PyEMMA
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Published
20 hours ago •
markovmodel
markovmodel
estimating Bayesian MSM very slow
Hi,
Im trying to follow the tutorial 6 (http://emma-project.org/latest/tutorials/notebooks/06-expectations-and-observables.html#Dynamic/kinetic-experimental-observables) to calculate the Trp-flourescene auto-correlation.
When I run this code
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import mdtraj as md
import pyemma
import pyemma.coordinates as coor
import numpy as np
import matplotlib.pyplot as plt
from pyemma.util.contexts import settings
from mdtraj import shrake_rupley, compute_rg
# Define the reader for loading trajectory data
torsions_feat = pyemma.coordinates.featurizer(pdb)
torsions_feat.add_backbone_torsions(cossin=True, periodic=False)
torsions_data = pyemma.coordinates.load(xtc, features=torsions_feat)
cluster = pyemma.coordinates.cluster_kmeans(torsions_data, k=50, max_iter=50)
dtrajs_concatenated = cluster.dtrajs[0]
print(dtrajs_concatenated)
its = pyemma.msm.its(
cluster.dtrajs, lags=[1, 2, 3, 5, 7, 10], nits=3, errors='bayes')
My jupyter notebook stays a lot of time saying estimating BayesianMSM 0% with no progress.
Is there anything that I missed on my code?
pip list
Package Version
--------------------------------- -----------
anyio 3.6.2
argon2-cffi 21.3.0
argon2-cffi-bindings 21.2.0
asttokens 2.1.0
astunparse 1.6.3
attrs 22.1.0
backcall 0.2.0
backports.functools-lru-cache 1.6.4
beautifulsoup4 4.11.1
bleach 5.0.1
brotlipy 0.7.0
cached-property 1.5.2
certifi 2022.9.24
cffi 1.15.1
charset-normalizer 2.1.1
colorama 0.4.6
contourpy 1.0.6
cryptography 38.0.3
cycler 0.11.0
debugpy 1.6.3
decorator 5.1.1
deeptime 0.4.3
defusedxml 0.7.1
dill 0.3.6
entrypoints 0.4
executing 1.2.0
fastjsonschema 2.16.2
flit_core 3.8.0
fonttools 4.38.0
h5py 3.7.0
humanfriendly 10.0
idna 3.4
importlib-metadata 5.0.0
importlib-resources 5.10.0
ipykernel 6.14.0
ipython 8.4.0
ipython-genutils 0.2.0
ipywidgets 8.0.2
jedi 0.18.1
Jinja2 3.1.2
joblib 1.2.0
jsonschema 4.17.0
jupyter_client 7.4.7
jupyter-contrib-core 0.4.0
jupyter-contrib-nbextensions 0.5.1
jupyter_core 5.0.0
jupyter-highlight-selected-word 0.2.0
jupyter-latex-envs 1.4.6
jupyter-nbextensions-configurator 0.4.1
jupyter-server 1.23.2
jupyterlab-pygments 0.2.2
jupyterlab-widgets 3.0.3
kiwisolver 1.4.4
lxml 4.9.1
MarkupSafe 2.1.1
matplotlib 3.6.2
matplotlib-inline 0.1.6
mdshare 0.4.2
mdtraj 1.9.7
mistune 2.0.4
multiprocess 0.70.14
munkres 1.1.4
nbclassic 0.4.8
nbclient 0.7.0
nbconvert 7.2.5
nbexamples 0.3.1
nbformat 5.7.0
nest-asyncio 1.5.6
nglview 3.0.3
notebook 6.5.2
notebook_shim 0.2.2
numexpr 2.8.3
numpy 1.23.4
packaging 21.3
pandas 1.5.1
pandocfilters 1.5.0
parso 0.8.3
pathos 0.3.0
pexpect 4.8.0
pickleshare 0.7.5
Pillow 9.2.0
pip 22.3.1
pkgutil_resolve_name 1.3.10
platformdirs 2.5.2
pox 0.3.2
ppft 1.7.6.6
progress-reporter 2.0
prometheus-client 0.15.0
prompt-toolkit 3.0.32
psutil 5.9.4
ptyprocess 0.7.0
pure-eval 0.2.2
pycparser 2.21
pyEMMA 2.5.12
Pygments 2.13.0
pyOpenSSL 22.1.0
pyparsing 3.0.9
pyrsistent 0.19.2
PySocks 1.7.1
python-dateutil 2.8.2
pytz 2022.6
PyYAML 6.0
pyzmq 24.0.1
requests 2.28.1
scikit-learn 1.1.3
scipy 1.9.3
Send2Trash 1.8.0
setuptools 65.5.1
six 1.16.0
sniffio 1.3.0
soupsieve 2.3.2.post1
stack-data 0.6.1
tables 3.7.0
terminado 0.15.0
threadpoolctl 3.1.0
tinycss2 1.2.1
tornado 6.2
tqdm 4.64.1
traitlets 5.5.0
typing_extensions 4.4.0
unicodedata2 15.0.0
urllib3 1.26.11
wcwidth 0.2.5
webencodings 0.5.1
websocket-client 1.4.2
wheel 0.38.4
widgetsnbextension 4.0.3
zipp 3.10.0
Thanks in advance
