// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
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// Author: sameeragarwal@google.com (Sameer Agarwal)

#include <vector>
#include <glog/logging.h>
#include "gtest/gtest.h"
#include "ceres/block_random_access_sparse_matrix.h"
#include "ceres/internal/eigen.h"

namespace ceres {
namespace internal {

TEST(BlockRandomAccessSparseMatrix, GetCell) {
  vector<int> blocks;
  blocks.push_back(3);
  blocks.push_back(4);
  blocks.push_back(5);
  const int num_rows = 3 + 4 + 5;

  set< pair<int, int> > block_pairs;
  int num_nonzeros = 0;
  block_pairs.insert(make_pair(0, 0));
  num_nonzeros += blocks[0] * blocks[0];

  block_pairs.insert(make_pair(1, 1));
  num_nonzeros += blocks[1] * blocks[1];

  block_pairs.insert(make_pair(1, 2));
  num_nonzeros += blocks[1] * blocks[2];

  block_pairs.insert(make_pair(2, 0));
  num_nonzeros += blocks[2] * blocks[0];

  BlockRandomAccessSparseMatrix m(blocks, block_pairs);
  EXPECT_EQ(m.num_rows(), num_rows);
  EXPECT_EQ(m.num_cols(), num_rows);

  for (set<pair<int, int> >::const_iterator it = block_pairs.begin();
       it != block_pairs.end();
       ++it) {
    const int row_block_id = it->first;
    const int col_block_id = it->second;
    int row;
    int col;
    int row_stride;
    int col_stride;
    CellInfo* cell =  m.GetCell(row_block_id, col_block_id,
                                &row, &col,
                                &row_stride, &col_stride);
    EXPECT_TRUE(cell != NULL);
    EXPECT_EQ(row, 0);
    EXPECT_EQ(col, 0);
    EXPECT_EQ(row_stride, blocks[row_block_id]);
    EXPECT_EQ(col_stride, blocks[col_block_id]);

    // Write into the block
    MatrixRef(cell->values, row_stride, col_stride).block(
        row, col, blocks[row_block_id], blocks[col_block_id]) =
        (row_block_id + 1) * (col_block_id +1) *
        Matrix::Ones(blocks[row_block_id], blocks[col_block_id]);
  }

  const TripletSparseMatrix* tsm = m.matrix();
  EXPECT_EQ(tsm->num_nonzeros(), num_nonzeros);
  EXPECT_EQ(tsm->max_num_nonzeros(), num_nonzeros);

  Matrix dense;
  tsm->ToDenseMatrix(&dense);

  double kTolerance = 1e-14;

  // (0,0)
  EXPECT_NEAR((dense.block(0, 0, 3, 3) - Matrix::Ones(3, 3)).norm(),
              0.0,
              kTolerance);
  // (1,1)
  EXPECT_NEAR((dense.block(3, 3, 4, 4) - 2 * 2 * Matrix::Ones(4, 4)).norm(),
              0.0,
              kTolerance);
  // (1,2)
  EXPECT_NEAR((dense.block(3, 3 + 4, 4, 5) - 2 * 3 * Matrix::Ones(4, 5)).norm(),
              0.0,
              kTolerance);
  // (2,0)
  EXPECT_NEAR((dense.block(3 + 4, 0, 5, 3) - 3 * 1 * Matrix::Ones(5, 3)).norm(),
              0.0,
              kTolerance);

  // There is nothing else in the matrix besides these four blocks.
  EXPECT_NEAR(dense.norm(), sqrt(9 + 16 * 16 + 36 * 20 + 9 * 15), kTolerance);
}

}  // namespace internal
}  // namespace ceres