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Elias Pipping authoredElias Pipping authored
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test-gradient-sample.cc 1.63 KiB
/* Checks if the descent direction is computed correctly using the
analytic solution; also checks if the algorithm converges
regardless of where it starts */
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include <cassert>
#include <dune/common/shared_ptr.hh>
#include <dune/tectonic/samplefunctional.hh>
#include "test-gradient-method-nicefunction.hh"
#include "test-gradient-method-helper.hh"
int main() {
int const dim = 2;
typedef Dune::SampleFunctional<dim> Functional;
typedef Functional::SmallMatrix SmallMatrix;
typedef Functional::SmallVector SmallVector;
SmallMatrix A;
A[0][0] = 3;
A[0][1] = A[1][0] = 1.5;
A[1][1] = 4;
SmallVector b;
b[0] = 1;
b[1] = 2;
auto f = Dune::make_shared<Dune::SampleFunction<2> const>();
auto phi = Dune::make_shared<Functional::NonlinearityType const>(f);
Functional J(A, b, phi);
SmallVector start = b;
start *= 17;
/*
j(x)
= Ax - b + 2/|x| x
= 17*(6, 9.5) - (1, 2) + 2/sqrt(5) (1, 2)
= (102 - 1 + 2/sqrt(5), 161.5 - 2 + 4/sqrt(5))
*/
SmallVector analytic_descent;
analytic_descent[0] = -(102 - 1 + 2 / sqrt(5));
analytic_descent[1] = -(161.5 - 2 + 4 / sqrt(5));
SmallVector numerical_descent;
J.descentDirection(start, numerical_descent);
assert(two_distance<dim>(analytic_descent, numerical_descent) < 1e-10);
double const ret1 = functionTester(J, start, 6);
// Something random
start[0] = 279;
start[1] = -96;
double const ret2 = functionTester(J, start, 10);
assert(std::abs(ret1 - ret2) < 1e-5);
start[0] = 0;
start[1] = 0;
double const ret3 = functionTester(J, start, 3);
assert(std::abs(ret1 - ret3) < 1e-5);
}