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Fix scoreutils #238

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Jun 21, 2025
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Fix scoreutils #238

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6 changes: 3 additions & 3 deletions causallearn/utils/ScoreUtils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -619,15 +619,15 @@ def cov_seard(loghyper=None, x=None, z=None, nargout=1):
sf2 = np.exp(2 * loghyper[D]) # signal variance

if loghyper is not None and x is not None:
K = sf2 * np.exp(-sq_dist(np.diag(1 / ell) * x.T) / 2)
K = sf2 * np.exp(-sq_dist(np.diag(1 / ell) @ x.T) / 2)
A = K
elif nargout == 2: # compute test set covariances
A = sf2 * np.ones((z, 1))
B = sf2 * np.exp(-sq_dist(np.diag(1 / ell) * x.T, np.diag(1 / ell) * z) / 2)
B = sf2 * np.exp(-sq_dist(np.diag(1 / ell) @ x.T, np.diag(1 / ell) @ z) / 2)
else:
# check for correct dimension of the previously calculated kernel matrix
if K.shape[0] != n or K.shape[1] != n:
K = sf2 * np.exp(-sq_dist(np.diag(1 / ell) * x.T) / 2)
K = sf2 * np.exp(-sq_dist(np.diag(1 / ell) @ x.T) / 2)

if z <= D: # length scale parameters
A = np.multiply(K, sq_dist(x[:, z].T / ell[z]))
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