def test_query_radius_count(self): # center the data X = 2 * self.X - 1 dm = DistanceMetric() D = dm.pdist(X, squareform=True) r = np.mean(D) bt = BallTree(X) count1 = bt.query_radius(X, r, count_only=True) count2 = (D <= r).sum(1) assert_array_almost_equal(count1, count2)
def test_query_radius_count(self): # center the data X = 2 * self.X - 1 dm = DistanceMetric() D = dm.pdist(X, squareform=True) r = np.mean(D) bt = BallTree(X) count1 = bt.query_radius(X, r, count_only=True) count2 = (D <= r).sum(1) assert_array_almost_equal(count1, count2)
def test_query_radius_indices(self, n_queries=20): # center the data X = 2 * self.X - 1 dm = DistanceMetric() D = dm.cdist(X[:n_queries], X) r = np.mean(D) bt = BallTree(X) ind = bt.query_radius(X[:n_queries], r, return_distance=False) ind2 = np.zeros(D.shape) + np.arange(D.shape[1]) ind = np.concatenate(map(np.sort, ind)) ind2 = ind2[D <= r] assert_array_almost_equal(ind, ind2)
def test_query_radius_indices(self, n_queries=20): # center the data X = 2 * self.X - 1 dm = DistanceMetric() D = dm.cdist(X[:n_queries], X) r = np.mean(D) bt = BallTree(X) ind = bt.query_radius(X[:n_queries], r, return_distance=False) ind2 = np.zeros(D.shape) + np.arange(D.shape[1]) ind = np.concatenate(map(np.sort, ind)) ind2 = ind2[D <= r] assert_array_almost_equal(ind, ind2)