9023806a1dd7097c71aadf77d95020c6fe2c618c,pyemma/coordinates/clustering/tests/test_kmeans.py,TestKmeans,test_3gaussian_1d_singletraj,#TestKmeans#,61

Before Change

                                       err_msg="should yield same centers with fixed seed for strategy %s" % init_strategy, atol=1e-6)

            // check a user defined seed
            seed = random.randint(0, 2**32-1)
            seed = 42312
            km1 = cluster_kmeans(X, k=10, init_strategy=init_strategy, fixed_seed=seed, n_jobs=1)
            km2 = cluster_kmeans(X, k=10, init_strategy=init_strategy, fixed_seed=seed, n_jobs=1)
            self.assertEqual(km1.fixed_seed, km2.fixed_seed)

After Change

        X = np.hstack(X)
        k = 50
        from pyemma._base.estimator import param_grid
        grid = param_grid({"init_strategy": ["uniform", "kmeans++"], "fixed_seed": [True, 463498]})
        for param in grid:
            init_strategy = param["init_strategy"]
            fixed_seed = param["fixed_seed"]
            kmeans = cluster_kmeans(X, k=10, init_strategy=init_strategy, n_jobs=1)
            cc = kmeans.clustercenters
            self.assertTrue(np.all(np.isfinite(cc)), "cluster centers borked for strat %s" % init_strategy)
            assert (np.any(cc < 1.0)), "failed for init_strategy=%s" % init_strategy
            assert (np.any((cc > -1.0) * (cc < 1.0))), "failed for init_strategy=%s" % init_strategy
            assert (np.any(cc > -1.0)), "failed for init_strategy=%s" % init_strategy

            km1 = cluster_kmeans(X, k=k, init_strategy=init_strategy, fixed_seed=fixed_seed, n_jobs=0)  // serial
            km2 = cluster_kmeans(X, k=k, init_strategy=init_strategy, fixed_seed=fixed_seed, n_jobs=2)  // parallel
            self.assertEqual(len(km1.clustercenters), k)
            self.assertEqual(len(km2.clustercenters), k)
            self.assertEqual(km1.fixed_seed, km2.fixed_seed)

            // check initial centers (after kmeans++, uniform init) are equal.
            np.testing.assert_equal(km1.initial_centers_, km2.initial_centers_)

            while not km1.converged:
                km1.estimate(X=X, clustercenters=km1.clustercenters)
            assert km1.converged
            while not km2.converged:
                km2.estimate(X=X, clustercenters=km2.clustercenters)
            assert km2.converged

Instances