convexhull torch实现
时间: 2024-02-15 09:05:23 浏览: 28
要使用PyTorch实现凸包(Convex Hull),可以按照以下步骤进行:
1. 安装PyTorch和numpy库
```python
pip install torch numpy
```
2. 实现快速求解凸包的算法,比如Graham扫描算法,该算法可以在线性时间内求解凸包。
```python
import torch
import numpy as np
def orientation(p, q, r):
"""返回三个点的方向"""
val = (q[1] - p[1]) * (r[0] - q[0]) - (q[0] - p[0]) * (r[1] - q[1])
if val == 0:
return 0 # 共线
elif val > 0:
return 1 # 顺时针
else:
return 2 # 逆时针
def convex_hull(points):
"""求解凸包"""
n = len(points)
if n < 3:
return None
hull = []
l = 0
for i in range(1, n):
if points[i][0] < points[l][0]:
l = i
p = l
while True:
hull.append(points[p])
q = (p + 1) % n
for i in range(n):
if orientation(points[p], points[i], points[q]) == 2:
q = i
p = q
if p == l:
break
return hull
```
3. 实现一个可以接受PyTorch Tensor作为输入的凸包函数。
```python
def convex_hull_torch(points):
"""求解凸包"""
n = points.shape[0]
if n < 3:
return None
hull = []
l = 0
for i in range(1, n):
if points[i][0] < points[l][0]:
l = i
p = l
while True:
hull.append(points[p])
q = (p + 1) % n
for i in range(n):
if orientation(points[p], points[i], points[q]) == 2:
q = i
p = q
if p == l:
break
return torch.stack(hull)
```
现在就可以使用convex_hull_torch函数来求解凸包了。假设有一个大小为(5, 2)的Tensor表示5个点的坐标,可以这样调用:
```python
points = torch.tensor([[0, 0], [0, 1], [1, 1], [1, 0], [0.5, 0.5]])
hull = convex_hull_torch(points)
print(hull)
```
输出结果为:
```
tensor([[0., 0.],
[1., 0.],
[1., 1.],
[0., 1.]])
```
这表示这5个点的凸包为一个正方形。