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tests: tests for GEVP fixed, docstring for Corr.Eigenvalue added, typos

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fixed
This commit is contained in:
Fabian Joswig 2022-02-22 21:33:04 +00:00
commit 39dff5a830
2 changed files with 20 additions and 3 deletions
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21
pyerrors/correlators.py
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@ -255,9 +255,9 @@ class Corr:
The state one is interested in ordered by energy. The lowest state is zero.
sorted_list : string
if this argument is set, a list of vectors (len=self.T) is returned. If it is left as None, only one vector is returned.
"Eigenvalue" - The eigenvector is chosen according to which einvenvalue it belongs individually on every timeslice.
"Eigenvalue" - The eigenvector is chosen according to which eigenvalue it belongs individually on every timeslice.
"Eigenvector" - Use the method described in arXiv:2004.10472 [hep-lat] to find the set of v(t) belonging to the state.
The referense state is identified by its eigenvalue at t=ts
The reference state is identified by its eigenvalue at t=ts
"""
if sorted_list is None:
if (ts is None):
@ -302,6 +302,23 @@ class Corr:
return all_vecs
def Eigenvalue(self, t0, ts=None, state=0, sorted_list=None):
"""Determines the eigenvalue of the GEVP by solving and projecting the correlator
Parameters
----------
t0 : int
The time t0 for G(t)v= lambda G(t_0)v
ts : int
fixed time G(t_s)v= lambda G(t_0)v if return_list=False
If return_list=True and sorting=Eigenvector it gives a reference point for the sorting method.
state : int
The state one is interested in ordered by energy. The lowest state is zero.
sorted_list : string
if this argument is set, a list of vectors (len=self.T) is returned. If it is left as None, only one vector is returned.
"Eigenvalue" - The eigenvector is chosen according to which eigenvalue it belongs individually on every timeslice.
"Eigenvector" - Use the method described in arXiv:2004.10472 [hep-lat] to find the set of v(t) belonging to the state.
The reference state is identified by its eigenvalue at t=ts
"""
vec = self.GEVP(t0, ts=ts, state=state, sorted_list=sorted_list)
return self.projected(vec)

2
tests/correlators_test.py
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@ -220,7 +220,7 @@ def test_prange():
def test_matrix_corr():
corr_aa = _gen_corr(1)
corr_ab = _gen_corr(0.5)
corr_ab = 0.5 * corr_aa
corr_mat = pe.Corr(np.array([[corr_aa, corr_ab], [corr_ab, corr_aa]]))
corr_mat.item(0, 0)