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Error address (nil), cause 'memory not mapped' #126

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nmolanog opened this issue Jul 27, 2020 · 1 comment
Open

Error address (nil), cause 'memory not mapped' #126

nmolanog opened this issue Jul 27, 2020 · 1 comment

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@nmolanog
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nmolanog commented Jul 27, 2020 •
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this error was presented while runing this code:

library(animation)
library(tidyverse)

mu_seq<-c(seq(0,15,by = .5),seq(15,0,by = -.5),seq(0,-15,by = -.5),rev(seq(0,-15,by = -.5)))
sig_seq<-c(rev(seq(0.001,225,length.out = 20)),seq(0.001,225,length.out = 15))
dfp<-data.frame(mu=c(mu_seq,
                     rep(0,length(sig_seq))),
                sig=c(rep(225,length(mu_seq)),sig_seq))

saveGIF({
  ani.options(interval = 0.2, nmax = nrow(dfp))
  ## use a loop to create images one by one
  for (i in 1:ani.options('nmax')) {
    m1<-dfp[i,1]
    sd1<-sqrt(dfp[i,2])
    weight_lim<-c(-40, 40)
    pdnorm1<-ggplot(data = data.frame(weight = weight_lim), aes(weight)) +
      stat_function(fun = dnorm, n = 101, args = list(mean = m1, sd = sd1),aes(color="black")) +
      ylab(expression(paste("f(x|",mu,",",sigma^2,")"))) +xlab("x") +  
      scale_color_identity(name = "",
                           breaks = c("black", "red", "blue","green"),
                           labels = c(substitute(paste(mu,"= ",m1,", ",sigma^2,"= ",sd1),list(m1=round(m1,1),sd1=round(sd1,3)))),
                           guide = "legend")+
      ylim(0,.25)+
      theme_bw()
    print(pdnorm1)
    ani.pause()   ## pause for a while ('interval')
  }
}, interval = 0.05, movie.name = 'dnorm.gif', ani.width = 680, ani.height = 500)

The Error output is this

Traceback:
 1: magick_image_write(image, format, quality, depth, density, comment)
 2: magick::image_write(anim, path = output)
 3: magick.convert(files = files, output = output, loop = loop, interval = interval,     dispose = dispose)
 4: im.convert(img.files, output = path.expand(movie.name), convert = convert,     cmd.fun = cmd.fun, clean = clean, extra.opts = extra.opts)
 5: saveGIF({    ani.options(interval = 0.2, nmax = nrow(dfp))    for (i in 1:ani.options("nmax")) {        m1 <- dfp[i, 1]        sd1 <- sqrt(dfp[i, 2])        weight_lim <- c(-40, 40)        pdnorm1 <- ggplot(data = data.frame(weight = weight_lim),             aes(weight)) + stat_function(fun = dnorm, n = 101,             args = list(mean = m1, sd = sd1), aes(color = "black")) +             ylab(expression(paste("f(x|", mu, ",", sigma^2, ")"))) +             xlab("x") + scale_color_identity(name = "", breaks = c("black",             "red", "blue", "green"), labels = c(substitute(paste(mu,             "= ", m1, ", ", sigma^2, "= ", sd1), list(m1 = round(m1,             1), sd1 = round(sd1, 3)))), guide = "legend") + ylim(0,             0.25) + theme_bw()        print(pdnorm1)        ani.pause()    }}, interval = 0.05, movie.name = "dnorm.gif", ani.width = 680,     ani.height = 500)

Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace

my session info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 4.0.2 (2020-06-22)
 os       Ubuntu 18.04.4 LTS          
 system   x86_64, linux-gnu           
 ui       X11                         
 language en                          
 collate  en_US.UTF-8                 
 ctype    en_US.UTF-8                 
 tz       America/Bogota              
 date     2020-07-27                  

