blob.core.windows.net/sanctuaries-prod/media/docs/2016-condition-report-channel-islands-nms.pdf){target="_blank"}.</details>')
} else {
expanded_caption = '<details>\n <summary>Click for Details</summary>\n\\1</details>'
}
details_md <- tbl %>%
dplyr::filter(is_details) %>%
dplyr::filter(ln != "") %>%
dplyr::pull(ln) %>%
paste0(collapse = "\n") %>%
stringr::str_replace("### Details\n(.*)", expanded_caption) %>%
stringr::str_trim()
if (get_details == T){
return(details_md)
} else {
return(simple_md)
}
}
#' Render all rmd files in the modals folder that have been changed
#'
#' @param nms The NMS sanctuary with only "cinms" currently doing anything.
#' @param interactive_only A Boolean variable indicating whether only rmd files containing interactive figures should be rendered. NOTE: If this is set to "TRUE", the rmd files containing interactive figures with MARINe data will be omitted. These latter figures can only be rendered in a local environment as they require connection to a shared Google Drive that is accessed via Google Drive File Stream.
#' @param render_all A Boolean variable indicating whether all rmd files should be rendered, whether or not there have been changes to them.
#' @export
#' @return The function outputs a html file for every rmd file in the modals folder.
#' @examples \dontrun{
#' render_all_rmd(interactive_only = T)
#' }
#'
render_all_rmd <- function (nms = "cinms", interactive_only = F, render_all = F){
# Let's figure out where we are. In my local environment, I am in the directory for
# the sanctuary. In a docker container though, I won't be. So the following section of
# code attempts to put us in the right directory if we aren't there already.
location <- here::here()
start_point <- nchar(location) - nchar(nms) +1
if (!(substr(location, start_point, nchar(location)) == nms)){
location <- paste(location, nms, sep = "/")
}
modal_dir<- paste0(location,"/modals/")
# let's get a list of all rmd files in the directory
modal_list<-list.files(path = modal_dir, pattern = ".Rmd", ignore.case = TRUE)
# Now, let's generate a list of rmd files that need to be skipped.
if (nms == "cinms"){
modal_list <- modal_list[!modal_list %in% "_key-climate-ocean.Rmd"]
interactive_rmd <- c("deep-seafloor_key-climate-ocean.Rmd",
"forage-assemblage.Rmd",
"forage-fish.Rmd",
"forage-inverts.Rmd",
"kelp-forest_key-climate-ocean.Rmd",
"key-climate-ocean.Rmd",
"pelagic_key-climate-ocean.Rmd",
"rocky-shore_key-climate-ocean.Rmd",
"sandy-beach_key-climate-ocean.Rmd",
"sandy-seafloor_key-climate-ocean.Rmd")
}
if (interactive_only==T) {
modal_list <-interactive_rmd
}
modal_list<-paste0(modal_dir,modal_list)
# The following section of code checks to see if there has been any change to
# the google spreadsheet cinms_content. If there has, we'll want to render all of the modal
# windows to account for changes to cinms_content
# Let's set a flag for whether the spreadsheet has changed
cinms_content_changed = FALSE
if (interactive_only==F) { # We only want to go through this process if we are going through every rmd file
# The sheets of the google spreadsheet
sheet_names <- c("info_modal_links", "info_figure_links", "glossary")
#The url of the google spreadsheet
cinms_content_url = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet="
# Let's go through all three sheets
for (i in 1:3){
# Save the new version of the sheet
sheet_url = paste0(cinms_content_url, sheet_names[i])
new_sheet <- read.csv(sheet_url)
new_filename <- paste0(here::here("data/saved_cinms_content/new_"),sheet_names[i], ".csv")
write.csv(new_sheet, file = new_filename)
# Check to see if the new version of the sheet matches the saved version, if it doesn't
# change cinms_content_changed to TRUE
saved_filename <- paste0(here::here("data/saved_cinms_content/saved_"),sheet_names[i], ".csv")
if (tools::md5sum(new_filename) != tools::md5sum(saved_filename)){
cinms_content_changed = TRUE
file.copy(new_filename, saved_filename, overwrite = TRUE)
}
file.remove (new_filename)
}
}
# let's go through every rmd file to be worked on
for (i in 1:length(modal_list)){
# let's check if the rmd file has changed since the last rendered version of
# the html was created
htm <- fs::path_ext_set(modal_list[i], "html")
if (file.exists(htm)){
rmd_newer <- fs::file_info(modal_list[i])$modification_time > fs::file_info(htm)$modification_time
} else {
rmd_newer <- T
}
# Render the modal window if:
# 1. the associated google spreadsheet has changed or
# 2. if the modal window contains interactive figures or
# 3. if the Rmd file has been recently modified or
# 4. if the function parameter "render_all" has been set to TRUE
if (rmd_newer | cinms_content_changed | basename(modal_list[i]) %in% interactive_rmd | render_all){
generate_html_4_rmd(modal_list[i])
}
}
}
#' Produce full html for static figures, minus tooltips.
#'
#' This is a function that generates the html to display a static figure and the
#' captions for that figure. Glossary tooltips are not created here, as that
#' occurs at a later stage of the html production process.
#'
#' @param figure_id The id of the figure.
#' @param figure_img The path of the figure image.
#' @return The output is a string containing the html tags to display the figure and figure caption.
#' @export
#' @examples \dontrun{
#' render_figure("Figure App.C.4.4.", "../img/cinms_cr/App.C.4.4.Leeworthy_landings.jpg")
#' }
#'
render_figure <- function(figure_id, figure_img){
glue::glue(
"
{get_figure_info(figure_id)}
{md_caption(figure_id, get_details=T)}
")
}
#' Render html for rmd file, including glossary tooltips.
#'
#' This function creates all of the html for a R markdown file, inserting in the
#' glossary tooltips. Note that this function will break html that contains interactive
#' figures, as most of the required javascript won't be loaded into the html <head>.
#'
#' @param rmd The R markdown file to be rendered into html.
#' @return The output is a html file that is the rendered rmd file.
#' @examples \dontrun{
#' rmd2html(here::here("modals/ca-sheephead.Rmd"))
#' }
rmd2html <- function(rmd){
md1 <- fs::path_ext_set(rmd, "md")
md2 <- paste0(fs::path_ext_remove(rmd), ".glossarized.md")
htm1 <- paste0(fs::path_ext_remove(rmd), ".glossarized.html")
htm2 <- fs::path_ext_set(rmd, "html")
# create the intermediary markdown file (with disposable html)
rmarkdown::render(
rmd, output_file = htm1,
output_format = "html_document",
output_options = list(self_contained = F, keep_md = T))
# glossarize
glossarize_md(md2, md2)
# create the final html file
rmarkdown::render(
md2, output_file = htm2,
output_format = "html_document",
output_options = list(self_contained = F), clean = F)
# final cleanup
file.remove(htm1)
file.remove(md2)
file.remove(paste0(substring(md2,1,stringr::str_length(md2)-3),".utf8.md"))
}
marinebon/infographiqR documentation built on Dec. 21, 2021, 2:44 p.m.
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Defines functions rmd2html render_figure md_caption insert_tooltip infographiq_template glossarize_md get_modal_info
Documented in get_modal_info glossarize_md infographiq_template insert_tooltip md_caption render_figure rmd2html
#' Generate the html for R markdown files
#'
#' Rmd files with interactive figures present a special problem in terms of rendering
#' them into html. The problem is that, if one uses the markdown library to
#' create the html, the figures will turn out fine but the glossary tooltip functionality
#' will be missing. This tooltip functionality is created by the function rmd2html,
#' described in this package. If one uses rmd2html to render a rmd file containing
#' interactive figures, the tooltips will turn out fine but the figures won't show
#' up. The problem with rmd2html is that the appropriate javascript libraries are
#' not loaded into the resulting <head> section of the final html. This function
#' solves the problem (thereby producing html with both working figures and tooltips)
#' by rendering the rmd using both the markdown and rmd2html approaches and then rewriting
#' the <head> section of the rmd2html version with the markdown version.
#'
#' @param target_rmd The R markdown file to be rendered
#' @param nms The NMS sanctuary, with only "cinms" currently doing anything.
#' @return The function outputs a html file that is the rendered version of the input rmd file.
#' @export
#' @examples \dontrun{
#' generate_html_4_rmd(here::here("modals/tar.Rmd"))
#' }
#'
generate_html_4_rmd <- function (target_rmd, nms = "cinms"){
# the following mini-function where_is_head has two simple purposes. When fed in a html file, which has already been brought in
# to R via readLines, the function will tell you the line number of the html file that contains "</html>" and
# the total number of lines in the file
where_is_head <-function(input_lines){
i<-1
while (!(input_lines[i]=="</head>")){
i <-i + 1
}
output_list <- list("total_lines" = length(input_lines), "head_line" = i)
return(output_list)
}
# Let's figure out where we are. In my local environment, I am in the directory for
# the sanctuary. In a docker container though, I won't be. So the following section of
# code attempts to put us in the right directory if we aren't there already.
location <- here::here()
start_point <- nchar(location) - nchar(nms) +1
if (!(substr(location, start_point, nchar(location)) == nms)){
location <- paste(location, nms, sep = "/")
}
modal_dir<- paste0(location,"/modals/")
# for a given rmd file, let's generate the html for it in two ways. Way 1 is via
# rmd2html which gives us the glossary tooltip working right (but where the interactive
# figures don't work). Way 2 is via render which gives us the interactive figures working
# right (but where the glossary tooltip doesn't work)
rmd2html(target_rmd)
rmarkdown::render(target_rmd, output_file = paste(modal_dir, "temp_file.html", sep ="/"))
# We want both the interactive figures and the glossary tooltip working in the html. The way to do
# that is to grab everything in the <head> section of the html produced by render and then
# to replace the <head> section of the html produced by rmd2html with that. The first step
# here is to read in the two html files
target_html <- gsub("Rmd", "html", target_rmd, ignore.case = TRUE)
target_lines <- readLines(target_html)
replacement_path <- paste0(modal_dir,"temp_file.html")
replacement_lines <- readLines(replacement_path)
# Next, let's figure out where the <head> section ends in each html file
target_location <- where_is_head(target_lines)
replacement_location <-where_is_head(replacement_lines)
# Now, let's replace the <head> section and save the new version of the html
output_file = c(replacement_lines[1:replacement_location$head_line],target_lines[(target_location$head_line+1):target_location$total_lines])
write(output_file, file = target_html)
# let's delete the temp html file that we created
file.remove(paste(modal_dir, "temp_file.html", sep ="/"))
}
#' Generate hyperlinked gray bar above figure
#'
#' The purpose of this function is to generate the hyperlinks for the monitoring program and data
#' associated with a figure and then to insert them into a gray bar above the figure in the modal window.
#'
#' @param figure_id The name of a row in the following google sheet cinms_content::info_figure_links
#' @return The output is a set of html tags to be inserted into a html file.
#' @export
#' @examples \dontrun{
#' get_figure_info("Figure App.E.11.8.")
