Re: [R] [External] converting MATLAB -> R | element-wise operation
Very interesting - thanks! Most of my problems are not limited by compute speed, but its clear that for some sorts of compute-intensive problems, sweep might be a limiting approach. On 2/29/2024 6:12 PM, Richard M. Heiberger wrote: > I decided to do a direct comparison of transpose and sweep. > > > library(microbenchmark) > > NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix > lambda <- c(2, 3, 4) # Example vector > colNN <- t(NN) > > microbenchmark( >sweep = sweep(NN, 2, lambda, "/"), >transpose = t(t(NN)/lambda), >colNN = colNN/lambda > ) > > > Unit: nanoseconds >expr minlq mean median uq max neval cld > sweep 13817 14145 15115.06 14350 14657.5 75932 100 a > transpose 1845 1927 2151.68 2132 2214.0 7093 100 b > colNN82 123 141.86123 164.0 492 100 c > > Note that transpose is much faster than sweep because it is doing less work, > I believe essentially just changing the order of indexing. > > Using the natural sequencing for column-ordered matrices is much much faster. > >> On Feb 28, 2024, at 18:43, peter dalgaard wrote: >> >>> rbind(1:3,4:6)/t(matrix(c(2,3,4), 3,2)) > [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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] [External] converting MATLAB -> R | element-wise operation
I added two more rows library(microbenchmark) NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix lambda <- c(2, 3, 4) # Example vector colNN <- t(NN) matlam <- matrix(lambda, byrow=TRUE, nrow=2, ncol=3) microbenchmark( sweep = sweep(NN, 2, lambda, "/"), transpose = t(t(NN)/lambda), colNN = colNN/lambda, fullsize = NN / matrix(lambda, byrow=TRUE, nrow=2, ncol=3), rowlam = NN / matlam ) Unit: nanoseconds expr minlq mean median uq max neval cld sweep 12546 12792 13919.91 12997.0 13325.0 85608 100 a transpose 1640 1763 1986.04 1947.5 2050.0 7462 100 b colNN8282 161.13 123.0 123.0 3854 100 c fullsize 738 820 932.34 881.5 963.5 2829 100 bc rowlam82 123 168.92 164.0 164.0 820 100 c reshaping the denominator to the correct size in advance is very helpful if you will be doing this division more than once. > On Feb 29, 2024, at 18:12, Richard M. Heiberger wrote: > > I decided to do a direct comparison of transpose and sweep. > > > library(microbenchmark) > > NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix > lambda <- c(2, 3, 4) # Example vector > colNN <- t(NN) > > microbenchmark( > sweep = sweep(NN, 2, lambda, "/"), > transpose = t(t(NN)/lambda), > colNN = colNN/lambda > ) > > > Unit: nanoseconds > expr minlq mean median uq max neval cld > sweep 13817 14145 15115.06 14350 14657.5 75932 100 a > transpose 1845 1927 2151.68 2132 2214.0 7093 100 b > colNN82 123 141.86123 164.0 492 100 c > > Note that transpose is much faster than sweep because it is doing less work, > I believe essentially just changing the order of indexing. > > Using the natural sequencing for column-ordered matrices is much much faster. > >> On Feb 28, 2024, at 18:43, peter dalgaard wrote: >> >>> rbind(1:3,4:6)/t(matrix(c(2,3,4), 3,2)) > > __ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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 -- To UNSUBSCRIBE and more, see 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] Clustering Functions used by Reverse-Dependencies
Dear Ivan, Thank you very much for this interesting information. Regarding: "For well-behaved packages that declare their dependencies correctly, parsing the NAMESPACE for importFrom() and import() calls should give you the explicit imports." I did learn something new (I am not very experienced in package writing). Unfortunately, Roxygen2 as of the current version still suggests to use the pkg::fname approach: "If you are using just a few functions from another package, we recommending adding the package to the Imports: field of the DESCRIPTION file and calling the functions explicitly using ::, e.g., pkg::fun()." https://roxygen2.r-lib.org/articles/namespace.html Regarding analysing the actual code: it is good to know that CMD check has also some functionality. I will look into it, when I find some free time. tools:::.check_packages_used is a few pages of code. On the other hand, the help page for codetools::checkUsage is quite cryptic. But it's good to know at least where to look. Sincerely, Leonard From: Ivan Krylov Sent: Wednesday, February 28, 2024 10:36 AM To: Leo Mada via R-help Cc: Leo Mada Subject: Re: [R] Clustering Functions used by