[R] closest match in R to c-like struct?

[(Ted Harding)]

See below.

On 01-May-10 19:14:08, steven mosher wrote:
> maybe I can illustrate the problem by showing how a c programmer
> might think about the problem and the kinds of mistakes 'we' (I)
> make when trying to do this in R
> 
>  cstruct<-function(int, bool){
> +
> + myint<- int*2;
> +
> + mybool<-!bool;
> + myvec<-rep(mybool,10)
> + mymat<-matrix(myint*10,nrow=3,ncol=3)
> + myframe<-data.frame(rep(myint,5),rep(bool,5))
> + returnlist<-list(myint,mybool,myvec,mymat,myframe)
> + return(returnlist)
> +
> +
> +
> + }
> 
># so I have a function that returns a list of hetergenous variables.
># an int, a bool, a vector of bools, a matrix of ints, a dataframe of
># ints and bools
> 
>> test<-cstruct(3,T)
> 
> 
>> test
> [[1]]
> [1] 6
> 
> [[2]]
> [1] FALSE
> 
> [[3]]
>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
> 
> [[4]]
>      [,1] [,2] [,3]
> [1,]   60   60   60
> [2,]   60   60   60
> [3,]   60   60   60
> 
> [[5]]
>   rep.myint..5. rep.bool..5.
> 1             6         TRUE
> 2             6         TRUE
> 3             6         TRUE
> 4             6         TRUE
> 5             6         TRUE
> 
># Now I want to access the first element of my list which is an
># "an int"
># first mistake I always make is I just revert to thinking in the
># 'dot' structure of a c struct.
> 
>> test.myint
> Error: object 'test.myint' not found
> 
># Then I think its stored like a var in a dataframe, accessed by
># the $
>> test$myint
> NULL
> 
># then I try to access the first element of the list
>> test[1]
> [[1]]
> [1] 6
> 
># That works.. but the [[1]] confuses me when I eval test[1] I want 6
># back
># again thinking in C.
># so I try the third element
> 
>> test[3]
> [[1]]
>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
> 
># ok I get my vect of bools back. Now I want the first element
># of that thing
># well test[3] is that thing.. and I want element 1 of test[3]
> 
>> test[3][1]
> [[1]]
>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
> 
>#hmm thats not what I expect. I wanted F back.
># frustrated I try this which i know is wrong
> 
>> test[3,1]
> Error in test[3, 1] : incorrect number of dimensions
> 
># crap.. maybe the $ is supposed to be used
>> test$V3
> NULL
> 
># arrg.. how about 'dot"
>> test.myvec
> Error: object 'test.myvec' not found
> 
> 
> Anyways, That's the kind of frustration. I have a list, third element
> is a matrix how do I referernce the 2 row 2 colum of the matrix in my
> list.. for example.
> and so forth..

When you constructed your return-list, you simply entered the list
components using the R-names of the objects, as used in the code:

  returnlist<-list(myint,mybool,myvec,mymat,myframe)

To use the "$" extractor, you need to give them "external" names,
so you could modify the above to:

  returnlist<-list(Myint=myint,Mybool=mybool,
                   Myvec=myvec,Mymat=mymat,Myframe=myframe)

Then, after

  test<-cstruct(3,T)

you can access test$Myint, test$mybool, etc.; and, in particular,
test$Mymat will be the matrix mymat you put in there, so you
can extract elements of this using

  test$Mymat[2,2]

for the element in row 2, column 2, and so on. Without making
the return-list a named list, its components have no names,
so then test$mymat (as you did) will not work because there
is no component with name "mymat" (there is no component with
any name). The name "mymat" was used by R to identify the
object whose contents were to be placed in the list; that
internal object-name does not get placed in the list.

Note: In my modification above I used "Myint=myint" etc. instead
of "myint=myint" to highlight the distinction between the
component-name and the object-name. But you can just as well
use exactly the same name for component-name as for object-name:
R will recognise them as distinct and do the right thing.
So you could just as well do:

  returnlist<-list(myint=myint,mybool=mybool,
                   myvec=myvec,mymat=mymat,myframe=myframe)

and then, after

  test<-cstruct(3,T)

do

  test$Mymat[2,2]

You can also use positional references if the list components have
no names. Since your "mymat" is in position 4,

  test[[4]]

would return the whole matrix. Then

  test[[4]][2,2]

would return the element in row 2, column 2.

As a standard example, try for instance

  X  <- 0.1*((-10):10)
  Y  <- 0.5*X + 0.2*rnorm(length(X))
  LM <- lm(Y ~ X)

  summary(LM)
  # Call:
  # lm(formula = Y ~ X)
  # Residuals:
  #       Min        1Q    Median        3Q       Max 
  # -0.373283 -0.083458  0.009206  0.139763  0.278242 
  # Coefficients:
  #             Estimate Std. Error t value Pr(>|t|)    
  # (Intercept) -0.06018    0.04448  -1.353    0.192    
  # X            0.46270    0.07345   6.299 4.78e-06 ***
  # ---
  # Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 
  # Residual standard error: 0.2038 on 19 degrees of freedom
  # Multiple R-squared: 0.6762,     Adjusted R-squared: 0.6592 
  # F-statistic: 39.68 on 1 and 19 DF,  p-value: 4.784e-06 

Suppose you just wanted the Estimates and P-values. Then

  summary(LM)$coef[,c(1,4)]
  #                Estimate     Pr(>|t|)
  # (Intercept) -0.06018002 1.919241e-01
  # X            0.46269824 4.783990e-06

The component $coef of summary(LM) is a matrix, so the above
extracts its first and fourth columns.

