/* -*- Mode:C++; c-file-style:"gnu"; indent-tabs-mode:nil; -*- */
/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License version 2 as
 * published by the Free Software Foundation;
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 */


#include <math.h>
#include <gsl/gsl_cdf.h>
#include <gsl/gsl_histogram.h>
#include <time.h>
#include <fstream>

#include "test.h"
#include "random-variable.h"

using namespace ns3;

void
FillHistoRangeUniformly (double *array, uint32_t n, double start, double end)
{
  double increment = (end - start) / (n - 1.);
  double d = start;
  
  for (uint32_t i = 0; i < n; ++i)
    {
      array[i] = d;
      d += increment;
    }
}

// ===========================================================================
// Test case for uniform distribution random number generator
// ===========================================================================
class RngUniformTestCase : public TestCase
{
public:
  static const uint32_t N_RUNS = 5;
  static const uint32_t N_BINS = 50;
  static const uint32_t N_MEASUREMENTS = 1000000;

  RngUniformTestCase ();
  virtual ~RngUniformTestCase ();

  double ChiSquaredTest (UniformVariable &u);

private:
  virtual bool DoRun (void);
};

RngUniformTestCase::RngUniformTestCase ()
  : TestCase ("Uniform Random Number Generator")
{
}

RngUniformTestCase::~RngUniformTestCase ()
{
}

double
RngUniformTestCase::ChiSquaredTest (UniformVariable &u)
{
  gsl_histogram * h = gsl_histogram_alloc (N_BINS);
  gsl_histogram_set_ranges_uniform (h, 0., 1.);

  for (uint32_t i = 0; i < N_MEASUREMENTS; ++i)
    {
      gsl_histogram_increment (h, u.GetValue ());
    }

  double tmp[N_BINS];

  double expected = ((double)N_MEASUREMENTS / (double)N_BINS);

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      tmp[i] = gsl_histogram_get (h, i);
      tmp[i] -= expected;
      tmp[i] *= tmp[i];
      tmp[i] /= expected;
    }

  gsl_histogram_free (h);

  double chiSquared = 0;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      chiSquared += tmp[i];
    }
  
  return chiSquared;
}

bool
RngUniformTestCase::DoRun (void)
{
  SeedManager::SetSeed (time (0));

  double sum = 0.;
  double maxStatistic = gsl_cdf_chisq_Qinv (0.05, N_BINS);

  for (uint32_t i = 0; i < N_RUNS; ++i)
    {
      UniformVariable u;
      double result = ChiSquaredTest (u);
      sum += result;
    }

  sum /= (double)N_RUNS;

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

// ===========================================================================
// Test case for normal distribution random number generator
// ===========================================================================
class RngNormalTestCase : public TestCase
{
public:
  static const uint32_t N_RUNS = 5;
  static const uint32_t N_BINS = 50;
  static const uint32_t N_MEASUREMENTS = 1000000;

  RngNormalTestCase ();
  virtual ~RngNormalTestCase ();

  double ChiSquaredTest (NormalVariable &n);

private:
  virtual bool DoRun (void);
};

RngNormalTestCase::RngNormalTestCase ()
  : TestCase ("Normal Random Number Generator")
{
}

RngNormalTestCase::~RngNormalTestCase ()
{
}

double
RngNormalTestCase::ChiSquaredTest (NormalVariable &n)
{
  gsl_histogram * h = gsl_histogram_alloc (N_BINS);

  double range[N_BINS + 1];
  FillHistoRangeUniformly (range, N_BINS + 1, -4., 4.);
  range[0] = -std::numeric_limits<double>::max ();
  range[N_BINS] = std::numeric_limits<double>::max ();

  gsl_histogram_set_ranges (h, range, N_BINS + 1);

  double expected[N_BINS];

  double sigma = 1.;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      expected[i] = gsl_cdf_gaussian_P (range[i + 1], sigma) - gsl_cdf_gaussian_P (range[i], sigma);
      expected[i] *= N_MEASUREMENTS;
    }

  for (uint32_t i = 0; i < N_MEASUREMENTS; ++i)
    {
      gsl_histogram_increment (h, n.GetValue ());
    }

  double tmp[N_BINS];

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      tmp[i] = gsl_histogram_get (h, i);
      tmp[i] -= expected[i];
      tmp[i] *= tmp[i];
      tmp[i] /= expected[i];
    }

  gsl_histogram_free (h);

  double chiSquared = 0;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      chiSquared += tmp[i];
    }
  
  return chiSquared;
}

bool
RngNormalTestCase::DoRun (void)
{
  SeedManager::SetSeed (time (0));

  double sum = 0.;
  double maxStatistic = gsl_cdf_chisq_Qinv (0.05, N_BINS);

  for (uint32_t i = 0; i < N_RUNS; ++i)
    {
      NormalVariable n;
      double result = ChiSquaredTest (n);
      sum += result;
    }

  sum /= (double)N_RUNS;

