Hi all,
I am currently using the code snippet below to minimize a function which I
wasn't able to minimize properly with optim (cliffy surface, constraints,
poles). Obviously this iteration is probably the poorest way of implementing
such a function and it is expectedly slow. I've already written some
vectorized functions, but I'm afraid that I'm missing the "big
picture" in
this case, I don't know how to start. Probably I could build a 3 x
(length(x) * length(y) * length(z)) matrix holding each possible parameter
combinations. With my current step-size and value range that would be
slightly more than 2,000,000 triples, so that should not be a problem. Then
comes the part I'm totally clueless about, that is applying the target
function to each of the triples in the matrix in an efficient way. From the
resulting vector I could then easily take the minimum value index and get
the parameters from the parameter matrix.
Could someone kindly give me a hint how this could be implemented?
Thanks a lot,
Daniel
Code Snippet:
fullEnumeration <- function(par, stepSize = c(.03, .03, .03))
{
res <- Inf
best.x <- -1
best.y <- -1
best.z <- -1
stepx <- stepSize[1]
stepy <- stepSize[2]
stepz <- stepSize[3]
x <- seq(.01, 2, by=stepx)
y <- seq(.01, 2, by=stepy)
z <- seq(.01, 15, by=stepz)
for (i in 1:length(x))
for (j in 1:length(y))
for (k in 1:length(z))
{
# Pass the current best result to the function being minimized to allow
for early termination
newRes <- fun(c(x[i], y[j], z[k]), par, res)
if (!is.na(newRes) && newRes < res)
{
res = newRes
best.x <- x[i]
best.y <- y[j]
best.z <- z[k]
}
}
return (c(
best.x,
best.y,
best.z))
}
fun <- function(x, par, currentBestValue=Inf)
{
x = x[1]
y = x[2]
z = x[3]
TMax <- length(par)
result <- 0
for (myT in 1:TMax)
{
result <- result +
(
((x * z) / (y-1) * (1 - (z / (z + myT))^(y-1) ))
- par[myT]
)^2
# Allow for short-cut evaluation if running in complete enumeration mode
if (is.na(result) || currentBestValue < result)
{
return (Inf)
}
}
return (result)
}
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Daniel Hoppe wrote:> > Hi all, > > I am currently using the code snippet below to minimize a function which I > wasn't able to minimize properly with optim (cliffy surface, constraints, > poles). Obviously this iteration is probably the poorest way of implementing > such a function and it is expectedly slow. I've already written some > vectorized functions, but I'm afraid that I'm missing the "big picture" in > this case, I don't know how to start. Probably I could build a 3 x > (length(x) * length(y) * length(z)) matrix holding each possible parameter > combinations. With my current step-size and value range that would be > slightly more than 2,000,000 triples, so that should not be a problem. Then > comes the part I'm totally clueless about, that is applying the target > function to each of the triples in the matrix in an efficient way. From the > resulting vector I could then easily take the minimum value index and get > the parameters from the parameter matrix. > > Could someone kindly give me a hint how this could be implemented?Without looking closer, I think this is a very nice example for a piece of code that should be implemented in either C or Fortran (on the one hand it is easy to implement, on the other hand its "S interpreted" execution takes quite a long time). OK, quite a few possible improvements of the R code are obvious, but I don't think this is the best point to start ... Nevertheless, the code looks like you are searching on a grid. Are you really sure whether there is no method in optim() which performs better? Uwe Ligges> Thanks a lot, > > Daniel > > Code Snippet: > fullEnumeration <- function(par, stepSize = c(.03, .03, .03)) > { > res <- Inf > > best.x <- -1 > best.y <- -1 > best.z <- -1 > > stepx <- stepSize[1] > stepy <- stepSize[2] > stepz <- stepSize[3] > x <- seq(.01, 2, by=stepx) > y <- seq(.01, 2, by=stepy) > z <- seq(.01, 15, by=stepz) > > for (i in 1:length(x)) > for (j in 1:length(y)) > for (k in 1:length(z)) > { > # Pass the current best result to the function being minimized to allow > for early termination > newRes <- fun(c(x[i], y[j], z[k]), par, res) > if (!is.na(newRes) && newRes < res) > { > res = newRes > best.x <- x[i] > best.y <- y[j] > best.z <- z[k] > } > > } > return (c( > best.x, > best.y, > best.z)) > > } > > fun <- function(x, par, currentBestValue=Inf) > { > x = x[1] > y = x[2] > z = x[3] > TMax <- length(par) > > result <- 0 > for (myT in 1:TMax) > { > result <- result + > ( > ((x * z) / (y-1) * (1 - (z / (z + myT))^(y-1) )) > - par[myT] > )^2 > > # Allow for short-cut evaluation if running in complete enumeration mode > > if (is.na(result) || currentBestValue < result) > { > return (Inf) > } > > } > return (result) > > } > > -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- > r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html > Send "info", "help", or "[un]subscribe" > (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch > _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
hi! i need to submit electronic figures to a journal that satisfy the following requirement: "Colour figures must be supplied in CMYK not RGB colours." can i produce graphs in R that satisfy this? thanks, rafael -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Hi, Well you can produce JPEG, PNG or BMP images directly from R and later you can transform the image to the desired type of file format with another second program (one that provide the feature you need is, ImageMagick). Carlos. -----Mensaje original----- De: owner-r-help at stat.math.ethz.ch [mailto:owner-r-help at stat.math.ethz.ch]En nombre de Rafael A. Irizarry Enviado el: martes, 26 de noviembre de 2002 15:02 Para: r-help at stat.math.ethz.ch Asunto: [R] CMYK hi! i need to submit electronic figures to a journal that satisfy the following requirement: "Colour figures must be supplied in CMYK not RGB colours." can i produce graphs in R that satisfy this? thanks, rafael -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-. -.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._. _._ _____ The information in this email is confidential and it may not be disclosed or used by anyone other than the addressee. If you are not the intended recipient, any disclosure, copying, distribution or any action taken or omitted is prohibited and may be unlawful. Minorplanet cannot accept responsibility for the accuracy or completeness of this email as it has been transmitted over a public network. If you suspect that the email may have been amended, please call the sender. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._