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refactor: correlators._solve_GEVP simplified and optimized, test added.
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2 changed files with 18 additions and 5 deletions
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@ -1219,8 +1219,6 @@ def _sort_vectors(vec_set, ts):
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return sorted_vec_set
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def _GEVP_solver(Gt, G0): # Just so normalization an sorting does not need to be repeated. Here we could later put in some checks
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sp_val, sp_vecs = scipy.linalg.eigh(Gt, G0)
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sp_vecs = [sp_vecs[:, np.argsort(sp_val)[-i]] for i in range(1, sp_vecs.shape[0] + 1)]
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sp_vecs = [v / np.sqrt((v.T @ G0 @ v)) for v in sp_vecs]
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return sp_vecs
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def _GEVP_solver(Gt, G0):
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"""Helper function for solving the GEVP and sorting the eigenvectors."""
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return scipy.linalg.eigh(Gt, G0)[1].T[::-1]
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@ -1,5 +1,6 @@
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import os
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import numpy as np
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import scipy
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import pyerrors as pe
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import pytest
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@ -290,6 +291,20 @@ def test_matrix_symmetric():
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assert np.all([np.all(o == o.T) for o in sym_corr_mat])
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def test_GEVP_solver():
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mat1 = np.random.rand(15, 15)
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mat2 = np.random.rand(15, 15)
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mat1 = mat1 @ mat1.T
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mat2 = mat2 @ mat2.T
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sp_val, sp_vecs = scipy.linalg.eigh(mat1, mat2)
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sp_vecs = [sp_vecs[:, np.argsort(sp_val)[-i]] for i in range(1, sp_vecs.shape[0] + 1)]
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sp_vecs = [v / np.sqrt((v.T @ mat2 @ v)) for v in sp_vecs]
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assert np.allclose(sp_vecs, pe.correlators._GEVP_solver(mat1, mat2), atol=1e-14)
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def test_hankel():
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corr_content = []
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for t in range(8):
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