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global.R
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# © Copyright World Health Organization (WHO) 2016.
# This file is part of the Health Equity Assessment Toolkit (HEAT).
# HEAT is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License Version 2 as published by
# the Free Software Foundation.
#
# HEAT is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with HEAT. If not, see http://www.gnu.org/licenses/.
library(shiny)
library(ggplot2)
library(grid)
library(gridExtra)
library(RColorBrewer)
library(dplyr)
library(DT)
library(data.table)
library(readxl)
library(tidyr)
library(stringr)
library(broom)
library(fst)
# highcharts
library(purrr)
library(htmltools)
library(scales)
library(highcharter)
library(shinyBS)
library(viridis)
source("utils/lang.R", local = TRUE)
HEATversion <- "whodata"
toggleHC <- TRUE
read_rds_or_fst <- function(data) {
path_base <- "data"
path_fst <- file.path(path_base, paste0(data, ".fst"))
path_rds <- file.path(path_base, paste0(data, ".RDS"))
if (file.exists(path_fst)) {
read_fst(path_fst)
} else {
# message("[ MESSAGE ] Create ", path_fst, " to use read_fst during startup")
readRDS(path_rds)
}
}
.global <- new.env(parent = emptyenv())
if (HEATversion == "whodata") {
.global$countryinfo <- read_rds_or_fst("countryinfo")
.global$geojson_subnational <- read_rds_or_fst("geojson_subnational")
.global$geojson_national <- read_rds_or_fst("geojson_national")
.global$geojson_disputed <- read_rds_or_fst("geojson_disputed")
.global$strata <- read_rds_or_fst("strata")
.global$dimensions <- read_rds_or_fst("dimensions")
.global$maindata <- read_rds_or_fst("maindata")
.global$inequals <- read_rds_or_fst("inequals")
.global$years <- read_rds_or_fst("years")
.global$subregion_minmax <- read_rds_or_fst("subregion_minmax")
}
# We want the Health indicator name and Summary measure name variables to
# be wider columns. I could not find a way to do this with DT after
# extensive attempts. Instead I forced them wide by adding non-breaking
# spaces. Originally I wrote the forceNonBreakFull function which basically
# would add a series of non-breaking spaces throughout the name with the
# occasional space that would allow the name to break. But this could result
# in some odd situations where you either have very long or relatively short
# breaks. So I re-wrote to add non-breaking spaces only in the first N chars.
forceNonBreak <- function (labels, maxCharPerLine = 14)
{
labels <- as.character(labels)
n = length(labels)
splitX = strsplit(labels, split=" ")
#newLabels = rep("", n)
newLabels = rep("", n)
for (l in 1:n) {
#l <- 1
if(length(splitX[[l]]) == 1 | nchar(splitX[[l]][1])>maxCharPerLine){
finline <- labels[l]
}else{
line <- splitX[[l]]
charsums <- cumsum(nchar(line))
if(all(charsums<=maxCharPerLine)){
finline <- paste(line, collapse = " ")
}else{
below <- charsums[charsums<=maxCharPerLine]
belowMax <- max(below)
indxMax <- which(charsums == belowMax)
longline <- paste(line[1:indxMax], collapse = " ")
rest <- paste(line[(indxMax+1):length(line)], collapse=" ")
finline <- paste(longline, rest, sep=" ")
}
}
newLabels[l] = finline
}
newLabels
}
