I am new to Julia so sorry if this question is obvious.
I am trying to use Julia to help me run a series of finite element models, which use a text input file to give instructions to the finite element solver. Basically, I would like to use Julia to read in the base input file, edit some parameters on some lines of the file and then write it as a new file. I am getting hung up on a couple things though.
Currently, I am reading in the file like this
mdl = "fullmodelSVTV"; #name of input file
A = readlines(mdl*".inp")
This read each line from the file in as a separate string in a vector which I like because it makes it easier to edit the sections I want but it also makes things more difficult when I try to write to a new file.
I am writing the file like this.
io = open("name.inp","w")
print(io,A)
close(io)
When I try to write to a new file the output ends up look like this
Output from code
which is ["string at index 1","string at index 2","string at index 3"...].
What I would like to do is output this the exact same way is it is read in with string at each index of the vector on its own line. I would also like to remove the brackets and quotation marks from the file, as they might interfere with the finite element solver.
I think I have found a way to concatenate all of the strings at each index and separated them with a new line like shown below.
for i in 1:length(A)
conc = conc*"\n"*lines[i]
end
The issue with this is that it takes a long time to do given the size of the input files I am working with and I feel like there has to achieve my goal.
I also cannot find a way to remove the brackets or quotation marks when writing the file.
So, I'm wondering if anyone has any advice for a better way to write these text files in terms of both concatenating all of the strings from the vector when outputting as well as outputting without the brackets and quotation marks.
Thanks, any advice is appreciated.
The issue with print(io,A) is that it is printing a representation of the vector, but in fact you want to print each element of the vector. To do so, you can simply print each line in a loop:
open("name.inp", "w") do io
for line in A
println(io, line)
end
end
This avoids the overhead of string concatenation.
I have a .csv file that is 112GB in weight but neither vroom nor data.table::fread will open it. Even if I ask to read in 10 rows or just a couple of columns it complains with mapping error: Cannot allocate memory.
df<-data.table::fread("FINAL_data_Bus.csv", select = c(1:2),nrows=10)
System errno 22 unmapping file: Invalid argument
Error in data.table::fread("FINAL_data_Bus.csv", select = c(1:2), nrows = 10) :
Opened 112.3GB (120565605488 bytes) file ok but could not memory map it. This is a 64bit process. There is probably not enough contiguous virtual memory available.
read.csv on the other hand will read the ten rows happily.
Why won't vroom or fread read it using the usual altrep, even for 10 rows?
This matter has been discussed by the main creator of data.table package at https://github.com/Rdatatable/data.table/issues/3526. See the comment by Matt Dowle himself at https://github.com/Rdatatable/data.table/issues/3526#issuecomment-488364641. From what I understand, the gist of the matter is that to read even 10 lines from a huge csv file with fread, the entire file needs to be memory mapped. So fread cannot be used on its own in case your csv file is too big for your machine. Please correct me if I'm wrong.
Also, I haven't been able to use vroom with big more-than-RAM csv files. Any pointers towards this end will be appreciated.
For me, the most convenient way to check out a huge (gzipped) csv file is by using a small command line tool csvtk from https://bioinf.shenwei.me/csvtk/
e.g., check dimensions with
csvtk dim BigFile.csv.gz
and, check out head with top 100 rows
csvtk head -n100 BigFile.csv.gz
get a better view of above with
csvtk head -n100 BigFile.csv.gz | csvtk pretty | less -SN
Here I've used less command available with "Gnu On Windows" at https://github.com/bmatzelle/gow
A word of caution - many people suggest using command
wc -l BigFile.csv
to check out no. of lines from a big csv file. In most cases, it will be equal to the no. of rows. But in case the big csv file contains newline characters within a cell, to use a spreadsheet term, the above command will not show the no. of rows. In such cases the no. of lines is different from the no. of rows. So it is advisable to use csvtk dim or csvtk nrow. Other csv command line tools like xsv, miller will also show correct results.
