#include <stdlib.h>#include <string.h>#include "svm.h"#include "mex.h"#if MX_API_VER < 0x07030000typedef int mwIndex;#endif #define NUM_OF_RETURN_FIELD 10#define Malloc(type,n) (type *)malloc((n)*sizeof(type))static const char *field_names[] = {	"Parameters",	"nr_class",	"totalSV",	"rho",	"Label",	"ProbA",	"ProbB",	"nSV",	"sv_coef",	"SVs"};const char *model_to_matlab_structure(mxArray *plhs[], int num_of_feature, struct svm_model *model){	int i, j, n;	double *ptr;	mxArray *return_model, **rhs;	int out_id = 0;	rhs = (mxArray **)mxMalloc(sizeof(mxArray *)*NUM_OF_RETURN_FIELD);	// Parameters	rhs[out_id] = mxCreateDoubleMatrix(5, 1, mxREAL);	ptr = mxGetPr(rhs[out_id]);	ptr[0] = model->param.svm_type;	ptr[1] = model->param.kernel_type;	ptr[2] = model->param.degree;	ptr[3] = model->param.gamma;	ptr[4] = model->param.coef0;	out_id++;	// nr_class	rhs[out_id] = mxCreateDoubleMatrix(1, 1, mxREAL);	ptr = mxGetPr(rhs[out_id]);	ptr[0] = model->nr_class;	out_id++;	// total SV	rhs[out_id] = mxCreateDoubleMatrix(1, 1, mxREAL);	ptr = mxGetPr(rhs[out_id]);	ptr[0] = model->l;	out_id++;	// rho	n = model->nr_class*(model->nr_class-1)/2;	rhs[out_id] = mxCreateDoubleMatrix(n, 1, mxREAL);	ptr = mxGetPr(rhs[out_id]);	for(i = 0; i < n; i++)		ptr[i] = model->rho[i];	out_id++;	// Label	if(model->label)	{		rhs[out_id] = mxCreateDoubleMatrix(model->nr_class, 1, mxREAL);		ptr = mxGetPr(rhs[out_id]);		for(i = 0; i < model->nr_class; i++)			ptr[i] = model->label[i];	}	else		rhs[out_id] = mxCreateDoubleMatrix(0, 0, mxREAL);	out_id++;	// probA	if(model->probA != NULL)	{		rhs[out_id] = mxCreateDoubleMatrix(n, 1, mxREAL);		ptr = mxGetPr(rhs[out_id]);		for(i = 0; i < n; i++)			ptr[i] = model->probA[i];	}	else		rhs[out_id] = mxCreateDoubleMatrix(0, 0, mxREAL);	out_id ++;	// probB	if(model->probB != NULL)	{		rhs[out_id] = mxCreateDoubleMatrix(n, 1, mxREAL);		ptr = mxGetPr(rhs[out_id]);		for(i = 0; i < n; i++)			ptr[i] = model->probB[i];	}	else		rhs[out_id] = mxCreateDoubleMatrix(0, 0, mxREAL);	out_id++;	// nSV	if(model->nSV)	{		rhs[out_id] = mxCreateDoubleMatrix(model->nr_class, 1, mxREAL);		ptr = mxGetPr(rhs[out_id]);		for(i = 0; i < model->nr_class; i++)			ptr[i] = model->nSV[i];	}	else		rhs[out_id] = mxCreateDoubleMatrix(0, 0, mxREAL);	out_id++;	// sv_coef	rhs[out_id] = mxCreateDoubleMatrix(model->l, model->nr_class-1, mxREAL);	ptr = mxGetPr(rhs[out_id]);	for(i = 0; i < model->nr_class-1; i++)		for(j = 0; j < model->l; j++)			ptr[(i*(model->l))+j] = model->sv_coef[i][j];	out_id++;	// SVs	{		int ir_index, nonzero_element;		mwIndex *ir, *jc;		mxArray *pprhs[1], *pplhs[1];			if(model->param.kernel_type == PRECOMPUTED)		{			nonzero_element = model->l;			num_of_feature = 1;		}		else		{			nonzero_element = 0;			for(i = 0; i < model->l; i++) {				j = 0;				while(model->SV[i][j].index != -1) 				{					nonzero_element++;					j++;				}			}		}		// SV in column, easier accessing		rhs[out_id] = mxCreateSparse(num_of_feature, model->l, nonzero_element, mxREAL);		ir = mxGetIr(rhs[out_id]);		jc = mxGetJc(rhs[out_id]);		ptr = mxGetPr(rhs[out_id]);		ir_index = jc[0] = 0;		for(i = 0;i < model->l; i++)		{			if(model->param.kernel_type == PRECOMPUTED)			{				// make a (1 x model->l) matrix				ir[ir_index] = 0; 				ptr[ir_index] = model->SV[i][0].value;				ir_index++;				jc[i+1] = jc[i] + 1;			}			else			{				int x_index = 0;				while (model->SV[i][x_index].index != -1)				{					ir[ir_index] = model->SV[i][x_index].index - 1; 					ptr[ir_index] = model->SV[i][x_index].value;					ir_index++, x_index++;				}				jc[i+1] = jc[i] + x_index;			}		}		// transpose back to SV in row		pprhs[0] = rhs[out_id];		if(mexCallMATLAB(1, pplhs, 1, pprhs, "transpose"))			