/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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.
 */
package org.apache.commons.statistics.distribution;

import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;

/**
 * Test cases for GumbelDistribution.
 */
class GumbelDistributionTest extends ContinuousDistributionAbstractTest {

    //-------------- Implementations for abstract methods ----------------------

    @Override
    public GumbelDistribution makeDistribution() {
        return new GumbelDistribution(0.5, 2);
    }

    @Override
    public double[] makeCumulativeTestPoints() {
        return new double[] {
            -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5
        };
    }

    @Override
    public double[] makeDensityTestValues() {
        return new double[] {
            1.258262e-06, 3.594689e-04, 9.115766e-03, 5.321100e-02, 1.274352e-01, 1.777864e-01,
            1.787177e-01, 1.472662e-01, 1.075659e-01, 7.302736e-02, 4.742782e-02
        };
    }

    @Override
    public double[] makeCumulativeTestValues() {
        return new double[] {
            1.608760e-07, 7.577548e-05, 3.168165e-03, 3.049041e-02, 1.203923e-01, 2.769203e-01,
            4.589561e-01, 6.235249e-01, 7.508835e-01, 8.404869e-01, 8.999652e-01
        };
    }

    @Override
    public double[] makeCumulativePrecisionTestPoints() {
        return new double[] {-7.0, -7.1};
    }

    @Override
    public double[] makeCumulativePrecisionTestValues() {
        // These were created using WolframAlpha, specifically =CDF[ExtremeValueDistribution[0.5, 2], x]
        return new double[] {3.414512624812977e-19, 3.859421750095851e-20};
    }

    @Override
    public double[] makeSurvivalPrecisionTestPoints() {
        return new double[] {75};
    }

    @Override
    public double[] makeSurvivalPrecisionTestValues() {
        // Not calculated via WolframAlpha, instead utilizing scipy gumbel_r, Wolframalpha could not get precise enough
        return new double[] {6.64554417291507e-17};
    }

    //-------------------- Additional test cases -------------------------------

    @Test
    void testInverseCumulativeProbabilityExtremes() {
        setInverseCumulativeTestPoints(new double[] {0.0, 1.0});
        setInverseCumulativeTestValues(new double[] {Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY});
        verifyInverseCumulativeProbabilities();
    }

    @Test
    void testParameterAccessors() {
        final GumbelDistribution dist = makeDistribution();
        Assertions.assertEquals(0.5, dist.getLocation());
        Assertions.assertEquals(2, dist.getScale());
    }

    @Test
    void testConstructorPrecondition1() {
        Assertions.assertThrows(DistributionException.class, () -> new GumbelDistribution(10, -0.1));
    }

    @Test
    void testMoments() {
        final double tol = 1e-9;
        GumbelDistribution dist;

        dist = new GumbelDistribution(10, 0.5);
        Assertions.assertEquals(10 + (Math.PI / (2 * Math.E)) * 0.5, dist.getMean(), tol);
        Assertions.assertEquals((Math.PI * Math.PI / 6) * 0.5 * 0.5, dist.getVariance(), tol);

        dist = new GumbelDistribution(30, 0.3);
        Assertions.assertEquals(30 + (Math.PI / (2 * Math.E)) * 0.3, dist.getMean(), tol);
        Assertions.assertEquals((Math.PI * Math.PI / 6) * 0.3 * 0.3, dist.getVariance(), tol);
    }

    @Test
    void testSupport() {
        final GumbelDistribution dist = makeDistribution();
        Assertions.assertEquals(Double.NEGATIVE_INFINITY, dist.getSupportLowerBound());
        Assertions.assertEquals(Double.POSITIVE_INFINITY, dist.getSupportUpperBound());
        Assertions.assertTrue(dist.isSupportConnected());
    }
}