R/analysis.GUI.R
In tmcd82070/SDrawNPS: Sample Draw NPS
#' @export analysis.GUI
#'
#' @title Graphic User Interface (GUI) to analyze the status of categorical
#' or continuous variables collected via GRTS samples.
#'
#' @description Initiates a dialog box via a GUI to analyze samples
#' from 2-D resources.
#'
#' @return A data frame with the name specified by the user in the GUI\eqn{'}s
#' \code{Output File} box. This data frame contains the sampling analysis
#' specifications, along with coordinates and projection information. Analysis
#' data frames are stored in the current workspace, while any export files,
#' including a \code{txt} log of the commands utilized to generate the sample,
#' as well as plots of empirical distribution functions and a \code{csv} of
#' their underlying data, are saved to the file directory specified via
#' \code{getwd}.
#'
#' @details This routine is intended to be called from the \code{SDrawNPS} menu,
#' but it can also be called from the command line in non-interactive
#' environments, such as RStudio. This routine uses the \code{RGtk2} package
#' windowing capabilities to construct a pop-up dialog box, or GUI. In the
#' dialog box, users specify at least the required input parameters, then
#' press the \sQuote{Run} button to analyze the sample.
#'
#' On submission, the GUI internally packages its inputs, processes the
#' necessary data, and executes the \code{spsurvey}-package
#' \code{cat.analysis} function for the analysis of categorical variables and
#' \code{cont.analysis} function for the same with respect to numeric
#' variables. All \code{SDrawNPS} GUI submissions utilizing the
#' \code{spsurvey} package analysis methodologies lead to the creation of a
#' text-based log file, which records all code utilized. The log file thus
#' serves as a historical record containing analysis information. It also
#' serves as a tool for enhancing methodological understanding.
#'
#' See \sQuote{References} for additional resources.
#'
#' @section Required Inputs:
#'
#' \enumerate{
#'
#' \item \sQuote{CSV file OR data.frame object} -- Specify the data frame or
#' \code{csv} containing the data for which analysis is required, or click
#' \sQuote{Browse} to browse for a data file with a \code{.csv} extension.
#' When specifying the name of a data file via use of the input box, do not
#' include the \code{.csv} extension. Following identification of the data,
#' click the \sQuote{Inspect Sample} button to list its variables.
#'
#' \item \sQuote{Output File} -- Specify the sample\eqn{'}s R object name to which
#' all analysis results will be assigned. The output will be a data frame
#' containing analysis results.
#'
#' \item \sQuote{Site-ID Variable} -- The case-sensitive variable in the input
#' data frame or \code{csv} identifying unique site identifiers.
#'
#' \item \sQuote{Evaluation Status Variable} -- The case-sensitive variable in
#' the input data frame or \code{csv} identifying which sites consitute the
#' surveyed targets. See \sQuote{Inclusion Identifier.}
#'
#' \item \sQuote{Inclusion Identifier} -- The case-sensitive text string that
#' identifies surveyed targets of sites in the variable identified via the
#' \sQuote{Evaluation Status Variable} box.
#'
#' \item \sQuote{Stratum / Subpopulation 1} -- The case-sensitive variable in
#' the input data frame or \code{csv} containing a stratification variable.
#' For example, this could be an elevational class associated with every point
#' in the shapefile. Constant values of this variable define the strata. This
#' box can be left blank if analysis requires no consideration of any strata.
#'
#' \item \sQuote{Stratum / Subpopulation 2} -- Same as \sQuote{Stratum /
#' Subpopuation 1}.
#'
#' \item \sQuote{Weight Variable} -- The case-sensitive variable in the input
#' data frame or \code{csv} containing the design weights of included sites.
#' Adjustment of included design weights, if appropriate, occurs via the
#' \sQuote{Adjust Weights?} and \sQuote{Population Inference} sections of the
#' GUI. See \sQuote{Optional Weighting Inputs.}
#'
#' \item \sQuote{X-Coordinate} -- The case-sensitive variable in the input
#' data frame or \code{csv} containing the \eqn{x}-coordinate of included
#' sites. Units do not matter.
#'
#' \item \sQuote{Y-Coordinate} -- The case-sensitive variable in the input
#' data frame or \code{csv} containing the \eqn{y}-coordinate of included
#' sites. Units do not matter.
#'
#' \item \sQuote{Outcome(s)} -- The list of case-sensitive variables in the
#' input data frame or \code{csv} for which analysis is required. Enter
#' multiple variables separated by commas and a space.
#'
#' \item \sQuote{Confidence Level} -- The confidence level to be utilized in
#' the analysis.
#'
#' }
#'
#' @section Optional Weighting Inputs:
#'
#' \enumerate{
#'
#' \item \sQuote{Adjust Weights?} -- When set to \sQuote{Yes}, design weights
#' specified via the \sQuote{Weight Variable} box are adjusted for frame
#' error. See function \code{Adjwgt_FrameNR}. No adjustment occurs when set
#' to \sQuote{No}.
#'
#' \item \sQuote{Population Inference} -- Assuming that the \sQuote{Adjust
#' Weights?} radio button is set to \sQuote{Yes}, selection of the
#' \sQuote{Population Inference} radio button specifies the value of the
#' \code{popn} argument in function \code{Adjwgt_FrameNR}. Explicitly,
#' selection of \sQuote{Target} specifies \code{popn="Target"} in
#' \code{Adjwgt_FrameNR}, while selection of \sQuote{Sampled} specifies
#' \code{popn="Sampled"}.
#'
#' }
#'
#' @section Dialog Buttons:
#'
#' \enumerate{
#'
#' \item \sQuote{Inspect Sample.} After specifying the \code{csv} file or data
#' frame object name, pressing the \sQuote{Inspect Sample} button lists all of
#' its constituent variables and vector classes.
#'
#' \item \sQuote{Run.} After specifying all required and optional inputs, the
#' \sQuote{Run} button analyzes the sample. The \code{.GlobalEnv} workspace
#' holds the resulting data frame entitled via the name specified in the GUI
#' \sQuote{Output File} box. A confirmation dialog appears following
#' completion of the analysis.
#'
#' \item \sQuote{Tabulate Sample.} Following analysis, display the GRTS
#' analysis file in a tabular format. The GRTS analysis file contains
#' information on each sampled unit, such as coordinates, and design
#' variables, e.g., stratum or multi-density category. It also contains
#' possibly adjusted design weights.
#'
#' \item \sQuote{Done.} Dismisses the GUI dialog box, leaving any analysis
#' objects in the \code{.GlobalEnv} workspace.