─ Packages ───────────────────────────────────────────────────────────────────
 package     * version date       lib source        
 animation   * 2.6     2018-12-11 [1] CRAN (R 4.0.2)
 assertthat    0.2.1   2019-03-21 [1] CRAN (R 4.0.2)
 backports     1.1.8   2020-06-17 [1] CRAN (R 4.0.2)
 blob          1.2.1   2020-01-20 [1] CRAN (R 4.0.2)
 broom         0.7.0   2020-07-09 [1] CRAN (R 4.0.2)
 callr         3.4.3   2020-03-28 [1] CRAN (R 4.0.2)
 cellranger    1.1.0   2016-07-27 [1] CRAN (R 4.0.2)
 cli           2.0.2   2020-02-28 [1] CRAN (R 4.0.2)
 colorspace    1.4-1   2019-03-18 [1] CRAN (R 4.0.2)
 crayon        1.3.4   2017-09-16 [1] CRAN (R 4.0.2)
 DBI           1.1.0   2019-12-15 [1] CRAN (R 4.0.2)
 dbplyr        1.4.4   2020-05-27 [1] CRAN (R 4.0.2)
 desc          1.2.0   2018-05-01 [1] CRAN (R 4.0.2)
 devtools      2.3.0   2020-04-10 [1] CRAN (R 4.0.2)
 digest        0.6.25  2020-02-23 [1] CRAN (R 4.0.2)
 dplyr       * 1.0.0   2020-05-29 [1] CRAN (R 4.0.2)
 ellipsis      0.3.1   2020-05-15 [1] CRAN (R 4.0.2)
 fansi         0.4.1   2020-01-08 [1] CRAN (R 4.0.2)
 forcats     * 0.5.0   2020-03-01 [1] CRAN (R 4.0.2)
 fs            1.4.2   2020-06-30 [1] CRAN (R 4.0.2)
 generics      0.0.2   2018-11-29 [1] CRAN (R 4.0.2)
 ggplot2     * 3.3.2   2020-06-19 [1] CRAN (R 4.0.2)
 glue          1.4.1   2020-05-13 [1] CRAN (R 4.0.2)
 gtable        0.3.0   2019-03-25 [1] CRAN (R 4.0.2)
 haven         2.3.1   2020-06-01 [1] CRAN (R 4.0.2)
 hms           0.5.3   2020-01-08 [1] CRAN (R 4.0.2)
 httr          1.4.2   2020-07-20 [1] CRAN (R 4.0.2)
 jsonlite      1.7.0   2020-06-25 [1] CRAN (R 4.0.2)
 lifecycle     0.2.0   2020-03-06 [1] CRAN (R 4.0.2)
 lubridate     1.7.9   2020-06-08 [1] CRAN (R 4.0.2)
 magrittr      1.5     2014-11-22 [1] CRAN (R 4.0.2)
 memoise       1.1.0   2017-04-21 [1] CRAN (R 4.0.2)
 modelr        0.1.8   2020-05-19 [1] CRAN (R 4.0.2)
 munsell       0.5.0   2018-06-12 [1] CRAN (R 4.0.2)
 pillar        1.4.6   2020-07-10 [1] CRAN (R 4.0.2)
 pkgbuild      1.1.0   2020-07-13 [1] CRAN (R 4.0.2)
 pkgconfig     2.0.3   2019-09-22 [1] CRAN (R 4.0.2)
 pkgload       1.1.0   2020-05-29 [1] CRAN (R 4.0.2)
 prettyunits   1.1.1   2020-01-24 [1] CRAN (R 4.0.2)
 processx      3.4.3   2020-07-05 [1] CRAN (R 4.0.2)
 ps            1.3.3   2020-05-08 [1] CRAN (R 4.0.2)
 purrr       * 0.3.4   2020-04-17 [1] CRAN (R 4.0.2)
 R6            2.4.1   2019-11-12 [1] CRAN (R 4.0.2)
 Rcpp          1.0.5   2020-07-06 [1] CRAN (R 4.0.2)
 readr       * 1.3.1   2018-12-21 [1] CRAN (R 4.0.2)
 readxl        1.3.1   2019-03-13 [1] CRAN (R 4.0.2)
 remotes       2.1.1   2020-02-15 [1] CRAN (R 4.0.2)
 reprex        0.3.0   2019-05-16 [1] CRAN (R 4.0.2)
 rlang         0.4.7   2020-07-09 [1] CRAN (R 4.0.2)
 rprojroot     1.3-2   2018-01-03 [1] CRAN (R 4.0.2)
 rstudioapi    0.11    2020-02-07 [1] CRAN (R 4.0.2)
 rvest         0.3.5   2019-11-08 [1] CRAN (R 4.0.2)
 scales        1.1.1   2020-05-11 [1] CRAN (R 4.0.2)
 sessioninfo   1.1.1   2018-11-05 [1] CRAN (R 4.0.2)
 stringi       1.4.6   2020-02-17 [1] CRAN (R 4.0.2)
 stringr     * 1.4.0   2019-02-10 [1] CRAN (R 4.0.2)
 testthat      2.3.2   2020-03-02 [1] CRAN (R 4.0.2)
 tibble      * 3.0.3   2020-07-10 [1] CRAN (R 4.0.2)
 tidyr       * 1.1.0   2020-05-20 [1] CRAN (R 4.0.2)
 tidyselect    1.1.0   2020-05-11 [1] CRAN (R 4.0.2)
 tidyverse   * 1.3.0   2019-11-21 [1] CRAN (R 4.0.2)
 usethis       1.6.1   2020-04-29 [1] CRAN (R 4.0.2)
 vctrs         0.3.2   2020-07-15 [1] CRAN (R 4.0.2)
 withr         2.2.0   2020-04-20 [1] CRAN (R 4.0.2)

