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Java example source code file (PairedStatsAccumulatorTest.java)

This example Java source code file (PairedStatsAccumulatorTest.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, expected, illegalstateexception, lineartransformation, many_values_count, manyvalues, other_many_values, other_one_value, other_one_value_stats, other_two_values, other_two_values_stats, pairedstatsaccumulator, pearson's, two_values_stats, util

The PairedStatsAccumulatorTest.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.EMPTY_STATS_ITERABLE;
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_STATS_ITERABLE;
import static com.google.common.math.StatsTesting.MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS;
import static com.google.common.math.StatsTesting.ONE_VALUE;
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_COUNT;
import static com.google.common.math.StatsTesting.OTHER_MANY_VALUES_STATS;
import static com.google.common.math.StatsTesting.OTHER_ONE_VALUE;
import static com.google.common.math.StatsTesting.OTHER_ONE_VALUE_STATS;
import static com.google.common.math.StatsTesting.OTHER_TWO_VALUES;
import static com.google.common.math.StatsTesting.OTHER_TWO_VALUES_STATS;
import static com.google.common.math.StatsTesting.TWO_VALUES;
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.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.createFilledPairedStatsAccumulator;
import static com.google.common.math.StatsTesting.createPartitionedFilledPairedStatsAccumulator;
import static com.google.common.truth.Truth.assertThat;

import com.google.common.math.StatsTesting.ManyValues;

import junit.framework.TestCase;

import java.util.Collections;

/**
 * Tests for {@link PairedStatsAccumulator}. This tests the stats methods for instances built with
 * {@link PairedStatsAccumulator#add}, and various error cases of that method. For tests of the
 * {@link PairedStatsAccumulator#snapshot} method which returns {@link PairedStats} instances, see
 * {@link PairedStatsTest}.
 *
 * @author Pete Gillin
 */
public class PairedStatsAccumulatorTest extends TestCase {

  private PairedStatsAccumulator emptyAccumulator;
  private PairedStatsAccumulator emptyAccumulatorByAddAllEmptyPairedStats;
  private PairedStatsAccumulator oneValueAccumulator;
  private PairedStatsAccumulator oneValueAccumulatorByAddAllEmptyPairedStats;
  private PairedStatsAccumulator twoValuesAccumulator;
  private PairedStatsAccumulator twoValuesAccumulatorByAddAllPartitionedPairedStats;
  private PairedStatsAccumulator manyValuesAccumulator;
  private PairedStatsAccumulator manyValuesAccumulatorByAddAllPartitionedPairedStats;
  private PairedStatsAccumulator horizontalValuesAccumulator;
  private PairedStatsAccumulator horizontalValuesAccumulatorByAddAllPartitionedPairedStats;
  private PairedStatsAccumulator verticalValuesAccumulator;
  private PairedStatsAccumulator verticalValuesAccumulatorByAddAllPartitionedPairedStats;
  private PairedStatsAccumulator constantValuesAccumulator;
  private PairedStatsAccumulator constantValuesAccumulatorByAddAllPartitionedPairedStats;

  @Override
  protected void setUp() throws Exception {
    super.setUp();

    emptyAccumulator = new PairedStatsAccumulator();

    emptyAccumulatorByAddAllEmptyPairedStats = new PairedStatsAccumulator();
    emptyAccumulatorByAddAllEmptyPairedStats.addAll(emptyAccumulator.snapshot());

    oneValueAccumulator = new PairedStatsAccumulator();
    oneValueAccumulator.add(ONE_VALUE, OTHER_ONE_VALUE);

    oneValueAccumulatorByAddAllEmptyPairedStats = new PairedStatsAccumulator();
    oneValueAccumulatorByAddAllEmptyPairedStats.add(ONE_VALUE, OTHER_ONE_VALUE);
    oneValueAccumulatorByAddAllEmptyPairedStats.addAll(emptyAccumulator.snapshot());

