Package cc.redberry.core.tensor

Source Code of cc.redberry.core.tensor.Derivative$DerivativeIterator

/*
* 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.tensor;

import cc.redberry.core.indices.InconsistentIndicesException;
import cc.redberry.core.context.CC;
import cc.redberry.core.context.Context;
import cc.redberry.core.context.ToStringMode;
import cc.redberry.core.indices.Indices;
import cc.redberry.core.indices.IndicesBuilderSorted;
import cc.redberry.core.indices.IndicesFactory;
import cc.redberry.core.parser.StringDefaults;
import cc.redberry.core.utils.ArraysUtils;
import cc.redberry.core.utils.Indicator;

import java.util.Arrays;

/**
* @author Dmitry Bolotin
* @author Stanislav Poslavsky
*/
public final class Derivative extends Tensor {
    //  First element is target.
    private Tensor[] data;
    private ProductContent content;
    private Indices indices;

    Derivative(Tensor[] data) {
        this.parent = Context.get().getRootParentTensor();
        this.data = data;
        setDataParent();
    }

    private Derivative(Tensor target, SimpleTensor[] variations, Tensor parent) {
        data = new Tensor[variations.length + 1];
        data[0] = target;
        System.arraycopy(variations, 0, data, 1, variations.length);
        testConsistent();
        this.parent = parent;
        setDataParent();
    }

    private void setDataParent() {
        for (Tensor t : data)
            t.setParent(this);
    }

    private void testConsistent() {
        IndicesBuilderSorted ib = new IndicesBuilderSorted();
        ib.append(data[0].getIndices().getFreeIndices());
        for (int i = 1; i < data.length; ++i)
            ib.append(data[i].getIndices());
        Indices indices = ib.getIndices();
        if (indices.size() == 0)
            return;
        if (CC.getRegim() == Context.Regim.TESTING)
            return;
        try {
            indices.testConsistentWithException();
        } catch (InconsistentIndicesException ex) {
            //Adding information about source tensor
            throw new InconsistentIndicesException(ex, this);
        }
    }

    @Override
    public Tensor clone() {
        Tensor[] newData = new Tensor[data.length];
        for (int i = 0; i < data.length; ++i)
            newData[i] = data[i].clone();
        return new Derivative(newData);
    }

    public Tensor getTarget() {
        return data[0];
    }

    public Tensor[] getVars() {
        return Arrays.copyOfRange(data, 1, data.length);
    }

    public SimpleTensor getVariation(int index) {
        return (SimpleTensor) data[index + 1];
    }

    public int getDerivativeOrder() {
        return data.length - 1;
    }

    @Override
    public void update() {
        content = null;
        indices = null;
        super.update();
    }

    @Override
    public ProductContent getContent() {
        if (content == null)
            content = ProductContentImpl.create(true, getIndices(), Arrays.copyOf(data, data.length));
        return content;
    }

    @Override
    public Indices getIndices() {
        if (indices == null) {
            IndicesBuilderSorted ib = new IndicesBuilderSorted();
            for (int i = 0; i < data.length; ++i)
                ib.append(data[i].getIndices());
            indices = ib.getIndices();
        }
        return indices;
    }

    @Override
    protected int hash() {
        return 71 * data[0].hashCode() + ArraysUtils.commutativeHashCode(data, 1, data.length);
    }

