Fixes failing tests due to scipy version bump

src/UQpy/sampling/stratified_sampling/strata/VoronoiStrata.py

@@ -175,18 +175,18 @@ def sample_strata(self, nsamples_per_stratum, random_state):
 
             # Compute volume of each delaunay
             volume = list()
-            for i in range(len(delaunay_obj.vertices)):
-                vert = delaunay_obj.vertices[i]
+            for i in range(len(delaunay_obj.simplices)):
+                vert = delaunay_obj.simplices[i]
                 ch = ConvexHull(seed_and_vertices[vert])
                 volume.append(ch.volume)
 
             temp_prob = np.array(volume) / sum(volume)
-            a = list(range(len(delaunay_obj.vertices)))
+            a = list(range(len(delaunay_obj.simplices)))
             for k in range(int(nsamples_per_stratum[j])):
                 simplex = random_state.choice(a, p=temp_prob)
 
                 new_samples = SimplexSampling(
-                    nodes=seed_and_vertices[delaunay_obj.vertices[simplex]],
+                    nodes=seed_and_vertices[delaunay_obj.simplices[simplex]],
                     nsamples=1,
                     random_state=self.random_state,
                 ).samples
@@ -205,15 +205,15 @@ def compute_centroids(self):
 
         for j in range(self.mesh.nsimplex):
             try:
-                ConvexHull(self.points[self.mesh.vertices[j]])
+                ConvexHull(self.points[self.mesh.simplices[j]])
                 self.mesh.centroids[j, :], self.mesh.volumes[j] = \
-                    DelaunayStrata.compute_delaunay_centroid_volume(self.points[self.mesh.vertices[j]])
+                    DelaunayStrata.compute_delaunay_centroid_volume(self.points[self.mesh.simplices[j]])
             except qhull.QhullError:
                 self.mesh.centroids[j, :], self.mesh.volumes[j] = (np.mean(self.points[self.mesh.vertices[j]]), 0,)
 
     def initialize(self, samples_number, training_points):
         self.add_boundary_points_and_construct_delaunay(samples_number, training_points)
-        self.mesh.old_vertices = self.mesh.vertices.copy()
+        self.mesh.old_vertices = self.mesh.simplices.copy()
 
     def add_boundary_points_and_construct_delaunay(
             self, samples_number, training_points
@@ -377,7 +377,7 @@ def _update_strata(self, new_point, samples_u01):
         p_ = new_point.shape[0]
         # Update the matrices to have recognize the new point
         self.points_to_samplesU01 = np.hstack([self.points_to_samplesU01, np.arange(i_, i_ + p_)])
-        self.mesh.old_vertices = self.mesh.vertices
+        self.mesh.old_vertices = self.mesh.simplices
 
         # Update the Delaunay triangulation mesh to include the new point.
         self.mesh.add_points(new_point)

tests/unit_tests/sampling/test_refined_stratified.py

@@ -1,5 +1,5 @@
 import pytest
-from beartype.roar import BeartypeCallHintPepParamException
+from beartype.roar import BeartypeCallHintPepParamException, BeartypeCallHintParamViolation
 
 from UQpy import GaussianProcessRegression, LinearRegression
 from UQpy.utilities.kernels.euclidean_kernels.RBF import RBF
@@ -180,11 +180,9 @@ def test_rss_kriging_object():
     x = TrueStratifiedSampling(distributions=marginals, strata_object=strata, nsamples_per_stratum=1, random_state=1)
     model = PythonModel(model_script='python_model_function.py', model_object_name="y_func")
     rmodel = RunModel(model=model)
-    with pytest.raises(NotImplementedError):
+    with pytest.raises(BeartypeCallHintParamViolation):
         refinement = GradientEnhancedRefinement(strata=x.strata_object, runmodel_object=rmodel,
                                                 surrogate="abc")
-        RefinedStratifiedSampling(stratified_sampling=x, nsamples=6, samples_per_iteration=2,
-                                  refinement_algorithm=refinement)
 
 
 def test_nsamples():