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#pragma once
#ifndef OPENGM_RANDOM_HXX
#define OPENGM_RANDOM_HXX

/// \cond HIDDEN_SYMBOLS

#include <stdio.h>
#include <stdlib.h>
#include <time.h>

#include "opengm/opengm.hxx"

namespace opengm {

template<class T>
   class RandomUniformBase;
template<class T>
   class RandomUniformFloatingPoint;
template<class T>
   class RandomUniformInteger;
template<class T>
   class RandomUniformUnknown;
template<class T>
   class RandomUniform;

template<class T>
class RandomUniformBase
{
public:
   RandomUniformBase& operator=(const RandomUniformBase& src)
   {
      if(this!=&src) {
         low_=src.low_;
         high_=src.high_;
      }
      return *this;
   }

   RandomUniformBase(const T low = 0, const T high = 1)
   :  low_(low),
      high_(high) 
   {}

   void setLow(const T low) {
      low_ = low;
   }

   void setHigh(const T high) {
      high_ = high;
   }

private:
   T low_;
   T high_;

template<class> friend class RandomUniformInteger;
template<class> friend class RandomUniformFloatingPoint;
template<class> friend class RandomUniformUnknown;
template<class> friend class RandomUniform;
};

template<class T>
class RandomUniformInteger
: public RandomUniformBase<T>
{
public:
   RandomUniformInteger(const T low = 0, const T high = 1)
   :  RandomUniformBase<T>(low, high)
   {}

   RandomUniformInteger(const T low, const T high, const size_t seed)
   :  RandomUniformBase<T>(low, high)
   {
      srand(time_t(seed));
   }

   T operator()() const
   {
      // intended semantics: random number is drawn from [low_, high)
      // however, not all std random number generators behave like this
      // thus this trivial work-around:
      T randomNumber = this->high_;
      while(randomNumber == this->high_) {
         randomNumber = static_cast<T>((rand() % (this->high_ - this->low_)) + this->low_);
      }
      return randomNumber;
   }

template<class> friend class RandomUniform;
};

template<class T>
class RandomUniformFloatingPoint
: public RandomUniformBase<T>
{
public:
   RandomUniformFloatingPoint(const T low = 0, const T high = 1)
   :  RandomUniformBase<T>(low, high)
   {}

   RandomUniformFloatingPoint(const T low, const T high, const size_t seed)
   :  RandomUniformBase<T>(low, high)
   {
      srand(time_t(seed));
   }

   T operator()() const
   {
      // intended semantics: random number is drawn from [low_, high)
      // however, not all std random number generators behave like this
      // thus this trivial work-around:
      T randomNumber = this->high_;
      while(randomNumber == this->high_) {
         randomNumber = (static_cast<T>(rand()) / static_cast<T>(RAND_MAX)) * (this->high_ - this->low_) + this->low_;
      }
      return randomNumber;
   }

template<class> friend class RandomUniform;
};

template<class T>
class RandomUniformUnknown : RandomUniformBase<T> {
template<class> friend class RandomUniform;
};

template<class T>
class RandomUniform
: public
      opengm::meta::If
      <
         opengm::meta::IsFundamental<T>::value,
         typename opengm::meta::If
         <
            opengm::meta::IsFloatingPoint<T>::value,
            opengm::RandomUniformFloatingPoint<T>,
            opengm::RandomUniformInteger<T>
         >::type,
         RandomUniformUnknown<T>
      >::type
{
private:
   typedef typename opengm::meta::If
   <
      opengm::meta::IsFundamental<T>::value,
      typename opengm::meta::If
      <
         opengm::meta::IsFloatingPoint<T>::value,
         opengm::RandomUniformFloatingPoint<T>,
         opengm::RandomUniformInteger<T>
      >::type,
      RandomUniformUnknown<T>
   >::type BaseType;

public:
   RandomUniform(const T low = 0, const T high = 1)
   :  BaseType(low, high)
   {}

   RandomUniform(const T low, const T high, const size_t seed)
   :  BaseType(low, high, seed)
   {}
};

template<class T, class U>
class RandomDiscreteWeighted
{
public:
   RandomDiscreteWeighted() {}

   template<class Iterator>
   RandomDiscreteWeighted(Iterator begin, Iterator end)
   :  probSum_(std::distance(begin, end)),
      randomFloatingPoint_(0, 1)
   {
      U sum = 0;
      // normalization
      for(size_t i=0;i<probSum_.size();++i) {
         probSum_[i]=static_cast<U>(*begin);
         ++begin;
         sum+=probSum_[i];
      }
      probSum_[0]/=sum;
      for(size_t i=1;i<probSum_.size();++i) {
         probSum_[i]/=sum;
         probSum_[i]+=probSum_[i-1];
      }
   }

   template<class Iterator>
   RandomDiscreteWeighted(Iterator begin, Iterator end, size_t seed)
   :  probSum_(std::distance(begin, end)),
      randomFloatingPoint_(0, 1, seed)
   {
      U sum=0;
      // normalization
      for(size_t i=0;i<probSum_.size();++i) {
         probSum_[i]=static_cast<U>(*begin);
         ++begin;
         sum+=probSum_[i];
      }
      probSum_[0]/=sum;
      // accumulatives
      for(size_t i=1;i<probSum_.size();++i) {
         probSum_[i]/=sum;
         probSum_[i]+=probSum_[i-1];
      }
   }

   T operator()() const
   {
      U rnd = randomFloatingPoint_();
      if(rnd < probSum_[0]) {
         return 0;
      }
      for(size_t i=0;i<probSum_.size()-1;++i) {
         if(probSum_[i]<=rnd && rnd<probSum_[i+1]) {
            return static_cast<T>(i+1);
         }
      }
      return static_cast<T>(probSum_.size() - 1);
   }

private:
   std::vector<U> probSum_;
   opengm::RandomUniform<U> randomFloatingPoint_;
};

} // namespace opengm

/// \endcond

#endif // #ifndef OPENGM_RANDOM_HXX