本文整理汇总了Python中sklearn.neighbors.kd_tree.KDTree.two_point_correlation方法的典型用法代码示例。如果您正苦于以下问题：Python KDTree.two_point_correlation方法的具体用法？Python KDTree.two_point_correlation怎么用？Python KDTree.two_point_correlation使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.neighbors.kd_tree.KDTree的用法示例。
在下文中一共展示了KDTree.two_point_correlation方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_kd_tree_two_point
# 需要导入模块: from sklearn.neighbors.kd_tree import KDTree [as 别名]
# 或者: from sklearn.neighbors.kd_tree.KDTree import two_point_correlation [as 别名]
def test_kd_tree_two_point(dualtree):
n_samples, n_features = (100, 3)
rng = check_random_state(0)
X = rng.random_sample((n_samples, n_features))
Y = rng.random_sample((n_samples, n_features))
r = np.linspace(0, 1, 10)
kdt = KDTree(X, leaf_size=10)
D = DistanceMetric.get_metric("euclidean").pairwise(Y, X)
counts_true = [(D <= ri).sum() for ri in r]
counts = kdt.two_point_correlation(Y, r=r, dualtree=dualtree)
assert_array_almost_equal(counts, counts_true)