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remove duplicated test
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imblearn/over_sampling/tests/test_adasyn.py

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@@ -142,46 +142,3 @@ def test_adasyn_error(adasyn_params, err_msg):
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adasyn = ADASYN(**adasyn_params)
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with pytest.raises(ValueError, match=err_msg):
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adasyn.fit_resample(X, Y)
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def test_ada_fit_resample_cuml_nn_obj():
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cuml = pytest.importorskip("cuml")
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nn = cuml.neighbors.NearestNeighbors(n_neighbors=2)
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ada = ADASYN(random_state=RND_SEED, n_neighbors=nn)
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X_resampled, y_resampled = ada.fit_resample(X, Y)
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X_gt = np.array(
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[
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[0.11622591, -0.0317206],
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[0.77481731, 0.60935141],
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[1.25192108, -0.22367336],
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[0.53366841, -0.30312976],
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[1.52091956, -0.49283504],
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[-0.28162401, -2.10400981],
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[0.83680821, 1.72827342],
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[0.3084254, 0.33299982],
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[0.70472253, -0.73309052],
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[0.28893132, -0.38761769],
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[1.15514042, 0.0129463],
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[0.88407872, 0.35454207],
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[1.31301027, -0.92648734],
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[-1.11515198, -0.93689695],
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[-0.18410027, -0.45194484],
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[0.9281014, 0.53085498],
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[-0.14374509, 0.27370049],
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[-0.41635887, -0.38299653],
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[0.08711622, 0.93259929],
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[1.70580611, -0.11219234],
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[0.34532399, -0.18067361],
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[1.44430593, -0.41617493],
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[0.28204936, -0.13953426],
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[1.08450984, 0.03948221],
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[-0.19072677, -0.2341768],
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]
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)
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y_gt = np.array(
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[0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]
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)
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assert_allclose(X_resampled, X_gt, rtol=R_TOL)
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assert_array_equal(y_resampled, y_gt)

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