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feat: construction of G0 in GEVP simplified and explicit check for

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positive-semidefiniteness added.
This commit is contained in:
Fabian Joswig 2022-11-30 16:42:30 +00:00
parent d7649834d5
commit 7eebba8387
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1 changed files with 3 additions and 2 deletions
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pyerrors/correlators.py
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@ -306,12 +306,14 @@ class Corr:
else:
symmetric_corr = self.matrix_symmetric()
G0 = np.vectorize(lambda x: x.value)(symmetric_corr[t0])
np.linalg.cholesky(G0) # Check if matrix G0 is positive-semidefinite.
if sort is None:
if (ts is None):
raise Exception("ts is required if sort=None.")
if (self.content[t0] is None) or (self.content[ts] is None):
raise Exception("Corr not defined at t0/ts.")
G0 = np.vectorize(lambda x: x.value)(symmetric_corr[t0])
Gt = np.vectorize(lambda x: x.value)(symmetric_corr[ts])
reordered_vecs = _GEVP_solver(Gt, G0)
@ -319,7 +321,6 @@ class Corr:
if sort == "Eigenvalue" and ts is not None:
warnings.warn("ts has no effect when sorting by eigenvalue is chosen.", RuntimeWarning)
all_vecs = [None] * (t0 + 1)
G0 = np.vectorize(lambda x: x.value)(symmetric_corr[t0])
for t in range(t0 + 1, self.T):
try:
Gt = np.vectorize(lambda x: x.value)(symmetric_corr[t])