The error is not present if number of iterations is reduced

rm(list=ls())
library(animation)
library(tidyverse)

mu_seq<-c(seq(0,15,by = 1.5),seq(15,0,by = -1.5),seq(0,-15,by = -1.5),rev(seq(0,-15,by = -1.5)))
sig_seq<-c(rev(seq(0.001,225,length.out = 20)),seq(0.001,225,length.out = 15))
dfp<-data.frame(mu=c(mu_seq,
                     rep(0,length(sig_seq))),
                sig=c(rep(225,length(mu_seq)),sig_seq))

saveGIF({
  ani.options(interval = 0.2, nmax = nrow(dfp))
  ## use a loop to create images one by one
  for (i in 1:ani.options('nmax')) {
    m1<-dfp[i,1]
    sd1<-sqrt(dfp[i,2])
    weight_lim<-c(-40, 40)
    pdnorm1<-ggplot(data = data.frame(weight = weight_lim), aes(weight)) +
      stat_function(fun = dnorm, n = 101, args = list(mean = m1, sd = sd1),aes(color="black")) +
      ylab(expression(paste("f(x|",mu,",",sigma^2,")"))) +xlab("x") +  
      scale_color_identity(name = "",
                           breaks = c("black", "red", "blue","green"),
                           labels = c(substitute(paste(mu,"= ",m1,", ",sigma^2,"= ",sd1),list(m1=round(m1,3),sd1=round(sd1,3)))),
                           guide = "legend")+
      ylim(0,.125)+
      theme_bw()
    print(pdnorm1)
    ani.pause()   ## pause for a while ('interval')
  }
}, interval = 0.05, movie.name = 'dnorm.gif', ani.width = 680, ani.height = 500)
#> Output at: dnorm.gif
#> [1] TRUE

Created on 2020-07-27 by the reprex package (v0.3.0)
@yulijia
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yulijia commented Jul 28, 2020

I couldn't reproduce the bug, both scripts are running well on my CentOS server.

Maybe the memory of your machine is too limited to run the first script.

Here is my session info.

> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblasp-r0.3.3.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8       
 [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
 [1] splines   parallel  stats4    stats     graphics  grDevices utils     datasets 
 [9] methods   base     

other attached packages:
 [1] animation_2.6               scClassify_1.0.0            monocle_2.16.0             
 [4] DDRTree_0.1.5               irlba_2.3.3                 VGAM_1.1-3                 
 [7] Matrix_1.2-18               plyr_1.8.6                  ggpubr_0.4.0               
[10] viridis_0.5.1               viridisLite_0.3.0           MAST_1.14.0                
[13] ggplot2_3.3.2               cluster_2.1.0               Rtsne_0.15                 
[16] mclust_5.4.6                edgeR_3.30.3                limma_3.44.3               
[19] dplyr_1.0.0                 SingleCellExperiment_1.10.1 SummarizedExperiment_1.18.2
[22] DelayedArray_0.14.1         matrixStats_0.56.0          Biobase_2.48.0             
[25] GenomicRanges_1.40.0        GenomeInfoDb_1.24.2         IRanges_2.22.2             
[28] S4Vectors_0.26.1            BiocGenerics_0.34.0        

loaded via a namespace (and not attached):
 [1] colorspace_1.4-1       ggsignif_0.6.0         ellipsis_0.3.1        
 [4] rio_0.5.16             XVector_0.28.0         proxy_0.4-24          
 [7] rstudioapi_0.11        farver_2.0.3           graphlayouts_0.7.0    
[10] ggrepel_0.8.2          docopt_0.7.1           polyclip_1.10-0       
[13] hopach_2.48.0          broom_0.7.0            kernlab_0.9-29        
[16] pheatmap_1.0.12        ggforce_0.3.2          compiler_4.0.2        
[19] backports_1.1.8        tweenr_1.0.1           tools_4.0.2           
[22] igraph_1.2.5           gtable_0.3.0           glue_1.4.1            
[25] GenomeInfoDbData_1.2.3 RANN_2.6.1             reshape2_1.4.4        
[28] Rcpp_1.0.5             carData_3.0-4          slam_0.1-47           
[31] cellranger_1.1.0       vctrs_0.3.2            nlme_3.1-148          
[34] ggraph_2.0.3           stringr_1.4.0          openxlsx_4.1.5        
[37] lifecycle_0.2.0        statmod_1.4.34         rstatix_0.6.0         
[40] zlibbioc_1.34.0        MASS_7.3-51.6          scales_1.1.1          
[43] tidygraph_1.2.0        hms_0.5.3              RColorBrewer_1.1-2    
[46] curl_4.3               gridExtra_2.3          segmented_1.2-0       
[49] fastICA_1.2-2          stringi_1.4.6          densityClust_0.3      
[52] zip_2.0.4              BiocParallel_1.22.0    rlang_0.4.7           
[55] pkgconfig_2.0.3        bitops_1.0-6           qlcMatrix_0.9.7       
[58] lattice_0.20-41        purrr_0.3.4            labeling_0.3          
[61] tidyselect_1.1.0       magrittr_1.5           R6_2.4.1              
[64] magick_2.4.0           generics_0.0.2         combinat_0.0-8        
[67] pillar_1.4.6           haven_2.3.1            foreign_0.8-80        
[70] withr_2.2.0            mgcv_1.8-31            proxyC_0.1.5          
[73] mixtools_1.2.0         survival_3.2-3         abind_1.4-5           
[76] RCurl_1.98-1.2         tibble_3.0.3           crayon_1.3.4          
[79] car_3.0-8              locfit_1.5-9.4         grid_4.0.2            
[82] readxl_1.3.1           minpack.lm_1.2-1       data.table_1.12.8     
[85] FNN_1.1.3              forcats_0.5.0          HSMMSingleCell_1.8.0  
[88] sparsesvd_0.2          digest_0.6.25          tidyr_1.1.0           
[91] RcppParallel_5.0.2     munsell_0.5.0

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@yulijia @nmolanog