LinAlgError: SVD did not converge in Linear Least Squares
FarnoodF opened this issue · 1 comments
FarnoodF commented
I get the following error the first time I run the ASR instance definition:
---------------------------------------------------------------------------
LinAlgError Traceback (most recent call last)
<ipython-input-17-f449c895e6b2> in <module>
----> 1 asrC = asr.ASR(sfreq=125)
c:\~\python\python38\lib\site-packages\meegkit\asr.py in __init__(self, sfreq, cutoff, blocksize, win_len, win_overlap, max_dropout_fraction, min_clean_fraction, name, method, **kwargs)
124 80.0, (sfreq / 2.0) - 1.0), sfreq / 2.0]) * 2.0 / sfreq
125 M = np.array([3, 0.75, 0.33, 0.33, 1, 1, 3, 3])
--> 126 B, A = yulewalk(8, F, M)
127 self.ab_ = (A, B)
128 self.cov_ = []
c:\~\python\python38\lib\site-packages\meegkit\utils\asr.py in yulewalk(order, F, M)
260 (1 / 2, np.ones((1, int(n2 - 1))), np.zeros((1, int(n - n2)))),
261 axis=None)
--> 262 A = polystab(denf(R, order)) # compute denominator
263
264 # compute additive decomposition
c:\~\python\python38\lib\site-packages\meegkit\utils\asr.py in denf(R, na)
521 Rhs = - R[na + 1:nr]
522 A = np.concatenate(
--> 523 (1, linalg.lstsq(Rm, Rhs.T, rcond=None)[0].T), axis=None)
524 return A
<__array_function__ internals> in lstsq(*args, **kwargs)
c:\~\python\python38\lib\site-packages\numpy\linalg\linalg.py in lstsq(a, b, rcond)
2257 # lapack can't handle n_rhs = 0 - so allocate the array one larger in that axis
2258 b = zeros(b.shape[:-2] + (m, n_rhs + 1), dtype=b.dtype)
-> 2259 x, resids, rank, s = gufunc(a, b, rcond, signature=signature, extobj=extobj)
2260 if m == 0:
2261 x[...] = 0
c:\~\python\python38\lib\site-packages\numpy\linalg\linalg.py in _raise_linalgerror_lstsq(err, flag)
107
108 def _raise_linalgerror_lstsq(err, flag):
--> 109 raise LinAlgError("SVD did not converge in Linear Least Squares")
110
111 def get_linalg_error_extobj(callback):
LinAlgError: SVD did not converge in Linear Least Squares
To reproduce the error, please run:
from meegkit import asr
asrC = asr.ASR(sfreq=125)
And my numpy
version is 1.18.5
, running python==3.8.6
.