Setting up TclArray in R - r

I am new to coding and I am trying to set up TclArray in R, so anytime users checks the checkbutton in GUI, TclArray will get input 0 or 1. The issues in my code occurs in value2, the code does not assign 1 or 0 each checkbutton. Also, once I value is assign, how do I assign it to other regular array?
Thanks,
library(tcltk)
base2 = tktoplevel()
tkwm.title(base2,'Process data Input')
headers <- c("Files","Tool1","Tool2","Tool3","Tool4")
file_name_GUI <- c("SYS1","SYS2","SYS3","SYS4") #More system can be added
parameters <- tclArray()
nfrm2 = tkframe(base2)
fontSub <- tkfont.create(family="times",size=11.0, weight="bold")
fontSub2 <- tkfont.create(family="times",size=11.0)
for (i in 0:length(file_name_GUI))
{
if(i == 0)
{
f2 = tkframe(nfrm2)
value = tklabel(f2,text=headers[1], font = fontSub, width = 20,bg="gray64", relief = 'raised')
tkgrid(value, row = i, column=0, padx =1, pady =1)
}else
{
f2 = tkframe(nfrm2)
value1 = tklabel(f2,text=file_name_GUI[i], font = fontSub2, width = 23)
tkgrid(value1,row=i,column=0, padx = 1, pady = 1)
}
for (j in 1:4)
{
if (i == 0){
value = tklabel(f2,text=headers[j+1], font = fontSub, width = 20,bg="gray64", relief = 'raised')
tkgrid(value,row=i,column=j,padx=1,padx=1)
}
else {
value2 = tkcheckbutton(f2, variable = .Tcl(paste("set parameters(", i, ",", j, ") 1", sep = "")), width = 23) #Issue is here, I can't assign value to each checkbox.
tkgrid(value2,row = i, column = j, padx = 1, pady =1)
}
}
tkpack(f2,side ='top')
}
tkpack(nfrm2)

Related

Altering code behind crosstalk's filter_slider() function

I am trying to modify the appearance of a crosstalk filter slider by changing its colour and font. There is no built-in option to do this within the filter_slider() function, so I looked up the code behind the function to see if it specifies the colour and font of the output. I found nothing that indicates that it does, so I was wondering if it is possible to add some lines to the function that enable changing the colour of the slider and its font. I have very limited knowledge of writing functions, so I do not know how to modify a complicated function like this one. I am attaching the code behind the filter_slider() function below.
function (id, label, sharedData, column, step = NULL, round = FALSE,
ticks = TRUE, animate = FALSE, width = NULL, sep = ",",
pre = NULL, post = NULL, timeFormat = NULL, timezone = NULL,
dragRange = TRUE, min = NULL, max = NULL)
{
if (is.character(column)) {
column <- lazyeval::f_new(as.symbol(column))
}
df <- sharedData$data(withKey = TRUE)
col <- lazyeval::f_eval(column, df)
values <- na.omit(col)
if (is.null(min))
min <- min(values)
if (is.null(max))
max <- max(values)
value <- range(values)
ord <- order(col)
options <- list(values = col[ord], keys = df$key_[ord], group = sharedData$groupName())
findStepSize <- function(min, max, step) {
if (!is.null(step))
return(step)
range <- max - min
if (range < 2 || hasDecimals(min) || hasDecimals(max)) {
step <- pretty(c(min, max), n = 100)
step[2] - step[1]
}
else {
1
}
}
if (inherits(min, "Date")) {
if (!inherits(max, "Date") || !inherits(value,
"Date"))
stop("`min`, `max`, and `value must all be Date or non-Date objects")
dataType <- "date"
if (is.null(timeFormat))
timeFormat <- "%F"
}
else if (inherits(min, "POSIXt")) {
if (!inherits(max, "POSIXt") || !inherits(value,
"POSIXt"))
stop("`min`, `max`, and `value must all be POSIXt or non-POSIXt objects")
dataType <- "datetime"
if (is.null(timeFormat))
timeFormat <- "%F %T"
}
else {
dataType <- "number"
}
if (isTRUE(round))
round <- 0
else if (!is.numeric(round))
round <- NULL
step <- findStepSize(min, max, step)
