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Java example source code file (PairedStatsTest.java)

This example Java source code file (PairedStatsTest.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

all_many_values, duplicate_many_values_paired_stats, equalstester, expected, illegalargumentexception, illegalstateexception, many_values_count, many_values_stats_iterable, manyvalues, nio, nullpointerexception, other_many_values, other_many_values_stats, pairedstats, pearson's

The PairedStatsTest.java Java example source code

/*
 * Copyright (C) 2012 The Guava Authors
 *
 * 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.
 */

package com.google.common.math;

import static com.google.common.math.StatsTesting.ALLOWED_ERROR;
import static com.google.common.math.StatsTesting.ALL_MANY_VALUES;
import static com.google.common.math.StatsTesting.ALL_PAIRED_STATS;
import static com.google.common.math.StatsTesting.CONSTANT_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.DUPLICATE_MANY_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.EMPTY_PAIRED_STATS;
import static com.google.common.math.StatsTesting.EMPTY_STATS_ITERABLE;
import static com.google.common.math.StatsTesting.HORIZONTAL_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.MANY_VALUES;
import static com.google.common.math.StatsTesting.MANY_VALUES_COUNT;
import static com.google.common.math.StatsTesting.MANY_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.MANY_VALUES_STATS_ITERABLE;
import static com.google.common.math.StatsTesting.MANY_VALUES_STATS_VARARGS;
import static com.google.common.math.StatsTesting.MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS;
import static com.google.common.math.StatsTesting.ONE_VALUE_PAIRED_STATS;
import static com.google.common.math.StatsTesting.ONE_VALUE_STATS;
import static com.google.common.math.StatsTesting.OTHER_MANY_VALUES;
import static com.google.common.math.StatsTesting.OTHER_MANY_VALUES_STATS;
import static com.google.common.math.StatsTesting.OTHER_ONE_VALUE_STATS;
import static com.google.common.math.StatsTesting.OTHER_TWO_VALUES_STATS;
import static com.google.common.math.StatsTesting.TWO_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.TWO_VALUES_STATS;
import static com.google.common.math.StatsTesting.TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS;
import static com.google.common.math.StatsTesting.VERTICAL_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.assertDiagonalLinearTransformation;
import static com.google.common.math.StatsTesting.assertHorizontalLinearTransformation;
import static com.google.common.math.StatsTesting.assertLinearTransformationNaN;
import static com.google.common.math.StatsTesting.assertStatsApproxEqual;
import static com.google.common.math.StatsTesting.assertVerticalLinearTransformation;
import static com.google.common.math.StatsTesting.createPairedStatsOf;
import static com.google.common.truth.Truth.assertThat;

import com.google.common.collect.ImmutableList;
import com.google.common.math.StatsTesting.ManyValues;
import com.google.common.testing.EqualsTester;
import com.google.common.testing.SerializableTester;

import junit.framework.TestCase;

import java.nio.ByteBuffer;
import java.nio.ByteOrder;

/**
 * Tests for {@link PairedStats}. This tests instances created by
 * {@link PairedStatsAccumulator#snapshot}.
 *
 * @author Pete Gillin
 */
public class PairedStatsTest extends TestCase {

  public void testCount() {
    assertThat(EMPTY_PAIRED_STATS.count()).isEqualTo(0);
    assertThat(ONE_VALUE_PAIRED_STATS.count()).isEqualTo(1);
    assertThat(TWO_VALUES_PAIRED_STATS.count()).isEqualTo(2);
    assertThat(MANY_VALUES_PAIRED_STATS.count()).isEqualTo(MANY_VALUES_COUNT);
  }

  public void testXStats() {
    assertStatsApproxEqual(EMPTY_STATS_ITERABLE, EMPTY_PAIRED_STATS.xStats());
    assertStatsApproxEqual(ONE_VALUE_STATS, ONE_VALUE_PAIRED_STATS.xStats());
    assertStatsApproxEqual(TWO_VALUES_STATS, TWO_VALUES_PAIRED_STATS.xStats());
    assertStatsApproxEqual(MANY_VALUES_STATS_ITERABLE, MANY_VALUES_PAIRED_STATS.xStats());
  }

  public void testYStats() {
    assertStatsApproxEqual(EMPTY_STATS_ITERABLE, EMPTY_PAIRED_STATS.yStats());
    assertStatsApproxEqual(OTHER_ONE_VALUE_STATS, ONE_VALUE_PAIRED_STATS.yStats());
    assertStatsApproxEqual(OTHER_TWO_VALUES_STATS, TWO_VALUES_PAIRED_STATS.yStats());
    assertStatsApproxEqual(OTHER_MANY_VALUES_STATS, MANY_VALUES_PAIRED_STATS.yStats());
  }

