Attachment #2653 for bug #2513

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    plot.AppendExtra ("set xrange [0:2]");

    Ptr<ParetoRandomVariable> x1 = CreateObject<ParetoRandomVariable> ();
    x1->SetAttribute ("Scale", DoubleValue (1.0));
    x1->SetAttribute ("Shape", DoubleValue (1.5));

    plot.AddDataset ( Histogramm (x1, probes, precision,
                                  "ParetoRandomVariable scale=1.0 shape=1.5") );

    Ptr<ParetoRandomVariable> x2 = CreateObject<ParetoRandomVariable> ();
    x2->SetAttribute ("Scale", DoubleValue (1.0));
    x2->SetAttribute ("Shape", DoubleValue (2.0));

    plot.AddDataset ( Histogramm (x2, probes, precision,
                                  "ParetoRandomVariable scale=1.0 shape=2.0") );

    Ptr<ParetoRandomVariable> x3 = CreateObject<ParetoRandomVariable> ();
    x3->SetAttribute ("Scale", DoubleValue (1.0));
    x3->SetAttribute ("Shape", DoubleValue (2.5));

    plot.AddDataset ( Histogramm (x3, probes, precision,
                                  "ParetoRandomVariable scale=1.0 shape=2.5") );

    gnuplots.AddPlot (plot);
  }

    x1->SetAttribute ("Shape", DoubleValue (1.0));

    plot.AddDataset ( Histogramm (x1, probes, precision,
                                  "WeibullRandomVariable scale=1.0 shape=1.0") );

    Ptr<WeibullRandomVariable> x2 = CreateObject<WeibullRandomVariable> ();
    x2->SetAttribute ("Scale", DoubleValue (1.0));
    x2->SetAttribute ("Shape", DoubleValue (2.0));

    plot.AddDataset ( Histogramm (x2, probes, precision,
                                  "WeibullRandomVariable scale=1.0 shape=2.0") );

    Ptr<WeibullRandomVariable> x3 = CreateObject<WeibullRandomVariable> ();
    x3->SetAttribute ("Scale", DoubleValue (1.0));
    x3->SetAttribute ("Shape", DoubleValue (3.0));

    plot.AddDataset ( Histogramm (x3, probes, precision,
                                  "WeibullRandomVariable scale=1.0 shape=3.0") );

    gnuplots.AddPlot (plot);
  }




    plot.AppendExtra ("set xrange [0:2]");

    Ptr<ParetoRandomVariable> x1 = CreateObject<ParetoRandomVariable> ();
    x1->SetAttribute ("Scale", DoubleValue (1.0));
    x1->SetAttribute ("Shape", DoubleValue (1.5));

    plot.AddDataset ( Histogramm (x1, probes, precision,
                                  "ParetoRandomVariable scale=1.0 shape=1.5") );

    Ptr<ParetoRandomVariable> x2 = CreateObject<ParetoRandomVariable> ();
    x2->SetAttribute ("Scale", DoubleValue (1.0));
    x2->SetAttribute ("Shape", DoubleValue (2.0));

    plot.AddDataset ( Histogramm (x2, probes, precision,
                                  "ParetoRandomVariable scale=1.0 shape=2.0") );

    Ptr<ParetoRandomVariable> x3 = CreateObject<ParetoRandomVariable> ();
    x3->SetAttribute ("Scale", DoubleValue (1.0));
    x3->SetAttribute ("Shape", DoubleValue (2.5));

    plot.AddDataset ( Histogramm (x3, probes, precision,
                                  "ParetoRandomVariable scale=1.0 shape=2.5") );

    gnuplots.AddPlot (plot);
  }

    x1->SetAttribute ("Shape", DoubleValue (1.0));

    plot.AddDataset ( Histogramm (x1, probes, precision,
                                  "WeibullRandomVariable scale=1.0 shape=1.0") );

    Ptr<WeibullRandomVariable> x2 = CreateObject<WeibullRandomVariable> ();
    x2->SetAttribute ("Scale", DoubleValue (1.0));
    x2->SetAttribute ("Shape", DoubleValue (2.0));

    plot.AddDataset ( Histogramm (x2, probes, precision,
                                  "WeibullRandomVariable scale=1.0 shape=2.0") );

    Ptr<WeibullRandomVariable> x3 = CreateObject<WeibullRandomVariable> ();
    x3->SetAttribute ("Scale", DoubleValue (1.0));
    x3->SetAttribute ("Shape", DoubleValue (3.0));

    plot.AddDataset ( Histogramm (x3, probes, precision,
                                  "WeibullRandomVariable scale=1.0 shape=3.0") );

    gnuplots.AddPlot (plot);
  }

(-)a/src/core/model/random-variable-stream.cc (-13 / +30 lines)

