#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 mintemplate <class T> inline T min(T x,T y) { return (x<y)?x:y; }#endif#ifndef maxtemplate <class T> inline T max(T x,T y) { return (x>y)?x:y; }#endiftemplate <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){	dst = new T[n];	memcpy((void *)dst,(void *)src,sizeof(T)*n);}inline double powi(double base, int times){        double tmp = base, ret = 1.0;        for(int t=times; t>0; t/=2)	{                if(t%2==1) ret*=tmp;                tmp = tmp * tmp;        }        return ret;}#define INF HUGE_VAL#define TAU 1e-12#define Malloc(type,n) (type *)malloc((n)*sizeof(type))#if 1void info(const char *fmt,...){	va_list ap;	va_start(ap,fmt);	vprintf(fmt,ap);	va_end(ap);}void info_flush(){	fflush(stdout);}#elsevoid info(char *fmt,...) {}void info_flush() {}#endif//// Kernel Cache//// l is the number of total data items// size is the cache size limit in bytes//class Cache{public:	Cache(int l,long int size);	~Cache();	// request data [0,len)	// return some position p where [p,len) need to be filled	// (p >= len if nothing needs to be filled)	int get_data(const int index, Qfloat **data, int len);	void swap_index(int i, int j);	// future_optionprivate:	int l;	long int size;	struct head_t	{		head_t *prev, *next;	// a cicular list		Qfloat *data;		int len;		// data[0,len) is cached in this entry	};	head_t *head;	head_t lru_head;	void lru_delete(head_t *h);	void lru_insert(head_t *h);};Cache::Cache(int l_,long int size_):l(l_),size(size_){	head = (head_t *)calloc(l,sizeof(head_t));	// initialized to 0	size /= sizeof(Qfloat);	size -= l * sizeof(head_t) / sizeof(Qfloat);	size = max(size, 2 * (long int) l);	// cache must be large enough for two columns	lru_head.next = lru_head.prev = &lru_head;}Cache::~Cache(){	for(head_t *h = lru_head.next; h != &lru_head; h=h->next)		free(h->data);	free(head);}void Cache::lru_delete(head_t *h){	// delete from current location	h->prev->next = h->next;	h->next->prev = h->prev;}void Cache::lru_insert(head_t *h){	// insert to last position	h->next = &lru_head;	h->prev = lru_head.prev;	h->prev->next = h;	h->next->prev = h;}int Cache::get_data(const int index, Qfloat **data, int len){	head_t *h = &head[index];	if(h->len) lru_delete(h);	int more = len - h->len;	if(more > 0)	{		// free old space		while(size < more)		{			head_t *old = lru_head.next;			lru_delete(old);			free(old->data);			size += old->len;			old->data = 0;			old->len = 0;		}		// allocate new space		h->data = (Qfloat *)realloc(h->data,sizeof(Qfloat)*len);		size -= more;		swap(h->len,len);	}	lru_insert(h);	*data = h->data;	return len;}void Cache::swap_index(int i, int j){	if(i==j) return;	if(head[i].len) lru_delete(&head[i]);	if(head[j].len) lru_delete(&head[j]);	swap(head[i].data,head[j].data);	swap(head[i].len,head[j].len);	if(head[i].len) lru_insert(&head[i]);	if(head[j].len) lru_insert(&head[j]);	if(i>j) swap(i,j);	for(head_t *h = lru_head.next; h!=&lru_head; h=h->next)	{		if(h->len > i)		{			if(h->len > j)				swap(h->data[i],h->data[j]);			else			{				// give up				lru_delete(h);				free(h->data);				size += h->len;				h->data = 0;				h->len = 0;			}		}	}}//// Kernel evaluation//// the static method k_function is for doing single kernel evaluation// the constructor of Kernel prepares to calculate the l*l kernel matrix// the member function get_Q is for getting one column from the Q Matrix//class QMatrix {public:	virtual Qfloat *get_Q(int column, int len) const = 0;	virtual Qfloat *get_QD() const = 0;	virtual void swap_index(int i, int j) const = 0;	virtual ~QMatrix() {}};class Kernel: public QMatrix {public:	Kernel(int l, svm_node * const * x, const svm_parameter& param);	virtual ~Kernel();	static double k_function(const svm_node *x, const svm_node *y,				 const svm_parameter& param);	virtual Qfloat *get_Q(int column, int len) const = 0;	virtual Qfloat *get_QD() const = 0;	virtual void swap_index(int i, int j) const	// no so const...	