  public void testPopulationCovariance() {
    try {
      EMPTY_PAIRED_STATS.populationCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertThat(ONE_VALUE_PAIRED_STATS.populationCovariance()).isWithin(0.0).of(0.0);
    assertThat(createSingleStats(Double.POSITIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NEGATIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NaN, 1.23).populationCovariance()).isNaN();
    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      double populationCovariance = stats.populationCovariance();
      if (values.hasAnyNonFinite()) {
        assertThat(populationCovariance).named("population covariance of " + values).isNaN();
      } else {
        assertThat(populationCovariance)
            .named("population covariance of " + values)
            .isWithin(ALLOWED_ERROR)
            .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
      }
    }
    assertThat(HORIZONTAL_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(0.0);
    assertThat(VERTICAL_VALUES_PAIRED_STATS.populationCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(CONSTANT_VALUES_PAIRED_STATS.populationCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
  }

  public void testSampleCovariance() {
    try {
      EMPTY_PAIRED_STATS.sampleCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      ONE_VALUE_PAIRED_STATS.sampleCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertThat(TWO_VALUES_PAIRED_STATS.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS);
    assertThat(MANY_VALUES_PAIRED_STATS.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / (MANY_VALUES_COUNT - 1));
    assertThat(HORIZONTAL_VALUES_PAIRED_STATS.sampleCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(VERTICAL_VALUES_PAIRED_STATS.sampleCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(CONSTANT_VALUES_PAIRED_STATS.sampleCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
  }

  public void testPearsonsCorrelationCoefficient() {
    try {
      EMPTY_PAIRED_STATS.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      ONE_VALUE_PAIRED_STATS.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      createSingleStats(Double.POSITIVE_INFINITY, 1.23).pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertThat(TWO_VALUES_PAIRED_STATS.pearsonsCorrelationCoefficient())
        .isWithin(ALLOWED_ERROR)
        .of(
            TWO_VALUES_PAIRED_STATS.populationCovariance()
                / (TWO_VALUES_PAIRED_STATS.xStats().populationStandardDeviation()
                    * TWO_VALUES_PAIRED_STATS.yStats().populationStandardDeviation()));
    // For datasets of many double values, we test many combinations of finite and non-finite
    // y-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(MANY_VALUES, values.asIterable());
      double pearsonsCorrelationCoefficient = stats.pearsonsCorrelationCoefficient();
      if (values.hasAnyNonFinite()) {
        assertThat(pearsonsCorrelationCoefficient)
            .named("Pearson's correlation coefficient of " + values)
            .isNaN();
      } else {
        assertThat(pearsonsCorrelationCoefficient)
            .named("Pearson's correlation coefficient of " + values)
            .isWithin(ALLOWED_ERROR)
            .of(
                stats.populationCovariance()
                    / (stats.xStats().populationStandardDeviation()
                        * stats.yStats().populationStandardDeviation()));
      }
    }
    try {
      HORIZONTAL_VALUES_PAIRED_STATS.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      VERTICAL_VALUES_PAIRED_STATS.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      CONSTANT_VALUES_PAIRED_STATS.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
  }

  public void testLeastSquaresFit() {
    try {
      EMPTY_PAIRED_STATS.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      ONE_VALUE_PAIRED_STATS.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      createSingleStats(Double.POSITIVE_INFINITY, 1.23).leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertDiagonalLinearTransformation(
        TWO_VALUES_PAIRED_STATS.leastSquaresFit(),
        TWO_VALUES_PAIRED_STATS.xStats().mean(),
        TWO_VALUES_PAIRED_STATS.yStats().mean(),
        TWO_VALUES_PAIRED_STATS.xStats().populationVariance(),
        TWO_VALUES_PAIRED_STATS.populationCovariance());
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      LinearTransformation fit = stats.leastSquaresFit();
      if (values.hasAnyNonFinite()) {
        assertLinearTransformationNaN(fit);
      } else {
        assertDiagonalLinearTransformation(
            fit,
            stats.xStats().mean(),
            stats.yStats().mean(),
            stats.xStats().populationVariance(),
            stats.populationCovariance());
      }
    }
    assertHorizontalLinearTransformation(
        HORIZONTAL_VALUES_PAIRED_STATS.leastSquaresFit(),
        HORIZONTAL_VALUES_PAIRED_STATS.yStats().mean());
    assertVerticalLinearTransformation(
        VERTICAL_VALUES_PAIRED_STATS.leastSquaresFit(),
        VERTICAL_VALUES_PAIRED_STATS.xStats().mean());
    try {
      CONSTANT_VALUES_PAIRED_STATS.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
  }

