I get the error:
Error in file(fn, "rb") : cannot open the connection
In addition: Warning message:
In file(fn, "rb") :
cannot open file 'C:\Users\***\AppData\Local\Temp\Rtmpwh6Zih\raster\r_tmp_2020-05-
13_170601_12152_33882.gri': No such file or directory
When I run the following code in RStudio (1.2.5042):
raster.binair <- vector(mode = "list", length = length(aggregated.rasters))
for (i in 1:NROW(aggregated.rasters)) {
+ clamped <- clamp(aggregated.rasters[[i]], upper=12, useValues=FALSE)
+ raster.binair[[i]] <- clamped
+ }
"aggregated.rasters" is a list of 96 rasters and when I separately run it, I get the correct list. I recently cleaned my temporary directory (accessed by tempdir()) and deleted the files in there. I suppose the part:
cannot open file 'C:\Users\***\AppData\Local\Temp\Rtmpwh6Zih\raster\r_tmp_2020-05-
13_170601_12152_33882.gri': No such file or directory
is referring to this. I don't know what I did wrong here. Can I get these files back or work around this error?
Files in the temp folder are deleted when an R session ends. So you should never count on them. You can run the code again, but if you want to permanently keep the results you need to write them elsewhere. Here are two options
Write many files
raster.binair <- vector(mode = "list", length = length(aggregated.rasters))
for (i in 1:NROW(aggregated.rasters)) {
f <- paste0("raster_", i)
clamped <- clamp(aggregated.rasters[[i]], upper=12, useValues=FALSE, filename=f)
raster.binair[[i]] <- clamped
}
Write a single file
raster.binair <- vector(mode = "list", length = length(aggregated.rasters))
for (i in 1:NROW(aggregated.rasters)) {
raster.binair[[i]] <- clamp(aggregated.rasters[[i]], upper=12, useValues=FALSE)
}
s <- stack(raster.binair)
s <- writeRaster(s, filename="mydata.tif")
Related
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'm relatively new to using R in this way and I'm completely stuck with the following problem.
I'm attempting to save html pages for parliamentary debates to a local folder in order to carry out some scraping in the future. I've written the following function (relying on other snippets of code rather than entirely freestyle!) in order to construct the directory, strip the URL down to a more understandable format (e.g. "2010-12_academieshl.html"), and then, if the file does not exist, write the file to the specified folder. (At this point I'm aware that the use of gsub below is kind of clumsy!)
dlPages <- function(pageurl, folder ,handle) {
dir.create(folder, showWarnings = FALSE)
gsub_URL <- gsub("/stages.html", "", link_list)
gsub_URL <- gsub("http://services.parliament.uk/bills/", "", gsub_URL)
gsub_URL <- gsub("/", "_", gsub_URL)
page_name <- str_c(gsub_URL, ".html")
if (!file.exists(str_c(folder, "/", page_name))) {
content <- try(getURL(pageurl, curl = handle))
write(content, str_c(folder, "/", page_name))
Sys.sleep(1)
} }
I'm then using l_ply to run a list (link_list) of links over the function:
handle <- getCurlHandle()
l_ply(link_list, dlPages,
folder = "lords_bills_all",
handle = handle)
The following error message is being returned:
Error in file(file, ifelse(append, "a", "w")) : invalid 'description' argument
Along with the following warning messages:
In addition: Warning messages:
1: In if (!file.exists(str_c(folder, "/", page_name))) { :
the condition has length > 1 and only the first element will be used
2: In if (file == "") file <- stdout() else if (substring(file, 1L, :
the condition has length > 1 and only the first element will be used
3: In if (substring(file, 1L, 1L) == "|") { :
the condition has length > 1 and only the first element will be used
Can someone help me understand where I'm going wrong? Also, is it best to use an 'if' argument in this scenario or write a 'for' loop instead?
Thanks in advance.
Andy
What I'm Attempting to Do
I'm attempting to download several weather data files from the US National Climatic Data Centre's FTP server but am running into problems with an error message after successfully completing several file downloads.
After successfully downloading two station/year combinations I start getting an error "530 Not logged in" message. I've tried starting at the offending year and running from there and get roughly the same results. It downloads a year or two of data and then stops with the same error message about not being logged in.
Working Example
Following is a working example (or not) with the output truncated and pasted below.
options(timeout = 300)
ftp <- "ftp://ftp.ncdc.noaa.gov/pub/data/gsod/"
td <- tempdir()
station <– c("983240-99999", "983250-99999", "983270-99999", "983280-99999", "984260-41231", "984290-99999", "984300-99999", "984320-99999", "984330-99999")
years <- 1960:2016
for (i in years) {
remote_file_list <- RCurl::getURL(
paste0(ftp, "/", i, "/"), ftp.use.epsv = FALSE, ftplistonly = TRUE,
crlf = TRUE, ssl.verifypeer = FALSE)
remote_file_list <- strsplit(remote_file_list, "\r*\n")[[1]]
file_list <- paste0(station, "-", i, ".op.gz")
file_list <- file_list[file_list %in% remote_file_list]
file_list <- paste0(ftp, i, "/", file_list)
Map(function(ftp, dest) utils::download.file(url = ftp,
destfile = dest, mode = "wb"),
file_list, file.path(td, basename(file_list)))
}
trying URL 'ftp://ftp.ncdc.noaa.gov/pub/data/gsod/1960/983250-99999-1960.op.gz'
Content type 'unknown' length 7135 bytes
==================================================
downloaded 7135 bytes
...
trying URL 'ftp://ftp.ncdc.noaa.gov/pub/data/gsod/1961/984290-99999-1961.op.gz'
Content type 'unknown' length 7649 bytes
==================================================
downloaded 7649 bytes
trying URL 'ftp://ftp.ncdc.noaa.gov/pub/data/gsod/1962/983250-99999-1962.op.gz'
downloaded 0 bytes
Error in utils::download.file(url = ftp, destfile = dest, mode = "wb") :
cannot download all files In addition: Warning message:
In utils::download.file(url = ftp, destfile = dest, mode = "wb") :
URL ftp://ftp.ncdc.noaa.gov/pub/data/gsod/1962/983250-99999-1962.op.gz':
status was '530 Not logged in'
Different Methods and Ideas I've Tried but Haven't Yet Been Successful
So far I've tried to slow the requests down using Sys.sleep in a for loop and any other manner of retrieving the files more slowly by opening then closing connections, etc. It's puzzling because: i) it works for a bit then stops and it's not related to the particular year/station combination per se; ii) I can use nearly the exact same code and download much larger annual files of global weather data without any errors over a long period of years like this; and iii) it's not always stopping after 1961 going to 1962, sometimes it stops at 1960 when it starts on 1961, etc., but it does seem to be consistently between years, not within from what I've found.
The login is anonymous, but you can use userpwd "ftp:your#email.address". So far I've been unsuccessful in using that method to ensure that I was logged in to download the station files.
I think you're going to need a more defensive strategy when working with this FTP server:
library(curl) # ++gd > RCurl
library(purrr) # consistent "data first" functional & piping idioms FTW
library(dplyr) # progress bar
# We'll use this to fill in the years
ftp_base <- "ftp://ftp.ncdc.noaa.gov/pub/data/gsod/%s/"
dir_list_handle <- new_handle(ftp_use_epsv=FALSE, dirlistonly=TRUE, crlf=TRUE,
ssl_verifypeer=FALSE, ftp_response_timeout=30)
# Since you, yourself, noted the server was perhaps behaving strangely or under load
# it's prbly a much better idea (and a practice of good netizenship) to cache the
# results somewhere predictable rather than a temporary, ephemeral directory
cache_dir <- "./gsod_cache"
dir.create(cache_dir, showWarnings=FALSE)
# Given the sporadic efficacy of server connection, we'll wrap our calls
# in safe & retry functions. Change this variable if you want to have it retry
# more times.
MAX_RETRIES <- 6
# Wrapping the memory fetcher (for dir listings)
s_curl_fetch_memory <- safely(curl_fetch_memory)
retry_cfm <- function(url, handle) {
i <- 0
repeat {
i <- i + 1
res <- s_curl_fetch_memory(url, handle=handle)
if (!is.null(res$result)) return(res$result)
if (i==MAX_RETRIES) { stop("Too many retries...server may be under load") }
}
}
# Wrapping the disk writer (for the actual files)
# Note the use of the cache dir. It won't waste your bandwidth or the
# server's bandwidth or CPU if the file has already been retrieved.
s_curl_fetch_disk <- safely(curl_fetch_disk)
retry_cfd <- function(url, path) {
# you should prbly be a bit more thorough than `basename` since
# i think there are issues with the 1971 and 1972 filenames.
# Gotta leave some work up to the OP
cache_file <- sprintf("%s/%s", cache_dir, basename(url))
if (file.exists(cache_file)) return()
i <- 0
repeat {
i <- i + 1
if (i==6) { stop("Too many retries...server may be under load") }
res <- s_curl_fetch_disk(url, cache_file)
if (!is.null(res$result)) return()
}
}
# the stations and years
station <- c("983240-99999", "983250-99999", "983270-99999", "983280-99999",
"984260-41231", "984290-99999", "984300-99999", "984320-99999",
"984330-99999")
years <- 1960:2016
# progress indicators are like bowties: cool
pb <- progress_estimated(length(years))
walk(years, function(yr) {
# the year we're working on
year_url <- sprintf(ftp_base, yr)
# fetch the directory listing
tmp <- retry_cfm(year_url, handle=dir_list_handle)
con <- rawConnection(tmp$content)
fils <- readLines(con)
close(con)
# sift out only the target stations
map(station, ~grep(., fils, value=TRUE)) %>%
keep(~length(.)>0) %>%
flatten_chr() -> fils
# grab the stations files
walk(paste(year_url, fils, sep=""), retry_cfd)
# tick off progress
pb$tick()$print()
})
You may also want to set curl_interrupt to TRUE in the curl handle if you want to be able to stop/esc/interrupt the downloads.
(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.