Reverse-Dependencies � Sat, 24 Feb 2024 03:08:26 + Leo Mada via R-help �: > Are there any tools to extract the function names called by > reverse-dependencies? For well-behaved packages that declare their dependencies correctly, parsing the NAMESPACE for importFrom() and import() calls should give you the explicit imports. (What if the package imports the whole dependency? The safe assumption is that all functions are used, but it comes with false positives. You could also walk the package code looking for function names that may belong to the imported package, but that may involve both false positives and false negatives.) For the rest of the imports and uses of weak dependencies, you'll have to walk the package code looking for the uses of the `::` operator. See how R CMD check walks the package code in functions tools:::.check_packages_used and codetools::checkUsage. A less-well-behaved package can always load a namespace during runtime and choose the functions to call depending on the phase of the moon or weather on Jupiter. For these, like for the halting problem, there's no general solution: the package could be written to say, "if Leonard's function says I'm about to call foo::bar, I won't do it, otherwise I will". -- Best regards, Ivan [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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] [External] converting MATLAB -> R | element-wise operation
I decided to do a direct comparison of transpose and sweep. library(microbenchmark) NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix lambda <- c(2, 3, 4) # Example vector colNN <- t(NN) microbenchmark( sweep = sweep(NN, 2, lambda, "/"), transpose = t(t(NN)/lambda), colNN = colNN/lambda ) Unit: nanoseconds expr minlq mean median uq max neval cld sweep 13817 14145 15115.06 14350 14657.5 75932 100 a transpose 1845 1927 2151.68 2132 2214.0 7093 100 b colNN82 123 141.86123 164.0 492 100 c Note that transpose is much faster than sweep because it is doing less work, I believe essentially just changing the order of indexing. Using the natural sequencing for column-ordered matrices is much much faster. > On Feb 28, 2024, at 18:43, peter dalgaard wrote: > >> rbind(1:3,4:6)/t(matrix(c(2,3,4), 3,2)) __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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] R 4.3.3 is released
The build system rolled up R-4.3.3.tar.gz and .xz (codename "Angel Food Cake")
this morning.
This is a minor update, intended as the wrap-up release for the 4.3.x series.
This also marks the 6th anniversary of R-1.0.0. (2000-02-29)
The list below details the changes in this release.
You can get the source code from
https://cran.r-project.org/src/base/R-4/R-4.3.3.tar.gz
https://cran.r-project.org/src/base/R-4/R-4.3.3.tar.xz
or wait for it to be mirrored at a CRAN site nearer to you.
Binaries for various platforms will appear in due course.
For the R Core Team,
Peter Dalgaard
These are the checksums (md5 and SHA-256) for the freshly created files, in
case you wish
to check that they are uncorrupted:
MD5 (AUTHORS) = 320967884b547734d6279dedbc739dd4
MD5 (COPYING) = eb723b61539feef013de476e68b5c50a
MD5 (COPYING.LIB) = a6f89e2100d9b6cdffcea4f398e37343
MD5 (FAQ) = 97a3ddc25aab502a70bfb1a79ab6f862
MD5 (INSTALL) = 7893f754308ca31f1ccf62055090ad7b
MD5 (NEWS) = 0aa4babeb5349c3abc6fb02700e8cf53
MD5 (NEWS.0) = bfcd7c147251b5474d96848c6f57e5a8
MD5 (NEWS.1) = 4108ab429e768e29b1c3b418c224246e
MD5 (NEWS.2) = b38d94569700664205a76a7de836ba83
MD5 (NEWS.3) = e55ed2c8a547b827b46e08eb7137ba23
MD5 (R-latest.tar.gz) = 4de100b35e3614c19df5e95e483cc3c3
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MD5 (README) = f468f281c919665e276a1b691decbbe6
MD5 (RESOURCES) = a79b9b338cab09bd665f6b62ac6f455b
MD5 (THANKS) = 45b6d2e88a6ecb5b24fa33a781351cd5
MD5 (VERSION-INFO.dcf) = becc8fce6e97db1703f9ca6d80e36c9d
MD5 (R-4/R-4.3.3.tar.gz) = 4de100b35e3614c19df5e95e483cc3c3
MD5 (R-4/R-4.3.3.tar.xz) = 5602f5996107c346dba12a16e866d2e2
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R-latest.tar.gz
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8b7d3856100220f4555d4d57140829f2e81c27eccec5b441f5dce616e9ec9061 RESOURCES
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R-4/R-4.3.3.tar.gz
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R-4/R-4.3.3.tar.xz
This is the relevant part of the NEWS file
CHANGES IN R 4.3.3:
NEW FEATURES:
* iconv() now fixes up variant encoding names such as "utf8"
case-insensitively.
DEPRECATED AND DEFUNCT:
* The legacy encoding = "MacRoman" is deprecated in pdf() and
postscript(): support was incomplete in earlier versions of R.
BUG FIXES:
* Arguments are now properly forwarded to methods on S4 generics
with ... in the middle of their formal arguments. This was broken
for the case when a method introduced an argument but did not
include ... in its own formals. Thanks to Herv'e Pag`es for the
report PR#18538.
* Some invalid file arguments to pictex(), postscript() and xfig()
opened a file called NA rather than throw an error. These
included postscript(NULL) (which some people expected to work
like pdf(NULL)).
* Passing filename = NA to svg(), cairo_pdf(), cairo_ps() or the
Cairo-based bitmap devices opened a file called NA: it now throws
an error.
* quartz(file = NA) opened a file called NA, including when used as
a Quartz-based bitmap device. It now gives an error.
* rank() now works, fixing PR#18617, thanks to Ilia
Kats.
* seq.int() did not adequately check its length.out argument.
* match(, .) is correct again for differing time zones,
ditto for "POSIXlt", fixing PR#18618 reported by Bastian Klein.
* drop.terms(*, dropx = <0-length>) now works, fixing PR#18563 as
proposed by Mikael Jagan.
* drop.terms(*) keeps + offset(.) terms when it should, PR#18565,
and drop.terms() no longer makes up a response, PR#18566, fixing
both bugs thanks to Mikael Jagan.
* getS3method("t", "test") no longer finds the t.test() function,
fixing PR#18627.
* pdf() and postscript() support for the documented Adobe encodings
"Greek" and "Cyrilllic" was missing (although the corresponding
Windows
Re: [R] Initializing vector and matrices
Thanks to all. Great ideas. I found Eik Vettorazzi's suggesstion easy to
implrment:
ebarm<-vbarm<-NULL
...
if (is.null(ebarm)) ebarm<-ame.00$ei/k else ebarm<-ebarm+ame.00$ei/k
if (is.null(vbarm)) vbarm<-ame.00$vi/k else vbarm<-vbarm+ame.00$vi/k
...
Steven Yen
On 2/29/2024 10:31 PM, Ebert,Timothy Aaron wrote:
You could declare a matrix much larger than you intend to use. This works with
a few megabytes of data. It is not very efficient, so scaling up may become a
problem.
m22 <- matrix(NA, 1:60, ncol=6)
It does not work to add a new column to the matrix, as in you get an error if
you try m22[ , 7] but convert to data frame and add a column
m23 <- data.frame(m22)
m23$x7 <- 12
The only penalty that I know of to having unused space in a matrix is the
amount of memory it takes. One side effect is that your program may have a
mistake that you would normally catch with a subscript out of bounds error but
with the extra space it now runs without errors.
Tim
-Original Message-
From: R-help On Behalf Of Richard O'Keefe
Sent: Thursday, February 29, 2024 5:29 AM
To: Steven Yen
Cc: R-help Mailing List
Subject: Re: [R] Initializing vector and matrices
[External Email]
x <- numeric(0)
for (...) {
x[length(x)+1] <- ...
}
works.
You can build a matrix by building a vector one element at a time this way, and
then reshaping it at the end. That only works if you don't need it to be a
matrix at all times.
Another approach is to build a list of rows. It's not a matrix, but a list of
rows can be a *ragged* matrix with rows of varying length.
On Wed, 28 Feb 2024 at 21:57, Steven Yen wrote:
Is there as way to initialize a vector (matrix) with an unknown length
(dimension)? NULL does not seem to work. The lines below work with a
vector of length 4 and a matrix of 4 x 4. What if I do not know
initially the length/dimension of the vector/matrix?
All I want is to add up (accumulate) the vector and matrix as I go
through the loop.
Or, are there other ways to accumulate such vectors and matrices?
