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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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 * 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
 *
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// @formatter:on

package org.tensorics.core.quantity.conditions;

import org.tensorics.core.quantity.QuantifiedValue;
import org.tensorics.core.quantity.options.QuantityEnvironment;

/**
 * A condition to test if a quantity is less than another quantity. In case at least one of the quantities has an error,
 * a statistical z-test is done at a given confidence level.
 * 
 * @author mihostet
 * @param  the value of the scalar (elements of the field)
 */
public class QuantityLessPredicate extends AbstractQuantityStatisticPredicate {
    final S confidenceLimit;

    public QuantityLessPredicate(QuantityEnvironment environment) {
        super(environment);
        confidenceLimit = inverseGaussianCumulativeDistributionFunction(calculate(one()).minus(
                environment.confidenceLevel()));
    }

    @Override
    public boolean test(QuantifiedValue left, QuantifiedValue right) {
        if (testIf(left.error().or(zero())).isEqualTo(zero()) && testIf(right.error().or(zero())).isEqualTo(zero())) {
            return testIf(subtractQuantities(left, right).value()).isLessThan(zero());
        }
        return testIf(zTestValueForDifference(left, right)).isLessThan(confidenceLimit);
    }
}