Bill Dunlap
2022-Oct-06 14:43 UTC
[R] Getting "Error in ect, plot.new has not been called yet" despite grouping plot call
Here is how you could have made an example that helpers could easily run.
It also includes the fix.
f <- function(print.it = FALSE) {
pdf(file.pdf <- tempfile(fileext=".pdf"))
series <- as.xts(setNames(sin(seq(0,10,by=.1)),
seq(as.Date("2022-10-06"),by="weeks",len=101)))
p <- plot(series)
if (print.it) {
print(p)
}
sm_series_2 <- smooth(series / 2)
lines(sm_series_2, col="red")
abline(h=0.1, col="blue")
dev.off()
file.pdf
}> f()
Error in plot.xy(xy.coords(x, y), type = type, ...) :
plot.new has not been called yet> f(TRUE)
[1]
"C:\\Users\\willi\\AppData\\Local\\Temp\\Rtmp0wX7rO\\file34843df652c.pdf"
If you remove the pdf() and dev.off() I think you will see that the added
lines do not show up. I think plot.xts fiddles with the coordinate system
before and after it plots so that add-ons must be done in a special way.
-Bill
On Thu, Oct 6, 2022 at 12:42 AM Deramus, Thomas Patrick <
tderamus at partners.org> wrote:
> Hi Rolf.
>
> I followed your suggestion (though it's probably not as trimmed as it
> could be), but the problem unfortunately persists.
>
> Does this make it any clearer or still too many moving parts to make sense
> of?
>
> rm(list = ls(all.names = TRUE)) #will clear all objects includes hidden
> objects.
>
> #Loads the packages
> library(plyr)
> library(dplyr)
> library(ggplot2)
> library(Kendall)
> library(lubridate)
> library(xts)
> library(TTR)
> library(trend)
> library(forecast)
> library(openxlsx)
>
> #Uses the learningCurve Package from Github:
> #https://github.com/AFIT-R/learningCurve
> library(learningCurve)
>
> #Only load this if using VS Studio because it changes the plot function
> #
>
https://stackoverflow.com/questions/52284345/how-to-show-r-graph-from-visual-studio-code
> library(httpgd)
> library(languageserver)
>
> #Loads the Excel files to Dataframes and cleans the data
> Game_Metrics_Word_Task <-
> read.xlsx("GamePack_Analytics_ALL_TIME_Short.xlsx",
"Boggle")
> Game_Metrics_Word_Task <- Game_Metrics_Word_Task %>%
filter(grepl('1440',
> StudyId))
> Game_Metrics_Word_Task$DeviceTime <-
> ymd_hms(Game_Metrics_Word_Task$DeviceTime, tz =
"America/New_York")
> Game_Metrics_Word_Task <-
> Game_Metrics_Word_Task[!duplicated(Game_Metrics_Word_Task[1:2,])]
>
> #Splits the dataframe into a tibble containing each participant
> Participant_Word_Task <-
> split(arrange(Game_Metrics_Word_Task,StudyId,DeviceTime),
>
arrange(Game_Metrics_Word_Task,StudyId,DeviceTime,StudyId,DeviceTime)$StudyId)
>
> #Generates a blank output dataframe
> WordFrame <- data.frame(Participant = c(0), Task = c(0), MannKendall_Tau
> c(0), MannKendall_P = c(0), Sen_Slope_Value = c(0), Sen_Slope_Pval = c(0),
> Pettitts_CIV = c(0), Pettitts_Pval = c(0), ARIMA_Model = c(0),
> Time_to_Petit = c(0), Number_of_Trials_to_Pettitt = c(0),
> Playtime_to_Petit_seconds = c(0), Time_Start_to_end_days = c(0),
> Number_of_Total_Trials = c(0), Total_Playtime_seconds = c(0),
> Learning_rate_days = c(0), Learning_rate_seconds = c(0), Learned_Task >
c(0))
>
> #The number of subjects in the xlsx file
> #Reduced to 2 for ease of use
> for (i in 1:2){
> #This timeseries only includes the trials where the participant
> completed the task
> success_series <- xts(filter(Participant_Word_Task[[i]], GameEndReason
> == "TIMER_UP")$NumberOfSuccesfulWords ,
order.by=as.POSIXct(filter(Participant_Word_Task[[i]],
> GameEndReason == "TIMER_UP")$DeviceTime))
> #This timeseries includes ALL the trials for the sake of plotting
> original_series <-
> xts(Participant_Word_Task[[i]]$NumberOfSuccesfulWords, order.by
> =as.POSIXct(Participant_Word_Task[[i]]$DeviceTime))
>
> #This is a decomposing process that xts seems to need for plotting.