#' }
#'
get_figure_info <- function (figure_id){
info_csv = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet=info_figure_links"
d <- readr::read_csv(info_csv) %>%
dplyr::filter(md_caption == figure_id)
if (nrow(d) == 0){
warning(paste("Need link in cinms_content:info_figure_links Google Sheet for", figure_id))
return("")
}
html <- NULL
no_ws <- c("before","after","outside","after-begin","before-end")
icons <- tibble::tribble(
~description_bkup , ~css, ~icon, ~fld_url, ~fld_description,
"Monitoring Program", "left", "clipboard-list", "url_monitoring", "title_monitoring",
"Data" , "right", "database" , "url_data", "title_data")
for (i in 1:nrow(icons)){ # i=1
h <- icons[i,]
url <- d[h$fld_url]
description <- d[h$fld_description]
if(!is.na(url) & substr(url,0,4) == "http"){
if (is.na(description)){
description <- h$description_bkup
} else {
description <- substr(stringr::str_trim(description), 0, 45)
}
html <- shiny::tagList(
html,
htmltools::div(
.noWS = no_ws,
style = glue::glue("text-align:{h$css}; display:table-cell;"),
htmltools::a(
.noWS = no_ws,
href = url, target = '_blank',
shiny::icon(h$icon), description)))
}
}
if (is.null(html))
return("")
shiny::tagList(
htmltools::div(
.noWS = no_ws,
style = "background:LightGrey; width:100%; display:table; font-size:120%; padding: 10px 10px 10px 10px; margin-bottom: 10px;",
htmltools::div(
.noWS = no_ws,
style = "display:table-row",
html)))
}
#' Generate introductory info for the html of a modal window
#'
#' This function generates the html tags for the top portion of a rmd modal window,
#' containing the introductory information about that window. This function only
#' will work within a rmd file to be knitted.
#'
#' @param rmd The name of an input file passed to knit().
#' @param info_modal_links_csv A hyperlink to the google sheet, in csv format, that contains the modal links info.
#' @return The function returns a string that is a set of html tags to be inserted into a html file.
#' @export
#' @examples \dontrun{
#' get_modal_info(info_modal_links_csv = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet=info_modal_links")
#' }
#'
get_modal_info <- function(rmd = knitr::current_input(), info_modal_links_csv){
modal_id <- basename(fs::path_ext_remove(rmd))
row <- readr::read_csv(info_modal_links_csv) %>%
dplyr::filter(modal == modal_id)
if (nrow(row) == 0) stop("Need link in cinms_content:info_modal_links Google Sheet!")
icons_html = NULL
if (!is.na(row$url_info)){
icons_html =
htmltools::a(shiny::icon("info-circle"), href=row$url_info, target='_blank')
}
if (!is.na(row$url_photo)){
icons_html = htmltools::tagList(
icons_html,
htmltools::a(shiny::icon("camera"), href=row$url_photo, target='_blank'))
}
htmltools::div(
htmltools::div(htmltools::tagList(icons_html), style = "margin-top: 10px;margin-bottom: 10px; margin-right: 10px; flex: 1;"), htmltools::div(
ifelse(!is.na(row$tagline), row$tagline, ""), style = "margin: 10px; font-style: italic; flex: 20; "), style="display: flex"
)
}
#' Insert html tags for glossary tooltips into md files
#'
#' The purpose of this function is to insert the html tags required for glossary
#' tooltip functionality into a given markdown file. The function glossarize_md
#' is used by the function rmd2html described in this package.
#'
#' @param md The markdown file where the tags are to be inserted.
#' @param md_out The markdown output file.
#' @return The output of this function is html tags inserted into a markdown file.
glossarize_md <- function(md, md_out = md){
# read the markdown file
tx <- readLines(md)
# only go forward with the glossarizing if the file contains more than "data to be added soon"
if (length(tx) > 12) {
# load in the glossary that will be used to create the tooltips. Reverse alphabetize the glossary, which will come in handy later
glossary_csv = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet=glossary"
glossary <- readr::read_csv(glossary_csv)
glossary <- glossary[order(glossary$term, decreasing = TRUE),]
# initialize the string variable that will hold the javascript tooltip
script_tooltip = ""
# go through each row of the glossary
for (q in 1:nrow(glossary)) {
# set a variable to zero that is used to keep track of whether a particular glossary word is in the modal window
flag = 0
# load in a specific glossary term
search_term = glossary$term[q]
# the css to be wrapped around any glossary word
span_definition = paste0('<span aria-describedby="tooltip', q, '" tabindex="0" style="border-bottom: 1px dashed #000000; font-size:100%" id="tooltip', q, '">')
# let's look to see if the glossary term is a subset of a longer glossary term (that is: "aragonite" and "aragonite saturation")
# if it is a subset, we want to identify the longer term (so that we don't put the tooltip for the
# shorter term with the longer term). Here is why the prior alphabetizing of the glossary matters
glossary_match = glossary$term[startsWith (glossary$term, search_term)]
if (length(glossary_match)>1){
longer_term = glossary_match[1]
}
# let's go through every line of the markdown file looking for glossary words. We are skipping the first several
# lines in order to avoid putting any tooltips in the modal window description
for (i in 12:length(tx)) {
# We want to avoid putting in tooltips in several situations that would cause the window to break.
# 1. No tooltips on tabs (that is what the searching for "#" takes care of)
# 2. No tooltips in the gray bar above the image (that is what the searching for the "</i>" and "</div> tags
# take care of)
# 3. No tooltips on lines where there is a link for a data download
# 4. No tooltips on lines that create interactive graphs (no line starting with "<script")
if (substr(tx[i],1,1) != "#" && stringr::str_sub(tx[i],-4) != "</i>" && stringr::str_sub(tx[i],-5) != "</div>" && substr(tx[i], 1, 24) != "Download timeseries data" && substr(tx[i], 1, 7) != "<script"){
# We also want to avoid inserting tooltips into the path of the image file, which is what the following
# image_start is looking for. If a line does contain an image path, we want to separate that from the rest of
# the line, do a glossary word replace on the image-less line, and then - later in this code - paste the image back on to the line
image_start = regexpr(pattern = "/img/cinms_cr", text = tx[i])[1] - 4
if (image_start > 1) {
line_content = substr(tx[i], 1, image_start)
image_link = stringr::str_sub(tx[i], -(nchar(tx[i])-image_start))
}
else {
line_content = tx[i]
}
# here is where we keep track of whether a glossary word shows up in the modal window - this will be used later
if (grepl(pattern = search_term, x = line_content, ignore.case = TRUE) ==TRUE){
flag = 1
}
# If the text contains a glossary term that is a shorter subset of another glossary term, we first
# split the text by the longer glossary term and separately save the longer glossary terms (to preserve
# the pattern of capitalization). We then run the split text through the tooltip function to add the required
# span tags around the glossary terms and then paste the split text back together
if (length(glossary_match)>1){
split_text_longer <- stringr::str_split(line_content, stringr::regex(longer_term, ignore_case = TRUE))[[1]]
save_glossary_terms_longer <- c(stringr::str_extract_all(line_content, stringr::regex(longer_term, ignore_case = TRUE))[[1]],"")
for (s in 1:length(split_text_longer)){
split_text_longer[s] <- insert_tooltip(split_text_longer[s], search_term, span_definition)
}
line_content<- paste0(split_text_longer, save_glossary_terms_longer, collapse="")
}
else {
# In the case that the glossary term is not a shorter subset, life is much easier. We just run the line of content
# through the insert tooltip function
line_content <- insert_tooltip(line_content, search_term, span_definition)
}
# if we separated the image path, let's paste it back on
if (image_start > 1) {
tx[i] = paste0(line_content, image_link)
}
else {
tx[i] = line_content
}
}
}
#if a glossary word was found in a modal window, let's add the javascript for that tooltip in
if (flag == 1){
script_tooltip = paste0(script_tooltip, '<script>tippy ("#tooltip', q, '",{content: "', glossary$definition[q], '"});</script>\r\n')
}
}
# let's replace the markdown file with the modified version of the markdown file that contains all of the tooltip stuff
# (if any)
writeLines(tx, con=md_out)
# if any glossary words are found, let's add in the javascript needed to make this all go
if (script_tooltip != ""){
load_script=' <script src="https://unpkg.com/@popperjs/core@2"></script><script src="https://unpkg.com/tippy.js@6"></script>\r\n'
write( load_script, file=md_out, append=TRUE)
write(script_tooltip, file=md_out, append=TRUE)
}
}
}
#' Create new site from template
#'
#' This function creates a new website from a template stored within the package.
#'
#' @param path The directory path where the new site should be located.
#' @return The output is a directory containing the template version of a site.
