I often see R posts where there is a paste of the output of someone's data, not using a dput(). Sometimes I see people use
data_in <- read.table("clipboard")
which on my OS X machine results in
data_in <- read.table("clipboard")
Error in file(file, "rt") : cannot open the connection
In addition: Warning message:
In file(file, "rt") : clipboard cannot be opened or contains no text
I found some previous answers here and here but for one the copy doesn't work on the way in, and for the other the readLines is leading to runaway R sessions for me, both documented below. I have worked through how to get text to and from the clipboard in OS X, which might be useful to some others, but I am hopeful that there are better methods or there is more finesse possible:
# some test data
data <- rbind(c(1,1,2,3), c(1,1, 3, 4), c(1,4,6,7))
str <- "Here is a special string \n\r with \t many üñåé tokens"
# a test input set of numbers to copy to your clipboard if you have nothing to hand
# [10:17:55, 10:37:40, 10:40:26, 10:48:18, 11:00:17, 11:01:12, 11:06:58, 11:09:20, 11:43:41, 11:48:24, 11:49:14, 12:07:31, 12:10:52, 12:10:52, 12:19:00, 12:19:00, 12:19:43, 12:20:55, 12:38:27, 12:38:27, 12:55:09, 12:55:10, 12:57:31, 12:57:31, 13:04:16, 13:04:16, 13:06:51 13:06:51, 14:55:06, 14:56:10, 15:01:30, 15:28:42, 3:29:17, 15:35:33, 15:58:32, 16:05:07, 16:09:16, 16:10:36, 16:32:57, 16:32:57, 16:34:32, 16:38:16, 17:43:27, 17:53:01, 17:56:14, 18:08:21, 18:17:23, 18:37:23, 18:37:23, 18:43:13, 18:43:13 18:51:43, 18:51:43, 19:05:39, 19:05:39]
# Input works reasonably well for tables and text
cb_handle <- pipe("pbcopy", "w")
write.table(data, file=cb_handle)
close(cb_handle)
cb_handle <- pipe("pbcopy", "w")
write(str, file = cb_handle)
close(cb_handle)
# DO NOT USE THIS ONE as it leads to a runaway R process
cb_handle <- pipe("pbcopy", "r")
read.table(cb_handle)
# This reads in the contents but leaves cleanup to do if not really a table
cb_handle <- pipe("pbpaste")
data_in <- read.table(cb_handle)
Related
This is my first question here. For now I'm learning how to use R in R-studio, and when I tried to read the data in a matrix form, the program showed the mistake. I tried this code:
ModelName = 'new_file' #I'm writing the file name in the same directory as the .r file is
FileName = paste(ModelName, '.txt', sep = '') #as far as I understand, I'm telling the program that
the file is in the form of txt
### Read Time series
d = as.matrix(read.table(FileName, header= T))
And then the program writes this:
Error in h(simpleError(msg, call)) :
error in evaluating the argument 'x' in selecting a method for function 'as.matrix':
cannot open the connection
And I don't understand why it's not working.
The file for analysis is in the txt form, the example of data is below:
decy Temp CTD_S OxFix Pro Syn Piceu Naneu
2011.74221 27.60333 36.20700 27.26667 58638.33333 13107.00000 799.66667 117.66667
2011.74401 26.97950 36.13400 27.05000 71392.50000 13228.50000 1149.00000 116.50000
2011.74617 24.99750 35.34450 24.80000 264292.00000 27514.00000 2434.50000 132.50000
2011.74692 24.78400 35.25800 25.82500 208996.50000 39284.00000 3761.75000 220.75000
My r-studio version is 4.2.0.
I would be very grateful for explanation.
I'm working with limited RAM (AWS free tier EC2 server - 1GB).
I have a relatively large txt file "vectors.txt" (800mb) I'm trying to read into R. Having tried various methods I have failed to read in this vector to memory.
So, I was researching ways of reading it in in chunks. I know that the dim of the resulting data frame should be 300K * 300. If I was able to read in the file e.g. 10K lines at a time and then save each chunk as an RDS file I would be able to loop over the results and get what I need, albeit just a little slower with less convenience than having the whole thing in memory.