> #nweeks is needed for xts to plot the x-axis
> success_decomp <- ts(success_series, frequency =
nweeks(success_series))
> original_decomp <- ts(original_series, frequency >
nweeks(success_series))
>
> #Values which will be included in the plots
> WordFrame[i,1] <- unique(Participant_Word_Task[[i]]$StudyId)
> WordFrame[i,5] <- sens.slope(success_decomp)$estimates
> WordFrame[i,6] <- sens.slope(success_decomp)$p.value
> WordFrame[i,7] <- pettitt.test(success_decomp)$estimate
> WordFrame[i,8] <- pettitt.test(success_decomp)$p.value
>
> #The simple moving average that will be overlayed with the plotted data
> simplemovingaverage <- SMA(original_series, n =
nweeks(original_series))
>
> #If the three tests are statistically significant, add a green
> horizontal like to value WordFrame[i,7]
> #Which would be where the slope changes in the series
> #Fluid variables have been removed from all pdf() and paste() functions
> for ease-of-use
> if (WordFrame[i,4] <= 0.05 & WordFrame[i,6] <= 0.05 &
WordFrame[i,8] <> 0.05){
> {
> pdf(file = "Word_Task_Acquisition.pdf")
> plout <- plot(original_series)
> lines(simplemovingaverage)
> abline(v = index(original_series[WordFrame[i,7]]),lty=2,
> col='green', lwd=3)
> title(paste("Word Task Acquisition for Subject"))
> dev.off()
> }
> #If the three tests are NOT statistically significant, generate a plot
> with NO horizontal line at WordFrame[i,7]
> } else {
> {
> pdf(file = "Word_Task_Acquisition.pdf")
> plout <- plot(original_series)
> lines(simplemovingaverage)
> title(paste("Word Task Acquisition for Subject"))
> dev.off()
> }
> }
> }
>
> ________________________________
> From: Rolf Turner <r.turner at auckland.ac.nz>
> Sent: Wednesday, October 5, 2022 6:06 AM
> To: Deramus, Thomas Patrick <tderamus at partners.org>
> Cc: r-help at r-project.org <r-help at r-project.org>
> Subject: Re: [R] Getting "Error in ect, plot.new has not been called
yet"
> despite grouping plot call
>
> External Email - Use Caution
>
> What you doing or trying to do is far too complex for my poor feeble
> and senile brain to come anywhere near comprehending. The code that
> you present exceeds my complexity tolerance by many orders of magnitude.
>
> I have a suggestion, but. Strip your code down to the *essentials*.
> Construct a simple sequence of plotting commands, with *simple* names
> for the pdf files involved. You should require only two or three such
> files and two or three index levels associated with each of your
> nested loops.
>
> Run the stripped down code and the source of the problem will almost
> surely become clear.
>
> cheers,
>
> Rolf Turner
>
> On Tue, 4 Oct 2022 23:35:09 +0000
> "Deramus, Thomas Patrick" <tderamus at partners.org> wrote:
>
> > Sorry to cross-post on Stackoverflow and here but I'm having some
> > difficulty.
> >
>
https://secure-web.cisco.com/1_juqv4RvefQFJofsnOQcQA3Ixge89s4uC26pjoPBaYOSxSLGisKtgUTZkanxeHNRqNmjl30B8wYKfsppHje4T8Su77i7t8UbMKzs3GBKEyQva4yTjPH76Q9-l6tT24bB4qNMPQeFAxrkG5lpozNpGrDIAjfKCMvgS-5Qjs-QmvhWZfo84_3SK9rHhJjJvO9CqXb0MewWwI-dEmkZemjxnliGe_D9nooo7Ebjuw0dpBuMnrdaTzQxDdivsbkujPnrGurdjLARh93RW5IWPszNwaoziRD7P-30McF1PrAP8_yjWrhxQ_S3AgG6k40EoQJU/https%3A%2F%2Fstackoverflow.com%2Fquestions%2F73942794%2Fstill-getting-error-in-ect-plot-new-has-not-been-called-yet-despite-grouping
> >
> > Trying to make a nested loop that produces PDFs off different graphs,
> > one for ACF/PACF diagnostics and another for the actual data, based
> > on some time-series analyses I'm doing.
