kill the LeastSquares module.

I didn't even put it in Eigen2Support because it requires several other modules. But if you want we can always create a new module, Eigen2Support_LeastSquares...

2 files changed, 0 insertions, 154 deletions

diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index b43a5c56d..90e6d6f2f 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -156,7 +156,6 @@ ei_add_test(geo_eulerangles)
 ei_add_test(geo_hyperplane)
 ei_add_test(geo_parametrizedline)
 ei_add_test(geo_alignedbox)
-ei_add_test(regression)
 ei_add_test(stdvector)
 ei_add_test(stdvector_overload)
 ei_add_test(stdlist)
diff --git a/test/regression.cpp b/test/regression.cpp
deleted file mode 100644
index a0f2ae102..000000000
--- a/test/regression.cpp
+++ /dev/null
@@ -1,153 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#include "main.h"
-#include <Eigen/LeastSquares>
-
-template<typename VectorType,
-         typename HyperplaneType>
-void makeNoisyCohyperplanarPoints(int numPoints,
-                                  VectorType **points,
-                                  HyperplaneType *hyperplane,
-                                  typename VectorType::Scalar noiseAmplitude)
-{
-  typedef typename VectorType::Scalar Scalar;
-  const int size = points[0]->size();
-  // pick a random hyperplane, store the coefficients of its equation
-  hyperplane->coeffs().resize(size + 1);
-  for(int j = 0; j < size + 1; j++)
-  {
-    do {
-      hyperplane->coeffs().coeffRef(j) = ei_random<Scalar>();
-    } while(ei_abs(hyperplane->coeffs().coeff(j)) < 0.5);
-  }
-
-  // now pick numPoints random points on this hyperplane
-  for(int i = 0; i < numPoints; i++)
-  {
-    VectorType& cur_point = *(points[i]);
-    do
-    {
-      cur_point = VectorType::Random(size)/*.normalized()*/;
-      // project cur_point onto the hyperplane
-      Scalar x = - (hyperplane->coeffs().head(size).cwiseProduct(cur_point)).sum();
-      cur_point *= hyperplane->coeffs().coeff(size) / x;
-    } while( cur_point.norm() < 0.5
-          || cur_point.norm() > 2.0 );
-  }
-
-  // add some noise to these points
-  for(int i = 0; i < numPoints; i++ )
-    *(points[i]) += noiseAmplitude * VectorType::Random(size);
-}
-
-template<typename VectorType>
-void check_linearRegression(int numPoints,
-                            VectorType **points,
-                            const VectorType& original,
-                            typename VectorType::Scalar tolerance)
-{
-  int size = points[0]->size();
-  assert(size==2);
-  VectorType result(size);
-  linearRegression(numPoints, points, &result, 1);
-  typename VectorType::Scalar error = (result - original).norm() / original.norm();
-  VERIFY(ei_abs(error) < ei_abs(tolerance));
-}
-
-template<typename VectorType,
-         typename HyperplaneType>
-void check_fitHyperplane(int numPoints,
-                         VectorType **points,
-                         const HyperplaneType& original,
-                         typename VectorType::Scalar tolerance)
-{
-  int size = points[0]->size();
-  HyperplaneType result(size);
-  fitHyperplane(numPoints, points, &result);
-  result.coeffs() *= original.coeffs().coeff(size)/result.coeffs().coeff(size);
-  typename VectorType::Scalar error = (result.coeffs() - original.coeffs()).norm() / original.coeffs().norm();
-  VERIFY(ei_abs(error) < ei_abs(tolerance));
-}
-
-void test_regression()
-{
-  for(int i = 0; i < g_repeat; i++)
-  {
-#ifdef EIGEN_TEST_PART_1
-    {
-      Vector2f points2f [1000];
-      Vector2f *points2f_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points2f_ptrs[i] = &(points2f[i]);
-      Vector2f coeffs2f;
-      Hyperplane<float,2> coeffs3f;
-      makeNoisyCohyperplanarPoints(1000, points2f_ptrs, &coeffs3f, 0.01f);
-      coeffs2f[0] = -coeffs3f.coeffs()[0]/coeffs3f.coeffs()[1];
-      coeffs2f[1] = -coeffs3f.coeffs()[2]/coeffs3f.coeffs()[1];
-      CALL_SUBTEST(check_linearRegression(10, points2f_ptrs, coeffs2f, 0.05f));
-      CALL_SUBTEST(check_linearRegression(100, points2f_ptrs, coeffs2f, 0.01f));
-      CALL_SUBTEST(check_linearRegression(1000, points2f_ptrs, coeffs2f, 0.002f));
-    }
-#endif
-
-#ifdef EIGEN_TEST_PART_2
-    {
-      Vector2f points2f [1000];
-      Vector2f *points2f_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points2f_ptrs[i] = &(points2f[i]);
-      Hyperplane<float,2> coeffs3f;
-      makeNoisyCohyperplanarPoints(1000, points2f_ptrs, &coeffs3f, 0.01f);
-      CALL_SUBTEST(check_fitHyperplane(10, points2f_ptrs, coeffs3f, 0.05f));
-      CALL_SUBTEST(check_fitHyperplane(100, points2f_ptrs, coeffs3f, 0.01f));
-      CALL_SUBTEST(check_fitHyperplane(1000, points2f_ptrs, coeffs3f, 0.002f));
-    }
-#endif
-
-#ifdef EIGEN_TEST_PART_3
-    {
-      Vector4d points4d [1000];
-      Vector4d *points4d_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points4d_ptrs[i] = &(points4d[i]);
-      Hyperplane<double,4> coeffs5d;
-      makeNoisyCohyperplanarPoints(1000, points4d_ptrs, &coeffs5d, 0.01);
-      CALL_SUBTEST(check_fitHyperplane(10, points4d_ptrs, coeffs5d, 0.05));
-      CALL_SUBTEST(check_fitHyperplane(100, points4d_ptrs, coeffs5d, 0.01));
-      CALL_SUBTEST(check_fitHyperplane(1000, points4d_ptrs, coeffs5d, 0.002));
-    }
-#endif
-
-#ifdef EIGEN_TEST_PART_4
-    {
-      VectorXcd *points11cd_ptrs[1000];
-      for(int i = 0; i < 1000; i++) points11cd_ptrs[i] = new VectorXcd(11);
-      Hyperplane<std::complex<double>,Dynamic> *coeffs12cd = new Hyperplane<std::complex<double>,Dynamic>(11);
-      makeNoisyCohyperplanarPoints(1000, points11cd_ptrs, coeffs12cd, 0.01);
-      CALL_SUBTEST(check_fitHyperplane(100, points11cd_ptrs, *coeffs12cd, 0.025));
-      CALL_SUBTEST(check_fitHyperplane(1000, points11cd_ptrs, *coeffs12cd, 0.006));
-      delete coeffs12cd;
-      for(int i = 0; i < 1000; i++) delete points11cd_ptrs[i];
-    }
-#endif
-  }
-}