Classe « KDTree »

Méthode scipy.spatial.KDTree.query_ball_tree

Signature de la méthode query_ball_tree

def query_ball_tree(self, other, r, p=2.0, eps=0) 

Description

query_ball_tree.__doc__

        Find all pairs of points between `self` and `other` whose distance is
        at most r.

        Parameters
        ----------
        other : KDTree instance
            The tree containing points to search against.
        r : float
            The maximum distance, has to be positive.
        p : float, optional
            Which Minkowski norm to use.  `p` has to meet the condition
            ``1 <= p <= infinity``.
        eps : float, optional
            Approximate search.  Branches of the tree are not explored
            if their nearest points are further than ``r/(1+eps)``, and
            branches are added in bulk if their furthest points are nearer
            than ``r * (1+eps)``.  `eps` has to be non-negative.

        Returns
        -------
        results : list of lists
            For each element ``self.data[i]`` of this tree, ``results[i]`` is a
            list of the indices of its neighbors in ``other.data``.

        Examples
        --------
        You can search all pairs of points between two kd-trees within a distance:

        >>> import matplotlib.pyplot as plt
        >>> import numpy as np
        >>> from scipy.spatial import KDTree
        >>> rng = np.random.default_rng()
        >>> points1 = rng.random((15, 2))
        >>> points2 = rng.random((15, 2))
        >>> plt.figure(figsize=(6, 6))
        >>> plt.plot(points1[:, 0], points1[:, 1], "xk", markersize=14)
        >>> plt.plot(points2[:, 0], points2[:, 1], "og", markersize=14)
        >>> kd_tree1 = KDTree(points1)
        >>> kd_tree2 = KDTree(points2)
        >>> indexes = kd_tree1.query_ball_tree(kd_tree2, r=0.2)
        >>> for i in range(len(indexes)):
        ...     for j in indexes[i]:
        ...         plt.plot([points1[i, 0], points2[j, 0]],
        ...             [points1[i, 1], points2[j, 1]], "-r")
        >>> plt.show()