我正在尝试使用Kdtree数据结构来从数组中移除最接近的点,而不需要for循环。
import sys
import time
import scipy.spatial
class KDTree:
"""
Nearest neighbor search class with KDTree
"""
def __init__(self, data):
# store kd-tree
self.tree = scipy.spatial.cKDTree(data)
def search(self, inp, k=1):
"""
Search NN
inp: input data, single frame or multi frame
"""
if len(inp.shape) >= 2: # multi input
index = []
dist = []
for i in inp.T:
idist, iindex = self.tree.query(i, k=k)
index.append(iindex)
dist.append(idist)
return index, dist
dist, index = self.tree.query(inp, k=k)
return index, dist
def search_in_distance(self, inp, r):
"""
find points with in a distance r
"""
index = self.tree.query_ball_point(inp, r)
return np.asarray(index)
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
start = time.time()
fig, ar = plt.subplots()
t = 0
R = 50.0
u = R *np.cos(t)
v = R *np.sin(t)
x = np.linspace(-100,100,51)
y = np.linspace(-100,100,51)
xx, yy = np.meshgrid(x,y)
points =np.vstack((xx.ravel(),yy.ravel())).T
Tree = KDTree(points)
ind = Tree.search_in_distance([u, v],10.0)
ar.scatter(points[:,0],points[:,1],c='k',s=1)
infected = points[ind]
ar.scatter(infected[:,0],infected[:,1],c='r',s=5)
def animate(i):
global R,t,start,points
ar.clear()
u = R *np.cos(t)
v = R *np.sin(t)
ind = Tree.search_in_distance([u, v],10.0)
ar.scatter(points[:,0],points[:,1],c='k',s=1)
infected = points[ind]
ar.scatter(infected[:,0],infected[:,1],c='r',s=5)
#points = np.delete(points,ind)
t+=0.01
end = time.time()
if end - start != 0:
print((end - start), end="\r")
start = end
ani = animation.FuncAnimation(fig, animate, interval=20)
plt.show()
但是无论我做什么,我都无法np.delete来处理ball_query方法返回的索引。我想念什么?
我想使红色点在每次迭代中都从点数组中消失。
您的points
数组是Nx2矩阵。您的索引是行索引的列表。您需要指定要删除的轴,最终是这样:
points = np.delete(points,ind,axis=0)
此外,一旦删除索引,请在下次迭代/计算中注意缺少的索引。也许您想要一个副本来删除点和图,并想要另一个副本来进行计算,但不要从中删除。