Merge pull request #19 from JuliaAI/levels

Bump CategoricalArrays="1"

Author: ablaom

.github/workflows/ci.yml

@@ -15,19 +15,19 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.6'
+          - 'lts'
           - '1'
         os:
           - ubuntu-latest
         arch:
           - x64
     steps:
       - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: actions/cache@v1
+      - uses: julia-actions/cache@v2
         env:
           cache-name: cache-artifacts
         with:

Project.toml

@@ -1,26 +1,30 @@
 name = "MLJLIBSVMInterface"
 uuid = "61c7150f-6c77-4bb1-949c-13197eac2a52"
 authors = ["Anthony D. Blaom <[email protected]>"]
-version = "0.2.1"
+version = "0.2.2"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
+CategoricalDistributions = "af321ab8-2d2e-40a6-b165-3d674595d28e"
 LIBSVM = "b1bec4e5-fd48-53fe-b0cb-9723c09d164b"
 MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
-CategoricalArrays = "0.10"
+CategoricalArrays = "1"
+CategoricalDistributions = "0.2.1"
 LIBSVM = "0.8"
 MLJModelInterface = "1.4"
-julia = "1.6"
+Statistics = "1"
+julia = "1.10"
 
 [extras]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLJTestInterface = "72560011-54dd-4dc2-94f3-c5de45b75ecd"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+StatisticalMeasures = "a19d573c-0a75-4610-95b3-7071388c7541"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["LinearAlgebra", "MLJBase", "MLJTestInterface", "StableRNGs", "Test"]
+test = ["LinearAlgebra", "MLJBase", "MLJTestInterface", "StableRNGs", "StatisticalMeasures", "Test"]

src/MLJLIBSVMInterface.jl

@@ -10,7 +10,7 @@ export ProbabilisticNuSVC
 import MLJModelInterface
 import MLJModelInterface: Table, Continuous, Count, Finite, OrderedFactor,
                           Multiclass
-import CategoricalArrays
+import CategoricalArrays, CategoricalDistributions
 import LIBSVM
 using Statistics
 
@@ -384,13 +384,12 @@ function encode(weights::Dict, y)
     kys = CategoricalArrays.levels(y)
     Set(keys(weights)) == Set(kys) || throw(err_bad_weights(kys))
     _weights = fix_keys(weights, y)
-    levels_seen = unique(y) # not `CategoricalValue`s !
-    cvs = [categorical_value(x, y) for x in levels_seen]
-    return Dict(MMI.int(cv) => _weights[cv] for cv in cvs)
+    levels_seen = unique(y)
+    return Dict(CategoricalDistributions.int(cv) => _weights[cv] for cv in levels_seen)
 end
 
 function get_encoding(decoder)
-    refs = MMI.int.(decoder.classes)
+    refs = CategoricalDistributions.int.(CategoricalArrays.levels(decoder))
     return Dict(i => decoder(i) for i in refs)
 end
 
@@ -430,8 +429,8 @@ function MMI.fit(
     )
 
     Xmatrix = MMI.matrix(X)' # notice the transpose
-    y_plain = MMI.int(y)
-    decode  = MMI.decoder(y[1]) # for predict method
+    y_plain = CategoricalDistributions.int(y)
+    decode  = CategoricalDistributions.decoder(y[1]) # for predict method
 
     _weights = if weights == nothing
         nothing
@@ -464,8 +463,8 @@ function MMI.fit(
 )
 
     Xmatrix = MMI.matrix(X)' # notice the transpose
-    y_plain = MMI.int(y)
-    decode  = MMI.decoder(y[1]) # for predict method
+    y_plain = CategoricalDistributions.int(y)
+    decode  = CategoricalDistributions.decoder(y[1]) # for predict method
 
     _weights = if weights == nothing
         nothing

test/runtests.jl

@@ -6,6 +6,7 @@ using MLJLIBSVMInterface
 import StableRNGs
 import LIBSVM
 import MLJTestInterface
+using StatisticalMeasures
 
 @testset "`fix_keys` and `encode` for weight dicts" begin
     v = categorical(['a', 'b', 'b', 'c'])
@@ -51,7 +52,7 @@ end
                 data...;
                 mod=@__MODULE__,
                 verbosity=0, # bump to debug
-                throw=false, # set to true to debug
+                throw=true, # set to true to debug
             )
             @test isempty(failures)
         end