palday
commented
3 years ago Let's go through this step by step. :smile:
RCall works its magic by creating a mechanism for defining conversions between Julia types and R type and then using that mechanism for a few common R/Julia types (data frames, vectors, etc.). This is relatively well tested code and I doubt that we're hitting a bug there.
JuliaCall starts a Julia process in the background, then loads RCall within that Julia process and let's RCall do all the heavy lifting. This is a bit of a Rube Goldberg machine, but I think it's gotten less fragile in the last year or so.
JellyMe4 uses the RCall mechanism to define some useful conversions between MixedModels.jl and lme4. However, there are deep philosophical differences between languages that rear their ugly head and so the conversion isn't as automagic as a lot of things using RCall are. In particular, lme4 models keep a copy of the data frame used to generate the model matrices (well, technically a reference that becomes a copy in certain circumstances, but we'll keep it simple here), but MixedModels.jl does not keep a copy of the data frame, instead keeping only the model matrices. This means that you can convert an lme4 model to a MixedModels.jl model because you can just discard the extra copy of the data, but a MixedModels.jl model is not sufficient to immediately create an lme4 model: you still need a copy of the data frame in question. Currently, this is done by passing a Julia tuple of the model and the data frame.
This brings us to your line / error:
julia.dir$eval("my_mod = fit(MixedModel, @formula(score ~ 1 + Machine + (1 + Machine|Worker)),dat)")
#> Error: Error happens in Julia.
#> ArgumentError: You must use a tuple with the data -- (MixedModel, DataFrame) -- not just a modelNotice the Julia error message: it's telling you what went wrong. To get a copy of that model back into R, you need to do something like:
julia.dir$eval("my_mod = fit(MixedModel, @formula(score ~ 1 + Machine + (1 + Machine|Worker)),dat); (my_mod, dat)")The bit before the semicolon fits and assigns the model to my_mod, the second part creates the required tuple. The last value (here: the tuple) is the return value and the one JuliaCall converts via RCall.
If you don't care about manipulating the model in Julia and thus don't need to assign it to a variable, you could fit the model and construct the tuple in one step:
julia.dir$eval("(fit(MixedModel, @formula(score ~ 1 + Machine + (1 + Machine|Worker)),dat), , dat)")Now, there is one piece of the puzzle remaining: why does it seem to work before JellyMe4 is loaded? Well, it's only kinda working: there is no defined conversion, so JuliaCall just calls the show method in Julia to get the Julia output and shows that in R. After you've loaded JellyMe4, there is a hook defined that says, "hey, you want to convert this model to R, but there isn't enough info to do so properly, so let's error and tell you what you need to do!".
You got this right with this line:
julia.dir$eval("robject(:lmerMod, Tuple([my_mod,dat]))", need_return="R")But when you tried fitting the model again, you only get the model and not the tuple back and so you get an error.
Hope that helps!
PS: You can simplify that line as well: julia.dir$eval("(my_mod,dat)").
john-b-edwards
I apologize for any ignorance on my part, as I'm far more well versed in R than I am in Julia. Been trying to come up with a way to run some large mixed models in Julia from R. I've noticed that when I load JellyMe4.jl, it breaks the fitting of mixed models using MixedModels.jl
Created on 2021-06-18 by the reprex package (v2.0.0)
If I call
julia.dir$library("JellyMe4")after fitting the model, then the code behaves correctly until I try to fit the mixed model again, when the same error pops up.Created on 2021-06-18 by the reprex package (v2.0.0)
What's unusual to me is that the Julia-equivalent code to me seems to work just fine, ex.
This very well might be an
RCallbug, but given that this specific interaction occurs betweenJellyMe4.jlandMixedModels.jl, I thought to post this here first and see if I could get any insight into why this is happening.