> >
> > Unfortunately, I keep getting the dreaded: Error plot.new has not
> > been called yet
> >
> > The code is meant to write a PDF containing the ACF and PACF graphs,
> > then do some analyses on the timeseries, and then make a separate PDF
> > containing a plot describing the timeseries based on the p-values of
> > each test for each individual.
> >
> > library(plyr)
> > library(dplyr)
> > library(ggplot2)
> > library(Kendall)
> > library(lubridate)
> > library(xts)
> > library(TTR)
> > library(trend)
> > library(forecast)
> > library(openxlsx)
> >
> > Game_Metrics_Word_Task <-
> > read.xlsx("GamePack_Analytics_ALL_TIME_Short.xlsx",
"Boggle")
> > Game_Metrics_Word_Task <- Game_Metrics_Word_Task %>%
> > filter(grepl('1440', StudyId))
Game_Metrics_Word_Task$DeviceTime <-
> > ymd_hms(Game_Metrics_Word_Task$DeviceTime, tz =
"America/New_York")
> > Game_Metrics_Word_Task <-
> > Game_Metrics_Word_Task[!duplicated(Game_Metrics_Word_Task[1:2,])]
> >
> > Participant_Word_Task <-
> > split(arrange(Game_Metrics_Word_Task,StudyId,DeviceTime),
> >
>
arrange(Game_Metrics_Word_Task,StudyId,DeviceTime,StudyId,DeviceTime)$StudyId)
> >
> > WordFrame <- data.frame(Participant = c(0), Task = c(0),
> > MannKendall_Tau = c(0), MannKendall_P = c(0), Sen_Slope_Value = c(0),
> > Sen_Slope_Pval = c(0), Pettitts_CIV = c(0), Pettitts_Pval = c(0),
> > ARIMA_Model = c(0), Time_to_Petit = c(0), Number_of_Trials_to_Pettitt
> > = c(0), Playtime_to_Petit_seconds = c(0), Time_Start_to_end_days >
> c(0), Number_of_Total_Trials = c(0), Total_Playtime_seconds = c(0),
> > Learning_rate_days = c(0), Learning_rate_seconds = c(0), Learned_Task
> > = c(0))
> >
> > for (i in 1:length(Participant_Word_Task)){
> > success_series <- xts(filter(Participant_Word_Task[[i]],
> > GameEndReason == "TIMER_UP")$NumberOfSuccesfulWords ,
> > order.by=as.POSIXct(filter(Participant_Word_Task[[i]], GameEndReason
> > == "TIMER_UP")$DeviceTime)) original_series <-
> > xts(Participant_Word_Task[[i]]$NumberOfSuccesfulWords,
> > order.by=as.POSIXct(Participant_Word_Task[[i]]$DeviceTime))
> > success_decomp <- ts(success_series, frequency > >
nweeks(success_series)) original_decomp <- ts(original_series,
> > frequency = nweeks(success_series))
> >
> >
>
pdf(paste("Word_Task_Autocorrelation_plots_for_subject_",unique(Participant_Word_Task[[i]]$StudyId),".pdf"
> > ,collapse = NULL, sep = "")) par(mfrow=c(1,2))
> > Autocorrelationplot <- acf(success_decomp,
main=paste(""))
> > PartialAutocorrelationplot <- pacf(success_decomp,
main=paste(""))
> > mtext(paste("Word Task Auto and Partialauto correlations for
> > subject ",unique(Participant_Word_Task[[i]]$StudyId)), side = 3,
line
> > = -3, outer = TRUE) dev.off()
> >
> > AutomatedArimaoutputs <- auto.arima(success_decomp)
> > p <- length(AutomatedArimaoutputs$model$phi)
> > #AR component
> > q <- length(AutomatedArimaoutputs$model$theta)
> > #MA component
> > d <- AutomatedArimaoutputs$model$Delta
> > #order of difference
