cc.redberry.transformation.Transformer 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;

import java.util.Arrays;
import java.util.List;
import cc.redberry.core.tensor.AbstractTensorWrapper;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorNumber;
import cc.redberry.core.tensor.TensorWrapper;
import cc.redberry.core.tensor.iterators.TensorTreeIterator;
import cc.redberry.core.tensor.iterators.TensorTreeIteratorFactory;

/**
 *
 * @author Dmitry Bolotin
 * @author Stanislav Poslavsky
 */
public class Transformer implements Transformation {
    private List transformations;

    public Transformer(Transformation... transformations) {
        this.transformations = Arrays.asList(transformations);
    }

    public Transformer(List transformations) {
        this.transformations = transformations;
    }

    @Override
    public Tensor transform(Tensor tensor) {
        return transform(tensor, false);
    }

    public Tensor transform(Tensor tensor, boolean tensorFirst) {
        //TODO review
        //Remembing parent
        Tensor parent = tensor.getParent();
        TensorWrapper wrapper = new TensorWrapper(tensor);
        TensorTreeIterator it = TensorTreeIteratorFactory.create(tensorFirst, wrapper);
        Tensor current, old;
        while (it.hasNext()) {
            old = current = it.next();
            for (Transformation transformation : transformations)
                if ((current = transformation.transform(current)) == null)
                    break;
            if (current == null)
                if (AbstractTensorWrapper.onInnerTensorIndicator.is(it))
                    it.set(TensorNumber.createZERO());
                else
                    it.remove();
            else if (old != current)
                it.set(current);
        }
        Tensor result = wrapper.getInnerTensor();
        result.setParent(parent);
        return result;
    }
}