math_util.cc

经网络提出了一种基于蚁群聚类算法的径向基神经网络. 利用蚁群算法的并行寻优特征和挥发系数方法的自适应更改信息量的能力,并以球面聚类的方式确定了径向基神经网络中基函数的位置, 同时通过比较隐层神经元的相

/* $Id: math_util.cc,v 1.3 2006-08-09 15:20:54 jonathan Exp $
 * Jonathan Ledlie, Harvard University.
 * Copyright 2005.  All rights reserved.
 */

#include <assert.h>
#include "math_util.h"

double poisson (double mean)
{
  double u;
  while ((u = randPct()) == 0.)
	  ;
  return (-mean) * log(u);
};

int poisson (int mean)
{
  return (int)(poisson((double)mean));
}

double mean (vector<double> v) 
{
  double sum = 0.;
  for (int i = 0; i < v.size(); i++) 
  {
    sum += v[i];
  }
  return sum/(double)v.size();
}

double square (double x)
{
  return x*x;
}

double stddev (vector<double> v, double mean) 
{
  double sum = 0.;
  if (v.size() <= 1) return 0.;
  for (int i = 0; i < v.size(); i++) 
  {
    sum += pow(v[i]-mean,2);
  }
  return sqrt (sum/(v.size()-1));
}

double percentile (vector<double> v, double percentile) 
{

  //cout << "size " << v.size() << " pct " << percentile << endl;

  if (v.size() == 0)   
  {
    return 0;
  }
  if (v.size() == 1) 
  {
    return v[0];
  }
  sort (v.begin(), v.end());

  assert (percentile >= 0 && percentile <= 1);
  int index = (int)(rint (percentile * v.size()));

  //cout << "size " << v.size() << " pct " << percentile 
  //<< " index " << index << " v[i] " << v[index] << endl;

  return v[index];
}

//返回0－1之间的随机数
double randPct () 
{
  double ret = Rand ();
  assert (ret >= 0. && ret < 1);
  return ret;
}

// Returns a number (a,b]
int unifRand (int a, int b)
{
  assert (a >= 0 && b >= 0);
  int diff = ABS ((a-b));
  int randValue = (int)(Rand()*(double)diff);
  return (int)(a + randValue);
}

// Returns a list of numbers (a,b]
vector<int> unifRands (int count, int a, int b)
{
  vector<int> rands;
  rands.reserve (count);
  for (int i = 0; i < count; i++)
  {
    rands.push_back (unifRand (a, b));
  }
  return rands;
}


double log16 (double x)
{
  const double logOf16 = log(16.);
  return log(x)/logOf16;
}

double log8 (double x)
{
  const double logOf8 = log(8.);
  return log(x)/logOf8;
}