cc.redberry.transformation.collect.PatternCollectManager Maven / Gradle / Ivy

Go to download
/*
 * Redberry: symbolic tensor computations.
 *
 * Copyright (c) 2010-2012:
 *   Stanislav Poslavsky   
 *   Bolotin Dmitriy       
 *
 * This file is part of Redberry.
 *
 * Redberry 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.
 *
 * Redberry 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 Redberry. If not, see .
 */
package cc.redberry.transformation.collect;

import java.util.ArrayDeque;
import java.util.Deque;
import cc.redberry.core.tensor.Sum;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorIterator;
import cc.redberry.core.tensor.testing.TTest;
import cc.redberry.transformation.Transformation;

/**
 *
 * @author Dmitry Bolotin
 * @author Stanislav Poslavsky
 */
public class PatternCollectManager implements Transformation{
    private final Deque patterns;
    private Deque tempPatterns;
    boolean reset = true;

    public PatternCollectManager(Deque patterns) {
        this.patterns = patterns;
    }

    private void reset() {
        tempPatterns = new ArrayDeque<>();
        for (SplitPattern sp : patterns)
            tempPatterns.add(sp);
        reset = false;
    }

    @Override
    public Tensor transform(Tensor target) {
        if (!(target instanceof Sum))
            return target;
        if (reset)
            reset();
        //main routine
        Tensor result = collect1(target);
        reset = true;
        return result;
    }

    private Tensor collect1(Tensor target) {
        //main routine
        if (!(target instanceof Sum))
            return target;
        if (tempPatterns.isEmpty()) {
            if (TTest.testIsScalar(target)) {
                CollectTerms act = new CollectTerms(ScalarsSplitCriteria.INSTANCE);
                return act.transform(target);
            }
            CollectTerms act = new CollectTerms(EqualsSplitCriteria.INSTANCE);
            return act.transform(target);
        }
        SplitPattern currentPattern = tempPatterns.poll();
        CollectTerms act = new CollectTerms(new PatternSplitCriteria(currentPattern));
        target = act.transform(target);
        if (!(target instanceof Sum))
            return target;
        for (Tensor term : target) {
            TensorIterator it = term.iterator();
            Tensor multiplyer;
            while (it.hasNext()) {
                multiplyer = it.next();
                if (multiplyer instanceof Sum)
                    it.set(collect1(multiplyer)); //                    break;
            }
        }
        return target;
    }
}