    twoValuesAccumulator = createFilledPairedStatsAccumulator(TWO_VALUES, OTHER_TWO_VALUES);
    twoValuesAccumulatorByAddAllPartitionedPairedStats =
        createPartitionedFilledPairedStatsAccumulator(TWO_VALUES, OTHER_TWO_VALUES, 1);

    manyValuesAccumulator = createFilledPairedStatsAccumulator(MANY_VALUES, OTHER_MANY_VALUES);
    manyValuesAccumulatorByAddAllPartitionedPairedStats =
        createPartitionedFilledPairedStatsAccumulator(MANY_VALUES, OTHER_MANY_VALUES, 2);

    horizontalValuesAccumulator =
        createFilledPairedStatsAccumulator(
            MANY_VALUES, Collections.nCopies(MANY_VALUES_COUNT, OTHER_ONE_VALUE));
    horizontalValuesAccumulatorByAddAllPartitionedPairedStats =
        createPartitionedFilledPairedStatsAccumulator(
            MANY_VALUES, Collections.nCopies(MANY_VALUES_COUNT, OTHER_ONE_VALUE), 2);

    verticalValuesAccumulator =
        createFilledPairedStatsAccumulator(
            Collections.nCopies(OTHER_MANY_VALUES_COUNT, ONE_VALUE), OTHER_MANY_VALUES);
    verticalValuesAccumulatorByAddAllPartitionedPairedStats =
        createPartitionedFilledPairedStatsAccumulator(
            Collections.nCopies(OTHER_MANY_VALUES_COUNT, ONE_VALUE), OTHER_MANY_VALUES, 2);

    constantValuesAccumulator =
        createFilledPairedStatsAccumulator(
            Collections.nCopies(MANY_VALUES_COUNT, ONE_VALUE),
            Collections.nCopies(MANY_VALUES_COUNT, OTHER_ONE_VALUE));
    constantValuesAccumulatorByAddAllPartitionedPairedStats =
        createPartitionedFilledPairedStatsAccumulator(
            Collections.nCopies(MANY_VALUES_COUNT, ONE_VALUE),
            Collections.nCopies(MANY_VALUES_COUNT, OTHER_ONE_VALUE),
            2);
  }

  public void testCount() {
    assertThat(emptyAccumulator.count()).isEqualTo(0);
    assertThat(emptyAccumulatorByAddAllEmptyPairedStats.count()).isEqualTo(0);
    assertThat(oneValueAccumulator.count()).isEqualTo(1);
    assertThat(oneValueAccumulatorByAddAllEmptyPairedStats.count()).isEqualTo(1);
    assertThat(twoValuesAccumulator.count()).isEqualTo(2);
    assertThat(twoValuesAccumulatorByAddAllPartitionedPairedStats.count()).isEqualTo(2);
    assertThat(manyValuesAccumulator.count()).isEqualTo(MANY_VALUES_COUNT);
    assertThat(manyValuesAccumulatorByAddAllPartitionedPairedStats.count())
        .isEqualTo(MANY_VALUES_COUNT);
  }

  public void testCountOverflow_doesNotThrow() {
    PairedStatsAccumulator accumulator = new PairedStatsAccumulator();
    accumulator.add(ONE_VALUE, OTHER_ONE_VALUE);
    for (int power = 1; power < Long.SIZE - 1; power++) {
      accumulator.addAll(accumulator.snapshot());
    }
    // Should overflow without throwing.
    accumulator.addAll(accumulator.snapshot());
    assertThat(accumulator.count()).isLessThan(0L);
  }