Lines 33-38	Link Here

#include "log.h"

#include "log.h"

#include "rng-stream.h"

#include "rng-stream.h"

#include "rng-seed-manager.h"

#include "rng-seed-manager.h"

#include "unused.h"

#include <cmath>

#include <cmath>

#include <iostream>

#include <iostream>

Lines 455-463	Link Here

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    .SetGroupName ("Core")

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    .SetGroupName ("Core")

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    .AddConstructor<ParetoRandomVariable> ()

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    .AddConstructor<ParetoRandomVariable> ()

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    .AddAttribute("Mean", "The mean parameter for the Pareto distribution returned by this RNG stream.",

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    .AddAttribute("Mean", "The mean parameter for the Pareto distribution returned by this RNG stream.",

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		  DoubleValue(1.0),

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      DoubleValue(0.0),

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		  MakeDoubleAccessor(&ParetoRandomVariable::m_mean),

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      MakeDoubleAccessor(&ParetoRandomVariable::m_mean),

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		  MakeDoubleChecker<double>())

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      MakeDoubleChecker<double>(),

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      TypeId::DEPRECATED,

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      "Not anymore used. Use 'Scale' instead.")

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    .AddAttribute("Scale", "The scale parameter for the Pareto distribution returned by this RNG stream.",

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      DoubleValue(1.0),

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      MakeDoubleAccessor(&ParetoRandomVariable::m_scale),

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      MakeDoubleChecker<double>())

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    .AddAttribute("Shape", "The shape parameter for the Pareto distribution returned by this RNG stream.",

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    .AddAttribute("Shape", "The shape parameter for the Pareto distribution returned by this RNG stream.",

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		  DoubleValue(2.0),

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		  DoubleValue(2.0),

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		  MakeDoubleAccessor(&ParetoRandomVariable::m_shape),

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		  MakeDoubleAccessor(&ParetoRandomVariable::m_shape),

Lines 471-493	Link Here

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ParetoRandomVariable::ParetoRandomVariable ()

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ParetoRandomVariable::ParetoRandomVariable ()

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  // m_mean, m_shape, and m_bound are initialized after constructor

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  // m_shape, m_shape, and m_bound are initialized after constructor

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  // by attributes

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  // by attributes

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  NS_LOG_FUNCTION (this);

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  NS_LOG_FUNCTION (this);

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  NS_UNUSED (m_mean);

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double

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double

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ParetoRandomVariable::GetMean (void) const

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ParetoRandomVariable::GetMean (void) const

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  NS_LOG_FUNCTION (this);

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  NS_LOG_FUNCTION (this);

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  return m_mean;

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  double mean = std::numeric_limits<double>::infinity();

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  if (m_shape > 1)

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      mean = m_shape * m_scale / (m_shape -1);

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  return mean;

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double

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double

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ParetoRandomVariable::GetShape (void) const

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ParetoRandomVariable::GetShape (void) const

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  NS_LOG_FUNCTION (this);

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  NS_LOG_FUNCTION (this);

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  return m_shape;

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  return m_shape;

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double

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double

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ParetoRandomVariable::GetBound (void) const

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ParetoRandomVariable::GetBound (void) const

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Lines 496-506	Link Here

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double

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double

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ParetoRandomVariable::GetValue (double mean, double shape, double bound)

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ParetoRandomVariable::GetValue (double scale, double shape, double bound)

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  // Calculate the scale parameter.

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  // Calculate the scale parameter.

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  NS_LOG_FUNCTION (this << mean << shape << bound);

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  NS_LOG_FUNCTION (this << scale << shape << bound);

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  double scale = mean * (shape - 1.0) / shape;

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  while (1)

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  while (1)

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Lines 522-544	Link Here

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uint32_t

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uint32_t

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ParetoRandomVariable::GetInteger (uint32_t mean, uint32_t shape, uint32_t bound)

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ParetoRandomVariable::GetInteger (uint32_t scale, uint32_t shape, uint32_t bound)

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  NS_LOG_FUNCTION (this << mean << shape << bound);

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  NS_LOG_FUNCTION (this << scale << shape << bound);

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  return static_cast<uint32_t> ( GetValue (mean, shape, bound) );

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  return static_cast<uint32_t> ( GetValue (scale, shape, bound) );

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double

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double

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ParetoRandomVariable::GetValue (void)

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ParetoRandomVariable::GetValue (void)

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  NS_LOG_FUNCTION (this);

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  NS_LOG_FUNCTION (this);

