/*
* Redberry: symbolic tensor computations.
*
* Copyright (c) 2010-2012:
* Stanislav Poslavsky <stvlpos@mail.ru>
* Bolotin Dmitriy <bolotin.dmitriy@gmail.com>
*
* 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 <http://www.gnu.org/licenses/>.
*/
package cc.redberry.transformation.concurrent;
import java.util.ArrayList;
import java.util.List;
import cc.redberry.core.tensor.Product;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorIterator;
import cc.redberry.core.tensor.testing.TTest;
import cc.redberry.transformation.Transformation;
import cc.redberry.transformation.Transformer;
/**
* Expands and collects scalars
*
* @author Dmitry Bolotin
* @author Stanislav Poslavsky
*/
public class EACScalars implements Transformation {
public static final EACScalars INSTANCE = new EACScalars();
private EACScalars() {
}
@Override
public Tensor transform(Tensor tensor) {
if (TTest.testIsSymbol(tensor))
return ExpandAndCollectTransformation.EXPAND_AND_COLLECT_SCALARS.transform(tensor);
if (tensor instanceof Product) {
TensorIterator it = tensor.iterator();
Tensor c;
List<Tensor> syms = new ArrayList<>();
while (it.hasNext())
if (TTest.testIsSymbol((c = it.next()))) {
syms.add(c);
it.remove();
}
if (syms.isEmpty())
return tensor;
if (syms.size() == 1) {
((Product) tensor).addFirst(syms.get(0));
return tensor;
}
((Product) tensor).addFirst(ExpandAndCollectTransformation.EXPAND_AND_COLLECT_SCALARS.transform(new Product(syms)));
return tensor;
}
return tensor;
}
public static Transformer getTransformer() {
return new Transformer(INSTANCE);
}
}