similar to: serializing recordedplot object

The documentation for recordPlot says the following: > As of R 3.3.0, it is possible (again) to replay a plot from another R session using, for example, saveRDS and readRDS. However, I haven't been able to save and restore a plot displaylist and have it work within the same R session, using R 3.4.3 or 3.3.3. Here's an example: # Save displaylist for a simple plot

>>>>> Paul Murrell <paul at stat.auckland.ac.nz> >>>>> on Tue, 3 Apr 2018 09:41:56 +1200 writes: > Hi What you are doing "wrong" is loading a recordedplot > into the same session that it was created in. The > saveRDS()/readRDS() works if you save in one R session and > then read in a different R session. The

Hi all, Is there any chance that readRDS and saveRDS might one day become read.rds and write.rds? That would make them more consistent with the other reading and writing functions. Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/

Hi all, I am not able to export an ALTREP object when `gctorture` is on in the worker. The package simplemmap can be used to reproduce the problem. See the example below ``` ## Create a temporary file filePath <- tempfile() con <- file(filePath, "wrb") writeBin(rep(0.0,10),con) close(con) library(simplemmap) library(parallel) cl <- makeCluster(1) x <- mmap(filePath,

This Index: src/main/altrep.c =================================================================== --- src/main/altrep.c (revision 79385) +++ src/main/altrep.c (working copy) @@ -275,10 +275,11 @@ SEXP psym = ALTREP_SERIALIZED_CLASS_PKGSYM(info); SEXP class = LookupClass(csym, psym); if (class == NULL) { - SEXP pname = ScalarString(PRINTNAME(psym)); + SEXP pname =

I hardly know anything about the format used in (non-compressed) serialization/RDS, but hoping someone with more knowledge could give me some feedback; Consider two R processes running in parallel on the same unknown file system. Both of them write and read to the same RDS file foo.rds (without compression) at random times using saveRDS(object, file="foo.rds", compress=FALSE) and

Hi there, I faced a weird problem doing a seemingly simple task in R. Specifically, when trying for reading an RDS file from the working directory, the following error is appeared. Code: records <- readRDS("tweets.rds") Error: Error in readRDS("tweets.rds") : error reading from connection In addition: Warning message: In readRDS("tweets.rds") : invalid or

Dear all I was thinking about efficient reading data into R and tried several ways to test if load(file.Rdata) or readRDS(file.rds) is faster. The files file.Rdata and file.rds contain the same data, the first created with save(d, ' file.Rdata', compress=F) and the second with saveRDS(d, ' file.rds', compress=F). First I used the function microbenchmark() and was a astonished

Hello, I looked in the R-help but could not find an archive addressing the following. I would like to convert a character to numeric after reading a file with RDS extension. After using as.numeric, I checked if it is numeric. It was not converted. Please help. Here is my code >Report <- readRDS(file="RDS/Report.RDS") > Report[1:2,] dive_id date

Wouldn't the obvious problem be that your data file is corrupted or was never created using saveRDS in the first place? Can you show us a complete example of creating and attempting to read what was just created? On April 22, 2018 10:20:05 AM CDT, mohammad moradi <mri.moradi at gmail.com> wrote: >Hi there, > >I faced a weird problem doing a seemingly simple task in R.

Each RDS is 40 MBs. What's a slick code to compare them row by row, IDing row numbers with mismatches? Thanks in advance. //

I've tried to re-experiment the tutorial presented at http://www.rdatamining.com/docs/twitter-analysis-with-r and specifically aimed to use rds files (tweet records) at http://www.rdatamining.com/data/. On Sun, Apr 22, 2018 at 9:16 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > Wouldn't the obvious problem be that your data file is corrupted or was > never created

Hi What you are doing "wrong" is loading a recordedplot into the same session that it was created in. The saveRDS()/readRDS() works if you save in one R session and then read in a different R session. The assumption is that if you are still in the same session that created the recordedplot you still have the recordedplot (e.g., you can just do replayPlot(r) instead of

Hi, I am dealing with very large datasets and it takes a long time to save a workspace image. The options to save compressed data are: "gzip", "bzip2" or "xz", the default being gzip. I wonder if it's possible to include the pbzip2 (http://compression.ca/pbzip2/) algorithm as an option when saving. "PBZIP2 is a parallel implementation of the bzip2

Also, it will be easier to provide helpful information if you'd describe what in your data you want to compare and what you hope to get out of the comparison. Best wishes, Ulrik Eric Berger <ericjberger at gmail.com> schrieb am Sa., 27. Jan. 2018, 08:18: > Hi Marsh, > An RDS is not a data structure such as a data.frame. It can be anything. > For example if I want to save my

Reviving an old thread. I haven't noticed this be a problem for a while when saving RDS's which is great. However, I noticed the problem again when saving `qs` files (https://github.com/traversc/qs) which is an RDS replacement with a fast serialization / compression system. I'd like to get an idea of what change was made within R to address this issue for `saveRDS`. My thought is that

The large value for maximum time may be due to garbage collection, which happens periodically. E.g., try the following, where the unlist(as.list()) creates a lot of garbage. I get a very large time every 102 or 51 iterations and a moderately large time more often mb <- microbenchmark::microbenchmark({ x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000)

Note that if you force a garbage collection each iteration the times are more stable. However, on the average it is faster to let the garbage collector decide when to leap into action. mb_gc <- microbenchmark::microbenchmark(gc(), { x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000, control=list(order="inorder")) with(mb_gc,

Hi Marsh, An RDS is not a data structure such as a data.frame. It can be anything. For example if I want to save my objects a, b, c I could do: > saveRDS( list(a,b,c,), file="tmp.RDS") Then read them back later with > myList <- readRDS( "tmp.RDS" ) Do you have additional information about your "RDSs" ? Eric On Sat, Jan 27, 2018 at 6:54 AM, Marsh Hardy

Hi Guys, I apologize for my rank & utter newness at R. I used summary() and found about 95 variables, both character and numeric, all with "Length:368842" I assume is the # of records. I'd like to know the record number (row #?) of any record where the data doesn't match in the 2 files of what should be the same output. Thanks in advance, M. //