Re: [R] assigning and saving datasets in a loop, with names changing with i
Marie Pierre Sylvestre wrote:
Dear R users,
I am analysing a very large data set and I need to perform several data
manipulations. The dataset is so big that the only way I can play with it
without having memory problems (E.g. cannot allocate vectors of size...)
is to write a batch script to:
1. cut the data into pieces
2. save the pieces in seperate .RData files
3. Remove everything from the environment
4. load one of the piece
5. perform the manipulations on it
6. save it and remove it from the environment
7. Redo 4-6 for every piece
8. Merge everything together at the end
It works if coded line by line but since I'll have to perform these tasks
on other data sets, I am trying to automate this as much as I can.
The trackObjs package is designed to make it easy to work in approximately
this manner -- it saves objects automatically to disk but they are still
accessible as normal.
Here's how you could do the above - this example works with 10 8Mb objects
in a R session with a limit of 40Mb.
# allow R only 40Mb of vector memory
mem.limits(vsize=40e6)
mem.limits()/1e6
library(trackObjs)
# start tracking to store data objects in the directory 'data'
# each object is 8Mb, and we store 10 of them
track.start(data)
n - 10
m - 1e6
constructObject - function(i) i+rnorm(m)
# steps 1, 2 3:
for (i in 1:n) {
xname - paste(x, i, sep=)
cat(, xname)
assign(xname, constructObject(i))
# store in a file, accessible by name:
track(list=xname)
}
cat(\n)
gc(TRUE)
# accessing object by name
object.size(x1)/2^20 # In Mb
mean(x1)
mean(x2)
gc(TRUE)
# steps 4:6
# accessing object through a constructed name
result - sapply(1:n, function(i) mean(get(paste(x, i, sep=
result
# remove the data objects
track.remove(list=paste(x, 1:n, sep=))
track.stop()
Here's the a full transcript of the above - note how whenever gc() is
called there is hardly any vector memory in use.
# allow R only 40Mb of vector memory
mem.limits(vsize=40e6)
nsizevsize
NA 4000
mem.limits()/1e6
nsize vsize
NA40
library(trackObjs)
# start tracking to store data objects in the directory 'data'
# each object is 8Mb, and we store 10 of them
track.start(data)
n - 10
m - 1e6
constructObject - function(i) i+rnorm(m)
# steps 1, 2 3:
for (i in 1:n) {
+xname - paste(x, i, sep=)
+cat(, xname)
+assign(xname, constructObject(i))
+# store in a file, accessible by name:
+track(list=xname)
+ }
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 cat(\n)
gc(TRUE)
Garbage collection 19 = 6+0+13 (level 2) ...
4.0 Mbytes of cons cells used (42%)
0.7 Mbytes of vectors used (5%)
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 148362 4.0 35 9.4 NA 35 9.4
Vcells 89973 0.71950935 14.9 38.2 2112735 16.2
# accessing object by name
object.size(x1)/2^20 # In Mb
[1] 7.629417
mean(x1)
[1] 0.998635
mean(x2)
[1] 1.999656
gc(TRUE)
Garbage collection 22 = 7+1+14 (level 2) ...
4.0 Mbytes of cons cells used (43%)
0.7 Mbytes of vectors used (6%)
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 149264 4.0 35 9.4 NA 35 9.4
Vcells 90160 0.71560747 12.0 38.2 2112735 16.2
# steps 4:6
result - sapply(1:n, function(i) mean(get(paste(x, i, sep=
result
[1] 0.998635 1.999656 2.997368 4.000197 5.000159 6.001216 6.999552
[8] 7.999743 8.82 10.001355
# remove the data objects
track.remove(list=paste(x, 1:n, sep=))
[1] x1 x2 x3 x4 x5 x6 x7 x8 x9 x10
track.stop()
I am using a loop in which I used 'assign' and 'get' (pseudo code below).
My problem is when I use 'get', it prints the whole object on the screen.
I am wondering whether there is a more efficient way to do what I need to
do. Any help would be appreciated. Please keep in mind that the whole
process is quite computer-intensive, so I can't keep everything in the
environment while R performs calculations.
Say I have 1 big dataframe called data. I use 'split' to divide it into a
list of 12 dataframes (call this list my.list)
my.fun is a function that takes a dataframe, performs several
manipulations on it and returns a dataframe.
for (i in 1:12){
assign( paste( data, i, sep=), my.fun(my.list[i])) # this works
# now I need to save this new object as a RData.
# The following line does not work
save(paste(data, i, sep = ), file = paste( paste(data, i, sep =
), RData, sep=.))
}
# This works but it is a bit convoluted!!!
temp - get(paste(data, i, sep = ))
save(temp, file = lala.RData)
}
I am *sure* there is something more clever to do but I can't find it. Any
help would be appreciated.
best regards,
MP
__
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and provide
Re: [R] assigning and saving datasets in a loop, with names changing with i
Won't it be simpler to do:
for (i in 1:12){
data - my.fun(my.list[i]))
save(data,file = paste(data,i,.RData, sep=)) }
--- Marie Pierre Sylvestre
[EMAIL PROTECTED] wrote:
Dear R users,
I am analysing a very large data set and I need to
perform several data
manipulations. The dataset is so big that the only
way I can play with it
without having memory problems (E.g. cannot
allocate vectors of size...)
is to write a batch script to:
1. cut the data into pieces
2. save the pieces in seperate .RData files
3. Remove everything from the environment
4. load one of the piece
5. perform the manipulations on it
6. save it and remove it from the environment
7. Redo 4-6 for every piece
8. Merge everything together at the end
It works if coded line by line but since I'll have
to perform these tasks
on other data sets, I am trying to automate this as
much as I can.
