// @(#)root/test:$Name: $:$Id: vlazy.cxx,v 1.9 2004/09/03 13:41:34 brun Exp $ // Author: Fons Rademakers 14/11/97 // // Sample code showing off a few advanced features // and comparing them (time-wise) with traditional ones. // // Simple example: downsampling a matrix, that is, creating a matrix // that is 4 times (twice in each dimension) smaller than the original // matrix, by picking every other sample of the latter. // #include "TStopwatch.h" #include "TMatrix.h" #include "TMatrixFLazy.h" #include "Riostream.h" class do_downsample : public TElementPosActionF { private: const TMatrix &fOrigMatrix; const int row_lwb, col_lwb; void Operation(Real_t &element) const { element = fOrigMatrix((fI-row_lwb)*2+row_lwb,(fJ-col_lwb)*2+col_lwb); } public: do_downsample(const TMatrix &orig_matrix) : fOrigMatrix(orig_matrix), row_lwb(orig_matrix.GetRowLwb()), col_lwb(orig_matrix.GetColLwb()) { } }; // Downsample matrix - new style class downsample_matrix : public TMatrixFLazy { private: const TMatrix &fOrigMatrix; void FillIn(TMatrixF &m) const; public: downsample_matrix(const TMatrix &orig_matrix); }; // Just figure out the dimensions of the downsampled (lazy) matrix downsample_matrix::downsample_matrix(const TMatrix &orig_matrix) : TMatrixFLazy(orig_matrix.GetRowLwb(), (orig_matrix.GetNrows()+1)/2 + orig_matrix.GetRowLwb()-1, orig_matrix.GetColLwb(), (orig_matrix.GetNcols()+1)/2 + orig_matrix.GetColLwb()-1), fOrigMatrix(orig_matrix) { } // "construct" the new matrix (when the lazy matrix is being "rolled out") void downsample_matrix::FillIn(TMatrixF &m) const { do_downsample d(fOrigMatrix); m.Apply(d); } // Downsample in the traditional style static TMatrix traditional_downsampling(const TMatrix &orig_matrix) { TMatrix smaller_m(orig_matrix.GetRowLwb(), (orig_matrix.GetNrows()+1)/2 + orig_matrix.GetRowLwb()-1, orig_matrix.GetColLwb(), (orig_matrix.GetNcols()+1)/2 + orig_matrix.GetColLwb()-1); for (int i = 0; i < smaller_m.GetNrows(); i++) for (int j = 0; j < smaller_m.GetNcols(); j++) smaller_m(i+smaller_m.GetRowLwb(),j+smaller_m.GetColLwb()) = orig_matrix(2*i+smaller_m.GetRowLwb(),2*j+smaller_m.GetColLwb()); return smaller_m; } int main() { cout << "\nDownsample matrices using traditional and non-traditional methods" << endl; TStopwatch sw; { cout << "\nMake sure that both methods give the same results" << endl; TMatrix orig_m = THaarMatrixF(9,201); // which is a pretty big matrix TMatrix small1 = traditional_downsampling(orig_m); TMatrix small2 = downsample_matrix(orig_m); R__ASSERT( small1 == small2 ); } { cout << "\nClock the traditional downsampling" << endl; sw.Start(); for (int order = 1; order <= 10; order++) { TMatrix orig_m = THaarMatrixF(order); // may be pretty big, btw for (int count = 0; count < (1<<(12-order)); count++) { TMatrix small = traditional_downsampling(orig_m); small(0,0) = 1; // just to use the matrix } } cout << "\tIt took " << sw.RealTime() << " sec to complete the test" << endl; } { cout << "\nClock the 'new style' downsampling (with lazy matrices)"<< endl; sw.Start(); for (int order = 1; order <= 10; order++) { TMatrix orig_m = THaarMatrixF(order); // may be pretty big, btw for (int count = 0; count < (1<<(12-order)); count++) { TMatrix small = downsample_matrix(orig_m); small(0,0) = 1; // just to use the matrix } } cout << "\tIt took " << sw.RealTime() << " sec to complete the test" << endl; } return 0; }