Weaken thresholds to deal with lower number of epochs in tests.

lmcinnes · Nov 24, 2020 · 4fd1a08 · 4fd1a08
1 parent 23b2e52
commit 4fd1a08
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Showing 2 changed files with 7 additions and 7 deletions.
diff --git a/umap/tests/test_aligned_umap.py b/umap/tests/test_aligned_umap.py
@@ -39,4 +39,4 @@ def test_local_clustering(aligned_iris, aligned_iris_model):
     embd = aligned_iris_model.embeddings_[3]
     clusters = KMeans(n_clusters=2).fit_predict(embd)
     ari = adjusted_rand_score(target[3], clusters)
-    assert_greater_equal(ari, 0.5)
+    assert_greater_equal(ari, 0.40)
diff --git a/umap/tests/test_composite_models.py b/umap/tests/test_composite_models.py
@@ -28,14 +28,14 @@ def test_composite_trustworthiness(nn_data):
     trust = trustworthiness(data, model3.embedding_, 10)
     assert_greater_equal(
         trust,
-        0.85,
+        0.82,
         "Insufficiently trustworthy embedding for" "nn dataset: {}".format(trust),
     )
     model4 = model1 + model2
     trust = trustworthiness(data, model4.embedding_, 10)
     assert_greater_equal(
         trust,
-        0.85,
+        0.82,
         "Insufficiently trustworthy embedding for" "nn dataset: {}".format(trust),
     )
 
@@ -52,14 +52,14 @@ def test_composite_trustworthiness_random_init(nn_data):
     trust = trustworthiness(data, model3.embedding_, 10)
     assert_greater_equal(
         trust,
-        0.85,
+        0.82,
         "Insufficiently trustworthy embedding for" "nn dataset: {}".format(trust),
     )
     model4 = model1 + model2
     trust = trustworthiness(data, model4.embedding_, 10)
     assert_greater_equal(
         trust,
-        0.85,
+        0.82,
         "Insufficiently trustworthy embedding for" "nn dataset: {}".format(trust),
     )
 
@@ -76,13 +76,13 @@ def test_composite_trustworthiness_on_iris(iris):
     trust = trustworthiness(iris.data, embedding, 10)
     assert_greater_equal(
         trust,
-        0.85,
+        0.82,
         "Insufficiently trustworthy embedding for" "iris dataset: {}".format(trust),
     )
     embedding = (iris_model1 * iris_model2).embedding_
     trust = trustworthiness(iris.data, embedding, 10)
     assert_greater_equal(
         trust,
-        0.85,
+        0.82,
         "Insufficiently trustworthy embedding for" "iris dataset: {}".format(trust),
     )