v0.11.3

What's Changed

• Faster evaluation for constant sub-expressions (SymbolicRegression.jl#129)
• Will now check variable names for spaces and other non-alphanumeric characters, aside from underscores. Before this would only raise an issue after a search, when trying to pickle the saved data.

Full Changelog: v0.11.2...v0.11.3

v0.11.2

(Fix for conda-forge build)

Full Changelog: v0.11.1...v0.11.2

v0.11.1

What's Changed

• Added Customization page in the docs for tweaking the backend's loss function and constraints.
• Adding two entries to papers.yml by @JayWadekar in #192
• Explicitly deprecate Julia <= 1.5 by @MilesCranmer in #194
• Allow custom shared projects for julia_project by @MilesCranmer @mkitti in #197
  • e.g., this would allow you to run with @my-project and it will set up a shared Julia project under my-project (in the environments dir)

New Contributors

• @JayWadekar made their first contribution in #192

Full Changelog: v0.11.0...v0.11.1-1

v0.11.0

What's Changed

• Update backend #191
  • Includes high-precision constants when precision=64
  • Enables datasets with zero variance (to allow fitting a constant)
  • Changes, e.g., abs(x)^y to x^y, with expressions avoided altogether for invalid input. This is because the former would sometimes give weird functional forms by exploiting the cusp at x=0. Thanks to @johanbluecreek.

Full Changelog: v0.10.4...v0.11.0

v0.10.4

What's Changed

• Fix install for Julia <=1.6 by @MilesCranmer @mkitti in #188
  • PyJulia will now launch directly into the shared pysr-{version} environment, rather than activating it later.

Full Changelog: v0.10.3...v0.10.4

v0.10.3

What's Changed

• Displays a warning message when PyTorch is imported before PyJulia starts. See pytorch/pytorch#78829. The only current solution is to start Julia beforehand.
• New docs! Using Material-Mkdocs:

v0.10.2

What's Changed

• Set JULIA_PROJECT, use Pkg.add once by @mkitti in #186

Full Changelog: v0.10.1...v0.10.2

v0.10.1

Full Changelog: v0.10.0...v0.10.1

v0.10.0

What's Changed

• Easy loading from auto-generated checkpoint files by @MilesCranmer w/ review @tttc3 @Pablo-Lemos in #167
  • Use .from_file to load from the auto-generated .pkl file.
• LaTeX table generator by @MilesCranmer w/ review @tttc3 @kazewong in #156
  • Generate a LaTeX table of discovered equations with .latex_table()
• Improved default model selection strategy by @MilesCranmer in #177
  • Old strategy is available as model_selection="score"
• Add opencontainers image-spec to Dockerfile by @SauravMaheshkar w/ review @MilesCranmer in #166
• Switch to comma-based csv format by @MilesCranmer in #176

Bug fixes

• Fixed conversions to torch and JAX when a rational number appears in the sympy expression (17c9b1a, f119733)
• Fixed pickle saving when trained with multi-output (3da0df5)
• Fixed pickle saving when using custom operators with defined sympy -> jax/torch/numpy mappings
• Backend fix avoids use of Julia's cp which is buggy for some file systems (e.g., EOS)

New Contributors

• @SauravMaheshkar made their first contribution in #166

Full Changelog: v0.9.0...v0.10.0

v0.9.0

What's Changed

• Refactor of PySRRegressor by @tttc3 in #146
  • PySRRegressor is now completely compatible with scikit-learn.
  • PySRRegressor can be stored in a pickle file, even after fitting, and then be reloaded and used with .predict()
  • PySRRegressor.equations -> PySRRegressor.equations_

New Contributors

• @tttc3 made their first contribution in #146

Full Changelog: v0.8.7...v0.9.0