Irucka,
You could assign names to the compare.all list ... for example ...
names(compare.all) <- paste0("Obs", 1:54)
Then, when you create the subset list, justbig, it will have the
appropriate names.
If you just want to see the indices of the successful locations, you could
print
(1:54)[compare.all > 0.7]
Jean
On Fri, Dec 28, 2012 at 11:10 AM, Irucka Embry <iruc...@mail2world.com>wrote:
> Hi Jean, thank-you.
>
> It was my fault on not ccing R-help on the previous correspondence. With
> regards to the FALSE/TRUE or 0/1, you are right that they are the same
> logical identities, but it better suits our original numerical data to
> display 0s and 1s.
>
> I want to thank you for correcting the 2 mistakes, the code works now.
>
> Is it possible to label each of the 54 matrices so that "justbig" lists
> the 31 approved matrices along with their name [whatever the name is for
> the 31 matrices out of the 54 total matrices]? For this code to be fully
> applied to this project we have to know which site locations are successful
> (> 0.7) and which ones are not (< 0.7).
>
> Thank-you Jean.
>
> Irucka
>
>
>
>
> <-----Original Message----->
> >From: Adams, Jean [jvad...@usgs.gov]
> >Sent: 12/21/2012 1:25:24 PM
> >To: iruc...@mail2world.com
> >Cc: r-help@r-project.org
> >Subject: Re: [R] comparison of large data set
> >
> >Irucka,
> >
> >
> >You should cc R-help on all correspondence so that other readers of the
> list can
> >follow the conversation.
> >
> >
> >(1) You say that you need 0s and 1s rather than TRUE/FALSE. Since a 0/1
> matrix
> >and TRUE/FALSE matrix behave exactly the same way in most applications,
> I'm not
> >sure why it would matter which one you had.
> >
> >
> >(2) My mistake. I had not noticed that you were eliminating the case where
> >both the observed and the modeled were FALSE.. I have modified my code to
> give
>
> >the same results as your f2 function.
> >compare.all <- sapply(modeldepth, function(md)
> mean((md==observeddepth)[md |
> >observeddepth]))
> >
> >
> >
> >(3) My mistake again. There should be only single brackets, not double
> brackets.
> >justbig <- modeldepth[compare.all > 0.7]
> >
> >
> >Jean
> >
> >
> >
> >
> >
> >On Fri, Dec 21, 2012 at 11:27 AM, Irucka Embry <iruc...@mail2world.com>
> wrote:
> >
> >Hi Jean Adams, how are you?
> >
> >I want to thank you for your response to my request for assistance.
> >
> >I received some assistance yesterday afternoon and I was able to update
> the code
> >which is posted here:
> >
> http://r.789695.n4.nabble.com/variable-names-in-numeric-list-and-Bayesian-inference-td4653674.html
> .
> >I posted the new code with some new questions that I have with regards to
> the
> >code that I have written. Can you look over that post and suggest any code
> >revisions for those aspects that do not work? Thank-you.
> >
> >The code that you suggested worked well overall, except for 3 aspects of
> it:
> >
> >Here I actually needed the binary 0s and 1s rather than a TRUE/FALSE
> logical matrix
> >
> ># a function to read in the data as a matrix of logicals
> >myreadfun <- function(file) {
> >as.matrix(read.ascii.grid(file)$data)!=0
> >}
> >
> >
> >Here I needed to calculate the f2 probability rather than the mean
> >
> >compare.all <- sapply(modeldepths, function(md) mean(md==observeddepth))
> >
> >> str(compare.all)
> >num [1:54] 0.936 0.94 0.944 0.944 0.945 ...
> >
> >Here most of the entries are greater than 0.7, but it should just be 31
> of the
> >54 that are greater than 0.7
> >
> >> justbig <- modeldepths[[compare.all > 0.7]]
> >
> >Error in modeldepths[[compare.all > 0.7]] :
> >recursive indexing failed at level 2
> >
> >Once again, thank-you for your assistance.
> >
> >Irucka Embry
> >
> >
> ><-----Original Message----->
> >>From: Adams, Jean [jvad...@usgs.gov]
> >>Sent: 12/21/2012 10:32:54 AM
> >>To: iruc...@mail2world.com
> >>Cc: r-help@r-project.org
> >>Subject: Re: [R] comparison of large data set
> >>
> >>Irucka,
> >>
> >>
> >>I did not test this code out on any data, but I think it will work.
> >>
> >>
> >>Jean
> >>
> >>
> >>
> >>
> >># a function to read in the data as a matrix of logicals
> >>myreadfun <- function(file) {
> >>as.matrix(read.ascii.grid(file)$data)!=0
> >>}
> >>
> >>
> >># names of the 54 modeled depth files
> >>modfiles <- paste0("MaxFloodDepth_", 1:54, ".txt")
> >>
> >>
> >># read in the observed and modeled depth files
> >># observeddepth is a matrix
> >>observeddepth <- myreadfun("MaxFloodDepth_Observed.txt")
> >>
> >># modeldepths is a list of matrices
> >>modeldepths <- lapply(filenames, myreadfun)
> >>
> >>
> >># calculate the proportion of matrix elements that agree with the
> observed file
> >># the results is a vector with one number for each modeled depth matrix
> >>compare.all <- sapply(modeldepths, function(md) mean(md==observeddepth))
> >>
> >>
> >># select just those matrices that had a large proportion of agreements
> >># justbig is a list of matrices
> >>justbig <- modeldepths[[compare.all > 0.7]]
> >>
> >
> >>______________________________________________
> >>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.
>
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