🐛 Fix CDDetector including tests and upgrade PyOD (#6)

* upgrade to pyod version 2

* fix cd detector

* fix tests to include all models

* upgrade package version

* fix python version to 3.12

* upgrade ci actions

* fix python version to 3.11

* fix ci actions to run only on master push and pr

* change to explicit sklearn python module import

* remove fixed python version again

.github/workflows/CI.yml

@@ -1,7 +1,10 @@
 name: CI
 on:
-  - push
-  - pull_request
+  push:
+      branches: [ master ]
+  # pull_request event is required only for autolabeler
+  pull_request:
+      types: [ opened, reopened, synchronize ]
 jobs:
   test:
     name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
@@ -19,12 +22,12 @@ jobs:
         arch:
           - x64
     steps:
-      - uses: actions/checkout@v3
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: julia-actions/cache@v1 # https://github.com/julia-actions/cache
+      - uses: julia-actions/cache@v2
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
       - uses: julia-actions/julia-processcoverage@v1

CondaPkg.toml

@@ -1,7 +1,7 @@
 channels = ["conda-forge"]
 
 [deps]
-pyod = "=1"
+pyod = "=2"
 
 [deps.llvmlite]
 channel = "numba"

Project.toml

@@ -1,7 +1,7 @@
 name = "OutlierDetectionPython"
 uuid = "2449c660-d36c-460e-a68b-92ab3c865b3e"
 authors = ["David Muhr <[email protected]> and contributors"]
-version = "0.2.2"
+version = "0.2.3"
 
 [deps]
 OutlierDetectionInterface = "1722ece6-f894-4ffc-b6be-6ca1174e2011"

src/OutlierDetectionPython.jl

@@ -3,9 +3,11 @@ module OutlierDetectionPython
     const OD = OutlierDetectionInterface
     using PythonCall
     const numpy = PythonCall.pynew()
+    const sklearn_linear = PythonCall.pynew()
 
     function __init__()
         PythonCall.pycopy!(numpy, pyimport("numpy"))
+        PythonCall.pycopy!(sklearn_linear, pyimport("sklearn.linear_model"))
     end
 
     include("utils.jl")

src/models.jl

@@ -38,8 +38,7 @@ end
 $(make_docs_link("cd"))
 """
 @pymodel mutable struct CDDetector <: UnsupervisedDetector
-    whitening::Bool = true
-    rule_of_thumb::Bool = false
+    model::Py = sklearn_linear.LinearRegression()
 end
 
 """    COPODDetector(n_jobs = 1)
@@ -77,7 +76,7 @@ $(make_docs_link("gmm"))
     reg_covar::Real = 1e-06::(_ >= 0)
     max_iter::Integer = 100::(_ > 0)
     n_init::Integer = 1::(_ > 0)
-    init_params::String = "kmeans"::(_ in ("kemans", "random"))
+    init_params::String = "kmeans"::(_ in ("kmeans", "random"))
     random_state::Union{Nothing,Integer} = nothing
     warm_start::Bool = false
 end

test/runtests.jl

@@ -1,59 +1,13 @@
 using OutlierDetectionPython
 using OutlierDetectionTest
 
+models = eval.(OutlierDetectionPython.MODELS)
+
 # Test the metadata of all exported detectors
-test_meta.(eval.(OutlierDetectionPython.MODELS))
+test_meta.(models)
 
 data = TestData()
 run_test(detector) = test_detector(detector, data)
 
-# ABOD
-run_test(ABODDetector())
-
-# CBLOF
-run_test(CBLOFDetector(random_state=0))
-
-# COF
-run_test(COFDetector())
-
-# COPOD
-run_test(COPODDetector())
-
-# HBOS
-run_test(HBOSDetector())
-
-# IForest
-run_test(IForestDetector(random_state=0))
-
-# KNN
-run_test(KNNDetector())
-
-# LMDD
-run_test(LMDDDetector(random_state=0))
-
-# LOD
-run_test(LODADetector())
-
-# LOF
-run_test(LOFDetector())
-
-# LOCI
-run_test(LOCIDetector())
-
-# MCD
-run_test(MCDDetector(random_state=0))
-
-# SVM
-run_test(OCSVMDetector())
-
-# PCA
-run_test(PCADetector(random_state=0))
-
-# ROD
-run_test(RODDetector())
-
-# SOD
-run_test(SODDetector())
-
-# SOS
-run_test(SOSDetector())
+# Test all models with default parameters
+run_test.([model() for model in models])