#' @export
#' @examples \dontrun{
#' infographiq_template("test_location")
#' }
#'
infographiq_template <- function(path){
if (dir.exists(path)){
stop(paste("Error: the directory -", path, "- already exists."))
}
dir_template <- system.file("template_website", package = "infographiqR")
file.copy(dir_template, dirname(path), recursive = T)
dir_tmp <- file.path(dirname(path), basename(dir_template))
file.rename(dir_tmp, path)
}
#' Insert tooltips into text.
#'
#' The purpose of the following function is, for a provided section of text, to
#' insert the required tooltip css around a provided glossary term. The function
#' preserves the pattern of capitalization of the glossary term that already exists.
#' This function is used by the function glossarize_md also described in this
#' package.
#'
#' @param text The section of text where tooltips are to be added.
#' @param glossary_term The glossary term to be looked for.
#' @param span_css The css tags to add before the glossary term.
#' @return The function outputs a string containing the text section with html tags inserted.
#
insert_tooltip<- function(text, glossary_term, span_css){
# We start by splitting the text by the glossary term and then separately saving the glossary terms. This is done
# so that we can preserve the pattern of capitalization of the glossary term
split_text <- stringr::str_split(text, stringr::regex(glossary_term, ignore_case = TRUE))[[1]]
save_glossary_terms <- c(stringr::str_extract_all(text, stringr::regex(glossary_term, ignore_case = TRUE))[[1]],"")
# Let's go through every section of the split text and add the required css tags
for (q in 1:length(split_text)){
if (q>1){
split_text[q] = paste0("</span>", split_text[q])
}
if (q<length(split_text)){
split_text[q] = paste0(split_text[q], span_css)
}
}
# put the split text and the glossary terms back together again and then return that as the output
return (paste0(split_text, save_glossary_terms, collapse=""))
}
#' Generate the caption for a figure
#'
#' This function generates either a short or expanded caption for a given figure.
#'
#' @param title The name of a figure.
#' @param md The md file containing the list of captions.
#' @param get_details A Boolean variable indicating whether a short or expanded caption is required.
#' @param fig_in_report A Boolean variable indicating whether the figure described in the caption is present in the condition report.
#' @return A string containing the caption, with html tags inserted.
#' @export
#' @examples \dontrun{
#' md_caption("Figure Ux.Ocean.SST.ERD.map.", get_details = T)
#' }
#'
md_caption <- function(title, md = here::here("modals/_captions.md"), get_details = F, fig_in_report = T){
stopifnot(file.exists(md))
tbl <- tibble::tibble(
# read lines of markdown in _captions.md
ln = readLines(md) %>% stringr::str_trim()) %>%
# detect header with title, set rest to NA
dplyr::mutate(
is_hdr = stringr::str_detect(
ln,
glue::glue('^## {stringr::str_replace_all(title, stringr::fixed("."), "\\\\.")}'))
%>% dplyr::na_if(FALSE)) %>%
# fill down so capturing all starting with title header
tidyr::fill(is_hdr) %>%
# filter for title header down, removing previous lines
dplyr::filter(is_hdr) %>%
# remove title header
dplyr::slice(-1) %>%
# detect subsequent headers
dplyr::mutate(
is_hdr = stringr::str_detect(ln, "^## ") %>% dplyr::na_if(F)) %>%
# fill down
tidyr::fill(is_hdr) %>%
dplyr::mutate(
is_hdr = tidyr::replace_na(is_hdr, FALSE)) %>%
# filter for not header down, removing subsequent lines outside caption
dplyr::filter(!is_hdr) %>%
# replace links in markdown with html to open in new tab
dplyr::mutate(
ln = stringr::str_replace_all(ln, "\\[(.*?)\\]\\((.*?)\\)", "<a href='\\2' target='_blank'>\\1</a>")) %>%
# details
dplyr::mutate(
is_details = stringr::str_detect(ln, "^### Details") %>% dplyr::na_if(F)) %>%
# fill down
tidyr::fill(is_details)
simple_md <- tbl %>%
dplyr::filter(is.na(is_details)) %>%
dplyr::filter(ln != "") %>%
dplyr::pull(ln) %>%
paste0(collapse = "\n") %>%
stringr::str_trim()