#'
#' }
#'
#' @author Jason Mitchell (jmitchell@@west-inc.com)
#'
#' @seealso \code{\link{spsurvey::cat.analysis}}, \code{\link{spsurvey::cont.analysis}}
#'
#' @references Kincaid, T. (2015). Analysis of a GRTS Survey Design for a Finite
#' Resource. Accessed online May 6, 2016.
#' \code{https://cran.r-project.org/web/packages/spsurvey/vignettes/Finite_Analysis.pdf}.
#'
#' Kincaid, T. (2015). Analysis of a GRTS Survey Design for an Area Resource.
#' Accessed online May 6, 2016.
#' \code{https://cran.r-project.org/web/packages/spsurvey/vignettes/Area_Analysis.pdf}.
#'
#' Starcevich L. A., DiDonato G., McDonald T., Mitchell, J. (2016). A GRTS
#' User\eqn{'}s Manual for the SDrawNPS Package: A graphical user interface for
#' Generalized Random Tessellation Stratified (GRTS) sampling and estimation.
#' National Park Service, U.S. Department of the Interior. Natural Resource
#' Report NPS/XXXX/NRR—20XX/XXX.
#'
#' Stevens, D. L. and A. R. Olsen (2004). Spatially balanced sampling of
#' natural resources. Journal of the American Statistical Association 99,
#' 262-278.
#'
#' @keywords design survey analysis missing
#'
#' @examples
#' # Open a GUI for analysis of a GRTS-obtained sample.
#' analysis.GUI()
#'
analysis.GUI <- function() {
#
# Setup and run a GUI to take inputs for an analysis file.
#
#
# ---- Define the main window
win <- gtkWindowNew("toplevel")
win$setSizeRequest(750,525) # width height
win$setBorderWidth(8)
win$setTitle("SDrawNPS : Continuous variable analysis interface")
vbox1 <- gtkVBoxNew(FALSE, 8)
vbox1$setBorderWidth(8)
win$add(vbox1)
# --------------------------- Middle horizontal box ---------------
# req.frame <- gtkFrameNew("Required Inputs")
# vbox1$packStart(req.frame)
#
# hbox1 <- gtkVBoxNew(FALSE, 8) #sets up middle horizontal box, FALSE means things not evenly spaced, 8 is for 8 pixels between things
# hbox1$setBorderWidth(8)
# req.frame$add(hbox1) #this adds the new horizontal box to the frame which is in the overall vertical box. we are building the window vertically
req.frame <- gtkFrameNew("Required Inputs")
req.frame$setBorderWidth(8)
hbox2 <- gtkHBoxNew(FALSE, 8)
hbox2$packStart(req.frame)
vbox1$packStart(hbox2)
#--------------------------- Middle horizontal box ---------------
# req.frame <- gtkFrameNew("Required Inputs")
# vbox1$packStart(req.frame)
hbox1 <- gtkVBoxNew(FALSE, 1) #sets up middle horizontal box, FALSE means things not evenly spaced, 8 is for 8 pixels between things
hbox1$setBorderWidth(1)
req.frame$add(hbox1) #this adds the new horizontal box to the frame which is in the overall vertical box. we are building the window vertically
# ================= Required Inputs frame ============================
frame.frame <- gtkFrameNew("Sample Information")
hbox1$add(frame.frame) # Adds the frame to the horizontal box
# ---- Define a vertical box
req.vbox <- gtkVBoxNew(FALSE, 8)
req.vbox$setBorderWidth(8)
frame.frame$add(req.vbox)
# ---- Define table of boxes so everything aligns
tbl <- gtkTable(18,2,FALSE) #3 rows, 2 columns, FALSE for nonhomogeneous
gtkTableSetRowSpacings(tbl,1) #1 pixel between rows
gtkTableSetColSpacings(tbl,5) #5 pixels between columns
# hbox1$packStart(tbl)
req.vbox$packStart(tbl)
# ---- Input csv file box
shape.in.entry <- gtkEntry()
shape.in.entry$setText( "" )
shape.file.label <- gtkLabel("CSV file OR data.frame object:")
shape.in.dir <- gtkEntry() # this entry box is hidden/not displayed
shape.in.dir$setText( getwd() )
#out.r.entry <- gtkEntry()
#out.r.entry$setText( "" )
# ---- Output R object box
out.r.entry <- gtkEntry()
out.r.entry$setText("")#paste("sdraw.", format(Sys.time(), "%Y.%m.%d.%H%M%S"), sep=""))
out.r.label <- gtkLabel("Output File:")
gtkTableAttach(tbl,out.r.label, 0, 1, 3, 4, xpadding=5, ypadding=0)
gtkTableAttach(tbl,out.r.entry, 1, 2, 3, 4, xpadding=5, ypadding=0)
shape.file.box <- gtkHBox(FALSE, 10)
browse.b <- gtkButton("Browse")
gSignalConnect(browse.b, "clicked", browse.for.shapefile,data=list(
shape.in.entry = shape.in.entry,
shape.in.dir = shape.in.dir,
out.r.entry = out.r.entry,
parent.window = win
))
shape.file.box$packEnd(browse.b)
shape.file.box$packStart(shape.in.entry)
