catch import error in tests

Author: JelmerBot

fast_hdbscan/branches.py

@@ -116,7 +116,7 @@ def fit(self, clusterer, labels=None, probabilities=None, sample_weight=None):
             self.probabilities_,
             self.cluster_probabilities_,
             self.cluster_points_,
-            self.linkage_trees_,
+            self._linkage_trees,
             label_sides_as_branches=self.label_sides_as_branches,
         )
         self.branch_labels_ = self.sub_cluster_labels_
@@ -135,7 +135,7 @@ def propagated_labels(self, label_sides_as_branches=None):
             np.zeros_like(self.probabilities_),
             np.zeros_like(self.probabilities_),
             self.cluster_points_,
-            self.linkage_trees_,
+            self._linkage_trees,
             label_sides_as_branches=label_sides_as_branches,
         )
         return labels, branch_labels

fast_hdbscan/tests/test_branches.py

@@ -7,6 +7,13 @@
 from sklearn.exceptions import NotFittedError
 from fast_hdbscan import HDBSCAN, BranchDetector, find_branch_sub_clusters
 
+try:
+    from hdbscan.plots import ApproximationGraph, CondensedTree, SingleLinkageTree
+
+    HAVE_HDBSCAN = True
+except ModuleNotFoundError:
+    HAVE_HDBSCAN = False
+
 
 def make_branches(points_per_branch=30):
     # Control points for line segments that merge three clusters
@@ -59,22 +66,15 @@ def check_detected_groups(c, n_clusters=3, n_branches=6, overridden=False):
 # --- Detecting Branches
 
 
+@pytest.mark.skipif(not HAVE_HDBSCAN, reason='Requires HDBSCAN')
 def test_attributes():
-    def check_attributes():
-        b = BranchDetector().fit(c)
-        check_detected_groups(b, n_clusters=2, n_branches=5)
-        assert len(b.linkage_trees_) == 2
-        assert len(b.condensed_trees_) == 2
-        assert isinstance(b.condensed_trees_[0], CondensedTree)
-        assert isinstance(b.linkage_trees_[0], SingleLinkageTree)
-        assert isinstance(b.approximation_graph_, ApproximationGraph)
-
-    try:
-        from hdbscan.plots import ApproximationGraph, CondensedTree, SingleLinkageTree
-
-        check_attributes()
-    except ImportError:
-        pass
+    b = BranchDetector().fit(c)
+    check_detected_groups(b, n_clusters=2, n_branches=5)
+    assert len(b.linkage_trees_) == 2
+    assert len(b.condensed_trees_) == 2
+    assert isinstance(b.condensed_trees_[0], CondensedTree)
+    assert isinstance(b.linkage_trees_[0], SingleLinkageTree)
+    assert isinstance(b.approximation_graph_, ApproximationGraph)
 
 
 def test_selection_method():

fast_hdbscan/tests/test_sub_clusters.py

@@ -6,6 +6,13 @@
 from fast_hdbscan.branches import compute_centrality
 from fast_hdbscan.sub_clusters import SubClusterDetector, find_sub_clusters
 
+try:
+    from hdbscan.plots import ApproximationGraph, CondensedTree, SingleLinkageTree
+
+    HAVE_HDBSCAN = True
+except ModuleNotFoundError:
+    HAVE_HDBSCAN = False
+
 
 def make_branches(points_per_branch=30):
     # Control points for line segments that merge three clusters
@@ -59,22 +66,15 @@ def check_detected_groups(c, n_clusters=3, n_subs=6, overridden=False):
 # --- Detecting SubClusters
 
 
+@pytest.mark.skipif(not HAVE_HDBSCAN, reason='Requires HDBSCAN')
 def test_attributes():
-    def check_attributes():
-        b = SubClusterDetector(lens_values=centrality).fit(c)
-        check_detected_groups(b, n_clusters=2, n_subs=7)
-        assert len(b.linkage_trees_) == 2
-        assert len(b.condensed_trees_) == 2
-        assert isinstance(b.condensed_trees_[0], CondensedTree)
-        assert isinstance(b.linkage_trees_[0], SingleLinkageTree)
-        assert isinstance(b.approximation_graph_, ApproximationGraph)
-
-    try:
-        from hdbscan.plots import ApproximationGraph, CondensedTree, SingleLinkageTree
-
-        check_attributes()
-    except ImportError:
-        pass
+    b = SubClusterDetector(lens_values=centrality).fit(c)
+    check_detected_groups(b, n_clusters=2, n_subs=7)
+    assert len(b.linkage_trees_) == 2
+    assert len(b.condensed_trees_) == 2
+    assert isinstance(b.condensed_trees_[0], CondensedTree)
+    assert isinstance(b.linkage_trees_[0], SingleLinkageTree)
+    assert isinstance(b.approximation_graph_, ApproximationGraph)
 
 
 def test_selection_method():