> x<-rep(0,4) # this works but I like to leave the length open >
for (i in 1:3){
+ x1<-1:4
+ x<-x+x1
+ }
> x
[1] 3 6 9 12
> y = 0*matrix(1:16, nrow = 4, ncol = 4); # this works but I like to
leave the dimension open
[,1] [,2] [,3] [,4]
[1,]0000
[2,]0000
[3,]0000
[4,]0000
> for (i in 1:3){
+ y1<-matrix(17:32, nrow = 4, ncol = 4)
+ y<-y+y1
+ }
> y
[,1] [,2] [,3] [,4]
[1,] 51 63 75 87
[2,] 54 66 78 90
[3,] 57 69 81 93
[4,] 60 72 84 96
>
__
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.ethz.ch%2Fmailman%2Flistinfo%2Fr-help&data=05%7C02%7Ctebert%40ufl.edu
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PtWjcDOnwO7PArVOSdgYbpz8ksjDPK%2Bn9ySyhwQC0gE%3D&reserved=0
PLEASE do read the posting guide
http://www.r/
-project.org%2Fposting-guide.html&data=05%7C02%7Ctebert%40ufl.edu%7Cdb
ccaccf29674b10b17308dc39114d38%7C0d4da0f84a314d76ace60a62331e1b84%7C0%
7C0%7C638447993707438911%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiL
CJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=Igb16
CBYgG21HLEDH4I4gfjjFBa3KjDFK8yEZUmBo8s%3D&reserved=0
and provide commented, minimal, self-contained, reproducible code.
__
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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 -- To UNSUBSCRIBE and more, see
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] Initializing vector and matrices
You could declare a matrix much larger than you intend to use. This works with
a few megabytes of data. It is not very efficient, so scaling up may become a
problem.
m22 <- matrix(NA, 1:60, ncol=6)
It does not work to add a new column to the matrix, as in you get an error if
you try m22[ , 7] but convert to data frame and add a column
m23 <- data.frame(m22)
m23$x7 <- 12
The only penalty that I know of to having unused space in a matrix is the
amount of memory it takes. One side effect is that your program may have a
mistake that you would normally catch with a subscript out of bounds error but
with the extra space it now runs without errors.
Tim
-Original Message-
From: R-help On Behalf Of Richard O'Keefe
Sent: Thursday, February 29, 2024 5:29 AM
To: Steven Yen
Cc: R-help Mailing List
Subject: Re: [R] Initializing vector and matrices
[External Email]
x <- numeric(0)
for (...) {
x[length(x)+1] <- ...
}
works.
You can build a matrix by building a vector one element at a time this way, and
then reshaping it at the end. That only works if you don't need it to be a
matrix at all times.
Another approach is to build a list of rows. It's not a matrix, but a list of
rows can be a *ragged* matrix with rows of varying length.
On Wed, 28 Feb 2024 at 21:57, Steven Yen wrote:
>
> Is there as way to initialize a vector (matrix) with an unknown length
> (dimension)? NULL does not seem to work. The lines below work with a
> vector of length 4 and a matrix of 4 x 4. What if I do not know
> initially the length/dimension of the vector/matrix?
>
> All I want is to add up (accumulate) the vector and matrix as I go
> through the loop.
>
> Or, are there other ways to accumulate such vectors and matrices?
>
> > x<-rep(0,4) # this works but I like to leave the length open >
> for (i in 1:3){
> + x1<-1:4
> + x<-x+x1
> + }
> > x
> [1] 3 6 9 12
>
> > y = 0*matrix(1:16, nrow = 4, ncol = 4); # this works but I like to
> leave the dimension open
> [,1] [,2] [,3] [,4]
> [1,]0000
> [2,]0000
> [3,]0000
> [4,]0000
> > for (i in 1:3){
> + y1<-matrix(17:32, nrow = 4, ncol = 4)
> + y<-y+y1
> + }
> > y
> [,1] [,2] [,3] [,4]
> [1,] 51 63 75 87
> [2,] 54 66 78 90
> [3,] 57 69 81 93
> [4,] 60 72 84 96
> >
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat/
> .ethz.ch%2Fmailman%2Flistinfo%2Fr-help&data=05%7C02%7Ctebert%40ufl.edu
> %7Cdbccaccf29674b10b17308dc39114d38%7C0d4da0f84a314d76ace60a62331e1b84
> %7C0%7C0%7C638447993707432549%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAw
> MDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=
> PtWjcDOnwO7PArVOSdgYbpz8ksjDPK%2Bn9ySyhwQC0gE%3D&reserved=0
> PLEASE do read the posting guide
> http://www.r/
> -project.org%2Fposting-guide.html&data=05%7C02%7Ctebert%40ufl.edu%7Cdb
> ccaccf29674b10b17308dc39114d38%7C0d4da0f84a314d76ace60a62331e1b84%7C0%
> 7C0%7C638447993707438911%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiL
> CJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=Igb16
> CBYgG21HLEDH4I4gfjjFBa3KjDFK8yEZUmBo8s%3D&reserved=0
> and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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 -- To UNSUBSCRIBE and more, see
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] Initializing vector and matrices
x <- numeric(0)
for (...) {
x[length(x)+1] <- ...
