Re: [Rd] On implementing zero-overhead code reuse
Hi Kynn,
Thanks for expanding.
I wrote a function like yours when I first started using R. It's
basically the same up to your "new.env()" line, I don't do anything
with environmentns. I just called my function "mysource" and it's
essentially a "source with path". That allows me to find code I reuse
in standard locations.
I don't know why R does not have built-in support for such a thing.
You can get it in C compilers with CPATH, and as you say in Perl with
PERL5LIB, in Python, etc. Obviously when I use my "mysource" I have to
remember that my code is now not portable without copying over some
files from other locations in my home directory. However, as a
beginner I find this tool to be indispensable, as R lacks several
functions which I use regularly, and I'm not necessarily ready to
confront the challenges associated with creating a package.
However, I guess since we can get your functionality pretty easily
using some lines in .Rprofile, that makes it seem less important to
have it built-in. In fact, if everyone has to implement their own
version of your "import", this almost guarantees that the function
won't appear by accident in any public code. My choice of name
"mysource" was meant to serve as a more visible lexical reminder that
the function is not meant to be seen by the public.
By the way, why do you do the stuff with environments in your "import"
function?
Dirk's take is interesting. I don't use version control for my
personal projects, just backing-up. Obviously not all R users are
interested in becoming package maintainers, in fact I think it would
clutter things a bit if this were the case. Or maybe it would be good
to have everyone publish their personal utility functions, who knows?
Anyway I appreciate Dirk's arguments, but I'm also a bit surprised
that Kynn and I seem to be the only ones who have written personal
functions to do what Kynn calls "zero-overhead code reuse". FWIW.
Cheers,
Frederick
On Sun, Oct 02, 2016 at 08:01:58PM -0400, Kynn Jones wrote:
> Hi Frederick,
>
> I described what I meant in the post I sent to R-help
> (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html),
> but in brief, by "zero overhead" I mean that the only thing needed for
> library code to be accessible to client code is for it to be located
> in a designated directory. No additional meta-files, packaging/compiling,
> etc. are required.
>
> Best,
>
> G.
>
> On Sun, Oct 2, 2016 at 7:09 PM, wrote:
> > Hi Kynn,
> >
> > Do you mind defining the term "zero-overhead model of code reuse"?
> >
> > I think I understand what you're getting at, but not sure.
> >
> > Thank you,
> >
> > Frederick
> >
> > On Sun, Oct 02, 2016 at 01:29:52PM -0400, Kynn Jones wrote:
> >> I'm looking for a way to approximate the "zero-overhead" model of code
> >> reuse available in languages like Python, Perl, etc.
> >>
> >> I've described this idea in more detail, and the motivation for this
> >> question in an earlier post to R-help
> >> (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html).
> >>
> >> (One of the responses I got advised that I post my question here instead.)
> >>
> >> The best I have so far is to configure my PROJ_R_LIB environment
> >> variable to point to the directory with my shared code, and put a
> >> function like the following in my .Rprofile file:
> >>
> >> import <- function(name){
> >> ## usage:
> >> ## import("foo")
> >> ## foo$bar()
> >> path <- file.path(Sys.getenv("PROJ_R_LIB"),paste0(name,".R"))
> >> if(!file.exists(path)) stop('file "',path,'" does not exist')
> >> mod <- new.env()
> >> source(path,local=mod)
> >> list2env(setNames(list(mod),list(name)),envir=parent.frame())
> >> invisible()
> >> }
> >>
> >> (NB: the idea above is an elaboration of the one I showed in my first
> >> post.)
> >>
> >> But this is very much of an R noob's solution. I figure there may
> >> already be more solid ways to achieve "zero-overhead" code reuse.
> >>
> >> I would appreciate any suggestions/critiques/pointers/comments.
> >>
> >> TIA!
> >>
> >> kj
> >>
> >> __
> >> R-devel@r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-devel
> >>
>
On Sun, Oct 02, 2016 at 08:05:53PM -0400, Kynn Jones wrote:
> On Sun, Oct 2, 2016 at 8:01 PM, Kynn Jones wrote:
> > Hi Frederick,
> >
> > I described what I meant in the post I sent to R-help
> > (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html),
> > but in brief, by "zero overhead" I mean that the only thing needed for
> > library code to be accessible to client code is for it to be located
> > in designed directory. No additional meta-files, packaging/compiling,
>
>
> Sorry, I meant to write "designated".
