Merge branch 'topology-tool-kit:dev' into critical-point-tracking

Author: thom-dani

.github/workflows/package.yml

@@ -345,6 +345,8 @@ jobs:
           rm python/harmonicSkeleton.py
           rm python/topologicalOptimization_torus.py
         fi
+        # remove sklearn examples -- buggy on MacOS since sklearn-1.7
+        rm python/1manifoldLearning.py python/clusteringKelvinHelmholtzInstabilities.py python/karhunenLoveDigits64Dimensions.py python/mergeTreeClustering.py python/persistentGenerators_householdAnalysis.py python/persistentGenerators_periodicPicture.py
         pvpython -u python/run.py
       env:
         PV_PLUGIN_PATH: /usr/local/bin/plugins/TopologyToolKit
@@ -686,7 +688,7 @@ jobs:
         asset_name: ttk-$tag.exe
 
     - name: Delete package artifacts
-      uses: geekyeggo/delete-artifact@v2
+      uses: geekyeggo/delete-artifact@v5
       with:
           name: |
               ttk*

.github/workflows/test.yml

@@ -258,7 +258,7 @@ jobs:
         diff python/hashes/${{ matrix.os }}.json python/res.json
 
     - name: Delete TTK package artifact
-      uses: geekyeggo/delete-artifact@v2
+      uses: geekyeggo/delete-artifact@v5
       # delete package only once
       if: matrix.testSet == 'screenshotTests'
       with:
@@ -398,6 +398,8 @@ jobs:
         rm python/mpiExample.py
         # remove examples which fill up the memory
         rm python/topologicalOptimization_darkSky.py
+        # remove sklearn examples -- buggy on MacOS since sklearn-1.7
+        rm python/1manifoldLearning.py python/clusteringKelvinHelmholtzInstabilities.py python/karhunenLoveDigits64Dimensions.py python/mergeTreeClustering.py python/persistentGenerators_householdAnalysis.py python/persistentGenerators_periodicPicture.py
         pvpython -u python/run.py
       env:
         PV_PLUGIN_PATH: /usr/local/bin/plugins/TopologyToolKit

core/base/dimensionReduction/dimensionReduction.py

@@ -15,15 +15,15 @@ def doIt(X, method, ncomponents, nneighbors, njobs, rstate, params):
         # at least one module is not installed, aborting...
         return 0
 
+    import sklearn
     from sklearn import manifold
     from sklearn import decomposition
     import numpy as np
     from sys import platform
+    from packaging import version
 
-    if platform == "darwin":
-        import sklearn
-
-        sklearn.utils.parallel_backend("threading")
+    #if platform == "darwin":
+    #    sklearn.utils.parallel_backend("threading")
 
     if rstate > 0:
         np.random.seed(0)
@@ -81,20 +81,36 @@ def doIt(X, method, ncomponents, nneighbors, njobs, rstate, params):
             Y = mds.fit_transform(X)
         elif method == 3:
             tsneParams = params[3]
-            tsne = manifold.TSNE(
-                n_components=ncomponents,
-                perplexity=tsneParams[0],
-                early_exaggeration=tsneParams[1],
-                learning_rate=tsneParams[2],
-                n_iter=tsneParams[3],
-                n_iter_without_progress=tsneParams[4],
-                min_grad_norm=tsneParams[5],
-                metric=tsneParams[6],
-                init=tsneParams[7],
-                verbose=tsneParams[8],
-                method=tsneParams[9],
-                angle=tsneParams[10],
-            )
+            if version.parse(sklearn.__version__) >= version.parse("1.7.0"):
+                tsne = manifold.TSNE(
+                    n_components=ncomponents,
+                    perplexity=tsneParams[0],
+                    early_exaggeration=tsneParams[1],
+                    learning_rate=tsneParams[2],
+                    max_iter=tsneParams[3],
+                    n_iter_without_progress=tsneParams[4],
+                    min_grad_norm=tsneParams[5],
+                    metric=tsneParams[6],
+                    init=tsneParams[7],
+                    verbose=tsneParams[8],
+                    method=tsneParams[9],
+                    angle=tsneParams[10],
+                )
+            else:
+                tsne = manifold.TSNE(
+                    n_components=ncomponents,
+                    perplexity=tsneParams[0],
+                    early_exaggeration=tsneParams[1],
+                    learning_rate=tsneParams[2],
+                    n_iter=tsneParams[3],
+                    n_iter_without_progress=tsneParams[4],
+                    min_grad_norm=tsneParams[5],
+                    metric=tsneParams[6],
+                    init=tsneParams[7],
+                    verbose=tsneParams[8],
+                    method=tsneParams[9],
+                    angle=tsneParams[10],
+                )
             Y = tsne.fit_transform(X)
         elif method == 4:
             isoParams = params[4]

core/base/ripsPersistenceDiagram/CMakeLists.txt

@@ -28,5 +28,9 @@ target_link_libraries(ripsPersistenceDiagram PUBLIC Boost::boost)
 
 if(TTK_ENABLE_CGAL)
   target_compile_definitions(ripsPersistenceDiagram PUBLIC TTK_ENABLE_CGAL)
-  target_link_libraries(ripsPersistenceDiagram PRIVATE ${CGAL_LIBRARIES})
-endif()
+  if(CGAL_VERSION VERSION_LESS "6.0")
+    target_link_libraries(ripsPersistenceDiagram PRIVATE ${CGAL_LIBRARIES})
+  else()
+    target_link_libraries(ripsPersistenceDiagram PUBLIC CGAL::CGAL)
+  endif()
+endif()