[Rcpp-devel] Push back to a matrix

[Douglas Bates]

On Mon, Sep 5, 2011 at 1:11 PM, Noah Silverman <noahsilverman at ucla.edu> wrote:
> Nice,
>
> But, how can I copy to the Rcpp::NumericMatrix column?
>
> This fails:
> std::vector<double> data1;
> // do stuff to populate data1
>
> Rcpp::NumericMatrix output(data1.size(), 6);
> std::copy(data1.begin(), data1.end(), output(_,0) );

std::copy(data1.begin(), data1.end(), output.begin());

for subsequent columns

std::copy(data2.begin(), data2.end(), output.begin() + output.ncol());

>
>
> I'm probably referencing the matrix column incorrectly, but can't find any documentation for Rcpp on how to do this correctly.
>
> --
> Noah Silverman
> UCLA Department of Statistics
> 8117 Math Sciences Building #8208
> Los Angeles, CA 90095
>
> On Sep 5, 2011, at 9:46 AM, Douglas Bates wrote:
>
>> On Mon, Sep 5, 2011 at 11:31 AM, Noah Silverman <noahsilverman at ucla.edu> wrote:
>>> Hi,
>>> Using Rcpp through inline.
>>> I want to return a matrix, but I don't know the size beforehand.  (My code
>>> loops through a large data set accumulating certain statistics.)
>>> With a NumericVector, I can use push_back() to just add values to the end of
>>> the vector as they occur.  Is there similar functionality for a
>>> NumericMatrix?
>>> Alternately, I could store all my generated statistics in several vectors
>>> (6-7) and then, when complete with my loop, glue them together into a
>>> matrix.  But, this seems inefficient.
>>
>> Not really.  The inefficient method is using push_back() on an Rcpp
>> object because it requires copying the existing vector to new storage
>> every time you add an element.
>>
>> My suggestion is to use std::vector<double> objects to accumulate the
>> results, then allocate the Rcpp::NumericMatrix and copy the results
>> into columns of that matrix.  Because the matrix will be in
>> column-major ordering you can do the copying using std::copy which is
>> reasonably efficient and less error prone than other methods.
>> However, this suggestion, like all other cases of determining
>> efficient ways to perform a calculation, should be benchmarked against
>> other methods.
>>
>>> Here is a rough example of what I'm trying to do.
>>> ------------------------------
>>> int n = inputData.size();
>>> Rcpp::NumericMatrix output;
>>> for(int i=0; i != n; i++){
>>> // generate some stats with a lot of code not shown
>>> foo = mean(stuff);
>>> bar = min(stuff);
>>> baz = max(stuff);
>>> // etc...
>>> output.push_back(foo, bar, baz);
>>> )
>>> return output;
>>> -------------------------------
>>>
>>> --
>>> Noah Silverman
>>> UCLA Department of Statistics
>>> 8117 Math Sciences Building #8208
>>> Los Angeles, CA 90095
>>>
>>> _______________________________________________
>>> Rcpp-devel mailing list
>>> Rcpp-devel at lists.r-forge.r-project.org
>>> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
>>>
>
>