* error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between
   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -

import static org.junit.Assert.assertThrows;

import com.google.common.base.CharMatcher;
import com.google.common.base.Equivalence;
import com.google.common.base.Joiner;
import com.google.common.base.Predicate;
import com.google.common.base.Splitter;
import com.google.common.base.Stopwatch;
import com.google.common.base.Ticker;
import com.google.common.collect.BiMap;
import com.google.common.collect.ClassToInstanceMap;

import java.util.List;
import java.util.ListIterator;
import java.util.NoSuchElementException;
import java.util.RandomAccess;
import java.util.concurrent.CopyOnWriteArrayList;
import java.util.function.Predicate;
import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * Static utility methods pertaining to {@link List} instances. Also see this class's counterparts

     *     <li>"l" or "l(num)" - lowest version or bottom list of lowest ones filter</li>
     *     <li>"s" - contextual snapshot filter</li>
     *     <li>"e(G:A:V)" - predicate filter (leaves out G:A:V from range, if hit, V can be range)</li>
     * </ul>
     * Example filter expression: <code>"h(5);s;e(org.foo:bar:1)</code> will cause: ranges are filtered for "top 5" (instead

   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between
   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import com.google.common.base.Predicate;
import com.google.common.collect.testing.AnEnum;
import com.google.common.collect.testing.IteratorTester;
import com.google.common.collect.testing.MinimalIterable;

   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between
   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -

    } catch (UnsupportedOperationException expected) {
    }
    assertCollectionsAreEquivalent(multiset, copy);

    try {
      multiset.removeIf(x -> false);
      fail("removeIf(Predicate) succeeded on unmodifiable collection");
    } catch (UnsupportedOperationException expected) {
    }
    assertCollectionsAreEquivalent(multiset, copy);

	if err := json.Unmarshal(xlMetaJSON, &jsoniterXLMeta); err != nil {
		t.Errorf("jsoniter parsing of XLMeta failed: %v", err)
	}

	compareXLMetaV1(t, unMarshalXLMeta, jsoniterXLMeta)
}

// Test the predicted part size from the part index
func TestGetPartSizeFromIdx(t *testing.T) {
	// Create test cases
	testCases := []struct {
		totalSize    int64
		partSize     int64
		partIndex    int
		expectedSize int64

   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between
   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -