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Merged
ozgesurer merged 8 commits into from
Oct 9, 2025
Merged

Develop #28

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4353418
change assert == to np.allclose
davidogara Oct 7, 2025
8713e12
multihetGP tests failing for some reason
davidogara Oct 7, 2025
953affc
revert back to previous version of multihetGP
davidogara Oct 7, 2025
d4c8924
add more numerically stable homGP conversion example
davidogara Oct 7, 2025
30b78e3
restore black formatting
davidogara Oct 7, 2025
2dfa27c
add more reps to stabilize example
davidogara Oct 7, 2025
4aa8d8f
black
davidogara Oct 7, 2025
4f0785e
Merge pull request #27 from parallelUQ/develop-check-examples
ozgesurer Oct 7, 2025
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40 changes: 23 additions & 17 deletions tests/unit_tests/test_hetGP.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,10 +30,10 @@ def test_fit():
test_model = emulator(x=X, theta=np.array([0]), f=Y, method="hetGP")
test_model.fit()

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])
assert np.allclose(test_model._info["Delta"], reference_model["Delta"])
assert np.allclose(test_model._info["Lambda"], reference_model["Lambda"])

Expand All @@ -56,10 +56,10 @@ def test_matern():
)
test_model.fit()

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])
assert np.allclose(test_model._info["Delta"], reference_model["Delta"])
assert np.allclose(test_model._info["Lambda"], reference_model["Lambda"])

Expand Down Expand Up @@ -114,10 +114,10 @@ def test_hetGP_update_kriging_believer():
test_model.fit()
test_model.update(Xnew)

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])


def test_hetGP_update():
Expand All @@ -132,16 +132,22 @@ def test_hetGP_update():
test_model.fit()
test_model.update(x=Xnew, Y=Ypred)

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])


def test_conversion_to_homGP():
# should return homoskedastic GP
X = np.linspace(0, 1, 20).reshape(-1, 1)
Y = X
rand = np.random.default_rng(2)
reps = rand.choice(len(X), size=len(X))
X = X[reps, :]
Y = np.sin(X).squeeze()
noise = 0.2 * rand.normal(size=Y.shape[0])
Y += noise
Y = Y.reshape(-1, 1)
model = emulator(x=X, theta=np.array([0]), f=Y, method="hetGP")
Xp = np.linspace(X.min(), X.max(), 100).reshape(-1, 1)
preds = model.predict(Xp)
Expand Down
32 changes: 16 additions & 16 deletions tests/unit_tests/test_homGP.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,10 +31,10 @@ def test_fit():
test_model = emulator(x=X, theta=np.array([0]), f=Y, method="homGP")
test_model.fit()

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])


def test_predict():
Expand Down Expand Up @@ -93,10 +93,10 @@ def test_matern():
)
test_model.fit()

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])


def test_homGP_update_kriging_believer():
Expand All @@ -111,10 +111,10 @@ def test_homGP_update_kriging_believer():
test_model.fit()
test_model.update(Xnew)

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])


def test_homGP_update():
Expand All @@ -129,10 +129,10 @@ def test_homGP_update():
test_model.fit()
test_model.update(x=Xnew, Y=Ypred)

assert test_model._info["ll"] == reference_model["ll"]
assert test_model._info["theta"] == reference_model["theta"]
assert test_model._info["g"] == reference_model["g"]
assert test_model._info["beta0"] == reference_model["beta0"]
assert np.allclose(test_model._info["ll"], reference_model["ll"])
assert np.allclose(test_model._info["theta"], reference_model["theta"])
assert np.allclose(test_model._info["g"], reference_model["g"])
assert np.allclose(test_model._info["beta0"], reference_model["beta0"])


if __name__ == "__main__":
Expand Down
7 changes: 4 additions & 3 deletions tests/unit_tests/test_multihetGP.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,19 +8,20 @@
from copy import deepcopy

# create some noise 2D data
np.random.seed(1)
rng = np.random.default_rng(1)
lhs = qmc.LatinHypercube(d=2, rng=rng)

X = lhs.random(n=100)
reps = rng.choice(len(X), size=100, replace=True)
reps = rng.choice(len(X), size=5000, replace=True)
X = X[reps,]
# prediction grid
Xp = lhs.random(n=100)
Y = 0 * X
Y[:, 0] = np.sin(X[:, 0])
Y[:, 1] = np.cos(X[:, 1])
# varying noise field
noise = rng.normal(size=Y.shape) * np.exp(-(X**2))
noise = rng.normal(size=Y.shape)
noise *= 2

Y += noise
Expand All @@ -41,7 +42,7 @@
}
NOISECONTROL = {"k_theta_g_bounds": (1, 100), "g_max": 1e2, "g_bounds": (1e-6, 1)}

MAXIT = 100
MAXIT = 200


def test_fit():
Expand Down