    @Override
    @SuppressWarnings("fallthrough")
    public String toString(ToStringMode mode) {
        StringBuilder sb = new StringBuilder();
        char delta = (char) 0x03b1 + 3;
        switch (mode) {
            case LaTeX:
                for (int i = 1; i < data.length; ++i)
                    sb.append("\\frac{\\delta}{\\delta ").append(toStringInv((SimpleTensor) data[i], mode)).append("}");
                break;
            case REDBERRY_SOUT:
            case REDBERRY:
                sb.append(StringDefaults.get(Derivative.class)).append("[").append(data[0].toString(mode)).append(',');
                for (int i = 1; i < data.length; ++i)
                    sb.append(toStringInv((SimpleTensor) data[i], mode)).append(',');
                sb.deleteCharAt(sb.length() - 1).append(']');
                return sb.toString();
            default:
                for (int i = 1; i < data.length; ++i)
                    sb.append(delta).append("/").append(delta).append("(").append(toStringInv((SimpleTensor) data[i], mode)).append(")");
        }
        if (data[0] instanceof SimpleTensor)
            sb.append(data[0].toString(mode));
        else
            sb.append("(").append(data[0].toString(mode)).append(")");
        return sb.toString();
    }

    private static String toStringInv(SimpleTensor st, ToStringMode mode) {
        StringBuilder sb = new StringBuilder();
        sb.append(CC.getNameDescriptor(st.name).getName());
        sb.append(st.indices.getInverseIndices().toString(mode));
        return sb.toString();
    }

    public static Indicator<TensorIterator> DerivativeIteratorIndicator(final Indicator<Derivative> indicator) {
        if (indicator == null)
            return derivativeIteratorIndicator;
        return new AbstractTensorIteratorIndicator() {
            @Override
            public boolean _is(TensorIterator object) {
                return (object instanceof DerivativeIterator) && indicator.is(((DerivativeIterator) object).derivative());
            }
        };
    }

    public static final Indicator<TensorIterator> onVarsIndicator = new AbstractTensorIteratorIndicator() {
        @Override
        public boolean _is(TensorIterator object) {
            return (object instanceof DerivativeIterator) && ((DerivativeIterator) object).isOnVars();
        }
    };
    public static final Indicator<TensorIterator> onTargetIndicator = new AbstractTensorIteratorIndicator() {
        @Override
        public boolean _is(TensorIterator object) {
            return (object instanceof DerivativeIterator) && ((DerivativeIterator) object).isOnTarget();
        }
    };
    public static final Indicator<TensorIterator> derivativeIteratorIndicator = new AbstractTensorIteratorIndicator() {
        @Override
        public boolean _is(TensorIterator object) {
            return object instanceof DerivativeIterator;
        }
    };

    @Override
    public TensorIterator iterator() {
        return new DerivativeIterator();
    }

    private class DerivativeIterator extends AbstractTensorIterator {
        private int index = -1;

        boolean isOnTarget() {
            return index == 0;
        }

        boolean isOnVars() {
            return index > 0;
        }

        @Override
        public void set(Tensor t) {
            if (index > 0 && (t.getClass() != SimpleTensor.class))
                throw new RuntimeException();
            t.parent = Derivative.this;
            data[index] = t;
            update();
        }

        @Override
        public boolean hasNext() {
            return index < data.length - 1;
        }

        @Override
        public Tensor next() {
            return data[++index];
        }

        @Override
        public void remove() {
            throw new UnsupportedOperationException();
        }

        public Derivative derivative() {
            return Derivative.this;
        }
    }

    public static Derivative create(Tensor target, SimpleTensor[] variations, Tensor parent) {
        SimpleTensor[] arr = new SimpleTensor[variations.length];
        for (int i = 0; i < arr.length; ++i)
            //TODO make factory methods for SimpleTensor
            arr[i] = new SimpleTensor(variations[i].name, IndicesFactory.createSimple(variations[i].indices.getInverseIndices()));
        return new Derivative(target, arr, parent);
    }

    public static Derivative create(Tensor target, SimpleTensor... variations) {
        return create(target, variations, CC.getRootParentTensor());
    }

    public static Derivative createFromInversed(Tensor target, SimpleTensor[] variations, Tensor parent) {
        return new Derivative(target, variations, parent);
    }

    public static Derivative createFromInversed(Tensor target, SimpleTensor... variations) {
        return new Derivative(target, variations, CC.getRootParentTensor());
    }
}
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