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/*
 * Copyright (c) 2011-2015, Georgia Tech Research Corporation
 * All rights reserved.
 *
 * Author(s): Sehoon Ha <sehoon.ha@gmail.com>,
 *            Jeongseok Lee <jslee02@gmail.com>
 *
 * Georgia Tech Graphics Lab and Humanoid Robotics Lab
 *
 * Directed by Prof. C. Karen Liu and Prof. Mike Stilman
 * <karenliu@cc.gatech.edu> <mstilman@cc.gatech.edu>
 *
 * This file is provided under the following "BSD-style" License:
 *   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.
 *   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 HOLDER 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 CONTRACT, STRICT
 *   LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
 *   ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 *   POSSIBILITY OF SUCH DAMAGE.
 */

#ifndef KIDO_MATH_HELPERS_HPP_
#define KIDO_MATH_HELPERS_HPP_

// Standard Libraries
#include <cfloat>
#include <climits>
#include <cmath>
#include <cstdlib>
#include <ctime>
#include <iomanip>
#include <iostream>

// External Libraries
#include <Eigen/Dense>
// Local Headers
#include "kido/common/Deprecated.hpp"
#include "kido/math/MathTypes.hpp"

namespace kido {
namespace math {

/// \brief a cross b = (CR*a) dot b
/// const Matd CR(2,2,0.0,-1.0,1.0,0.0);
const Eigen::Matrix2d CR((Eigen::Matrix2d() << 0.0, -1.0, 1.0, 0.0).finished());

inline int delta(int _i, int _j) {
  if (_i == _j)
    return 1;
  return 0;
}

#if defined(_MSC_VER)
// TODO: Change to constexpr once Visual Studio supports it
template <typename T> inline
#else
template <typename T> inline constexpr
#endif
int sign(T x, std::false_type)
{
  return static_cast<T>(0) < x;
}

#if defined(_MSC_VER)
// TODO: Change to constexpr once Visual Studio supports it
template <typename T> inline
#else
template <typename T> inline constexpr
#endif
int sign(T x, std::true_type)
{
  return (static_cast<T>(0) < x) - (x < static_cast<T>(0));
}

#if defined(_MSC_VER)
// TODO: Change to constexpr once Visual Studio supports it
template <typename T> inline
#else
template <typename T> inline constexpr
#endif
int sign(T x)
{
  return sign(x, std::is_signed<T>());
}

DEPRECATED(5.1)
inline int sgn(double _a)
{
  return sign(_a);
}

inline double sqr(double _x) {
  return _x*_x;
}

inline double Tsinc(double _theta) {
  return 0.5-sqrt(_theta)/48;
}

inline bool isZero(double _theta) {
  return (std::abs(_theta) < KIDO_EPSILON);
}

inline double asinh(double _X) {
  return log(_X + sqrt(_X * _X + 1));
}

inline double acosh(double _X) {
  return log(_X + sqrt(_X * _X - 1));
}

inline double atanh(double _X) {
  return log((1 + _X)/(1 - _X))/ 2;
}

inline double asech(double _X) {
  return log((sqrt(-_X * _X + 1) + 1) / _X);
}

inline double acosech(double _X) {
  return log((sign(_X) * sqrt(_X * _X + 1) +1) / _X);
}

inline double acotanh(double _X) {
  return log((_X + 1) / (_X - 1)) / 2;
}

inline double round(double _x) {
  return floor(_x + 0.5);
}

inline double round2(double _x) {
  int gintx = static_cast<int>(std::floor(_x));
  if (_x - gintx < 0.5)
    return static_cast<double>(gintx);
  else
    return static_cast<double>(gintx + 1.0);
}

template <typename T>
inline T clip(const T& val, const T& lower, const T& upper)
{
  return std::max(lower, std::min(val, upper));
}

template <typename DerivedA, typename DerivedB>
inline typename DerivedA::PlainObject clip(
    const Eigen::MatrixBase<DerivedA>& val,
    const Eigen::MatrixBase<DerivedB>& lower,
    const Eigen::MatrixBase<DerivedB>& upper)
{
  return lower.cwiseMax(val.cwiseMin(upper));
}

inline bool isEqual(double _x, double _y) {
  return (std::abs(_x - _y) < KIDO_EPSILON);
}

// check if it is an integer
inline bool isInt(double _x) {
  if (isEqual(round(_x), _x))
    return true;
  return false;
}

/// \brief Returns whether _v is a NaN (Not-A-Number) value
inline bool isNan(double _v) {
#ifdef _WIN32
  return _isnan(_v) != 0;
#else
  return std::isnan(_v);
#endif
}

/// \brief Returns whether _m is a NaN (Not-A-Number) matrix
inline bool isNan(const Eigen::MatrixXd& _m) {
  for (int i = 0; i < _m.rows(); ++i)
    for (int j = 0; j < _m.cols(); ++j)
      if (isNan(_m(i, j)))
        return true;

  return false;
}

/// \brief Returns whether _v is an infinity value (either positive infinity or
/// negative infinity).
inline bool isInf(double _v) {
#ifdef _WIN32
  return !_finite(_v);
#else
  return std::isinf(_v);
#endif
}

/// \brief Returns whether _m is an infinity matrix (either positive infinity or
/// negative infinity).
inline bool isInf(const Eigen::MatrixXd& _m) {
  for (int i = 0; i < _m.rows(); ++i)
    for (int j = 0; j < _m.cols(); ++j)
      if (isInf(_m(i, j)))
        return true;

  return false;
}

/// \brief Returns whether _m is symmetric or not
inline bool isSymmetric(const Eigen::MatrixXd& _m, double _tol = 1e-6) {
  size_t rows = _m.rows();
  size_t cols = _m.cols();

  if (rows != cols)
    return false;

  for (size_t i = 0; i < rows; ++i) {
    for (size_t j = i + 1; j < cols; ++j) {
      if (std::abs(_m(i, j) - _m(j, i)) > _tol) {
        std::cout << "A: " << std::endl;
        for (size_t k = 0; k < rows; ++k) {
          for (size_t l = 0; l < cols; ++l)
            std::cout << std::setprecision(4) << _m(k, l) << " ";
          std::cout << std::endl;
        }

        std::cout << "A(" << i << ", " << j << "): " << _m(i, j) << std::endl;
        std::cout << "A(" << j << ", " << i << "): " << _m(i, j) << std::endl;
        return false;
      }
    }
  }

  return true;
}

inline unsigned seedRand() {
  time_t now = time(0);
  unsigned char* p = reinterpret_cast<unsigned char*>(&now);
  unsigned seed = 0;
  size_t i;

  for (i = 0; i < sizeof(now); i++)
    seed = seed * (UCHAR_MAX + 2U) + p[i];

  srand(seed);
  return seed;
}

inline double random(double _min, double _max) {
  return _min + ((static_cast<double>(rand()) / (RAND_MAX + 1.0))
                * (_max - _min));
}

template<int N>
Eigen::Matrix<double, N, 1> randomVector(double _min, double _max)
{
  Eigen::Matrix<double, N, 1> v;
  for(size_t i=0; i<N; ++i)
    v[i] = random(_min, _max);

  return v;
}

template<int N>
Eigen::Matrix<double, N, 1> randomVector(double _limit)
{
  return randomVector<N>(-std::abs(_limit), std::abs(_limit));
}

//==============================================================================
inline Eigen::VectorXd randomVectorXd(size_t size, double min, double max)
{
  Eigen::VectorXd v = Eigen::VectorXd::Zero(size);

  for (size_t i = 0; i < size; ++i)
    v[i] = random(min, max);

  return v;
}

//==============================================================================
inline Eigen::VectorXd randomVectorXd(size_t size, double limit)
{
  return randomVectorXd(size, -std::abs(limit), std::abs(limit));
}

}  // namespace math

namespace Color
{

inline Eigen::Vector4d Red(double alpha)
{
  return Eigen::Vector4d(0.9, 0.1, 0.1, alpha);
}

inline Eigen::Vector3d Red()
{
  return Eigen::Vector3d(0.9, 0.1, 0.1);
}

inline Eigen::Vector3d Fuschia()
{
  return Eigen::Vector3d(1.0, 0.0, 0.5);
}

inline Eigen::Vector4d Fuschia(double alpha)
{
  return Eigen::Vector4d(1.0, 0.0, 0.5, alpha);
}

inline Eigen::Vector4d Orange(double alpha)
{
  return Eigen::Vector4d(1.0, 0.63, 0.0, alpha);
}

inline Eigen::Vector3d Orange()
{
  return Eigen::Vector3d(1.0, 0.63, 0.0);
}

inline Eigen::Vector4d Green(double alpha)
{
  return Eigen::Vector4d(0.1, 0.9, 0.1, alpha);
}

inline Eigen::Vector3d Green()
{
  return Eigen::Vector3d(0.1, 0.9, 0.1);
}

inline Eigen::Vector4d Blue(double alpha)
{
  return Eigen::Vector4d(0.1, 0.1, 0.9, alpha);
}

inline Eigen::Vector3d Blue()
{
  return Eigen::Vector3d(0.1, 0.1, 0.9);
}

inline Eigen::Vector4d White(double alpha)
{
  return Eigen::Vector4d(1.0, 1.0, 1.0, alpha);
}

inline Eigen::Vector3d White()
{
  return Eigen::Vector3d(1.0, 1.0, 1.0);
}

inline Eigen::Vector4d Black(double alpha)
{
  return Eigen::Vector4d(0.05, 0.05, 0.05, alpha);
}

inline Eigen::Vector3d Black()
{
  return Eigen::Vector3d(0.05, 0.05, 0.05);
}

inline Eigen::Vector4d Gray(double alpha)
{
  return Eigen::Vector4d(0.6, 0.6, 0.6, alpha);
}

inline Eigen::Vector3d Gray()
{
  return Eigen::Vector3d(0.6, 0.6, 0.6);
}

inline Eigen::Vector4d Random(double alpha)
{
  return Eigen::Vector4d(math::random(0.0, 1.0),
                         math::random(0.0, 1.0),
                         math::random(0.0, 1.0),
                         alpha);
}

inline Eigen::Vector3d Random()
{
  return Eigen::Vector3d(math::random(0.0, 1.0),
                         math::random(0.0, 1.0),
                         math::random(0.0, 1.0));
}

} // namespace Color

}  // namespace kido

#endif  // KIDO_MATH_HELPERS_HPP_