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View Code? Open in Web Editor NEWAutomatic detection of equilibrated regions of molecular simulations
Home Page: http://dx.doi.org/10.1101/021659
Automatic detection of equilibrated regions of molecular simulations
Home Page: http://dx.doi.org/10.1101/021659
Would be useful to add an initial convex sum implementation, since I believe this is the optimal approach for our kinds of problems.
http://www.stat.umn.edu/geyer/mcmc/library/mcmc/html/initseq.html
Wei Yang helpfully points out that Fig 2 of his RCA paper computes the statistical inefficiency over different terminal segments. We should incorporate an expanded discussion of this work and its influence on the ideas in the paper.
The required packages are no longer available on omnia.
Creating` new conda environment 'argon' containing versions of tools needed for reproducibility...
Collecting package metadata (repodata.json): ...working... done
Solving environment: ...working... failed
ResolvePackageNotFound:
- python==2.7.10=1
- libgfortran==1.0=0
- freetype==2.5.5=0
- setuptools==19.1.1=py27_0
- qt==4.8.7=1
- openblas==0.2.14=3
- netcdf4==1.2.1=np110py27_0
- numpy==1.10.2=py27_0
- wheel==0.26.0=py27_1
- libpng==1.6.17=0
- hdf5==1.8.15.1=2
- krb5==1.13.2=0
- matplotlib==1.5.0=np110py27_0
- sip==4.16.9=py27_0
- tk==8.5.18=0
- readline==6.2=2
- scipy==0.16.1=np110py27_0
- libnetcdf==4.3.3.1=1
- sqlite==3.8.4.1=1
- pip==7.1.2=py27_0
- seaborn==0.6.0=np110py27_0
- pyparsing==2.0.3=py27_0
- pytz==2015.7=py27_0
- python-dateutil==2.4.2=py27_0
- curl==7.43.0=1
- openssl==1.0.1k=1
Could not find conda environment: argon
You can list all discoverable environments with `conda info --envs`.
Running simulations...
File "simulate.py", line 41
print "characteristic timescale = %.3f ps" % (characteristic_timescale / unit.picoseconds)
^
SyntaxError: invalid syntax
Generating figures...
File "analyze-1.py", line 33
print "Creating figures directory..."
^
SyntaxError: Missing parentheses in call to 'print'. Did you mean print("Creating figures directory...")?
File "analyze-2.py", line 36
print "Creating figures directory..."
^
SyntaxError: Missing parentheses in call to 'print'. Did you mean print("Creating figures directory...")?
File "analyze-3.py", line 33
print "Creating figures directory..."
^
SyntaxError: Missing parentheses in call to 'print'. Did you mean print("Creating figures directory...")?
File "analyze-4.py", line 36
print "Creating figures directory..."
^
SyntaxError: Missing parentheses in call to 'print'. Did you mean print("Creating figures directory...")?
DeprecationWarning: 'source deactivate' is deprecated. Use 'conda deactivate'.
Finished.
You can now safely remove the conda environment with:
conda env remove -n argon
I cloned the repo and, after installing Miniconda, tried running reproduce.sh. This complains about seaborn
lambda 508 $ ./reproduce.sh
discarding /Users/fowler/miniconda/bin from PATH
prepending /Users/fowler/tmp/automatic-equilibration-detection/examples/liquid-argon-density/conda-env/bin to PATH
characteristic timescale = 0.285 ps
timestep = 0.002846993438 ps
Minimizing positions...
Writing initial positions to initial.pdb
Traceback (most recent call last):
File "simulate.py", line 72, in <module>
ncfile = utils.create_netcdf_datastore(netcdf_filename, testsystem.system, initial_positions, nreplicates, niterations, observation_interval)
File "/Users/fowler/tmp/automatic-equilibration-detection/examples/liquid-argon-density/utils.py", line 86, in create_netcdf_datastore
raise Exception("Datafile '%s' already exists." % filename)
Exception: Datafile 'data.nc' already exists.
Traceback (most recent call last):
File "analyze-1.py", line 19, in <module>
import seaborn as sns
ImportError: No module named seaborn
Traceback (most recent call last):
File "analyze-2.py", line 19, in <module>
import seaborn as sns
ImportError: No module named seaborn
So I tried installing it using MacPorts (this is all on a Mac running Yosemite).
port install py27-seaborn
And this didn't work either (although the conda env prob won't see the MacPort installed module).
It may be useful to include results for more complex systems, such as a TIP3P water box and a peptide.
If we can guarantee N_eff(t0)
to be unimodal, a bisection search like @kyleabeauchamp has experimented with could likely be guaranteed to be optimal.
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