EIC code displayed by LXR master/​include/​boost/​polygon/​detail/​voronoi_robust_fpt.hpp	Source navigation Diff markup Identifier search General search
	Version: master test Revert   Change

File indexing completed on 2025-12-16 10:04:55

 // Boost.Polygon library detail/voronoi_robust_fpt.hpp header file
 
 //          Copyright Andrii Sydorchuk 2010-2012.
 // Distributed under the Boost Software License, Version 1.0.
 //    (See accompanying file LICENSE_1_0.txt or copy at
 //          http://www.boost.org/LICENSE_1_0.txt)
 
 // See http://www.boost.org for updates, documentation, and revision history.
 
 #ifndef BOOST_POLYGON_DETAIL_VORONOI_ROBUST_FPT
 #define BOOST_POLYGON_DETAIL_VORONOI_ROBUST_FPT
 
 #include <algorithm>
 #include <cmath>
 
 // Geometry predicates with floating-point variables usually require
 // high-precision predicates to retrieve the correct result.
 // Epsilon robust predicates give the result within some epsilon relative
 // error, but are a lot faster than high-precision predicates.
 // To make algorithm robust and efficient epsilon robust predicates are
 // used at the first step. In case of the undefined result high-precision
 // arithmetic is used to produce required robustness. This approach
 // requires exact computation of epsilon intervals within which epsilon
 // robust predicates have undefined value.
 // There are two ways to measure an error of floating-point calculations:
 // relative error and ULPs (units in the last place).
 // Let EPS be machine epsilon, then next inequalities have place:
 // 1 EPS <= 1 ULP <= 2 EPS (1), 0.5 ULP <= 1 EPS <= 1 ULP (2).
 // ULPs are good for measuring rounding errors and comparing values.
 // Relative errors are good for computation of general relative
 // error of formulas or expressions. So to calculate epsilon
 // interval within which epsilon robust predicates have undefined result
 // next schema is used:
 //     1) Compute rounding errors of initial variables using ULPs;
 //     2) Transform ULPs to epsilons using upper bound of the (1);
 //     3) Compute relative error of the formula using epsilon arithmetic;
 //     4) Transform epsilon to ULPs using upper bound of the (2);
 // In case two values are inside undefined ULP range use high-precision
 // arithmetic to produce the correct result, else output the result.
 // Look at almost_equal function to see how two floating-point variables
 // are checked to fit in the ULP range.
 // If A has relative error of r(A) and B has relative error of r(B) then:
 //     1) r(A + B) <= max(r(A), r(B)), for A * B >= 0;
 //     2) r(A - B) <= B*r(A)+A*r(B)/(A-B), for A * B >= 0;
 //     2) r(A * B) <= r(A) + r(B);
 //     3) r(A / B) <= r(A) + r(B);
 // In addition rounding error should be added, that is always equal to
 // 0.5 ULP or at most 1 epsilon. As you might see from the above formulas
 // subtraction relative error may be extremely large, that's why
 // epsilon robust comparator class is used to store floating point values
 // and compute subtraction as the final step of the evaluation.
 // For further information about relative errors and ULPs try this link:
 // http://docs.sun.com/source/806-3568/ncg_goldberg.html
 
 namespace boost {
 namespace polygon {
 namespace detail {
 
 template <typename T>
 T get_sqrt(const T& that) {
   return (std::sqrt)(that);
 }
 
 template <typename T>
 bool is_pos(const T& that) {
   return that > 0;
 }
 
 template <typename T>
 bool is_neg(const T& that) {
   return that < 0;
 }
 
 template <typename T>
 bool is_zero(const T& that) {
   return that == 0;
 }
 
 template <typename _fpt>
 class robust_fpt {
  public:
   typedef _fpt floating_point_type;
   typedef _fpt relative_error_type;
 
   // Rounding error is at most 1 EPS.
   enum {
     ROUNDING_ERROR = 1
   };
 
   robust_fpt() : fpv_(0.0), re_(0.0) {}
   explicit robust_fpt(floating_point_type fpv) :
       fpv_(fpv), re_(0.0) {}
   robust_fpt(floating_point_type fpv, relative_error_type error) :
       fpv_(fpv), re_(error) {}
 
   floating_point_type fpv() const { return fpv_; }
   relative_error_type re() const { return re_; }
   relative_error_type ulp() const { return re_; }
 