>
> > etc. are required.
>
On Sun, Oct 02, 2016 at 07:18:41PM -0500, Dirk Eddelbuettel wrote:
>
> Kynn,
>
> How much homework have you done researching any othe
Re: [Rd] On implementing zero-overhead code reuse
Have a look at the CRAN modules package and the import package.
On Sun, Oct 2, 2016 at 1:29 PM, Kynn Jones wrote:
> I'm looking for a way to approximate the "zero-overhead" model of code
> reuse available in languages like Python, Perl, etc.
>
> I've described this idea in more detail, and the motivation for this
> question in an earlier post to R-help
> (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html).
>
> (One of the responses I got advised that I post my question here instead.)
>
> The best I have so far is to configure my PROJ_R_LIB environment
> variable to point to the directory with my shared code, and put a
> function like the following in my .Rprofile file:
>
> import <- function(name){
> ## usage:
> ## import("foo")
> ## foo$bar()
> path <- file.path(Sys.getenv("PROJ_R_LIB"),paste0(name,".R"))
> if(!file.exists(path)) stop('file "',path,'" does not exist')
> mod <- new.env()
> source(path,local=mod)
> list2env(setNames(list(mod),list(name)),envir=parent.frame())
> invisible()
> }
>
> (NB: the idea above is an elaboration of the one I showed in my first post.)
>
> But this is very much of an R noob's solution. I figure there may
> already be more solid ways to achieve "zero-overhead" code reuse.
>
> I would appreciate any suggestions/critiques/pointers/comments.
>
> TIA!
>
> kj
>
> __
> R-devel@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
--
Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com
__
R-devel@r-project.org mailing list
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Re: [Rd] On implementing zero-overhead code reuse
On Mon, Oct 3, 2016 at 10:18 AM, wrote:
> Hi Kynn,
>
> Thanks for expanding.
>
> I wrote a function like yours when I first started using R. It's
> basically the same up to your "new.env()" line, I don't do anything
> with environmentns. I just called my function "mysource" and it's
> essentially a "source with path". That allows me to find code I reuse
> in standard locations.
>
> I don't know why R does not have built-in support for such a thing.
> You can get it in C compilers with CPATH, and as you say in Perl with
> PERL5LIB, in Python, etc. Obviously when I use my "mysource" I have to
> remember that my code is now not portable without copying over some
> files from other locations in my home directory. However, as a
> beginner I find this tool to be indispensable, as R lacks several
> functions which I use regularly, and I'm not necessarily ready to
> confront the challenges associated with creating a package.
>
I can pretty much guarantee that when you finally confront the "challenge"
of making your own package you'll realize (1) it is pretty easy if the
intention is only to use it yourself (and perhaps a couple of
collaborators) - by easy I mean I can make a package in 5m max. (2) you'll
ask yourself "why didn't I do this earlier?". I still get that feeling
now, when I have done it many times for internal use. Almost every time I
think I should have made an internal package earlier in the process.
Of course, all of this is hard to see when you're standing in the middle of
your work.
Best,
Kasper
> However, I guess since we can get your functionality pretty easily
> using some lines in .Rprofile, that makes it seem less important to
> have it built-in. In fact, if everyone has to implement their own
> version of your "import", this almost guarantees that the function
> won't appear by accident in any public code. My choice of name
> "mysource" was meant to serve as a more visible lexical reminder that
> the function is not meant to be seen by the public.
>
> By the way, why do you do the stuff with environments in your "import"
> function?
>
> Dirk's take is interesting. I don't use version control for my
> personal projects, just backing-up. Obviously not all R users are
> interested in becoming package maintainers, in fact I think it would
> clutter things a bit if this were the case. Or maybe it would be good
> to have everyone publish their personal utility functions, who knows?
> Anyway I appreciate Dirk's arguments, but I'm also a bit surprised
> that Kynn and I seem to be the only ones who have written personal
> functions to do what Kynn calls "zero-overhead code reuse". FWIW.
>
> Cheers,
>
> Frederick
>
> On Sun, Oct 02, 2016 at 08:01:58PM -0400, Kynn Jones wrote:
> > Hi Frederick,
> >
> > I described what I meant in the post I sent to R-help
> > (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html),
> > but in brief, by "zero overhead" I mean that the only thing needed for
> > library code to be accessible to client code is for it to be located
> > in a designated directory. No additional meta-files,
> packaging/compiling,
> > etc. are required.
> >
> > Best,
> >
> > G.
> >
> > On Sun, Oct 2, 2016 at 7:09 PM, wrote:
> > > Hi Kynn,
> > >
> > > Do you mind defining the term "zero-overhead model of code reuse"?
> > >
> > > I think I understand what you're getting at, but not sure.
> > >
> > > Thank you,
> > >
> > > Frederick
> > >
> > > On Sun, Oct 02, 2016 at 01:29:52PM -0400, Kynn Jones wrote:
> > >> I'm looking for a way to approximate the "zero-overhead" model of code
> > >> reuse available in languages like Python, Perl, etc.
> > >>
> > >> I've described this idea in more detail, and the motivation for this
> > >> question in an earlier post to R-help
> > >> (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html).
> > >>
> > >> (One of the responses I got advised that I post my question here
> instead.)
> > >>
> > >> The best I have so far is to configure my PROJ_R_LIB environment
> > >> variable to point to the directory with my shared code, and put a
> > >> function like the following in my .Rprofile file:
> > >>
> > >> import <- function(name){
> > >> ## usage:
> > >> ## import("foo")
> > >> ## foo$bar()
> > >> path <- file.path(Sys.getenv("PROJ_R_LIB"),paste0(name,".R"))
> > >> if(!file.exists(path)) stop('file "',path,'" does not exist')
> > >> mod <- new.env()
> > >> source(path,local=mod)
> > >> list2env(setNames(list(mod),list(name)),envir=parent.frame())
> > >> invisible()
> > >> }
> > >>
> > >> (NB: the idea above is an elaboration of the one I showed in my first
> post.)
> > >>
> > >> But this is very much of an R noob's solution. I figure there may
> > >> already be more solid ways to achieve "zero-overhead" code reuse.
> > >>
> > >> I would appreciate any suggestions/critiques/pointers/comments.
> > >>
> > >> TIA!
> > >>
> > >> kj
> > >>
> > >> __
Re: [Rd] grep
On 02/10/2016 17:54, Pi wrote: Hello. It would be great if the grep function in R had the option to use the -m parameter as the linux command does. I guess you mean the non-standard flag of the GNU version of grep (probably but not necessarily as used by Linux). That the POSIX standard for grep does not have this (nor any other commonly used implementation I am aware of) indicates that your enthusiasm for this is not shared by grep experts. That would allow to stop a grep search as soon as something is found. It would make many operations much faster. Those who would have to do the work to implement this will not be taking your word for that, but would expect convincing examples of real problems where it was so and grep was the bottleneck. Your 'case' seems to be for a shortcut for any(grepl()) along the lines of anyDuplicated(). [[alternative HTML version deleted]] This is a non-HTML list, as the posting guide told you. And using a real name adds credibility. -- Brian D. Ripley, rip...@stats.ox.ac.uk Emeritus Professor of Applied Statistics, University of Oxford __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] On implementing zero-overhead code reuse
Thank you all for your comments and suggestions.
@Frederik, my reason for mucking with environments is that I want to
minimize the number of names that import adds to my current
environment. For instance, if module foo defines a function bar, I
want my client code to look like this:
import("foo")
foo$bar(1,2,3)
rather than
import("foo")
bar(1,2,3)
(Just a personal preference.)
@Dirk, @Kasper, as I see it, the benefit of scripting languages like
Python, Perl, etc., is that they allow very quick development, with
minimal up-front cost. Their main strength is precisely that one can,
without much difficulty, *immediately* start *programming
productively*, without having to worry at all about (to quote Dirk)
"repositories. And package management. And version control (at the
package level). And ... byte compilation. And associated
documentation. And unit tests. And continuous integration."
