tdigest
On-line accumulation of rank-based statistics
https://github.com/phadej/haskell-tdigest#readme
| LTS Haskell 20.16: | 0.2.1.1@rev:3 |
| Stackage Nightly 2022-11-17: | 0.2.1.1@rev:3 |
| Latest on Hackage: | 0.2.1.1@rev:3 |
This version can be pinned in stack with:
tdigest-0.2.1.1@sha256:1607bb1fb9a5b5d7284b6ce67edf2d40c6c3d7c874a563b30170c2331cdf6928,2855Module documentation for 0.2.1.1
Depends on 9 packages(full list with versions):
Used by 1 package in nightly-2022-11-17(full list with versions):
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