   bool has_pos_value() const {
     return is_pos(fpv_);
   }
 
   bool has_neg_value() const {
     return is_neg(fpv_);
   }
 
   bool has_zero_value() const {
     return is_zero(fpv_);
   }
 
   robust_fpt operator-() const {
     return robust_fpt(-fpv_, re_);
   }
 
   robust_fpt& operator+=(const robust_fpt& that) {
     floating_point_type fpv = this->fpv_ + that.fpv_;
     if ((!is_neg(this->fpv_) && !is_neg(that.fpv_)) ||
         (!is_pos(this->fpv_) && !is_pos(that.fpv_))) {
       this->re_ = (std::max)(this->re_, that.re_) + ROUNDING_ERROR;
     } else {
       floating_point_type temp =
         (this->fpv_ * this->re_ - that.fpv_ * that.re_) / fpv;
       if (is_neg(temp))
         temp = -temp;
       this->re_ = temp + ROUNDING_ERROR;
     }
     this->fpv_ = fpv;
     return *this;
   }
 
   robust_fpt& operator-=(const robust_fpt& that) {
     floating_point_type fpv = this->fpv_ - that.fpv_;
     if ((!is_neg(this->fpv_) && !is_pos(that.fpv_)) ||
         (!is_pos(this->fpv_) && !is_neg(that.fpv_))) {
        this->re_ = (std::max)(this->re_, that.re_) + ROUNDING_ERROR;
     } else {
       floating_point_type temp =
         (this->fpv_ * this->re_ + that.fpv_ * that.re_) / fpv;
       if (is_neg(temp))
          temp = -temp;
       this->re_ = temp + ROUNDING_ERROR;
     }
     this->fpv_ = fpv;
     return *this;
   }
 
   robust_fpt& operator*=(const robust_fpt& that) {
     this->re_ += that.re_ + ROUNDING_ERROR;
     this->fpv_ *= that.fpv_;
     return *this;
   }
 
   robust_fpt& operator/=(const robust_fpt& that) {
     this->re_ += that.re_ + ROUNDING_ERROR;
     this->fpv_ /= that.fpv_;
     return *this;
   }
 
   robust_fpt operator+(const robust_fpt& that) const {
     floating_point_type fpv = this->fpv_ + that.fpv_;
     relative_error_type re;
     if ((!is_neg(this->fpv_) && !is_neg(that.fpv_)) ||
         (!is_pos(this->fpv_) && !is_pos(that.fpv_))) {
       re = (std::max)(this->re_, that.re_) + ROUNDING_ERROR;
     } else {
       floating_point_type temp =
         (this->fpv_ * this->re_ - that.fpv_ * that.re_) / fpv;
       if (is_neg(temp))
         temp = -temp;
       re = temp + ROUNDING_ERROR;
     }
     return robust_fpt(fpv, re);
   }
 
   robust_fpt operator-(const robust_fpt& that) const {
     floating_point_type fpv = this->fpv_ - that.fpv_;
     relative_error_type re;
     if ((!is_neg(this->fpv_) && !is_pos(that.fpv_)) ||
         (!is_pos(this->fpv_) && !is_neg(that.fpv_))) {
       re = (std::max)(this->re_, that.re_) + ROUNDING_ERROR;
     } else {
       floating_point_type temp =
         (this->fpv_ * this->re_ + that.fpv_ * that.re_) / fpv;
       if (is_neg(temp))
         temp = -temp;
       re = temp + ROUNDING_ERROR;
     }
     return robust_fpt(fpv, re);
   }
 
   robust_fpt operator*(const robust_fpt& that) const {
     floating_point_type fpv = this->fpv_ * that.fpv_;
     relative_error_type re = this->re_ + that.re_ + ROUNDING_ERROR;
     return robust_fpt(fpv, re);
   }
 
   robust_fpt operator/(const robust_fpt& that) const {
     floating_point_type fpv = this->fpv_ / that.fpv_;
     relative_error_type re = this->re_ + that.re_ + ROUNDING_ERROR;
     return robust_fpt(fpv, re);
   }
 
   robust_fpt sqrt() const {
     return robust_fpt(get_sqrt(fpv_),
                       re_ * static_cast<relative_error_type>(0.5) +
                       ROUNDING_ERROR);
   }
 
  private:
   floating_point_type fpv_;
   relative_error_type re_;
 };
 
 template <typename T>
 robust_fpt<T> get_sqrt(const robust_fpt<T>& that) {
   return that.sqrt();
 }
 
 template <typename T>
 bool is_pos(const robust_fpt<T>& that) {
   return that.has_pos_value();
 }
 
 template <typename T>
 bool is_neg(const robust_fpt<T>& that) {
   return that.has_neg_value();
 }
 
 template <typename T>
 bool is_zero(const robust_fpt<T>& that) {
   return that.has_zero_value();
 }
 
