{"action":"created","comment":{"url":"https://api.github.com/repos/pele-python/pele/pulls/comments/46533938","id":46533938,"diff_hunk":"@@ -1,6 +1,6 @@\n from PyQt4 import QtGui, QtCore\n from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas\n-from matplotlib.backends.backend_qt4agg import NavigationToolbar2QTAgg as NavigationToolbar\n+from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar","path":"pele/gui/ui/mplwidget.py","position":4,"original_position":4,"commit_id":"e510ed31fa39718980c277fac307a304529acb95","original_commit_id":"e510ed31fa39718980c277fac307a304529acb95","user":{"login":"smcantab","id":3187259,"avatar_url":"https://avatars.githubusercontent.com/u/3187259?v=3","gravatar_id":"","url":"https://api.github.com/users/smcantab","html_url":"https://github.com/smcantab","followers_url":"https://api.github.com/users/smcantab/followers","following_url":"https://api.github.com/users/smcantab/following{/other_user}","gists_url":"https://api.github.com/users/smcantab/gists{/gist_id}","starred_url":"https://api.github.com/users/smcantab/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/smcantab/subscriptions","organizations_url":"https://api.github.com/users/smcantab/orgs","repos_url":"https://api.github.com/users/smcantab/repos","events_url":"https://api.github.com/users/smcantab/events{/privacy}","received_events_url":"https://api.github.com/users/smcantab/received_events","type":"User","site_admin":false},"body":"current version of matplotlib is 1.5. I have 1.3.1 on my computer, which I think is the one that comes with apt-get and I don't get an import error when running the nosetests, so I think we're good","created_at":"2015-12-03T10:17:24Z","updated_at":"2015-12-03T10:17:24Z","html_url":"https://github.com/pele-python/pele/pull/138#discussion_r46533938","pull_request_url":"https://api.github.com/repos/pele-python/pele/pulls/138","_links":{"self":{"href":"https://api.github.com/repos/pele-python/pele/pulls/comments/46533938"},"html":{"href":"https://github.com/pele-python/pele/pull/138#discussion_r46533938"},"pull_request":{"href":"https://api.github.com/repos/pele-python/pele/pulls/138"}}},"pull_request":{"url":"https://api.github.com/repos/pele-python/pele/pulls/138","id":51835065,"html_url":"https://github.com/pele-python/pele/pull/138","diff_url":"https://github.com/pele-python/pele/pull/138.diff","patch_url":"https://github.com/pele-python/pele/pull/138.patch","issue_url":"https://api.github.com/repos/pele-python/pele/issues/138","number":138,"state":"open","locked":false,"title":"Implementation of mean field p-spin glass potential","user":{"login":"smcantab","id":3187259,"avatar_url":"https://avatars.githubusercontent.com/u/3187259?v=3","gravatar_id":"","url":"https://api.github.com/users/smcantab","html_url":"https://github.com/smcantab","followers_url":"https://api.github.com/users/smcantab/followers","following_url":"https://api.github.com/users/smcantab/following{/other_user}","gists_url":"https://api.github.com/users/smcantab/gists{/gist_id}","starred_url":"https://api.github.com/users/smcantab/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/smcantab/subscriptions","organizations_url":"https://api.github.com/users/smcantab/orgs","repos_url":"https://api.github.com/users/smcantab/repos","events_url":"https://api.github.com/users/smcantab/events{/privacy}","received_events_url":"https://api.github.com/users/smcantab/received_events","type":"User","site_admin":false},"body":"This is an implementation of the mean field p-spin glass model (a spin glass model with disordered quenched couplings).\r\n\r\n- [x] c++ implementation for general p\r\n- [x] next combination utility\r\n- [ ] c++ template specialization for most common p=2 and p=3 cases\r\n- [x] c++ Hessian\r\n- [x] c++ tests\r\n- [x] python wrapper\r\n- [x] python tests\r\n- [x] make tests more robust\r\n- [ ] implement system class to run in gui\r\n\r\nAs part of this PR I have added a class that generates the next combination out of the N choose p possibilities, this should improve considerably energy evaluations although a simple nested loop might run faster, hence I am thinking of writing template specializations for p=2,3 which are the most commonly used parameters. I also need to implement the Hessian that is not so straightforward because the degrees of freedom are N-1, but this is a known problem that has been solved before. \r\n\r\nThere is a design feature of the combination_generator class, viz. the last combination returns false (this is the default behaviour for std::next_permutation as well) so I had to copy the body of the while loops outside one extra time, otherwise the sums are short of one combination of indexes. If you can think of a more elegant solution please let me know, I'm all hears. Today I couldn't think of anything better than 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