# Keep this function, see above for description
# forceNonBreakFull <- function (labels, maxCharPerLine = 14, split = " ", fixed = TRUE,
# newsplit = split, keepSplitAtEOL = TRUE)
# {
# #labels <- rep("Births attended by skilled health personnel (in the two or three years preceding the survey) (%)", 3)
# # split <- " "
# # fixed = TRUE
# # maxCharPerLine <- 30
# # newsplit <- " "
# labels <- as.character(labels)
# n = length(labels)
# splitX = strsplit(labels, split = split, fixed = fixed)
# newLabels = rep("", n)
# for (l in 1:n) {
# #l <- 1
# nl = ""
# line = ""
# if (nchar(labels[l]) > 0)
# for (s in 1:length(splitX[[l]])) {
# #s <- 1
# newLen = nchar(line) + nchar(splitX[[l]][s])
# if (nchar(line) < 5 | newLen <= maxCharPerLine) {
# nl = paste(nl, splitX[[l]][s], sep = newsplit)
# line = paste(line, splitX[[l]][s], sep = newsplit)
# }
# else {
# nl = paste(nl, splitX[[l]][s], sep = paste0(if (keepSplitAtEOL)
# newsplit
# else "", " "))
# line = splitX[[l]][s]
# }
# }
# newLabels[l] = nl
# }
# substring(newLabels, nchar(newsplit) + 1)
# }
#
# this is the function for writing the table as CSV or TSV
# with the header lines. I use file() first so that I can
# essentially write.csv and then read.csv to get the formatting
# right and then I add the footnote
# dat is the data, file is the path and sep is the separator
write_table_wcitation <- function(dat, file, sep, citation) {
if (!is.null(dat[["measure_abbr"]])) {
dat$measure_abbr <- toupper(dat$measure_abbr)
}
tmp <- file(encoding = "cp1252")
write.table(dat, tmp, sep = sep, fileEncoding = "cp1252", row.names = FALSE)
dat <- readLines(tmp, encoding = "cp1252")
tmp2 <- file(file, encoding = "cp1252")
citation <- strsplit(citation, "<br>", fixed = TRUE)[[1]]
citation <- if (sep == ",") paste0('"', citation, '"') else citation
cat(c(citation, dat), file = tmp2, sep = "\n")
close(tmp)
close(tmp2)
}
# Function used to add the citation to the plots for download
# it is called in server_downloading. If it' the upload version
# then no citation is added
save_plot_wcitation <- function(file, theplot, citation, heights = c(0.9, 0.1), width = 24, height = 24){
#if(.rdata[['HEATversion']] == "whodata"){
g <- grid.arrange(theplot, citation, ncol=1, nrow=2, heights=heights)
#}else{
# g <- theplot
#}
ggsave(file, g, width=width, height=height, units="cm", limitsize = FALSE, dpi = 320)
}
getISO3 <- function(countryname){
filter(.rdata[['countryinfo']], country==countryname) %>% .$iso3
}
# originally using shinyBS but the modals were not working with
# the new version of Shiny (perhaps because of new bootstrap)
# This is my own code to create a function to create a modal
# allowing for extra tags in the body after the paragraph
bsModal_alt <- function(id, title, trigger, ...){
mo <- tags$div(class = "modal fade", id = id,
`data-trigger` = trigger,
tabindex = "-1",
role = "dialog",
tags$div(class="modal-dialog", role="document",
tags$div(class="modal-content",
tags$div(class = "modal-header",
tags$button(Type = "button", class = "close", `data-dismiss` = "modal", HTML("×")),
tags$h3(title)),
tags$div(class = "modal-body"),
tags$div(class = "modal-footer",
tags$a(href = "#", class = "btn btn-primary",
`data-dismiss` = "modal", icon("times")) #"Close")
)# end modal footer
)#end modal content
)#end modal dialog
)# end modal fade
mo$children[[1]]$children[[1]]$children[[2]] <-
tagAppendChildren(mo$children[[1]]$children[[1]]$children[[2]], list = list(...))
