learner.h

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/* =============================================================================
 *
 * learn.h
 * -- Learns structure of Bayesian net from data
 *
 * =============================================================================
 *
 * Copyright (C) Stanford University, 2006.  All Rights Reserved.
 * Author: Chi Cao Minh
 *
 * =============================================================================
 *
 * For the license of bayes/sort.h and bayes/sort.c, please see the header
 * of the files.
 *
 * ------------------------------------------------------------------------
 *
 * For the license of kmeans, please see kmeans/LICENSE.kmeans
 *
 * ------------------------------------------------------------------------
 *
 * For the license of ssca2, please see ssca2/COPYRIGHT
 *
 * ------------------------------------------------------------------------
 *
 * For the license of lib/mt19937ar.c and lib/mt19937ar.h, please see the
 * header of the files.
 *
 * ------------------------------------------------------------------------
 *
 * For the license of lib/rbtree.h and lib/rbtree.c, please see
 * lib/LEGALNOTICE.rbtree and lib/LICENSE.rbtree
 *
 * ------------------------------------------------------------------------
 *
 * Unless otherwise noted, the following license applies to STAMP files:
 *
 * Copyright (c) 2007, Stanford University
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are
 * met:
 *
 *     * Redistributions of source code must retain the above copyright
 *       notice, this list of conditions and the following disclaimer.
 *
 *     * 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.
 *
 *     * Neither the name of Stanford University 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 STANFORD UNIVERSITY ``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 STANFORD UNIVERSITY 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.
 *
 * =============================================================================
 */


#ifndef LEARNER_H
#define LEARNER_H 1

#include "adtree.h"
#include "data.h"
#include "net.h"
#include "query.h"

typedef struct learner_task learner_task_t;

#define CACHE_LINE_SIZE (64)

typedef struct learner {
    adtree_t* adtreePtr;
    net_t* netPtr;
    float* localBaseLogLikelihoods;
    char pad1[CACHE_LINE_SIZE - sizeof(float*)];
    float baseLogLikelihood;
    char pad2[CACHE_LINE_SIZE - sizeof(float)];
    learner_task_t* tasks;
    char pad3[CACHE_LINE_SIZE - sizeof(learner_task_t*)];
    list_t* taskListPtr;
    char pad4[CACHE_LINE_SIZE - sizeof(list_t*)];
    long numTotalParent;
    char pad5[CACHE_LINE_SIZE - sizeof(long)];
} learner_t;


/* =============================================================================
 * learner_alloc
 * =============================================================================
 */
learner_t*
learner_alloc (data_t* dataPtr, adtree_t* adtreePtr, long numThread);


/* =============================================================================
 * learner_free
 * =============================================================================
 */
void
learner_free (learner_t* learnerPtr);


/* =============================================================================
 * learner_run
 * =============================================================================
 */
void
learner_run (learner_t* learnerPtr);


/* =============================================================================
 * learner_score
 * -- Score entire network
 * =============================================================================
 */
float
learner_score (learner_t* learnerPtr);


#endif /* LEARNER_H */


/* =============================================================================
 *
 * End of learner.h
 *
 * =============================================================================
 */