Closed fabian-paul closed 8 years ago
Please update. Perhaps you have a mix of a older PyEMMA version (2.0.3) and a newer bhmm version...
Am 04/03/16 um 12:23 schrieb fabian-paul:
|HMM <class 'pyemma.msm.estimators.maximum_likelihood_hmsm.MaximumLikelihoodHMSM'> 3 Traceback (most recent call last): File "scripts/msm_feature_coarse_grain.py", line 162, in
hmm_ck = hmm.cktest(mlags=10,conf=0.95,err_est=False,show_progress=True) File ".../miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/msm/estimators/maximum_likelihood_hmsm.py", line 317, in cktest ck.estimate(self._dtrajs_full) File "./miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/_base/estimator.py", line 342, in estimate self._model = self._estimate(X) File "./miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/msm/estimators/lagged_model_validators.py", line 137, in _estimate n_jobs=self.n_jobs) File "./miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/_base/estimator.py", line 300, in estimate_param_scan res = pool(task_iter) File "./miniconda/lib/python2.7/site-packages/joblib/parallel.py", line 653, in call self.dispatch(function, args, kwargs) File "./miniconda/lib/python2.7/site-packages/joblib/parallel.py", line 400, in dispatch job = ImmediateApply(func, args, kwargs) File "./miniconda/lib/python2.7/site-packages/joblib/parallel.py", line 138, in init self.results = func(_args, *_kwargs) File "./miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/_base/estimator.py", line 132, in _estimate_param_scan_worker model = estimator.estimate(X, **params) File "./miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/_base/estimator.py", line 342, in estimate self._model = self._estimate(X) File "./miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/msm/estimators/maximum_likelihood_hmsm.py", line 189, in _estimate assert _types.is_int(self.nstates) and self.nstates > 1 and self.nstates <= msm_init.nstates, \ File "./miniconda/lib/python2.7/site-packages/pyEMMA-2.0.3-py2.7-linux-x86_64.egg/pyemma/msm/models/msm.py", line 202, in nstates return self._nstates AttributeError: 'MaximumLikelihoodMSM' object has no attribute '_nstates' | — Reply to this email directly or view it on GitHub https://github.com/markovmodel/PyEMMA/issues/716.
Prof. Dr. Frank Noe Head of Computational Molecular Biology group Freie Universitaet Berlin
Phone: (+49) (0)30 838 75354 Web: research.franknoe.de
@fabian-paul has this been caused by an old version?
I think this might be the issue of not getting a bhmm update with the release candidate.
Am 10/03/16 um 18:23 schrieb Martin K. Scherer:
@fabian-paul https://github.com/fabian-paul has this been caused by an old version?
— Reply to this email directly or view it on GitHub https://github.com/markovmodel/PyEMMA/issues/716#issuecomment-194965482.
Prof. Dr. Frank Noe Head of Computational Molecular Biology group Freie Universitaet Berlin
Phone: (+49) (0)30 838 75354 Web: research.franknoe.de
BTW, when can we release 2.1 normally? I guess that might fix this problem.
Am 10/03/16 um 18:23 schrieb Martin K. Scherer:
@fabian-paul https://github.com/fabian-paul has this been caused by an old version?
— Reply to this email directly or view it on GitHub https://github.com/markovmodel/PyEMMA/issues/716#issuecomment-194965482.
Prof. Dr. Frank Noe Head of Computational Molecular Biology group Freie Universitaet Berlin
Phone: (+49) (0)30 838 75354 Web: research.franknoe.de
I fear it won't solve the problem:
marscher@area51:~/workspace/pyemma/doc$ conda install pyemma=2.0.3
Using Anaconda Cloud api site https://api.anaconda.org
Fetching package metadata: ........
Solving package specifications: ...........
Package plan for installation in environment /home/marscher/miniconda:
The following packages will be downloaded:
package | build
---------------------------|-----------------
numexpr-2.4.6 | np110py34_0 334 KB
scikit-learn-0.17.1 | np110py34_0 8.8 MB
pyemma-2.0.3 | py34_0 692 KB
------------------------------------------------------------
Total: 9.8 MB
The following packages will be UPDATED:
numexpr: 2.4.4-np110py34_p0 [mkl] --> 2.4.6-np110py34_0
scikit-learn: 0.17-np110py34_p1 [mkl] --> 0.17.1-np110py34_0
The following packages will be DOWNGRADED:
bhmm: 0.6.1-np110py34_0 --> 0.5.2-np110py34_0
pyemma: 2.0.4-py34_1 --> 2.0.3-py34_0
Proceed ([y]/n)? y
Fetching packages ...
numexpr-2.4.6- 100%
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Time: 0:00:00 429.82 kB/s
scikit-learn-0 100%
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Time: 0:00:11 805.95 kB/s
pyemma-2.0.3-p 100%
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Time: 0:00:01 653.47 kB/s
Extracting packages ...
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100%
Unlinking packages ...
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100%
Linking packages ...
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marscher@area51:~/workspace/pyemma/doc$ conda install pyemma=2.0.4
Using Anaconda Cloud api site https://api.anaconda.org
Fetching package metadata: ........
Solving package specifications: ...........
Package plan for installation in environment /home/marscher/miniconda:
The following packages will be UPDATED:
pyemma: 2.0.3-py34_0 --> 2.0.4-py34_1
Proceed ([y]/n)? y
Unlinking packages ...
[ COMPLETE
]|#########################################################################################################################################|
100%
Linking packages ...
[ COMPLETE
]|#########################################################################################################################################|
However I'd expect that we can close the bug fixing window at end of this week.