cc.redberry.transformation.collect.CollectPowers 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.indices.EmptyIndices;
import cc.redberry.core.tensor.AbstractScalarFunction;
import cc.redberry.core.tensor.Product;
import cc.redberry.core.tensor.SimpleTensor;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorIterator;
import cc.redberry.transformation.Transformation;

/**
 *
 * @author Dmitry Bolotin
 * @author Stanislav Poslavsky
 */
public class CollectPowers implements Transformation {
    public static final CollectPowers INSTANCE = new CollectPowers();

    private CollectPowers() {
    }

    @Override
    public Tensor transform(Tensor tensor) {
        if (!(tensor instanceof Product))
            return tensor;
        CollectPowersInputPort port = new CollectPowersInputPort();
        TensorIterator iterator = tensor.iterator();
        Tensor current;
        while (iterator.hasNext()) {
            current = iterator.next();
            if ((current instanceof SimpleTensor && current.getIndices() instanceof EmptyIndices)
                    || current instanceof AbstractScalarFunction) {
                port.put(current);
                iterator.remove();
            }
        }
        if (port.isEmpty())
            return tensor;
        ((Product) tensor).addFirst(port.getResult());
        return tensor.equivalent();
    }
}