Xtykutl

I have two overlapping sets of points T and B.

I want to return all points from T that are within the convex hull of B
I compute the convex hulls as follows

from scipy.spatial import Convexhull

import numpy as np

T=np.asarray(T)

B=np.asarray(B)



Thull = ConvexHull(T)

Bhull = ConvexHull(B)

How do I do the spatial query?

Here is an example of what you want using the function defined in the other question I posted in the comments:

from scipy.spatial import Delaunay

import numpy as np

import matplotlib.pyplot as plt



def in_hull(p, hull):

    """

    Test if points in `p` are in `hull`



    `p` should be a `NxK` coordinates of `N` points in `K` dimensions

    `hull` is either a scipy.spatial.Delaunay object or the `MxK` array of the 

    coordinates of `M` points in `K`dimensions for which Delaunay triangulation

    will be computed

    """

    if not isinstance(hull,Delaunay):

        hull = Delaunay(hull)



    return hull.find_simplex(p)>=0



T = np.random.rand(30,2)

B = T + np.array([[0.4, 0] for i in range(30)])



plt.plot(T[:,0], T[:,1], 'o')

plt.plot(B[:,0], B[:,1], 'o')





new_points = T[in_hull(T,B)]



plt.plot(new_points[:,0], new_points[:,1], 'x', markersize=8)

This finds all points of T in the hull of B and saves them in new_points. I also plot it, so you see the result