%module svmc%{#include "svm.h"%}enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR };	/* svm_type */enum { LINEAR, POLY, RBF, SIGMOID };	/* kernel_type */%pragma make_defaultstruct svm_parameter{	int svm_type;	int kernel_type;	double 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};struct svm_problem{	int l;	double *y;	struct svm_node **x;};%pragma no_defaultstruct svm_model *svm_train(const struct svm_problem *prob,			    const struct svm_parameter *param);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);double svm_predict(const struct svm_model *model, const struct svm_node *x);void svm_destroy_model(struct svm_model *model);const char *svm_check_parameter(const struct svm_problem *prob, const struct svm_parameter *param);%include array.i		// for double array operations%inline %{struct svm_node *svm_node_array(int size){	return (struct svm_node *)malloc(sizeof(struct svm_node)*size);}void svm_node_array_set(struct svm_node *array, int i, int index, double value){	array[i].index = index;	array[i].value = value;}void svm_node_array_destroy(struct svm_node *array){	free(array);}struct svm_node **svm_node_matrix(int size){	return (struct svm_node **)malloc(sizeof(struct svm_node *)*size);	}void svm_node_matrix_set(struct svm_node **matrix, int i, struct svm_node* array){	matrix[i] = array;}void svm_node_matrix_destroy(struct svm_node **matrix){	free(matrix);}%}