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

// ===========================================================================
// Test case for exponential distribution random number generator
// ===========================================================================
class RngExponentialTestCase : public TestCase
{
public:
  static const uint32_t N_RUNS = 5;
  static const uint32_t N_BINS = 50;
  static const uint32_t N_MEASUREMENTS = 1000000;

  RngExponentialTestCase ();
  virtual ~RngExponentialTestCase ();

  double ChiSquaredTest (ExponentialVariable &n);

private:
  virtual bool DoRun (void);
};

RngExponentialTestCase::RngExponentialTestCase ()
  : TestCase ("Exponential Random Number Generator")
{
}

RngExponentialTestCase::~RngExponentialTestCase ()
{
}

double
RngExponentialTestCase::ChiSquaredTest (ExponentialVariable &e)
{
  gsl_histogram * h = gsl_histogram_alloc (N_BINS);

  double range[N_BINS + 1];
  FillHistoRangeUniformly (range, N_BINS + 1, 0., 10.);
  range[N_BINS] = std::numeric_limits<double>::max ();

  gsl_histogram_set_ranges (h, range, N_BINS + 1);

  double expected[N_BINS];

  double mu = 1.;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      expected[i] = gsl_cdf_exponential_P (range[i + 1], mu) - gsl_cdf_exponential_P (range[i], mu);
      expected[i] *= N_MEASUREMENTS;
    }

  for (uint32_t i = 0; i < N_MEASUREMENTS; ++i)
    {
      gsl_histogram_increment (h, e.GetValue ());
    }

  double tmp[N_BINS];

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      tmp[i] = gsl_histogram_get (h, i);
      tmp[i] -= expected[i];
      tmp[i] *= tmp[i];
      tmp[i] /= expected[i];
    }

  gsl_histogram_free (h);

  double chiSquared = 0;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      chiSquared += tmp[i];
    }
  
  return chiSquared;
}

bool
RngExponentialTestCase::DoRun (void)
{
  SeedManager::SetSeed (time (0));

  double sum = 0.;
  double maxStatistic = gsl_cdf_chisq_Qinv (0.05, N_BINS);

  for (uint32_t i = 0; i < N_RUNS; ++i)
    {
      ExponentialVariable e;
      double result = ChiSquaredTest (e);
      sum += result;
    }

  sum /= (double)N_RUNS;

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

// ===========================================================================
// Test case for pareto distribution random number generator
// ===========================================================================
class RngParetoTestCase : public TestCase
{
public:
  static const uint32_t N_RUNS = 5;
  static const uint32_t N_BINS = 50;
  static const uint32_t N_MEASUREMENTS = 1000000;

  RngParetoTestCase ();
  virtual ~RngParetoTestCase ();

  double ChiSquaredTest (ParetoVariable &p);

private:
  virtual bool DoRun (void);
};

RngParetoTestCase::RngParetoTestCase ()
  : TestCase ("Pareto Random Number Generator")
{
}

RngParetoTestCase::~RngParetoTestCase ()
{
}

double
RngParetoTestCase::ChiSquaredTest (ParetoVariable &p)
{
  gsl_histogram * h = gsl_histogram_alloc (N_BINS);

  double range[N_BINS + 1];
  FillHistoRangeUniformly (range, N_BINS + 1, 1., 10.);
  range[N_BINS] = std::numeric_limits<double>::max ();

  gsl_histogram_set_ranges (h, range, N_BINS + 1);

  double expected[N_BINS];

  double a = 1.5;
  double b = 0.33333333;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      expected[i] = gsl_cdf_pareto_P (range[i + 1], a, b) - gsl_cdf_pareto_P (range[i], a, b);
      expected[i] *= N_MEASUREMENTS;
    }

  for (uint32_t i = 0; i < N_MEASUREMENTS; ++i)
    {
      gsl_histogram_increment (h, p.GetValue ());
    }

  double tmp[N_BINS];

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      tmp[i] = gsl_histogram_get (h, i);
      tmp[i] -= expected[i];
      tmp[i] *= tmp[i];
      tmp[i] /= expected[i];
    }

  gsl_histogram_free (h);

  double chiSquared = 0;

  for (uint32_t i = 0; i < N_BINS; ++i)
    {
      chiSquared += tmp[i];
    }
  
  return chiSquared;
}

bool
RngParetoTestCase::DoRun (void)
{
  SeedManager::SetSeed (time (0));

  double sum = 0.;
  double maxStatistic = gsl_cdf_chisq_Qinv (0.05, N_BINS);

  for (uint32_t i = 0; i < N_RUNS; ++i)
    {
      ParetoVariable e;
      double result = ChiSquaredTest (e);
      sum += result;
    }

  sum /= (double)N_RUNS;

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

class RngTestSuite : public TestSuite
{
public:
  RngTestSuite ();
};

RngTestSuite::RngTestSuite ()
  : TestSuite ("random-number-generators", UNIT)
{
  AddTestCase (new RngUniformTestCase);
  AddTestCase (new RngNormalTestCase);
  AddTestCase (new RngExponentialTestCase);
  AddTestCase (new RngParetoTestCase);
}

RngTestSuite rngTestSuite;
