*/

package com.google.common.math;

import static com.google.common.math.MathTesting.ALL_BIGINTEGER_CANDIDATES;
import static com.google.common.math.MathTesting.FINITE_DOUBLE_CANDIDATES;
import static com.google.common.math.MathTesting.POSITIVE_FINITE_DOUBLE_CANDIDATES;
import static org.junit.Assert.assertThrows;

import java.lang.reflect.Method;
import java.math.BigInteger;
import junit.framework.TestCase;

/**

   * finite. Call either {@link LinearTransformationBuilder#and} or {@link
   * LinearTransformationBuilder#withSlope} on the returned object to finish building the instance.
   */
  public static LinearTransformationBuilder mapping(double x1, double y1) {
    checkArgument(isFinite(x1) && isFinite(y1));
    return new LinearTransformationBuilder(x1, y1);
  }

  /**

        fractionalBuilder.add(x);
      }
    }
    FRACTIONAL_DOUBLE_CANDIDATES = fractionalBuilder.build();
    FINITE_DOUBLE_CANDIDATES =
        Iterables.concat(FRACTIONAL_DOUBLE_CANDIDATES, INTEGRAL_DOUBLE_CANDIDATES);
    POSITIVE_FINITE_DOUBLE_CANDIDATES =
        Iterables.filter(
            FINITE_DOUBLE_CANDIDATES,
            new Predicate<Double>() {
              @Override

        .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);

        .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);

  /**
   * Helper class for testing with non-finite values. {@link #ALL_MANY_VALUES} gives a number of
   * instances with many combinations of finite and non-finite values. All have {@link
   * #MANY_VALUES_COUNT} values. If all the values are finite then the mean is {@link
   * #MANY_VALUES_MEAN} and the sum-of-squares-of-deltas is {@link
   * #MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS}. The smallest and largest finite values are always

    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();

    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();

        fractionalBuilder.add(x);
      }
    }
    FRACTIONAL_DOUBLE_CANDIDATES = fractionalBuilder.build();
    FINITE_DOUBLE_CANDIDATES =
        Iterables.concat(FRACTIONAL_DOUBLE_CANDIDATES, INTEGRAL_DOUBLE_CANDIDATES);
    POSITIVE_FINITE_DOUBLE_CANDIDATES =
        Iterables.filter(
            FINITE_DOUBLE_CANDIDATES,
            new Predicate<Double>() {
              @Override

    assertThat(TWO_VALUES_STATS.mean()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MEAN);
    // For datasets of many double values created from an array, we test many combinations of finite
    // and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      double mean = Stats.of(values.asArray()).mean();
      if (values.hasAnyNaN()) {
        assertWithMessage("mean of " + values).that(mean).isNaN();