/*
* 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.collect.old;
import java.util.ArrayList;
import java.util.List;
import cc.redberry.core.tensor.Product;
import cc.redberry.core.tensor.SimpleTensor;
import cc.redberry.core.tensor.Sum;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorIterator;
import cc.redberry.core.tensor.TensorNumber;
import cc.redberry.core.tensor.testing.TTest;
import cc.redberry.transformation.Transformation;
/**
*
* @author Dmitry Bolotin
* @author Stanislav Poslavsky
*/
public class CollectScalars implements Transformation {
public static final CollectScalars INSTANCE = new CollectScalars();
private CollectScalars() {
}
public Tensor transform(Tensor tensor) {
if (!(tensor instanceof Sum))
return tensor;
if (!TTest.testIsScalar(tensor))
return tensor;
List<SplitNumber> result = new ArrayList<>();
OUT_FOR:
for (Tensor current : tensor) {
SplitNumber split = splitNumber(current);
for (SplitNumber r : result)
if (TTest.testParity(r.nonNumber, split.nonNumber)) {
r.number.add(split.number);
continue OUT_FOR;
}
result.add(splitNumber(current));
}
Sum sum = new Sum();
for (SplitNumber split : result)
if (split.number.isOne())
sum.add(split.nonNumber);
else
sum.add(new Product(split.number, split.nonNumber));
return sum.equivalent();
}
private SplitNumber splitNumber(Tensor tensor) {
if (tensor instanceof SimpleTensor)
return new SplitNumber(TensorNumber.createONE(), tensor);
if (tensor instanceof TensorNumber)
return new SplitNumber(TensorNumber.createONE(), tensor);
if (tensor instanceof Product) {
TensorNumber number = TensorNumber.createONE();
TensorIterator iterator = tensor.iterator();
Tensor current;
while (iterator.hasNext()) {
current = iterator.next();
if (current instanceof TensorNumber) {
number.multiply((TensorNumber) current);
iterator.remove();
}
}
return new SplitNumber(number, tensor.equivalent());
}
throw new UnsupportedOperationException();
}
private static class SplitNumber {
TensorNumber number;
Tensor nonNumber;
SplitNumber(TensorNumber number, Tensor nonNumber) {
this.number = number;
this.nonNumber = nonNumber;
}
}
}