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Tensorics is a java framework which uses a tensor as a central object. A tensor represents a set of values placed in an N-dimensional space. Wherever you are tempted to use maps of maps, a tensor might be a good choice ;-) Tensorics provides methods to create, transform and performing calculations with those tensors.

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// @formatter:off
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 *
 * This file is part of tensorics.
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 * Copyright (c) 2008-2011, CERN. All rights reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// @formatter:on

package org.tensorics.core.quantity.operations;

import org.tensorics.core.lang.Tensorics;
import org.tensorics.core.quantity.QuantifiedValue;
import org.tensorics.core.quantity.options.QuantityEnvironment;
import org.tensorics.core.units.Unit;

/**
 * The binary operation which describes the division of two quantities.
 * 
 * @author kfuchsbe
 * @param  the type of the scalar values (field elements) on which all the operations are based on
 */
public class QuantityDivision extends QuantityBinaryOperation {

    public QuantityDivision(QuantityEnvironment environment) {
        super(environment, environment.field().division());
    }

    @Override
    public QuantifiedValue perform(QuantifiedValue left, QuantifiedValue right) {
        S value = operation().perform(left.value(), right.value());
        Unit unit = environment().quantification().divide(left.unit(), right.unit());
        return Tensorics.quantityOf(value, unit).withValidity(validityFor(left, right))
                .withError(productError(left, right));
    }

}