first post and I hope I'm doing everything correctly. I'm using RStudio: Version 1.1.423; R-Version: 3.4.2, OS: Windows 10
Short problem summary: I start a gwidgets based GUI and the text shows in the desired font size, but when I click the save button, it suddenly changes to a smaller font.
Context: I'm currently doing a systematic literature review and I use the Metagear package by mjlajeunesse (https://github.com/cran/metagear) to screen the abstracts and decide if I shuold include them. Here's a picture of the original GUI: Original Abstract Screener GUI
Short description of functionality: I just click on one of the buttons (Yes, No, Maybe) and the abstract screener moves on to the next abstract in the file. I then click save to save my progress.
Changes I made to the code: However, I added some additional fields so I had to change that behaviour, so that it doesn't immediately jump to the next entry as soon as I click one of the buttons. So I merged that part of the function with the save function. Now I get the following behaviour: When I first open the abstract screener the fontsize is as desired as seen in this picture: Adapted Abstract Screener before clicking Save & Next
As soon as I click Save & Next it shows me the next abstract (as desired), but suddenly the font changes to a much smaller one, making it rather unpleasant to read, because it's so small, as seen here Adapted Abstract Screener after clicking Save & Next
Here's the code that I use/adapted to override the original functions of the metagear package. I iteratively adapted the code so I only included the functions of the metagear package that I needed to make things work. Here's the code I'm using(I included the code I use to execute the different functions at the bottom, including some sample data frame, instead of my CSV file):
# Load libraries
library(metagear)
library(EBImage)
library(cairoDevice)
library(gWidgets)
library(gWidgetsRGtk2)
library(gWidgets2)
library(gWidgets2RGtk2)
library(RGtk2)
library(utils)
##############################
# dirty adaptations for the METAGEAR package start here
##############################
##########################
# better_effort_utils (important for effort_save)
##########################
effort_save <- function (aDataFrame,
column_name = "REVIEWERS",
directory = getwd(),
quiet = FALSE) {
split_List <- split(aDataFrame, f = aDataFrame[, column_name])
lapply(split_List, function(x, column_name) {
fileName <- paste0("effort_", x[1, column_name], ".csv")
if(file.exists(file.path(directory, fileName))) {
while (file.exists(file.path(directory, fileName)) != FALSE) fileName <- renameFile(fileName)
if(!quiet) message(paste0("File already existed, renamed: ", fileName))
}
fileName <- file.path(directory, fileName)
write.csv(x, file = fileName, na = "NA", row.names = FALSE)
}, column_name = column_name)
if(!quiet) message(paste0(length(split_List), " files saved in: ", directory))
}
######################
# better_effort_initialize
######################
better_effort_initialize <- function(aDataFrame,
study_ID = TRUE,
unscreenedValue = "not vetted",
unscreenedCommentValue = "Please paste text here",
studyTypeValue = "not vetted",
studyTypeCommentValue = "Please paste text here",
dual = FALSE,
front = TRUE) {
# adding new columns start, add the new columns as part of the "if" statement as well as the "else" statement
if(dual == TRUE) {
new_cols <- data.frame(REVIEWERS_A = NA,
INCLUDE_A = unscreenedValue,
REVIEWERS_B = NA,
INCLUDE_B = unscreenedValue,
INCLUDE_COMMENT = unscreenedCommentValue,
TYPE_OF_STUDY = studyTypeValue,
TYPE_OF_STUDY_COMMENT = studyTypeCommentValue) # There will have to be a version A and version B, just like with the reviewers
}
else new_cols <- data.frame(REVIEWERS = NA,
INCLUDE = unscreenedValue,
INCLUDE_COMMENT = unscreenedCommentValue,
