From 4d0f0d4ad1a5a7193c73bff0e910f3833fcd450a Mon Sep 17 00:00:00 2001
From: Elias Pipping <elias.pipping@fu-berlin.de>
Date: Mon, 30 Jul 2012 10:13:11 +0200
Subject: [PATCH] New test: parabola
---
src/Makefile.am | 1 +
src/test-gradient-method-nicefunction.hh | 14 +++++
src/test-gradient-parabola.cc | 66 ++++++++++++++++++++++++
3 files changed, 81 insertions(+)
create mode 100644 src/test-gradient-parabola.cc
diff --git a/src/Makefile.am b/src/Makefile.am
index 299b4e70..49700b93 100644
--- a/src/Makefile.am
+++ b/src/Makefile.am
@@ -2,6 +2,7 @@ check_PROGRAMS = \
test-gradient-horrible \
test-gradient-horrible-logarithmic \
test-gradient-identity \
+ test-gradient-parabola \
test-gradient-sample \
test-gradient-sample-3d \
test-gradient-sample-nonsmooth \
diff --git a/src/test-gradient-method-nicefunction.hh b/src/test-gradient-method-nicefunction.hh
index eb62eff3..7ef9e642 100644
--- a/src/test-gradient-method-nicefunction.hh
+++ b/src/test-gradient-method-nicefunction.hh
@@ -18,6 +18,20 @@ class MyFunction : public NiceFunction {
}
};
+class Parabola : public MyFunction {
+ void virtual evaluate(double const &x, double &y) const { y = x * x; }
+
+ double virtual leftDifferential(double s) const { return 2 * s; }
+
+ double virtual rightDifferential(double s) const { return 2 * s; }
+
+ double virtual second_deriv(double s) const { return 2; }
+
+ double virtual regularity(double s) const { return 2; }
+
+ bool virtual smoothesNorm() const { return true; }
+};
+
class LinearFunction : public MyFunction {
public:
LinearFunction(double a) : coefficient(a) {}
diff --git a/src/test-gradient-parabola.cc b/src/test-gradient-parabola.cc
new file mode 100644
index 00000000..03b396fd
--- /dev/null
+++ b/src/test-gradient-parabola.cc
@@ -0,0 +1,66 @@
+/* Checks if the descent direction is computed correctly using the
+ analytic solution; also checks if the algorithm converges
+ to the right solution 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-helper.hh"
+#include "test-gradient-method-nicefunction.hh"
+
+int main() {
+ int const dim = 2;
+ typedef Dune::SampleFunctional<dim> Functional;
+
+ Functional::SmallMatrix A;
+ A[0][0] = 3;
+ A[0][1] = A[1][0] = 1.5;
+ A[1][1] = 4;
+ Functional::SmallVector b;
+ b[0] = 1;
+ b[1] = 2;
+
+ // |x|^2 as the nonlinearity is the same as having no nonlinearity
+ // but twice the identity matrix added to A. In other words, we're
+ // solving A + 2*id = b
+ auto f = Dune::make_shared<Dune::Parabola const>();
+ auto phi = Dune::make_shared<Functional::NonlinearityType const>(f);
+ Functional J(A, b, phi);
+
+ Functional::SmallVector solution; // Analytic solution
+ solution[0] = 4.0 / 37.0;
+ solution[1] = 34.0 / 111.0;
+
+ Functional::SmallMatrix M = A;
+ M[0][0] += 2;
+ M[1][1] += 2;
+
+ Functional::SmallVector start = b;
+ start *= 17;
+
+ Functional::SmallVector analytic_descent = b;
+ M.mmv(start, analytic_descent);
+
+ Functional::SmallVector numerical_descent;
+ J.descentDirection(start, numerical_descent);
+ assert(two_distance<dim>(numerical_descent, analytic_descent) < 1e-10);
+
+ double const ret1 = functionTester(J, start, 6);
+ assert(two_distance<dim>(start, solution) < 1e-6);
+
+ // Something random
+ start[0] = 279;
+ start[1] = -96;
+
+ double const ret2 = functionTester(J, start, 15);
+ assert(two_distance<dim>(start, solution) < 1e-6);
+
+ assert(std::abs(ret1 - ret2) < 1e-11);
+}
--
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