Of course, *eventually*, and for a fraction of one's total code base
(in my case, a *very small* fraction), one will want to worry about
all those things, but I see no point in burdening *all* my code with
all those concerns from the start. Again, please keep in mind that
those concerns come into play for at most 5% of the code I write.
Also, I'd like to point out that the Python, Perl, etc. communities
are no less committed to all the concerns that Dirk listed (version
control, package management, documentation, testing, etc.) than the R
community is. And yet, Python, Perl, etc. support the "zero-overhead"
model of code reuse. There's no contradiction here. Support for
"zero-overhead" code reuse does not preclude forms of code reuse with
more overhead.
One benefit the zero-overhead model is that the concerns of
documentation, testing, etc. can be addressed with varying degrees of
thoroughness, depending on the situation's demands. (For example,
documentation that would be perfectly adequate for me as the author of
a function would not be adequate for the general user.)
This means that the transition from writing private code to writing
code that can be shared with the world can be made much more
gradually, according to the programmer's needs and means.
Currently, in the R world, the choice for programmers is much starker:
either stay writing little scripts that one sources from an
interactive session, or learn to implement packages. There's too
little in-between.
Of course, from the point of view of someone who has already written
several packages, the barrier to writing a package may seem too small
to fret over, but adopting the expert's perspective is likely to
result in excluding the non-experts.
Best, kj
On Mon, Oct 3, 2016 at 12:06 PM, Kasper Daniel Hansen
wrote:
>
>
> On Mon, Oct 3, 2016 at 10:18 AM, wrote:
>>
>> Hi Kynn,
>>
>> Thanks for expanding.
>>
>> I wrote a function like yours when I first started using R. It's
>> basically the same up to your "new.env()" line, I don't do anything
>> with environmentns. I just called my function "mysource" and it's
>> essentially a "source with path". That allows me to find code I reuse
>> in standard locations.
>>
>> I don't know why R does not have built-in support for such a thing.
>> You can get it in C compilers with CPATH, and as you say in Perl with
>> PERL5LIB, in Python, etc. Obviously when I use my "mysource" I have to
>> remember that my code is now not portable without copying over some
>> files from other locations in my home directory. However, as a
>> beginner I find this tool to be indispensable, as R lacks several
>> functions which I use regularly, and I'm not necessarily ready to
>> confront the challenges associated with creating a package.
>
>
> I can pretty much guarantee that when you finally confront the "challenge"
> of making your own package you'll realize (1) it is pretty easy if the
> intention is only to use it yourself (and perhaps a couple of collaborators)
> - by easy I mean I can make a package in 5m max. (2) you'll ask yourself
> "why didn't I do this earlier?". I still get that feeling now, when I have
> done it many times for internal use. Almost every time I think I should
> have made an internal package earlier in the process.
>
> Of course, all of this is hard to see when you're standing in the middle of
> your work.
>
> Best,
> Kasper
>
>
>
>
>
>>
>> However, I guess since we can get your functionality pretty easily
>> using some lines in .Rprofile, that makes it seem less important to
>> have it built-in. In fact, if everyone has to implement their own
>> version of your "import", this almost guarantees that the function
>> won't appear by accident in any public code. My choice of name
>> "mysource" was meant to serve as a more visible lexical reminder that
>> the function is not meant to be seen by the public.
>>
>> By the way, why do you do the stuff with environments in your "import"
>> function?
>>
>> Dirk's take is interesting. I don't use version control for my
>> personal projects, just bac
Re: [Rd] On implementing zero-overhead code reuse
Kynn, You appear confused by the meaning of the word "optional". All the things I listed for packages are additional features you _may_ use, not onces that are imposed on you so that they _must_ be used. Lastly, I forgot to mention NAMESPACE support. Which gives pretty much exactly what you outlined at the beginning of your post as a desiderata. But it seems you know full well what you need, so by all means do charge full speed ahead. But before I close allow me to reiterate that you are somewhat ill-informed. Packages do not impose anything. Asking to be included in a high-quality repository such as CRAN does. For local and personal packages you can be precisely as ad-hoc as you are in sourced files. Yet you still have access to the very framework that gives you _options_ for more structure. Dirk -- http://dirk.eddelbuettel.com | @eddelbuettel | e...@debian.org __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] On implementing zero-overhead code reuse
On 10/03/2016 01:51 PM, Kynn Jones wrote:
Thank you all for your comments and suggestions.
@Frederik, my reason for mucking with environments is that I want to
minimize the number of names that import adds to my current
environment. For instance, if module foo defines a function bar, I
want my client code to look like this:
import("foo")
foo$bar(1,2,3)
rather than
import("foo")
bar(1,2,3)
(Just a personal preference.)
@Dirk, @Kasper, as I see it, the benefit of scripting languages like
Python, Perl, etc., is that they allow very quick development, with
minimal up-front cost. Their main strength is precisely that one can,
without much difficulty, *immediately* start *programming
productively*, without having to worry at all about (to quote Dirk)
"repositories. And package management. And version control (at the
package level). And ... byte compilation. And associated
documentation. And unit tests. And continuous integration."
Of course, *eventually*, and for a fraction of one's total code base
(in my case, a *very small* fraction), one will want to worry about
all those things, but I see no point in burdening *all* my code with
all those concerns from the start. Again, please keep in mind that
those concerns come into play for at most 5% of the code I write.
Also, I'd like to point out that the Python, Perl, etc. communities
are no less committed to all the concerns that Dirk listed (version
control, package management, documentation, testing, etc.) than the R
community is. And yet, Python, Perl, etc. support the "zero-overhead"
model of code reuse. There's no contradiction here. Support for
"zero-overhead" code reuse does not preclude forms of code reuse with
more overhead.
One benefit the zero-overhead model is that the concerns of
documentation, testing, etc. can be addressed with varying degrees of
thoroughness, depending on the situation's demands. (For example,
documentation that would be perfectly adequate for me as the author of
a function would not be adequate for the general user.)
This means that the transition from writing private code to writing
code that can be shared with the world can be made much more
gradually, according to the programmer's needs and means.
Currently, in the R world, the choice for programmers is much starker:
either stay writing little scripts that one sources from an
interactive session, or learn to implement packages. There's too
little in-between.
I know it's flogging the same horse, but for the non-expert I create and
attach a complete package
devtools::create("myutils")
library(myutils)
Of course it doesn't do anything, so I write my code by editing a plain
text file myutils/R/foo.R to contain
foo = function() "hello wirld"
then return to my still-running R session and install the updated
package and use my new function
devtools::install("myutils")
foo()
myutils::foo() # same, but belt-and-suspenders
I notice my typo, update the file, and use the updated package
devtools::install("myutils")
foo()
The transition from here to a robust package can be gradual, updating
the DESCRIPTION file, adding roxygen2 documentation, unit tests, using
version control, etc... in a completely incremental way. At the end of
it all, I'll still install and use my package with
devtools::install("myutils")
foo()
maybe graduating to
devtools::install_github("mtmorgan/myutils")
library(myutils)
foo()
when it's time to share my work with the wirld.
Martin
Of course, from the point of view of someone who has already written
several packages, the barrier to writing a package may seem too small
to fret over, but adopting the expert's perspective is likely to
result in excluding the non-experts.
Best, kj
On Mon, Oct 3, 2016 at 12:06 PM, Kasper Daniel Hansen
wrote:
On Mon, Oct 3, 2016 at 10:18 AM, wrote:
Hi Kynn,
Thanks for expanding.
I wrote a function like yours when I first started using R. It's
basically the same up to your "new.env()" line, I don't do anything
with environmentns. I just called my function "mysource" and it's
essentially a "source with path". That allows me to find code I reuse
in standard locations.
I don't know why R does not have built-in support for such a thing.
You can get it in C compilers with CPATH, and as you say in Perl with
PERL5LIB, in Python, etc. Obviously when I use my "mysource" I have to
remember that my code is now not portable without copying over some
files from other locations in my home directory. However, as a
beginner I find this tool to be indispensable, as R lacks several
functions which I use regularly, and I'm not necessarily ready to
confront the challenges associated with creating a package.