gtkTableAttach(tbl,shape.file.label, 0, 1, 1, 2, xpadding=5, ypadding=0)
gtkTableAttach(tbl,shape.file.box, 1, 2, 1, 2, xpadding=5, ypadding=0)
# ---- needed analysis variables
# siteID
siteID.entry <- gtkEntryNew()
siteID.entry$setText( "siteID" )
siteID.label <- gtkLabel("Site-ID Variable:")
gtkTableAttach(tbl,siteID.label, 0, 1, 5, 6, xpadding=5, ypadding=0)
gtkTableAttach(tbl,siteID.entry, 1, 2, 5, 6, xpadding=5, ypadding=0)
# EvalStatus
evalStatus.entry <- gtkEntryNew()
evalStatus.entry$setText( "EvalStatus" )
evalStatus.label <- gtkLabel("Evaluation Status Variable:")
gtkTableAttach(tbl,evalStatus.label, 0, 1, 7, 8, xpadding=5, ypadding=0)
gtkTableAttach(tbl,evalStatus.entry, 1, 2, 7, 8, xpadding=5, ypadding=0)
# Target_Sampled
evalStatusYes.entry <- gtkEntryNew()
evalStatusYes.entry$setText( "Target - Surveyed" )
evalStatusYes.label <- gtkLabel("Inclusion Identifier:")
#evalStatusYes.label$setMarkup("<span color='red'>Inclusion Identifier:</span>")
gtkTableAttach(tbl,evalStatusYes.label, 0, 1, 9, 10, xpadding=5, ypadding=0)
gtkTableAttach(tbl,evalStatusYes.entry, 1, 2, 9, 10, xpadding=5, ypadding=0)
# (sub)Population 2 -- recall population 1 is all elements together
pop2.entry <- gtkEntryNew()
pop2.entry$setText( "" )
pop2.label <- gtkLabel("Stratum / Subpopulation 1:")
gtkTableAttach(tbl,pop2.label, 0, 1, 11, 12, xpadding=5, ypadding=0)
gtkTableAttach(tbl,pop2.entry, 1, 2, 11, 12, xpadding=5, ypadding=0)
# (sub)Population 3 -- recall population 1 is all elements together
pop3.entry <- gtkEntryNew()
pop3.entry$setText( "" )
pop3.label <- gtkLabel("Stratum / Subpopulation 2:")
gtkTableAttach(tbl,pop3.label, 0, 1, 13, 14, xpadding=5, ypadding=0)
gtkTableAttach(tbl,pop3.entry, 1, 2, 13, 14, xpadding=5, ypadding=0)
# wgt
wgt.entry <- gtkEntryNew()
wgt.entry$setText( "wgt" )
wgt.label <- gtkLabel("Weight Variable:")
gtkTableAttach(tbl,wgt.label, 0, 1, 15, 16, xpadding=5, ypadding=0)
gtkTableAttach(tbl,wgt.entry, 1, 2, 15, 16, xpadding=5, ypadding=0)
# xcoord
xcoord.entry <- gtkEntryNew()
xcoord.entry$setText( "xcoord" )
xcoord.label <- gtkLabel("X-Coordinate:")
gtkTableAttach(tbl,xcoord.label, 0, 1, 17, 18, xpadding=5, ypadding=0)
gtkTableAttach(tbl,xcoord.entry, 1, 2, 17, 18, xpadding=5, ypadding=0)
# ycoord
ycoord.entry <- gtkEntryNew()
ycoord.entry$setText( "ycoord" )
ycoord.label <- gtkLabel("Y-Coordinate:")
gtkTableAttach(tbl,ycoord.label, 0, 1, 19, 20, xpadding=5, ypadding=0)
gtkTableAttach(tbl,ycoord.entry, 1, 2, 19, 20, xpadding=5, ypadding=0)
# continuous analysis variable
# cont.var.entry <- gtkEntryNew()
# cont.var.entry$setText( "contvar" )
# cont.var.label <- gtkLabel("Continuous Outcome:")
# gtkTableAttach(tbl,cont.var.label, 0, 1, 21, 22, xpadding=5, ypadding=5)
# gtkTableAttach(tbl,cont.var.entry, 1, 2, 21, 22, xpadding=5, ypadding=5)
# analysis variable(s)
vars.entry <- gtkEntryNew()
vars.entry$setText( "variable1, variable2, variable3, ..." )
vars.label <- gtkLabel("Outcome(s):")
gtkTableAttach(tbl,vars.label, 0, 1, 21, 22, xpadding=5, ypadding=0)
gtkTableAttach(tbl,vars.entry, 1, 2, 21, 22, xpadding=5, ypadding=0)
# confidence level variable(s)
conf.entry <- gtkEntryNew()
conf.entry$setText(95)
conf.label <- gtkLabel("Confidence Level:")
gtkTableAttach(tbl,conf.label, 0, 1, 23, 24, xpadding=5, ypadding=0)
gtkTableAttach(tbl,conf.entry, 1, 2, 23, 24, xpadding=5, ypadding=0)
# ============================ Sample Weights frame ===========
# ---- Separator
#vbox1$packStart(gtkHSeparatorNew(), expand=FALSE)
samp.frame <- gtkFrameNew("Optional Weighting Inputs")
vbox1$packStart(samp.frame)
# # ---- NEW ------------------------------------
# # ---- Define a vertical box
# req.vbox <- gtkVBoxNew(FALSE, 8)
# req.vbox$setBorderWidth(8)
# frame.frame$add(req.vbox)
# # ---- NEW ------------------------------------
hbox1 <- gtkHBoxNew(FALSE, 1) #sets up middle horizontal box, FALSE means things not evenly spaced, 8 is for 8 pixels between things
hbox1$setBorderWidth(1)
samp.frame$add(hbox1) #this adds the new horizontal box to the frame which is in the overall vertical box. we are building the window vertically
# add weight boxes.
samp.weight.frame <- gtkFrameNew("Adjust Weights?")
