eu.crisis_economics.abm.model.parameters.ParameterUtils.java Source code

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Here is the source code for eu.crisis_economics.abm.model.parameters.ParameterUtils.java

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/*
 * This file is part of CRISIS, an economics simulator.
 * 
 * Copyright (C) 2015 John Kieran Phillips
 *
 * CRISIS 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.
 *
 * CRISIS 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 CRISIS.  If not, see <http://www.gnu.org/licenses/>.
 */
package eu.crisis_economics.abm.model.parameters;

import org.apache.commons.math3.distribution.NormalDistribution;
import org.apache.commons.math3.distribution.UniformRealDistribution;

import com.google.common.base.Preconditions;

/**
  * Static utilities for {@link Parameter} classes.
  * 
  * @author phillips
  */
public final class ParameterUtils {

    /**
      * Convert an object {@code X} to a {@link Parameter} returning {@code X}.
      * 
      * @param value
      *        The object {@code X}
      */
    public static <T> ModelParameter<T> asParameter(final T value) {
        return new ModelParameter<T>() {
            @Override
            public T get() {
                return value;
            }

            @Override
            public String getName() {
                return "Anonymous Model Parameter";
            }

            @Override
            public Class<?> getParameterType() {
                return value.getClass();
            }
        };
    }

    /**
      * Convert an object {@code X} into a {@link TimeseriesParameter}
      * returning {@code X}.
      * 
      * @param value
      *        The object {@code X}.
      */
    public static <T> TimeseriesParameter<T> asMultiSampleParameter(final T value) {
        return new TimeseriesParameter<T>(asParameter(value));
    }

    /**
      * Convert an instance of a {@link Parameter}{@code <T>} to an instance of
      * a {@link TimeseriesParameter}{@code <T>}. The argument must be non-<code>null</code>.
      * 
      * @param modelParameter (<code>M</code>)</br>
      *        The {@link Parameter} object to use.
      * @return
      *        A non-<code>null</code> {@link TimeseriesParameter}{@code <T>} implemented
      *        by {@code M}.
      */
    public static <T> TimeseriesParameter<T> asTimeseries(final ModelParameter<T> modelParameter) {
        return new TimeseriesParameter<T>(Preconditions.checkNotNull(modelParameter));
    }

    /**
      * Create a {@link TimeseriesParameter}{@code <T>} from an instance, {@code X},
      * of {@code T}. The resulting {@link TimeseriesParameter} will always return 
      * a reference to {@code X}.
      * 
      * @param constantValue ({@code X})
      * @return
      *        A {@link TimeseriesParameter} {@code M} whose value {@code M(t)} is {@code X}.
      */
    public static <T> TimeseriesParameter<T> asTimeseries(final T constantValue) {
        return new TimeseriesParameter<T>(new FixedValue<T>("Unnamed Paramter", constantValue));
    }

    /**
      * Create a model parameter with a double value drawn from a
      * normal distribution.
      * 
      * @param parameterName
      *        The name of the model parameter.
      * @param mean
      *        The minimum value of the paremeter.
      * @param stdDeviation
      *        The maximum value of the parameter.
      */
    public static ModelParameter<?> createParameterWithNormalDistribution(final String parameterName,
            final double mean, final double stdDeviation) {
        Preconditions.checkArgument(stdDeviation >= 0.);
        return new FromRealDistributionModelParameter(new NormalDistribution(mean, stdDeviation), parameterName);
    }

    /**
      * Create a model parameter with a double value drawn from a
      * uniform distribution.
      * 
      * @param parameterName
      *        The name of the model parameter.
      * @param minParameterValue
      *        The minimum value of the paremeter.
      * @param maxParameterValue
      *        The maximum value of the parameter.
      */
    public static ModelParameter<?> createParameterWithUniformDistribution(final String parameterName,
            final double minParameterValue, final double maxParameterValue) {
        Preconditions.checkArgument(minParameterValue <= maxParameterValue);
        return new FromRealDistributionModelParameter(
                new UniformRealDistribution(minParameterValue, maxParameterValue), parameterName);
    }

    private ParameterUtils() {
    } // Uninstantiable
}