// Ceres Solver - A fast non-linear least squares minimizer

// Copyright 2015 Google Inc. All rights reserved.

// http://ceres-solver.org/

//

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// Author: sameeragarwal@google.com (Sameer Agarwal)

#include "ceres/program.h"

#include <limits>

#include <cmath>

#include <vector>

#include "ceres/sized_cost_function.h"

#include "ceres/problem_impl.h"

#include "ceres/residual_block.h"

#include "ceres/triplet_sparse_matrix.h"

#include "gtest/gtest.h"

namespace ceres {

namespace internal {

using std::string;

using std::vector;

// A cost function that simply returns its argument.

class UnaryIdentityCostFunction : public SizedCostFunction<1, 1> {

 public:

  virtual bool Evaluate(double const* const* parameters,

                        double* residuals,

                        double** jacobians) const {

    residuals[0] = parameters[0][0];

    if (jacobians != NULL && jacobians[0] != NULL) {

      jacobians[0][0] = 1.0;

    }

    return true;

  }

};

// Templated base class for the CostFunction signatures.

template <int kNumResiduals, int N0, int N1, int N2>

class MockCostFunctionBase : public

SizedCostFunction<kNumResiduals, N0, N1, N2> {

 public:

  virtual bool Evaluate(double const* const* parameters,

                        double* residuals,

                        double** jacobians) const {

    for (int i = 0; i < kNumResiduals; ++i) {

      residuals[i] = kNumResiduals +  N0 + N1 + N2;

    }

    return true;

  }

};

class UnaryCostFunction : public MockCostFunctionBase<2, 1, 0, 0> {};

class BinaryCostFunction : public MockCostFunctionBase<2, 1, 1, 0> {};

class TernaryCostFunction : public MockCostFunctionBase<2, 1, 1, 1> {};

TEST(Program, RemoveFixedBlocksNothingConstant) {

  ProblemImpl problem;

  double x;

  double y;

  double z;

  problem.AddParameterBlock(&x, 1);

  problem.AddParameterBlock(&y, 1);

  problem.AddParameterBlock(&z, 1);

  problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);

  problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);

  problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z);

  vector<double*> removed_parameter_blocks;

  double fixed_cost = 0.0;

  string message;

  scoped_ptr<Program> reduced_program(

      CHECK_NOTNULL(problem

                    .program()

                    .CreateReducedProgram(&removed_parameter_blocks,

                                          &fixed_cost,

                                          &message)));

  EXPECT_EQ(reduced_program->NumParameterBlocks(), 3);

  EXPECT_EQ(reduced_program->NumResidualBlocks(), 3);

  EXPECT_EQ(removed_parameter_blocks.size(), 0);

  EXPECT_EQ(fixed_cost, 0.0);

}

TEST(Program, RemoveFixedBlocksAllParameterBlocksConstant) {

  ProblemImpl problem;

  double x = 1.0;

  problem.AddParameterBlock(&x, 1);

  problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);

  problem.SetParameterBlockConstant(&x);

  vector<double*> removed_parameter_blocks;

  double fixed_cost = 0.0;

  string message;

  scoped_ptr<Program> reduced_program(

      CHECK_NOTNULL(problem

                    .program()

                    .CreateReducedProgram(&removed_parameter_blocks,

                                          &fixed_cost,

                                          &message)));

  EXPECT_EQ(reduced_program->NumParameterBlocks(), 0);

  EXPECT_EQ(reduced_program->NumResidualBlocks(), 0);

  EXPECT_EQ(removed_parameter_blocks.size(), 1);

  EXPECT_EQ(removed_parameter_blocks[0], &x);

  EXPECT_EQ(fixed_cost, 9.0);

}

TEST(Program, RemoveFixedBlocksNoResidualBlocks) {

  ProblemImpl problem;

  double x;

  double y;

  double z;

  problem.AddParameterBlock(&x, 1);

  problem.AddParameterBlock(&y, 1);

  problem.AddParameterBlock(&z, 1);

  vector<double*> removed_parameter_blocks;

  double fixed_cost = 0.0;

  string message;

  scoped_ptr<Program> reduced_program(

      CHECK_NOTNULL(problem

                    .program()

                    .CreateReducedProgram(&removed_parameter_blocks,

                                          &fixed_cost,

                                          &message)));

  EXPECT_EQ(reduced_program->NumParameterBlocks(), 0);

  EXPECT_EQ(reduced_program->NumResidualBlocks(), 0);

  EXPECT_EQ(removed_parameter_blocks.size(), 3);

  EXPECT_EQ(fixed_cost, 0.0);

}

TEST(Program, RemoveFixedBlocksOneParameterBlockConstant) {

  ProblemImpl problem;

  double x;

  double y;

  double z;

  problem.AddParameterBlock(&x, 1);

  problem.AddParameterBlock(&y, 1);

  problem.AddParameterBlock(&z, 1);

  problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);

  problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);

  problem.SetParameterBlockConstant(&x);

  vector<double*> removed_parameter_blocks;

  double fixed_cost = 0.0;

  string message;

  scoped_ptr<Program> reduced_program(

      CHECK_NOTNULL(problem

                    .program()