hbox1$add(samp.weight.frame) # alloc
# Radio Buttons to Specify Sample Weights
stype.box <- gtkHBoxNew(TRUE, 0)
stype.box$setBorderWidth(0)
samp.weight.frame$add( stype.box )
n.rb <- gtkRadioButtonNewWithLabel(label="No") # prop.rb
y.rb <- gtkRadioButtonNewWithLabelFromWidget(n.rb,"Yes") #const.rb
stype.box$packStart(y.rb, TRUE, TRUE, 0)
stype.box$packStart(n.rb, TRUE, TRUE, 0)
popn.weight.frame <- gtkFrameNew("Population Inference")
hbox1$add(popn.weight.frame) # alloc
# Radio Buttons to Specify popn Parameter in Adj Wgt Function
ttype.box <- gtkHBoxNew(TRUE, 0)
ttype.box$setBorderWidth(0)
popn.weight.frame$add( ttype.box )
T.rb <- gtkRadioButtonNewWithLabel(label="Target") # popn="Target"
S.rb <- gtkRadioButtonNewWithLabelFromWidget(T.rb,label="Sampled") #popn="Sampled"
ttype.box$packStart(T.rb, TRUE, TRUE, 0)
ttype.box$packStart(S.rb, TRUE, TRUE, 0)
# ------ display box
display.hbox <- gtkHBoxNew(TRUE, 2)
display.hbox$setBorderWidth(8)
hbox2$packStart(display.hbox)
display.frame <- gtkFrameNew("Data Info")
display.hbox$packStart(display.frame)
display.vbox <- gtkVBoxNew(FALSE, 8)
display.vbox$setBorderWidth(8)
display.frame$add(display.vbox)
# ---- Define table of boxes so everything aligns
finfo.title <- gtkLabel("Sample\nContents: \n<pending>")
display.vbox$packStart(finfo.title, expand=FALSE, fill=FALSE)
display.vbox$packStart(gtkVSeparatorNew(), expand=FALSE)
max.vars <- 20 # maximum number of variables to display
n.blank.cols <- 4 # must be even, half place on left and half on right
finfo.tbl <- gtkTable(max.vars+1,n.blank.cols+2,FALSE) #FALSE for nonhomogeneous
gtkTableSetRowSpacings(finfo.tbl,1) #1 pixel between rows
gtkTableSetColSpacings(finfo.tbl,5) #5 pixels between columns
display.vbox$packStart(finfo.tbl)
# Allocate the labels
names.labs <- lapply(1:(max.vars+1), gtkLabel, str="")
vtypes.labs <- lapply(1:(max.vars+1), gtkLabel, str="")
# Place column header labels
names.labs[[1]]$setText("VARIABLE")
vtypes.labs[[1]]$setText("CLASS")
gtkTableAttach(finfo.tbl, names.labs[[1]], (n.blank.cols/2), (n.blank.cols/2)+1, 0,1 )
gtkTableAttach(finfo.tbl, vtypes.labs[[1]], (n.blank.cols/2)+1, (n.blank.cols/2)+2, 0,1 )
# Place separators
gtkTableAttach(finfo.tbl, gtkHSeparatorNew(), (n.blank.cols/2), (n.blank.cols/2)+1, 1,2)
gtkTableAttach(finfo.tbl, gtkHSeparatorNew(), (n.blank.cols/2)+1, (n.blank.cols/2)+2, 1,2)
# Set their length
# f.setlablen <-function(x,lablist){
# lablist[[x]]$setWidthChars(25)
# #lablist[[x]]$setJustify(GTK_JUSTIFY_LEFT)
# #lablist[[x]]$setAlignment(0,.5)
# }
# names.labs <- lapply(1:(max.vars+1), f.setlablen, lablist=names.labs)
# vtypes.labs <- lapply(1:(max.vars+1), f.setlablen, lablist=vtypes.labs)
# place them
placelabs <- function(x, lablist, obj, labcol, bcols){
gtkTableAttach( obj, lablist[[x+1]], bcols+labcol-1, bcols+labcol, x-1+2, x+2) # + 2 for header
}
lapply(1:max.vars, placelabs, lablist=names.labs, obj=finfo.tbl, labcol=1, bcols=n.blank.cols/2)
lapply(1:max.vars, placelabs, lablist=vtypes.labs, obj=finfo.tbl, labcol=2, bcols=n.blank.cols/2 )
# blank.labs <- lapply(1:(n.blank.cols+2), gtkLabel, str=" ")
# placeblanklabs <- function(x, lablist, obj, side){
# gtkTableAttach( obj, lablist[[side+x]], side+x-1, side+x, 0, 1)
# }
# lapply(1:(n.blank.cols/2), placeblanklabs, lablist=blank.labs, obj=finfo.tbl, side=0)
# lapply(1:(n.blank.cols/2), placeblanklabs, lablist=blank.labs, obj=finfo.tbl, side=(n.blank.cols/2)+1)
# Initial values in columns, and hide all but first
names.labs[[2]]$setText("<pending>")
vtypes.labs[[2]]$setText("<pending>")
lapply(2:max.vars, function(x,lablist){lablist[[x+1]]$hide()}, lablist=names.labs)
lapply(2:max.vars, function(x,lablist){lablist[[x+1]]$hide()}, lablist=vtypes.labs)
# =========================== Bottom row of buttons ==================================
# ---- Separator
#vbox1$packStart(gtkHSeparatorNew(), expand=FALSE)
# ---- Define box for row of buttons at bottom
bbox <- gtkHButtonBox()
bbox$SetLayout("Spread") # Layout can be c("Start", "Edge", "Spread", "End")
bbox$SetBorderWidth(10)
# ---- Read frame button, but do not draw sample, this displays variables in shapefile
read.b <- gtkButton("Inspect\n Sample")
gSignalConnect(read.b, "clicked", readButtonActionCSV,
data=list(
shape.in.entry=shape.in.entry,
shape.in.dir=shape.in.dir,
out.r.entry=out.r.entry,
name.labs=names.labs,
type.labs=vtypes.labs,
finfo.title=finfo.title
)
)
bbox$packEnd(read.b, expand=FALSE)
# ---- Run button
run.b <- gtkButton("Run")
gSignalConnect(run.b, "clicked", analysis, data=list(
shape.in.entry=shape.in.entry,
shape.in.dir=shape.in.dir,
siteID.entry=siteID.entry,
evalStatus.entry=evalStatus.entry,
evalStatusYes.entry=evalStatusYes.entry,
pop2.entry=pop2.entry,
pop3.entry=pop3.entry,
wgt.entry=wgt.entry,
xcoord.entry=xcoord.entry,
ycoord.entry=ycoord.entry,
#cont.var.entry=cont.var.entry,
vars.entry=vars.entry,
out.r.entry = out.r.entry,
y.rb=y.rb,
n.rb=n.rb,
S.rb=S.rb,
T.rb=T.rb,
conf.entry=conf.entry
)
)
bbox$packEnd(run.b, expand=FALSE)
# ---- Read frame button, but do not draw sample, this plots resulting CDF
# plot.b <- gtkButton(" Plot\nCDF")
# gSignalConnect(plot.b, "clicked", analysisPlotCDF,
# data=list(
# )
# )
# bbox$packEnd(plot.b, expand=FALSE)
# ---- View button
view.b <- gtkButton("Tabulate\n Sample")
gSignalConnect(view.b, "clicked", view.analysis.sample, data=list(
out.r.entry = out.r.entry
))
bbox$packEnd( view.b, expand=FALSE)
# # ---- Write to csv button
# write.csv.b <- gtkButton("Export")
# gSignalConnect(write.csv.b, "clicked", my.write.csv, data=list(
# out.r.entry = out.r.entry,
# parent.window = win
# ))
# bbox$packEnd( write.csv.b, expand=FALSE)
# ---- Done button
cancel.b <- gtkButton("Done")
gSignalConnect(cancel.b, "clicked", function(x){
win$Hide();
win$Destroy()
})
bbox$packEnd( cancel.b, expand=FALSE)
# ---- Pack the rows of buttons into the vertical box
vbox1$packEnd( bbox, expand=FALSE)
gtkWindowResize(win,678,525)
# ---- Finally, show the window
win$Show()
}
tmcd82070/SDrawNPS documentation built on May 31, 2019, 4:37 p.m.
