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#include <stdlib.h>
#include <string.h>
#include "linear.h"
#include "mex.h"
#ifdef MX_API_VER
#if MX_API_VER < 0x07030000
typedef int mwIndex;
#endif
#endif
#define Malloc(type,n) (type *)malloc((n)*sizeof(type))
#define NUM_OF_RETURN_FIELD 7
static const char *field_names[] = {
"Parameters",
"nr_class",
"nr_feature",
"bias",
"Label",
"w",
"rho",
};
const char *model_to_matlab_structure(mxArray *plhs[], struct model *model_)
{
int i;
int nr_w;
double *ptr;
mxArray *return_model, **rhs;
int out_id = 0;
int n, w_size;
rhs = (mxArray **)mxMalloc(sizeof(mxArray *)*NUM_OF_RETURN_FIELD);
// Parameters
// for now, only solver_type is needed
rhs[out_id] = mxCreateDoubleMatrix(1, 1, mxREAL);
ptr = mxGetPr(rhs[out_id]);
ptr[0] = model_->param.solver_type;
out_id++;
// nr_class
rhs[out_id] = mxCreateDoubleMatrix(1, 1, mxREAL);
ptr = mxGetPr(rhs[out_id]);
ptr[0] = model_->nr_class;
out_id++;
if(model_->nr_class==2 && model_->param.solver_type != MCSVM_CS)
nr_w=1;
else
nr_w=model_->nr_class;
// nr_feature
rhs[out_id] = mxCreateDoubleMatrix(1, 1, mxREAL);
ptr = mxGetPr(rhs[out_id]);
ptr[0] = model_->nr_feature;
out_id++;
// bias
rhs[out_id] = mxCreateDoubleMatrix(1, 1, mxREAL);
ptr = mxGetPr(rhs[out_id]);
ptr[0] = model_->bias;
out_id++;
if(model_->bias>=0)
n=model_->nr_feature+1;
else
n=model_->nr_feature;
w_size = n;
// 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++;
// w
rhs[out_id] = mxCreateDoubleMatrix(nr_w, w_size, mxREAL);
ptr = mxGetPr(rhs[out_id]);
for(i = 0; i < w_size*nr_w; i++)
ptr[i]=model_->w[i];
out_id++;
// rho
rhs[out_id] = mxCreateDoubleMatrix(1, 1, mxREAL);
ptr = mxGetPr(rhs[out_id]);
ptr[0] = model_->rho;
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;
}
const char *matlab_matrix_to_model(struct model *model_, const mxArray *matlab_struct)
{
int i, num_of_fields;
int nr_w;
double *ptr;
int id = 0;
int n, w_size;
mxArray **rhs;
num_of_fields = mxGetNumberOfFields(matlab_struct);
rhs = (mxArray **) mxMalloc(sizeof(mxArray *)*num_of_fields);
for(i=0;i<num_of_fields;i++)
rhs[i] = mxGetFieldByNumber(matlab_struct, 0, i);
model_->nr_class=0;
nr_w=0;
model_->nr_feature=0;
model_->w=NULL;
model_->label=NULL;
// Parameters
ptr = mxGetPr(rhs[id]);
model_->param.solver_type = (int)ptr[0];
id++;
// nr_class
ptr = mxGetPr(rhs[id]);
model_->nr_class = (int)ptr[0];
id++;
if(model_->nr_class==2 && model_->param.solver_type != MCSVM_CS)
nr_w=1;
else
nr_w=model_->nr_class;
// nr_feature
ptr = mxGetPr(rhs[id]);
model_->nr_feature = (int)ptr[0];
id++;
// bias
ptr = mxGetPr(rhs[id]);
model_->bias = ptr[0];
id++;
if(model_->bias>=0)
n=model_->nr_feature+1;
else
n=model_->nr_feature;
w_size = n;
// Label
if(mxIsEmpty(rhs[id]) == 0)
{
model_->label = Malloc(int, model_->nr_class);
ptr = mxGetPr(rhs[id]);
for(i=0;i<model_->nr_class;i++)
model_->label[i] = (int)ptr[i];
}
id++;
// w
ptr = mxGetPr(rhs[id]);
model_->w=Malloc(double, w_size*nr_w);
for(i = 0; i < w_size*nr_w; i++)
model_->w[i]=ptr[i];
id++;
// rho
ptr = mxGetPr(rhs[id]);
model_->rho = ptr[0];
id++;
mxFree(rhs);
return NULL;
}
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