step <- signif(step, 14)
if (dataType %in% c("date", "datetime")) {
to_ms <- function(x) 1000 * as.numeric(as.POSIXct(x))
step <- to_ms(max) - to_ms(max - step)
min <- to_ms(min)
max <- to_ms(max)
value <- to_ms(value)
}
range <- max - min
if (ticks) {
n_steps <- range/step
scale_factor <- ceiling(n_steps/10)
n_ticks <- n_steps/scale_factor
}
else {
n_ticks <- NULL
}
sliderProps <- dropNulls(list(`data-type` = if (length(value) >
1) "double", `data-min` = formatNoSci(min),
`data-max` = formatNoSci(max), `data-from` = formatNoSci(value[1]),
`data-to` = if (length(value) > 1) formatNoSci(value[2]),
`data-step` = formatNoSci(step), `data-grid` = ticks,
`data-grid-num` = n_ticks, `data-grid-snap` = FALSE,
`data-prettify-separator` = sep, `data-prefix` = pre,
`data-postfix` = post, `data-keyboard` = TRUE,
`data-keyboard-step` = step/(max - min) * 100,
`data-drag-interval` = dragRange, `data-round` = round,
`data-data-type` = dataType, `data-time-format` = timeFormat,
`data-timezone` = timezone))
sliderProps <- lapply(sliderProps, function(x) {
if (identical(x, TRUE))
"true"
else if (identical(x, FALSE))
"false"
else x
})
sliderTag <- div(class = "form-group crosstalk-input",
class = "crosstalk-input-slider js-range-slider",
id = id, style = if (!is.null(width))
paste0("width: ", validateCssUnit(width), ";"),
if (!is.null(label))
controlLabel(id, label), do.call(tags$input, sliderProps),
tags$script(type = "application/json", `data-for` = id,
jsonlite::toJSON(options, dataframe = "columns",
pretty = TRUE)))
if (identical(animate, TRUE))
animate <- shiny::animationOptions()
if (!is.null(animate) && !identical(animate, FALSE)) {
if (is.null(animate$playButton))
animate$playButton <- shiny::icon("play", lib = "glyphicon")
if (is.null(animate$pauseButton))
animate$pauseButton <- shiny::icon("pause",
lib = "glyphicon")
sliderTag <- tagAppendChild(sliderTag, tags$div(class = "slider-animate-container",
tags$a(href = "#", class = "slider-animate-button",
`data-target-id` = id, `data-interval` = animate$interval,
`data-loop` = animate$loop, span(class = "play",
animate$playButton), span(class = "pause",
animate$pauseButton))))
}
htmltools::browsable(attachDependencies(sliderTag, c(ionrangesliderLibs(),
crosstalkLibs())))
}
To change the font and colour of the slider, you don't need to modify the function. Instead, you can add some additional CSS to customise the appearance.
If you run the following Rmarkdown file, you can see the slider now has blue text and is in cursive font, with a red bar.
---
title: "Crosstalk Slider CSS"
output: html_document
---
<style>
.crosstalk-input-slider, .irs-grid-text{
color: blue;
font-family: cursive;
}
.irs-bar {
background-color:red;
}
</style>
## Crosstalk Slider CSS
```{r}
library(crosstalk)
shared_mtcars <- SharedData$new(mtcars)
filter_checkbox("cyl", "Cylinders", shared_mtcars, ~cyl, inline = TRUE)
filter_slider("hp", "Horsepower", shared_mtcars, ~hp, width = "100%")
filter_select("auto", "Automatic", shared_mtcars, ~ifelse(am == 0, "Yes", "No"))
```

How to modify pre-existing function in local environment in R

I am trying to modify an existing function by copy and pasting it to an R script, and assigning it to a new function object in my local environment. However the new function cannot find functions that are called to within the original function. How can I fix this without looking up and finding each function individually? I am guessing that the original function is somehow linked to the package or its dependencies and 'knows where to look' for the missing function, but I cannot figure out how to do this with my new copy-and-pasted function.