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#' @export analysis.GUI
#'
#' @title Graphic User Interface (GUI) to analyze the status of categorical
#' or continuous variables collected via GRTS samples.
#'
#' @description Initiates a dialog box via a GUI to analyze samples
#' from 2-D resources.
#'
#' @return A data frame with the name specified by the user in the GUI\eqn{'}s
#' \code{Output File} box. This data frame contains the sampling analysis
#' specifications, along with coordinates and projection information. Analysis
#' data frames are stored in the current workspace, while any export files,
#' including a \code{txt} log of the commands utilized to generate the sample,
#' as well as plots of empirical distribution functions and a \code{csv} of
#' their underlying data, are saved to the file directory specified via
#' \code{getwd}.
#'
#' @details This routine is intended to be called from the \code{SDrawNPS} menu,
#' but it can also be called from the command line in non-interactive
#' environments, such as RStudio. This routine uses the \code{RGtk2} package
#' windowing capabilities to construct a pop-up dialog box, or GUI. In the
#' dialog box, users specify at least the required input parameters, then
#' press the \sQuote{Run} button to analyze the sample.
#'
#' On submission, the GUI internally packages its inputs, processes the
#' necessary data, and executes the \code{spsurvey}-package
#' \code{cat.analysis} function for the analysis of categorical variables and
#' \code{cont.analysis} function for the same with respect to numeric
#' variables. All \code{SDrawNPS} GUI submissions utilizing the
#' \code{spsurvey} package analysis methodologies lead to the creation of a
#' text-based log file, which records all code utilized. The log file thus
#' serves as a historical record containing analysis information. It also
#' serves as a tool for enhancing methodological understanding.
#'
#' See \sQuote{References} for additional resources.
#'
#' @section Required Inputs:
#'
#' \enumerate{
#'
#' \item \sQuote{CSV file OR data.frame object} -- Specify the data frame or
#' \code{csv} containing the data for which analysis is required, or click
#' \sQuote{Browse} to browse for a data file with a \code{.csv} extension.
#' When specifying the name of a data file via use of the input box, do not
#' include the \code{.csv} extension. Following identification of the data,
#' click the \sQuote{Inspect Sample} button to list its variables.
#'
#' \item \sQuote{Output File} -- Specify the sample\eqn{'}s R object name to which
#' all analysis results will be assigned. The output will be a data frame
#' containing analysis results.
#'
#' \item \sQuote{Site-ID Variable} -- The case-sensitive variable in the input
#' data frame or \code{csv} identifying unique site identifiers.
#'
#' \item \sQuote{Evaluation Status Variable} -- The case-sensitive variable in
#' the input data frame or \code{csv} identifying which sites consitute the
#' surveyed targets. See \sQuote{Inclusion Identifier.}
#'
#' \item \sQuote{Inclusion Identifier} -- The case-sensitive text string that
#' identifies surveyed targets of sites in the variable identified via the
#' \sQuote{Evaluation Status Variable} box.
#'
#' \item \sQuote{Stratum / Subpopulation 1} -- The case-sensitive variable in
#' the input data frame or \code{csv} containing a stratification variable.
#' For example, this could be an elevational class associated with every point
#' in the shapefile. Constant values of this variable define the strata. This
#' box can be left blank if analysis requires no consideration of any strata.
#'
#' \item \sQuote{Stratum / Subpopulation 2} -- Same as \sQuote{Stratum /
#' Subpopuation 1}.
#'
#' \item \sQuote{Weight Variable} -- The case-sensitive variable in the input
#' data frame or \code{csv} containing the design weights of included sites.
#' Adjustment of included design weights, if appropriate, occurs via the
#' \sQuote{Adjust Weights?} and \sQuote{Population Inference} sections of the
#' GUI. See \sQuote{Optional Weighting Inputs.}
#'
#' \item \sQuote{X-Coordinate} -- The case-sensitive variable in the input
#' data frame or \code{csv} containing the \eqn{x}-coordinate of included
#' sites. Units do not matter.
#'
#' \item \sQuote{Y-Coordinate} -- The case-sensitive variable in the input
#' data frame or \code{csv} containing the \eqn{y}-coordinate of included
#' sites. Units do not matter.
#'
#' \item \sQuote{Outcome(s)} -- The list of case-sensitive variables in the
#' input data frame or \code{csv} for which analysis is required. Enter
#' multiple variables separated by commas and a space.
#'
#' \item \sQuote{Confidence Level} -- The confidence level to be utilized in
#' the analysis.
#'
#' }
#'
#' @section Optional Weighting Inputs:
#'
#' \enumerate{
#'
#' \item \sQuote{Adjust Weights?} -- When set to \sQuote{Yes}, design weights
#' specified via the \sQuote{Weight Variable} box are adjusted for frame
#' error. See function \code{Adjwgt_FrameNR}. No adjustment occurs when set
#' to \sQuote{No}.
#'
#' \item \sQuote{Population Inference} -- Assuming that the \sQuote{Adjust
#' Weights?} radio button is set to \sQuote{Yes}, selection of the
#' \sQuote{Population Inference} radio button specifies the value of the
#' \code{popn} argument in function \code{Adjwgt_FrameNR}. Explicitly,
#' selection of \sQuote{Target} specifies \code{popn="Target"} in
#' \code{Adjwgt_FrameNR}, while selection of \sQuote{Sampled} specifies
#' \code{popn="Sampled"}.
#'
#' }
#'
#' @section Dialog Buttons:
#'
#' \enumerate{
#'
#' \item \sQuote{Inspect Sample.} After specifying the \code{csv} file or data
#' frame object name, pressing the \sQuote{Inspect Sample} button lists all of
#' its constituent variables and vector classes.
#'
#' \item \sQuote{Run.} After specifying all required and optional inputs, the
#' \sQuote{Run} button analyzes the sample. The \code{.GlobalEnv} workspace
#' holds the resulting data frame entitled via the name specified in the GUI
#' \sQuote{Output File} box. A confirmation dialog appears following
#' completion of the analysis.
#'
#' \item \sQuote{Tabulate Sample.} Following analysis, display the GRTS
#' analysis file in a tabular format. The GRTS analysis file contains
#' information on each sampled unit, such as coordinates, and design
#' variables, e.g., stratum or multi-density category. It also contains
#' possibly adjusted design weights.
#'
#' \item \sQuote{Done.} Dismisses the GUI dialog box, leaving any analysis
#' objects in the \code{.GlobalEnv} workspace.