# Remove spaces around figure title.
title <- stringr::str_trim(title)
# If the last character of the figure title is a period, delete it. This will
# improve how the title looks when embedded into the text.
if (substring(title, nchar(title))=="."){
title<- substring(title,0,nchar(title)-1)
}
# If figure is in condition report, append figure title (like App.F.13.2) to the
# end of expanded figure caption and add link to condition report
if (fig_in_report == T) {
expanded_caption = paste('<details>\n <summary>Click for Details</summary>\n\\1 For more information, consult', title,
'in the [CINMS 2016 Condition Report](https://nmssanctuaries.blob.core.windows.net/sanctuaries-prod/media/docs/2016-condition-report-channel-islands-nms.pdf){target="_blank"}.</details>')
} else {
expanded_caption = '<details>\n <summary>Click for Details</summary>\n\\1</details>'
}
details_md <- tbl %>%
dplyr::filter(is_details) %>%
dplyr::filter(ln != "") %>%
dplyr::pull(ln) %>%
paste0(collapse = "\n") %>%
stringr::str_replace("### Details\n(.*)", expanded_caption) %>%
stringr::str_trim()
if (get_details == T){
return(details_md)
} else {
return(simple_md)
}
}
#' Render all rmd files in the modals folder that have been changed
#'
#' @param nms The NMS sanctuary with only "cinms" currently doing anything.
#' @param interactive_only A Boolean variable indicating whether only rmd files containing interactive figures should be rendered. NOTE: If this is set to "TRUE", the rmd files containing interactive figures with MARINe data will be omitted. These latter figures can only be rendered in a local environment as they require connection to a shared Google Drive that is accessed via Google Drive File Stream.
#' @param render_all A Boolean variable indicating whether all rmd files should be rendered, whether or not there have been changes to them.
#' @export
#' @return The function outputs a html file for every rmd file in the modals folder.
#' @examples \dontrun{
#' render_all_rmd(interactive_only = T)
#' }
#'
render_all_rmd <- function (nms = "cinms", interactive_only = F, render_all = F){
# Let's figure out where we are. In my local environment, I am in the directory for
# the sanctuary. In a docker container though, I won't be. So the following section of
# code attempts to put us in the right directory if we aren't there already.
location <- here::here()
start_point <- nchar(location) - nchar(nms) +1
if (!(substr(location, start_point, nchar(location)) == nms)){
location <- paste(location, nms, sep = "/")
}
modal_dir<- paste0(location,"/modals/")
# let's get a list of all rmd files in the directory
modal_list<-list.files(path = modal_dir, pattern = ".Rmd", ignore.case = TRUE)
