Open alecloudenback opened 1 year ago
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
I think the first table like this facilitates comparison more so than the latte:
vs