#'
#' }
#'
#' @author Jason Mitchell (jmitchell@@west-inc.com)
#'
#' @seealso \code{\link{spsurvey::cat.analysis}}, \code{\link{spsurvey::cont.analysis}}
#'
#' @references Kincaid, T. (2015). Analysis of a GRTS Survey Design for a Finite
#' Resource. Accessed online May 6, 2016.
#' \code{https://cran.r-project.org/web/packages/spsurvey/vignettes/Finite_Analysis.pdf}.
#'
#' Kincaid, T. (2015). Analysis of a GRTS Survey Design for an Area Resource.
#' Accessed online May 6, 2016.
#' \code{https://cran.r-project.org/web/packages/spsurvey/vignettes/Area_Analysis.pdf}.
#'
#' Starcevich L. A., DiDonato G., McDonald T., Mitchell, J. (2016). A GRTS
#' User\eqn{'}s Manual for the SDrawNPS Package: A graphical user interface for
#' Generalized Random Tessellation Stratified (GRTS) sampling and estimation.
#' National Park Service, U.S. Department of the Interior. Natural Resource
#' Report NPS/XXXX/NRR—20XX/XXX.
#'
#' Stevens, D. L. and A. R. Olsen (2004). Spatially balanced sampling of
#' natural resources. Journal of the American Statistical Association 99,
#' 262-278.
#'
#' @keywords design survey analysis missing
#'
#' @examples
#' # Open a GUI for analysis of a GRTS-obtained sample.
#' analysis.GUI()
#'
analysis.GUI <- function() {
#
# Setup and run a GUI to take inputs for an analysis file.
#
#
# ---- Define the main window
win <- gtkWindowNew("toplevel")
win$setSizeRequest(750,525) # width height
win$setBorderWidth(8)
win$setTitle("SDrawNPS : Continuous variable analysis interface")
vbox1 <- gtkVBoxNew(FALSE, 8)
vbox1$setBorderWidth(8)
win$add(vbox1)
# --------------------------- Middle horizontal box ---------------
# req.frame <- gtkFrameNew("Required Inputs")
# vbox1$packStart(req.frame)
#
# hbox1 <- gtkVBoxNew(FALSE, 8) #sets up middle horizontal box, FALSE means things not evenly spaced, 8 is for 8 pixels between things
# hbox1$setBorderWidth(8)
# req.frame$add(hbox1) #this adds the new horizontal box to the frame which is in the overall vertical box. we are building the window vertically
req.frame <- gtkFrameNew("Required Inputs")
req.frame$setBorderWidth(8)
hbox2 <- gtkHBoxNew(FALSE, 8)
hbox2$packStart(req.frame)
vbox1$packStart(hbox2)
#--------------------------- Middle horizontal box ---------------
# req.frame <- gtkFrameNew("Required Inputs")
# vbox1$packStart(req.frame)
hbox1 <- gtkVBoxNew(FALSE, 1) #sets up middle horizontal box, FALSE means things not evenly spaced, 8 is for 8 pixels between things
hbox1$setBorderWidth(1)
req.frame$add(hbox1) #this adds the new horizontal box to the frame which is in the overall vertical box. we are building the window vertically
# ================= Required Inputs frame ============================
frame.frame <- gtkFrameNew("Sample Information")
hbox1$add(frame.frame) # Adds the frame to the horizontal box
# ---- Define a vertical box
req.vbox <- gtkVBoxNew(FALSE, 8)
req.vbox$setBorderWidth(8)
frame.frame$add(req.vbox)
# ---- Define table of boxes so everything aligns
tbl <- gtkTable(18,2,FALSE) #3 rows, 2 columns, FALSE for nonhomogeneous
gtkTableSetRowSpacings(tbl,1) #1 pixel between rows
gtkTableSetColSpacings(tbl,5) #5 pixels between columns
# hbox1$packStart(tbl)
req.vbox$packStart(tbl)
# ---- Input csv file box
shape.in.entry <- gtkEntry()
shape.in.entry$setText( "" )
shape.file.label <- gtkLabel("CSV file OR data.frame object:")
shape.in.dir <- gtkEntry() # this entry box is hidden/not displayed
shape.in.dir$setText( getwd() )
#out.r.entry <- gtkEntry()
#out.r.entry$setText( "" )
# ---- Output R object box
out.r.entry <- gtkEntry()
out.r.entry$setText("")#paste("sdraw.", format(Sys.time(), "%Y.%m.%d.%H%M%S"), sep=""))
out.r.label <- gtkLabel("Output File:")
gtkTableAttach(tbl,out.r.label, 0, 1, 3, 4, xpadding=5, ypadding=0)
gtkTableAttach(tbl,out.r.entry, 1, 2, 3, 4, xpadding=5, ypadding=0)
shape.file.box <- gtkHBox(FALSE, 10)
browse.b <- gtkButton("Browse")
gSignalConnect(browse.b, "clicked", browse.for.shapefile,data=list(
shape.in.entry = shape.in.entry,
shape.in.dir = shape.in.dir,
out.r.entry = out.r.entry,
parent.window = win
))
shape.file.box$packEnd(browse.b)
shape.file.box$packStart(shape.in.entry)
