Petr,

You can get an example dataset at
http://dl.dropbox.com/u/3845242/torhelp.csv. I'll look at the rest of your
suggestions in the morning, thanks for taking a look at it.

Ben
*
*


On Mon, Apr 2, 2012 at 10:33 PM, Petr PIKAL <petr.pikal@precheza.cz> wrote:

> Hi
>
> There is some mismatch in curly braces in your plotter function but when I
> try to use it I get
>
> >
>
> plotter(10,3,fram=rwb,framvec=rwb$prcnt.char.depth,obj=prcnt.char.depth,form1=
> + post.f.crwn.length~shigo.av,form2=post.f.crwn.length~shigo.av-1,
> + form3=leaf.area~(1/exp(shigo.av*x))*n,type=2,xlm=70,ylm=35)
> Error in sub.plotter(i, fram, framvec, obj, form1, form2, form3, type,  :
>  object 'rwb' not found
>
> You did not mention where we can get rwb so it is quite difficult to
> present any help.
>
> Your function nesting seems to me also a little bit weird as the result
> from nested function is not known to enclosing function.
>
>
> > test<- function (a,b) {
> + g <- a/b
> + sub.test <- function (a, b, d=10000) (e <- a*b*d)
> + c(g, e)
> + }
> >
> > test(2,4)
> Error in test(2, 4) : object 'e' not found
>
> But when you define sub.test outside of test
>
> > sub.test <- function (a, b, d=10000) {
> + e <- a*b*d
> + e
> + }
> >
> > test<- function (a,b) {
> + g <- a/b
> + e <- sub.test(a,b)
> + c(g, e)
> + }
> > test(2,4)
> [1] 5e-01 8e+04
>
> everything works. And it seems to me easier to maintain smaller chunks of
> working code and put them together like a puzzle. Its a behaviour I was
> taught in ancient times when "gosub" was a standard way of Basic
> programming paradigm and much more preferred from "goto".
>
> Best regards
> Petr
>
>
>
>
>
>
>
> >
> > Josh,
> >
> > Many thanks - here's a subset of the data and a couple examples:
> >
> >
>
> plotter(10,3,fram=rwb,framvec=rwb$prcnt.char.depth,obj=prcnt.char.depth,form1=
> > post.f.crwn.length~shigo.av,form2=post.f.crwn.length~shigo.av-1,
> > form3=leaf.area~(1/exp(shigo.av*x))*n,type=2,xlm=70,ylm=35)
> >
> > plotter(10,3,fram=rwb, framvec=rwb$prcnt.char.depth,
> obj=prcnt.char.depth,
> > form1= post.f.crwn.length~leaf.area,
> form2=post.f.crwn.length~leaf.area-1,
> > form3=leaf.area~(1/exp(shigo.av*x))*n,type=1, xlm=1500, ylm=35,
> > sx=.01,sn=25)
> >
> >
> >
> >
> > plotter<-function(a,b,fram,framvec,obj,form1,form2,form3, type=1, xlm,
> ylm,
> > sx=.01,sn=25){
> > g<-ceiling(a/b)
> > par(mfrow=c(b,g))
> > num<-rep(0,a)
> > sub.plotter<-function(i,fram,framvec,obj,form1,form2,form3,type,
> > xlm,ylm,var1,var2){
> > temp.i<-fram[framvec <=(i*.10),] #trees in the list that have an
> attribute
> > less than or equal to a progressively larger percentage
> >  plot(form1, data=temp.i, xlim=c(0,xlm), ylim=c(0,ylm),
> main=((i-1)*.10))
> > if(type==1){
> >  mod<-lm(form2,data=temp.i)
> > r2<-summary(mod)$adj.r.squared
> > num[i]<-r2
> >  legend("bottomright", legend=signif(r2), col="black")
> > abline(mod)
> >  num}
> > else{
> > if(type==2){
> >  try(mod<-nls(form3, data=temp.i, start=list(x=sx,n=sn),
> > na.action="na.omit"), silent=TRUE)
> > try(x1<-summary(mod)$coefficients[1,1], silent=TRUE)
> >  try(n1<-summary(mod)$coefficients[2,1], silent=TRUE)
> > try(lines((1/exp(c(0:70)*x1)*n1)), silent=TRUE)
> >  try(num[i]<-AIC(mod), silent=TRUE)
> > try(legend("bottomright", legend=round(num[i],3) , col="black"),
> > silent=TRUE)
> >  try((num), silent=TRUE)
> >   }
> > }}
> > for(i in 0:a+1){
> >  num<-sub.plotter(i,fram,framvec,obj,form1,form2,form3,type,xlm,ylm)
> > }
> > plot.cor<-function(x){
> > temp<-a+1
> > lengthx<-c(1:temp)
> > plot(x~c(1:temp))
> > m2<-lm(x~c(1:temp))
> > abline(m2)
> > n<-summary(m2)$adj.r.squared
> > legend("bottomright", legend=signif(n), col="black")
> > slope<-(coef(m2)[2])# slope
> > values<-(num)#values for aic or adj r2
> > r2ofr2<-(n) #r2 of r2 or AIC
> > output<-data.frame(lengthx,slope,values,r2ofr2)
> > }
> > plot.cor(num)
> > write.csv(plot.cor(num)$output,"output.csv") # can't seem to use
> > paste(substitute(form3),".csv",sep="") to name it at the moment
> > par(mfrow=c(1,1))
> > }
> >
> >
> >
> >
> > On Sun, Apr 1, 2012 at 3:25 PM, Joshua Wiley <jwiley.psych@gmail.com>
> wrote:
> >
> > > Hi,
> > >
> > > Glancing through your code it was not immediately obvious to me why it
> > > does not work, but I can see a lot of things that could be simplified.
> > >  It would really help if you could give us a reproducible example.
> > > Find/upload/create (in R) some data, and examples of how you would use
> > > the function.  Right now, I can only guess what your data etc. are
> > > like and based on your description plus what the code you wrote seems
> > > to expect to be given.  I could try to give code suggestions, but I
