MilesCranmer/PySR: v0.15.0

• Backend version update by @MilesCranmer in https://github.com/MilesCranmer/PySR/pull/389. Includes:
  • Dimensional analysis (see docs examples page)
  • Printing improvements
  • Many misc changes (see below)

• https://github.com/MilesCranmer/SymbolicRegression.jl/pull/228 and https://github.com/MilesCranmer/SymbolicRegression.jl/pull/230 and https://github.com/MilesCranmer/SymbolicRegression.jl/pull/231 and https://github.com/MilesCranmer/SymbolicRegression.jl/pull/235
  • Dimensional analysis (228)
    • Allows you to (softly) constrain discovered expressions to those that respect physical dimensions
    • Pass vectors of DynamicQuantities.jl Quantity type to the MLJ interface.
    • OR, specify X_units, y_units to low-level equation_search.
  • Printing improvements (228)
    • By default, only 5 significant digits are now printed, rather than the entire float. You can change this with the print_precision option.
    • In the default printed equations, x₁ is used rather than x1.
    • y = is printed at the start (or y₁ = for multi-output). With units this becomes, for example, y[kg] =.
  • Misc
    • Easier to convert from MLJ interface to SymbolicUtils (via node_to_symbolic(::Node, ::AbstractSRRegressor)) (228)
    • Improved precompilation (228)
    • Various performance and type stability improvements (228)
    • Inlined the recording option to speedup compilation (230)
    • Updated tutorials to use MLJ rather than low-level interface (228)
    • Moved JSON3.jl to extension (231)
    • Use PackageExtensionsCompat.jl over Requires.jl (231)
    • Require LossFunctions.jl to be 0.10 (231)
    • Batching inside optimization loop + batching support for custom objectives by (235)
    • Update docker defaults: Julia=1.9.1; Python=3.10.11 by @MilesCranmer in https://github.com/MilesCranmer/PySR/pull/371

Backend Changelog: https://github.com/MilesCranmer/SymbolicRegression.jl/compare/v0.20.0...v0.21.0

PySR Changelog: https://github.com/MilesCranmer/PySR/compare/v0.14.3...v0.15.0