Skip to content

Presentation of output #27

@alecloudenback

Description

@alecloudenback

I think the first table like this facilitates comparison more so than the latte:

Times are in nanoseconds:
┌──────────┬──────────────────┬───────────────────┬─────────┬─────────────┬───────────────┐
│ Language │          Package │          Function │  Median │        Mean │ Relative Mean │
├──────────┼──────────────────┼───────────────────┼─────────┼─────────────┼───────────────┤
│   Python │  numpy_financial │               irr │ missing │  5339167688 │       332824x │
│   Python │           better │ irr_binary_search │ missing │     6167798 │          384x │
│   Python │           better │        irr_newton │ missing │      945813 │           59x │
│    Julia │ ActuaryUtilities │               irr │   16000 │       16042 │            1x │
└──────────┴──────────────────┴───────────────────┴─────────┴─────────────┴───────────────┘

vs

basic_term_benchmark:
- Julia CacheFlow basic_term:
    mean: TrialEstimate(192.127 ms)
    result: 1.4489630534602132e7
- Python jax basic_term_m:
    mean: 337.39129650000166 milliseconds
    result: 14489630.53460337
  Python lifelib basic_term_m:
    mean: 1182.7541804499986 milliseconds
    result: 14489630.534601536
  Python scratch basic_term_m:
    mean: 957.6274868500008 milliseconds
    result: 14489630.534603368

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions