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kpeter (Peter Kovacs)
kpeter@inf.elte.hu
Minor doc improvements
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1 file changed with 9 insertions and 23 deletions:
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Ignore white space 8 line context
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@@ -539,12 +539,8 @@
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    ///\name Initialization
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    ///
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    /// @{
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    ///\name Initialization
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    ///
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    /// @{
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    /// \brief Default constructor
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    ///
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    /// Constructor with constant seeding.
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    Random() { core.initState(); }
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@@ -707,14 +703,8 @@
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    Number real(Number a, Number b) {
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      return real<Number>() * (b - a) + a;
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    }
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    /// @}
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    ///\name Uniform distributions
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    ///
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    /// @{
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    /// \brief Returns a random real number from the range [0, 1)
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    ///
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    /// It returns a random double from the range [0, 1).
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    double operator()() {
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@@ -770,10 +760,8 @@
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    Number uinteger() {
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      return _random_bits::IntConversion<Number, Word>::convert(core);
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    }
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    /// @}
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    unsigned int uinteger() {
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      return uinteger<unsigned int>();
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    }
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@@ -805,21 +793,20 @@
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    /// @}
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    ///\name Non-uniform distributions
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    ///
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    ///@{
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    /// \brief Returns a random bool
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    /// \brief Returns a random bool with given probability of true result.
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    ///
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    /// It returns a random bool with given probability of true result.
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    bool boolean(double p) {
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      return operator()() < p;
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    }
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    /// Standard Gauss distribution
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    /// Standard normal (Gauss) distribution
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    /// Standard Gauss distribution.
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    /// Standard normal (Gauss) distribution.
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    /// \note The Cartesian form of the Box-Muller
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    /// transformation is used to generate a random normal distribution.
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    double gauss()
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    {
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@@ -830,11 +817,11 @@
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        S=V1*V1+V2*V2;
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      } while(S>=1);
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      return std::sqrt(-2*std::log(S)/S)*V1;
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    }
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    /// Gauss distribution with given mean and standard deviation
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    /// Normal (Gauss) distribution with given mean and standard deviation
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    /// Gauss distribution with given mean and standard deviation.
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    /// Normal (Gauss) distribution with given mean and standard deviation.
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    /// \sa gauss()
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    double gauss(double mean,double std_dev)
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    {
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      return gauss()*std_dev+mean;
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@@ -863,24 +850,24 @@
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    /// This function computes the lognormal parameters from mean and
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    /// standard deviation. The return value can direcly be passed to
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    /// lognormal().
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    std::pair<double,double> lognormalParamsFromMD(double mean,
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						   double std_dev)
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                                                   double std_dev)
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    {
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      double fr=std_dev/mean;
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      fr*=fr;
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      double lg=std::log(1+fr);
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      return std::pair<double,double>(std::log(mean)-lg/2.0,std::sqrt(lg));
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    }
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    /// Lognormal distribution with given mean and standard deviation
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    /// Lognormal distribution with given mean and standard deviation.
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    ///
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    double lognormalMD(double mean,double std_dev)
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    {
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      return lognormal(lognormalParamsFromMD(mean,std_dev));
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    }
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    /// Exponential distribution with given mean
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    /// This function generates an exponential distribution random number
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    /// with mean <tt>1/lambda</tt>.
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@@ -982,9 +969,8 @@
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    ///@}
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    ///\name Two dimensional distributions
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    ///
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    ///@{
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    /// Uniform distribution on the full unit circle
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@@ -999,9 +985,9 @@
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      } while(V1*V1+V2*V2>=1);
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      return dim2::Point<double>(V1,V2);
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    }
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    /// A kind of two dimensional Gauss distribution
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    /// A kind of two dimensional normal (Gauss) distribution
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    /// This function provides a turning symmetric two-dimensional distribution.
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    /// Both coordinates are of standard normal distribution, but they are not
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    /// independent.
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