> > WordFrame[i,1] <- unique(Participant_Word_Task[[i]]$StudyId)
> > WordFrame[i,2] <- "Word"
> > WordFrame[i,3] <- MannKendall(success_decomp)$tau[1]
> > WordFrame[i,4] <- MannKendall(success_decomp)$sl[1]
> > WordFrame[i,5] <- sens.slope(success_decomp)$estimates
> > WordFrame[i,6] <- sens.slope(success_decomp)$p.value
> > WordFrame[i,7] <- pettitt.test(success_decomp)$estimate
> > WordFrame[i,8] <- pettitt.test(success_decomp)$p.value
> > WordFrame[i,9] <-
paste("ARIMA(",p,",",q,",",d,")",
collapse > > NULL, sep = "") WordFrame[i,10] <-
> >
difftime(time(success_series[WordFrame[i,7]]),time(original_series[1]))
> > WordFrame[i,11] <- tail(which(grepl(success_series[WordFrame[i,7]],
> > original_series)), n=1) WordFrame[i,12] <-
> >
>
sum(Participant_Word_Task[[i]]$TotalDuration[1:WordFrame[i,11]])-sum(Participant_Word_Task[[i]]$TotalTimePaused[1:WordFrame[i,11]])
> > WordFrame[i,13] <-
> >
>
difftime(time(original_series[length(original_series)]),time(original_series[1]))
> > WordFrame[i,14] <- length(original_series) WordFrame[i,15] <-
> >
>
sum(Participant_Word_Task[[i]]$TotalDuration[1:length(original_series)])-sum(Participant_Word_Task[[i]]$TotalTimePaused[1:length(original_series)])
> >
> >
> > simplemovingaverage <- SMA(original_series, n > >
nweeks(original_series))
> >
> > if (WordFrame[i,4] <= 0.05 & WordFrame[i,6] <= 0.05
&
> > WordFrame[i,8] <= 0.05){ {
> >
> pdf(paste(WordFrame[i,1],"_Word_Task_Acquisition.pdf",collapse
> > = NULL, sep = "")) plout <-
> >
plot(original_series,type='l',col='blue',xlab="Date of
> > Play",ylab="Number of Successful Words")
> > lines(simplemovingaverage,type='l',col='red')
title(paste("Word Task
> > Acquisition for Subject", WordFrame[i,1])) abline(v > >
index(original_series[WordFrame[i,7]]),lty=2, col='green', lwd=3)
> > dev.off() } WordFrame[i,18] <- T
> > WordFrame[i,16] <-
(1-(WordFrame[i,10]/WordFrame[i,13]))
> > WordFrame[i,17] <-
(1-(WordFrame[i,12]/WordFrame[i,15]))
> > } else {
> > {
> >
> pdf(paste(WordFrame[i,1],"_Word_Task_Acquisition.pdf",collapse
> > = NULL, sep = "")) plout <-
> >
plot(original_series,type='l',col='blue',xlab="Date of
> > Play",ylab="Number of Successful Words")
> > lines(simplemovingaverage,type='l',col='red')
title(paste("Word Task
> > Acquisition for Subject", WordFrame[i,1])) dev.off() }
> > WordFrame[i,18] <- F
> > WordFrame[i,16] <- 0
> > WordFrame[i,17] <- 0
> > }
> > }
> >
> > It will work just fine if I run the lines individually (e.g. set i
> > 1, 2, ect), and if I comment out abline and title (lines seems to
> > work fine). But it will throw the error everytime I try to run the
> > loop without these commented.
> >
> > Have tried just about everything I could find on the Stack forums to
> > run everything as a single argument and I'm just not sure what is
> > wrong with it.
> >
> > dev.list() spits out:
> >
> > pdf
> > 2
> > following the error.
> >
> > With abline and title commented out and lines run individually
it's
> > NULL.
