/*
 * 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.math.stat.descriptive;

import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;

import org.apache.commons.math.util.NumberTransformer;
import org.apache.commons.math.util.TransformerMap;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;

/**
 * Test cases for the {@link ListUnivariateImpl} class.
 *
 * @version $Revision$ $Date$
 */

public final class MixedListUnivariateImplTest extends TestCase {
	private double one = 1;
	private float two = 2;
	private int three = 3;

	private double mean = 2;
	private double sumSq = 18;
	private double sum = 8;
	private double var = 0.666666666666666666667;
	private double std = Math.sqrt(var);
	private double n = 4;
	private double min = 1;
	private double max = 3;
	private double tolerance = 10E-15;

	private TransformerMap transformers = new TransformerMap();

	public MixedListUnivariateImplTest(String name) {
		super(name);
		transformers = new TransformerMap();

		transformers.putTransformer(Foo.class, new FooTransformer());

		transformers.putTransformer(Bar.class, new BarTransformer());

	}

	public static Test suite() {
		TestSuite suite = new TestSuite(MixedListUnivariateImplTest.class);
		suite.setName("Mixed List Tests");
		return suite;
	}

	/** test stats */
	public void testStats() {
		List<Object> externalList = new ArrayList<Object>();

		DescriptiveStatistics u = new ListUnivariateImpl(externalList, transformers);

		assertEquals("total count", 0, u.getN(), tolerance);
		u.addValue(one);
		u.addValue(two);
		u.addValue(two);
		u.addValue(three);
		assertEquals("N", n, u.getN(), tolerance);
		assertEquals("sum", sum, u.getSum(), tolerance);
		assertEquals("sumsq", sumSq, u.getSumsq(), tolerance);
		assertEquals("var", var, u.getVariance(), tolerance);
		assertEquals("std", std, u.getStandardDeviation(), tolerance);
		assertEquals("mean", mean, u.getMean(), tolerance);
		assertEquals("min", min, u.getMin(), tolerance);
		assertEquals("max", max, u.getMax(), tolerance);
		u.clear();
		assertEquals("total count", 0, u.getN(), tolerance);
	}

	public void testN0andN1Conditions() throws Exception {
		DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<Object>(), transformers);

		assertTrue("Mean of n = 0 set should be NaN", Double.isNaN(u.getMean()));
		assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN(u.getStandardDeviation()));
		assertTrue("Variance of n = 0 set should be NaN", Double.isNaN(u.getVariance()));

		u.addValue(one);

		assertTrue("Mean of n = 1 set should be value of single item n1, instead it is " + u.getMean(),
				u.getMean() == one);

		assertTrue("StdDev of n = 1 set should be zero, instead it is: " + u.getStandardDeviation(),
				u.getStandardDeviation() == 0);
		assertTrue("Variance of n = 1 set should be zero", u.getVariance() == 0);
	}

	public void testSkewAndKurtosis() {
		ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<Object>(), transformers);

		u.addObject("12.5");
		u.addObject(Integer.valueOf(12));
		u.addObject("11.8");
		u.addObject("14.2");
		u.addObject(new Foo());
		u.addObject("14.5");
		u.addObject(Long.valueOf(21));
		u.addObject("8.2");
		u.addObject("10.3");
		u.addObject("11.3");
		u.addObject(Float.valueOf(14.1f));
		u.addObject("9.9");
		u.addObject("12.2");
		u.addObject(new Bar());
		u.addObject("12.1");
		u.addObject("11");
		u.addObject(Double.valueOf(19.8));
		u.addObject("11");
		u.addObject("10");
		u.addObject("8.8");
		u.addObject("9");
		u.addObject("12.3");

		assertEquals("mean", 12.40455, u.getMean(), 0.0001);
		assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
		assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
		assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
	}

	public void testProductAndGeometricMean() throws Exception {
		ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<Object>(), transformers);
		u.setWindowSize(10);

		u.addValue(1.0);
		u.addValue(2.0);
		u.addValue(3.0);
		u.addValue(4.0);

		assertEquals("Geometric mean not expected", 2.213364, u.getGeometricMean(), 0.00001);

		// Now test rolling - StorelessDescriptiveStatistics should discount the
		// contribution
		// of a discarded element
		for (int i = 0; i < 10; i++) {
			u.addValue(i + 2);
		}
		// Values should be (2,3,4,5,6,7,8,9,10,11)
		assertEquals("Geometric mean not expected", 5.755931, u.getGeometricMean(), 0.00001);

	}

	public static final class Foo {
		public String heresFoo() {
			return "14.9";
		}
	}

	public static final class FooTransformer implements NumberTransformer, Serializable {
		private static final long serialVersionUID = -4252248129291326127L;

		public double transform(Object o) {
			return Double.parseDouble(((Foo) o).heresFoo());
		}
	}

	public static final class Bar {
		public String heresBar() {
			return "12.0";
		}
	}

	public static final class BarTransformer implements NumberTransformer, Serializable {
		private static final long serialVersionUID = -1768345377764262043L;

		public double transform(Object o) {
			return Double.parseDouble(((Bar) o).heresBar());
		}
	}

}