}
works.
You can build a matrix by building a vector one element at a time this way,
and then reshaping it at the end. That only works if you don't need it to be
a matrix at all times.
Another approach is to build a list of rows. It's not a matrix, but a list of
rows can be a *ragged* matrix with rows of varying length.
On Wed, 28 Feb 2024 at 21:57, Steven Yen wrote:
>
> Is there as way to initialize a vector (matrix) with an unknown length
> (dimension)? NULL does not seem to work. The lines below work with a
> vector of length 4 and a matrix of 4 x 4. What if I do not know
> initially the length/dimension of the vector/matrix?
>
> All I want is to add up (accumulate) the vector and matrix as I go
> through the loop.
>
> Or, are there other ways to accumulate such vectors and matrices?
>
> > x<-rep(0,4) # this works but I like to leave the length open
> > for (i in 1:3){
> + x1<-1:4
> + x<-x+x1
> + }
> > x
> [1] 3 6 9 12
>
> > y = 0*matrix(1:16, nrow = 4, ncol = 4); # this works but I like to
> leave the dimension open
> [,1] [,2] [,3] [,4]
> [1,]0000
> [2,]0000
> [3,]0000
> [4,]0000
> > for (i in 1:3){
> + y1<-matrix(17:32, nrow = 4, ncol = 4)
> + y<-y+y1
> + }
> > y
> [,1] [,2] [,3] [,4]
> [1,] 51 63 75 87
> [2,] 54 66 78 90
> [3,] 57 69 81 93
> [4,] 60 72 84 96
> >
>
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> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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Re: [R] [EXT] Re: Initializing vector and matrices
Dear Steven,
I used "sample" just to generate a non-trivial example, you could insert
your code of generating the real xi at this point :-)
If you want to stick to for-loops for some reasons, something like this
could work
x<-NULL
for (i in 1:5){
xi<-1:5
if (is.null(x)) x<-xi else x<-x+xi
}
cheers
Am 29.02.2024 um 09:23 schrieb Steven Yen:
Hello Eik:
Thanks. I do not need to sample. Essentially, I have a do loop which
produces 24 vectors of length of some length (say k=300) and 24 matrices
of 300x300. Then, I simply need to take the averages of these 24
vectors and matrices:
x=(x1+x2+...+x24)/k
y=(y1+y2+...+y24)/k
I am just looking for ways to do this in a do loop, which requires
initialization (to 0's) of x and y. My struggle is not knowning length
of x until x1 is produced in the first of the loop. Thanks.
Steven
On 2/28/2024 6:22 PM, Eik Vettorazzi wrote:
Hi Steven,
It's not entirely clear what you actually want to achieve in the end.
As soon as you "know" x1, and assuming that the different "xi" do not
differ in length in the real application, you know the length of the
target vector.
Instead of the loop, you can use 'Reduce' without having to initialize
a starting vector.
# generate sample vectors, put them in a list
xi<-lapply(1:5, \(x)sample(5))
# look at xi
xi
# sum over xi
Reduce("+",xi)
this works also for matrices
# generate sample matrices, put them in a list
Xi<-lapply(1:3, \(x)matrix(sample(16), nrow=4))
# look at them
Xi
# sum over Xi
Reduce("+",Xi)
Hope that helps
Eik
Am 28.02.2024 um 09:56 schrieb Steven Yen:
Is there as way to initialize a vector (matrix) with an unknown
length (dimension)? NULL does not seem to work. The lines below work
with a vector of length 4 and a matrix of 4 x 4. What if I do not
know initially the length/dimension of the vector/matrix?