return "cannot transpose SV matrix";		rhs[out_id] = pplhs[0];		out_id++;	}	/* Create a struct matrix contains NUM_OF_RETURN_FIELD fields */	return_model = mxCreateStructMatrix(1, 1, NUM_OF_RETURN_FIELD, field_names);	/* Fill struct matrix with input arguments */	for(i = 0; i < NUM_OF_RETURN_FIELD; i++)		mxSetField(return_model,0,field_names[i],mxDuplicateArray(rhs[i]));	/* return */	plhs[0] = return_model;	mxFree(rhs);	return NULL;}struct svm_model *matlab_matrix_to_model(const mxArray *matlab_struct, const char **msg){	int i, j, n, num_of_fields;	double *ptr;	int id = 0;	struct svm_node *x_space;	struct svm_model *model;	mxArray **rhs;	num_of_fields = mxGetNumberOfFields(matlab_struct);	if(num_of_fields != NUM_OF_RETURN_FIELD) 	{		*msg = "number of return field is not correct";		return NULL;	}	rhs = (mxArray **) mxMalloc(sizeof(mxArray *)*num_of_fields);	for(i=0;i<num_of_fields;i++)		rhs[i] = mxGetFieldByNumber(matlab_struct, 0, i);	model = Malloc(struct svm_model, 1);	model->rho = NULL;	model->probA = NULL;	model->probB = NULL;	model->label = NULL;	model->nSV = NULL;	model->free_sv = 1; // XXX	ptr = mxGetPr(rhs[id]);	model->param.svm_type	  = (int)ptr[0];	model->param.kernel_type  = (int)ptr[1];	model->param.degree	  = (int)ptr[2];	model->param.gamma	  = ptr[3];	model->param.coef0	  = ptr[4];	id++;	ptr = mxGetPr(rhs[id]);	model->nr_class = (int)ptr[0];	id++;	ptr = mxGetPr(rhs[id]);	model->l = (int)ptr[0];	id++;	// rho	n = model->nr_class * (model->nr_class-1)/2;	model->rho = (double*) malloc(n*sizeof(double));	ptr = mxGetPr(rhs[id]);	for(i=0;i<n;i++)		model->rho[i] = ptr[i];	id++;	// label	if(mxIsEmpty(rhs[id]) == 0)	{		model->label = (int*) malloc(model->nr_class*sizeof(int));		ptr = mxGetPr(rhs[id]);		for(i=0;i<model->nr_class;i++)			model->label[i] = (int)ptr[i];	}	id++;	// probA	if(mxIsEmpty(rhs[id]) == 0)	{		model->probA = (double*) malloc(n*sizeof(double));		ptr = mxGetPr(rhs[id]);		for(i=0;i<n;i++)			model->probA[i] = ptr[i];	}	id++;	// probB	if(mxIsEmpty(rhs[id]) == 0)	{		model->probB = (double*) malloc(n*sizeof(double));		ptr = mxGetPr(rhs[id]);		for(i=0;i<n;i++)			model->probB[i] = ptr[i];	}	id++;	// nSV	if(mxIsEmpty(rhs[id]) == 0)	{		model->nSV = (int*) malloc(model->nr_class*sizeof(int));		ptr = mxGetPr(rhs[id]);		for(i=0;i<model->nr_class;i++)			model->nSV[i] = (int)ptr[i];	}	id++;	// sv_coef	ptr = mxGetPr(rhs[id]);	model->sv_coef = (double**) malloc((model->nr_class-1)*sizeof(double));	for( i=0 ; i< model->nr_class -1 ; i++ )		model->sv_coef[i] = (double*) malloc((model->l)*sizeof(double));	for(i = 0; i < model->nr_class - 1; i++)		for(j = 0; j < model->l; j++)			model->sv_coef[i][j] = ptr[i*(model->l)+j];	id++;	// SV	{		int sr, sc, elements;		int num_samples;		mwIndex *ir, *jc;		mxArray *pprhs[1], *pplhs[1];		// transpose SV		pprhs[0] = rhs[id];		if(mexCallMATLAB(1, pplhs, 1, pprhs, "transpose")) 		{			svm_destroy_model(model);			*msg = "cannot transpose SV matrix";			return NULL;		}		rhs[id] = pplhs[0];		sr = mxGetN(rhs[id]);		sc = mxGetM(rhs[id]);		ptr = mxGetPr(rhs[id]);		ir = mxGetIr(rhs[id]);		jc = mxGetJc(rhs[id]);		num_samples = mxGetNzmax(rhs[id]);		elements = num_samples + sr;		model->SV = (struct svm_node **) malloc(sr * sizeof(struct svm_node *));		x_space = (struct svm_node *)malloc(elements * sizeof(struct svm_node));		// SV is in column		for(i=0;i<sr;i++)		{			int low = jc[i], high = jc[i+1];			int x_index = 0;			model->SV[i] = &x_space[low+i];			for(j=low;j<high;j++)			{				model->SV[i][x_index].index = ir[j] + 1; 				model->SV[i][x_index].value = ptr[j];				x_index++;			}			model->SV[i][x_index].index = -1;		}		id++;	}	mxFree(rhs);	return model;}