def test_num_obs_linkage_multi_matrix(self): # Tests num_obs_linkage with observation matrices of multiple sizes. for n in range(2, 10): X = np.random.rand(n, 4) Y = pdist(X) Z = linkage(Y) self.assertTrue(num_obs_linkage(Z) == n)
def test_num_obs_linkage_multi_matrix(self): # Tests num_obs_linkage with observation matrices of multiple sizes. for n in xrange(2, 10): X = np.random.rand(n, 4) Y = pdist(X) Z = linkage(Y) self.assertTrue(num_obs_linkage(Z) == n)
def test_leaders_single(self): # Tests leaders using a flat clustering generated by single linkage. X = hierarchy_test_data.Q_X Y = pdist(X) Z = linkage(Y) T = fcluster(Z, criterion='maxclust', t=3) Lright = (np.array([53, 55, 56]), np.array([2, 3, 1])) L = leaders(Z, T) assert_equal(L, Lright)