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

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// Author: richie.stebbing@gmail.com (Richard Stebbing)

#include "ceres/dynamic_compressed_row_sparse_matrix.h"

#include "ceres/casts.h"

#include "ceres/compressed_row_sparse_matrix.h"

#include "ceres/internal/eigen.h"

#include "ceres/internal/scoped_ptr.h"

#include "ceres/linear_least_squares_problems.h"

#include "ceres/triplet_sparse_matrix.h"

#include "gtest/gtest.h"

namespace ceres {

namespace internal {

using std::copy;

using std::vector;

class DynamicCompressedRowSparseMatrixTest : public ::testing::Test {

 protected:

  virtual void SetUp() {

    num_rows = 7;

    num_cols = 4;

    // The number of additional elements reserved when `Finalize` is called

    // should have no effect on the number of rows, columns or nonzeros.

    // Set this to some nonzero value to be sure.

    num_additional_elements = 13;

    expected_num_nonzeros = num_rows * num_cols - std::min(num_rows, num_cols);

    InitialiseDenseReference();

    InitialiseSparseMatrixReferences();

    dcrsm.reset(new DynamicCompressedRowSparseMatrix(num_rows,

                                                     num_cols,

                                                     0));

  }

  void Finalize() {

    dcrsm->Finalize(num_additional_elements);

  }

  void InitialiseDenseReference() {

    dense.resize(num_rows, num_cols);

    dense.setZero();

    int num_nonzeros = 0;

    for (int i = 0; i < (num_rows * num_cols); ++i) {

      const int r = i / num_cols, c = i % num_cols;

      if (r != c) {

        dense(r, c) = i + 1;

        ++num_nonzeros;

      }

    }

    ASSERT_EQ(num_nonzeros, expected_num_nonzeros);

  }

  void InitialiseSparseMatrixReferences() {

    vector<int> rows, cols;

    vector<double> values;

    for (int i = 0; i < (num_rows * num_cols); ++i) {

      const int r = i / num_cols, c = i % num_cols;

      if (r != c) {

        rows.push_back(r);

        cols.push_back(c);

        values.push_back(i + 1);

      }

    }

    ASSERT_EQ(values.size(), expected_num_nonzeros);

    tsm.reset(new TripletSparseMatrix(num_rows,

                                      num_cols,

                                      expected_num_nonzeros));

    copy(rows.begin(), rows.end(), tsm->mutable_rows());

    copy(cols.begin(), cols.end(), tsm->mutable_cols());

    copy(values.begin(), values.end(), tsm->mutable_values());

    tsm->set_num_nonzeros(values.size());

    Matrix dense_from_tsm;

    tsm->ToDenseMatrix(&dense_from_tsm);

    ASSERT_TRUE((dense.array() == dense_from_tsm.array()).all());

    crsm.reset(CompressedRowSparseMatrix::FromTripletSparseMatrix(*tsm));

    Matrix dense_from_crsm;

    crsm->ToDenseMatrix(&dense_from_crsm);

    ASSERT_TRUE((dense.array() == dense_from_crsm.array()).all());

  }

  void InsertNonZeroEntriesFromDenseReference() {

    for (int r = 0; r < num_rows; ++r) {

      for (int c = 0; c < num_cols; ++c) {

        const double& v = dense(r, c);

        if (v != 0.0) {

          dcrsm->InsertEntry(r, c, v);

        }

      }

    }

  }

  void ExpectEmpty() {

    EXPECT_EQ(dcrsm->num_rows(), num_rows);

    EXPECT_EQ(dcrsm->num_cols(), num_cols);

    EXPECT_EQ(dcrsm->num_nonzeros(), 0);

    Matrix dense_from_dcrsm;

    dcrsm->ToDenseMatrix(&dense_from_dcrsm);

    EXPECT_EQ(dense_from_dcrsm.rows(), num_rows);

    EXPECT_EQ(dense_from_dcrsm.cols(), num_cols);

    EXPECT_TRUE((dense_from_dcrsm.array() == 0.0).all());

  }

  void ExpectEqualToDenseReference() {

    Matrix dense_from_dcrsm;

    dcrsm->ToDenseMatrix(&dense_from_dcrsm);

    EXPECT_TRUE((dense.array() == dense_from_dcrsm.array()).all());

  }

  void ExpectEqualToCompressedRowSparseMatrixReference() {

    typedef Eigen::Map<const Eigen::VectorXi> ConstIntVectorRef;

    ConstIntVectorRef crsm_rows(crsm->rows(), crsm->num_rows() + 1);

    ConstIntVectorRef dcrsm_rows(dcrsm->rows(), dcrsm->num_rows() + 1);

    EXPECT_TRUE((crsm_rows.array() == dcrsm_rows.array()).all());

    ConstIntVectorRef crsm_cols(crsm->cols(), crsm->num_nonzeros());

    ConstIntVectorRef dcrsm_cols(dcrsm->cols(), dcrsm->num_nonzeros());

    EXPECT_TRUE((crsm_cols.array() == dcrsm_cols.array()).all());

    ConstVectorRef crsm_values(crsm->values(), crsm->num_nonzeros());

    ConstVectorRef dcrsm_values(dcrsm->values(), dcrsm->num_nonzeros());

    EXPECT_TRUE((crsm_values.array() == dcrsm_values.array()).all());

  }

  int num_rows;

  int num_cols;

  int num_additional_elements;

  int expected_num_nonzeros;

  Matrix dense;

  scoped_ptr<TripletSparseMatrix> tsm;

  scoped_ptr<CompressedRowSparseMatrix> crsm;

  scoped_ptr<DynamicCompressedRowSparseMatrix> dcrsm;

};

TEST_F(DynamicCompressedRowSparseMatrixTest, Initialization) {

  ExpectEmpty();

  Finalize();

  ExpectEmpty();

}

TEST_F(DynamicCompressedRowSparseMatrixTest, InsertEntryAndFinalize) {

  InsertNonZeroEntriesFromDenseReference();

  ExpectEmpty();

  Finalize();

  ExpectEqualToDenseReference();

  ExpectEqualToCompressedRowSparseMatrixReference();

}

TEST_F(DynamicCompressedRowSparseMatrixTest, ClearRows) {

  InsertNonZeroEntriesFromDenseReference();

  Finalize();

  ExpectEqualToDenseReference();

  ExpectEqualToCompressedRowSparseMatrixReference();

  dcrsm->ClearRows(0, 0);

  Finalize();

  ExpectEqualToDenseReference();

  ExpectEqualToCompressedRowSparseMatrixReference();

  dcrsm->ClearRows(0, num_rows);

  ExpectEqualToCompressedRowSparseMatrixReference();

  Finalize();

  ExpectEmpty();

  InsertNonZeroEntriesFromDenseReference();

  dcrsm->ClearRows(1, 2);

  Finalize();

  dense.block(1, 0, 2, num_cols).setZero();

  ExpectEqualToDenseReference();

  InitialiseDenseReference();

}

}  // namespace internal

}  // namespace ceres