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Fixed MVN norm factor. #58

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Merged
AlexanderFabisch merged 5 commits into from
Aug 13, 2025
Merged

Fixed MVN norm factor. #58

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b6e88e8
Fixed MVN norm factor.
ARoefer Aug 12, 2025
badc1ca
Added new MVN density test with 3D data.
ARoefer Aug 13, 2025
c18c5e5
Fixed norm calculation. Test revealed it to be faulty.
ARoefer Aug 13, 2025
9d68323
Fixed norm factor after test found it to be faulty.
ARoefer Aug 13, 2025
a83f39e
Removed unnecessary "1 /" in MVN norm
ARoefer Aug 13, 2025
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2 changes: 1 addition & 1 deletion gmr/mvn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -185,7 +185,7 @@ def to_norm_factor_and_exponents(self, X):
if self.norm is None:
# Suppress a determinant of 0 to avoid numerical problems
L_det = max(sp.linalg.det(L), np.finfo(L.dtype).eps)
self.norm = 0.5 / np.pi ** (0.5 * n_features) / L_det
self.norm = (2 * np.pi) ** (-n_features/2) / L_det

# Solve L x = (X - mean)^T for x with triangular L
# (LL^T = Sigma), that is, x = L^T^-1 (X - mean)^T.
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10 changes: 7 additions & 3 deletions gmr/tests/test_mvn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,6 @@
mean = np.array([0.0, 1.0])
covariance = np.array([[0.5, -1.0], [-1.0, 5.0]])


class AxisStub:
def __init__(self):
self.count = 0
Expand Down Expand Up @@ -75,13 +74,18 @@ def test_sample_confidence_region():

def test_probability_density():
"""Test PDF of MVN."""
mean = np.array([0.0, 1.0, 2.0])
covariance = np.array([[ 0.5, -1.0, 0.0],
[-1.0, 5.0, -0.5],
[ 0.0, -0.5, 1.0]])

random_state = check_random_state(0)
mvn = MVN(mean, covariance, random_state=random_state)

x = np.linspace(-100, 100, 201)
X = np.vstack(list(map(np.ravel, np.meshgrid(x, x)))).T
X = np.vstack(list(map(np.ravel, np.meshgrid(x, x, x)))).T
p = mvn.to_probability_density(X)
approx_int = np.sum(p) * ((x[-1] - x[0]) / 201) ** 2
approx_int = np.sum(p)
assert np.abs(1.0 - approx_int) < 0.01


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