Another word of caution - the short command fread(cmd="head -n 10 BigFile.csv") is not advisable to preview top few lines in case some columns contain significant leading zeros in data such as 0301, 0542, etc. since without column specification, fread will interpret them as integers and not show leading zeros from such columns. For example, in some databases that I have to analyse, the first digit zero in a particular column means that it is a Revenue Receipt. So better use a command line tool like csvtk, miller, xsv with less -SN for previewing a big csv file which show the file "as is" without any potentially wrong interpretation.
PS1: Even spreadsheets like MS Excel and LibreOffice Calc loses leading zeroes in csv files by default. LibreOffice Calc actually shows leading zeroes in the preview window but loses them when you load the file! I'm yet to find a spreadsheet that does not lose leading zeroes in csv files by default.
PS2: I've posted my approach to querying very large csv files at https://stackoverflow.com/a/68693819/8079808
EDIT:
VROOM does have difficulty when dealing with huge files since it needs to store the index in memory as well as any data you read from the file. See development thread https://github.com/r-lib/vroom/issues/203
if you can help with converting a big text:
sample of the text :
X1"II"ID_Sitze.x"II"Produktionsdatum.x"II"Herstellernummer.x"II"Werksnummer.x"II"Fehlerhaft.x"II"Fehlerhaft_Datum.x"II"Fehlerhaft_Fahrleistung.x"II"ID_Sitze.y"II"Produktionsdatum.y"II"Herstellernummer.y"II"Werksnummer.y"II"Fehlerhaft.y"II"Fehlerhaft_Datum.y"II"Fehlerhaft_Fahrleistung.y""1"II1II"K2LE1-109-1091-2"II2008-11-12II"109"II1091II1II2010-10-18II37080IINAIINAIINAIINAIINAIINAIINA"2"II2II"K2LE1-109-1091-1"II2008-11-12II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"3"II3II"K2LE1-109-1091-12"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"4"II4II"K2LE1-109-1091-5"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"5"II5II"K2LE1-109-1091-40"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"6"II6II"K2LE1-109-1091-15"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"7"II7II"K2LE1-109-1091-31"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"8"II8II"K2LE1-109-1091-6"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"9"II9II"K2LE1-109-1091-8"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"10"II10II"K2LE1-109-1091-25"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"11"II11II"K2LE1-109-1091-24"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"12"II12II"K2LE1-109-1091-36"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"13"II13II"K2LE1-109-1091-33"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"14"II14II"K2LE1-109-1091-42"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"15"II15II"K2LE1-109-1091-14"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"16"II16II"K2LE1-109-1091-21"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"17"II17II"K2LE1-109-1091-43"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"18"II18II"K2LE1-109-1091-44"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA"19"II19II"K2LE1-109-1091-19"II2008-11-13II"109"II1091II1II2010-10-19II37
with separator "II" to a Dataframe.
i have used :
df_BSt7<-readLines("Komponente_K2LE1.txt")
df_BST7<-str_replace_all(df_BSt7,"II",",")
df_BST7<-read.table(df_BST7,sep = ",")
head(df_BST7)
but I am always getting an Error
could not allocate memory (206 Mb) in C function 'R_AllocStringBuffer'
and when i call head() I am getting
'"X1","ID_Sitze.x","Produktionsdatum.x","Herstellernummer.x","Werksnummer.x","Fehlerhaft.x","Fehlerhaft_Datum.x","Fehlerhaft_Fahrleistung.x","ID_Sitze.y","Produktionsdatum.y","Herstellernummer.y","Werksnummer.y","Fehlerhaft.y","Fehlerhaft_Datum.y","Fehlerhaft_Fahrleistung.y""1",1,"K2LE1-109-1091-2",2008-11-12,"109",1091,1,2010-10-18,37080,NA,NA,NA,NA,NA,NA,NA"2",2,"K2LE1-109-1091-1",2008-11-12,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"3",3,"K2LE1-109-1091-12",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"4",4,"K2LE1-109-1091-5",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"5",5,"K2LE1-109-1091-40",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"6",6,"K2LE1-109-1091-15",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"7",7,"K2LE1-109-1091-31",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"8",8,"K2LE1-109-1091-6",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"9",9,"K2LE1-109-1091-8",2008-11-13,"109",1091,0,NA,0,NA,NA,NA,NA,NA,NA,NA"10",10,"K2LE1-109-109 [... abgeschnitten]
So, there are several possible problems, some might be specific to your examples.
