Question regarding the use of TMatrixT

Dear ROOTers

I need to apply the following matrix calculations:

trp(M) * M   //multiply transposed matrix with matrix
vector * M   //multiply matrix with vector
const  * M   //multiply matrix with constant
diagonale(M) //get the matrix diagonale
M1 * M2      //multiply 2 matrices
M1 + M2      //add 2 matrices

The matrices that I need to handle are Double_t and can have sizes of up to 500 x 600 (or even larger),
and I want to do the calculation on a computer with only 1GB RAM.

My question is:
Can I use class TMatrixT for this purpose or does ROOT supply a better alternative?

Best regards


Handling matrices of 500x600 should not be a memory problem at all on a 1Gb machine.


Dear Rene

Thank you for your reply.

The reason for my question is that I want to convert an algorithm implemented in R using matrix notation to C++.
Meanwhile I am able to aks my question in a more specific way, since I have converted most of the R code using matrices in the usual way.

Since I need to pass the original matrix X as vector X[i*ncol+j] I have implemented e.g. “mm = tr(X)*X” and “XX = (mm + tr(mm))/2” as follows:

   Double_t *mm = new Double_t[nrow*nrow];
   Double_t *XX = new Double_t[nrow*nrow];

   // mm = tr(X)*X/ncol
   Double_t sum = 0.0;
   for (Int_t i=0; i<nrow; i++) {
      for (Int_t k=0; k<nrow; k++) {
         sum = 0.0;
         for (Int_t j=0; j<ncol; j++) {
            sum += X[i*ncol + j]*X[k*ncol + j];
         mm[i*nrow + k] = sum;

   // XX = (mm + tr(mm))/2 but positive definit
   for (Int_t i=0; i<nrow; i++) {
      for (Int_t k=0; k<nrow; k++) {
         sum = (mm[i*nrow + k] + mm[k*nrow + i])/2.0;
         XX[i*nrow + k] = (sum > 0.0) ? sum : 0.0;

   delete [] XX;
   delete [] mm;

Thus my questions are:
What is the advantage of using TMatrixT or TMatrixD?
Is using TMatrixT faster than my current implementation?
Does using TMatrixT need less RAM than my current implementation?

Best regards

Hi Christian,

TMatrixD is just a “Double_t” representation of the templated TMatrixT …

I see no advantage of using TMatrixT insteade of your code as far as speed
or memory usage is concerned .

However, I think using TMatrixT results in compacter code and less
errors because the algorithms are already contained in this class .
It also allows for easy futher manipulation of the matrix .

For instance “mm = tr(X)*X” would be:

TMatrixD *X = new TMatrixD(nrow,nrow);
TMatrixD mm(TMatrixD::kAtA,*X);

and XX = (mm + tr(mm))/2":

TMatrixD XX = 0.5*(mm+TMatrixD(TMatrixD::kTransposed,mm);

trp(M) * M //multiply transposed matrix with matrix: see above
vector * M //multiply matrix with vector : M * vector
const * M //multiply matrix with constant: see above
diagonale(M) //get the matrix diagonale : TVectorD v = TMatrixDDiag(M)
M1 * M2 //multiply 2 matrices : TMatrixD(M1,TMatrixD::kMult,M2) or M1*m2
M1 + M2 //add 2 matrices : TMatrixD(M1,TMatrixD::kPlus,M2) or M1 + M2


Dear Eddy

Thank you for your reply and especially for the demonstration code on how to use TMatrixD.
I agree with you that using TMatrixT results in compacter code and is less error prone, and
I intend to use it in the future, too.

Best regards