  public void testXStats() {
    assertStatsApproxEqual(EMPTY_STATS_ITERABLE, emptyAccumulator.xStats());
    assertStatsApproxEqual(EMPTY_STATS_ITERABLE, emptyAccumulatorByAddAllEmptyPairedStats.xStats());
    assertStatsApproxEqual(ONE_VALUE_STATS, oneValueAccumulator.xStats());
    assertStatsApproxEqual(ONE_VALUE_STATS, oneValueAccumulatorByAddAllEmptyPairedStats.xStats());
    assertStatsApproxEqual(TWO_VALUES_STATS, twoValuesAccumulator.xStats());
    assertStatsApproxEqual(
        TWO_VALUES_STATS, twoValuesAccumulatorByAddAllPartitionedPairedStats.xStats());
    assertStatsApproxEqual(MANY_VALUES_STATS_ITERABLE, manyValuesAccumulator.xStats());
    assertStatsApproxEqual(
        MANY_VALUES_STATS_ITERABLE, manyValuesAccumulatorByAddAllPartitionedPairedStats.xStats());
  }

  public void testYStats() {
    assertStatsApproxEqual(EMPTY_STATS_ITERABLE, emptyAccumulator.yStats());
    assertStatsApproxEqual(EMPTY_STATS_ITERABLE, emptyAccumulatorByAddAllEmptyPairedStats.yStats());
    assertStatsApproxEqual(OTHER_ONE_VALUE_STATS, oneValueAccumulator.yStats());
    assertStatsApproxEqual(
        OTHER_ONE_VALUE_STATS, oneValueAccumulatorByAddAllEmptyPairedStats.yStats());
    assertStatsApproxEqual(OTHER_TWO_VALUES_STATS, twoValuesAccumulator.yStats());
    assertStatsApproxEqual(
        OTHER_TWO_VALUES_STATS, twoValuesAccumulatorByAddAllPartitionedPairedStats.yStats());
    assertStatsApproxEqual(OTHER_MANY_VALUES_STATS, manyValuesAccumulator.yStats());
    assertStatsApproxEqual(
        OTHER_MANY_VALUES_STATS, manyValuesAccumulatorByAddAllPartitionedPairedStats.yStats());
  }

  public void testPopulationCovariance() {
    try {
      emptyAccumulator.populationCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      emptyAccumulatorByAddAllEmptyPairedStats.populationCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertThat(oneValueAccumulator.populationCovariance()).isWithin(0.0).of(0.0);
    assertThat(oneValueAccumulatorByAddAllEmptyPairedStats.populationCovariance())
        .isWithin(0.0)
        .of(0.0);
    assertThat(twoValuesAccumulator.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    assertThat(twoValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    assertThat(manyValuesAccumulator.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    assertThat(manyValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =
          createFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES);
      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =
          createPartitionedFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES, 2);
      double populationCovariance = accumulator.populationCovariance();
      double populationCovarianceByAddAllPartitionedPairedStats =
          accumulatorByAddAllPartitionedPairedStats.populationCovariance();
      if (values.hasAnyNonFinite()) {
        assertThat(populationCovariance).named("population covariance of " + values).isNaN();
        assertThat(populationCovarianceByAddAllPartitionedPairedStats)
            .named("population covariance by addAll(PairedStats) 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(populationCovarianceByAddAllPartitionedPairedStats)
            .named("population covariance by addAll(PairedStats) of " + values)
            .isWithin(ALLOWED_ERROR)
            .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
      }
    }
    assertThat(horizontalValuesAccumulator.populationCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(horizontalValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(0.0);
    assertThat(verticalValuesAccumulator.populationCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(verticalValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(0.0);
    assertThat(constantValuesAccumulator.populationCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(constantValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(0.0);
  }