TYPE_OF_STUDY = studyTypeValue,
TYPE_OF_STUDY_COMMENT = studyTypeCommentValue)
if(study_ID == TRUE) new_cols <- cbind(data.frame(STUDY_ID = 1:nrow(aDataFrame)),
new_cols)
if(front == TRUE) newDataFrame <- cbind(new_cols, aDataFrame)
else newDataFrame <- cbind(aDataFrame, new_cols)
return(newDataFrame)
}
#################################
# better_effort_distribute
#################################
better_effort_distribute <- function (aDataFrame = NULL,
dual = FALSE,
reviewers = theTeam,
column_name = "REVIEWERS",
effort = NULL,
initialize = FALSE,
save_split = FALSE,
directory = getwd() ) {
if(is.null(reviewers)) .metagearPROBLEM("error",
"no reviewers were assigned")
if(is.null(aDataFrame)) .metagearPROBLEM("error",
"a dataframe with refs was not specified")
number_REFS <- nrow(aDataFrame)
number_reviewers <- length(reviewers)
# add REVIEWER, STUDY_ID, and INCLUDE columns to reference library
if(initialize == TRUE) aDataFrame <- better_effort_initialize(aDataFrame,
dual = dual)
if(dual == TRUE) {
if(!is.null(effort)) .metagearPROBLEM("error",
"can only assign dual effort evenly among reviewers")
if(number_reviewers %% 2 == 1) .metagearPROBLEM("error",
"can only assign dual effort with an even number of reviewers")
reviewers_A <- reviewers[1:number_reviewers %% 2 == 1]
theEffort_A <- gl(length(reviewers_A),
ceiling(number_REFS / length(reviewers_A)),
number_REFS,
labels = reviewers_A)
reviewers_B <- reviewers[1:number_reviewers %% 2 == 0]
theEffort_B <- gl(length(reviewers_B),
ceiling(number_REFS / length(reviewers_B)),
number_REFS,
labels = reviewers_B)
dualEffort <- data.frame(A = theEffort_A, B = theEffort_B)
theEffort <- dualEffort[sample(nrow(dualEffort),
nrow(dualEffort), replace = FALSE), ]
aDataFrame["REVIEWERS_A"] <- theEffort["A"]
aDataFrame["REVIEWERS_B"] <- theEffort["B"]
}
else {
# generate reviewers tasks evenly or via custom 'effort'
if(is.vector(effort) && length(unique(effort)) != 1) {
if(sum(effort) != 100) .metagearPROBLEM("error",
"Effort does not sum to 100.")
theEffort <- rep(reviewers, round((number_REFS * (effort / 100))))
} else {
theEffort <- gl(number_REFS,
ceiling(number_REFS / number_reviewers),
number_REFS,
labels = reviewers)
}
# randomly populate REVIEWERS column with tasks
aDataFrame[, column_name] <- sample(theEffort,
length(theEffort),
replace = FALSE)
}
# splits reference library into seperate reviewer csv files and
# hides teams if dual reviewing
if(save_split == TRUE) {
if(dual == TRUE) {
removeVars <- names(aDataFrame) %in% c("REVIEWERS_B", "INCLUDE_B")
effort_save(aDataFrame[!removeVars],
column_name = "REVIEWERS_A", directory)
removeVars <- names(aDataFrame) %in% c("REVIEWERS_A", "INCLUDE_A")
effort_save(aDataFrame[!removeVars],
column_name = "REVIEWERS_B", directory)
}
else effort_save(aDataFrame, column_name, directory)
}
return(aDataFrame)
}
#######################################
# better_abstract_screener
#######################################
#' @param file The file name and location of a .csv file containing the
#' abstracts and titles. The .csv file should have been initialized with
#' \code{effort_initialize} and populated with screeners (reviewers) using
#' \code{better_effort_distribute}.
#' @param aReviewer The name (a string) of the reviewer to screen abstracts.
#' It is used when there are multiple reviewers assigned to screen abstracts.
#' The default column label is "REVIEWERS" as initialized with
#' \code{better_effort_distribute}.
#' @param reviewerColumnName The name of the column heading in the .csv file
#' that contains the reviewer names that will screen abstracts. The default
#' column label is "REVIEWERS".
#' @param unscreenedColumnName The name of the column heading in the .csv file
#' that contains the screening outcomes (i.e. vetting outcomes by a reviewer).