I am using a loop in which I used 'assign' and 'get'
(pseudo code below).
My problem is when I use 'get', it prints the whole
object on the screen.
I am wondering whether there is a more efficient way
to do what I need to
do. Any help would be appreciated. Please keep in
mind that the whole
process is quite computer-intensive, so I can't keep
everything in the
environment while R performs calculations.
Say I have 1 big dataframe called data. I use
'split' to divide it into a
list of 12 dataframes (call this list my.list)
my.fun is a function that takes a dataframe,
performs several
manipulations on it and returns a dataframe.
for (i in 1:12){
assign( paste( data, i, sep=),
my.fun(my.list[i])) # this works
# now I need to save this new object as a RData.
# The following line does not work
save(paste(data, i, sep = ), file = paste(
paste(data, i, sep =
), RData, sep=.))
}
# This works but it is a bit convoluted!!!
temp - get(paste(data, i, sep = ))
save(temp, file = lala.RData)
}
I am *sure* there is something more clever to do but
I can't find it. Any
help would be appreciated.
best regards,
MP
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained,
reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] assigning and saving datasets in a loop, with names changing with i
Dear R users,
I am analysing a very large data set and I need to perform several data
manipulations. The dataset is so big that the only way I can play with it
without having memory problems (E.g. cannot allocate vectors of size...)
is to write a batch script to:
1. cut the data into pieces
2. save the pieces in seperate .RData files
3. Remove everything from the environment
4. load one of the piece
5. perform the manipulations on it
6. save it and remove it from the environment
7. Redo 4-6 for every piece
8. Merge everything together at the end
It works if coded line by line but since I'll have to perform these tasks
on other data sets, I am trying to automate this as much as I can.
I am using a loop in which I used 'assign' and 'get' (pseudo code below).
My problem is when I use 'get', it prints the whole object on the screen.
I am wondering whether there is a more efficient way to do what I need to
do. Any help would be appreciated. Please keep in mind that the whole
process is quite computer-intensive, so I can't keep everything in the
environment while R performs calculations.
Say I have 1 big dataframe called data. I use 'split' to divide it into a
list of 12 dataframes (call this list my.list)
my.fun is a function that takes a dataframe, performs several
manipulations on it and returns a dataframe.
for (i in 1:12){
assign( paste( data, i, sep=), my.fun(my.list[i])) # this works
# now I need to save this new object as a RData.
# The following line does not work
save(paste(data, i, sep = ), file = paste( paste(data, i, sep =
), RData, sep=.))
}
# This works but it is a bit convoluted!!!
temp - get(paste(data, i, sep = ))
save(temp, file = lala.RData)
}
I am *sure* there is something more clever to do but I can't find it. Any
help would be appreciated.
best regards,
MP
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] assigning and saving datasets in a loop, with names changing with i
you want to use:
save(list=paste(data, i, sep=), file=paste(data, i, .Rdata,
sep=))
b
On Dec 18, 2007, at 9:24 PM, Marie Pierre Sylvestre wrote:
Dear R users,
I am analysing a very large data set and I need to perform several
data
manipulations. The dataset is so big that the only way I can play
with it
without having memory problems (E.g. cannot allocate vectors of
size...)
is to write a batch script to:
1. cut the data into pieces
2. save the pieces in seperate .RData files
3. Remove everything from the environment
4. load one of the piece
5. perform the manipulations on it
6. save it and remove it from the environment
7. Redo 4-6 for every piece
8. Merge everything together at the end
It works if coded line by line but since I'll have to perform these
tasks
on other data sets, I am trying to automate this as much as I can.
I am using a loop in which I used 'assign' and 'get' (pseudo code
below).
My problem is when I use 'get', it prints the whole object on the
screen.
I am wondering whether there is a more efficient way to do what I
need to
do. Any help would be appreciated. Please keep in mind that the whole
process is quite computer-intensive, so I can't keep everything in the
environment while R performs calculations.
Say I have 1 big dataframe called data. I use 'split' to divide it
into a
list of 12 dataframes (call this list my.list)
my.fun is a function that takes a dataframe, performs several
manipulations on it and returns a dataframe.
for (i in 1:12){
assign( paste( data, i, sep=), my.fun(my.list[i])) # this
works
# now I need to save this new object as a RData.
# The following line does not work
save(paste(data, i, sep = ), file = paste( paste(data, i,
sep =
), RData, sep=.))
}
# This works but it is a bit convoluted!!!
temp - get(paste(data, i, sep = ))
save(temp, file = lala.RData)
}
I am *sure* there is something more clever to do but I can't find
it. Any
help would be appreciated.
best regards,
MP
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