gtkTableAttach(tbl,shape.file.label, 0, 1, 1, 2, xpadding=5, ypadding=0)
gtkTableAttach(tbl,shape.file.box, 1, 2, 1, 2, xpadding=5, ypadding=0)
# ---- needed analysis variables
# siteID
siteID.entry <- gtkEntryNew()
siteID.entry$setText( "siteID" )
siteID.label <- gtkLabel("Site-ID Variable:")
gtkTableAttach(tbl,siteID.label, 0, 1, 5, 6, xpadding=5, ypadding=0)
gtkTableAttach(tbl,siteID.entry, 1, 2, 5, 6, xpadding=5, ypadding=0)
# EvalStatus
evalStatus.entry <- gtkEntryNew()
evalStatus.entry$setText( "EvalStatus" )
evalStatus.label <- gtkLabel("Evaluation Status Variable:")
gtkTableAttach(tbl,evalStatus.label, 0, 1, 7, 8, xpadding=5, ypadding=0)
gtkTableAttach(tbl,evalStatus.entry, 1, 2, 7, 8, xpadding=5, ypadding=0)
# Target_Sampled
evalStatusYes.entry <- gtkEntryNew()
evalStatusYes.entry$setText( "Target - Surveyed" )
evalStatusYes.label <- gtkLabel("Inclusion Identifier:")
#evalStatusYes.label$setMarkup("<span color='red'>Inclusion Identifier:</span>")
gtkTableAttach(tbl,evalStatusYes.label, 0, 1, 9, 10, xpadding=5, ypadding=0)
gtkTableAttach(tbl,evalStatusYes.entry, 1, 2, 9, 10, xpadding=5, ypadding=0)
# (sub)Population 2 -- recall population 1 is all elements together
pop2.entry <- gtkEntryNew()
pop2.entry$setText( "" )
pop2.label <- gtkLabel("Stratum / Subpopulation 1:")
gtkTableAttach(tbl,pop2.label, 0, 1, 11, 12, xpadding=5, ypadding=0)
gtkTableAttach(tbl,pop2.entry, 1, 2, 11, 12, xpadding=5, ypadding=0)
# (sub)Population 3 -- recall population 1 is all elements together
pop3.entry <- gtkEntryNew()
pop3.entry$setText( "" )
pop3.label <- gtkLabel("Stratum / Subpopulation 2:")
gtkTableAttach(tbl,pop3.label, 0, 1, 13, 14, xpadding=5, ypadding=0)
gtkTableAttach(tbl,pop3.entry, 1, 2, 13, 14, xpadding=5, ypadding=0)
# wgt
wgt.entry <- gtkEntryNew()
wgt.entry$setText( "wgt" )
wgt.label <- gtkLabel("Weight Variable:")
gtkTableAttach(tbl,wgt.label, 0, 1, 15, 16, xpadding=5, ypadding=0)
gtkTableAttach(tbl,wgt.entry, 1, 2, 15, 16, xpadding=5, ypadding=0)
# xcoord
xcoord.entry <- gtkEntryNew()
xcoord.entry$setText( "xcoord" )
xcoord.label <- gtkLabel("X-Coordinate:")
gtkTableAttach(tbl,xcoord.label, 0, 1, 17, 18, xpadding=5, ypadding=0)
gtkTableAttach(tbl,xcoord.entry, 1, 2, 17, 18, xpadding=5, ypadding=0)
# ycoord
ycoord.entry <- gtkEntryNew()
ycoord.entry$setText( "ycoord" )
ycoord.label <- gtkLabel("Y-Coordinate:")
gtkTableAttach(tbl,ycoord.label, 0, 1, 19, 20, xpadding=5, ypadding=0)
gtkTableAttach(tbl,ycoord.entry, 1, 2, 19, 20, xpadding=5, ypadding=0)
# continuous analysis variable
# cont.var.entry <- gtkEntryNew()
# cont.var.entry$setText( "contvar" )
# cont.var.label <- gtkLabel("Continuous Outcome:")
# gtkTableAttach(tbl,cont.var.label, 0, 1, 21, 22, xpadding=5, ypadding=5)
# gtkTableAttach(tbl,cont.var.entry, 1, 2, 21, 22, xpadding=5, ypadding=5)
# analysis variable(s)
vars.entry <- gtkEntryNew()
vars.entry$setText( "variable1, variable2, variable3, ..." )
vars.label <- gtkLabel("Outcome(s):")
gtkTableAttach(tbl,vars.label, 0, 1, 21, 22, xpadding=5, ypadding=0)
gtkTableAttach(tbl,vars.entry, 1, 2, 21, 22, xpadding=5, ypadding=0)
# confidence level variable(s)
conf.entry <- gtkEntryNew()
conf.entry$setText(95)
conf.label <- gtkLabel("Confidence Level:")
gtkTableAttach(tbl,conf.label, 0, 1, 23, 24, xpadding=5, ypadding=0)
gtkTableAttach(tbl,conf.entry, 1, 2, 23, 24, xpadding=5, ypadding=0)
# ============================ Sample Weights frame ===========
# ---- Separator
#vbox1$packStart(gtkHSeparatorNew(), expand=FALSE)
samp.frame <- gtkFrameNew("Optional Weighting Inputs")
vbox1$packStart(samp.frame)
# # ---- NEW ------------------------------------
# # ---- Define a vertical box
# req.vbox <- gtkVBoxNew(FALSE, 8)
# req.vbox$setBorderWidth(8)
# frame.frame$add(req.vbox)
# # ---- NEW ------------------------------------
hbox1 <- gtkHBoxNew(FALSE, 1) #sets up middle horizontal box, FALSE means things not evenly spaced, 8 is for 8 pixels between things
hbox1$setBorderWidth(1)
samp.frame$add(hbox1) #this adds the new horizontal box to the frame which is in the overall vertical box. we are building the window vertically
# add weight boxes.
samp.weight.frame <- gtkFrameNew("Adjust Weights?")
hbox1$add(samp.weight.frame) # alloc
# Radio Buttons to Specify Sample Weights
stype.box <- gtkHBoxNew(TRUE, 0)
stype.box$setBorderWidth(0)
samp.weight.frame$add( stype.box )
n.rb <- gtkRadioButtonNewWithLabel(label="No") # prop.rb
y.rb <- gtkRadioButtonNewWithLabelFromWidget(n.rb,"Yes") #const.rb
stype.box$packStart(y.rb, TRUE, TRUE, 0)
stype.box$packStart(n.rb, TRUE, TRUE, 0)
popn.weight.frame <- gtkFrameNew("Population Inference")
hbox1$add(popn.weight.frame) # alloc
# Radio Buttons to Specify popn Parameter in Adj Wgt Function
ttype.box <- gtkHBoxNew(TRUE, 0)
ttype.box$setBorderWidth(0)
popn.weight.frame$add( ttype.box )
T.rb <- gtkRadioButtonNewWithLabel(label="Target") # popn="Target"
S.rb <- gtkRadioButtonNewWithLabelFromWidget(T.rb,label="Sampled") #popn="Sampled"
ttype.box$packStart(T.rb, TRUE, TRUE, 0)
ttype.box$packStart(S.rb, TRUE, TRUE, 0)
# ------ display box
display.hbox <- gtkHBoxNew(TRUE, 2)
display.hbox$setBorderWidth(8)
hbox2$packStart(display.hbox)
display.frame <- gtkFrameNew("Data Info")
display.hbox$packStart(display.frame)
display.vbox <- gtkVBoxNew(FALSE, 8)
display.vbox$setBorderWidth(8)
display.frame$add(display.vbox)
# ---- Define table of boxes so everything aligns
finfo.title <- gtkLabel("Sample\nContents: \n<pending>")
display.vbox$packStart(finfo.title, expand=FALSE, fill=FALSE)
display.vbox$packStart(gtkVSeparatorNew(), expand=FALSE)
max.vars <- 20 # maximum number of variables to display
n.blank.cols <- 4 # must be even, half place on left and half on right
finfo.tbl <- gtkTable(max.vars+1,n.blank.cols+2,FALSE) #FALSE for nonhomogeneous
gtkTableSetRowSpacings(finfo.tbl,1) #1 pixel between rows
gtkTableSetColSpacings(finfo.tbl,5) #5 pixels between columns
display.vbox$packStart(finfo.tbl)
# Allocate the labels
names.labs <- lapply(1:(max.vars+1), gtkLabel, str="")
vtypes.labs <- lapply(1:(max.vars+1), gtkLabel, str="")
# Place column header labels
names.labs[[1]]$setText("VARIABLE")
vtypes.labs[[1]]$setText("CLASS")
gtkTableAttach(finfo.tbl, names.labs[[1]], (n.blank.cols/2), (n.blank.cols/2)+1, 0,1 )
gtkTableAttach(finfo.tbl, vtypes.labs[[1]], (n.blank.cols/2)+1, (n.blank.cols/2)+2, 0,1 )
# Place separators
gtkTableAttach(finfo.tbl, gtkHSeparatorNew(), (n.blank.cols/2), (n.blank.cols/2)+1, 1,2)
gtkTableAttach(finfo.tbl, gtkHSeparatorNew(), (n.blank.cols/2)+1, (n.blank.cols/2)+2, 1,2)
# Set their length
# f.setlablen <-function(x,lablist){
# lablist[[x]]$setWidthChars(25)
# #lablist[[x]]$setJustify(GTK_JUSTIFY_LEFT)
# #lablist[[x]]$setAlignment(0,.5)
# }
# names.labs <- lapply(1:(max.vars+1), f.setlablen, lablist=names.labs)
# vtypes.labs <- lapply(1:(max.vars+1), f.setlablen, lablist=vtypes.labs)
# place them
placelabs <- function(x, lablist, obj, labcol, bcols){
gtkTableAttach( obj, lablist[[x+1]], bcols+labcol-1, bcols+labcol, x-1+2, x+2) # + 2 for header
}
lapply(1:max.vars, placelabs, lablist=names.labs, obj=finfo.tbl, labcol=1, bcols=n.blank.cols/2)
lapply(1:max.vars, placelabs, lablist=vtypes.labs, obj=finfo.tbl, labcol=2, bcols=n.blank.cols/2 )
# blank.labs <- lapply(1:(n.blank.cols+2), gtkLabel, str=" ")
# placeblanklabs <- function(x, lablist, obj, side){
# gtkTableAttach( obj, lablist[[side+x]], side+x-1, side+x, 0, 1)
# }
# lapply(1:(n.blank.cols/2), placeblanklabs, lablist=blank.labs, obj=finfo.tbl, side=0)
# lapply(1:(n.blank.cols/2), placeblanklabs, lablist=blank.labs, obj=finfo.tbl, side=(n.blank.cols/2)+1)
# Initial values in columns, and hide all but first
names.labs[[2]]$setText("<pending>")
vtypes.labs[[2]]$setText("<pending>")
lapply(2:max.vars, function(x,lablist){lablist[[x+1]]$hide()}, lablist=names.labs)
lapply(2:max.vars, function(x,lablist){lablist[[x+1]]$hide()}, lablist=vtypes.labs)
# =========================== Bottom row of buttons ==================================
# ---- Separator
#vbox1$packStart(gtkHSeparatorNew(), expand=FALSE)
# ---- Define box for row of buttons at bottom
bbox <- gtkHButtonBox()
bbox$SetLayout("Spread") # Layout can be c("Start", "Edge", "Spread", "End")
bbox$SetBorderWidth(10)
# ---- Read frame button, but do not draw sample, this displays variables in shapefile
read.b <- gtkButton("Inspect\n Sample")
gSignalConnect(read.b, "clicked", readButtonActionCSV,
data=list(
shape.in.entry=shape.in.entry,
shape.in.dir=shape.in.dir,
out.r.entry=out.r.entry,
name.labs=names.labs,
type.labs=vtypes.labs,
finfo.title=finfo.title
)
)
bbox$packEnd(read.b, expand=FALSE)
# ---- Run button
run.b <- gtkButton("Run")
gSignalConnect(run.b, "clicked", analysis, data=list(
shape.in.entry=shape.in.entry,
shape.in.dir=shape.in.dir,
siteID.entry=siteID.entry,
evalStatus.entry=evalStatus.entry,
evalStatusYes.entry=evalStatusYes.entry,
pop2.entry=pop2.entry,
pop3.entry=pop3.entry,
wgt.entry=wgt.entry,
xcoord.entry=xcoord.entry,
ycoord.entry=ycoord.entry,
#cont.var.entry=cont.var.entry,
vars.entry=vars.entry,
out.r.entry = out.r.entry,
y.rb=y.rb,
n.rb=n.rb,
S.rb=S.rb,
T.rb=T.rb,
conf.entry=conf.entry
)
)
bbox$packEnd(run.b, expand=FALSE)
# ---- Read frame button, but do not draw sample, this plots resulting CDF
# plot.b <- gtkButton(" Plot\nCDF")
# gSignalConnect(plot.b, "clicked", analysisPlotCDF,
# data=list(
# )
# )
# bbox$packEnd(plot.b, expand=FALSE)
# ---- View button
view.b <- gtkButton("Tabulate\n Sample")
gSignalConnect(view.b, "clicked", view.analysis.sample, data=list(
out.r.entry = out.r.entry
))
bbox$packEnd( view.b, expand=FALSE)
# # ---- Write to csv button
# write.csv.b <- gtkButton("Export")
# gSignalConnect(write.csv.b, "clicked", my.write.csv, data=list(
# out.r.entry = out.r.entry,
# parent.window = win
# ))
# bbox$packEnd( write.csv.b, expand=FALSE)
# ---- Done button
cancel.b <- gtkButton("Done")
gSignalConnect(cancel.b, "clicked", function(x){
win$Hide();
win$Destroy()
})
bbox$packEnd( cancel.b, expand=FALSE)
# ---- Pack the rows of buttons into the vertical box
vbox1$packEnd( bbox, expand=FALSE)
gtkWindowResize(win,678,525)
# ---- Finally, show the window
win$Show()
}
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