> >
> > Happens in both RStudio
> >
> > 2022.07.2+576 "Spotted Wakerobin" Release
> > (e7373ef832b49b2a9b88162cfe7eac5f22c40b34, 2022-09-06) for Ubuntu
> > Bionic Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML,
> > like Gecko) QtWebEngine/5.12.8 Chrome/69.0.3497.128 Safari/537.36
> >
> > And R:
> >
> > platform x86_64-pc-linux-gnu
> > arch x86_64
> > os linux-gnu
> > system x86_64, linux-gnu
> > status
> > major 4
> > minor 2.1
> > year 2022
> > month 06
> > day 23
> > svn rev 82513
> > language R
> > version.string R version 4.2.1 (2022-06-23)
> > nickname Funny-Looking Kid
> >
> >
> > My OS:
> > PRETTY_NAME="Debian GNU/Linux 11 (bullseye)"
> > NAME="Debian GNU/Linux"
> > VERSION_ID="11"
> > VERSION="11 (bullseye)"
> > VERSION_CODENAME=bullseye
> > ID=debian
> > HOME_URL="
>
https://secure-web.cisco.com/1Ruvt90Q90ixR-GE-RDiKJgzRpfDjlNz-lZTqQQGM8Tf4GAoj5QOfE2vXMaMWxMoexuf1npQrX7uAjFuU2viz28h42RPmHQK7jGDX7BpRLkTNcERyxHVKJTxgYegXo-n9N7rqegcKsrr47xlGmTcMOJcBAqH7SpTPQlYDOGgjz1ErtetQRzUsd-eKs9l4oCVPiF6SKV40C7s_NXm0tuCswL2Jhyfv70-edCtBO_4j9-3dSi5ZdFLYaWsMScnwwxNIGYU2n0vw5NH4GJcZNsv6Scu-r6W8ndJaGL4UmX9J3PX0LrdFyjLbGtA7RqPpKFUQ/https%3A%2F%2Fwww.debian.org
> "
> > SUPPORT_URL="
>
https://secure-web.cisco.com/1gveQttVrJNRSM85857IiydpLraxrrtJobMyCNkRvQ4V2f00DH67Z0hEa50LLpCVYQvIjMsQZxHAVMZvYQV_Cp2-e82TDZzPY4aSR2td2th3bwuXGxtI7CTgSUudOWgPpmnwVLT5r34EnwXEmwnMoiPVnOEC7slpF1fLGq11wSynuyttcTagMfpN6qdYfgtbu_mz0JOBUecQ-etUQYw5BDmXEKv5JZ_y5Uyt8Q89Kirhi7Hk8FMbCVcxRZpOZZmghxlPMxYaNVIOnln-R0H8J2QIzqE49cQQPKkFZ9O29zpr8odlBXqjObKn24ReYPDhH/https%3A%2F%2Fwww.debian.org%2Fsupport
> "
> > BUG_REPORT_URL="
>
https://secure-web.cisco.com/1tepDnCjDgHsmvw9Eth-7nfyKi3doVSOFKVzz83wskdyf8lsrEVkG2NYw7am6ePhSFfjQXdDyceMyc21Un-vqTirSQYKdPavRdKJy85HgHMP66Xk-OgxFf-5KXiPzmFreDfuuJlYizGSUNOLcADyNVTCo47xFfRgtB83Hs8j3yYAJFrff7TqNOFWzSzTcfrycio_WSSfbQkLpUl-1xGzg-dvP16tKuwkRr62bkPeydXJC_iH1FfnWv5b1G04au3aFmRTem8t2RS40LPMS9Mh0UmMvHD_9qwX16cFMHQ8U4x9Sp9IUcAFhgnbffOyPQm1C/https%3A%2F%2Fbugs.debian.org
> "
> > No LSB modules are available.
> > Distributor ID: Debian
> > Description: Debian GNU/Linux 11 (bullseye)
> > Release: 11
> > Codename: bullseye
> > Icon name: computer-desktop
> > Chassis: desktop
> > Machine ID: 053ebf23707f49c8ad4e0684f4cf19d3
> > Boot ID: d0e6294d3b944286bef10e76c21e6401
> > Operating System: Debian GNU/Linux 11 (bullseye)
> > Kernel: Linux 5.10.0-18-amd64
> > Architecture: x86-64
> >
> >
> > Any suggestions would be greatly appreciated.