Alternatively, similarly to the positional extraction shown
for your "test" list:

  summary(LM)[[4]][,c(2,4)]
  #             Std. Error     Pr(>|t|)
  # (Intercept) 0.04447759 1.919241e-01
  # X           0.07345233 4.783990e-06

Since LM is of class lm ("linear model"), summary(LM) sees this and
calls the method summary.lm; this returns a list, and to find out
what's in it have a look at

  ?summary.lm

under "Value:"

 "The function 'summary.lm' computes and returns a list of summary
  statistics of the fitted linear model given in ?object?, using the
  components (list elements) '"call"' and '"terms"' from its
  argument, plus
  [...]
  coefficients: a p x 4 matrix with columns for the estimated
    coefficient, its standard error, t-statistic and corresponding
    (two-sided) p-value.  Aliased coefficients are omitted.
  [...]"

And so on. ("coefficients" is, by implication from '?summary.lm',
in position 4 in the list -- just like your "mymat", as it happens!)

Ted.

> On Sat, May 1, 2010 at 10:56 AM, Ted Harding
> <Ted.Harding at manchester.ac.uk>wrote:
> 
>> On 01-May-10 16:58:49, Giovanni Azua wrote:
>> >
>> > On May 1, 2010, at 6:48 PM, steven mosher wrote:
>> >> I was talking with another guy on the list about this very topic.
>> >>
>> >> A simple example would help.
>> >>
>> >> first a sample C struct, and then how one would do the equivalent
>> >> in
>> >> R.
>> >>
>> >> In the end i suppose one want to do a an 'array' of these structs,
>> >> or
>> >> list
>> >> of the structs.
>> >
>> > Or like in my use-case ... I needed a c-like struct to define the
>> > type
>> > for aggregating the data to return from a function.
>> >
>> > Best regards,
>> > Giovanni
>>
>> Assuming that I understand what you want, this is straightforward
>> and can be found throughout the many functions available in R.
>> The general form is:
>>
>>  myfunction <- function(...){
>>    <code to compute objects A1, A2, ... , An>
>>    list(valA1=A1, valA2=A2, ... , valAn=An)
>>  }
>>
>> and then a call like
>>
>>  myresults <- myfunction(...)
>>
>> will create a list "myresults" with compnents "valA1", ... ,"valAn"
>> which you can access as desired on the lines of
>>
>>  myresults$valA5
>>
>> As a simple example, the following is a function which explores
>> by simulation the power of the Fisher Exact Test for comparing
>> two proportions in a 2x2 table:
>>
>>  power.fisher.test <- function(p1,p2,n1,n2,alpha=0.05,nsim=100){
>>    y1 <- rbinom(nsim,size=n1,prob=p1)
>>    y2 <- rbinom(nsim,size=n2,prob=p2)
>>    y <- cbind(y1,n1-y1,y2,n2-y2)
>>    p.value <- rep(0,nsim)
>>    for (i in 1:nsim)
>>      p.value[i] <- fisher.test(matrix(y[i,],2,2))$p.value
>>    list(Pwr=mean(p.value < alpha),SE.Pwr=sd(p.value <
>>    alpha)/sqrt(nsim))
>>  }
>>
>> So, given two binomials B(n1,p1) and B(n2,p2), what would be the
>> power of the Fisher test to detect that p1 was different from p2,
>> at given significance level alpha? This is investigated by repeating,
>> nsim times:
>>  sample from Bin(n1,p1), sample from Bin(n2.p2)
>>  do a Fisher test and get its P-value; store it
>>    in a vector p.value of length nsim
>> and then finally:
>>  estimate the power as the proportion Pwr of the nsim cases
>>    in which the P-value was less than alpha
>>  get the SE of this estimate
>>  return these two values as components Pwr and SE.Pwr of a list
>>
>> As it happens, here each component of the resulting list is of
>> the same type (a single number); but in a different computation
>> each component (and of course there could be more than two)
>> could be anything -- even another list. So you can have lists
>> of lists ... !
>>
>> Thus, instead of the simple returned list above:
>>
>>  list(Pwr=mean(p.value < alpha),
>>       SE.Pwr=sd(p.value < alpha)/sqrt(nsim))
>>
>> you could have
>>
>>  list(Binoms=list(Bin1=list(size=n1,prob=p1),
>>                   Bin2=list(size=n2,prob=p2))
>>       Pwr=mean(p.value < alpha),
>>       SE.Pwr=sd(p.value < alpha)/sqrt(nsim))
>>
>> thus also returning the details of the Binomials for which the
>> simulation was carried out. You could access these all together as:
>>
>>  power.fisher.test(...)$Binoms
>>
>> or separately as
>>
>>  power.fisher.test(...)$Binoms$Bin1
>> or
>>  power.fisher.test(...)$Binoms$Bin2
>>
>> or even
>>  power.fisher.test(...)$Binoms$Bin1$size
>>  power.fisher.test(...)$Binoms$Bin1$prob
>> etc.
>>
>> Ted.
>>
>> --------------------------------------------------------------------
>> E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk>
>> Fax-to-email: +44 (0)870 094 0861
>> Date: 01-May-10                                       Time: 18:56:50
>> ------------------------------ XFMail ------------------------------
>>
>> ______________________________________________
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>> 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]]
> 
> ______________________________________________
> R-help at 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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E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk>
Fax-to-email: +44 (0)870 094 0861
Date: 01-May-10                                       Time: 21:18:59
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