[MAINT] Update Ubuntu runner versions (#54)

braindatalab · Feb 13, 2025 · 6558292 · 6558292
1 parent 0779b03
commit 6558292
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Showing 2 changed files with 7 additions and 7 deletions.
diff --git a/.github/workflows/unit_tests.yml b/.github/workflows/unit_tests.yml
@@ -63,7 +63,7 @@ jobs:
 
   test_conda:
     timeout-minutes: 90
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-latest
     defaults:
       run:
         shell: bash -el {0}

diff --git a/tests/test_results.py b/tests/test_results.py
@@ -128,10 +128,10 @@ def test_results_cfc_runs() -> None:
         data=data[subset], indices=indices_subset, f1s=f1s, f2s=f2s, name=name
     )
     results_array, array_indices = results.get_results(form="compact")
-    assert np.max(array_indices) == np.unique(indices_subset).max()
+    assert np.max(array_indices) == len(np.unique(indices_subset)) - 1
     # Check that the results array is NaN for missing nodes
     array_subset_mask = np.zeros(results_array.shape[:2], dtype=bool)
-    array_subset_mask[indices_subset[0], indices_subset[1]] = True
+    array_subset_mask[array_indices[0], array_indices[1]] = True
     assert not np.isnan(results_array[array_subset_mask]).all()
     assert np.isnan(results_array[~array_subset_mask]).all()
 
@@ -311,10 +311,10 @@ def test_results_tde_runs(freq_bands: tuple) -> None:
 
     results_array, array_indices = results.get_results(form="compact")
 
-    assert np.max(array_indices) == np.unique(indices_subset).max()
+    assert np.max(array_indices) == len(np.unique(indices_subset)) - 1
     # Check that the results array is NaN for missing nodes
     array_subset_mask = np.zeros(results_array.shape[:2], dtype=bool)
-    array_subset_mask[indices_subset[0], indices_subset[1]] = True
+    array_subset_mask[array_indices[0], array_indices[1]] = True
     assert not np.isnan(results_array[array_subset_mask]).all()
     assert np.isnan(results_array[~array_subset_mask]).all()
 
@@ -533,9 +533,9 @@ def test_results_general_runs() -> None:
         data=data[subset], indices=indices_subset, f1s=f1s, f2s=f2s, name=name
     )
     results_array, array_indices = results.get_results(form="compact")
-    assert np.max(array_indices) == np.unique(indices_subset).max()
+    assert np.max(array_indices) == len(np.unique(indices_subset)) - 1
     # Check that the results array is NaN for missing nodes
     array_subset_mask = np.zeros(results_array.shape[:3], dtype=bool)
-    array_subset_mask[indices_subset[0], indices_subset[1], indices_subset[2]] = True
+    array_subset_mask[array_indices[0], array_indices[1], array_indices[2]] = True
     assert not np.isnan(results_array[array_subset_mask]).all()
     assert np.isnan(results_array[~array_subset_mask]).all()