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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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 *
 * This file is part of tensorics.
 * 
 * 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.
 * See the License for the specific language governing permissions and
 * limitations under the License.
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// @formatter:on

package org.tensorics.core.quantity.options;

import org.tensorics.core.math.ExtendedField;
import org.tensorics.core.quantity.ErronousValue;
import org.tensorics.core.scalar.lang.ScalarSupport;

import com.google.common.base.Optional;


/**
 * This error propagation assumes uncorrelated errors.
 * 
 * See http://en .wikipedia.org/wiki/
 * Propagation_of_uncertainty
 * 
 * @author kfuchsbe
 * @param 
 */
public class UncorrelatedErrorPropagationStrategy extends ScalarSupport implements ErrorPropagationStrategy {

    public UncorrelatedErrorPropagationStrategy(ExtendedField field) {
        super(field);
    }

    @Override
    public Optional errorForSumAndDifference(ErronousValue left, ErronousValue right) {
        if (left.error().isPresent() && right.error().isPresent()) {
            V first = squareOf(left.error().get());
            V second = squareOf(right.error().get());
            return Optional.of(squareRootOf(calculate(first).plus(second)));
        }
        return Optional. absent();
    }

    @Override
    public Optional errorForProductAndDivision(ErronousValue left, ErronousValue right) {
        if (left.error().isPresent() && right.error().isPresent()) {
            V first = squaredValueErrorProduct(left, right);
            V second = squaredValueErrorProduct(right, left);
            return Optional.of(squareRootOf(calculate(first).plus(second)));
        }
        return Optional. absent();
    }

    private V squaredValueErrorProduct(ErronousValue left, ErronousValue right) {
        return calculate(squareOf(left.value())).times(squareOf(right.error().get()));
    }

    @SuppressWarnings("rawtypes")
    @Override
    public Class getMarkerInterface() {
        return ErrorPropagationStrategy.class;
    }

}