#' Unscreened references are by default labeled as "not vetted". The
#' reviewer then can code to "YES" (is a relevant study), "NO" is not relevant
#' and should be excluded, or "MAYBE" if the title/abstract is missing or
#' does not contains enough information to fully assess inclusivity.
#' The default label of this column is "INCLUDE".
#' @param unscreenedValue Changes the default coding (a string) of "not vetted"
#' that designates whether an abstract remains to be screened or vetted.
#' @param abstractColumnName The name of the column heading in the .csv file
#' that contains the abstracts. The default label of this column is
#' "ABSTRACT".
#' @param titleColumnName The name of the column heading in the .csv file
#' that contains the titles. The default label of this column is "TITLE".
#' @param browserSearch Change the url for the browser title search; the
#' default is Google.
#' @param protect When \code{"TRUE"}, prevents the title and abstract from being
#' clicked, selected or edited.
#' @param fontSize Change the font size of the title and abstract text.
#' @param windowWidth Change the default width of the GUI window.
#' @param windowHeight Change the default height of the GUI window.
#' @param buttonSize Change the default size of the "YES" and "NO" buttons.
#'
#'
#' @return NULL
#'
#' @examples \dontrun{
#'
#' data(example_references_metagear)
#' better_effort_distribute(example_references_metagear,
#' initialize = TRUE, reviewers = "marc", save_split = TRUE)
#' abstract_screener("effort_marc.csv", aReviewer = "marc")
#'}
#'
#' @note \strong{Installation and troubleshooting}\cr\cr Upon first use,
#' \code{abstract_screener} will download the gWidgets package
#' and associated toolkits needed to build GUI interfaces. A small window will
#' also prompt you to download GTK+ asking "Need GTK+ ?". From the listed
#' options answer: "Install GTK+" and click 'OK'. Once installed these will
#' not be downloaded again. Sometimes there is an issue with the installation
#' of GTK+, see \url{http://www.learnanalytics.in/blog/?p=31} for advice based
#' on the \code{Rattle} R Package (both \code{Rattle} and \code{metagear} use
#' the same GUI dependencies). \cr\cr \strong{How to use the screener}
#' \cr\cr The GUI itself will appear as a single window with the first
#' title/abstract listed in the .csv file. If abstracts have already been
#' screened/coded, it will begin at the nearest reference labeled as
#' "not vetted". The SEARCH WEB button opens the default browser and
#' searches Google with the title of the reference. The YES, MAYBE, NO
#' buttons, which also have shortcuts ALT-Y and ALT-N, are used to code the
#' inclusion/exclusion of the reference. Once clicked/coded the next
#' reference is loaded. The SAVE button is used to save the coding progress
#' of screening tasks. It will save coding progress directly to the
#' loaded .csv file. \strong{Closing the GUI and not saving will result in
#' the loss of screening efforts relative to last save.} \cr\cr There is
#' also an ISSUE FIXES menu bar with quick corrections to screening errors.
#' These include ISSUE FIXES: REFRESH TITLE AND ABSTRACT TEXT which reloads
#' the text of the current abstract in case portions were deleted when
#' copying and pasting sections (this can be avoided if
#' \code{protect = TRUE} is enabled), ISSUE FIXES: STATUS OF CURRENT ABSTRACT
#' which provides information on whether or not the abstract was previously
#' screened, and ISSUE FIXES: RETURN TO PREVIOUS ABSTRACT that
#' backtracks to the previous abstract if a selection error occurred (note a
#' warning will appear of there is a change to its inclusion/exclusion
#' coding).
