Package cc.redberry.transformation.fraction

Source Code of cc.redberry.transformation.fraction.ToCommonDenominatorOld

/*
* 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.fraction;

import java.util.ArrayList;
import java.util.List;
import cc.redberry.core.tensor.Fraction;
import cc.redberry.core.tensor.Product;
import cc.redberry.core.tensor.Sum;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorSortedContent;
import cc.redberry.core.tensor.testing.TTest;
import cc.redberry.transformation.Transformation;

/**
* The class represents reduction of fractions to a common translation.
* The transformation reduces fraction by pairs generated fraction with
* common denominator for adding it to the next summand of incoming tensor.
* For instance: we have a/b+c/d+f/e+... The first step of cycle is sums of
* a/b+c/d=(a*d+c*b)/(b*d). The next step is sum of this fraction and the next
* summand: (a*d+c*b)/(b*d)+f/e. And so on.
* The transformation also take into account the common members of fraction's
* denominators.
*
* @author Konstantin Kiselev
* @author Dmitry Bolotin
* @author Stanislav Poslavsky
*
*/
public class ToCommonDenominatorOld implements Transformation {
    private boolean isProduct(Tensor tensor) {
        return (tensor instanceof Product);
    }

    /*
     * If first and second fractions' denominators are products, find fracion with
     * common denominator.
     */
    private Fraction getSumWithProductDenominator(Fraction first, Fraction second) {
        TensorSortedContent firstContent = ((Product) first.getDenominator()).getContent();
        TensorSortedContent secondContent = ((Product) second.getDenominator()).getContent();
        Tensor firstMultiplyed = first.getNumerator();
        Tensor secondMultiplyed = second.getNumerator();

        List<Tensor> firstProduct = new ArrayList<>();
        List<Tensor> secondProduct = new ArrayList<>();
        firstProduct.add(secondMultiplyed);
        secondProduct.add(firstMultiplyed);

        Product denominator = new Product();

        int j = 0;
        boolean firstIsFinish = false;
        for (int i = 0; i < secondContent.size(); i++) {
            if (firstIsFinish) {
                secondProduct.add(secondContent.get(i));
                denominator.add(secondContent.get(i));
                continue;
            }
            if (secondContent.get(i).hashCode() < firstContent.get(j).hashCode()) {
                secondProduct.add(secondContent.get(i));
                denominator.add(secondContent.get(i));
                continue;
            } else if (secondContent.get(i).hashCode() > firstContent.get(j).hashCode()) {
                firstProduct.add(firstContent.get(j));
                denominator.add(firstContent.get(j));
                j++;
                if (j == firstContent.size())
                    firstIsFinish = true;
                i--;
                continue;
            } else if (secondContent.get(i).hashCode() == firstContent.get(j).hashCode())
                while (secondContent.get(i).hashCode() == firstContent.get(j).hashCode() && j < firstContent.size())
                    if (TTest.testParity(secondContent.get(i), firstContent.get(j))) {
                        denominator.add(firstContent.get(j));
                        j++;
                        if (j == firstContent.size())
                            firstIsFinish = true;
                        break;
                    }
        }
        if (!firstIsFinish)
            for (int i = j; i < firstContent.size(); i++) {
                firstProduct.add(firstContent.get(j));
                denominator.add(firstContent.get(j));
            }

        Tensor summond1 = new Product(firstProduct);
        Tensor summond2 = new Product(secondProduct);
        return new Fraction(new Sum(summond1, summond2), denominator);
    }

    /*
     * If first fraction's denominator is product but second isn't, find
     * fraction with common denominator.
     */
    private Fraction getSumWithProductAndSimpleDenominator(Fraction first, Fraction second) {
        TensorSortedContent firstFracContent = ((Product) first.getDenominator()).getContent();
        Product denom = new Product();
        boolean is = false;

        for (int i = 0; i < firstFracContent.size(); i++)
            if (!is) {
                if (!(firstFracContent.get(i).hashCode() == second.getDenominator().hashCode())) {
                    denom.add(firstFracContent.get(i));
                    continue;
                }
                if (!TTest.testParity(firstFracContent.get(i), second.getDenominator()))
                    denom.add(firstFracContent.get(i));
                else
                    is = true;

            } else
                denom.add(firstFracContent.get(i));
        Tensor denominator = is ? first.getDenominator() : new Product(denom.clone(), second.getDenominator());
        Tensor summand1 = is ? first.getNumerator() : new Product(first.getNumerator(), second.getDenominator());
        Tensor summand2 = new Product(second.getNumerator().clone(), denom);
        return new Fraction(new Sum(summand1, summand2), denominator);
    }

    @Override
    public Tensor transform(Tensor tensor) {
        if (!(tensor instanceof Sum))
            return tensor;

        List<Tensor> listTensor = new ArrayList<>();
        List<Fraction> listFrac = new ArrayList<>();
       
        for (Tensor s :  tensor)
            if (s instanceof Fraction)
                listFrac.add((Fraction) s);
            else
                listTensor.add(s);

        if (listFrac.isEmpty())
            return tensor;

        Fraction resultFrac = null;
        for (Fraction f : listFrac) {
            if (resultFrac == null) {
                resultFrac = f;
                continue;
            }
            Tensor resultFracN = resultFrac.getNumerator();
            Tensor resultFracD = resultFrac.getDenominator();
            Tensor fD = f.getDenominator();
            Tensor fN = f.getNumerator();

            boolean resultIsProduct = isProduct(resultFracD);
            boolean fIsProduct = isProduct(fD);

            if (!(resultIsProduct || fIsProduct))
                if (TTest.testParity(resultFracD, fD))
                    resultFrac = new Fraction(new Sum(resultFracN, fN), resultFracD);
                else {
                    Tensor summond1 = new Product(resultFracN, fD);
                    Tensor summond2 = new Product(fN, resultFracD.clone());

                    Tensor newNumerator = new Sum(summond1, summond2);
                    Tensor newDenumerator = new Product(resultFracD.clone(), fD);

                    resultFrac = new Fraction(newNumerator, newDenumerator);
                }
            else if (resultIsProduct ^ fIsProduct)
                if (resultIsProduct)
                    resultFrac = getSumWithProductAndSimpleDenominator(resultFrac, f);
                else
                    resultFrac = getSumWithProductAndSimpleDenominator(f, resultFrac);
            else
                if (((Product) resultFracD).size() >= ((Product) fD).size())
                    resultFrac = getSumWithProductDenominator(resultFrac, f);
                else
                    resultFrac = getSumWithProductDenominator(f, resultFrac);


        }

        if (!listTensor.isEmpty()) {
            Tensor simpleSum = new Sum(listTensor);
            Tensor summand1 = new Product(simpleSum, resultFrac.getDenominator().clone());
            Tensor summand2 = resultFrac.getNumerator();
            Tensor result = new Fraction(new Sum(summand1, summand2), resultFrac.getDenominator());
            return result;
        }
        return resultFrac;
    }
}
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