  public void testSampleCovariance() {
    try {
      emptyAccumulator.sampleCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      emptyAccumulatorByAddAllEmptyPairedStats.sampleCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      oneValueAccumulator.sampleCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      oneValueAccumulatorByAddAllEmptyPairedStats.sampleCovariance();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertThat(twoValuesAccumulator.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS);
    assertThat(twoValuesAccumulatorByAddAllPartitionedPairedStats.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS);
    assertThat(manyValuesAccumulator.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / (MANY_VALUES_COUNT - 1));
    assertThat(manyValuesAccumulatorByAddAllPartitionedPairedStats.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / (MANY_VALUES_COUNT - 1));
    assertThat(horizontalValuesAccumulator.sampleCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(horizontalValuesAccumulatorByAddAllPartitionedPairedStats.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(0.0);
    assertThat(verticalValuesAccumulator.sampleCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(verticalValuesAccumulatorByAddAllPartitionedPairedStats.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(0.0);
    assertThat(constantValuesAccumulator.sampleCovariance()).isWithin(ALLOWED_ERROR).of(0.0);
    assertThat(constantValuesAccumulatorByAddAllPartitionedPairedStats.sampleCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(0.0);
  }

  public void testPearsonsCorrelationCoefficient() {
    try {
      emptyAccumulator.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      emptyAccumulatorByAddAllEmptyPairedStats.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      oneValueAccumulator.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      oneValueAccumulatorByAddAllEmptyPairedStats.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertThat(twoValuesAccumulator.pearsonsCorrelationCoefficient())
        .isWithin(ALLOWED_ERROR)
        .of(
            twoValuesAccumulator.populationCovariance()
                / (twoValuesAccumulator.xStats().populationStandardDeviation()
                    * twoValuesAccumulator.yStats().populationStandardDeviation()));
    assertThat(manyValuesAccumulator.pearsonsCorrelationCoefficient())
        .isWithin(ALLOWED_ERROR)
        .of(
            manyValuesAccumulator.populationCovariance()
                / (manyValuesAccumulator.xStats().populationStandardDeviation()
                    * manyValuesAccumulator.yStats().populationStandardDeviation()));
    assertThat(manyValuesAccumulatorByAddAllPartitionedPairedStats.pearsonsCorrelationCoefficient())
        .isWithin(ALLOWED_ERROR)
        .of(
            manyValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance()
                / (manyValuesAccumulatorByAddAllPartitionedPairedStats
                        .xStats()
                        .populationStandardDeviation()
                    * manyValuesAccumulatorByAddAllPartitionedPairedStats
                        .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) {
      PairedStatsAccumulator accumulator =
          createFilledPairedStatsAccumulator(MANY_VALUES, values.asIterable());
      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =
          createPartitionedFilledPairedStatsAccumulator(MANY_VALUES, values.asIterable(), 2);
      double pearsonsCorrelationCoefficient = accumulator.pearsonsCorrelationCoefficient();
      double pearsonsCorrelationCoefficientByAddAllPartitionedPairedStats =
          accumulatorByAddAllPartitionedPairedStats.pearsonsCorrelationCoefficient();
      if (values.hasAnyNonFinite()) {
        assertThat(pearsonsCorrelationCoefficient)
            .named("Pearson's correlation coefficient of " + values)
            .isNaN();
        assertThat(pearsonsCorrelationCoefficient)
            .named("Pearson's correlation coefficient by addAll(PairedStats) of " + values)
            .isNaN();
      } else {
        assertThat(pearsonsCorrelationCoefficient)
            .named("Pearson's correlation coefficient of " + values)
            .isWithin(ALLOWED_ERROR)
            .of(
                accumulator.populationCovariance()
                    / (accumulator.xStats().populationStandardDeviation()
                        * accumulator.yStats().populationStandardDeviation()));
        assertThat(pearsonsCorrelationCoefficientByAddAllPartitionedPairedStats)
            .named("Pearson's correlation coefficient by addAll(PairedStats) of " + values)
            .isWithin(ALLOWED_ERROR)
            .of(
                accumulatorByAddAllPartitionedPairedStats.populationCovariance()
                    / (accumulatorByAddAllPartitionedPairedStats
                            .xStats()
                            .populationStandardDeviation()
                        * accumulatorByAddAllPartitionedPairedStats
                            .yStats()
                            .populationStandardDeviation()));
      }
    }
    try {
      horizontalValuesAccumulator.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      horizontalValuesAccumulatorByAddAllPartitionedPairedStats.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      verticalValuesAccumulator.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      verticalValuesAccumulatorByAddAllPartitionedPairedStats.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      constantValuesAccumulator.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      constantValuesAccumulatorByAddAllPartitionedPairedStats.pearsonsCorrelationCoefficient();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
  }