                    .CreateReducedProgram(&removed_parameter_blocks,

                                          &fixed_cost,

                                          &message)));

  EXPECT_EQ(reduced_program->NumParameterBlocks(), 1);

  EXPECT_EQ(reduced_program->NumResidualBlocks(), 1);

}

TEST(Program, RemoveFixedBlocksNumEliminateBlocks) {

  ProblemImpl problem;

  double x;

  double y;

  double z;

  problem.AddParameterBlock(&x, 1);

  problem.AddParameterBlock(&y, 1);

  problem.AddParameterBlock(&z, 1);

  problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x);

  problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z);

  problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);

  problem.SetParameterBlockConstant(&x);

  vector<double*> removed_parameter_blocks;

  double fixed_cost = 0.0;

  string message;

  scoped_ptr<Program> reduced_program(

      CHECK_NOTNULL(problem

                    .program()

                    .CreateReducedProgram(&removed_parameter_blocks,

                                          &fixed_cost,

                                          &message)));

  EXPECT_EQ(reduced_program->NumParameterBlocks(), 2);

  EXPECT_EQ(reduced_program->NumResidualBlocks(), 2);

}

TEST(Program, RemoveFixedBlocksFixedCost) {

  ProblemImpl problem;

  double x = 1.23;

  double y = 4.56;

  double z = 7.89;

  problem.AddParameterBlock(&x, 1);

  problem.AddParameterBlock(&y, 1);

  problem.AddParameterBlock(&z, 1);

  problem.AddResidualBlock(new UnaryIdentityCostFunction(), NULL, &x);

  problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z);

  problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y);

  problem.SetParameterBlockConstant(&x);

  ResidualBlock *expected_removed_block =

      problem.program().residual_blocks()[0];

  scoped_array<double> scratch(

      new double[expected_removed_block->NumScratchDoublesForEvaluate()]);

  double expected_fixed_cost;

  expected_removed_block->Evaluate(true,

                                   &expected_fixed_cost,

                                   NULL,

                                   NULL,

                                   scratch.get());

  vector<double*> removed_parameter_blocks;

  double fixed_cost = 0.0;

  string message;

  scoped_ptr<Program> reduced_program(

      CHECK_NOTNULL(problem

                    .program()

                    .CreateReducedProgram(&removed_parameter_blocks,

                                          &fixed_cost,

                                          &message)));

  EXPECT_EQ(reduced_program->NumParameterBlocks(), 2);

  EXPECT_EQ(reduced_program->NumResidualBlocks(), 2);

  EXPECT_DOUBLE_EQ(fixed_cost, expected_fixed_cost);

}

TEST(Program, CreateJacobianBlockSparsityTranspose) {

  ProblemImpl problem;

  double x[2];

  double y[3];

  double z;

  problem.AddParameterBlock(x, 2);

  problem.AddParameterBlock(y, 3);

  problem.AddParameterBlock(&z, 1);

  problem.AddResidualBlock(new MockCostFunctionBase<2, 2, 0, 0>(), NULL, x);

  problem.AddResidualBlock(new MockCostFunctionBase<3, 1, 2, 0>(), NULL, &z, x);

  problem.AddResidualBlock(new MockCostFunctionBase<4, 1, 3, 0>(), NULL, &z, y);

  problem.AddResidualBlock(new MockCostFunctionBase<5, 1, 3, 0>(), NULL, &z, y);

  problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 1, 0>(), NULL, x, &z);

  problem.AddResidualBlock(new MockCostFunctionBase<2, 1, 3, 0>(), NULL, &z, y);

  problem.AddResidualBlock(new MockCostFunctionBase<2, 2, 1, 0>(), NULL, x, &z);

  problem.AddResidualBlock(new MockCostFunctionBase<1, 3, 0, 0>(), NULL, y);

  TripletSparseMatrix expected_block_sparse_jacobian(3, 8, 14);

  {

    int* rows = expected_block_sparse_jacobian.mutable_rows();

    int* cols = expected_block_sparse_jacobian.mutable_cols();

    double* values = expected_block_sparse_jacobian.mutable_values();

    rows[0] = 0;

    cols[0] = 0;

    rows[1] = 2;

    cols[1] = 1;

    rows[2] = 0;

    cols[2] = 1;

    rows[3] = 2;

    cols[3] = 2;

    rows[4] = 1;

    cols[4] = 2;

    rows[5] = 2;

    cols[5] = 3;

    rows[6] = 1;

    cols[6] = 3;

    rows[7] = 0;

    cols[7] = 4;

    rows[8] = 2;

    cols[8] = 4;

    rows[9] = 2;

    cols[9] = 5;

    rows[10] = 1;

    cols[10] = 5;

    rows[11] = 0;

    cols[11] = 6;

    rows[12] = 2;

    cols[12] = 6;

    rows[13] = 1;

    cols[13] = 7;

    std::fill(values, values + 14, 1.0);

    expected_block_sparse_jacobian.set_num_nonzeros(14);

  }

  Program* program = problem.mutable_program();

  program->SetParameterOffsetsAndIndex();

  scoped_ptr<TripletSparseMatrix> actual_block_sparse_jacobian(

      program->CreateJacobianBlockSparsityTranspose());

  Matrix expected_dense_jacobian;

  expected_block_sparse_jacobian.ToDenseMatrix(&expected_dense_jacobian);

  Matrix actual_dense_jacobian;

  actual_block_sparse_jacobian->ToDenseMatrix(&actual_dense_jacobian);

  EXPECT_EQ((expected_dense_jacobian - actual_dense_jacobian).norm(), 0.0);

}

template <int kNumResiduals, int kNumParameterBlocks>

class NumParameterBlocksCostFunction : public CostFunction {

 public:

  NumParameterBlocksCostFunction() {

    set_num_residuals(kNumResiduals);

    for (int i = 0; i < kNumParameterBlocks; ++i) {

      mutable_parameter_block_sizes()->push_back(1);

    }

  }

  virtual ~NumParameterBlocksCostFunction() {

  }

  virtual bool Evaluate(double const* const* parameters,

                        double* residuals,

                        double** jacobians) const {

    return true;

  }

};

TEST(Program, ReallocationInCreateJacobianBlockSparsityTranspose) {

  // CreateJacobianBlockSparsityTranspose starts with a conservative

  // estimate of the size of the sparsity pattern. This test ensures

  // that when those estimates are violated, the reallocation/resizing

  // logic works correctly.

  ProblemImpl problem;

  double x[20];

  vector<double*> parameter_blocks;

  for (int i = 0; i < 20; ++i) {

    problem.AddParameterBlock(x + i, 1);

    parameter_blocks.push_back(x + i);

  }

  problem.AddResidualBlock(new NumParameterBlocksCostFunction<1, 20>(),

                           NULL,

                           parameter_blocks);

  TripletSparseMatrix expected_block_sparse_jacobian(20, 1, 20);

  {

    int* rows = expected_block_sparse_jacobian.mutable_rows();

    int* cols = expected_block_sparse_jacobian.mutable_cols();

    for (int i = 0; i < 20; ++i) {

      rows[i] = i;

      cols[i] = 0;

    }

    double* values = expected_block_sparse_jacobian.mutable_values();

    std::fill(values, values + 20, 1.0);

    expected_block_sparse_jacobian.set_num_nonzeros(20);

  }

  Program* program = problem.mutable_program();

  program->SetParameterOffsetsAndIndex();

  scoped_ptr<TripletSparseMatrix> actual_block_sparse_jacobian(

      program->CreateJacobianBlockSparsityTranspose());

  Matrix expected_dense_jacobian;

  expected_block_sparse_jacobian.ToDenseMatrix(&expected_dense_jacobian);

  Matrix actual_dense_jacobian;

  actual_block_sparse_jacobian->ToDenseMatrix(&actual_dense_jacobian);

  EXPECT_EQ((expected_dense_jacobian - actual_dense_jacobian).norm(), 0.0);

}

TEST(Program, ProblemHasNanParameterBlocks) {

  ProblemImpl problem;

  double x[2];

  x[0] = 1.0;

  x[1] = std::numeric_limits<double>::quiet_NaN();

  problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 0, 0>(), NULL, x);

  string error;

  EXPECT_FALSE(problem.program().ParameterBlocksAreFinite(&error));

  EXPECT_NE(error.find("has at least one invalid value"),

            string::npos) << error;

}

TEST(Program, InfeasibleParameterBlock) {

  ProblemImpl problem;

  double x[] = {0.0, 0.0};

  problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 0, 0>(), NULL, x);

  problem.SetParameterLowerBound(x, 0, 2.0);

  problem.SetParameterUpperBound(x, 0, 1.0);

  string error;

  EXPECT_FALSE(problem.program().IsFeasible(&error));

  EXPECT_NE(error.find("infeasible bound"), string::npos) << error;

}

TEST(Program, InfeasibleConstantParameterBlock) {

  ProblemImpl problem;

  double x[] = {0.0, 0.0};

  problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 0, 0>(), NULL, x);

  problem.SetParameterLowerBound(x, 0, 1.0);

  problem.SetParameterUpperBound(x, 0, 2.0);

  problem.SetParameterBlockConstant(x);

  string error;

  EXPECT_FALSE(problem.program().IsFeasible(&error));

  EXPECT_NE(error.find("infeasible value"), string::npos) << error;

}

}  // namespace internal

}  // namespace ceres