library("camtrapR")
Print the function name
activityDensity
The output here is the code for this function. I have omitted it here because it is long (and I have pasted it below), but I copy and paste the output of the function code exactly (see below where I assign this exact code to a new function), except for the last two lines of output, which I think are important:
<bytecode: 0x000000002a2d1e20>
<environment: namespace:camtrapR>
So now I assign the copy and pasted code from the output above to a new function with New <-
New <- function (recordTable, species, allSpecies = FALSE, speciesCol = "Species",
recordDateTimeCol = "DateTimeOriginal", recordDateTimeFormat = "%Y-%m-%d %H:%M:%S",
plotR = TRUE, writePNG = FALSE, plotDirectory, createDir = FALSE,
pngMaxPix = 1000, add.rug = TRUE, ...)
{
wd0 <- getwd()
mar0 <- par()$mar
on.exit(setwd(wd0))
on.exit(par(mar = mar0), add = TRUE)
recordTable <- dataFrameTibbleCheck(df = recordTable)
timeZone <- "UTC"
checkForSpacesInColumnNames(speciesCol = speciesCol, recordDateTimeCol = recordDateTimeCol)
if (!is.data.frame(recordTable))
stop("recordTable must be a data frame", call. = FALSE)
if (!speciesCol %in% colnames(recordTable))
stop(paste("speciesCol = \"", speciesCol, "\" is not a column name in recordTable",
sep = ""), call. = FALSE)
if (!recordDateTimeCol %in% colnames(recordTable))
stop(paste("recordDateTimeCol = \"", recordDateTimeCol,
"\" is not a column name in recordTable", sep = ""),
call. = FALSE)
stopifnot(is.logical(c(allSpecies, writePNG, plotR, createDir)))
if (allSpecies == FALSE) {
stopifnot(species %in% recordTable[, speciesCol])
stopifnot(hasArg(species))
}
recordTable$DateTime2 <- parseDateTimeObject(inputColumn = recordTable[,
recordDateTimeCol], dateTimeFormat = recordDateTimeFormat,
timeZone = timeZone)
recordTable$Time2 <- format(recordTable$DateTime2, format = "%H:%M:%S",
usetz = FALSE)
recordTable$Time.rad <- (as.numeric(as.POSIXct(strptime(recordTable$Time2,
format = "%H:%M:%S", tz = timeZone))) - as.numeric(as.POSIXct(strptime("0",
format = "%S", tz = timeZone))))/3600 * (pi/12)
if (isTRUE(writePNG)) {
if (hasArg(plotDirectory)) {
if (isTRUE(createDir)) {
dir.create(plotDirectory, recursive = TRUE, showWarnings = FALSE)
setwd(plotDirectory)
}
else {
stopifnot(file.exists(plotDirectory))
setwd(plotDirectory)
}
}
else {
stop("writePNG is TRUE. Please set plotDirectory",
call. = FALSE)
}
}
pngWidth <- pngMaxPix
pngHeight <- round(pngMaxPix * 0.8)
if (allSpecies == FALSE) {
subset_species <- subset(recordTable, recordTable[, speciesCol] ==
species)
if (nrow(subset_species) == 1)
stop(paste(species, "had only 1 record. Cannot estimate density."),
call. = FALSE)
try_error_tmp <- try({
if (isTRUE(writePNG))
png(filename = paste("activity_density_",
species, "_", Sys.Date(), ".png",
sep = ""), width = pngWidth, height = pngHeight,
units = "px", res = 96, type = "cairo")
if (isTRUE(writePNG) | isTRUE(plotR)) {
densityPlot(subset_species$Time.rad, main = paste("Activity of",
species), rug = add.rug, ...)