  public void testEqualsAndHashCode() {
    new EqualsTester()
        .addEqualityGroup(
            MANY_VALUES_PAIRED_STATS,
            DUPLICATE_MANY_VALUES_PAIRED_STATS,
            SerializableTester.reserialize(MANY_VALUES_PAIRED_STATS))
        .addEqualityGroup(
            new PairedStats(MANY_VALUES_STATS_ITERABLE, OTHER_MANY_VALUES_STATS, 1.23),
            new PairedStats(MANY_VALUES_STATS_VARARGS, OTHER_MANY_VALUES_STATS, 1.23))
        .addEqualityGroup(
            new PairedStats(OTHER_MANY_VALUES_STATS, MANY_VALUES_STATS_ITERABLE, 1.23))
        .addEqualityGroup(
            new PairedStats(MANY_VALUES_STATS_ITERABLE, MANY_VALUES_STATS_ITERABLE, 1.23))
        .addEqualityGroup(
            new PairedStats(TWO_VALUES_STATS, MANY_VALUES_STATS_ITERABLE, 1.23))
        .addEqualityGroup(
            new PairedStats(MANY_VALUES_STATS_ITERABLE, ONE_VALUE_STATS, 1.23))
        .addEqualityGroup(
            new PairedStats(MANY_VALUES_STATS_ITERABLE, MANY_VALUES_STATS_ITERABLE, 1.234))
        .testEquals();
  }

  public void testSerializable() {
    SerializableTester.reserializeAndAssert(MANY_VALUES_PAIRED_STATS);
  }

  public void testToString() {
    assertThat(EMPTY_PAIRED_STATS.toString())
        .isEqualTo("PairedStats{xStats=Stats{count=0}, yStats=Stats{count=0}}");
    assertThat(MANY_VALUES_PAIRED_STATS.toString())
        .isEqualTo(
            "PairedStats{xStats="
                + MANY_VALUES_PAIRED_STATS.xStats()
                + ", yStats="
                + MANY_VALUES_PAIRED_STATS.yStats()
                + ", populationCovariance="
                + MANY_VALUES_PAIRED_STATS.populationCovariance()
                + "}");
  }

  private PairedStats createSingleStats(double x, double y) {
    return createPairedStatsOf(ImmutableList.of(x), ImmutableList.of(y));
  }

  public void testToByteArrayAndFromByteArrayRoundTrip() {
    for (PairedStats pairedStats : ALL_PAIRED_STATS) {
      byte[] pairedStatsByteArray = pairedStats.toByteArray();

      // Round trip to byte array and back
      assertThat(PairedStats.fromByteArray(pairedStatsByteArray)).isEqualTo(pairedStats);
    }
  }

  public void testFromByteArray_withNullInputThrowsNullPointerException() {
    try {
      PairedStats.fromByteArray(null);
      fail("Expected NullPointerException");
    } catch (NullPointerException expected) {
    }
  }

  public void testFromByteArray_withEmptyArrayInputThrowsIllegalArgumentException() {
   try {
      PairedStats.fromByteArray(new byte[0]);
      fail("Expected IllegalArgumentException");
    } catch (IllegalArgumentException expected) {
    }
  }

  public void testFromByteArray_withTooLongArrayInputThrowsIllegalArgumentException() {
    byte[] buffer = MANY_VALUES_PAIRED_STATS.toByteArray();
    byte[] tooLongByteArray = ByteBuffer.allocate(buffer.length + 2)
        .order(ByteOrder.LITTLE_ENDIAN)
        .put(buffer)
        .putChar('.')
        .array();
      try {
        PairedStats.fromByteArray(tooLongByteArray);
        fail("Expected IllegalArgumentException");
      } catch (IllegalArgumentException expected) {
      }
  }

  public void testFromByteArrayWithTooShortArrayInputThrowsIllegalArgumentException() {
    byte[] buffer = MANY_VALUES_PAIRED_STATS.toByteArray();
    byte[] tooShortByteArray = ByteBuffer.allocate(buffer.length - 1)
        .order(ByteOrder.LITTLE_ENDIAN)
        .put(buffer, 0, buffer.length - 1)
        .array();
    try {
      PairedStats.fromByteArray(tooShortByteArray);
      fail("Expected IllegalArgumentException");
    } catch (IllegalArgumentException expected) {
    }
  }
}

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