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] > > “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 the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Mass General Brigham Compliance HelpLine at https://www.massgeneralbrigham.org/complianceline <https://www.massgeneralbrigham.org/complianceline> . Please note that this e-mail is not secure (encrypted). If you do not wish to continue communication over unencrypted e-mail, please notify the sender of this message immediately. Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail. ______________________________________________ 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 guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