  public void testLeastSquaresFit() {
    try {
      emptyAccumulator.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      emptyAccumulatorByAddAllEmptyPairedStats.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      oneValueAccumulator.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      oneValueAccumulatorByAddAllEmptyPairedStats.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    assertDiagonalLinearTransformation(
        twoValuesAccumulator.leastSquaresFit(),
        twoValuesAccumulator.xStats().mean(),
        twoValuesAccumulator.yStats().mean(),
        twoValuesAccumulator.xStats().populationVariance(),
        twoValuesAccumulator.populationCovariance());
    assertDiagonalLinearTransformation(
        twoValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit(),
        twoValuesAccumulatorByAddAllPartitionedPairedStats.xStats().mean(),
        twoValuesAccumulatorByAddAllPartitionedPairedStats.yStats().mean(),
        twoValuesAccumulatorByAddAllPartitionedPairedStats.xStats().populationVariance(),
        twoValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance());
    assertDiagonalLinearTransformation(
        manyValuesAccumulator.leastSquaresFit(),
        manyValuesAccumulator.xStats().mean(),
        manyValuesAccumulator.yStats().mean(),
        manyValuesAccumulator.xStats().populationVariance(),
        manyValuesAccumulator.populationCovariance());
    assertDiagonalLinearTransformation(
        manyValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit(),
        manyValuesAccumulatorByAddAllPartitionedPairedStats.xStats().mean(),
        manyValuesAccumulatorByAddAllPartitionedPairedStats.yStats().mean(),
        manyValuesAccumulatorByAddAllPartitionedPairedStats.xStats().populationVariance(),
        manyValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance());
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =
          createFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES);
      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =
          createPartitionedFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES, 2);
      LinearTransformation fit = accumulator.leastSquaresFit();
      LinearTransformation fitByAddAllPartitionedPairedStats =
          accumulatorByAddAllPartitionedPairedStats.leastSquaresFit();
      if (values.hasAnyNonFinite()) {
        assertLinearTransformationNaN(fit);
        assertLinearTransformationNaN(fitByAddAllPartitionedPairedStats);
      } else {
        assertDiagonalLinearTransformation(
            fit,
            accumulator.xStats().mean(),
            accumulator.yStats().mean(),
            accumulator.xStats().populationVariance(),
            accumulator.populationCovariance());
        assertDiagonalLinearTransformation(
            fitByAddAllPartitionedPairedStats,
            accumulatorByAddAllPartitionedPairedStats.xStats().mean(),
            accumulatorByAddAllPartitionedPairedStats.yStats().mean(),
            accumulatorByAddAllPartitionedPairedStats.xStats().populationVariance(),
            accumulatorByAddAllPartitionedPairedStats.populationCovariance());
      }
    }
    assertHorizontalLinearTransformation(
        horizontalValuesAccumulator.leastSquaresFit(),
        horizontalValuesAccumulator.yStats().mean());
    assertHorizontalLinearTransformation(
        horizontalValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit(),
        horizontalValuesAccumulatorByAddAllPartitionedPairedStats.yStats().mean());
    assertVerticalLinearTransformation(
        verticalValuesAccumulator.leastSquaresFit(),
        verticalValuesAccumulator.xStats().mean());
    assertVerticalLinearTransformation(
        verticalValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit(),
        verticalValuesAccumulatorByAddAllPartitionedPairedStats.xStats().mean());
    try {
      constantValuesAccumulator.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
    try {
      constantValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit();
      fail("Expected IllegalStateException");
    } catch (IllegalStateException expected) {
    }
  }
}

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