mtext(paste("number of records:", nrow(subset_species)),
side = 3, line = 0)
}
if (isTRUE(writePNG))
dev.off()
}, silent = TRUE)
if (class(try_error_tmp) == "try-error")
warning(paste(toupper(species), ": ", try_error_tmp[1],
" - SKIPPED", sep = ""), call. = FALSE)
}
else {
subset_species_list <- list()
for (i in 1:length(unique(recordTable[, speciesCol]))) {
spec.tmp <- unique(recordTable[, speciesCol])[i]
subset_species <- subset(recordTable, recordTable[,
speciesCol] == spec.tmp)
plot_main_title <- paste("Activity of", spec.tmp)
if (nrow(subset_species) == 1) {
warning(paste(toupper(spec.tmp), ": It had only 1 record. Cannot estimate density. - SKIPPED",
sep = ""), call. = FALSE)
next
}
else {
try_error_tmp <- try({
if (isTRUE(writePNG))
png(filename = paste("activity_density_",
spec.tmp, "_", Sys.Date(), ".png",
sep = ""), width = pngWidth, height = pngHeight,
units = "px", res = 96, type = "cairo")
if (isTRUE(writePNG) | isTRUE(plotR)) {
densityPlot(subset_species$Time.rad, main = plot_main_title,
rug = add.rug, ...)
mtext(paste("number of records:", nrow(subset_species)),
side = 3, line = 0)
}
if (isTRUE(writePNG))
dev.off()
}, silent = TRUE)
if (class(try_error_tmp) == "try-error")
warning(paste(toupper(spec.tmp), ": ",
try_error_tmp[1], " - SKIPPED",
sep = ""), call. = FALSE)
}
subset_species_list[[i]] <- subset_species$Time.rad
names(subset_species_list)[i] <- spec.tmp
}
}
if (allSpecies == FALSE) {
return(invisible(subset_species$Time.rad))
}
else {
return(invisible(subset_species_list))
}
}
Yet, when I try to run this new function (arguments omitted here for clarity), it can't find a function embedded within.
How can I somehow assign this function to look within the original package camtrapR for any dependencies, etc.? and why does the code output from the function not already do this?
New()
Error in dataFrameTibbleCheck(df = recordTable) :
could not find function "dataFrameTibbleCheck"
This answer here: https://stackoverflow.com/a/49277036/9096420 allows one to manually edit and save a function's code for each R session, but it is non-reproducible (not code) that can be shared or re-used.
If New is the new function copied from camtrapR then use
environment(New) <- asNamespace("camtrapR")
to ensure that the function calls in its body are looked up in the correct places.

Editing a function from a package in R?

I am using the referenceIntervals package in R, to do some data analytics.
In particular I am using the refLimit function which calculates reference and confidence intervals. I want to edit it to remove certain functionality (for instance it runs a shapiro normalitiy test, which stops the entire code if the data larger than 5000, it wont allow you to parametrically test samples less than 120). To do this I have been typing refLimit into the terminal - copying the function definition, then saving it as a separate file (below is the full original definition of the function).
singleRefLimit =
function (data, dname = "default", out.method = "horn", out.rm = FALSE,
RI = "p", CI = "p", refConf = 0.95, limitConf = 0.9)
{
if (out.method == "dixon") {
output = dixon.outliers(data)
}
else if (out.method == "cook") {
output = cook.outliers(data)
}
else if (out.method == "vanderLoo") {
output = vanderLoo.outliers(data)
}
else {
output = horn.outliers(data)
}
if (out.rm == TRUE) {
data = output$subset
}
outliers = output$outliers
n = length(data)
mean = mean(data, na.rm = TRUE)
sd = sd(data, na.rm = TRUE)
norm = NULL
if (RI == "n") {
methodRI = "Reference Interval calculated nonparametrically"
data = sort(data)
holder = nonparRI(data, indices = 1:length(data), refConf)
lowerRefLimit = holder[1]
upperRefLimit = holder[2]
if (CI == "p") {
CI = "n"
}
}
if (RI == "r") {
methodRI = "Reference Interval calculated using Robust algorithm"
