Class Stats

java.lang.Object
com.google.common.math.Stats
All Implemented Interfaces:
Serializable
@GwtIncompatible public final class Stats extends Object implements Serializable
A bundle of statistical summary values -- sum, count, mean/average, min and max, and several forms of variance -- that were computed from a single set of zero or more floating-point values.

There are two ways to obtain a Stats instance:

  • If all the values you want to summarize are already known, use the appropriate Stats.of factory method below. Primitive arrays, iterables and iterators of any kind of Number, and primitive varargs are supported.
  • Or, to avoid storing up all the data first, create a StatsAccumulator instance, feed values to it as you get them, then call StatsAccumulator.snapshot().

Static convenience methods called meanOf are also provided for users who wish to calculate only the mean.

Java 8+ users: If you are not using any of the variance statistics, you may wish to use built-in JDK libraries instead of this class.

Since:
20.0
Author:
Pete Gillin, Kevin Bourrillion
See Also:

  • Method Details

    • of

      public static Stats of(Iterable<? extends Number> values)
      Returns statistics over a dataset containing the given values.
      Parameters:
      values - a series of values, which will be converted to double values (this may cause loss of precision)

    • of

      public static Stats of(Iterator<? extends Number> values)
      Returns statistics over a dataset containing the given values. The iterator will be completely consumed by this method.
      Parameters:
      values - a series of values, which will be converted to double values (this may cause loss of precision)

    • of

      public static Stats of(double... values)
      Returns statistics over a dataset containing the given values.
      Parameters:
      values - a series of values

    • of

      public static Stats of(int... values)
      Returns statistics over a dataset containing the given values.
      Parameters:
      values - a series of values

    • of

      public static Stats of(long... values)
      Returns statistics over a dataset containing the given values.
      Parameters:
      values - a series of values, which will be converted to double values (this may cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))

    • of

      public static Stats of(DoubleStream values)
      Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method.

      If you have a Stream<Double> rather than a DoubleStream, you should collect the values using toStats() instead.

      Parameters:
      values - a series of values
      Since:
      28.2 (but only since 33.4.0 in the Android flavor)

    • of

      public static Stats of(IntStream values)
      Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method.

      If you have a Stream<Integer> rather than an IntStream, you should collect the values using toStats() instead.

      Parameters:
      values - a series of values
      Since:
      28.2 (but only since 33.4.0 in the Android flavor)

    • of

      public static Stats of(LongStream values)
      Returns statistics over a dataset containing the given values. The stream will be completely consumed by this method.

      If you have a Stream<Long> rather than a LongStream, you should collect the values using toStats() instead.

      Parameters:
      values - a series of values, which will be converted to double values (this may cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
      Since:
      28.2 (but only since 33.4.0 in the Android flavor)

    • toStats

      public static Collector<Number,StatsAccumulator,Stats> toStats()
      Returns a Collector which accumulates statistics from a Stream of any type of boxed Number into a Stats. Use by calling boxedNumericStream.collect(toStats()). The numbers will be converted to double values (which may cause loss of precision).

      If you have any of the primitive streams DoubleStream, IntStream, or LongStream, you should use the factory method of(java.lang.Iterable<? extends java.lang.Number>) instead.

      Since:
      28.2 (but only since 33.4.0 in the Android flavor)

    • count

      public long count()
      Returns the number of values.

    • mean

      public double mean()
      Returns the arithmetic mean of the values. The count must be non-zero.

      If these values are a sample drawn from a population, this is also an unbiased estimator of the arithmetic mean of the population.

      Non-finite values

      If the dataset contains Double.NaN then the result is Double.NaN. If it contains both Double.POSITIVE_INFINITY and Double.NEGATIVE_INFINITY then the result is Double.NaN. If it contains Double.POSITIVE_INFINITY and finite values only or Double.POSITIVE_INFINITY only, the result is Double.POSITIVE_INFINITY. If it contains Double.NEGATIVE_INFINITY and finite values only or Double.NEGATIVE_INFINITY only, the result is Double.NEGATIVE_INFINITY.

      If you only want to calculate the mean, use meanOf(java.lang.Iterable<? extends java.lang.Number>) instead of creating a Stats instance.

      Throws:
      IllegalStateException - if the dataset is empty

    • sum

      public double sum()
      Returns the sum of the values.

      Non-finite values

      If the dataset contains Double.NaN then the result is Double.NaN. If it contains both Double.POSITIVE_INFINITY and Double.NEGATIVE_INFINITY then the result is Double.NaN. If it contains Double.POSITIVE_INFINITY and finite values only or Double.POSITIVE_INFINITY only, the result is Double.POSITIVE_INFINITY. If it contains Double.NEGATIVE_INFINITY and finite values only or Double.NEGATIVE_INFINITY only, the result is Double.NEGATIVE_INFINITY.

    • populationVariance

      public double populationVariance()
      Returns the population variance of the values. The count must be non-zero.

      This is guaranteed to return zero if the dataset contains only exactly one finite value. It is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.

      Non-finite values

      If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.

      Throws:
      IllegalStateException - if the dataset is empty

    • populationStandardDeviation

      public double populationStandardDeviation()
      Returns the population standard deviation of the values. The count must be non-zero.