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  return GetValue (m_mean, m_shape, m_bound);

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  return GetValue (m_scale, m_shape, m_bound);

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uint32_t

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uint32_t

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ParetoRandomVariable::GetInteger (void)

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ParetoRandomVariable::GetInteger (void)

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  NS_LOG_FUNCTION (this);

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  NS_LOG_FUNCTION (this);

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  return (uint32_t)GetValue (m_mean, m_shape, m_bound);

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  return (uint32_t)GetValue (m_scale, m_shape, m_bound);

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NS_OBJECT_ENSURE_REGISTERED(WeibullRandomVariable);

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NS_OBJECT_ENSURE_REGISTERED(WeibullRandomVariable);




  /**
   * \brief Get the next random value, as an unsigned integer from
   * the exponential distribution with the specified mean and upper bound.
   * \param [in] mean Mean value of the unbounded exponential distribution.
   * \param [in] bound Upper bound on values returned.
   * \return A random unsigned integer value.
   */

 * The probability density function of a Pareto variable is defined
 * over the range [\f$x_m\f$,\f$+\infty\f$) as: \f$ k \frac{x_m^k}{x^{k+1}}\f$
 * where \f$x_m > 0\f$ is called the scale parameter and \f$ k > 0\f$
 * is called the Pareto index or shape.
 *
 * The parameter \f$ x_m \f$ can be inferred from the mean and the parameter \f$ k \f$
 * with the equation \f$ x_m = mean \frac{k-1}{k},  k > 1\f$.
 *
 * Since Pareto distributions can theoretically return unbounded values,

 *
 * Here is an example of how to use this class:
 * \code
 *   double scale = 5.0;
 *   double shape = 2.0;
 * 
 *   Ptr<ParetoRandomVariable> x = CreateObject<ParetoRandomVariable> ();
 *   x->SetAttribute ("Scale", DoubleValue (scale));
 *   x->SetAttribute ("Shape", DoubleValue (shape));
 * 
 *   // The expected value for the mean of the values returned by a

 *   //                   shape * scale
 *   //     E[value]  =  ---------------  ,
 *   //                     shape - 1
 *
 *   // where
 *   // 
 *   //     scale  =  mean * (shape - 1.0) / shape .
 *   //
 *   double value = x->GetValue ();
 * \endcode
 */

   * \brief Returns the mean parameter for the Pareto distribution returned by this RNG stream.
   * \return The mean parameter for the Pareto distribution returned by this RNG stream.
   */
  NS_DEPRECATED
  double GetMean (void) const;

  /**
   * \brief Returns the scale parameter for the Pareto distribution returned by this RNG stream.
   * \return The scale parameter for the Pareto distribution returned by this RNG stream.
   */
  double GetScale (void) const;

  /**
   * \brief Returns the shape parameter for the Pareto distribution returned by this RNG stream.
   * \return The shape parameter for the Pareto distribution returned by this RNG stream.
   */

  double GetBound (void) const;

  /**
   * \brief Returns a random double from a Pareto distribution with the specified scale, shape, and upper bound.
   * \param [in] scale Mean parameter for the Pareto distribution.
   * \param [in] shape Shape parameter for the Pareto distribution.
   * \param [in] bound Upper bound on values returned.
   * \return A floating point random value.

   *         x = \frac{scale}{u^{\frac{1}{shape}}}
   *    \f]
   *
   * is a value that would be returned normally.
   *     
   *    \f[
   *         scale  =  mean * (shape - 1.0) / shape  .
   *    \f]
   *    
   * The value returned in the antithetic case, \f$x'\f$, is
   * \f$1\f$.  The value returned in the antithetic case, \f$x'\f$, is
   * calculated as
   *
   *    \f[
   *         x' = \frac{scale}{{(1 - u)}^{\frac{1}{shape}}} ,
   *    \f]
   *
   * which now involves the distance \f$u\f$ is from 1 in the denominator.
   */
  double GetValue (double scale, double shape, double bound);

  /**
   * \brief Returns a random unsigned integer from a Pareto distribution with the specified mean, shape, and upper bound.
   * \param [in] scale Scale parameter for the Pareto distribution.
   * \param [in] shape Shape parameter for the Pareto distribution.
   * \param [in] bound Upper bound on values returned.
   * \return A random unsigned integer value.

