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

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/*
 * 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 cc.redberry.core.context.CC;
import cc.redberry.core.tensor.*;
import cc.redberry.core.tensor.testing.TTest;
import java.util.ArrayList;
import java.util.List;

/**
 *
 * @author Dmitry Bolotin
 * @author Stanislav Poslavsky
 */
////TODO understand, where clone() is need
public class EqualsSplitCriteria implements SplitCriteria {
    public static final EqualsSplitCriteria INSTANCE = new EqualsSplitCriteria();

    private EqualsSplitCriteria() {
    }

    @Override
    public boolean factorOut(Tensor tensor) {
        return (tensor instanceof TensorNumber) || TTest.testIsSymbol(tensor);
    }

    @Override
    public EqualsSplit split(Tensor tensor) {
        if (tensor instanceof Product) {
            TensorIterator it = tensor.iterator();
            Tensor current;
            List factored = null;
            while (it.hasNext()) {
                current = it.next();
                if (factorOut(current)) {
                    if (factored == null)
                        factored = new ArrayList<>();
                    factored.add(current);
                    it.remove();
                }
            }
            if (((Product) tensor).isEmpty())
                throw new RuntimeException("Scalar sum must be collected with CollectScalars!");
            Tensor term = tensor.equivalent();
            term.setParent(CC.getRootParentTensor());
            if (factored == null)
                return new EqualsSplit(TensorNumber.createONE(), term);
            Tensor factoredTensor;
            if (factored.size() == 1) {
                factoredTensor = factored.get(0);
                factoredTensor.setParent(CC.getRootParentTensor());
            } else
                factoredTensor = new Product(factored);
            return new EqualsSplit(factoredTensor, term);
        }
        if (tensor instanceof SimpleTensor)
            if (factorOut(tensor))
                throw new RuntimeException("Scalar sum must be collected with CollectScalars!");
            else {
                Tensor term = tensor.equivalent();
                term.setParent(CC.getRootParentTensor());
                return new EqualsSplit(TensorNumber.createONE(), term);
            }
        throw new UnsupportedOperationException("Not supported yet.");
    }
}