def status(self):
        docs = {'updated'  : [],
                'committed': [],
                'to_commit': []}

        row = self.db.internal.find_one({'_id': 'last_sync'})

        if row and 'update' in row:
            for id in row['update']:
                docs['updated'].append(self.get(id, deleted=True))

        if row and 'commit' in row:
            for id in row['commit']:
                docs['committed'].append(self.get(id, deleted=True))

        to_commit =  self.get_docs_to_commit()
        for row in to_commit:
            doc = Document(**row)
            docs['to_commit'].append(doc)
        return docs
def compute_svm_subjects(K, y, n_folds=5):
    """
    """
    cv = KFold(len(K)/2, n_folds)
    scores = np.zeros(n_folds)
    for i, (train, test) in enumerate(cv):
        train_ids = np.concatenate((train, len(K)/2+train))
        test_ids = np.concatenate((test, len(K)/2+test))
        clf = SVC(kernel='precomputed')
        clf.fit(K[train_ids, :][:, train_ids], y[train_ids])
        scores[i] = clf.score(K[test_ids, :][:, train_ids], y[test_ids])

    return scores.mean()