 // robust_dif consists of two not negative values: value1 and value2.
 // The resulting expression is equal to the value1 - value2.
 // Subtraction of a positive value is equivalent to the addition to value2
 // and subtraction of a negative value is equivalent to the addition to
 // value1. The structure implicitly avoids difference computation.
 template <typename T>
 class robust_dif {
  public:
   robust_dif() :
       positive_sum_(0),
       negative_sum_(0) {}
 
   explicit robust_dif(const T& value) :
       positive_sum_((value > 0)?value:0),
       negative_sum_((value < 0)?-value:0) {}
 
   robust_dif(const T& pos, const T& neg) :
       positive_sum_(pos),
       negative_sum_(neg) {}
 
   T dif() const {
     return positive_sum_ - negative_sum_;
   }
 
   T pos() const {
     return positive_sum_;
   }
 
   T neg() const {
     return negative_sum_;
   }
 
   robust_dif<T> operator-() const {
     return robust_dif(negative_sum_, positive_sum_);
   }
 
   robust_dif<T>& operator+=(const T& val) {
     if (!is_neg(val))
       positive_sum_ += val;
     else
       negative_sum_ -= val;
     return *this;
   }
 
   robust_dif<T>& operator+=(const robust_dif<T>& that) {
     positive_sum_ += that.positive_sum_;
     negative_sum_ += that.negative_sum_;
     return *this;
   }
 
   robust_dif<T>& operator-=(const T& val) {
     if (!is_neg(val))
       negative_sum_ += val;
     else
       positive_sum_ -= val;
     return *this;
   }
 
   robust_dif<T>& operator-=(const robust_dif<T>& that) {
     positive_sum_ += that.negative_sum_;
     negative_sum_ += that.positive_sum_;
     return *this;
   }
 
   robust_dif<T>& operator*=(const T& val) {
     if (!is_neg(val)) {
       positive_sum_ *= val;
       negative_sum_ *= val;
     } else {
       positive_sum_ *= -val;
       negative_sum_ *= -val;
       swap();
     }
     return *this;
   }
 
   robust_dif<T>& operator*=(const robust_dif<T>& that) {
     T positive_sum = this->positive_sum_ * that.positive_sum_ +
                      this->negative_sum_ * that.negative_sum_;
     T negative_sum = this->positive_sum_ * that.negative_sum_ +
                      this->negative_sum_ * that.positive_sum_;
     positive_sum_ = positive_sum;
     negative_sum_ = negative_sum;
     return *this;
   }
 
   robust_dif<T>& operator/=(const T& val) {
     if (!is_neg(val)) {
       positive_sum_ /= val;
       negative_sum_ /= val;
     } else {
       positive_sum_ /= -val;
       negative_sum_ /= -val;
       swap();
     }
     return *this;
   }
 
  private:
   void swap() {
     (std::swap)(positive_sum_, negative_sum_);
   }
 
   T positive_sum_;
   T negative_sum_;
 };
 
 template<typename T>
 robust_dif<T> operator+(const robust_dif<T>& lhs,
                         const robust_dif<T>& rhs) {
   return robust_dif<T>(lhs.pos() + rhs.pos(), lhs.neg() + rhs.neg());
 }
 
 template<typename T>
 robust_dif<T> operator+(const robust_dif<T>& lhs, const T& rhs) {
   if (!is_neg(rhs)) {
     return robust_dif<T>(lhs.pos() + rhs, lhs.neg());
   } else {
     return robust_dif<T>(lhs.pos(), lhs.neg() - rhs);
   }
 }
 
 template<typename T>
 robust_dif<T> operator+(const T& lhs, const robust_dif<T>& rhs) {
   if (!is_neg(lhs)) {
     return robust_dif<T>(lhs + rhs.pos(), rhs.neg());
   } else {
     return robust_dif<T>(rhs.pos(), rhs.neg() - lhs);
   }
 }
 
 template<typename T>
 robust_dif<T> operator-(const robust_dif<T>& lhs,
                         const robust_dif<T>& rhs) {
   return robust_dif<T>(lhs.pos() + rhs.neg(), lhs.neg() + rhs.pos());
 }
 
 template<typename T>
 robust_dif<T> operator-(const robust_dif<T>& lhs, const T& rhs) {
   if (!is_neg(rhs)) {
     return robust_dif<T>(lhs.pos(), lhs.neg() + rhs);
   } else {
     return robust_dif<T>(lhs.pos() - rhs, lhs.neg());
   }
 }
 
 template<typename T>
 robust_dif<T> operator-(const T& lhs, const robust_dif<T>& rhs) {
   if (!is_neg(lhs)) {
     return robust_dif<T>(lhs + rhs.neg(), rhs.pos());
   } else {
     return robust_dif<T>(rhs.neg(), rhs.pos() - lhs);
   }
 }
 
 template<typename T>
 robust_dif<T> operator*(const robust_dif<T>& lhs,
                         const robust_dif<T>& rhs) {
   T res_pos = lhs.pos() * rhs.pos() + lhs.neg() * rhs.neg();
   T res_neg = lhs.pos() * rhs.neg() + lhs.neg() * rhs.pos();
   return robust_dif<T>(res_pos, res_neg);
 }
 