> >
> > --
> >
> > Thomas DeRamus (He/Him/His)
> >
> > Data Analyst
> >
> > Massachusetts General Hospital Brigham
> >
> > Alzheimer?s Clinical & Translational Research Unit
> >
> > 149 13th Street
> >
> > Charlestown, MA 02129
> >
> > Phone: 205-834-5066
> >
> > Email: tderamus at partners.org<mailto:tderamus at
partners.org>,
> > tpderamus at gmail.com<mailto:tpderamus at gmail.com>
> >
> >
> > [
>
https://secure-web.cisco.com/1AI4S4rz4bDZGM8naa-19GTAeSORO5ZmNe056Q_nhPRk4JVAzPiRKUBWitBK5TpxoKBLoLvNfoMDanGd1n5Bnf4SJFT7l7HnaLcjjH7oVk2BZdDfCLHo8a8eePvD4XrF2Fw3iuxKgIZY5dwdesP3P8pSvkmVGvyZ-HiEKRetk4uJHhRa6gSgOQ8MbCVKmi6XP1dtozTEH1RpDrFJ4EyevPO52UzaTAY6CR8USLWNbsxXJsnsjUz1G6_4P7B3ULuMu9mEPeQz_GnTrSXTrGZooK_idhoEougti7I8NYV0CS09Yahmp4Fe_vh9wu4Jkdal3/https%3A%2F%2Fci3.googleusercontent.com%2Fmail-sig%2FAIorK4we2sU30P2HyfDQF5hpEjYTt-9FTBK7cAVsP7EenrZ0nsKCf48fuYMtElj6Szn_2fpSPWr66eQ][https://ci3.googleusercontent.com/mail-sig/AIorK4yyY0DlImU0UONJrHTbPc5T3lJj8Kmu8SbDKJJ3XjcX6CgvVsvSueYKwficYFz4zXt6fZV8YIY
>
<https://secure-web.cisco.com/1AI4S4rz4bDZGM8naa-19GTAeSORO5ZmNe056Q_nhPRk4JVAzPiRKUBWitBK5TpxoKBLoLvNfoMDanGd1n5Bnf4SJFT7l7HnaLcjjH7oVk2BZdDfCLHo8a8eePvD4XrF2Fw3iuxKgIZY5dwdesP3P8pSvkmVGvyZ-HiEKRetk4uJHhRa6gSgOQ8MbCVKmi6XP1dtozTEH1RpDrFJ4EyevPO52UzaTAY6CR8USLWNbsxXJsnsjUz1G6_4P7B3ULuMu9mEPeQz_GnTrSXTrGZooK_idhoEougti7I8NYV0CS09Yahmp4Fe_vh9wu4Jkdal3/https%3A%2F%2Fci3.googleusercontent.com%2Fmail-sig%2FAIorK4we2sU30P2HyfDQF5hpEjYTt-9FTBK7cAVsP7EenrZ0nsKCf48fuYMtElj6Szn_2fpSPWr66eQ%5D%5Bhttps://ci3.googleusercontent.com/mail-sig/AIorK4yyY0DlImU0UONJrHTbPc5T3lJj8Kmu8SbDKJJ3XjcX6CgvVsvSueYKwficYFz4zXt6fZV8YIY>
> ]
> >
> > ?If knowledge can create problems, it is not through ignorance that
> > we can solve them.?
> >
> > ?Issac Asimov
>
> The information in this e-mail is intended only for th...{{dropped:22}}
Joshua Ulrich
2022-Oct-06 15:26 UTC
[R] Getting "Error in ect, plot.new has not been called yet" despite grouping plot call
On Thu, Oct 6, 2022 at 9:44 AM Bill Dunlap <williamwdunlap at gmail.com> wrote:> > Here is how you could have made an example that helpers could easily run. > It also includes the fix. > > f <- function(print.it = FALSE) { > pdf(file.pdf <- tempfile(fileext=".pdf")) > series <- as.xts(setNames(sin(seq(0,10,by=.1)), > seq(as.Date("2022-10-06"),by="weeks",len=101))) > p <- plot(series) > if (print.it) { > print(p) > } > sm_series_2 <- smooth(series / 2) > lines(sm_series_2, col="red") > abline(h=0.1, col="blue") > dev.off() > file.pdf > } > > f() > Error in plot.xy(xy.coords(x, y), type = type, ...) : > plot.new has not been called yet > > f(TRUE) > [1] > "C:\\Users\\willi\\AppData\\Local\\Temp\\Rtmp0wX7rO\\file34843df652c.pdf" > > If you remove the pdf() and dev.off() I think you will see that the added > lines do not show up. I think plot.xts fiddles with the coordinate system > before and after it plots so that add-ons must be done in a special way. >plot.xts() waits until the plot is rendered before calculating the coordinate system. That allows users to add multiple series that have different values for the index (x-axis) and data (y-axis). lines() doesn't show up in your example because it's called after the plot is rendered, and it's not rendered again after they're added. `sm_series_2` also needs to be an xts object, otherwise lines.xts() is not dispatched. title() and abline() need to be called after the plot is rendered because they are standard graphics functions. I admit that's very confusing... I'll see what I can do to fix that. Here's a revised example that works for me: f <- function(print.it = FALSE) { pdf(file.pdf <- tempfile(fileext=".pdf")) series <- xts(sin(seq(0,10,by=.1)), seq(as.Date("2022-10-06"),by="weeks",length.out=101)) p <- plot(series) sm2 <- xts(smooth(series/2), index(series)) lines(sm2, col="red") if (print.it) { print(p) title("Sine curve example") abline(h=0.1, col="green") } dev.off() file.pdf } f(TRUE)> -Bill > > On Thu, Oct 6, 2022 at 12:42 AM Deramus, Thomas Patrick < > tderamus at partners.org> wrote: > > > Hi Rolf. > > > > I followed your suggestion (though it's probably not as trimmed as it > > could be), but the problem unfortunately persists. > > > > Does this make it any clearer or still too many moving parts to make sense > > of? > > > > rm(list = ls(all.names = TRUE)) #will clear all objects includes hidden > > objects. > > > > #Loads the packages > > library(plyr) > > library(dplyr) > > library(ggplot2) > > library(Kendall) > > library(lubridate) > > library(xts) > > library(TTR) > > library(trend) > > library(forecast) > > library(openxlsx) > > > > #Uses the learningCurve Package from Github: > > #https://github.com/AFIT-R/learningCurve > > library(learningCurve) > > > > #Only load this if using VS Studio because it changes the plot function > > # > > https://stackoverflow.com/questions/52284345/how-to-show-r-graph-from-visual-studio-code > > library(httpgd) > > library(languageserver) > > > > #Loads the Excel files to Dataframes and cleans the data > > Game_Metrics_Word_Task <- > > read.xlsx("GamePack_Analytics_ALL_TIME_Short.xlsx", "Boggle") > > Game_Metrics_Word_Task <- Game_Metrics_Word_Task %>% filter(grepl('1440', > > StudyId)) > > Game_Metrics_Word_Task$DeviceTime <- > > ymd_hms(Game_Metrics_Word_Task$DeviceTime, tz = "America/New_York") > > Game_Metrics_Word_Task <- > > Game_Metrics_Word_Task[!duplicated(Game_Metrics_Word_Task[1:2,])] > > > > #Splits the dataframe into a tibble containing each participant > > Participant_Word_Task <- > > split(arrange(Game_Metrics_Word_Task,StudyId,DeviceTime), > > arrange(Game_Metrics_Word_Task,StudyId,DeviceTime,StudyId,DeviceTime)$StudyId) > > > > #Generates a blank output dataframe > > WordFrame <- data.frame(Participant = c(0), Task = c(0), MannKendall_Tau > > c(0), MannKendall_P = c(0), Sen_Slope_Value = c(0), Sen_Slope_Pval = c(0), > > Pettitts_CIV = c(0), Pettitts_Pval = c(0), ARIMA_Model = c(0), > > Time_to_Petit = c(0), Number_of_Trials_to_Pettitt = c(0), > > Playtime_to_Petit_seconds = c(0), Time_Start_to_end_days = c(0), > > Number_of_Total_Trials = c(0), Total_Playtime_seconds = c(0), > > Learning_rate_days = c(0), Learning_rate_seconds = c(0), Learned_Task > > c(0)) > > > > #The number of subjects in the xlsx file > > #Reduced to 2 for ease of use > > for (i in 1:2){ > > #This timeseries only includes the trials where the participant > > completed the task > > success_series <- xts(filter(Participant_Word_Task[[i]], GameEndReason > > == "TIMER_UP")$NumberOfSuccesfulWords , order.by=as.POSIXct(filter(Participant_Word_Task[[i]], > > GameEndReason == "TIMER_UP")$DeviceTime)) > > #This timeseries includes ALL the trials for the sake of plotting > > original_series <- > > xts(Participant_Word_Task[[i]]$NumberOfSuccesfulWords, order.by > > =as.POSIXct(Participant_Word_Task[[i]]$DeviceTime)) > > > > #This is a decomposing process that xts seems to need for plotting. > > #nweeks is needed for xts to plot the x-axis > > success_decomp <- ts(success_series, frequency = nweeks(success_series)) > > original_decomp <- ts(original_series, frequency > > nweeks(success_series)) > > > > #Values which will be included in the plots > > WordFrame[i,1] <- unique(Participant_Word_Task[[i]]$StudyId) > > WordFrame[i,5] <- sens.slope(success_decomp)$estimates > > WordFrame[i,6] <- sens.slope(success_decomp)$p.value > > WordFrame[i,7] <- pettitt.test(success_decomp)$estimate > > WordFrame[i,8] <- pettitt.test(success_decomp)$p.value > > > > #The simple moving average that will be overlayed with the plotted data > > simplemovingaverage <- SMA(original_series, n = nweeks(original_series)) > > > > #If the three tests are statistically significant, add a green > > horizontal like to value WordFrame[i,7] > > #Which would be where the slope changes in the series > > #Fluid variables have been removed from all pdf() and paste() functions > > for ease-of-use > > if (WordFrame[i,4] <= 0.05 & WordFrame[i,6] <= 0.05 & WordFrame[i,8] <> > 0.05){ > > { > > pdf(file = "Word_Task_Acquisition.pdf") > > plout <- plot(original_series) > > lines(simplemovingaverage) > > abline(v = index(original_series[WordFrame[i,7]]),lty=2, > > col='green', lwd=3) > > title(paste("Word Task Acquisition for Subject")) > > dev.off() > > } > > #If the three tests are NOT statistically significant, generate a plot > > with NO horizontal line at WordFrame[i,7] > > } else { > > { > > pdf(file = "Word_Task_Acquisition.pdf") > > plout <- plot(original_series) > > lines(simplemovingaverage) > > title(paste("Word Task Acquisition for Subject")) > > dev.off() > > } > > } > > } > > > > ________________________________ > > From: Rolf Turner <r.turner at auckland.ac.nz> > > Sent: Wednesday, October 5, 2022 6:06 AM > > To: Deramus, Thomas Patrick <tderamus at partners.org> > > Cc: r-help at r-project.org <r-help at r-project.org> > > Subject: Re: [R] Getting "Error in ect, plot.new has not been called yet" > > despite grouping plot call > > > > External Email - Use Caution > > > > What you doing or trying to do is far too complex for my poor feeble > > and senile brain to come anywhere near comprehending. The code that > > you present exceeds my complexity tolerance by many orders of magnitude. > > > > I have a suggestion, but. Strip your code down to the *essentials*. > > Construct a simple sequence of plotting commands, with *simple* names > > for the pdf files involved. You should require only two or three such > > files and two or three index levels associated with each of your > > nested loops. > > > > Run the stripped down code and the source of the problem will almost > > surely become clear. > > > > cheers, > > > > Rolf Turner > > > > On Tue, 4 Oct 2022 23:35:09 +0000 > > "Deramus, Thomas Patrick" <tderamus at partners.org> wrote: > ><snip>> > > ?Issac Asimov > > > > The information in this e-mail is intended only for th...{{dropped:22}} > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-- Joshua Ulrich | about.me/joshuaulrich FOSS Trading | www.fosstrading.com