[ase-users] [ase-developers] Genetic algorithm added to ase

Mon Mar 10 15:19:34 CET 2014

In principle it should be possible to change it to using the ase.db interface. All data communication happens through the module data.py, so the change is fairly isolated. I will try looking into it.

/Lasse

On 10/03/2014, at 14.20, Jens Jørgen Mortensen <jensj at fysik.dtu.dk<mailto:jensj at fysik.dtu.dk>> wrote:

Den 27-02-2014 15:38, Lasse Vilhelmsen skrev:
Hi Marcin,

Thank you for adding the branch to the test build system. I have added a number of tests to the folder you suggested which verifies that essential parts of the GA work as intended. I have just committed the tests to the svn and the buildbot has given them the all clear :)

Concerning your comment about how to refer to py scripts in the documentation and the location for these I am a bit confused. If I look through the other tutorials in doc/tutorials most of them reference py scripts located in doc/tutorials using the .. literalinclude:: syntax. I therefore take it that is the correct way to include py samples in the tutorials?

The tutorial scripts I have created serve as full examples of the GA and they therefore take quite some time to execute and they should therefore not be considered tests.

I see that the new GA stuff uses an SQLite database.  Could the new ase.db module be used instead?

    https://wiki.fysik.dtu.dk/ase/ase/db/db.html

Jens Jørgen

Best Regards
Lasse

On 27/02/2014, at 11.40, Marcin Dulak <Marcin.Dulak at fysik.dtu.dk<mailto:Marcin.Dulak at fysik.dtu.dk>> wrote:

Hi,

On 02/27/2014 11:22 AM, Lasse Vilhelmsen wrote:
Hi Michael,

It was Jens Jørgens suggestion to first put it in a separate branch to let people test it out before moving it into the trunk version.

I have already updated the optimize.rst file in the ga branch with a short description of the method and a reference to the tutorial.

I am unsure when it is an appropriate step to move the code from the branch to the trunk, but I assume that a few need to test it out first to ensure the high quality of the code in the trunk.
your branch is now added to automatic testing at https://ase-buildbot.fysik.dtu.dk/waterfall
Please do not add python scripts to documentation - they should be part of the running tests,
and only referred to in the rst file using :svn:. See https://wiki.fysik.dtu.dk/ase/ase/calculators/abinit.html for an example.
Consider also creating a special ase/test/ga subdirectory.
The tests must be fast - few seconds max.

Best regards,

Marcin

Best Regards
Lasse

On 27/02/2014, at 10.59, Michael Walter <Michael.Walter at fmf.uni-freiburg.de<mailto:Michael.Walter at fmf.uni-freiburg.de>> wrote:

Dear Lasse,

great that there is a genetic algorith in ase now !

I suggest to put the algorithm to trunk and add the explanation (or the link) to the list of global optimization agorithms:
https://wiki.fysik.dtu.dk/ase/ase/optimize.html#global-optimization

Best,
Michael

2014-02-27 9:50 GMT+01:00 Lasse Vilhelmsen <lassebv at phys.au.dk<mailto:lassebv at phys.au.dk>>:
Dear ase-users and ase-developers,

I have in the past couple of years developed and used a genetic algorithm for global structure optimization within ase. The method has been used for the optimization of metal clusters and oxide structures both on supported surfaces, in metal organic frameworks and in vacuum. The method implements the cut-and-splice pairing operator by Deaven and Ho, a set of different mutations, a way to verify if two structures are equal, a starting population generator and a population that can propose structures to pair. The method works with all calculators in ase and it has especially been developed for parallel execution of multiple local relaxations simultaneously using first principles calculations.

The code is currently located in the svn branch ga of ase. The entire genetic algorithm code is located in ase/optimiize/genetic_algorithm with a tutorial describing the method in the documentations section.

My hope is that some of you might have an interest in trying the method and giving some feedback on what aspects of the implementation you find intuitive and easy to use, and which parts of the method you find counter intuitive and weird. The reporting any sorts of bugs are of course also very much appreciated!

I have compiled the current version of the tutorial and published it on the following link for easy reference. This tutorial is the optimal way to start using the method, since it includes full test examples:
http://users-phys.au.dk/lassebv/ga_optimize.html

The ga branch of ase can easily be obtained using the following command
svn co https://svn.fysik.dtu.dk/projects/ase/branches/ga

I look forward to any feedback you might have!

Best Regards
Lasse

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