To reproduce:
# Get data
url <- 'https://github.com/eyaler/word2vec-slim/blob/master/GoogleNews-vectors-negative300-SLIM.bin.gz?raw=true'
file <- "GoogleNews-vectors-negative300-SLIM.bin.gz"
download.file(url, file) # takes a few minutes
R.utils::gunzip(file)
# word2vec r library
library(rword2vec)
w2v_gnews <- "GoogleNews-vectors-negative300-SLIM.bin"
bin_to_txt(w2v_gnews,"vector.txt")
So far so good. Here's where I struggle:
word_vectors = as.data.frame(read.table("vector.txt",skip = 1, nrows = 10))
Returns "cannot allocate a vector of size [size]" error message.
Tried alternatives:
word_vectors <- ff::read.table.ffdf(file = "vector.txt", header = TRUE)
Same, not enough memory
word_vectors <- readr::read_tsv_chunked("vector.txt",
callback = function(x, i) saveRDS(x, i),
chunk_size = 10000)
Resulted in:
Parsed with column specification:
cols(
`299567 300` = col_character()
)
|=========================================================================================| 100% 817 MB
Error in read_tokens_chunked_(data, callback, chunk_size, tokenizer, col_specs, :
Evaluation error: bad 'file' argument.
Is there any other way to turn vectors.txt into a data frame? Maybe by breaking it into pieces and reading in each piece, saving as a data frame and then to rds? Or any other alternatives?
EDIT:
From Jonathan's answer below, tried:
library(rword2vec)
library(RSQLite)
# Download pre trained Google News word2vec model (Slimmed down version)
# https://github.com/eyaler/word2vec-slim
url <- 'https://github.com/eyaler/word2vec-slim/blob/master/GoogleNews-vectors-negative300-SLIM.bin.gz?raw=true'
file <- "GoogleNews-vectors-negative300-SLIM.bin.gz"
download.file(url, file) # takes a few minutes
R.utils::gunzip(file)
w2v_gnews <- "GoogleNews-vectors-negative300-SLIM.bin"
bin_to_txt(w2v_gnews,"vector.txt")
# from https://privefl.github.io/bigreadr/articles/csv2sqlite.html
csv2sqlite <- function(tsv,
every_nlines,
table_name,
dbname = sub("\\.txt$", ".sqlite", tsv),
...) {
# Prepare reading
con <- RSQLite::dbConnect(RSQLite::SQLite(), dbname)
init <- TRUE
fill_sqlite <- function(df) {
if (init) {
RSQLite::dbCreateTable(con, table_name, df)
init <<- FALSE
}
RSQLite::dbAppendTable(con, table_name, df)
NULL
}
# Read and fill by parts
bigreadr::big_fread1(tsv, every_nlines,
.transform = fill_sqlite,
.combine = unlist,
... = ...)
# Returns
con
}
vectors_data <- csv2sqlite("vector.txt", every_nlines = 1e6, table_name = "vectors")
Resulted in:
Splitting: 12.4 seconds.
Error: nThread >= 1L is not TRUE
Another option would be to do the processing on-disk, e.g. using an SQLite file and dplyr's database functionality. Here's one option: https://stackoverflow.com/a/38651229/4168169
To get the CSV into SQLite you can also use the bigreadr package which has an article on doing just this: https://privefl.github.io/bigreadr/articles/csv2sqlite.html
I have a code block of the following:
# Obtain records from all patients
patientDir <- sort(list.dirs(path = "sample_images", full.names = TRUE, recursive = FALSE))
dataframes <- list()
i = 1
while(i<19){
# Strip the patient out
patient <- coreHist(patientDir[i])
print("1")
setwd("/Volumes/HUGE storage drive/")
exists<- file.exists(patientDir[i])
print(exists)
# Extract the relevant information from the patient
dicom <- readDICOM(patientDir[i])
dicomdf <- dicomTable(dicom$hdr)
patient_id <- dicomdf$`0010-0020-PatientID`[1]
print("2")
# Normalize their VX's
sum<- sum(patient$histData$finalFreq)
print("3")
# Create the new VX's
patient$histData$finalFreq_scaled <- (patient$histData$finalFreq/sum)
print("4")
# Add their ID
patient$histData$patientid <- patient_id
print("5")
# Keep only the important columns
patient$histData <- patient$histData[c("patientid", "Var1", "finalFreq_scaled")]
print("6")
# Add these dataframes to a list for better recall afterwards
dataframes[[i]] <- patient$histData
print("7")
# Additional code to transpose and merge dataframes
if(i == 1){
wide_df <- patient$histData
}else{
wide_df <- rbind(wide_df,patient$histData )
}
print("8")
print(paste(c("Patient", i), sep ="", collapse = "-"))
i = i+1
}
However, after a (seemingly random) number of iterations, the code fails right after the line "print("1")" with the following error:
Error in file(con, "rb") : cannot open the connection
The working directory is set to an external hard drive as the "sample_images" folder is 62GB large. I thought perhaps there was a timeout connection with R studio and my external hard drive so I tried to "remain active" on my computer, I've also tried resetting the working directory after each iteration to make sure it can find the file.