# Now, let's generate a list of rmd files that need to be skipped.
if (nms == "cinms"){
modal_list <- modal_list[!modal_list %in% "_key-climate-ocean.Rmd"]
interactive_rmd <- c("deep-seafloor_key-climate-ocean.Rmd",
"forage-assemblage.Rmd",
"forage-fish.Rmd",
"forage-inverts.Rmd",
"kelp-forest_key-climate-ocean.Rmd",
"key-climate-ocean.Rmd",
"pelagic_key-climate-ocean.Rmd",
"rocky-shore_key-climate-ocean.Rmd",
"sandy-beach_key-climate-ocean.Rmd",
"sandy-seafloor_key-climate-ocean.Rmd")
}
if (interactive_only==T) {
modal_list <-interactive_rmd
}
modal_list<-paste0(modal_dir,modal_list)
# The following section of code checks to see if there has been any change to
# the google spreadsheet cinms_content. If there has, we'll want to render all of the modal
# windows to account for changes to cinms_content
# Let's set a flag for whether the spreadsheet has changed
cinms_content_changed = FALSE
if (interactive_only==F) { # We only want to go through this process if we are going through every rmd file
# The sheets of the google spreadsheet
sheet_names <- c("info_modal_links", "info_figure_links", "glossary")
#The url of the google spreadsheet
cinms_content_url = "https://docs.google.com/spreadsheets/d/1yEuI7BT9fJEcGAFNPM0mCq16nFsbn0b-bNirYPU5W8c/gviz/tq?tqx=out:csv&sheet="
# Let's go through all three sheets
for (i in 1:3){
# Save the new version of the sheet
sheet_url = paste0(cinms_content_url, sheet_names[i])
new_sheet <- read.csv(sheet_url)
new_filename <- paste0(here::here("data/saved_cinms_content/new_"),sheet_names[i], ".csv")
write.csv(new_sheet, file = new_filename)
# Check to see if the new version of the sheet matches the saved version, if it doesn't
# change cinms_content_changed to TRUE
saved_filename <- paste0(here::here("data/saved_cinms_content/saved_"),sheet_names[i], ".csv")
if (tools::md5sum(new_filename) != tools::md5sum(saved_filename)){
cinms_content_changed = TRUE
file.copy(new_filename, saved_filename, overwrite = TRUE)
}
file.remove (new_filename)
}
}
# let's go through every rmd file to be worked on
for (i in 1:length(modal_list)){
# let's check if the rmd file has changed since the last rendered version of
# the html was created
htm <- fs::path_ext_set(modal_list[i], "html")
if (file.exists(htm)){
rmd_newer <- fs::file_info(modal_list[i])$modification_time > fs::file_info(htm)$modification_time
} else {
rmd_newer <- T
}
# Render the modal window if:
# 1. the associated google spreadsheet has changed or
# 2. if the modal window contains interactive figures or
# 3. if the Rmd file has been recently modified or
# 4. if the function parameter "render_all" has been set to TRUE
if (rmd_newer | cinms_content_changed | basename(modal_list[i]) %in% interactive_rmd | render_all){
generate_html_4_rmd(modal_list[i])
}
}
}
#' Produce full html for static figures, minus tooltips.
#'
#' This is a function that generates the html to display a static figure and the
#' captions for that figure. Glossary tooltips are not created here, as that
#' occurs at a later stage of the html production process.
#'
#' @param figure_id The id of the figure.
#' @param figure_img The path of the figure image.
#' @return The output is a string containing the html tags to display the figure and figure caption.
#' @export
#' @examples \dontrun{
#' render_figure("Figure App.C.4.4.", "../img/cinms_cr/App.C.4.4.Leeworthy_landings.jpg")
#' }
#'
render_figure <- function(figure_id, figure_img){
glue::glue(
"
{get_figure_info(figure_id)}
{md_caption(figure_id, get_details=T)}
")
}
#' Render html for rmd file, including glossary tooltips.
#'
#' This function creates all of the html for a R markdown file, inserting in the
#' glossary tooltips. Note that this function will break html that contains interactive
#' figures, as most of the required javascript won't be loaded into the html <head>.
#'
#' @param rmd The R markdown file to be rendered into html.
#' @return The output is a html file that is the rendered rmd file.
#' @examples \dontrun{
#' rmd2html(here::here("modals/ca-sheephead.Rmd"))
#' }
rmd2html <- function(rmd){
md1 <- fs::path_ext_set(rmd, "md")
md2 <- paste0(fs::path_ext_remove(rmd), ".glossarized.md")
htm1 <- paste0(fs::path_ext_remove(rmd), ".glossarized.html")
htm2 <- fs::path_ext_set(rmd, "html")
# create the intermediary markdown file (with disposable html)
rmarkdown::render(
rmd, output_file = htm1,
output_format = "html_document",
output_options = list(self_contained = F, keep_md = T))
# glossarize
glossarize_md(md2, md2)
# create the final html file
rmarkdown::render(
md2, output_file = htm2,
output_format = "html_document",
output_options = list(self_contained = F), clean = F)
# final cleanup
file.remove(htm1)
file.remove(md2)
file.remove(paste0(substring(md2,1,stringr::str_length(md2)-3),".utf8.md"))
}
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