tdigest

On-line accumulation of rank-based statistics

https://github.com/futurice/haskell-tdigest#readme

Version on this page:0.1@rev:2
LTS Haskell 22.39:0.3.1
Stackage Nightly 2024-10-31:0.3.1
Latest on Hackage:0.3.1

See all snapshots tdigest appears in

BSD-3-Clause licensed and maintained by Oleg Grenrus
This version can be pinned in stack with:tdigest-0.1@sha256:b371e737f90876cccc9ef69bf1c5a7087c1cacd2e7a4ad2ba53c90a0fcafa43c,2612

Module documentation for 0.1

Used by 4 packages in lts-9.21(full list with versions):
chart-unit, online, perf, tdigest-Chart

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

0.1

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