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 < tdera...@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.tur...@auckland.ac.nz> > Sent: Wednesday, October 5, 2022 6:06 AM > To: Deramus, Thomas Patrick <tdera...@partners.org> > Cc: r-help@r-project.org <r-help@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" <tdera...@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: tdera...@partners.org<mailto:tdera...@partners.org>, > > tpdera...@gmail.com<mailto:tpdera...@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}} ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting 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