// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
//   this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
//   this list of conditions and the following disclaimer in the documentation
//   and/or other materials provided with the distribution.
// * Neither the name of Google Inc. nor the names of its contributors may be
//   used to endorse or promote products derived from this software without
//   specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: strandmark@google.com (Petter Strandmark)

#ifndef CERES_NO_CXSPARSE

#include "ceres/cxsparse.h"

#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"

namespace ceres {
namespace internal {

CXSparse::CXSparse() : scratch_size_(0), scratch_(NULL) {
}

CXSparse::~CXSparse() {
  if (scratch_size_ > 0) {
    cs_free(scratch_);
  }
}

bool CXSparse::SolveCholesky(cs_di* A, cs_dis* factor, double* b) {
  // Make sure we have enough scratch space available.
  if (scratch_size_ < A->n) {
    if (scratch_size_ > 0) {
      cs_free(scratch_);
    }
    scratch_ = reinterpret_cast<CS_ENTRY*>(cs_malloc(A->n, sizeof(CS_ENTRY)));
  }

  // Solve using Cholesky factorization
  csn* N = cs_chol(A, factor);
  if (N == NULL) {
    LOG(WARNING) << "Cholesky factorization failed.";
    return false;
  }

  // When the Cholesky factorization succeeded, these methods are guaranteed to
  // succeed as well. In the comments below, "x" refers to the scratch space.
  // Set x = P * b.
  cs_ipvec(factor->pinv, b, scratch_, A->n);

  // Set x = L \ x.
  cs_lsolve(N->L, scratch_);

  // Set x = L' \ x.
  cs_ltsolve(N->L, scratch_);

  // Set b = P' * x.
  cs_pvec(factor->pinv, scratch_, b, A->n);

  // Free Cholesky factorization.
  cs_nfree(N);
  return true;
}

cs_dis* CXSparse::AnalyzeCholesky(cs_di* A) {
  // order = 1 for Cholesky factorization.
  return cs_schol(1, A);
}

cs_di CXSparse::CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A) {
  cs_di At;
  At.m = A->num_cols();
  At.n = A->num_rows();
  At.nz = -1;
  At.nzmax = A->num_nonzeros();
  At.p = A->mutable_rows();
  At.i = A->mutable_cols();
  At.x = A->mutable_values();
  return At;
}

cs_di* CXSparse::CreateSparseMatrix(TripletSparseMatrix* tsm) {
  cs_di_sparse tsm_wrapper;
  tsm_wrapper.nzmax = tsm->num_nonzeros();;
  tsm_wrapper.nz = tsm->num_nonzeros();;
  tsm_wrapper.m = tsm->num_rows();
  tsm_wrapper.n = tsm->num_cols();
  tsm_wrapper.p = tsm->mutable_cols();
  tsm_wrapper.i = tsm->mutable_rows();
  tsm_wrapper.x = tsm->mutable_values();

  return cs_compress(&tsm_wrapper);
}

void CXSparse::Free(cs_di* factor) {
  cs_free(factor);
}

void CXSparse::Free(cs_dis* factor) {
  cs_sfree(factor);
}

}  // namespace internal
}  // namespace ceres

#endif  // CERES_NO_CXSPARSE