// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

// discard stack allocation as that too bypasses malloc
#define EIGEN_STACK_ALLOCATION_LIMIT 0
// heap allocation will raise an assert if enabled at runtime
#define EIGEN_RUNTIME_NO_MALLOC

#include "main.h"
using namespace std;
template <typename MatrixType>
void diagonalmatrices(const MatrixType& m) {
  typedef typename MatrixType::Scalar Scalar;
  enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
  typedef Matrix<Scalar, Rows, 1> VectorType;
  typedef Matrix<Scalar, 1, Cols> RowVectorType;
  typedef Matrix<Scalar, Rows, Rows> SquareMatrixType;
  typedef Matrix<Scalar, Dynamic, Dynamic> DynMatrixType;
  typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix;
  typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
  typedef Matrix<Scalar, Rows == Dynamic ? Dynamic : 2 * Rows, Cols == Dynamic ? Dynamic : 2 * Cols> BigMatrix;
  Index rows = m.rows();
  Index cols = m.cols();

  MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols);
  VectorType v1 = VectorType::Random(rows), v2 = VectorType::Random(rows);
  RowVectorType rv1 = RowVectorType::Random(cols), rv2 = RowVectorType::Random(cols);

  LeftDiagonalMatrix ldm1(v1), ldm2(v2);
  RightDiagonalMatrix rdm1(rv1), rdm2(rv2);

  Scalar s1 = internal::random<Scalar>();

  SquareMatrixType sq_m1(v1.asDiagonal());
  VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
  sq_m1 = v1.asDiagonal();
  VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
  SquareMatrixType sq_m2 = v1.asDiagonal();
  VERIFY_IS_APPROX(sq_m1, sq_m2);

  ldm1 = v1.asDiagonal();
  LeftDiagonalMatrix ldm3(v1);
  VERIFY_IS_APPROX(ldm1.diagonal(), ldm3.diagonal());
  LeftDiagonalMatrix ldm4 = v1.asDiagonal();
  VERIFY_IS_APPROX(ldm1.diagonal(), ldm4.diagonal());

  sq_m1.block(0, 0, rows, rows) = ldm1;
  VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
  sq_m1.transpose() = ldm1;
  VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());

  Index i = internal::random<Index>(0, rows - 1);
  Index j = internal::random<Index>(0, cols - 1);

  internal::set_is_malloc_allowed(false);
  VERIFY_IS_APPROX(((ldm1 * m1)(i, j)), ldm1.diagonal()(i) * m1(i, j));
  VERIFY_IS_APPROX(((ldm1 * (m1 + m2))(i, j)), ldm1.diagonal()(i) * (m1 + m2)(i, j));
  VERIFY_IS_APPROX(((m1 * rdm1)(i, j)), rdm1.diagonal()(j) * m1(i, j));
  VERIFY_IS_APPROX(((v1.asDiagonal() * m1)(i, j)), v1(i) * m1(i, j));
  VERIFY_IS_APPROX(((m1 * rv1.asDiagonal())(i, j)), rv1(j) * m1(i, j));
  VERIFY_IS_APPROX((((v1 + v2).asDiagonal() * m1)(i, j)), (v1 + v2)(i)*m1(i, j));
  VERIFY_IS_APPROX((((v1 + v2).asDiagonal() * (m1 + m2))(i, j)), (v1 + v2)(i) * (m1 + m2)(i, j));
  VERIFY_IS_APPROX(((m1 * (rv1 + rv2).asDiagonal())(i, j)), (rv1 + rv2)(j)*m1(i, j));
  VERIFY_IS_APPROX((((m1 + m2) * (rv1 + rv2).asDiagonal())(i, j)), (rv1 + rv2)(j) * (m1 + m2)(i, j));
  VERIFY_IS_APPROX((ldm1 * ldm1).diagonal()(i), ldm1.diagonal()(i) * ldm1.diagonal()(i));
  VERIFY_IS_APPROX((ldm1 * ldm1 * m1)(i, j), ldm1.diagonal()(i) * ldm1.diagonal()(i) * m1(i, j));
  VERIFY_IS_APPROX(((v1.asDiagonal() * v1.asDiagonal()).diagonal()(i)), v1(i) * v1(i));
  internal::set_is_malloc_allowed(true);

  if (rows > 1) {
    DynMatrixType tmp = m1.topRows(rows / 2), res;
    VERIFY_IS_APPROX((res = m1.topRows(rows / 2) * rv1.asDiagonal()), tmp * rv1.asDiagonal());
    VERIFY_IS_APPROX((res = v1.head(rows / 2).asDiagonal() * m1.topRows(rows / 2)),
                     v1.head(rows / 2).asDiagonal() * tmp);
  }

  BigMatrix big;
  big.setZero(2 * rows, 2 * cols);

  big.block(i, j, rows, cols) = m1;
  big.block(i, j, rows, cols) = v1.asDiagonal() * big.block(i, j, rows, cols);

  VERIFY_IS_APPROX((big.block(i, j, rows, cols)), v1.asDiagonal() * m1);

  big.block(i, j, rows, cols) = m1;
  big.block(i, j, rows, cols) = big.block(i, j, rows, cols) * rv1.asDiagonal();
  VERIFY_IS_APPROX((big.block(i, j, rows, cols)), m1 * rv1.asDiagonal());

  // products do not allocate memory
  MatrixType res(rows, cols);
  internal::set_is_malloc_allowed(false);
  res.noalias() = ldm1 * m1;
  res.noalias() = m1 * rdm1;
  res.noalias() = ldm1 * m1 * rdm1;
  res.noalias() = LeftDiagonalMatrix::Identity(rows) * m1 * RightDiagonalMatrix::Zero(cols);
  internal::set_is_malloc_allowed(true);