holder = robust(data, 1:length(data), refConf)
lowerRefLimit = holder[1]
upperRefLimit = holder[2]
CI = "boot"
}
if (RI == "p") {
methodRI = "Reference Interval calculated parametrically"
methodCI = "Confidence Intervals calculated parametrically"
refZ = qnorm(1 - ((1 - refConf)/2))
limitZ = qnorm(1 - ((1 - limitConf)/2))
lowerRefLimit = mean - refZ * sd
upperRefLimit = mean + refZ * sd
se = sqrt(((sd^2)/n) + (((refZ^2) * (sd^2))/(2 * n)))
lowerRefLowLimit = lowerRefLimit - limitZ * se
lowerRefUpperLimit = lowerRefLimit + limitZ * se
upperRefLowLimit = upperRefLimit - limitZ * se
upperRefUpperLimit = upperRefLimit + limitZ * se
shap_normalcy = shapiro.test(data)
shap_output = paste(c("Shapiro-Wilk: W = ", format(shap_normalcy$statistic,
digits = 6), ", p-value = ", format(shap_normalcy$p.value,
digits = 6)), collapse = "")
ks_normalcy = suppressWarnings(ks.test(data, "pnorm",
m = mean, sd = sd))
ks_output = paste(c("Kolmorgorov-Smirnov: D = ", format(ks_normalcy$statistic,
digits = 6), ", p-value = ", format(ks_normalcy$p.value,
digits = 6)), collapse = "")
if (shap_normalcy$p.value < 0.05 | ks_normalcy$p.value <
0.05) {
norm = list(shap_output, ks_output)
}
else {
norm = list(shap_output, ks_output)
}
}
if (CI == "n") {
if (n < 120) {
cat("\nSample size too small for non-parametric confidence intervals, \n \t\tbootstrapping instead\n")
CI = "boot"
}
else {
methodCI = "Confidence Intervals calculated nonparametrically"
ranks = nonparRanks[which(nonparRanks$SampleSize ==
n), ]
lowerRefLowLimit = data[ranks$Lower]
lowerRefUpperLimit = data[ranks$Upper]
upperRefLowLimit = data[(n + 1) - ranks$Upper]
upperRefUpperLimit = data[(n + 1) - ranks$Lower]
}
}
if (CI == "boot" & (RI == "n" | RI == "r")) {
methodCI = "Confidence Intervals calculated by bootstrapping, R = 5000"
if (RI == "n") {
bootresult = boot::boot(data = data, statistic = nonparRI,
refConf = refConf, R = 5000)
}
if (RI == "r") {
bootresult = boot::boot(data = data, statistic = robust,
refConf = refConf, R = 5000)
}
bootresultlower = boot::boot.ci(bootresult, conf = limitConf,
type = "basic", index = 1)
bootresultupper = boot::boot.ci(bootresult, conf = limitConf,
type = "basic", index = 2)
lowerRefLowLimit = bootresultlower$basic[4]
lowerRefUpperLimit = bootresultlower$basic[5]
upperRefLowLimit = bootresultupper$basic[4]
upperRefUpperLimit = bootresultupper$basic[5]
}
RVAL = list(size = n, dname = dname, out.method = out.method,
out.rm = out.rm, outliers = outliers, methodRI = methodRI,
methodCI = methodCI, norm = norm, refConf = refConf,
limitConf = limitConf, Ref_Int = c(lowerRefLimit = lowerRefLimit,
upperRefLimit = upperRefLimit), Conf_Int = c(lowerRefLowLimit = lowerRefLowLimit,
lowerRefUpperLimit = lowerRefUpperLimit, upperRefLowLimit = upperRefLowLimit,
upperRefUpperLimit = upperRefUpperLimit))
class(RVAL) = "interval"
return(RVAL)
}
However when I then execute this file a large number of terms end up being undefined, for instance when I use the function I get 'object 'nonparRanks' not found'.
How do I edit the function in the package? I have looked at trying to important the package namespace and environment but this has not helped. I have also tried to find the actual function in the package files in my directory, but not been able to.
I am reasonably experienced in R, but I have never had to edit a package before. I am clearly missing something about how functions are defined in packages, but I am not sure what.
In the beginning of the package there is a line
data(sysdata, envir=environment())
See here: https://github.com/cran/referenceIntervals/tree/master/data/sysdata.rda
I suspect that "nonparRanks" is defined there as I don't see it defined anywhere else. So perhaps you could download that file, write your own function, then run that same line before running your function and it may work.