   *         x = \frac{scale}{u^{\frac{1}{shape}}}
   *    \f]
   *
   * is a value that would be returned normally.
   *
   * The value returned in the antithetic case, \f$x'\f$, is
   *         scale  =  mean * (shape - 1.0) / shape  .
   *    \f]
   *    
   * Then \f$(1 - u\f$) is the distance that \f$u\f$ would be from
   * \f$1\f$.  The value returned in the antithetic case, \f$x'\f$, is
   * calculated as
   *
   *    \f[
   *         x' = \frac{scale}{{(1 - u)}^{\frac{1}{shape}}} ,
   *    \f]
   *
   * which now involves the distance \f$u\f$ is from 1 in the denominator.
   */
  uint32_t GetInteger (uint32_t scale, uint32_t shape, uint32_t bound);

  /**
   * \brief Returns a random double from a Pareto distribution with the current mean, shape, and upper bound.

   *         scale  =  mean * (shape - 1.0) / shape  .
   *    \f]
   *    
   * The value returned in the antithetic case, \f$x'\f$, is
   * \f$1\f$.  The value returned in the antithetic case, \f$x'\f$, is
   * calculated as
   *
   *    \f[
   *         x' = \frac{scale}{{(1 - u)}^{\frac{1}{shape}}} ,
   *    \f]
   *
   * which now involves the distance \f$u\f$ is from 1 in the denominator.
   *
   * Note that we have to re-implement this method here because the method is
   * overloaded above for the three-argument variant and the c++ name resolution

   *         x = \frac{scale}{u^{\frac{1}{shape}}}
   *    \f]
   *
   * is a value that would be returned normally.
   *
   * The value returned in the antithetic case, \f$x'\f$, is
   *         scale  =  mean * (shape - 1.0) / shape  .
   *    \f]
   *    
   * Then \f$(1 - u\f$) is the distance that \f$u\f$ would be from
   * \f$1\f$.  The value returned in the antithetic case, \f$x'\f$, is
   * calculated as
   *
   *    \f[
   *         x' = \frac{scale}{{(1 - u)}^{\frac{1}{shape}}} ,
   *    \f]
   *
   * which now involves the distance \f$u\f$ is from 1 in the denominator.
   */
  virtual uint32_t GetInteger (void);


  /** The mean parameter for the Pareto distribution returned by this RNG stream. */
  double m_mean;

  /** The scale parameter for the Pareto distribution returned by this RNG stream. */
  double m_scale;

  /** The shape parameter for the Pareto distribution returned by this RNG stream. */
  double m_shape;






  double expected[N_BINS];

  // Note that this assumes that p has mean equal to 1 and shape equal
  // to 2, which are their default values for this distribution.
  double mean = 1.0;
  double shape = 2.0;
  double scale = 1.0;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {


  NS_TEST_ASSERT_MSG_LT (sum, maxStatistic, "Chi-squared statistic out of range");

  double mean = 5.0;
  double shape = 2.0;
  double scale = 1.0;
  double value;

  // Create the RNG with the specified range.
  Ptr<ParetoRandomVariable> x = CreateObject<ParetoRandomVariable> ();
  x->SetAttribute ("Mean", DoubleValue (mean));
  x->SetAttribute ("Shape", DoubleValue (shape));
  x->SetAttribute ("Scale", DoubleValue (scale));

  // Calculate the mean of these values.
  sum = 0.0;


  double expected[N_BINS];

  // Note that this assumes that p has mean equal to 1 and shape equal
  // to 2, which are their default values for this distribution.
  double mean = 1.0;
  double shape = 2.0;
  double scale = 1.0;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {


  NS_TEST_ASSERT_MSG_LT (sum, maxStatistic, "Chi-squared statistic out of range");

  double mean = 5.0;
  double shape = 2.0;
  double scale = 1.0;
  double value;

  // Create the RNG with the specified range.
  Ptr<ParetoRandomVariable> x = CreateObject<ParetoRandomVariable> ();
  x->SetAttribute ("Mean", DoubleValue (mean));
  x->SetAttribute ("Shape", DoubleValue (shape));
  x->SetAttribute ("Scale", DoubleValue (scale));

  // Make this generate antithetic values.
  x->SetAttribute ("Antithetic", BooleanValue (true));

(-)a/src/core/test/rng-test-suite.cc (+1 lines)

Lines 408-413	Link Here

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      Ptr<ParetoRandomVariable> e = CreateObject<ParetoRandomVariable> ();

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      Ptr<ParetoRandomVariable> e = CreateObject<ParetoRandomVariable> ();

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      e->SetAttribute ("Shape", DoubleValue (1.5));

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      e->SetAttribute ("Shape", DoubleValue (1.5));

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      e->SetAttribute ("Scale", DoubleValue (0.33333333));

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      double result = ChiSquaredTest (e);

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      double result = ChiSquaredTest (e);

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      sum += result;

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      sum += result;

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