> > > have no easy way of testing them so it would be very easy to make
> > > typos, etc.  Then you just get back my edits to your code that still
> > > do not work and maybe it is because of something fundamentally wrong
> > > with what I have done, a simple typo, or something else still wrong in
> > > your code that I did not fix.
> > >
> > > Anyway, if you send some data and an example using your function
> > > (i.e., using the data you send, write our form1, form2, type, etc.), I
> > > will take a look at your function and see if I can make it run.
> > >
> > > Cheers,
> > >
> > > Josh
> > >
> > > On Sun, Apr 1, 2012 at 3:13 PM, Benjamin Caldwell
> > > <btcaldwell@berkeley.edu> wrote:
> > > > Hello,
> > > >
> > > > I've written a small function that's supposed to save me some time,
> and
> > > > it's ending up killing it- the intention is to iteratively subset a
> > > dataset
> > > > fram on framevec, fit a model (either lm or nls depending on type)
> and
> > > > return the r2 or AIC from the model, respectively. Although as far
> as I
> > > can
> > > > tell in my code the plots are dependent on the fit of the model to
> the
> > > data
> > > > and the r2 and AIC reported are also dependent on the re-fitted
> model,
> > > the
> > > > plots show the same linear or non-linear model used for every subset
> of
> > > the
> > > > data.
> > > >
> > > > However, the r2 and AIC values come back different for each subset.
> > > >
> > > > When I do the subsetting and model fitting outside the function, the
> > > model
> > > > fit is different, with different slopes, for each subset of the
> data.
> > > >
> > > > I'm going to end up doing this without the function if I don't solve
> this
> > > > soon. Any help much appreciated.
> > > >
> > > >
> > > > #a is the number of times to loop the tenth of percent, b is first
> > > > dimension of mfrow, frame is the dataframe, framevec is the vector
> within
> > > > the dataframe you're using to subset (should be a percentage), form
> 1 is
> > > > the simple y~x for the plot, form 2 is y~x for regression, type is
> lm 1
> > > or
> > > > 2 nls ,form 3 is the formula for the nls, sx and sn are the start
> values
> > > > for nls
> > > >
> > > > plotter<-function(a,b,fram,framvec,form1,form2,form3, type=1, xlm,
> ylm,
> > > > sx=.01,sn=25){
> > > > g<-ceiling(a/b)
> > > > par(mfrow=c(b,g))
> > > >  num<-rep(0,a)
> > > > sub.plotter<-function(i,fram,framvec,form1,form2,form3,type,
> > > > xlm,ylm,var1,var2){
> > > > temp.i<-fram[framvec <=(i*.10),]
> > > >  plot(form1, data=temp.i, xlim=c(0,xlm), ylim=c(0,ylm),
> main=((i-1)*.10))
> > > > if(type==1){
> > > >  mod<-lm(form2,data=temp.i)
> > > > r2<-summary(mod)$adj.r.squared
> > > > num<-r2
> > > >  legend("bottomright", legend=signif(r2), col="black")
> > > > abline(mod)
> > > >  num}
> > > > else{
> > > > if(type==2){
> > > >  try(mod<-nls(form3, data=temp.i, start=list(x=sx,n=sn),
> > > > na.action="na.omit"), silent=TRUE)
> > > > try(x1<-summary(mod)$coefficients[1,1], silent=TRUE)
> > > >  try(n1<-summary(mod)$coefficients[2,1], silent=TRUE)
> > > > try(lines((1/exp(c(0:70)*x1)*n1)), silent=TRUE)
> > > >  try(num[i]<-AIC(mod), silent=TRUE)
> > > > try(legend("bottomright", legend=round(num[i],3) , col="black"),
> > > > silent=TRUE)
> > > >  try((num), silent=TRUE)
> > > >  }
> > > > }}
> > > > for(i in 0:a+1){
> > > >  num<-sub.plotter(i,fram,framvec,form1,form2,form3,type,xlm,ylm)
> > > > }
> > > > plot.cor<-function(x){
> > > > temp<-a+1
> > > > lengthx<-c(1:temp)
> > > >  plot(x~c(1:temp))
> > > > m2<-lm(x~c(1:temp))
> > > > abline(m2)
> > > >  n<-summary(m2)$adj.r.squared
> > > > legend("bottomright", legend=signif(n), col="black")
> > > >  slope<-(coef(m2)[2])# slope
> > > > values<-(num)#values for aic or adj r2
> > > > r2ofr2<-(n) #r2 of r2 or AIC
> > > >  output<-data.frame(lengthx,slope,values,r2ofr2)
> > > > }
> > > > plot.cor(num)
> > > > write.csv(plot.cor(num)$output,"output.csv") # can't seem to use
> > > > paste(substitute(form3),".csv",sep="") to name it at the moment
> > > > par(mfrow=c(1,1))
> > > > }
> > > >
> > > > Ben
> > > >
> > > >        [[alternative HTML version deleted]]
> > > >
> > > > ______________________________________________
> > > > 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.
> > >
> > >
> > >
> > > --
> > > Joshua Wiley
> > > Ph.D. Student, Health Psychology
> > > Programmer Analyst II, Statistical Consulting Group
> > > University of California, Los Angeles
> > > https://joshuawiley.com/
> > >
> > ______________________________________________
> > 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.
>
>

	[[alternative HTML version deleted]]