EDIT:
Download the file then run:
load("C:/sysdata.rda")
With your path to the file and then your function will work.
nonparRanks is a function in the referenceIntervals package:
Table that dictate the ranks for the confidence intervals
around thecalculated reference interval
Your method of saving and editing the function is fine, but make sure you load all the necessary underlying functions to run it too.
The easiest thing to do might be to:
save your copied and pasted R function as a different name, e.g. singleRefLimit2, then
call library("referenceIntervals"), which will load all the underlying functions you need and then
load your function source("singelRefLimit2.R"), with whatever edits you choose to make.

Filename in text box using tcltk in R

Using tcltk to create a GUI in R, I want to make a non-editable text box that displays the name of the save file that was selected by the user. I am able to create the button and the box, but I cannot figure out how to display the name of the selected file. I think I need to use tkinsert()
This is what I have so far:
library(tcltk)
library(tcltk2)
library(readxl)
test1 <- tktoplevel()
tkwm.title(test1, "Test 1")
tkgrid.rowconfigure(test1, 4)
tkgrid.columnconfigure(test1, 3)
getXlsx <- function() {
xlsheet <- tclvalue(tkgetOpenFile(
filetypes = "{ {Excel Files} {.xlsx} } { {All Files} * }"))
a <- read_excel(xlsheet)
assign("a", a, envir = .GlobalEnv)
}
test1$env$butSelect1 <- tk2button(test1, text = " Select File ", command
= getXlsx)
tkgrid(test1$env$butSelect1, padx = c(10,0), pady = 10, column = 0, row =
0)
test1$env$txt1 <- tk2text(test1, width = 40, height = 1)
tkgrid(test1$env$txt1, padx = c(10,10), pady = 10, column = 1, row = 0,
columnspan = 2)
tkconfigure(test1$env$txt1, state = "disabled")
### tkinsert(test1$env$txt1, ???) ###
Any help would be greatly appreciated, thank you.
I got it now, I had to add 4 lines to the function itself:
getXlsx <- function() {
xlsheet <- tclvalue(tkgetOpenFile(
filetypes = "{ {Excel Files} {.xlsx} } { {All Files} * }"))
a <- read_excel(xlsheet)
assign("a", a, envir = .GlobalEnv)
assign("z", xlsheet, envir = .GlobalEnv)
tkconfigure(test1$env$txt1, state = "normal")
tkinsert(test1$env$txt1, "end", z)
tkconfigure(test1$env$txt1, state = "disabled")
}
This creates a new "z" value in the global environment with the path name, then allows the text box to be editable, then adds the path name, then makes the text box non-editable again.

How can I add text to a network plot in R?

I am using the package networkDynamic to visualise two evolving networks and I would like to add, close to each network a simple legend (a few words of text). I can't find a way of doing this.
In the networkDynamic package, the function render.animation uses plot.network (from the package network) to render each frame and then compiles the different frames into an animation.
The plot.network arguments can be passed to render.animation, so the problem seems to boils down to adding text to a plot generated with plot.network but there doesn't seem to be a way of adding text at specified coordinates.
With a normal plot I would use the text function, but is there a way of including this function into the plot.network arguments?
render.animation is a function in the ndtv package. You will have to create a custom render.animation2 function based on render.animation. In the following function, I add an extra line to the render.animation function. I add an mtext after each plot.network calls (see about 20 lines from the end). You could change it to a text instead of mtext.
render.animation2 <- function (net, render.par = list(tween.frames = 10, show.time = TRUE,
show.stats = NULL, extraPlotCmds = NULL, initial.coords = 0),
plot.par = list(bg = "white"), ani.options = list(interval = 0.1),
render.cache = c("plot.list", "none"), verbose = TRUE, ...)
{
if (!is.network(net)) {
stop("render.animation requires the first argument to be a network object")
}
if (is.null(render.par)) {
stop("render.animation is missing the 'render.par' argument (a list of rendering parameters).")
