Add and use two_distance

src/test-gradient-method-helper.hh

@@ -24,4 +24,13 @@ double functionTester(Dune::SampleFunctional<dim> J,
   std::cout << boost::format("%8g -> %e") % original % final << std::endl;
   return final;
 }
+
+template <int dim>
+double two_distance(
+    typename Dune::SampleFunctional<dim>::SmallVector const &x,
+    typename Dune::SampleFunctional<dim>::SmallVector const &y) {
+  typename Dune::SampleFunctional<dim>::SmallVector tmp = x;
+  tmp -= y;
+  return tmp.two_norm();
+}
 #endif

src/test-gradient-sample-nonsmooth.cc

@@ -31,7 +31,7 @@ int main() {
   Functional J(A, b, phi);
 
   Functional::SmallVector start;
-  Functional::SmallVector error;
+  Functional::SmallVector analytic_descent;
   /*
     for x = b/|b|:
 
@@ -50,12 +50,11 @@ int main() {
     start /= (b.two_norm() + 1e-12);
     assert(start.two_norm() < 1);
 
-    Functional::SmallVector returned;
-    J.descentDirection(start, returned);
-    error[0] = -(7 / sqrt(5) - 1);
-    error[1] = -(11.5 / sqrt(5) - 2);
-    error -= returned;
-    assert(error.two_norm() < 1e-10);
+    Functional::SmallVector numerical_descent;
+    J.descentDirection(start, numerical_descent);
+    analytic_descent[0] = -(7 / sqrt(5) - 1);
+    analytic_descent[1] = -(11.5 / sqrt(5) - 2);
+    assert(two_distance<dim>(analytic_descent, numerical_descent) < 1e-10);
 
     functionTester(J, start, 6);
   }
@@ -64,12 +63,11 @@ int main() {
     start /= (b.two_norm() - 1e-12); // Make sure the norm is above 1;
     assert(start.two_norm() > 1);
 
-    Functional::SmallVector returned;
-    J.descentDirection(start, returned);
-    error[0] = -(8 / sqrt(5) - 1);
-    error[1] = -(13.5 / sqrt(5) - 2);
-    error -= returned;
-    assert(error.two_norm() < 1e-10);
+    Functional::SmallVector numerical_descent;
+    J.descentDirection(start, numerical_descent);
+    analytic_descent[0] = -(8 / sqrt(5) - 1);
+    analytic_descent[1] = -(13.5 / sqrt(5) - 2);
+    assert(two_distance<dim>(analytic_descent, numerical_descent) < 1e-10);
 
     functionTester(J, start, 6);
   }

src/test-gradient-sample.cc

@@ -40,13 +40,12 @@ int main() {
     = 17*(6, 9.5) - (1, 2) + 2/sqrt(5) (1, 2)
     = (102 - 1 + 2/sqrt(5), 161.5 - 2 + 4/sqrt(5))
   */
-  Functional::SmallVector error;
-  error[0] = -(102 - 1 + 2 / sqrt(5));
-  error[1] = -(161.5 - 2 + 4 / sqrt(5));
-  Functional::SmallVector returned;
-  J.descentDirection(start, returned);
-  error -= returned;
-  assert(error.two_norm() < 1e-10);
+  Functional::SmallVector analytic_descent;
+  analytic_descent[0] = -(102 - 1 + 2 / sqrt(5));
+  analytic_descent[1] = -(161.5 - 2 + 4 / sqrt(5));
+  Functional::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);
 

src/test-gradient-trivial.cc

@@ -44,27 +44,22 @@ int main() {
     = 17*(6, 9.5) - (1, 2)
     = (102 - 1, 161.5 - 2)
   */
-  Functional::SmallVector error;
-  error[0] = -101;
-  error[1] = -159.5;
-  Functional::SmallVector returned;
-  J.descentDirection(start, returned);
-  error -= returned;
-  assert(error.two_norm() < 1e-10);
+  Functional::SmallVector analytic_descent;
+  analytic_descent[0] = -101;
+  analytic_descent[1] = -159.5;
+  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);
-  error = solution;
-  error -= start;
-  assert(error.two_norm() < 1e-5);
+  assert(two_distance<dim>(start, solution) < 1e-5);
 
   // Something random
   start[0] = 279;
   start[1] = -96;
 
   double const ret2 = functionTester(J, start, 25);
-  error = solution;
-  error -= start;
-  assert(error.two_norm() < 1e-6);
+  assert(two_distance<dim>(start, solution) < 1e-6);
 
   assert(std::abs(ret1 - ret2) < 1e-5);
 }