/*

$Id$
Copyright (c) 2000-2009 Chih-Chung Chang and Chih-Jen Lin
Copyright (c) 2010 Alois Schloegl <alois.schloegl@gmail.com>
This function is part of the NaN-toolbox
http://pub.ist.ac.at/~schloegl/matlab/NaN/

This code was extracted from libsvm-mat-2.9-1 in Jan 2010 and 
modified for the use with Octave 

This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program; if not, see <http://www.gnu.org/licenses/>.


Copyright (c) 2000-2009 Chih-Chung Chang and Chih-Jen Lin
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:

1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.

3. Neither name of copyright holders nor the names of its contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.


THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE REGENTS OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

*/


#include <stdlib.h>
#include <string.h>
#include "svm.h"

#include "mex.h"

#ifdef tmwtypes_h
  #if (MX_API_VER<=0x07020000)
    typedef int mwSize;
    typedef int mwIndex;
  #endif 
#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"
};

#ifdef __cplusplus
extern "C" {
#endif

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]);
		jc[0] = ir_index = 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_free_and_destroy_model(&model);
			*msg = "cannot transpose SV matrix";
			return NULL;
		}
		rhs[id] = pplhs[0];

		sr = (int)mxGetN(rhs[id]);
		sc = (int)mxGetM(rhs[id]);

		ptr = mxGetPr(rhs[id]);
		ir = mxGetIr(rhs[id]);
		jc = mxGetJc(rhs[id]);

		num_samples = (int)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 = (int)jc[i], high = (int)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 = (int)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;
}

#ifdef __cplusplus
}
#endif