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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,6 @@ | ||
| # | ||
| # author: Jungtaek Kim ([email protected]) | ||
| # last updated: July 8, 2024 | ||
| # last updated: July 9, 2024 | ||
| # | ||
| """test_covariance""" | ||
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@@ -12,9 +12,6 @@ | |
| from bayeso.utils import utils_covariance | ||
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| TEST_EPSILON = 1e-7 | ||
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| def test_choose_fun_cov_typing(): | ||
| annos = package_target.choose_fun_cov.__annotations__ | ||
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@@ -258,7 +255,7 @@ def test_cov_se(): | |
| cov_ = package_target.cov_se(X, Xp, cur_hyps["lengthscales"], cur_hyps["signal"]) | ||
| print(cov_) | ||
| truth_cov_ = 0.22313016014842987 | ||
| np.testing.assert_allclose(cov_[0], truth_cov_) | ||
| np.testing.assert_allclose(cov_[0, 0], truth_cov_) | ||
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| X = np.array([[1.0, 2.0, 0.0]]) | ||
| Xp = np.array([[2.0, 1.0, 1.0], [0.0, 0.0, 0.0]]) | ||
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@@ -363,7 +360,7 @@ def test_cov_matern32(): | |
| ) | ||
| print(cov_) | ||
| truth_cov_ = 0.19914827347145583 | ||
| np.testing.assert_allclose(cov_[0], truth_cov_) | ||
| np.testing.assert_allclose(cov_[0, 0], truth_cov_) | ||
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| X = np.array([[1.0, 2.0, 0.0]]) | ||
| Xp = np.array([[2.0, 1.0, 1.0], [0.0, 0.0, 0.0]]) | ||
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@@ -481,13 +478,7 @@ def test_cov_matern52(): | |
| package_target.cov_matern52( | ||
| np.zeros((1, 2)), np.zeros((1, 2)), np.array([1.0, 1.0]), 1 | ||
| ) | ||
| assert ( | ||
| np.abs( | ||
| package_target.cov_matern52(np.zeros((1, 2)), np.zeros((1, 2)), 1.0, 0.1)[0] | ||
| - 0.01 | ||
| ) | ||
| < TEST_EPSILON | ||
| ) | ||
| np.testing.assert_allclose(package_target.cov_matern52(np.zeros((1, 2)), np.zeros((1, 2)), 1.0, 0.1)[0, 0], 0.01) | ||
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| X = np.array([[1.0, 2.0, 0.0]]) | ||
| Xp = np.array([[2.0, 1.0, 1.0]]) | ||
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@@ -497,7 +488,7 @@ def test_cov_matern52(): | |
| ) | ||
| print(cov_) | ||
| truth_cov_ = 0.20532087608359792 | ||
| assert np.abs(cov_[0] - truth_cov_) < TEST_EPSILON | ||
| np.testing.assert_allclose(cov_[0, 0], truth_cov_) | ||
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| X = np.array([[1.0, 2.0, 0.0]]) | ||
| Xp = np.array([[2.0, 1.0, 1.0], [0.0, 0.0, 0.0]]) | ||
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@@ -508,7 +499,7 @@ def test_cov_matern52(): | |
| ) | ||
| print(cov_) | ||
| truth_cov_ = np.array([[0.20532088, 0.09657724]]) | ||
| assert np.all(np.abs(cov_[0] - truth_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(cov_, truth_cov_) | ||
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| def test_grad_cov_matern52_typing(): | ||
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@@ -568,8 +559,7 @@ def test_grad_cov_matern52(): | |
| [[0.0, 1.04798822, 0.57644039, 0.0], [0.02, 2.00002, 0.0, 0.0]], | ||
| ] | ||
| ) | ||
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| assert np.all(np.abs(truth_grad_cov_ - grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| num_hyps = X_train.shape[1] + 1 | ||
| grad_cov_ = package_target.grad_cov_matern52( | ||
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@@ -586,8 +576,7 @@ def test_grad_cov_matern52(): | |
| [[1.04798822, 0.57644039, 0.0], [2.00002, 0.0, 0.0]], | ||
| ] | ||
| ) | ||
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| assert np.all(np.abs(truth_grad_cov_ - grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| def test_cov_set_typing(): | ||
