sweetpareto 1.0.0rc0

Extracting and plotting pareto fronts

sweet_pareto

Generate pareto fronts from pandas data frames

Usage

Best used inside a Jupyter Notebook. There are some quirks trying to make the plot and save natively with matplotlib that I'm trying to sort out still.

Plot API

Install from pypi with pip or uv (or compliant tool of your choice) with pip install sweetpareto[plot].

Using the Palmer penguins dataset

import seaborn
import sweetpareto.vis as spv

df = seaborn.load_dataset("penguins")

>>> spv.pareto_plot(
...     df,
...     xs="flipper_length_mm",
...     y="body_mass_g",
...     maxx=False,
...     maxy=True,
...     col="sex",
...     color="species",
...     marker="species",
...     height=4,
...     aspect=1,
...     theme="whitegrid",
...     show_points=True,
... )

There is also spv.Pareto, a seaborn.objects.Stat object that can be used to make your own plots with the seaborn.objects API

Core API

The sweetpareto module provides two functions: pareto_indices and pareto_index. The names are similar, but their purposes are slightly different.

If you have a pandas.DataFrame, you can obtain a subsection of the index for the points that reside on the pareto front with pareto_index

>>> ix = sweetpareto.pareto_index(
...     df,
...     x="flipper_length_mm",
...     y="body_mass_g",
...     maxx=False,
...     maxy=True,
... )
>>> ix
Index([28, 20, 122, 31, 29, 39, 7, 81, 109, 252, 259, 329, 233, 297, 237], dtype='int64')

This Index can be used to access the whole data set along the pareto front with df.loc[ix].

pareto_index uses pareto_indices behind the scenes. This function works on two equal sized vectors x and y. The returned list contains the positions in x and y that make up the pareto front.

The core API can be installed with pip install sweetpareto, excluding the [plot] extras group.

Engines

For a little future proofing / YAGNI-as-a-service, everything discussed this far also accepts an engines argument. Presently, the only engine that is supported is a pure numpy + python routine for finding the pareto front. The goal of this API is to eventually ship some more performant engines

Dev

The dev environment is managed with hatch. I'm still learning this so if you see something that needs improvement, please let me know.

Release

For a given version X.Y.Z,

hatch version "X.Y.Z"

will update the project version. This will need to be committed and, eventually, merged to main.

Once the new version has been merged to main,

1. Make a tag with git tag
2. Build with hatch build
3. Publish with hatch publish

Test images

Build the test images with

hatch run test:gen-test-images

and then, upon acceptable review of images in tests/baseline, stage and commit the new images.

License

This project is made available under the terms of the Mozilla Public License, version 2.0

Issues / features

If you find something doesn't work as expected, or you'd like to propose a feature, please consider creating an issue on the codeberg issue tracker.

This is a fun project for me to work on, and it's also an excuse for me to try out new (to me) Python things. So, be aware that I might not respond immediately, and may not take up your issue or feature request. That doesn't mean it's not worthwhile. Just that I've got a life outside of this project and will not be able to handle all requests.

Contributing

Thank you! I'm glad you found this project interesting enough to put some of your valuable time into a pull request. See the CONTRIBUTING.md file for advice.