SlidingPercentile

Artifact: androidx.media3:media3-exoplayer

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Kotlin |Java

@UnstableApi
class SlidingPercentile

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Calculate any percentile over a sliding window of weighted values. A maximum weight is configured. Once the total weight of the values reaches the maximum weight, the oldest value is reduced in weight until it reaches zero and is removed. This maintains a constant total weight, equal to the maximum allowed, at the steady state.

This class can be used for bandwidth estimation based on a sliding window of past transfer rate observations. This is an alternative to sliding mean and exponential averaging which suffer from susceptibility to outliers and slow adaptation to step functions.

See the following Wikipedia articles:

• Moving average
• Selection algorithm

Summary

Public constructors
SlidingPercentile(maxWeight: Int)

Public functions
Unit	addSample(weight: Int, value: Float) Adds a new weighted value.
Float	getPercentile(percentile: Float) Computes a percentile by integration.
Unit	reset() Resets the sliding percentile.

Public constructors

SlidingPercentile

SlidingPercentile(maxWeight: Int)

Parameters
maxWeight: Int	The maximum weight.

Public functions

addSample

fun addSample(weight: Int, value: Float): Unit

Adds a new weighted value.

Parameters
weight: Int	The weight of the new observation.
value: Float	The value of the new observation.

getPercentile

fun getPercentile(percentile: Float): Float

Computes a percentile by integration.

Parameters
percentile: Float	The desired percentile, expressed as a fraction in the range (0,1].

Returns
Float	The requested percentile value or NaN if no samples have been added.

reset

fun reset(): Unit

Resets the sliding percentile.