[R] Getting "Error in ect, plot.new has not been called yet" despite grouping plot call

Wed Oct 5 12:06:08 CEST 2022

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 using partners.org> wrote:

> Sorry to cross-post on Stackoverflow and here but I'm having some
> difficulty.
> https://stackoverflow.com/questions/73942794/still-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://www.debian.org"
> SUPPORT_URL="https://www.debian.org/support"
> BUG_REPORT_URL="https://bugs.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 using partners.org<mailto:tderamus using partners.org>,
> tpderamus using gmail.com<mailto:tpderamus using gmail.com>
> 
> 
> [https://ci3.googleusercontent.com/mail-sig/AIorK4we2sU30P2HyfDQF5hpEjYTt-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