}
if (is.null(render.par$tween.frames)) {
render.par$tween.frames <- 10
}
if (is.null(render.par$show.time)) {
render.par$show.time <- TRUE
}
if (is.null(render.par$initial.coords)) {
render.par$initial.coords <- matrix(0, ncol = 2, nrow = network.size(net))
}
if (!all(c("animation.x.active", "animation.y.active") %in%
list.vertex.attributes(net))) {
net <- compute.animation(net, verbose = verbose)
}
externalDevice <- FALSE
doRStudioHack <- TRUE
if (!is.null(render.par$do_RStudio_plot_hack)) {
doRStudioHack <- render.par$do_RStudio_plot_hack
}
if (!is.function(options()$device)) {
if (names(dev.cur()) == "RStudioGD" & doRStudioHack) {
message("RStudio's graphics device is not well supported by ndtv, attempting to open another type of plot window")
if (.Platform$OS.type == "windows") {
windows()
}
else if (length(grep(R.version$platform, pattern = "apple")) >
0) {
quartz()
}
else {
x11()
}
externalDevice <- TRUE
}
}
if (par("bg") == "transparent" & is.null(plot.par$bg)) {
plot.par$bg <- "white"
}
origPar <- par(plot.par)
oopts <- ani.options(ani.options)
slice.par <- get.network.attribute(net, "slice.par")
if (is.null(slice.par)) {
stop("render.animation can not locate the 'slice.par' list of parameters in the input network object")
}
render.cache <- match.arg(render.cache)
plot_params <- list(...)
if (is.null(plot_params$label)) {
plot_params$label <- function(slice) {
network.vertex.names(slice)
}
}
if (is.null(plot_params$xlab) & render.par$show.time) {
plot_params$xlab <- function(onset, terminus) {
ifelse(onset == terminus, paste("t=", onset, sep = ""),
paste("t=", onset, "-", terminus, sep = ""))
}
}
if (!is.null(render.par$show.stats) && render.par$show.stats !=
FALSE) {
if (render.par$show.time) {
plot_params$xlab <- eval(parse(text = paste("function(slice,onset,terminus){stats<-summary.statistics.network(slice",
render.par$show.stats, ")\n return(paste('t=',onset,'-',terminus,' ',paste(rbind(names(stats),stats),collapse=':'),sep='')) }",
sep = "")))
}
else {
plot_params$xlab <- eval(parse(text = paste("function(slice){stats<-summary.statistics.network(slice",
render.par$show.stats, ")\n return(paste(rbind(names(stats),stats),collapse=':')) }",
sep = "")))
}
}
if (is.null(plot_params$jitter)) {
plot_params$jitter <- FALSE
}
interp.fun <- coord.interp.smoothstep
starts <- seq(from = slice.par$start, to = slice.par$end,
by = slice.par$interval)
ends <- seq(from = slice.par$start + slice.par$aggregate.dur,
to = slice.par$end + slice.par$aggregate.dur, by = slice.par$interval)
xmin <- aggregate.vertex.attribute.active(net, "animation.x",
min)
xmax <- aggregate.vertex.attribute.active(net, "animation.x",
max)
ymin <- aggregate.vertex.attribute.active(net, "animation.y",
min)
ymax <- aggregate.vertex.attribute.active(net, "animation.y",
max)
if (is.null(plot_params$xlim)) {
if (xmin == xmax) {
xmax <- xmin + 1
xmin <- xmin - 1
}
plot_params$xlim <- c(xmin, xmax)
}
if (is.null(plot_params$ylim)) {
if (ymin == ymax) {
ymax <- ymin + 1
ymin <- ymin - 1
}
plot_params$ylim <- c(ymin, ymax)
}
if (is.numeric(render.par$initial.coords)) {
coords <- matrix(render.par$initial.coords, ncol = 2,
nrow = network.size(net))
}
slice <- network.collapse(net, starts[1], ends[1], rule = slice.par$rule,
rm.time.info = FALSE)
activev <- is.active(net, starts[1], ends[1], v = seq_len(network.size(net)),
rule = if (slice.par$rule != "all") {
"any"
})
if (length(slice) > 0 & network.size(slice) > 0) {
coords[activev, 1] <- get.vertex.attribute(slice, "animation.x")
coords[activev, 2] <- get.vertex.attribute(slice, "animation.y")
