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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

Added

  • Badge to README to show code coverage percentage.
  • Support for Python 3.12.
  • Additional data classes coreax.data.Data and coreax.data.SupervisedData that draw distinction between supervised and unsupervised datasets, and handle weighted data.

Fixed

  • Wording improvements in README.
  • Documentation now builds without warnings.
  • GitHub workflow runs automatically after Pre-commit autoupdate.
  • coreax.kernel.Kernel.length_scale and coreax.kernel.Kernel.output_scale are treated as dynamic elements of the kernel pytree.

Changed

  • Documentation has been rearranged.
  • Renamed coreax.weights.MMD to coreax.weights.MMDWeightsOptimiser and added deprecation warning.
  • Renamed coreax.weights.SBQ to coreax.weights.SBQWeightsOptimiser and added deprecation warning.
  • requirements-*.txt will no longer be updated frequently, thereby providing stable versions.
  • Single requirements files covering all supported Python versions.
  • All references to kernel_matrix_row_{sum,mean} have been replaced with Gramian row-mean.

Removed

  • Bash script to run integration tests has been removed. pytest tests/integration should now work as expected.
  • Tests for coreax.kernels.Kernel.{calculate, update}_kernel_matrix_row_sum.
  • coreax.util.KernelComputeType; use Callable[[ArrayLike, ArrayLike], Array] instead.
  • coreax.kernels.Kernel.calculate_kernel_matrix_row_{sum,mean}; use coreax.kernels.Kernel.gramian_row_mean.
  • coreax.kernels.Kernel.updated_kernel_matrix_row_sum; use coreax.kernels.Kernel.gramian_row_mean if possible.

Deprecated

  • All uses of coreax.weights.MMD should be replaced with coreax.weights.MMDWeightsOptimiser.
  • All uses of coreax.weights.SBQ should be replaced with coreax.weights.SBQWeightsOptimiser.

0.1.0 - 2024-02-16

Added

  • Base Coreax package using Object-Oriented Programming incorporating:
    • coreset methods: kernel herding, random sample
    • reduction strategies: size reduce, map reduce
    • kernels: squared exponential, Laplacian, PCIMQ, Stein
    • refinement: regular, reverse, random
    • metrics: MMD
    • approximations of kernel matrix row sum mean: random, ANNchor, Nystrom
    • weights optimisers: SBQ, MMD
    • score matching: sliced score matching, kernel density estimation
    • I/O: array data not requiring any preprocessing
  • Near-complete unit test coverage.
  • Example scripts for coreset generation, which may be called as integration tests.
  • Bash script to run integration tests in sequence to avoid Jax errors.
  • Detailed documentation for the Coreax package published to Read the Docs.
  • README.md including an overview of what coresets are, setup instructions, a how-to guide, example applications and an overview of features coming soon.
  • Support for Python 3.9-3.11.
  • Project configuration and dependencies through pyproject.toml.
  • Requirements files providing a pinned set of dependencies that are known to work for each supported Python version.
  • Mark Coreax as typed.
  • This changelog to make it easier for users and contributors to see precisely what notable changes have been made between each release of the project.
  • FAQ.md to address any commonly asked questions.
  • Contributor guidelines, code of conduct, license and security policy.
  • Git configuration.
  • GitHub Actions to run unit tests on Windows, macOS and Ubuntu for supported Python versions.
  • Pre-commit checks to run the following, also checked by GitHub Actions:
    • black
    • isort
    • pylint
    • cspell spell check with custom dictionaries for library names, people and miscellaneous
    • pyroma
    • pydocstyle
    • assorted file format and encoding checks

Deprecated

  • Look-before-you-leap validation of all input to public functions