#'
#' @import gWidgets
#' @import gWidgetsRGtk2
#' @importFrom utils browseURL read.csv write.csv
#' @export abstract_screener
############################
better_abstract_screener <- function(file = file.choose(),
aReviewer = NULL,
reviewerColumnName = "REVIEWERS",
unscreenedColumnName = "INCLUDE",
unscreenedValue = "not vetted",
unscreenedCommentColumnName = "INCLUDE_COMMENT",
unscreenedCommentValue = "",
studyTypeColumnName = "TYPE_OF_STUDY",
studyTypeValue = "not vetted",
studyTypeCommentColumnName = "TYPE_OF_STUDY_COMMENT",
studyTypeCommentValue = "",
abstractColumnName = "Abstract",
titleColumnName = "Title",
browserSearch = "https://scholar.google.de/scholar?hl=de&as_sdt=0%2C5&q=",
protect = FALSE,
fontSize = 13,
windowWidth = 700,
windowHeight = 400,
buttonSize = 30) {
# get file with abstract
aDataFrame <- read.csv(file, header = TRUE)
# subset abstracts based on the current screener (aka 'reviewer')
subData <- subset(aDataFrame, aDataFrame[reviewerColumnName] == aReviewer)
subData <- data.frame(lapply(subData, as.character), stringsAsFactors = FALSE)
# check if all abstracts have been already vetted
if(unscreenedValue %in% subData[, unscreenedColumnName] ) {
# start screener at first unvetted abstract
currentItem <- max.col(t(subData[unscreenedColumnName] == unscreenedValue),
"first")
} else {
.metagearPROBLEM("error",
paste("all abstracts have already been screened,
no more abstracts coded as:", unscreenedValue))
}
options("guiToolkit" = "RGtk2")
# used to update the reference list
theAnswer <- function(theValue, ...) {
updateAll(theValue, ...)
}
theAnswer_INCLUDE_COMMENT <- function(theValue_INCLUDE_COMMENT, ...) {
updateAll_INCLUDE_COMMENT(theValue_INCLUDE_COMMENT, ...)
}
theAnswer_ToS <- function(theValue_ToS, ...) {
updateAll_ToS(theValue_ToS, ...)
}
theAnswer_ToS_COMMENT <- function(theValue_ToS_COMMENT, ...) {
updateAll_ToS_COMMENT(theValue_ToS_COMMENT, ...)
}
# helper function used to update and keep track of screened abstracts
updateAll <- function(theValue, ...) {
if(currentItem <= nrow(subData)) {
subData[[currentItem, unscreenedColumnName]] <<- theValue
}
}
updateAll_INCLUDE_COMMENT <- function(theValue_INCLUDE_COMMENT, ...) { ################### EXPERIMENTAL
if(currentItem <= nrow(subData)) {
subData[[currentItem, unscreenedCommentColumnName]] <<- theValue_INCLUDE_COMMENT
}
}
updateAll_ToS <- function(theValue_ToS, ...) {
if(currentItem <= nrow(subData)) {
subData[[currentItem, studyTypeColumnName]] <<- theValue_ToS
}
}
updateAll_ToS_COMMENT <- function(theValue_ToS_COMMENT, ...) {
if(currentItem <= nrow(subData)) {
subData[[currentItem, studyTypeCommentColumnName]] <<- theValue_ToS_COMMENT
}
}
####################
# START of SCREENER GUI
####################
win <- gwindow("metagear: Abstract Screener", visible = TRUE)
paned <- ggroup(container = win, horizontal = FALSE)
# Frame(s) for title, abstract and websearch button
#####
#beginnig frame_TITLE
frame_TITLE <- gframe("Title", container = paned, horizontal = TRUE)
text_TITLE <- gtext(subData[currentItem, titleColumnName],
container = frame_TITLE,
expand = TRUE,
font.attr = list(style = "normal", size = fontSize))
size(text_TITLE) <- c(windowWidth, 50)
if(protect == TRUE) enabled(text_TITLE) <- FALSE
addSpace(frame_TITLE, 2)
aButton_webSearch <- gbutton("Search\n Web",
container = frame_TITLE,
handler = function(h, ...)