return(mo)
}
# bsModal_alt("myid", "mytrigger", "mytitle",
# tags$p("This is a p"), tags$h3("this is h3"))
#http://stackoverflow.com/questions/11335836/increase-number-of-axis-ticks-in-ggplot2
number_ticks <- function(n) {function(limits) pretty(limits, n)}
# from package (WGCNA)
splitLabels <- function(variable, value){
return(formatLabels(value, maxCharPerLine = 15))
}
splitLabelsWide <- function(variable, value){
return(formatLabels(value, maxCharPerLine = 25))
}
formatLabels <- function(labels, maxCharPerLine = 14, split = " ", fixed = TRUE,
newsplit = split, keepSplitAtEOL = TRUE) {
labels <- as.character(labels)
n <- length(labels)
splitX <- strsplit(labels, split = split, fixed = fixed)
newLabels <- rep("", n)
for (l in 1:n) {
nl <- ""
line <- ""
if (nchar(labels[l]) > 0) {
for (s in 1:length(splitX[[l]])) {
newLen <- nchar(line) + nchar(splitX[[l]][s])
if (nchar(line) < 5 | newLen <= maxCharPerLine) {
nl <- paste(nl, splitX[[l]][s], sep = newsplit)
line <- paste(line, splitX[[l]][s], sep = newsplit)
} else {
nl <- paste(
nl, splitX[[l]][s],
sep = paste0(if (keepSplitAtEOL) newsplit else "", "\n")
)
line <- splitX[[l]][s]
}
}
}
newLabels[l] <- nl
}
substring(newLabels, nchar(newsplit) + 1)
}
textInputRow <-function (inputId, label, value = ""){
# A function to handle the creation of side-by-side numeric input boxes
div(style="display: inline-block;",
tags$label(label, `for` = inputId),
tags$input(id = inputId, type = "text", value = value, class="input-custom"))
}
textPassword <-function (inputId, label, value = ""){
# A function to handle the creation of side-by-side numeric input boxes
div(style="display: inline-block;",
tags$label(label, `for` = inputId),
tags$input(id = inputId, type = "password", value = value, class="input-custom"))
}
myHiddenBoolean <-function (inputId, label, value = ""){
# A function to handle the creation of side-by-side numeric input boxes
div(style="display: none;",
tags$label(label, `for` = inputId),
tags$input(id = inputId, type = "checkbox", value = value, class="input-boolean"))
}
myHiddenText <-function (inputId, label, value = ""){
# A function to handle the creation of side-by-side numeric input boxes
div(style="display: none;",
tags$label(label, `for` = inputId),
tags$input(id = inputId, type = "text", value = value, class="input-text"))
}
####################
# copied from single files
####################
# *****************************
lappend <- function (lst, ...){
# Append an item to a list; e.g.:
# vara <- list("axislimit"=T)
# vara <- lappend(vara, "print"=F)
lst <- c(lst, list(...))
return(lst)
}
# *****************************
is.rank <- function(x){
ranked <- T
if(any(x < 1)){
# The data are not an ordered subgroup
ranked <- F
}
if(all(!x==1)){
# The data are ordered by subgroup, but the base subgroup is missing
ranked <- F
}
return(ranked)
}
# *****************************
notin <- function (vector1, vector2){
# Return the elements in vector1 that are not in vector2
el <- which(!(vector1 %in% vector2)) # svae in 'el' the element-locations on v1 not in v2
if(length(el)==0){ # If there aren't any, return NULL
return(NULL)
}
else{ # Else return the elements
return (vector1[el])
}
}
findCommon <- function(vectora, vectorb){
# Find the health indicators that are common to every year.
# vectora: the list of heath indicators
# vectorb: the years in which the indicators occur
if(length(vectora)!=length(vectorb)){
stop("Vectors must be of the same length")
}
names(which(rowSums(table(vectora, vectorb))==length(unique(vectorb))))
}
convert_names_to_old <- function(current.names, conversion){
# current.names <- names(maindata)
indx <- which(current.names%in%conversion$new)
x <- current.names[indx]
y <- match(x, conversion$new)
current.names[indx] <- conversion$old[y]
current.names
}
# This code comes from the tools package
file_ext <- function (x)
{
pos <- regexpr("\\.([[:alnum:]]+)$", x)
ifelse(pos > -1L, substring(x, pos + 1L), "")
}
# Get list of folders with data
get_data_folders <- function() {
folders <- list.files("data/user-data/")
#folders <- folders[!folders%in%c("HEAT-data")]
ss <- unlist(strsplit(folders, "____"))
folders <- unique(ss[!grepl(".rds|.txt", ss, ignore.case = TRUE)])
if(length(folders) == 0) folders <- c("No existing data available" = "none")
folders
}
# make encoding unknown so data.table has a non-mixed encoding
make_unknown_encoding <- function(vals){
vals <- enc2native(vals)
Encoding(vals) <- "unknown"
vals
}
plot_decimals_setup <- function(plotData, type){
if(nrow(plotData) == 0) return(plotData)
if(type == "disag"){
plotData <- mutate(plotData,
estimate = round(estimate, 1),
lower_95ci = round(lower_95ci, 1),
upper_95ci = round(upper_95ci,1),
se = round(se, 1),
popshare = round(popshare,1),
national = round(national,1))
}
if(type == "sum"){
plotData[!plotData$measure%in%c("r", "rci", "mld", "ti"),c("inequal", "se", "estimate", "se.lowerci", "se.upperci")] <-
round(plotData[,c("inequal", "se", "estimate", "se.lowerci", "se.upperci")],1)
plotData[plotData$measure == "r",c("inequal", "se", "estimate", "se.lowerci", "se.upperci")] <-
round(plotData[,c("inequal", "se", "estimate", "se.lowerci", "se.upperci")],2)
plotData[plotData$measure%in%c("rci", "mld", "ti"),c("inequal", "se", "estimate", "se.lowerci", "se.upperci")] <-
round(plotData[,c("inequal", "se", "estimate", "se.lowerci", "se.upperci")],4)
}
plotData
}
# This is an alteration of navbarMenu to allow us to drop a
# specific tab panel
navbarMenu_drop <- function (title, drop = -1, ..., icon = NULL)
{
if(drop<0){tabs <- list(...)}else {tabs <- list(...)[-drop]}
structure(list(title = title, tabs = tabs, iconClass = shiny:::iconClass(icon)),
class = "shiny.navbarmenu")
}
assignColorsShapes <- function(dimensiondetails) {
# dimensiondetails
# dimension subgroup order maxn dimension_type
# 1 Economic status Quintile 1 (poorest) 1 5 other
# 2 Economic status Quintile 2 2 5 other
# 3 Economic status Quintile 3 3 5 other
# 4 Economic status Quintile 4 4 5 other
# 5 Economic status Quintile 5 (richest) 5 5 other
# 6 Education No education 1 3 other
# 7 Education Primary school 2 3 other
# 8 Education Secondary school + 3 3 other
# 9 Place of residence Rural 0 2 other
# 10 Place of residence Urban 0 2 other
# 11 Subnational region 01 barishal 0 50 region
# 12 Subnational region 02 chittagong 0 50 region
# this orders by subgroup if non ordered otherwise by
# order number
dimensiondetails <- order_dimensions(dimensiondetails)
dimensiondetails <- group_by(dimensiondetails, dimension) %>% mutate(totn = n())
dimensiondetails$ordered <- !dimensiondetails$order == 0
# create a table showing how many of each type
info <- distinct(dimensiondetails, maxn, totn, ordered)
info$greater7 <- info$maxn>7
info$ncol <- info$maxn
info$ncol[info$greater7] <- 1
# info
# maxn ordered dimension greater7 ncol
# <int> <lgl> <chr> <lgl> <dbl>
# 1 5 TRUE Economic status FALSE 5
# 2 3 TRUE Education FALSE 3
# 3 2 FALSE Place of residence FALSE 2
# 4 50 FALSE Subnational region TRUE 1
# how many in each category of color. First is ordered multi-level
# second is categorical multi-level and third is EITHER a dimension
# with more than 7 categories OR a categorical/ordered that has
# just one level (National average).
l_multi_ord <- sum(!info$greater7 & info$ordered & info$maxn!=1)
l_multi_cat <- sum(!info$greater7 & !info$ordered & info$maxn!=1)
l_one <- sum(info$greater7 | info$maxn==1)
# for sequential and qualitative these are palettes not colors
# for single, that is a function that just returns colors
sequential <- rep(c("blue", "red", "turquoise", "orange", "green", "purple", "yellow", "pink"), 10)
qualitative <- rep(c("redgreen", "blueorange", "greenpurple", "turquoisepink", "orangeblue", "bluered", "purplegreen"), 10)
single <- rep(pal_single(), 10) # just gives a list of colors
# now pull out the palettes (or individual colors) you'll need
multi_ord <- sequential[1:l_multi_ord]
multi_cat <- qualitative[1:l_multi_cat]
multi_single <- single[1:l_one]
# assign colors or palettes to the dimensions
info$palette <- NA
info$palette[!info$greater7 & info$ordered & info$maxn!=1] <- multi_ord
info$palette[!info$greater7 & !info$ordered & info$maxn!=1] <- multi_cat
info$palette[info$greater7 | info$maxn==1] <- multi_single
tmpcols <- pmap(info[, c("totn", "ordered", "ncol", "palette")], ~ {
if (..3 == 1) {
rep.int(..4, ..1)
} else if (..2) {
pal_ordered(..3, ..4, c(20, if (..3 > 7) 100 else 80))
} else {
pal_nonordered(..3, ..4)
}
})
# here is tmpcolos
# [[1]]
# [1] "#B2FF86" "#7CDD49" "#45A500" "#007000" "#004000"
#
# [[2]]
# [1] "#BBFFFF" "#00A698" "#004D3A"
#
# [[3]]
# [1] "#007300"
#
# [[4]]
# [1] "#00CD8D" "#FF7A9E"
#
# [[5]]
# [1] "#00AECF" "#CA8200"
#
# [[6]]
# [1] "#00B39C"
# we're almost there. For the non-single colors we have the
# right number of colors
# cols <- unlist(sapply(1:nrow(info), function(x){
#
# if(info$ncol[x] == 1){return(rep(tmpcols[[x]][1], info$totn[x]))}else{
# return(tmpcols[[x]])
# }
# }))
dimensiondetails$colors <- c(unlist(tmpcols))
dimensiondetails$shapes <- 21
dimensiondetails
}
updateFocusYear <- function(yr = yr){
if(all(yr%in%.rdata[['focus_year']])){
.rdata[['focus_year']] <<- unique(c(yr, .rdata[['focus_year']]))
}
}
# ------ Alternate select
# We had a situation where if the use had selected data sources
# in the order MICS, DHS rather than DHS, MICS the select
# was getting re-ordered. We don't want this
selectInputWHO <- function (inputId, label, choices, selected = NULL, multiple = FALSE,
selectize = TRUE, width = NULL, size = NULL, keep.order = FALSE)
{
inputId <- "a"
label = ""
choices <- c("a", "b" , "c")
selected <- c("b", "a")
selected <- restoreInput(id = inputId, default = selected)
choices <- shiny:::choicesWithNames(choices)
if (is.null(selected)) {
if (!multiple)
selected <- firstChoice(choices)
}
else selected <- validateSelected(selected, choices, inputId)
if (!is.null(size) && selectize) {
stop("'size' argument is incompatible with 'selectize=TRUE'.")
}
selectTag <- tags$select(id = inputId, class = if (!selectize)
"form-control", size = size, selectOptionsWHO(choices, selected, keep.order = keep.order))
if (multiple)
selectTag$attribs$multiple <- "multiple"
res <- div(class = "form-group shiny-input-container", style = if (!is.null(width))
paste0("width: ", validateCssUnit(width), ";"), controlLabel(inputId,
label), div(selectTag))
if (!selectize)
return(res)
selectizeIt(inputId, res, NULL, nonempty = !multiple && !("" %in%
choices))
}
selectOptionsWHO <- function (choices, selected = NULL, keep.order = TRUE)
{
html <- mapply(choices, names(choices), FUN = function(choice,
label) {
if (is.list(choice)) {
sprintf("<optgroup label=\"%s\">\n%s\n</optgroup>",
htmlEscape(label, TRUE), shiny:::selectOptions(choice,
selected))
}
else {
sprintf("<option value=\"%s\"%s>%s</option>", htmlEscape(choice,
TRUE), if (choice %in% selected)
" selected"
else "", htmlEscape(label))
}
})
if(keep.order){
a <- match(selected, names(html))
html <- c(html[a], html[-a])
}
HTML(paste(html, collapse = "\n"))
}
debounce <- function(expr, millis, env = parent.frame(), quoted = FALSE,
domain = getDefaultReactiveDomain()) {
force(millis)
f <- exprToFunction(expr, env, quoted)
label <- sprintf("debounce(%s)", paste(deparse(body(f)), collapse = "\n"))
v <- reactiveValues(
trigger = NULL,
when = NULL # the deadline for the timer to fire; NULL if not scheduled
)
# Responsible for tracking when f() changes.
observeEvent(f(), {
# The value changed. Start or reset the timer.
v$when <- Sys.time() + millis/1000
}, ignoreNULL = FALSE)
# This observer is the timer. It rests until v$when elapses, then touches
# v$trigger.
observe({
if (is.null(v$when))
return()
now <- Sys.time()
if (now >= v$when) {
v$trigger <- runif(1)
v$when <- NULL
} else {
invalidateLater((v$when - now) * 1000, domain)
}
})