{		swap(x[i],x[j]);		if(x_square) swap(x_square[i],x_square[j]);	}protected:	double (Kernel::*kernel_function)(int i, int j) const;private:	const svm_node **x;	double *x_square;	// svm_parameter	const int kernel_type;	const int degree;	const double gamma;	const double coef0;	static double dot(const svm_node *px, const svm_node *py);	double kernel_linear(int i, int j) const	{		return dot(x[i],x[j]);	}	double kernel_poly(int i, int j) const	{		return powi(gamma*dot(x[i],x[j])+coef0,degree);	}	double kernel_rbf(int i, int j) const	{		return exp(-gamma*(x_square[i]+x_square[j]-2*dot(x[i],x[j])));	}	double kernel_sigmoid(int i, int j) const	{		return tanh(gamma*dot(x[i],x[j])+coef0);	}	double kernel_precomputed(int i, int j) const	{		return x[i][(int)(x[j][0].value)].value;	}};Kernel::Kernel(int l, svm_node * const * x_, const svm_parameter& param):kernel_type(param.kernel_type), degree(param.degree), gamma(param.gamma), coef0(param.coef0){	switch(kernel_type)	{		case LINEAR:			kernel_function = &Kernel::kernel_linear;			break;		case POLY:			kernel_function = &Kernel::kernel_poly;			break;		case RBF:			kernel_function = &Kernel::kernel_rbf;			break;		case SIGMOID:			kernel_function = &Kernel::kernel_sigmoid;			break;		case PRECOMPUTED:			kernel_function = &Kernel::kernel_precomputed;			break;	}	clone(x,x_,l);	if(kernel_type == RBF)	{		x_square = new double[l];		for(int i=0;i<l;i++)			x_square[i] = dot(x[i],x[i]);	}	else		x_square = 0;}Kernel::~Kernel(){	delete[] x;	delete[] x_square;}double Kernel::dot(const svm_node *px, const svm_node *py){	double sum = 0;	while(px->index != -1 && py->index != -1)	{		if(px->index == py->index)		{			sum += px->value * py->value;			++px;			++py;		}		else		{			if(px->index > py->index)				++py;			else				++px;		}				}	return sum;}double Kernel::k_function(const svm_node *x, const svm_node *y,			  const svm_parameter& param){	switch(param.kernel_type)	{		case LINEAR:			return dot(x,y);		case POLY:			return powi(param.gamma*dot(x,y)+param.coef0,param.degree);		case RBF:		{			double sum = 0;			while(x->index != -1 && y->index !=-1)			{				if(x->index == y->index)				{					double d = x->value - y->value;					sum += d*d;					++x;					++y;				}				else				{					if(x->index > y->index)					{							sum += y->value * y->value;						++y;					}					else					{						sum += x->value * x->value;						++x;					}				}			}			while(x->index != -1)			{				sum += x->value * x->value;				++x;			}			while(y->index != -1)			{				sum += y->value * y->value;				++y;			}						return exp(-param.gamma*sum);		}		case SIGMOID:			return tanh(param.gamma*dot(x,y)+param.coef0);		case PRECOMPUTED:  //x: test (validation), y: SV			return x[(int)(y->value)].value;		default:			return 0;  // Unreachable 	}}// An SMO algorithm in Fan et al., JMLR 6(2005), p. 1889--1918// Solves:////	min 0.5(\alpha^T Q \alpha) + p^T \alpha////		y^T \alpha = \delta//		y_i = +1 or -1//		0 <= alpha_i <= Cp for y_i = 1//		0 <= alpha_i <= Cn for y_i = -1//// Given:////	Q, p, y, Cp, Cn, and an initial feasible point \alpha//	l is the size of vectors and matrices//	eps is the stopping tolerance//// solution will be put in \alpha, objective value will be put in obj//class Solver {public:	Solver() {};	virtual ~Solver() {};	struct SolutionInfo {		double obj;		double rho;		double upper_bound_p;		double upper_bound_n;		double r;	// for Solver_NU	};	void Solve(int l, const QMatrix& Q, const double *p_, const schar *y_,		   double *alpha_, double Cp, double Cn, double eps,		   SolutionInfo* si, int shrinking);protected:	int active_size;	schar *y;	double *G;		// gradient of objective function	enum { LOWER_BOUND, UPPER_BOUND, FREE };	char *alpha_status;	