EmpiricalDynamics 0.1.5

Bug fixes (Julia / SymbolicRegression.jl backend)

This release repairs the JuliaCall path of the Julia backend, which had drifted out of sync with current SymbolicRegression.jl (tested against 1.13.2) and failed for all users on that path. The underlying engine was working; the R-side glue was not.

• setup_julia_backend() reported the backend as unavailable even when it was installed. The installed-package check used an incorrect hard-coded UUID for SymbolicRegression.jl (8254be44-1295-4e6a-a16d-e31fe2c4a48b); the correct UUID is 8254be44-1295-4e6a-a16d-46603ac705cb. The check now succeeds, so setup_julia_backend() returns TRUE when the package is present.

• symbolic_search(backend = "julia") failed with a single predictor. A one-column predictors produced a length-1 character vector that JuliaCall transfers to Julia as a scalar String, while SymbolicRegression’s variable_names argument requires an AbstractVector{String} (TypeError: in keyword argument variable_names ...). variable_names is now coerced to a Vector{String} on the Julia side, so single-predictor searches work.

• symbolic_search(backend = "julia") failed when extracting results. The Hall-of-Fame extraction sent a multi-statement Julia block through a julia_command call that parses a single expression, raising ParseError("extra token after end of expression") after a successful search. The extraction block is now wrapped in begin ... end (a single expression), so results are returned correctly as the Pareto frontier.

These fixes restore end-to-end operation of symbolic_search(backend = "julia") (both single- and multi-predictor) and of setup_julia_backend() on the JuliaCall path. No user-facing API changed.