All I want is to add up (accumulate) the vector and matrix as I go
through the loop.
Or, are there other ways to accumulate such vectors and matrices?
> x<-rep(0,4) # this works but I like to leave the length open
> for (i in 1:3){
+ x1<-1:4
+ x<-x+x1
+ }
> x
[1] 3 6 9 12
> y = 0*matrix(1:16, nrow = 4, ncol = 4); # this works but I like to
leave the dimension open
[,1] [,2] [,3] [,4]
[1,] 0 0 0 0
[2,] 0 0 0 0
[3,] 0 0 0 0
[4,] 0 0 0 0
> for (i in 1:3){
+ y1<-matrix(17:32, nrow = 4, ncol = 4)
+ y<-y+y1
+ }
> y
[,1] [,2] [,3] [,4]
[1,] 51 63 75 87
[2,] 54 66 78 90
[3,] 57 69 81 93
[4,] 60 72 84 96
>
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PLEASE do read the posting guide
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--
Eik Vettorazzi
Universitätsklinikum Hamburg-Eppendorf
Institut für Medizinische Biometrie und Epidemiologie
Christoph-Probst-Weg 1
4. Obergeschoss, Raum 04.1.021.1
20246 Hamburg
Telefon: +49 (0) 40 7410 - 58243
Fax: +49 (0) 40 7410 - 57790
Web: www.uke.de/imbe
Webex: https://webteaching-uke.webex.com/meet/e.vettorazzi
--
_
Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts;
Gerichtsstand: Hamburg | www.uke.de
Vorstandsmitglieder: Prof. Dr. Christian Gerloff (Vorsitzender), Joachim Prölß,
Prof. Dr. Blanche Schwappach-Pignataro, Matthias Waldmann (komm.)
_
SAVE PAPER - THINK BEFORE PRINTING
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Re: [R] [EXT] Initializing vector and matrices
Hello Eik:
Thanks. I do not need to sample. Essentially, I have a do loop which
produces 24 vectors of length of some length (say k=300) and 24 matrices
of 300x300. Then, I simply need to take the averages of these 24
vectors and matrices:
x=(x1+x2+...+x24)/k
y=(y1+y2+...+y24)/k
I am just looking for ways to do this in a do loop, which requires
initialization (to 0's) of x and y. My struggle is not knowning length
of x until x1 is produced in the first of the loop. Thanks.
Steven
On 2/28/2024 6:22 PM, Eik Vettorazzi wrote:
Hi Steven,
It's not entirely clear what you actually want to achieve in the end.
As soon as you "know" x1, and assuming that the different "xi" do not
differ in length in the real application, you know the length of the
target vector.
Instead of the loop, you can use 'Reduce' without having to initialize
a starting vector.
# generate sample vectors, put them in a list
xi<-lapply(1:5, \(x)sample(5))
# look at xi
xi
# sum over xi
Reduce("+",xi)
this works also for matrices
# generate sample matrices, put them in a list
Xi<-lapply(1:3, \(x)matrix(sample(16), nrow=4))
# look at them
Xi
# sum over Xi
Reduce("+",Xi)
Hope that helps
Eik
Am 28.02.2024 um 09:56 schrieb Steven Yen:
Is there as way to initialize a vector (matrix) with an unknown
length (dimension)? NULL does not seem to work. The lines below work
with a vector of length 4 and a matrix of 4 x 4. What if I do not
know initially the length/dimension of the vector/matrix?
All I want is to add up (accumulate) the vector and matrix as I go
through the loop.
Or, are there other ways to accumulate such vectors and matrices?
> x<-rep(0,4) # this works but I like to leave the length open
> for (i in 1:3){
+ x1<-1:4
+ x<-x+x1
+ }
> x
[1] 3 6 9 12
> y = 0*matrix(1:16, nrow = 4, ncol = 4); # this works but I like to
leave the dimension open
[,1] [,2] [,3] [,4]
[1,] 0 0 0 0
[2,] 0 0 0 0
[3,] 0 0 0 0
[4,] 0 0 0 0
> for (i in 1:3){
+ y1<-matrix(17:32, nrow = 4, ncol = 4)
+ y<-y+y1
+ }
> y
[,1] [,2] [,3] [,4]
[1,] 51 63 75 87
[2,] 54 66 78 90
[3,] 57 69 81 93
[4,] 60 72 84 96
>
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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 -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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