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handle any number of differents algorithms

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nojhan 2011-12-15 23:12:24 +01:00
commit 0adabc84fa
2 changed files with 47 additions and 45 deletions
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2
cholesky.h
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@ -289,7 +289,7 @@ public:
sqrt_D(i,i) = sqrt(D(i,i));
}
// the factorization is thus _L*D^1/2
// the factorization is thus L*D^1/2
return ublas::prod( L, sqrt_D );
}
};

92
test.cpp
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@ -24,6 +24,9 @@ Authors:
#include <limits>
#include <iomanip>
#include <numeric>
#include <string>
#include <map>
#include <vector>
#include "cholesky.h"
@ -130,14 +133,23 @@ void test( unsigned int M, unsigned int N, unsigned int F, unsigned int R, unsig
typedef typename cholesky::Cholesky<T>::CovarMat CovarMat;
typedef typename cholesky::Cholesky<T>::FactorMat FactorMat;
typedef typename std::map< std::string, cholesky::Cholesky<T>* > AlgoMap;
AlgoMap algos;
algos["LLT"] = new cholesky::LLT<T>;
algos["LLTa"] = new cholesky::LLTabs<T>;
algos["LLTz"] = new cholesky::LLTzero<T>;
algos["LDLT"] = new cholesky::LDLT<T>;
cholesky::LLT<T> llt;
cholesky::LLTabs<T> llta;
cholesky::LLTzero<T> lltz;
cholesky::LDLT<T> ldlt;
// init data structures on the same keys than given algorithms
std::map<std::string,unsigned int> fails;
// triangular errors sum
std::map<std::string, std::vector<double> > errors;
for( typename AlgoMap::iterator ialgo = algos.begin(); ialgo != algos.end(); ++ialgo ) {
fails[ialgo->first] = 0;
errors[ialgo->first] = std::vector<double>();
}
unsigned int llt_fail = 0;
std::vector<double> s0,s1,s2,s3;
for( unsigned int n=0; n<R; ++n ) {
// a random sample matrix
@ -159,48 +171,36 @@ void test( unsigned int M, unsigned int N, unsigned int F, unsigned int R, unsig
}
#endif
// The LLT algorithm can fail on a sqrt(x<0) and throw an error
// we thus count the failures
FactorMat L0;
try {
L0 = llt(V);
CovarMat V0 = ublas::prod( L0, ublas::trans(L0) );
s0.push_back( trigsum(error(V,V0)) );
} catch( cholesky::NotDefinitePositive & error ) {
llt_fail++;
for( typename AlgoMap::iterator ialgo = algos.begin(); ialgo != algos.end(); ++ialgo ) {
// The LLT algorithm can fail on a sqrt(x<0) and throw an error
// we thus count the failures
FactorMat L;
try {
L = (*ialgo->second)(V);
CovarMat Vn = ublas::prod( L, ublas::trans(L) );
errors[ialgo->first].push_back( trigsum(error(V,Vn)) );
} catch( cholesky::NotDefinitePositive & error ) {
fails[ialgo->first]++;
#ifndef NDEBUG
std::cout << "LLT FAILED:\t" << error.what() << std::endl;
std::cout << "FAILED:\t" << error.what() << std::endl;
#endif
}
} // for ialgo in algos
} // for n in R
for( typename AlgoMap::iterator ialgo = algos.begin(); ialgo != algos.end(); ++ialgo ) {
std::string a = ialgo->first;
std::cout << "\t" << a << ": (" << fails[a] << "/" << R << ")\t";
if( errors[a].size() == 0 ) {
std::cout << "NAN";
} else {
std::cout << sum(errors[a])/R;
}
FactorMat L1 = llta(V);
// reconstruct the covariance matrix
CovarMat V1 = ublas::prod( L1, ublas::trans(L1) );
// store the triangular error distance with the initial covar matrix
s1.push_back( trigsum(error(V,V1)) );
FactorMat L2 = lltz(V);
CovarMat V2 = ublas::prod( L2, ublas::trans(L2) );
s2.push_back( trigsum(error(V,V2)) );
FactorMat L3 = ldlt(V);
CovarMat V3 = ublas::prod( L3, ublas::trans(L3) );
s3.push_back( trigsum(error(V,V3)) );
}
std::cout << "Average error:" << std::endl;
std::cout << "\tLLT: ";
if( s0.size() == 0 ) {
std::cout << "NAN";
} else {
std::cout << sum(s0)/R;
}
std::cout << "\t" << llt_fail << "/" << R << " failures" << std::endl;
std::cout << "\tLLTa: " << sum(s1)/R << std::endl;
std::cout << "\tLLTz: " << sum(s2)/R << std::endl;
std::cout << "\tLDLT: " << sum(s3)/R << std::endl;
std::cout << std::endl;
} // for a in algos
}
@ -230,6 +230,8 @@ int main(int argc, char** argv)
std::clog << "\tmatrix size = " << N << std::endl;
std::clog << "\trandom range = " << F << std::endl;
std::clog << "\trepetitions = " << R << std::endl;
std::clog << "Legend:" << std::endl;
std::clog << "\tAlgo: (failures/runs)\tAverage error" << std::endl;
std::cout << std::endl << "FLOAT" << std::endl;
test<float>(M,N,F,R,seed);