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@@ -653,19 +642,7 @@ def test_cov_set(): | |
| np.array([1.0, 1.0, 1.0]), | ||
| 1, | ||
| ) | ||
| assert ( | ||
| np.abs( | ||
| package_target.cov_set( | ||
| str_cov, | ||
| np.zeros((num_instances, num_dim)), | ||
| np.zeros((num_instances, num_dim)), | ||
| 1.0, | ||
| 0.1, | ||
| ) | ||
| - 0.01 | ||
| ) | ||
| < TEST_EPSILON | ||
| ) | ||
| np.testing.assert_allclose(package_target.cov_set(str_cov, np.zeros((num_instances, num_dim)), np.zeros((num_instances, num_dim)), 1.0, 0.1), 0.01) | ||
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| bx = np.array([[1.0, 2.0, 0.0], [2.0, 1.0, 0.0]]) | ||
| bxp = np.array([[2.0, 1.0, 1.0], [2.0, 2.0, 2.0]]) | ||
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@@ -675,7 +652,7 @@ def test_cov_set(): | |
| ) | ||
| print(cov_) | ||
| truth_cov_ = 0.23061736638896702 | ||
| assert np.abs(cov_ - truth_cov_) < TEST_EPSILON | ||
| np.testing.assert_allclose(cov_, truth_cov_) | ||
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| def test_cov_main_typing(): | ||
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@@ -891,15 +868,15 @@ def test_grad_cov_main(): | |
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| print(grad_cov_) | ||
| truth_grad_cov_ = np.array([[[2.00002, 0.0, 0.0]]]) | ||
| assert np.all(np.abs(grad_cov_ - truth_grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| grad_cov_ = package_target.grad_cov_main( | ||
| "se", np.ones((1, 2)), np.ones((1, 2)), cur_hyps, False | ||
| ) | ||
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| print(grad_cov_) | ||
| truth_grad_cov_ = np.array([[[0.02, 2.00002, 0.0, 0.0]]]) | ||
| assert np.all(np.abs(grad_cov_ - truth_grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| cur_hyps["lengthscales"] = 1.0 | ||
| grad_cov_ = package_target.grad_cov_main( | ||
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@@ -908,23 +885,23 @@ def test_grad_cov_main(): | |
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| print(grad_cov_) | ||
| truth_grad_cov_ = np.array([[[0.02, 0.73577888, 0.73577888]]]) | ||
| assert np.all(np.abs(grad_cov_ - truth_grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| grad_cov_ = package_target.grad_cov_main( | ||
| "matern32", np.ones((1, 2)), np.zeros((1, 2)), cur_hyps, False | ||
| ) | ||
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| print(grad_cov_) | ||
| truth_grad_cov_ = np.array([[[0.02, 0.59566154, 0.51802578]]]) | ||
| assert np.all(np.abs(grad_cov_ - truth_grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| grad_cov_ = package_target.grad_cov_main( | ||
| "matern32", np.ones((1, 2)), np.zeros((1, 2)), cur_hyps, True | ||
| ) | ||
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| print(grad_cov_) | ||
| truth_grad_cov_ = np.array([[[0.59566154, 0.51802578]]]) | ||
| assert np.all(np.abs(grad_cov_ - truth_grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| grad_cov_ = package_target.grad_cov_main( | ||
| "matern52", np.ones((1, 2)), np.zeros((1, 2)), cur_hyps, False | ||
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@@ -935,4 +912,4 @@ def test_grad_cov_main(): | |
| print(np.squeeze(grad_cov_)[1]) | ||
| print(np.squeeze(grad_cov_)[2]) | ||
| truth_grad_cov_ = np.array([[[0.02, 0.6345867279080876, 0.5872865507000906]]]) | ||
| assert np.all(np.abs(grad_cov_ - truth_grad_cov_) < TEST_EPSILON) | ||
| np.testing.assert_allclose(grad_cov_, truth_grad_cov_) | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,6 @@ | ||
| # | ||
| # author: Jungtaek Kim ([email protected]) | ||
| # last updated: October 13, 2021 | ||
| # author: Jungtaek Kim ([email protected]) | ||
| # last updated: July 9, 2024 | ||
| # | ||
| """test_trees""" | ||
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