Clean example data
First, let's take a look at your example data. In what you provide, there are no newlines, everything is on a single line. Is that the case in the original "Komponente_K2LE1.txt" file? If yes, we might need some more work to find where to add newlines (see below).
The first column name, X1, only has a quote on the right. It can't work without the quote on the left: "X1"IIID_Sitze.
The saved dataframe has 16 columns, I expect because there is a row number at the beginning of each row which is not in the header. So we can add an additional column header to have 16 of them:
"row_nb"II"X1"II"ID_Sitze.x"II"Produktionsdatum.x"II"Herstellernummer.x"II"Werksnummer.x"II"Fehlerhaft.x"II"Fehlerhaft_Datum.x"II"
Then we have a small problem with line 19 which is truncated, I assume it comes from your copy/paste and that's not a problem with the full file. So let's forget about it for now. So I have this text:
raw_lines <- '"row_nb"II"X1"II"ID_Sitze.x"II"Produktionsdatum.x"II"Herstellernummer.x"II"Werksnummer.x"II"Fehlerhaft.x"II"Fehlerhaft_Datum.x"II"Fehlerhaft_Fahrleistung.x"II"ID_Sitze.y"II"Produktionsdatum.y"II"Herstellernummer.y"II"Werksnummer.y"II"Fehlerhaft.y"II"Fehlerhaft_Datum.y"II"Fehlerhaft_Fahrleistung.y"
"1"II1II"K2LE1-109-1091-2"II2008-11-12II"109"II1091II1II2010-10-18II37080IINAIINAIINAIINAIINAIINAIINA
"2"II2II"K2LE1-109-1091-1"II2008-11-12II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"3"II3II"K2LE1-109-1091-12"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"4"II4II"K2LE1-109-1091-5"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"5"II5II"K2LE1-109-1091-40"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"6"II6II"K2LE1-109-1091-15"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"7"II7II"K2LE1-109-1091-31"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"8"II8II"K2LE1-109-1091-6"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"9"II9II"K2LE1-109-1091-8"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"10"II10II"K2LE1-109-1091-25"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"11"II11II"K2LE1-109-1091-24"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"12"II12II"K2LE1-109-1091-36"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"13"II13II"K2LE1-109-1091-33"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"14"II14II"K2LE1-109-1091-42"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"15"II15II"K2LE1-109-1091-14"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"16"II16II"K2LE1-109-1091-21"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"17"II17II"K2LE1-109-1091-43"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA
"18"II18II"K2LE1-109-1091-44"II2008-11-13II"109"II1091II0IINAII0IINAIINAIINAIINAIINAIINAIINA'
Now you are replacing "II" with "," and reading it with read.table(), which is perfectly correct, except that read.table() would assume you're giving a file name and throw an error as it can't open that connection (that file). To make it work you need this:
df_BST7<-str_replace_all(raw_lines,'II',",")
df_BST7 <- read.table(text = df_BST7,sep = ",")
So now that does run on my computer.
Side note, since you're already using the tidyverse, you could as well use that equivalent code instead:
df_BST7 <- str_replace_all(raw_lines,'II',",")
df_BST7 <- read_csv(df_BST7)
which could help with something later
The error message
Now the error message you get suggests it's a memory problem. I see 2 possibilities: the table is so big it can't fit in your computer's memory, or indeed your whole input table is on a single line, so that makes a very long line, which won't fit in memory.
