/*
* 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.functions;
import cc.redberry.core.tensor.AbstractScalarFunction;
import cc.redberry.core.tensor.Fraction;
import cc.redberry.core.tensor.Product;
import cc.redberry.core.tensor.Tensor;
import cc.redberry.core.tensor.TensorNumber;
/**
*
* @author Dmitry Bolotin
* @author Stanislav Poslavsky
*/
public class Tan extends AbstractScalarFunction {
public Tan(Tensor argument) {
super(argument);
}
public Tan(Tensor argument, Tensor parent) {
super(argument, parent);
}
@Override
public Tensor derivative() {
return new Fraction(TensorNumber.createONE(), new Product(new Cos(innerTensor.clone()), new Cos(innerTensor.clone())));
}
// @Override
// public String stringSymbol() {
// return "Tan";
// }
@Override
public Tensor clone() {
return new Tan(innerTensor.clone());
}
@Override
protected int hash() {
return 17 * innerTensor.hashCode();
}
}