CI tweaks

.github/workflows/ci.yml

@@ -41,6 +41,6 @@ jobs:
         uses: julia-actions/julia-processcoverage@v1
       - name: Coverage Upload
         uses: codecov/codecov-action@v5
-        env:
-          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
           slug: JuliaMixedModels/MixedModelsExtras.jl

Project.toml

@@ -21,6 +21,7 @@ LinearAlgebra = "1"
 MixedModels = "4, 5"
 MixedModelsDatasets = "0.1"
 RDatasets = "0.7.7, 0.8"
+Suppressor = "0.2.8"
 StableRNGs = "1"
 Statistics = "1"
 StatsBase = "0.33, 0.34"
@@ -36,7 +37,8 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 MixedModelsDatasets = "7e9fb7ac-9f67-43bf-b2c8-96ba0796cbb6"
 RDatasets = "ce6b1742-4840-55fa-b093-852dadbb1d8b"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test", "Aqua", "DataFrames", "Distributions", "MixedModelsDatasets", "RDatasets", "StableRNGs"]
+test = ["Test", "Aqua", "DataFrames", "Distributions", "MixedModelsDatasets", "RDatasets", "Suppressor", "StableRNGs"]

test/icc.jl

@@ -2,7 +2,7 @@
     model = fit(MixedModel, @formula(reaction ~ 1 + (1 | subj)), dataset(:sleepstudy);
                 progress)
     @test icc(model, :subj) == icc(model, [:subj]) == icc(model)
-    @test icc(model, :subj) ≈ 0.37918288
+    @test icc(model, :subj) ≈ 0.37918288 rtol = 1e-6
 
     formula = @formula(rt_trunc ~ 1 + spkr * prec * load +
                                   (1 + spkr | subj) +
@@ -25,8 +25,9 @@ end
 
 @testset "Binomial" begin
     cbpp = dataset(:cbpp)
-    model = fit(MixedModel, @formula((incid / hsz) ~ 1 + (1 | herd)),
-                cbpp, Binomial(); wts=float(cbpp.hsz), progress)
+    # suppress depwarn on wts vs weights
+    model = @suppress fit(MixedModel, @formula((incid / hsz) ~ 1 + (1 | herd)),
+                          cbpp, Binomial(); wts=float(cbpp.hsz), progress)
     @test icc(model, :herd) == icc(model, [:herd]) == icc(model)
     @test icc(model, :herd) ≈ 0.1668 atol = 0.0005
 end
@@ -36,8 +37,10 @@ end
     modelbern = fit(MixedModel, @formula(use ~ 1 + (1 | urban & dist)),
                     contra, Bernoulli(); fast=true, progress)
     # force treating as a Binomial model
-    modelbin = fit(MixedModel, @formula(use ~ 1 + (1 | urban & dist)),
-                   contra, Binomial(); fast=true, wts=ones(length(contra.dist)), progress)
+    # suppress depwarn on wts vs weights
+    modelbin = @suppress fit(MixedModel, @formula(use ~ 1 + (1 | urban & dist)),
+                             contra, Binomial(); fast=true, wts=ones(length(contra.dist)),
+                             progress)
     # Bernoullis are a special case of binomial, so make sure they give the same answer
     @test icc(modelbern, Symbol("urban & dist")) ≈ icc(modelbin, Symbol("urban & dist"))
 

test/set_up_tests.jl

@@ -5,6 +5,7 @@ using GLM
 using LinearAlgebra
 using MixedModels
 using MixedModelsExtras
+using Suppressor
 using StableRNGs
 using Statistics
 using StatsBase

test/shrinkage.jl

@@ -16,7 +16,7 @@
     end
 
     @testset "_ranef error path" begin
-        @test_throws PosDefException _ranef(m1, 1e12 .* m1.optsum.initial)
+        @suppress @test_throws PosDefException _ranef(m1, 1e12 .* m1.optsum.initial)
     end
 end
 
@@ -41,6 +41,6 @@ end
                     @formula(ticks ~ 1 + year + height + (1 | index) + (1 | brood) +
                                      (1 | location)),
                     grouseticks, Poisson(); fast=true, progress)
-        @test_throws ArgumentError _ranef(model, NaN .* model.optsum.initial)
+        @suppress @test_throws ArgumentError _ranef(model, NaN .* model.optsum.initial)
     end
 end