}
coords2 <- coords
if (render.cache == "plot.list") {
ani.record(reset = TRUE)
}
for (s in 1:length(starts)) {
if (verbose) {
print(paste("rendering", render.par$tween.frames,
"frames for slice", s - 1))
}
slice <- network.collapse(net, starts[s], ends[s], rule = slice.par$rule,
rm.time.info = FALSE)
activev <- is.active(net, starts[s], ends[s], v = seq_len(network.size(net)),
rule = if (slice.par$rule != "all") {
"any"
})
if (length(slice) > 0 & network.size(slice) > 0) {
evald_params <- .evaluate_plot_params(plot_params = plot_params,
net = net, slice = slice, s = s, onset = starts[s],
terminus = ends[s])
for (t in 1:render.par$tween.frames) {
coords2[activev, 1] <- get.vertex.attribute(slice,
"animation.x")
coords2[activev, 2] <- get.vertex.attribute(slice,
"animation.y")
tweenCoords <- interp.fun(coords, coords2, t,
render.par$tween.frames)
plot_args <- list(x = slice, coord = tweenCoords[activev,
, drop = FALSE])
plot_args <- c(plot_args, evald_params)
do.call(plot.network, plot_args)
mtext("my text\n on two lines", side = 3) #my.legend
if (!is.null(render.par$extraPlotCmds)) {
eval(render.par$extraPlotCmds)
}
if (render.cache == "plot.list") {
ani.record()
}
}
coords <- coords2
}
else {
evald_params <- .evaluate_plot_params(plot_params = plot_params,
net = net, slice = slice, s = s, onset = starts[s],
terminus = ends[s])
if (render.par$show.time) {
xlab <- evald_params$xlab
}
else {
xlab <- NULL
}
singlenet <- network.initialize(1)
for (t in 1:render.par$tween.frames) {
plot.network(singlenet, vertex.cex = 0, xlab = xlab)
if (!is.null(render.par$extraPlotCmds)) {
eval(render.par$extraPlotCmds)
}
if (render.cache == "plot.list") {
ani.record()
}
}
}
}
par(origPar)
if (externalDevice) {
dev.off()
}
}
It is then important to assign your new function render.animation2 to the ndtv namespace. If you don't, it will crash because render.animation refers to functions that can only be found in its own namespace.
environment(render.animation2) <- asNamespace('ndtv')
environment(render.animation) #<environment: namespace:ndtv>
environment(render.animation2) #<environment: namespace:ndtv>
Using, render.animation2, you will then get your legend printed on each slide of the animation.
require(ndtv)
triangle <- network.initialize(3) # create a toy network
add.edge(triangle,1,2)
# add an edge between vertices 1 and 2
add.edge(triangle,2,3)
# add a more edges
activate.edges(triangle,at=1) # turn on all edges at time 1 only
activate.edges(triangle,onset=2, terminus=3,
e=get.edgeIDs(triangle,v=1,alter=2))
add.edges.active(triangle,onset=4, length=2,tail=3,head=1)
render.animation2(triangle) #custom function
ani.replay()
Here's what the last slide looks like in the animation:
If you only need to add a few lines of text, you can pass the standard plot arguments main (for the main title) or xlab (for the x-axis caption). you can separate lines with the newline escape "\n"
library(ndtv)
data(short.stergm.sim)
render.animation(short.stergm.sim,main='hello\nworld')
It is also possible to plot other graphic elements (such as legend or text or maps) using the extraPlotCmds argument to render.animation. For example, if you wanted to plot "hello world" in blue at coordiantes 0,0 using text you can wrap it in an expression and pass it in via render.par
render.animation(short.stergm.sim,
render.par=list(extraPlotCmds=expression(
text(0,0,'hello\nworld',col='blue')
))
)
the extra plot command will evaluated on each frame as the network is rendered

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