Miles Cranmer

Hi @firmai, Could you be more specific? Do you mean the `model.predict` function? Best, Miles

Ah, I think I see an issue (at least, for testing this). Right now the `init_julia` only sets the environment via an environment variable - rather than the `activate()` command....

Okay so now the `DEPOT_PATH` correctly sets the project. However, for some reason, `julia.install()` switches the environment back to the normal `DEPOT_PATH`... Not sure why. ```python from pysr.julia_helpers import init_julia,...

Thanks - the weird thing is that those commands are from the same Python session. So the DEPOT_PATH should stick around through the `install()` call…

Okay I think that got it. It wasn't the subprocess - it was the `JULIA_DEPOT_PATH` that was missing! Good catch.

Cool: ``` Activating project at `/var/folders/1h/xyppkvx52cl6w3_h8bw_gdqh0000gr/T/tmpmrkyi7cm/environments/pysr_test_env` ``` Not sure what the conda errors are though.

Ah, the conda errors were just because the `environment.yml` wasn't updated to the new Julia 1.8.0 requirement for openlibm - have since unpinned it and seems to be happy.

> It's not clear to me why SymbolicRegressions.jl should only be installed into a shared environment. I think this may just be left over logic when it was being installed...

Hi @Jgmedina95, Thanks for raising this! So this should be because `@inbounds` is used throughout the evaluation to have faster compute. I make an in-bounds assumption since trees made during...

Hi @qwertyjl, could you be more specific about where this is? I don't see much of a difference: ```julia julia> @btime 1.0 == 1; 1.583 ns (0 allocations: 0 bytes)...