Whole table too big
I don't think it's the problem here, but just in case, check how big the file on the disk is, and how much memory is free on your computer, and whether you could free up enough memory by just closing a few programs. Possibly you could save your modified text to disk and delete it from R's memory with rm(df_BSt7), then load it directly from disk into df_BST7. Since the raw text fits in memory, that should work. If memory is a challenge, you can replace read_csv() with read_csv_chunked() and process one chunk at a time.
All on one line
I think this is the most likely. Again, there are two possibilities.
Missing carriage return
Actually line breaks can be described in 2 ways, Unix-like systems (MacOS and GNU/Linux) use the symbol newline (\n), whereas Windows uses a pair of carriage return and newline (\r\n). I'm not sure how this could create problems inside R, but if your file was generated on a Unix-like system and you're trying to read it on Windows that's an explanation. Then the goal would become to replace \n with \r\n.
No line breaks at all
If there is absolutely no line break, neither \r nor \n, then we need to guess where they are. On a Unix system you could try awk or sed, but there are ways to do it in R. The following code should work, except the last column will need some cleaning up afterwards:
raw_lines2 <- str_remove_all(raw_lines2, "\r")
all_fields <- raw_lines2 %>%
str_split("II") %>%
unlist()
nb_lines <- (length(all_fields) - 1)/15
reconstruct_lines <- map_chr(0:(nb_lines-1), ~ paste(all_fields[(2+15*.):(16+15*.)], collapse = ",")) %>%
paste(collapse = "\n")
cat(reconstruct_lines)
I am using the fread function in R for reading files to data.tables objects.
However, when reading the file I'd like to skip lines that start with #, is that possible?
I could not find any mention to that in the documentation.
fread can read from a piped command that filters out such lines, like this:
fread("grep -v '^#' filename")
Not currently, but it's on the list to do.
Are the # lines at the top forming a header which is more than 30 lines long?
If so, that's come up before and the solution is :
fread("filename", autostart=60)
where 60 is chosen to be inside the block of data to be read.
From ?fread :
Once the separator is found on line autostart, the number of columns
is determined. Then the file is searched backwards from autostart
until a row is found that doesn't have that number of columns. Thus,
the first data row is found and any human readable banners are
automatically skipped. This feature can be particularly useful for
loading a set of files which may not all have consistently sized
banners. Setting skip>0 overrides this feature by setting
autostart=skip+1 and turning off the search upwards step.
The default autostart=30 might just need bumping up a bit in your case.
Or maybe skip=n or skip="string" helps :
If -1 (default) use the procedure described below starting on line autostart to find the first data row. skip>=0 means ignore autostart and take line skip+1 as the first data row (or column names according to header="auto"|TRUE|FALSE as usual). skip="string" searches for "string" in the file (e.g. a substring of the column names row) and starts on that line (inspired by read.xls in package gdata).
Setting:
I have (simple) .csv and .dat files created from laboratory devices and other programs storing information on measurements or calculations. I have found this for other languages but nor for R
Problem:
Using R, I am trying to extract values to quickly display results w/o opening the created files. Hereby I have two typical settings:
a) I need to read a priori unknown values after known key words
b) I need to read lines after known key words or lines
I can't make functions such as scan() and grep() work.
c) Finally I would like to loop over dozens of files in a folder and give me a summary (to make the picture complete: I will manage this part)
I woul appreciate any form of help.
ok, it works for the key value (although perhaps not very nice)
variable<-scan("file.csv", what=character(),sep="")
returns a charactor vector of everything
variable[grep("keyword", ks)+2] # + 2 as the actual value is stored two places ahead
returns characters of seaked values.
as.numeric(lapply(variable, gsub, patt=",", replace="."))
for completion: data had to be altered to number and "," and "." problem needed to be solved.
in a line:
data=as.numeric(lapply(ks[grep("Ks_Boden", ks)+2], gsub, patt=",", replace="."))
Perseverence is not to bad of an asset ;-)
The rest isn't finished, yet, I will post once finished.