browseURL(paste0(browserSearch,
subData[currentItem, titleColumnName])))
size(aButton_webSearch) <- c(50, 40)
addSpace(frame_TITLE, 5)
# end of frame_TITLE
# beginning frame_Abstract
frame_ABSTRACT <- gframe("Abstract", container = paned, horizontal = FALSE)
text_ABSTRACT <- gtext(subData[currentItem, abstractColumnName],
container = frame_ABSTRACT,
expand = TRUE,
font.attr = list(style = "normal", size = fontSize)
)
size(text_ABSTRACT) <- c(windowWidth + 50, 300)
if(protect == TRUE) enabled(text_ABSTRACT) <- FALSE
# end of frame_ABSTRACT
# beginning: Type of Study (ToS), buttons and comment
frame_TYPE_OF_STUDY <- gframe("Type of Study", container = paned, horizontal = TRUE)
addSpace(frame_TYPE_OF_STUDY, 20)
radioButtonNames_ToS <- c("not vetted", "empirical", "conceptual", "review")
radioButtons_ToS <- gradio(radioButtonNames_ToS, selected = which(radioButtonNames_ToS == subData[currentItem, studyTypeColumnName]), horizontal = FALSE, container = frame_TYPE_OF_STUDY,
handler = function(h,...){
svalue(h) <- subData[currentItem, studyTypeColumnName]
theAnswer_ToS(theValue_ToS = radioButtonNames_ToS[svalue(radioButtons_ToS, index = TRUE)], ...) # EXPERIMENTAL: Need to find a way t make the 3 a dynamic option that shows current selection (Current solution seems to be working)
}
)
frame_TYPE_OF_STUDY_COMMENT <- gframe("Please copy the text snippet upon which you base your decision",
container = frame_TYPE_OF_STUDY, horizontal = TRUE)
text_TYPE_OF_STUDY_COMMENT <- gtext(subData[currentItem, studyTypeCommentColumnName],
container = frame_TYPE_OF_STUDY_COMMENT,
#container = frame_TYPE_OF_STUDY, ### change to this frame and disable frame_TYPE_OF_STUDY_COMMENT, if you want the text field width to be expandable
expand = TRUE,
font.attr = list(style = "normal", size = fontSize),
handler = function(h, ...) {
theAnswer_ToS_COMMENT(theValue_ToS_COMMENT = svalue(text_TYPE_OF_STUDY_COMMENT))
}
)
size(text_TYPE_OF_STUDY_COMMENT) <- c(windowWidth, 70)
# end: Type of Study (ToS), buttons and comment
# beginning: Include/Exclude (YES/NO), buttons and comment
frame_INCLUDE <- gframe("Should the Abstract be included?", container = paned, horizontal = TRUE)
addSpace(frame_INCLUDE, 20)
radioButtonNames_INCLUDE <- c("not vetted", "YES", "NO", "MAYBE")
radioButtons_INCLUDE <- gradio(radioButtonNames_INCLUDE, selected = which(radioButtonNames_INCLUDE == subData[currentItem, unscreenedColumnName]),
horizontal = FALSE, container = frame_INCLUDE,
handler = function(h,...){
svalue(h) <- subData[currentItem, unscreenedColumnName]
theAnswer(theValue = radioButtonNames_INCLUDE[svalue(radioButtons_INCLUDE, index = TRUE)], ...)
}
)
frame_INCLUDE_COMMENT <- gframe("Please copy the text snippet upon which you base your decision", container = frame_INCLUDE,
horizontal = TRUE)
text_INCLUDE_COMMENT <- gtext(subData[currentItem, unscreenedCommentColumnName],
container = frame_INCLUDE_COMMENT,
# container = frame_INCLUDE, ### change to this frame and disable frame_INCLUDE_COMMENT, if you want the text field width to be expandable
expand = TRUE,
font.attr = list(style = "normal", size = fontSize),
handler = function(h, ...) {
theAnswer_INCLUDE_COMMENT(theValue_INCLUDE_COMMENT = svalue(text_INCLUDE_COMMENT))
}
)
size(text_INCLUDE_COMMENT) <- c(windowWidth, 70)
#end: Include/Exclude (YES/NO), buttons and comment
#beginning: Progress and Save
buttons_paned <- ggroup(container = paned)
addSpace(buttons_paned, 50)
frame_PROGRESS <- gframe("Progress", container = buttons_paned, expand = TRUE)
addSpace(frame_PROGRESS, 10)
text_progress <- glabel(paste0("Reviewer: ",
aReviewer,
" | ",
round(((currentItem - 1.0)/nrow(subData)) * 100, digits = 1),
"% complete (", currentItem, " of ",
nrow(subData) , ")"),
container = frame_PROGRESS)
aButton_save <- gbutton("SAVE & CONTINUE",
container = frame_PROGRESS,
handler = function(h, ...)
{
{
write.csv(subData,
file = file, #file was dataFilename
row.names = FALSE)
svalue(text_lastSaved) <- paste("last saved: ", Sys.time())
}
currentItem <<- currentItem + 1
if(currentItem > nrow(subData))
{svalue(text_ABSTRACT) <- "You have screened all the Abstracts!"
svalue(text_TITLE) <- ""
} else
{svalue(text_ABSTRACT) <- subData[currentItem, abstractColumnName]
svalue(text_TITLE) <- subData[currentItem, titleColumnName]
svalue(text_progress) <- paste0(
round(((currentItem - 1.0)/nrow(subData)) * 100, digits = 1),
"% complete (", currentItem, " of ", nrow(subData), ")")
svalue(text_TYPE_OF_STUDY_COMMENT) <- subData[currentItem, studyTypeCommentColumnName]
svalue(radioButtons_ToS) <- subData[currentItem, studyTypeColumnName]
svalue(radioButtons_INCLUDE) <- subData[currentItem, unscreenedColumnName]
svalue(text_INCLUDE_COMMENT) <- subData[currentItem, unscreenedCommentColumnName]
}
}
)
size(aButton_save) <- c(130, 40)
text_lastSaved <- glabel(paste(" last saved: not this session"), # empty space at beginning on purpose to leave some distance to button, as addSpace() screwed things up
container = frame_PROGRESS)
#end of Progress and Save
#end of buttons_paned
#end of paned
visible(win) <- TRUE
# end of win
}
###############
# Preparation of the files and starting of the GUI
###############
# Set working directory
setwd("C:/Users/Hilser/Documents/R")
# Add team member(s)
theTeam <- c("Stefan")
#import .csv-file and name it review" ##### REPLACED BY SAMPLE DATA BELOW
# review <- read.csv("C:/Users/Hilser/Documents/R/Metagear/Better_Metagear/review_duplicates_removed.csv", header = TRUE, sep = ",")
# Create Sample Data instead of importing .csv-file
Title <- c("Title 1", "Title 2", "Title 3", "Title 4")
Abstract <- c( "Abstract 1", "Abstract 2", "Abstract 3", "Abstract 4")
review <- data.frame(Title, Abstract)
# Prepare file: Adding columns "STUDY_ID", "REVIEWERS", "INCLUDE" (and fill with "not vetted"), "INCLUDE_COMMENT", "TYPE_OF_STUDY"
review_initialized <- better_effort_initialize(review, study_ID = TRUE, unscreenedValue = "not vetted", dual = FALSE, front = TRUE)
# distribute effort amongst Reviewers, adding their name (reviewers = ) to the column "REVIEWERS"
review_distributed <- better_effort_distribute(review_initialized, dual = FALSE, reviewers = theTeam, column_name = "REVIEWERS",
effort = 100, initialize = FALSE, save_split = TRUE)
# opens a graphical user interface (GUI) that allows for abstract screening
better_abstract_screener("effort_Stefan.csv", aReviewer = "Stefan")
From the described behaviour, I assume that the error lies somewhere in one of the following functions:
Sorry, my guess is that the font.attribute you specify for text_TITLE isn't being preserved after you call svalue(text_TITLE) <-. The easy solution would be to call font(text_TITLE)<- ... after setting the text. The proper solution would be to fix this method: https://github.com/jverzani/gWidgets2RGtk2/blob/master/R/gtext.R#L84 (this should use the method insert_text https://github.com/jverzani/gWidgets2RGtk2/blob/master/R/gtext.R#L160 which does adjust for the font attribute.
With that in mind, you might try this 1-2 punch to set text:
svalue(text_TITLE) <- ""
text_TITLE$insert_text(new_text, "beginning")