// LOWER_BOUND, UPPER_BOUND, FREE	double *alpha;	const QMatrix *Q;	const Qfloat *QD;	double eps;	double Cp,Cn;	double *p;	int *active_set;	double *G_bar;		// gradient, if we treat free variables as 0	int l;	bool unshrinked;	// XXX	double get_C(int i)	{		return (y[i] > 0)? Cp : Cn;	}	void update_alpha_status(int i)	{		if(alpha[i] >= get_C(i))			alpha_status[i] = UPPER_BOUND;		else if(alpha[i] <= 0)			alpha_status[i] = LOWER_BOUND;		else alpha_status[i] = FREE;	}	bool is_upper_bound(int i) { return alpha_status[i] == UPPER_BOUND; }	bool is_lower_bound(int i) { return alpha_status[i] == LOWER_BOUND; }	bool is_free(int i) { return alpha_status[i] == FREE; }	void swap_index(int i, int j);	void reconstruct_gradient();	virtual int select_working_set(int &i, int &j);	virtual double calculate_rho();	virtual void do_shrinking();private:	bool be_shrunken(int i, double Gmax1, double Gmax2);	};void Solver::swap_index(int i, int j){	Q->swap_index(i,j);	swap(y[i],y[j]);	swap(G[i],G[j]);	swap(alpha_status[i],alpha_status[j]);	swap(alpha[i],alpha[j]);	swap(p[i],p[j]);	swap(active_set[i],active_set[j]);	swap(G_bar[i],G_bar[j]);}void Solver::reconstruct_gradient(){	// reconstruct inactive elements of G from G_bar and free variables	if(active_size == l) return;	int i;	for(i=active_size;i<l;i++)		G[i] = G_bar[i] + p[i];		for(i=0;i<active_size;i++)		if(is_free(i))		{			const Qfloat *Q_i = Q->get_Q(i,l);			double alpha_i = alpha[i];			for(int j=active_size;j<l;j++)				G[j] += alpha_i * Q_i[j];		}}void Solver::Solve(int l, const QMatrix& Q, const double *p_, const schar *y_,		   double *alpha_, double Cp, double Cn, double eps,		   SolutionInfo* si, int shrinking){	this->l = l;	this->Q = &Q;	QD=Q.get_QD();	clone(p, p_,l);	clone(y, y_,l);	clone(alpha,alpha_,l);	this->Cp = Cp;	this->Cn = Cn;	this->eps = eps;	unshrinked = false;	// initialize alpha_status	{		alpha_status = new char[l];		for(int i=0;i<l;i++)			update_alpha_status(i);	}	// initialize active set (for shrinking)	{		active_set = new int[l];		for(int i=0;i<l;i++)			active_set[i] = i;		active_size = l;	}	// initialize gradient	{		G = new double[l];		G_bar = new double[l];		int i;		for(i=0;i<l;i++)		{			G[i] = p[i];			G_bar[i] = 0;		}		for(i=0;i<l;i++)			if(!is_lower_bound(i))			{				const Qfloat *Q_i = Q.get_Q(i,l);				double alpha_i = alpha[i];				int j;				for(j=0;j<l;j++)					G[j] += alpha_i*Q_i[j];				if(is_upper_bound(i))					for(j=0;j<l;j++)						G_bar[j] += get_C(i) * Q_i[j];			}	}	// optimization step	int iter = 0;	int counter = min(l,1000)+1;	while(1)	{		// show progress and do shrinking		if(--counter == 0)		{			counter = min(l,1000);			if(shrinking) do_shrinking();			info("."); info_flush();		}		int i,j;		if(select_working_set(i,j)!=0)		{			// reconstruct the whole gradient			reconstruct_gradient();			// reset active set size and check			active_size = l;			info("*"); info_flush();			if(select_working_set(i,j)!=0)				break;			else				counter = 1;	// do shrinking next iteration		}				++iter;		// update alpha[i] and alpha[j], handle bounds carefully				const Qfloat *Q_i = Q.get_Q(i,active_size);		const Qfloat *Q_j = Q.get_Q(j,active_size);		double C_i = get_C(i);		double C_j = get_C(j);		double old_alpha_i = alpha[i];		double old_alpha_j = alpha[j];		if(y[i]!=y[j])		{			double quad_coef = Q_i[i]+Q_j[j]+2*Q_i[j];			if (quad_coef <= 0)				quad_coef = TAU;			double delta = (-G[i]-G[j])/quad_coef;			double diff = alpha[i] - alpha[j];			alpha[i] += delta;			alpha[j] += delta;						if(diff > 0)			{				if(alpha[j] < 0)				{					alpha[j] = 0;					alpha[i] = diff;				}			}			else			{				if(alpha[i] < 0)				{					alpha[i] = 0;					alpha[j] = -diff;				}			}			if(diff > C_i - C_j)			{				if(alpha[i] > C_i)				{					alpha[i] = C_i;					alpha[j] = C_i - diff;				}			}			else			{				if(alpha[j] > C_j)				{