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Update of /cvsroot/echempp/Analysis/Classification
In directory sc8-pr-cvs17.sourceforge.net:/tmp/cvs-serv29098/Analysis/Classification

Modified Files:
	Makefile.am 
Added Files:
	svm.cpp svm.h 
Log Message:
svm add-on


Index: Makefile.am
===================================================================
RCS file: /cvsroot/echempp/Analysis/Classification/Makefile.am,v
retrieving revision 1.5
retrieving revision 1.6
diff -C2 -d -r1.5 -r1.6
*** Makefile.am	5 Mar 2007 19:49:50 -0000	1.5
--- Makefile.am	19 Dec 2007 13:21:03 -0000	1.6
***************
*** 9,16 ****
  	result.cpp \
  	result.h \
! 	tool.h
  #libeppClassification_la_CXXFLAGS =
  
! libeppClassification_la_LDFLAGS = $(ANALYSIS_LDFLAGS) -version-info 0:0:0
  
  doc:
--- 9,18 ----
  	result.cpp \
  	result.h \
! 	tool.h \
! 	svm.cpp \
! 	svm.h
  #libeppClassification_la_CXXFLAGS =
  
! libeppClassification_la_LDFLAGS = -lm $(ANALYSIS_LDFLAGS) -version-info 0:0:0
  
  doc:

--- NEW FILE: svm.cpp ---
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <ctype.h>
#include <float.h>
#include <string.h>
#include <stdarg.h>
#include "svm.h"
typedef float Qfloat;
typedef signed char schar;
#ifndef min
template <class T> inline T min(T x,T y) { return (x<y)?x:y; }
#endif
#ifndef max
template <class T> inline T max(T x,T y) { return (x>y)?x:y; }
#endif
template <class T> inline void swap(T& x, T& y) { T t=x; x=y; y=t; }
template <class S, class T> inline void clone(T*& dst, S* src, int n)
{
[...3012 lines suppressed...]
					free(label);
					free(count);
					return "specified nu is infeasible";
				}
			}
		}
		free(label);
		free(count);
	}

	return NULL;
}

int svm_check_probability_model(const svm_model *model)
{
	return ((model->param.svm_type == C_SVC || model->param.svm_type == NU_SVC) &&
		model->probA!=NULL && model->probB!=NULL) ||
		((model->param.svm_type == EPSILON_SVR || model->param.svm_type == NU_SVR) &&
		 model->probA!=NULL);
}

--- NEW FILE: svm.h ---
#ifndef _LIBSVM_H
#define _LIBSVM_H

#ifdef __cplusplus
extern "C" {
#endif

struct svm_node
{
	int index;
	double value;
};

struct svm_problem
{
	int l;
	double *y;
	struct svm_node **x;
};

enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR };	/* svm_type */
enum { LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED }; /* kernel_type */

struct svm_parameter
{
	int svm_type;
	int kernel_type;
	int degree;	/* for poly */
	double gamma;	/* for poly/rbf/sigmoid */
	double coef0;	/* for poly/sigmoid */

	/* these are for training only */
	double cache_size; /* in MB */
	double eps;	/* stopping criteria */
	double C;	/* for C_SVC, EPSILON_SVR and NU_SVR */
	int nr_weight;		/* for C_SVC */
	int *weight_label;	/* for C_SVC */
	double* weight;		/* for C_SVC */
	double nu;	/* for NU_SVC, ONE_CLASS, and NU_SVR */
	double p;	/* for EPSILON_SVR */
	int shrinking;	/* use the shrinking heuristics */
	int probability; /* do probability estimates */
};

//
// svm_model
//
struct svm_model
{
	svm_parameter param;	// parameter
	int nr_class;		// number of classes, = 2 in regression/one class svm
	int l;			// total #SV
	svm_node **SV;		// SVs (SV[l])
	double **sv_coef;	// coefficients for SVs in decision functions (sv_coef[n-1][l])
	double *rho;		// constants in decision functions (rho[n*(n-1)/2])
	double *probA;          // pariwise probability information
	double *probB;

	// for classification only

	int *label;		// label of each class (label[n])
	int *nSV;		// number of SVs for each class (nSV[n])
				// nSV[0] + nSV[1] + ... + nSV[n-1] = l
	// XXX
	int free_sv;		// 1 if svm_model is created by svm_load_model
				// 0 if svm_model is created by svm_train
};

struct svm_model *svm_train(const struct svm_problem *prob, const struct svm_parameter *param);
void svm_cross_validation(const struct svm_problem *prob, const struct svm_parameter *param, int nr_fold, double *target);

int svm_save_model(const char *model_file_name, const struct svm_model *model);
struct svm_model *svm_load_model(const char *model_file_name);

int svm_get_svm_type(const struct svm_model *model);
int svm_get_nr_class(const struct svm_model *model);
void svm_get_labels(const struct svm_model *model, int *label);
double svm_get_svr_probability(const struct svm_model *model);

void svm_predict_values(const struct svm_model *model, const struct svm_node *x, double* dec_values);
double svm_predict(const struct svm_model *model, const struct svm_node *x);
double svm_predict_probability(const struct svm_model *model, const struct svm_node *x, double* prob_estimates);

void svm_destroy_model(struct svm_model *model);
void svm_destroy_param(struct svm_parameter *param);

const char *svm_check_parameter(const struct svm_problem *prob, const struct svm_parameter *param);
int svm_check_probability_model(const struct svm_model *model);

#ifdef __cplusplus
}
#endif

#endif /* _LIBSVM_H */

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