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File /opt/anaconda3/envs/ent15y/lib/python3.9/site-packages/libstempo/toasim.py:159, in make_ideal(psr)
156 """Adjust the TOAs so that the residuals to zero, then refit."""
158 psr.stoas[:] -= psr.residuals() / 86400.0
--> 159 psr.fit()
File libstempo/libstempo.pyx:2087, in libstempo.libstempo.tempopulsar.fit()
File libstempo/libstempo.pyx:2054, in libstempo.libstempo.tempopulsar._fit()
File /opt/anaconda3/envs/ent15y/lib/python3.9/site-packages/scipy/linalg/_decomp_cholesky.py:154, in cho_factor(a, lower, overwrite_a, check_finite)
94 def cho_factor(a, lower=False, overwrite_a=False, check_finite=True):
95 """
96 Compute the Cholesky decomposition of a matrix, to use in cho_solve
97
(...)
152
153 """
--> 154 c, lower = _cholesky(a, lower=lower, overwrite_a=overwrite_a, clean=False,
155 check_finite=check_finite)
156 return c, lower
File /opt/anaconda3/envs/ent15y/lib/python3.9/site-packages/scipy/linalg/_decomp_cholesky.py:37, in _cholesky(a, lower, overwrite_a, clean, check_finite)
35 c, info = potrf(a1, lower=lower, overwrite_a=overwrite_a, clean=clean)
36 if info > 0:
---> 37 raise LinAlgError("%d-th leading minor of the array is not positive "
38 "definite" % info)
39 if info < 0:
40 raise ValueError('LAPACK reported an illegal value in {}-th argument'
41 'on entry to "POTRF".'.format(-info))
LinAlgError: 19-th leading minor of the array is not positive definite`
I am trying to produce a synthetic data set which matches as close as possible the NG15yr data-- if this is my goal, is it necessary to re fit?
Any help on resolving this would be much appreciated.
The text was updated successfully, but these errors were encountered:
I have been trying to load J1713+0747 from the 15 year data and when I try to run 'LT.make_ideal(psr)' it fails and gives me the following errors:
Warning: one or more of the design-matrix columns is null. Disabling renormalization (if active), but fit may fail.
and then fails with the following output
`---------------------------------------------------------------------------
LinAlgError Traceback (most recent call last)
Cell In[5], line 1
----> 1 LT.make_ideal(psr)
File /opt/anaconda3/envs/ent15y/lib/python3.9/site-packages/libstempo/toasim.py:159, in make_ideal(psr)
156 """Adjust the TOAs so that the residuals to zero, then refit."""
158 psr.stoas[:] -= psr.residuals() / 86400.0
--> 159 psr.fit()
File libstempo/libstempo.pyx:2087, in libstempo.libstempo.tempopulsar.fit()
File libstempo/libstempo.pyx:2054, in libstempo.libstempo.tempopulsar._fit()
File /opt/anaconda3/envs/ent15y/lib/python3.9/site-packages/scipy/linalg/_decomp_cholesky.py:154, in cho_factor(a, lower, overwrite_a, check_finite)
94 def cho_factor(a, lower=False, overwrite_a=False, check_finite=True):
95 """
96 Compute the Cholesky decomposition of a matrix, to use in cho_solve
97
(...)
152
153 """
--> 154 c, lower = _cholesky(a, lower=lower, overwrite_a=overwrite_a, clean=False,
155 check_finite=check_finite)
156 return c, lower
File /opt/anaconda3/envs/ent15y/lib/python3.9/site-packages/scipy/linalg/_decomp_cholesky.py:37, in _cholesky(a, lower, overwrite_a, clean, check_finite)
35 c, info = potrf(a1, lower=lower, overwrite_a=overwrite_a, clean=clean)
36 if info > 0:
---> 37 raise LinAlgError("%d-th leading minor of the array is not positive "
38 "definite" % info)
39 if info < 0:
40 raise ValueError('LAPACK reported an illegal value in {}-th argument'
41 'on entry to "POTRF".'.format(-info))
LinAlgError: 19-th leading minor of the array is not positive definite`
I am trying to produce a synthetic data set which matches as close as possible the NG15yr data-- if this is my goal, is it necessary to re fit?
Any help on resolving this would be much appreciated.
The text was updated successfully, but these errors were encountered: