Slots(const P1& plugin1 = P1(),
const P2& plugin2 = P2(),
const P3& plugin3 = P3(),
const P4& plugin4 = P4(),
const P5& plugin5 = P5())
: BaseT( plugin1, BaseSlots(plugin2, plugin3, plugin4, plugin5, NullT()) )
{ }
int main() {
Point center(41,29);
// The numbering of the nodes corresponds to gslib's output order
Node P5(38,28,0.5740);
Node P8(45,29,1.2110);
Node P4(41,26,2.1270);
Node P3(39,31,8.3400);
Node P6(38,31,18.6420);
Node P2(39,30,7.9380);
Node P7(39,32,2.2840);
Node P1(40,31,2.5090);
Node P9(37,20,0.5740);
Node P10(25,28,1.2110);
Node P11(39,26,2.1270);
Node P12(32,31,8.3400);
Node P13(30,34,18.6420);
Node P14(33,35,7.9380);
Node P15(42,32,2.2840);
Node P16(31,23,2.5090);
neighborhood voisin;
voisin.add_node(P1);
voisin.add_node(P2);
voisin.add_node(P3);
voisin.add_node(P4);
voisin.add_node(P5);
voisin.add_node(P6);
voisin.add_node(P7);
voisin.add_node(P8);
voisin.add_node(P9);
voisin.add_node(P10);
voisin.add_node(P11);
voisin.add_node(P12);
voisin.add_node(P13);
voisin.add_node(P14);
voisin.add_node(P15);
voisin.add_node(P16);
typedef matrix_lib_traits<TNT_lib<double> >::Vector TNTvector;
covariance covar;
//______________________________
// Simple Kriging
//______________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "Simple kriging"
<< std::endl << std::endl;
TNTvector SK_weights;
SK_constraints SK;
OK_constraints OK;
double sk_variance;
TNT::stopwatch chrono;
chrono.start();
for(int count = 0 ; count < 50000 ; count ++) {
int change=1;
if(drand48() <0.5) change = -1;
(voisin[0].location())[0] += change;
kriging_weights<GSTL_TNT_lib>(SK_weights,
center, voisin,
covar, OK );
}
chrono.stop();
std::cout << "time elapsed using Gauss: " << chrono.read() << std::endl;
chrono.reset();
chrono.start();
for(int count = 0 ; count < 50000 ; count ++) {
int change=1;
if(drand48() <0.5) change = -1;
voisin[0].property_value() = 0.5*count;
kriging_weights(SK_weights,
center, voisin,
covar, OK );
}
chrono.stop();
std::cout << "time elapsed using LU: " << chrono.read() << std::endl;
/*
//______________________________
// Ordinary Kriging
//______________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "Ordinary kriging"
<< std::endl << std::endl;
TNTvector OK_weights;
OK_constraints OK;
double ok_variance;
status = kriging_weights(OK_weights, ok_variance,
center, voisin,
covar, OK);
std::cout << "Here are the weights:" << std::endl
<< OK_weights << std::endl;
//______________________________
// Kriging with Trend
//______________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "Kriging with Trend"
<< std::endl << std::endl;
TNTvector KT_weights;
KT_constraints<functIter> KT(functArray.begin(),functArray.end());
double kt_variance;
status = kriging_weights(KT_weights, kt_variance,
center, voisin,
covar, KT);
std::cout << "Here are the weights:" << std::endl
<< KT_weights << std::endl;
*/
return 0;
}
int main() {
Node center_node(41,29,-99);
// The numbering of the nodes corresponds to gslib's output order
Node P5(38,28,0.5740);
Node P8(45,29,1.2110);
Node P4(41,26,2.1270);
Node P3(39,31,8.3400);
Node P6(38,31,18.6420);
Node P2(39,30,7.9380);
Node P7(39,32,2.2840);
Node P1(40,31,2.5090);
neighborhood voisin;
voisin.add_node(P1);
voisin.add_node(P2);
voisin.add_node(P3);
voisin.add_node(P4);
voisin.add_node(P5);
voisin.add_node(P6);
voisin.add_node(P7);
voisin.add_node(P8);
typedef TNT_lib<double> TNT;
typedef matrix_lib_traits<TNT>::Vector TNTvector;
typedef matrix_lib_traits<TNT>::Symmetric_matrix TNTMatrix;
covariance covar;
//_____________________________
// gaussian cdf estimator
//_____________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "estimating gaussian cdf with SK"
<< std::endl << std::endl;
Gaussian_cdf g_ccdf;
typedef Kriging_combiner<std::vector<double>::const_iterator,
neighborhood> KCombiner;
KCombiner sk_combiner( new SK_combiner<std::vector<double>::const_iterator,
neighborhood>( 9.0 ) );
typedef Kriging_constraints<neighborhood, Point, TNT> KConstraints;
KConstraints constraints( new SKConstraints_impl<neighborhood, Point,TNT> );
Gaussian_cdf_Kestimator<covariance,
neighborhood,KConstraints,TNT> gK_estimator( covar, constraints, sk_combiner );
gK_estimator(center_node, voisin, g_ccdf);
std::cout << "gaussian cdf : mean= " << g_ccdf.mean() << " variance= "
<< g_ccdf.variance() << std::endl;
/*
Gaussian_cdf g_ccdf2;
Gaussian_cdf_Kestimator<covariance,
neighborhood, SK_constraints> gK_estimator2( covar, SK_constraints(), sk_combiner2 );
gK_estimator2(center, voisin, g_ccdf2);
std::cout << "gaussian cdf : mean= " << g_ccdf2.mean() << " variance= "
<< g_ccdf2.variance() << std::endl;
*/
}