When it fails on a certain patient, I check manually to see if that file does indeed exist, and it does. Any thoughts?
I'm actually not sure why the error was happening, but to fix it I simply added a "try" statement:
attempt <- 1
while(is.null(dicom) && attempt <= 3){
attempt <- attempt + 1
try(
dicom <- readDICOM(patientDir[i])
)
}
This did indeed work.
I am following the tutorials of Machine Learning for Hackers (https://github.com/johnmyleswhite/ML_for_Hackers) and I am using Sublime Text as a text editor. To run my code, I use SublimeREPL R.
I am using this code, taken directly from the book:
setwd("/path/to/folder")
# Load the text mining package
library(tm)
library(ggplot2)
# Loading all necessary paths
spam.path <- "data/spam/"
spam2.path <- "data/spam_2/"
easyham.path <- "data/easy_ham/"
easyham.path2 <- "data/easy_ham_2/"
hardham.path <- "data/hard_ham/"
hardham2.path <- "data/hard_ham_2/"
# Get the content of each email
get.msg <- function(path) {
con <- file(path, open = "rt", encoding = "latin1")
text <- readLines(con)
msg <- text[seq(which(text == "")[1] + 1, length(text),1)]
close(con)
return(paste(msg, collapse = "\n"))
}
# Create a vector where each element is an email
spam.docs <- dir(spam.path)
spam.docs <- spam.docs[which(spam.docs != "cmds")]
all.spam <- sapply(spam.docs, function(p) get.msg(paste(spam.path, p, sep = "")))
# Log the spam
head(all.spam)
This piece of code works fine in RStudio (with the data provided here: https://github.com/johnmyleswhite/ML_for_Hackers/tree/master/03-Classification) but when I run it in Sublime, Iget the following error message:
> all.spam <- sapply(spam.docs,
+ function(p) get.msg(file.path(spam.path, p)))
Error in seq.default(which(text == "")[1] + 1, length(text), 1) :
'from' cannot be NA, NaN or infinite
In addition: Warning messages:
1: In readLines(con) :
invalid input found on input connection 'data/spam/00006.5ab5620d3d7c6c0db76234556a16f6c1'
2: In readLines(con) :
invalid input found on input connection 'data/spam/00009.027bf6e0b0c4ab34db3ce0ea4bf2edab'
3: In readLines(con) :
invalid input found on input connection 'data/spam/00031.a78bb452b3a7376202b5e62a81530449'
4: In readLines(con) :
incomplete final line found on 'data/spam/00031.a78bb452b3a7376202b5e62a81530449'
5: In readLines(con) :
invalid input found on input connection 'data/spam/00035.7ce3307b56dd90453027a6630179282e'
6: In readLines(con) :
incomplete final line found on 'data/spam/00035.7ce3307b56dd90453027a6630179282e'
>
I get the same results when I take the code from John Myles White's repo.
How can I fix this?
Thanks
I think the problem got is in using encoding=latin1, you can just remove this one, I test it in my environment, it ran well.
spam.docs <- paste(spam.path,spam.docs,sep="")
all.spam <- sapply(spam.docs,get.msg)
Warning message:
In readLines(con) :
incomplete final line found on 'XXXXXXXXXXXXXXXXX/ML_for_Hackers-master/03-Classification/data/spam/00136.faa39d8e816c70f23b4bb8758d8a74f0'
still some warnnings in it, but it can produce the results well.
Thanks.
(Windows 7 / R version 3.0.1)
Below the commands and the resulting error:
> library(tm)
> pdf <- readPDF(PdftotextOptions = "-layout")
> dat <- pdf(elem = list(uri = "17214.pdf"), language="de", id="id1")
Error in file(con, "r") : cannot open the connection
In addition: Warning message:
In file(con, "r") :
cannot open file 'C:\Users\Raffael\AppData\Local\Temp
\RtmpS8Uql1\pdfinfo167c2bc159f8': No such file or directory
How do I solve this issue?
EDIT I
(As suggested by Ben and described here)
I downloaded Xpdf copied the 32bit version to
C:\Program Files (x86)\xpdf32
and the 64bit version to
C:\Program Files\xpdf64
The environment variables pdfinfo and pdftotext are referring to the respective executables either 32bit (tested with R 32bit) or to 64bit (tested with R 64bit)
EDIT II
One very confusing observation is that starting from a fresh session (tm not loaded) the last command alone will produce the error:
> dat <- pdf(elem = list(uri = "17214.pdf"), language="de", id="id1")
Error in file(con, "r") : cannot open the connection
In addition: Warning message:
In file(con, "r") :
cannot open file 'C:\Users\Raffael\AppData\Local\Temp\RtmpKi5GnL
\pdfinfode8283c422f': No such file or directory
I don't understand this at all because the function variable is not defined by tm.readPDF yet. Below you'll find the function pdf refers to "naturally" and to what is returned by tm.readPDF:
> pdf
function (elem, language, id)
{
meta <- tm:::pdfinfo(elem$uri)
content <- system2("pdftotext", c(PdftotextOptions, shQuote(elem$uri),
"-"), stdout = TRUE)
PlainTextDocument(content, meta$Author, meta$CreationDate,
meta$Subject, meta$Title, id, meta$Creator, language)
}
<environment: 0x0674bd8c>
> library(tm)
> pdf <- readPDF(PdftotextOptions = "-layout")
> pdf
function (elem, language, id)
{
meta <- tm:::pdfinfo(elem$uri)
content <- system2("pdftotext", c(PdftotextOptions, shQuote(elem$uri),
"-"), stdout = TRUE)
PlainTextDocument(content, meta$Author, meta$CreationDate,
meta$Subject, meta$Title, id, meta$Creator, language)
}
<environment: 0x0c3d7364>
Apparently there is no difference - then why use readPDF at all?
EDIT III
The pdf file is located here: C:\Users\Raffael\Documents
> getwd()
[1] "C:/Users/Raffael/Documents"
EDIT IV
First instruction in pdf() is a call to tm:::pdfinfo() - and there the error is caused within the first few lines:
> outfile <- tempfile("pdfinfo")
> on.exit(unlink(outfile))
> status <- system2("pdfinfo", shQuote(normalizePath("C:/Users/Raffael/Documents/17214.pdf")),
+ stdout = outfile)
> tags <- c("Title", "Subject", "Keywords", "Author", "Creator",
+ "Producer", "CreationDate", "ModDate", "Tagged", "Form",
+ "Pages", "Encrypted", "Page size", "File size", "Optimized",
+ "PDF version")
> re <- sprintf("^(%s)", paste(sprintf("%-16s", sprintf("%s:",
+ tags)), collapse = "|"))
> lines <- readLines(outfile, warn = FALSE)
Error in file(con, "r") : cannot open the connection
In addition: Warning message:
In file(con, "r") :
cannot open file 'C:\Users\Raffael\AppData\Local\Temp\RtmpquRYX6\pdfinfo8d419174450': No such file or direc
Apparently tempfile() simply doesn't create a file.
> outfile <- tempfile("pdfinfo")
> outfile
[1] "C:\\Users\\Raffael\\AppData\\Local\\Temp\\RtmpquRYX6\\pdfinfo8d437bd65d9"
The folder C:\Users\Raffael\AppData\Local\Temp\RtmpquRYX6 exists and holds some files but none is named pdfinfo8d437bd65d9.
Intersting, on my machine after a fresh start pdf is a function to convert an image to a PDF:
getAnywhere(pdf)
A single object matching ‘pdf’ was found
It was found in the following places
package:grDevices
namespace:grDevices [etc.]
But back to the problem of reading in PDF files as text, fiddling with the PATH is a bit hit-and-miss (and annoying if you work across several different computers), so I think the simplest and safest method is to call pdf2text using system as Tony Breyal describes here.
In your case it would be (note the two sets of quotes):
system(paste('"C:/Program Files/xpdf64/pdftotext.exe"',
'"C:/Users/Raffael/Documents/17214.pdf"'), wait=FALSE)
This could easily be extended with an *apply function or loop if you have many PDF files.