/*
* 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.core.transformations.substitutions;
import cc.redberry.core.indexmapping.IndexMappingBuffer;
import cc.redberry.core.indexmapping.IndexMappings;
import cc.redberry.core.indices.Indices;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorField;
import cc.redberry.core.transformations.ApplyIndexMapping;
import cc.redberry.core.transformations.Transformation;
import cc.redberry.core.utils.TensorUtils;
import java.util.ArrayList;
import java.util.List;
/**
*
* @author Dmitry Bolotin
* @author Stanislav Poslavsky
*/
class TensorFieldSubstitution implements Transformation {
final static SubstitutionProvider TENSOR_FIELD_PROVIDER = new SubstitutionProvider() {
@Override
public Transformation createSubstitution(Tensor from, Tensor to) {
return new TensorFieldSubstitution((TensorField) from, to);
}
};
private final TensorField from;
private final Tensor to;
private final boolean symbolic;
private TensorFieldSubstitution(TensorField from, Tensor to) {
this.from = from;
this.to = to;
this.symbolic = TensorUtils.isSymbolic(to);
}
@Override
public Tensor transform(Tensor tensor) {
SubstitutionIterator iterator = new SubstitutionIterator(tensor);
Tensor current;
OUT:
while ((current = iterator.next()) != null) {
if (!(current instanceof TensorField))
continue;
TensorField currentField = (TensorField) current;
IndexMappingBuffer buffer = IndexMappings.simpleTensorsPort(from, currentField).take();
if (buffer == null)
continue;
Indices[] fromIndices = from.getArgIndices(), currentIndices = currentField.getArgIndices();
List<Transformation> transformations = new ArrayList<>();
Tensor fArg;
int[] cIndices, fIndices;
int i;
for (i = from.size() - 1; i >= 0; --i) {
if (IndexMappings.mappingExists(current.get(i), from.get(i)))
continue;
fIndices = fromIndices[i].getAllIndices().copy();
cIndices = currentIndices[i].getAllIndices().copy();
assert cIndices.length == fIndices.length;
fArg = ApplyIndexMapping.applyIndexMapping(from.get(i), fIndices, cIndices, new int[0]);
transformations.add(Substitutions.getTransformation(fArg, current.get(i)));
}
Tensor newTo;
if (symbolic)
newTo = to;
else {
int[] forbidden = new int[iterator.forbiddenIndices().size()];
int c = -1;
for (Integer f : iterator.forbiddenIndices())
forbidden[++c] = f;
newTo = ApplyIndexMapping.applyIndexMapping(to, buffer, forbidden);
// if (newTo != to)
iterator.forbiddenIndices().addAll(TensorUtils.getAllIndicesNames(newTo));
}
for (Transformation transformation : transformations)
newTo = transformation.transform(newTo);
if (!symbolic) {
int[] forbidden = new int[iterator.forbiddenIndices().size()];
int c = -1;
for (Integer f : iterator.forbiddenIndices())
forbidden[++c] = f;
Tensor temp = newTo;
newTo = ApplyIndexMapping.renameDummy(temp, forbidden);
if (temp != newTo)
iterator.forbiddenIndices().addAll(TensorUtils.getAllIndicesNames(newTo));
}
iterator.set(newTo);
}
return iterator.result();
}
}