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      1 // Ceres Solver - A fast non-linear least squares minimizer
      2 // Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
      3 // http://code.google.com/p/ceres-solver/
      4 //
      5 // Redistribution and use in source and binary forms, with or without
      6 // modification, are permitted provided that the following conditions are met:
      7 //
      8 // * Redistributions of source code must retain the above copyright notice,
      9 //   this list of conditions and the following disclaimer.
     10 // * Redistributions in binary form must reproduce the above copyright notice,
     11 //   this list of conditions and the following disclaimer in the documentation
     12 //   and/or other materials provided with the distribution.
     13 // * Neither the name of Google Inc. nor the names of its contributors may be
     14 //   used to endorse or promote products derived from this software without
     15 //   specific prior written permission.
     16 //
     17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
     18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
     19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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     22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
     23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
     24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
     25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
     26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
     27 // POSSIBILITY OF SUCH DAMAGE.
     28 //
     29 // Author: wjr (at) google.com (William Rucklidge)
     30 //
     31 // Tests for the conditioned cost function.
     32 
     33 #include "ceres/conditioned_cost_function.h"
     34 
     35 #include "ceres/internal/eigen.h"
     36 #include "ceres/normal_prior.h"
     37 #include "ceres/types.h"
     38 #include "gtest/gtest.h"
     39 
     40 namespace ceres {
     41 namespace internal {
     42 
     43 // The size of the cost functions we build.
     44 static const int kTestCostFunctionSize = 3;
     45 
     46 // A simple cost function: return ax + b.
     47 class LinearCostFunction : public CostFunction {
     48  public:
     49   LinearCostFunction(double a, double b) : a_(a), b_(b) {
     50     set_num_residuals(1);
     51     mutable_parameter_block_sizes()->push_back(1);
     52   }
     53 
     54   virtual bool Evaluate(double const* const* parameters,
     55                         double* residuals,
     56                         double** jacobians) const {
     57     *residuals = **parameters * a_ + b_;
     58     if (jacobians && *jacobians) {
     59       **jacobians = a_;
     60     }
     61 
     62     return true;
     63   }
     64 
     65  private:
     66   const double a_, b_;
     67 };
     68 
     69 // Tests that ConditionedCostFunction does what it's supposed to.
     70 TEST(CostFunctionTest, ConditionedCostFunction) {
     71   double v1[kTestCostFunctionSize], v2[kTestCostFunctionSize],
     72       jac[kTestCostFunctionSize * kTestCostFunctionSize],
     73       result[kTestCostFunctionSize];
     74 
     75   for (int i = 0; i < kTestCostFunctionSize; i++) {
     76     v1[i] = i;
     77     v2[i] = i * 10;
     78     // Seed a few garbage values in the Jacobian matrix, to make sure that
     79     // they're overwritten.
     80     jac[i * 2] = i * i;
     81     result[i] = i * i * i;
     82   }
     83 
     84   // Make a cost function that computes x - v2
     85   VectorRef v2_vector(v2, kTestCostFunctionSize, 1);
     86   Matrix identity(kTestCostFunctionSize, kTestCostFunctionSize);
     87   identity.setIdentity();
     88   NormalPrior* difference_cost_function = new NormalPrior(identity, v2_vector);
     89 
     90   vector<CostFunction*> conditioners;
     91   for (int i = 0; i < kTestCostFunctionSize; i++) {
     92     conditioners.push_back(new LinearCostFunction(i + 2, i * 7));
     93   }
     94 
     95   ConditionedCostFunction conditioned_cost_function(difference_cost_function,
     96                                                     conditioners,
     97                                                     TAKE_OWNERSHIP);
     98   EXPECT_EQ(difference_cost_function->num_residuals(),
     99             conditioned_cost_function.num_residuals());
    100   EXPECT_EQ(difference_cost_function->parameter_block_sizes(),
    101             conditioned_cost_function.parameter_block_sizes());
    102 
    103   double *parameters[1];
    104   parameters[0] = v1;
    105   double *jacs[1];
    106   jacs[0] = jac;
    107 
    108   conditioned_cost_function.Evaluate(parameters, result, jacs);
    109   for (int i = 0; i < kTestCostFunctionSize; i++) {
    110     EXPECT_DOUBLE_EQ((i + 2) * (v1[i] - v2[i]) + i * 7, result[i]);
    111   }
    112 
    113   for (int i = 0; i < kTestCostFunctionSize; i++) {
    114     for (int j = 0; j < kTestCostFunctionSize; j++) {
    115       double actual = jac[i * kTestCostFunctionSize + j];
    116       if (i != j) {
    117         EXPECT_DOUBLE_EQ(0, actual);
    118       } else {
    119         EXPECT_DOUBLE_EQ(i + 2, actual);
    120       }
    121     }
    122   }
    123 }
    124 
    125 }  // namespace internal
    126 }  // namespace ceres
    127