BSD-3-Clause licensed and maintained by Oleg Grenrus
This version can be pinned in stack with:tdigest-0.2@sha256:c5af793969f3773c6ffce2b75c00c344726ed30549e2c5c833ae1dfc7e766767,3187

Module documentation for 0.2

  • Data
    • Data.TDigest
      • Data.TDigest.Internal
      • Data.TDigest.NonEmpty
      • Data.TDigest.Postprocess
        • Data.TDigest.Postprocess.Internal
      • Data.TDigest.Tree
        • Data.TDigest.Tree.Internal
        • Data.TDigest.Tree.NonEmpty
        • Data.TDigest.Tree.Postprocess
      • Data.TDigest.Vector
        • Data.TDigest.Vector.Internal
        • Data.TDigest.Vector.NonEmpty
        • Data.TDigest.Vector.Postprocess

tdigest

A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means.

See original paper: “Computing extremely accurate quantiles using t-digest” by Ted Dunning and Otmar Ertl

Synopsis

λ *Data.TDigest > median (tdigest [1..1000] :: TDigest 3)
Just 499.0090729817737

Benchmarks

Using 50M exponentially distributed numbers:

  • average: 16s; incorrect approximation of median, mostly to measure prng speed
  • sorting using vector-algorithms: 33s; using 1000MB of memory
  • sparking t-digest (using some par): 53s
  • buffered t-digest: 68s
  • sequential t-digest: 65s

Example histogram

tdigest-simple -m tdigest -d standard -s 100000 -c 10 -o output.svg -i 34
cp output.svg example.svg
inkscape --export-png=example.png --export-dpi=80 --export-background-opacity=0 --without-gui example.svg

Example

Changes

0.2

  • Add Data.TDigest.Vector module.

0.1

  • Add validateHistogram and debugPrint
  • Fix a pointy centroid bug.
  • Add Data.TDigest.NonEmpty module
  • Add mean, variance, stddev