  // scalar multiple
  VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1 * s1).diagonal(), ldm1.diagonal() * s1);
  VERIFY_IS_APPROX(LeftDiagonalMatrix(s1 * ldm1).diagonal(), s1 * ldm1.diagonal());

  VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1);
  VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1);

  // Diagonal to dense
  sq_m1.setRandom();
  sq_m2 = sq_m1;
  VERIFY_IS_APPROX((sq_m1 += (s1 * v1).asDiagonal()), sq_m2 += (s1 * v1).asDiagonal().toDenseMatrix());
  VERIFY_IS_APPROX((sq_m1 -= (s1 * v1).asDiagonal()), sq_m2 -= (s1 * v1).asDiagonal().toDenseMatrix());
  VERIFY_IS_APPROX((sq_m1 = (s1 * v1).asDiagonal()), (s1 * v1).asDiagonal().toDenseMatrix());

  sq_m1.setRandom();
  sq_m2 = v1.asDiagonal();
  sq_m2 = sq_m1 * sq_m2;
  VERIFY_IS_APPROX((sq_m1 * v1.asDiagonal()).col(i), sq_m2.col(i));
  VERIFY_IS_APPROX((sq_m1 * v1.asDiagonal()).row(i), sq_m2.row(i));

  sq_m1 = v1.asDiagonal();
  sq_m2 = v2.asDiagonal();
  SquareMatrixType sq_m3 = v1.asDiagonal();
  VERIFY_IS_APPROX(sq_m3 = v1.asDiagonal() + v2.asDiagonal(), sq_m1 + sq_m2);
  VERIFY_IS_APPROX(sq_m3 = v1.asDiagonal() - v2.asDiagonal(), sq_m1 - sq_m2);
  VERIFY_IS_APPROX(sq_m3 = v1.asDiagonal() - 2 * v2.asDiagonal() + v1.asDiagonal(), sq_m1 - 2 * sq_m2 + sq_m1);

  // Zero and Identity
  LeftDiagonalMatrix zero = LeftDiagonalMatrix::Zero(rows);
  LeftDiagonalMatrix identity = LeftDiagonalMatrix::Identity(rows);
  VERIFY_IS_APPROX(identity.diagonal().sum(), Scalar(rows));
  VERIFY_IS_APPROX(zero.diagonal().sum(), Scalar(0));
  VERIFY_IS_APPROX((zero + 2 * LeftDiagonalMatrix::Identity(rows)).diagonal().sum(), Scalar(2 * rows));
}

template <typename MatrixType>
void as_scalar_product(const MatrixType& m) {
  typedef typename MatrixType::Scalar Scalar;
  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
  typedef Matrix<Scalar, Dynamic, Dynamic> DynMatrixType;
  typedef Matrix<Scalar, Dynamic, 1> DynVectorType;
  typedef Matrix<Scalar, 1, Dynamic> DynRowVectorType;

  Index rows = m.rows();
  Index depth = internal::random<Index>(1, EIGEN_TEST_MAX_SIZE);

  VectorType v1 = VectorType::Random(rows);
  DynVectorType dv1 = DynVectorType::Random(depth);
  DynRowVectorType drv1 = DynRowVectorType::Random(depth);
  DynMatrixType dm1 = dv1;
  DynMatrixType drm1 = drv1;

  Scalar s = v1(0);

  VERIFY_IS_APPROX(v1.asDiagonal() * drv1, s * drv1);
  VERIFY_IS_APPROX(dv1 * v1.asDiagonal(), dv1 * s);

  VERIFY_IS_APPROX(v1.asDiagonal() * drm1, s * drm1);
  VERIFY_IS_APPROX(dm1 * v1.asDiagonal(), dm1 * s);
}

template <int>
void bug987() {
  Matrix3Xd points = Matrix3Xd::Random(3, 3);
  Vector2d diag = Vector2d::Random();
  Matrix2Xd tmp1 = points.topRows<2>(), res1, res2;
  VERIFY_IS_APPROX(res1 = diag.asDiagonal() * points.topRows<2>(), res2 = diag.asDiagonal() * tmp1);
  Matrix2d tmp2 = points.topLeftCorner<2, 2>();
  VERIFY_IS_APPROX((res1 = points.topLeftCorner<2, 2>() * diag.asDiagonal()), res2 = tmp2 * diag.asDiagonal());
}

EIGEN_DECLARE_TEST(diagonalmatrices) {
  for (int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST_1(diagonalmatrices(Matrix<float, 1, 1>()));
    CALL_SUBTEST_1(as_scalar_product(Matrix<float, 1, 1>()));

    CALL_SUBTEST_2(diagonalmatrices(Matrix3f()));
    CALL_SUBTEST_3(diagonalmatrices(Matrix<double, 3, 3, RowMajor>()));
    CALL_SUBTEST_4(diagonalmatrices(Matrix4d()));
    CALL_SUBTEST_5(diagonalmatrices(Matrix<float, 4, 4, RowMajor>()));
    CALL_SUBTEST_6(diagonalmatrices(
        MatrixXcf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
    CALL_SUBTEST_6(as_scalar_product(MatrixXcf(1, 1)));
    CALL_SUBTEST_7(diagonalmatrices(
        MatrixXi(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
    CALL_SUBTEST_8(diagonalmatrices(Matrix<double, Dynamic, Dynamic, RowMajor>(
        internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
    CALL_SUBTEST_9(diagonalmatrices(
        MatrixXf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
    CALL_SUBTEST_9(diagonalmatrices(MatrixXf(1, 1)));
    CALL_SUBTEST_9(as_scalar_product(MatrixXf(1, 1)));
  }
  CALL_SUBTEST_10(bug987<0>());
}