#include "math/dense_blas_internal.h"

#include <gtest/gtest.h>

#include <array>
#include <cmath>
#include <cstddef>
#include <limits>
#include <stdexcept>

namespace fesa::dense_blas_internal {
namespace {

TEST(DenseBlasInternal, CDup003ConvertsZeroNormalAndOverflowLengths) {
  const auto zero = ToMklSize(0U);
  ASSERT_TRUE(zero.HasValue());
  EXPECT_EQ(zero.Value(), 0);

  const auto normal = ToMklSize(3U);
  ASSERT_TRUE(normal.HasValue());
  EXPECT_EQ(normal.Value(), 3);

  const std::size_t overflow =
      static_cast<std::size_t>((std::numeric_limits<MKL_INT>::max)()) + 1U;
  const auto rejected = ToMklSize(overflow);
  EXPECT_FALSE(rejected.HasValue());
  EXPECT_FALSE(rejected.GetStatus().IsOk());
}

TEST(DenseBlasInternal, CDup003CopiesZeroAndNonzeroContiguousValues) {
  EXPECT_NO_THROW(CopyValues(nullptr, 0U, nullptr));

  const std::array<double, 3U> source{1.25, -2.5, 4.0};
  std::array<double, 3U> destination{};
  CopyValues(source.data(), source.size(), destination.data());

  EXPECT_EQ(destination, source);
}

TEST(DenseBlasInternal, TransposeProductChecksShapeAndKnownRectangularAction) {
  Matrix left{3U, 2U};
  Matrix right{3U, 1U};
  for (std::size_t row = 0; row < 3U; ++row) {
    left(row, 0U) = static_cast<double>(row + 1U);
    left(row, 1U) = 2.0;
    right(row, 0U) = static_cast<double>(row);
  }
  const auto product = MultiplyTransposeLeft(left, right);
  ASSERT_EQ(product.Rows(), 2U);
  ASSERT_EQ(product.Columns(), 1U);
  EXPECT_DOUBLE_EQ(product(0U, 0U), 8.0);
  EXPECT_DOUBLE_EQ(product(1U, 0U), 6.0);
  EXPECT_THROW(static_cast<void>(MultiplyTransposeLeft(left, Matrix{2U, 1U})),
               std::invalid_argument);
  const auto empty = MultiplyTransposeLeft(Matrix{0U, 2U}, Matrix{0U, 3U});
  EXPECT_EQ(empty.Rows(), 2U);
  EXPECT_EQ(empty.Columns(), 3U);
  EXPECT_DOUBLE_EQ(empty(1U, 2U), 0.0);
}

TEST(DenseBlasInternal, DiagonalProductKeepsEntrywiseCancellationAndChecks) {
  Vector diagonal{3U};
  diagonal[0U] = 4;
  diagonal[1U] = 2;
  diagonal[2U] = -1;
  Vector input{3U};
  const double large = std::ldexp(1.0, 56);
  input[0U] = 1;
  input[1U] = -large;
  input[2U] = 2 * large;
  const auto product = MultiplyDiagonal(diagonal, input);
  EXPECT_DOUBLE_EQ(product[0U] + (product[1U] - product[2U]), 4);
  EXPECT_EQ(MultiplyDiagonal(Vector{0U}, Vector{0U}).Size(), 0U);
  EXPECT_THROW(static_cast<void>(MultiplyDiagonal(diagonal, Vector{2U})),
               std::invalid_argument);
  input[0U] = std::numeric_limits<double>::infinity();
  EXPECT_THROW(static_cast<void>(MultiplyDiagonal(diagonal, input)),
               std::invalid_argument);
  input[0U] = 1;
  diagonal[0U] = std::numeric_limits<double>::quiet_NaN();
  EXPECT_THROW(static_cast<void>(MultiplyDiagonal(diagonal, input)),
               std::invalid_argument);
}

TEST(DenseBlasInternal, CholeskyAndInverseMatchKnownFactorsAndKeepFailedOutput) {
  Matrix matrix{2U, 2U};
  matrix(0U, 0U) = 4;
  matrix(0U, 1U) = 2;
  matrix(1U, 0U) = 2;
  matrix(1U, 1U) = 5;
  Matrix lower{0U, 0U}, inverse{0U, 0U};
  ASSERT_TRUE(CholeskyLowerAndInverse(matrix, lower, inverse));
  EXPECT_DOUBLE_EQ(lower(0U, 0U), 2);
  EXPECT_DOUBLE_EQ(lower(1U, 0U), 1);
  EXPECT_DOUBLE_EQ(lower(1U, 1U), 2);
  EXPECT_DOUBLE_EQ(lower(0U, 1U), 0);
  EXPECT_DOUBLE_EQ(inverse(0U, 0U), .5);
  EXPECT_DOUBLE_EQ(inverse(1U, 0U), -.25);
  EXPECT_DOUBLE_EQ(inverse(1U, 1U), .5);
  matrix(1U, 1U) = 0;
  EXPECT_FALSE(CholeskyLowerAndInverse(matrix, lower, inverse));
  EXPECT_DOUBLE_EQ(lower(1U, 1U), 2);
  EXPECT_DOUBLE_EQ(inverse(1U, 1U), .5);
  EXPECT_THROW(static_cast<void>(CholeskyLowerAndInverse(
                   Matrix{2U, 1U}, lower, inverse)), std::invalid_argument);
  matrix(0U, 0U) = std::numeric_limits<double>::quiet_NaN();
  EXPECT_THROW(static_cast<void>(CholeskyLowerAndInverse(matrix, lower, inverse)),
               std::invalid_argument);
}

}  // namespace
}  // namespace fesa::dense_blas_internal