 template<typename T>
 robust_dif<T> operator*(const robust_dif<T>& lhs, const T& val) {
   if (!is_neg(val)) {
     return robust_dif<T>(lhs.pos() * val, lhs.neg() * val);
   } else {
     return robust_dif<T>(-lhs.neg() * val, -lhs.pos() * val);
   }
 }
 
 template<typename T>
 robust_dif<T> operator*(const T& val, const robust_dif<T>& rhs) {
   if (!is_neg(val)) {
     return robust_dif<T>(val * rhs.pos(), val * rhs.neg());
   } else {
     return robust_dif<T>(-val * rhs.neg(), -val * rhs.pos());
   }
 }
 
 template<typename T>
 robust_dif<T> operator/(const robust_dif<T>& lhs, const T& val) {
   if (!is_neg(val)) {
     return robust_dif<T>(lhs.pos() / val, lhs.neg() / val);
   } else {
     return robust_dif<T>(-lhs.neg() / val, -lhs.pos() / val);
   }
 }
 
 // Used to compute expressions that operate with sqrts with predefined
 // relative error. Evaluates expressions of the next type:
 // sum(i = 1 .. n)(A[i] * sqrt(B[i])), 1 <= n <= 4.
 template <typename _int, typename _fpt, typename _converter>
 class robust_sqrt_expr {
  public:
   enum MAX_RELATIVE_ERROR {
     MAX_RELATIVE_ERROR_EVAL1 = 4,
     MAX_RELATIVE_ERROR_EVAL2 = 7,
     MAX_RELATIVE_ERROR_EVAL3 = 16,
     MAX_RELATIVE_ERROR_EVAL4 = 25
   };
 
   // Evaluates expression (re = 4 EPS):
   // A[0] * sqrt(B[0]).
   _fpt eval1(_int* A, _int* B) {
     _fpt a = convert(A[0]);
     _fpt b = convert(B[0]);
     return a * get_sqrt(b);
   }
 
   // Evaluates expression (re = 7 EPS):
   // A[0] * sqrt(B[0]) + A[1] * sqrt(B[1]).
   _fpt eval2(_int* A, _int* B) {
     _fpt a = eval1(A, B);
     _fpt b = eval1(A + 1, B + 1);
     if ((!is_neg(a) && !is_neg(b)) ||
         (!is_pos(a) && !is_pos(b)))
       return a + b;
     return convert(A[0] * A[0] * B[0] - A[1] * A[1] * B[1]) / (a - b);
   }
 
   // Evaluates expression (re = 16 EPS):
   // A[0] * sqrt(B[0]) + A[1] * sqrt(B[1]) + A[2] * sqrt(B[2]).
   _fpt eval3(_int* A, _int* B) {
     _fpt a = eval2(A, B);
     _fpt b = eval1(A + 2, B + 2);
     if ((!is_neg(a) && !is_neg(b)) ||
         (!is_pos(a) && !is_pos(b)))
       return a + b;
     tA[3] = A[0] * A[0] * B[0] + A[1] * A[1] * B[1] - A[2] * A[2] * B[2];
     tB[3] = 1;
     tA[4] = A[0] * A[1] * 2;
     tB[4] = B[0] * B[1];
     return eval2(tA + 3, tB + 3) / (a - b);
   }
 
 
   // Evaluates expression (re = 25 EPS):
   // A[0] * sqrt(B[0]) + A[1] * sqrt(B[1]) +
   // A[2] * sqrt(B[2]) + A[3] * sqrt(B[3]).
   _fpt eval4(_int* A, _int* B) {
     _fpt a = eval2(A, B);
     _fpt b = eval2(A + 2, B + 2);
     if ((!is_neg(a) && !is_neg(b)) ||
         (!is_pos(a) && !is_pos(b)))
       return a + b;
     tA[0] = A[0] * A[0] * B[0] + A[1] * A[1] * B[1] -
             A[2] * A[2] * B[2] - A[3] * A[3] * B[3];
     tB[0] = 1;
     tA[1] = A[0] * A[1] * 2;
     tB[1] = B[0] * B[1];
     tA[2] = A[2] * A[3] * -2;
     tB[2] = B[2] * B[3];
     return eval3(tA, tB) / (a - b);
   }
 
  private:
   _int tA[5];
   _int tB[5];
   _converter convert;
 };
 }  // detail
 }  // polygon
 }  // boost
 
 #endif  // BOOST_POLYGON_DETAIL_VORONOI_ROBUST_FPT

This page was automatically generated by the 2.3.7 LXR engine. The LXR team