statistics.h

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/* statistics.h
 * 
 * Copyright (C) 2009 Marcel Schumann
 * 
 * This file is part of QuEasy -- A Toolbox for Automated QSAR Model
 * Construction and Validation.
 * QuEasy is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or (at
 * your option) any later version.
 * 
 * QuEasy 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, see <http://www.gnu.org/licenses/>.
 */

// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
// 

#ifndef STATISTICS
#define STATISTICS

#include <vector>
#include <iostream>
#include <BALL/MATHS/LINALG/matrix.h>
#include <cmath>
#include <BALL/MATHS/parsedFunction.h>

#include <set>

namespace BALL 
{
  namespace QSAR
  {
    class BALL_EXPORT Statistics
    {
      public:
        Statistics(){};
        
        ~Statistics(){};
        
        
        
        static void scaling(std::vector<double>& v);
  
        static void scaling(std::vector<std::vector<double> >& m);
  
        static void centering(std::vector<std::vector<double> >& m);
        
        static void centering(std::vector<double>& v);
        
        static void centering(vector<double>& v, double& mean, double& std);
        
        static double getVariance(const std::vector<double>& v, double mean=-1);
        
        static double getStddev(const vector<double>& v, double mean=-1);
        
        static double getCovariance(const vector<double>& v1, const vector<double>& v2, double mean1, double mean2);
  
        static double getMean(const std::vector<double>& v);
  
        
        //--- methods for calculating mean, covar, var of matrix-ROWS ---
        
        static double getRowCovariance(const vector<vector<double> >& v, int row1, int row2, double mean1=-1, double mean2=-1, std::multiset<int>* features_to_use=0);
        
        static double getRowMean(const vector<vector<double> >& v, int row, std::multiset<int>* features_to_use=0);
        
        static double getRowVariance(const vector<vector<double> >& v, int row, double mean=-1, std::multiset<int>* features_to_use=0);
        
        static double getRowStddev(const vector<vector<double> >& v, int row, double mean=-1, std::multiset<int>* features_to_use=0);
                
        //  ------------------------
        
        
        static void centering(BALL::Matrix<double>& m);
  
        static void centering(BALL::Matrix<double>& m, int col);
  
        static double getMean(const BALL::Matrix<double>& m, int col);
  
        static double getVariance(const BALL::Matrix<double>& m, int col, double mean=-1);
        
        static double getStddev(const BALL::Matrix<double>& m, int col, double mean=-1);
        
        static double getCovariance(const BALL::Matrix<double>& m, int col1, int col2, double mean1=-1, double mean2=-1);
        
        static double sq(const BALL::Matrix<double>& m, int col, double mean=-1);
        
        static double distance(const BALL::Matrix<double>& m, int& row1, int& row2, double& p);
        
        static double distance(const BALL::Matrix<double>& m1, const BALL::Matrix<double>& m2, int& row1, int& row2, double& p);

        
        static double distance(const BALL::Matrix<double>& m1, const BALL::Matrix<double>& m2, int& row1, int& row2, String& f, String& g);
        
        
        static double euclDistance(const BALL::Matrix<double>& m1, const BALL::Matrix<double>& m2, int row1, int row2);
        
        static double euclNorm(const Vector<double>& cv);
    
        static double euclDistance(const Vector<double>& c1, const Vector<double>& c2);
        
        static double scalarProduct(const Vector<double>& cv);
    
    };
  }
}


#endif // STATISTICS

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