      This is guaranteed to return zero if the dataset contains only exactly one finite value. It is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.

      Non-finite values

      If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.

      Throws:
      IllegalStateException - if the dataset is empty

    • sampleVariance

      public double sampleVariance()
      Returns the unbiased sample variance of the values. If this dataset is a sample drawn from a population, this is an unbiased estimator of the population variance of the population. The count must be greater than one.

      This is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.

      Non-finite values

      If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.

      Throws:
      IllegalStateException - if the dataset is empty or contains a single value

    • sampleStandardDeviation

      public double sampleStandardDeviation()
      Returns the corrected sample standard deviation of the values. If this dataset is a sample drawn from a population, this is an estimator of the population standard deviation of the population which is less biased than populationStandardDeviation() (the unbiased estimator depends on the distribution). The count must be greater than one.

      This is not guaranteed to return zero when the dataset consists of the same value multiple times, due to numerical errors. However, it is guaranteed never to return a negative result.

      Non-finite values

      If the dataset contains any non-finite values (Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, or Double.NaN) then the result is Double.NaN.

      Throws:
      IllegalStateException - if the dataset is empty or contains a single value

    • min

      public double min()
      Returns the lowest value in the dataset. The count must be non-zero.

      Non-finite values

      If the dataset contains Double.NaN then the result is Double.NaN. If it contains Double.NEGATIVE_INFINITY and not Double.NaN then the result is Double.NEGATIVE_INFINITY. If it contains Double.POSITIVE_INFINITY and finite values only then the result is the lowest finite value. If it contains Double.POSITIVE_INFINITY only then the result is Double.POSITIVE_INFINITY.

      Throws:
      IllegalStateException - if the dataset is empty

    • max

      public double max()
      Returns the highest value in the dataset. The count must be non-zero.

      Non-finite values

      If the dataset contains Double.NaN then the result is Double.NaN. If it contains Double.POSITIVE_INFINITY and not Double.NaN then the result is Double.POSITIVE_INFINITY. If it contains Double.NEGATIVE_INFINITY and finite values only then the result is the highest finite value. If it contains Double.NEGATIVE_INFINITY only then the result is Double.NEGATIVE_INFINITY.

      Throws:
      IllegalStateException - if the dataset is empty

    • equals

      public boolean equals(@Nullable Object obj)

      Note: This tests exact equality of the calculated statistics, including the floating point values. Two instances are guaranteed to be considered equal if one is copied from the other using second = new StatsAccumulator().addAll(first).snapshot(), if both were obtained by calling snapshot() on the same StatsAccumulator without adding any values in between the two calls, or if one is obtained from the other after round-tripping through java serialization. However, floating point rounding errors mean that it may be false for some instances where the statistics are mathematically equal, including instances constructed from the same values in a different order... or (in the general case) even in the same order. (It is guaranteed to return true for instances constructed from the same values in the same order if strictfp is in effect, or if the system architecture guarantees strictfp-like semantics.)

      Overrides:
      equals in class Object

    • hashCode

      public int hashCode()

      Note: This hash code is consistent with exact equality of the calculated statistics, including the floating point values. See the note on equals(java.lang.Object) for details.

      Overrides:
      hashCode in class Object

    • toString

      public String toString()
      Overrides:
      toString in class Object

    • meanOf

      public static double meanOf(Iterable<? extends Number> values)
      Returns the arithmetic mean of the values. The count must be non-zero.

      The definition of the mean is the same as mean.

      Parameters:
      values - a series of values, which will be converted to double values (this may cause loss of precision)
      Throws:
      IllegalArgumentException - if the dataset is empty

    • meanOf

      public static double meanOf(Iterator<? extends Number> values)
      Returns the arithmetic mean of the values. The count must be non-zero.

      The definition of the mean is the same as mean.

      Parameters:
      values - a series of values, which will be converted to double values (this may cause loss of precision)
      Throws:
      IllegalArgumentException - if the dataset is empty

    • meanOf

      public static double meanOf(double... values)
      Returns the arithmetic mean of the values. The count must be non-zero.

      The definition of the mean is the same as mean.

      Parameters:
      values - a series of values
      Throws:
      IllegalArgumentException - if the dataset is empty

    • meanOf

      public static double meanOf(int... values)
      Returns the arithmetic mean of the values. The count must be non-zero.

      The definition of the mean is the same as mean.

      Parameters:
      values - a series of values
      Throws:
      IllegalArgumentException - if the dataset is empty

    • meanOf

      public static double meanOf(long... values)
      Returns the arithmetic mean of the values. The count must be non-zero.

      The definition of the mean is the same as mean.

      Parameters:
      values - a series of values, which will be converted to double values (this may cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
      Throws:
      IllegalArgumentException - if the dataset is empty

    • toByteArray

      public byte[] toByteArray()
      Gets a byte array representation of this instance.

      Note: No guarantees are made regarding stability of the representation between versions.

    • fromByteArray

      public static Stats fromByteArray(byte[] byteArray)
      Creates a Stats instance from the given byte representation which was obtained by toByteArray().

      Note: No guarantees are made regarding stability of the representation between versions.