# This is the actual reactive that is returned to the user. It returns the
# value of f(), but only invalidates/updates when v$trigger is touched.
eventReactive(v$trigger, {
f()
}, ignoreNULL = FALSE)
}
busyIndicator <- function(text = "",img = "spinner.gif", wait=1000) {
tagList(
div(class="busy-indicator",p(text),img(src=img))
,tags$script(sprintf(
" setInterval(function(){
if ($('html').hasClass('shiny-busy')) {
setTimeout(function() {
if ($('html').hasClass('shiny-busy')) {
$('div.busy-indicator').show()
}
}, %d)
} else {
$('div.busy-indicator').hide()
}
},100)
",wait)
)
)
}
barWidth <- function(cnts, detailedBar = FALSE){
# nrows <- nrow(plotData)
if(detailedBar){
if(cnts == 1) return(50)
if(cnts == 2) return(50)
if(cnts == 3) return(50)
return(200/cnts)
}else{
if(cnts == 1) return(50)
if(cnts == 2) return(50)
if(cnts == 3) return(50)
return(NULL)
}
#20 + 100/nrow(plotData)
}
conf.int.norm <- function(val, se){
l <- val - se * qnorm(0.975)
u <- val + se * qnorm(0.975)
return(list(l = l, u = u))
}
order_dimensions <- function(dat) {
dimension_ordered <- arrange(filter(dat, order != 0), dimension, order)
dimension_nonordered <- arrange(filter(dat, order == 0), dimension, subgroup)
dat <- bind_rows(dimension_ordered, dimension_nonordered)
dat$subgroup <- factor(dat$subgroup, levels = unique(dat$subgroup))
dat
}
pal_ordered <- function (n, color, l = c(20, 100), power = 1, fixup = TRUE,
alpha = 1, ...) {
if (n < 1) {
return(character(0))
}
h_val <- case_when(
color == "green" ~ 120,
color == "turquoise" ~ 180,
color == "blue" ~ 260,
color == "purple" ~ 280,
color == "pink" ~ 320,
color == "red" ~ 10,
color == "orange" ~ 30,
color == "yellow" ~ 60,
color == "lightgreen" ~ 100,
color == "lightblue" ~ 210
)
c_val <- case_when(
color == "green" ~ c(80, 100),
color == "turquoise" ~ c(80, 40),
color == "blue" ~ c(80, 100),
color == "purple" ~ c(80, 100),
color == "pink" ~ c(80, 100),
color == "red" ~ c(80, 100),
color == "orange" ~ c(80, 100),
color == "yellow" ~ c(80, 100),
color == "lightgreen" ~ c(80, 100),
color == "lightblue" ~ c(80, 40)
)
r_vals <- seq(1, 0, length = n)
rval <- hex(
polarLUV(
L = l[2L] - diff(l) * r_vals^power,
C = c_val[2L] - diff(c_val) * r_vals^power,
H = h_val[1L]
),
fixup = fixup,
...
)
if (!missing(alpha)) {
alpha <- pmax(pmin(alpha, 1), 0)
alpha <- format(as.hexmode(round(alpha * 255 + 1e-04)),
width = 2L, upper.case = TRUE)
rval <- paste(rval, alpha, sep = "")
}
return(rval)
}
#plot(1:10, 1:10, pch = 16, cex = 1.3, col = pal_nonordered(10, "blueorange"))
pal_nonordered <- function (n, col, c = 100, fixup = TRUE,
gamma = NULL, alpha = 1, ...)
{
vals <- switch(col,
"redgreen" = list(l = 70, start = -360, end = -200),
"orangeblue" = list(l = 60, start = -310, end = -150),
"greenpurple" = list(l = 50, start = -260, end = -100),
"purplegreen" = list(l = 70, start = -100, end = -260),
"turquoisepink" = list(l = 70, start = -210, end = -50),
"bluered" = list(l = 60, start = -160, end = 0),
"blueorange" = list(l = 50, start = -110, end = 50),
"orangeblue" = list(l = 70, start = -60, end = -100),
NULL)
if(is.null(vals)) stop("Wrong choice of color palette")
l <- vals$l
start <- vals$start
end <- vals$end
if (!is.null(gamma))
warning("'gamma' is deprecated and has no effect")
if (n < 1L)
return(character(0L))
rval <- hex(polarLUV(L = l, C = c, H = seq(start, end, length = n)),
fixup = fixup, ...)
if (!missing(alpha)) {
alpha <- pmax(pmin(alpha, 1), 0)
alpha <- format(as.hexmode(round(alpha * 255 + 1e-04)),
width = 2L, upper.case = TRUE)
rval <- paste(rval, alpha, sep = "")
}
return(rval)
}
# taken from package colorspace
hex <- function (from, gamma = NULL, fixup = FALSE)
{
if (!is.null(gamma))
warning("'gamma' is deprecated and has no effect")
coords <- as(from, "sRGB")@coords
rval <- .Call("sRGB_to_RColor", coords, fixup, PACKAGE = "colorspace")
if (!is.null(dnam <- attr(coords, "dimnames")))
names(rval) <- dnam[[1L]]
rval <- rev(rval)
return(rval)
}
# taken from package colorspace
polarLUV <- function (L, C, H, names)
{
if (missing(L))
return(new("polarLUV"))
if (missing(names))
names = dimnames(L)[[1]]
coords = cbind(L, if (missing(C))
NULL
else C, if (missing(H))
NULL
else H)
dimnames(coords) = list(names, c("L", "C", "H"))
new("polarLUV", coords = coords)
}
pal_single <- function(){
c("green" = "#007300",
"turquoise" = "#00B39C",
"blue" = "#003AC3",
"purple" = "#7D00EC",
"pink" = "#D65EE9",
"red" = "#CE4951",
"orange" = "#DE7429",
"yellow" = "#FFDA3D",
"lightgreen" = "#B0D500",
"lightblue" = "#00AECF")
}
adjust_axes <- function(plt, x = TRUE, y = FALSE, Xaxismin = NULL, Xaxismax = NULL,
Yaxismin = NULL, Yaxismax = NULL,
flip = FALSE){
#browser()
pbuild<-ggplot_build(plt)
if(!any(is.null(c(Xaxismin, Xaxismax)))){
xaxisrange<-pbuild$layout$panel_scales_x[[1]]$range$range
Xaxismin<-ifelse(Xaxismin=="", xaxisrange[1], as.numeric(Xaxismin))
Xaxismax<-ifelse(Xaxismax=="", xaxisrange[2], as.numeric(Xaxismax))
}
if(!any(is.null(c(Yaxismin, Yaxismax)))){
yaxisrange<-pbuild$layout$panel_scales_y[[1]]$range$range
Yaxismin<-ifelse(Yaxismin=="", yaxisrange[1], as.numeric(Yaxismin))
Yaxismax<-ifelse(Yaxismax=="", yaxisrange[2], as.numeric(Yaxismax))
}
if(x & !y & !flip){
plt <- plt + coord_cartesian(xlim=c(Xaxismin, Xaxismax))
}
if(!x & y & !flip){
plt <- plt + coord_cartesian(ylim=c(Yaxismin, Yaxismax))
}
if(x & y & !flip){
plt <- plt + coord_cartesian(xlim=c(Xaxismin, Xaxismax), ylim=c(Yaxismin, Yaxismax))
}
if(x & !y & flip){
plt <- plot + coord_flip(ylim=c(Xaxismin, Xaxismax))
}
return(plt)
}
translationOutput <- function(id, key = id, parent = span, ..., html = FALSE) {
(if (!html) textOutput else htmlOutput)(
outputId = id,
container = function(id, class) {
parent(id = id, class = class, translate(key, "english"), ...)
}
)
}
#************************************************
# Function for R and D with percentiles ----
#************************************************
r_d_percentile <- function(dat, n_subgroup){
#dat <- plotData
res <- group_by(dat, country, year, source, indic_name) %>%
mutate(n_valid_estimates = sum(estimate!=-9999)) %>%
nest()
rdvals <- map(res$data, function(x){
#vals <- "Not enough subgroups to compute valid estimates"
#if(x$n_valid_estimates[1]>=30){
vals <- r_d_diff_ratio(c(0.2, 0.8), x)
names(vals) <- c("Difference (percentile 80 - percentile 20)",
"Ratio (percentile 80 / percentile 20)",
"Difference (mean quintile 5 - mean quintile 1)",
"Ratio (mean quintile 5 / mean quintile 1)")
#}
if(x$n_valid_estimates[1]>=60){
vals1 <- r_d_diff_ratio(c(0.1, 0.9), x)
names(vals1) <- c("Difference (percentile 90 - percentile 10)",
"Ratio (percentile 90 / percentile 10)",
"Difference (mean decile 90 - mean decile 10)",
"Ratio (mean decile 90 / mean decile 10)")
vals <- c(vals, vals1)
}
if(x$n_valid_estimates[1]>=100){