I can pretty much guarantee that when you finally confront the "challenge"
of making your own package you'll realize (1) it is pretty easy if the
intention is only to use it yourself (and perhaps a couple of collaborators)
- by easy I mean I can make a pac
Re: [Rd] On implementing zero-overhead code reuse
Martin, thanks for that example. It's definitely eye-opening, and very good to know. The installation business, however, is still a killer for me. Of course, it's a trivial step in a simple example like the one you showed. But consider this scenario: suppose I perform an analysis that I may publish in the future, so I commit the project's state at the time of the analysis, and tag the commit with the KEEPER tag. Several months later, I want to repeat that exact analysis for some whatever reason. If the code for the analysis was in Python (say), all I need to do is this (at the Unix command line): % git checkout KEEPER % python src/python/go_to_town.py ...knowing that the `git checkout KEEPER` command, *all by itself*, has put the working directory in the state I want it to be before I re-do the analysis. AFAICT, if the code for the analysis was in R, then `git checkout`, by itself, would *not* put the working directory in the desired state. I still need to re-install all the R libraries in the repo. And I better not forget to do this re-installation, otherwise I will end up running code different from the one I thought I was running. (I find this prospect horrifying, for some reason.) A similar need to re-install stuff would arise whenever I update the repo. Please correct me if I'm wrong. __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
[Rd] suggested addition to model.matrix
Hello, All:
What's the simplest way to convert a data.frame into a model.matrix?
One way is given by the following example, modified from the
examples in help(model.matrix):
dd <- data.frame(a = gl(3,4), b = gl(4,1,12))
ab <- model.matrix(~ a + b, dd)
ab0 <- model.matrix(~., dd)
all.equal(ab, ab0)
What do you think about replacing "model.matrix(~ a + b, dd)" in
the current help(model.matrix) with this 3-line expansion?
I suggest this, because I spent a few hours today trying to
convert a data.frame into a model.matrix before finding this.
Also, what do you think about adding something like the following
to the stats package:
model.matrix.data.frame <- function(object, ...){
model.matrix(~., object, ...)
}
And then extend the above example as follows:
ab. <- model.matrix(dd)
all.equal(ab, ab.)
Thanks,
Spencer Graves
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Re: [Rd] suggested addition to model.matrix
Dear Spencer,
I don't think that the problem of "converting a data frame into a model matrix"
is well-defined, because there isn't a unique mapping from one to the other.
In your example, you build the model matrix for the additive formula ~ a + b
from the data frame matrix containing a and b, using "treatment" contrasts, but
there are other possible formulas (e.g., ~ a*b) and contrasts [e.g.,
model.matrix(~ a + b, dd, contrasts=list(a=contr.sum, b=contr.helmert)].
So I think that the current approach is sensible -- to require both a data
frame and a formula.
Best,
John
> -Original Message-
> From: R-devel [mailto:r-devel-boun...@r-project.org] On Behalf Of Spencer
> Graves
> Sent: October 3, 2016 7:59 PM
> To: r-devel@r-project.org
> Subject: [Rd] suggested addition to model.matrix
>
> Hello, All:
>
>
>What's the simplest way to convert a data.frame into a model.matrix?
>
>
>One way is given by the following example, modified from the examples
> in
> help(model.matrix):
>
>
> dd <- data.frame(a = gl(3,4), b = gl(4,1,12))
> ab <- model.matrix(~ a + b, dd)
> ab0 <- model.matrix(~., dd)
> all.equal(ab, ab0)
>
>
>What do you think about replacing "model.matrix(~ a + b, dd)" in
> the current help(model.matrix) with this 3-line expansion?
>
>
>I suggest this, because I spent a few hours today trying to
> convert a data.frame into a model.matrix before finding this.
>
>
>Also, what do you think about adding something like the following
> to the stats package:
>
>
> model.matrix.data.frame <- function(object, ...){
> model.matrix(~., object, ...)
> }
>
>
>And then extend the above example as follows:
>
> ab. <- model.matrix(dd)
> all.equal(ab, ab.)
>
>
>Thanks,
>Spencer Graves
>
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