diff --git a/NEWS.md b/NEWS.md index fa0da0825..3c413b95c 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,8 @@ +MixedModels v4.25.2 Release Notes +============================== +- Use `public` keyword so that users don't see unnecessary docstring warnings on 1.11+. [#776] +- Fix accidental export of `dataset` and `datasets` and make them `public` instead. [#776] + MixedModels v4.25.1 Release Notes ============================== - Use more sophisticated checks on property names in `restoreoptsum` to allow for optsums saved by pre-v4.25 versions to be used with this version and later. [#775] @@ -543,3 +548,4 @@ Package dependencies [#772]: https://github.com/JuliaStats/MixedModels.jl/issues/772 [#773]: https://github.com/JuliaStats/MixedModels.jl/issues/773 [#775]: https://github.com/JuliaStats/MixedModels.jl/issues/775 +[#776]: https://github.com/JuliaStats/MixedModels.jl/issues/776 diff --git a/Project.toml b/Project.toml index 52e937998..d66f85475 100644 --- a/Project.toml +++ b/Project.toml @@ -1,11 +1,12 @@ name = "MixedModels" uuid = "ff71e718-51f3-5ec2-a782-8ffcbfa3c316" author = ["Phillip Alday ", "Douglas Bates ", "Jose Bayoan Santiago Calderon "] -version = "4.25.1" +version = "4.25.2" [deps] Arrow = "69666777-d1a9-59fb-9406-91d4454c9d45" BSplineKit = "093aae92-e908-43d7-9660-e50ee39d5a0a" +Compat = "34da2185-b29b-5c13-b0c7-acf172513d20" DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a" Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f" GLM = "38e38edf-8417-5370-95a0-9cbb8c7f171a" @@ -33,6 +34,7 @@ TypedTables = "9d95f2ec-7b3d-5a63-8d20-e2491e220bb9" Aqua = "0.8" Arrow = "1, 2" BSplineKit = "0.14, 0.15, 0.16, 0.17" +Compat = "4.10" DataAPI = "1" DataFrames = "1" Distributions = "0.21, 0.22, 0.23, 0.24, 0.25" diff --git a/src/MixedModels.jl b/src/MixedModels.jl index 27037facc..d3b1bddb2 100644 --- a/src/MixedModels.jl +++ b/src/MixedModels.jl @@ -4,6 +4,7 @@ using Arrow: Arrow using Base: Ryu, require_one_based_indexing using BSplineKit: BSplineKit, BSplineOrder, Natural, Derivative, SplineInterpolation using BSplineKit: interpolate +using Compat: @compat using DataAPI: DataAPI, levels, refpool, refarray, refvalue using Distributions: Distributions, Bernoulli, Binomial, Chisq, Distribution, Gamma using Distributions: InverseGaussian, Normal, Poisson, ccdf @@ -89,8 +90,6 @@ export @formula, condVar, condVartables, confint, - dataset, - datasets, deviance, dispersion, dispersion_parameter, @@ -160,6 +159,8 @@ export @formula, # TODO: move this to the correct spot in list once we've decided on name export savereplicates, restorereplicates +@compat public rePCA, PCA, dataset, datasets + """ MixedModel @@ -209,8 +210,8 @@ include("profile/profile.jl") @setup_workload begin # Putting some things in `setup` can reduce the size of the # precompile file and potentially make loading faster. - sleepstudy = MixedModels.dataset(:sleepstudy) - contra = MixedModels.dataset(:contra) + sleepstudy = dataset(:sleepstudy) + contra = dataset(:contra) progress = false @compile_workload begin # all calls in this block will be precompiled, regardless of whether diff --git a/test/pls.jl b/test/pls.jl index 5d39e69b9..c0a540278 100644 --- a/test/pls.jl +++ b/test/pls.jl @@ -628,7 +628,7 @@ end """ ) @test_throws(ArgumentError("initial or final parameters in io do not satisfy lowerbd"), - restoreoptsum!(m, seekstart(iob))) + @suppress restoreoptsum!(m, seekstart(iob))) # make sure new fields are correctly restored mktemp() do path, io @@ -638,7 +638,7 @@ end saveoptsum(io, m) m.optsum.xtol_zero_abs = 1.0 m.optsum.ftol_zero_abs = 1.0 - restoreoptsum!(m, seekstart(io)) + @suppress restoreoptsum!(m, seekstart(io)) @test m.optsum.xtol_zero_abs == 0.5 @test m.optsum.ftol_zero_abs == 0.5 end @@ -646,7 +646,7 @@ end end @testset "profile" begin - pr = profile(last(models(:sleepstudy))) + pr = @suppress profile(last(models(:sleepstudy))) tbl = pr.tbl @test length(tbl) >= 122 ci = confint(pr) diff --git a/test/predict.jl b/test/predict.jl index a55272bbc..8307bd5c7 100644 --- a/test/predict.jl +++ b/test/predict.jl @@ -143,7 +143,7 @@ end slp1 = subset(slp, :days => ByRow(>(0))) # this model probably doesn't make much sense, but it has two # variables on the left hand side in a FunctionTerm - m = fit(MixedModel, @formula(reaction / days ~ 1 + (1|subj)), slp1) + m = @suppress fit(MixedModel, @formula(reaction / days ~ 1 + (1|subj)), slp1) # make sure that we're getting the transformation @test response(m) ≈ slp1.reaction ./ slp1.days @test_throws ArgumentError predict(m, slp[:, Not(:reaction)]) @@ -154,7 +154,7 @@ end @test predict(m, slp1) ≈ fitted(m) - m = fit(MixedModel, @formula(log10(reaction) ~ 1 + days + (1|subj)), slp1) + m = @suppress fit(MixedModel, @formula(log10(reaction) ~ 1 + days + (1|subj)), slp1) # make sure that we're getting the transformation @test response(m) ≈ log10.(slp1.reaction) @test_throws ArgumentError predict(m, slp[:, Not(:reaction)])