Revision 353ee6cd90b8e10ec132ce3d430319a7b29795f4 authored by Jonas Rembser on 17 April 2024, 17:24:06 UTC, committed by Jonas Rembser on 19 April 2024, 11:35:25 UTC
After commit a27e60a6d4f, it is not important anymore that only the variables used by the expression are passed to RooFormula. Removing the corresponding warnings helps to get rid of useless warnings in the case where you want to try out variations of the formula that omit certain terms, and in particular it helps in `RooAbsData::reduce()`, where the formula is always passed all the varaiables in the dataset, whether the reduction uses them or not.
1 parent 311b78e
vlazy.cxx
// @(#)root/test:$Id$
// 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 override
{ 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 override;
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()
{
std::cout << "\nDownsample matrices using traditional and non-traditional methods"
<< std::endl;
TStopwatch sw;
{
std::cout << "\nMake sure that both methods give the same results" << std::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 );
}
{
std::cout << "\nClock the traditional downsampling" << std::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
}
}
std::cout << "\tIt took " << sw.RealTime()
<< " sec to complete the test" << std::endl;
}
{
std::cout << "\nClock the 'new style' downsampling (with lazy matrices)"<< std::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
}
}
std::cout << "\tIt took " << sw.RealTime()
<< " sec to complete the test" << std::endl;
}
return 0;
}
![swh spinner](/static/img/swh-spinner.gif)
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