这是一个C#实现的算法,其解释可以在这里找到。它还使用了Unity数学库和集合包。
public static NativeArray<float2> ExpandPoly(NativeArray<float2> oldPoints, float offset, int outer_ccw = 1)
{
int num_points = oldPoints.Length;
NativeArray<float2> newPoints = new NativeArray<float2>(num_points, Allocator.Temp);
for (int curr = 0; curr < num_points; curr++)
{
int prev = (curr + num_points - 1) % num_points;
int next = (curr + 1) % num_points;
float2 vn = oldPoints[next] - oldPoints[curr];
float2 vnn = math.normalize(vn);
float nnnX = vnn.y;
float nnnY = -vnn.x;
float2 vp = oldPoints[curr] - oldPoints[prev];
float2 vpn = math.normalize(vp);
float npnX = vpn.y * outer_ccw;
float npnY = -vpn.x * outer_ccw;
float bisX = (nnnX + npnX) * outer_ccw;
float bisY = (nnnY + npnY) * outer_ccw;
float2 bisn = math.normalize(new float2(bisX, bisY));
float bislen = offset / math.sqrt((1 + nnnX * npnX + nnnY * npnY) / 2);
newPoints[curr] = new float2(oldPoints[curr].x + bislen * bisn.x, oldPoints[curr].y + bislen * bisn.y);
}
return newPoints;
}
typedef struct {
double x;
double y;
} Point2D;
double Hypot(double x, double y)
{
return std::sqrt(x * x + y * y);
}
Point2D NormalizeVector(const Point2D& p)
{
double h = Hypot(p.x, p.y);
if (h < 0.0001)
return Point2D({ 0.0, 0.0 });
double inverseHypot = 1 / h;
return Point2D({ (double)p.x * inverseHypot, (double)p.y * inverseHypot });
}
void offsetPolygon(std::vector<Point2D>& polyCoords, std::vector<Point2D>& newPolyCoords, double offset, int outer_ccw)
{
if (offset == 0.0 || polyCoords.size() < 3)
return;
Point2D vnn, vpn, bisn;
double vnX, vnY, vpX, vpY;
double nnnX, nnnY;
double npnX, npnY;
double bisX, bisY, bisLen;
unsigned int nVerts = polyCoords.size() - 1;
for (unsigned int curr = 0; curr < polyCoords.size(); curr++)
{
int prev = (curr + nVerts - 1) % nVerts;
int next = (curr + 1) % nVerts;
vnX = polyCoords[next].x - polyCoords[curr].x;
vnY = polyCoords[next].y - polyCoords[curr].y;
vnn = NormalizeVector({ vnX, vnY });
nnnX = vnn.y;
nnnY = -vnn.x;
vpX = polyCoords[curr].x - polyCoords[prev].x;
vpY = polyCoords[curr].y - polyCoords[prev].y;
vpn = NormalizeVector({ vpX, vpY });
npnX = vpn.y * outer_ccw;
npnY = -vpn.x * outer_ccw;
bisX = (nnnX + npnX) * outer_ccw;
bisY = (nnnY + npnY) * outer_ccw;
bisn = NormalizeVector({ bisX, bisY });
bisLen = offset / std::sqrt((1 + nnnX * npnX + nnnY * npnY) / 2);
newPolyCoords.push_back({ polyCoords[curr].x + bisLen * bisn.x, polyCoords[curr].y + bisLen * bisn.y });
}
}
有几个库可以使用(也可用于3D数据集)。
用户还可以找到这些库的相应出版物,以更详细地了解算法。
最后一个具有最少的依赖关系,是自包含的,并且可以读取 .obj 文件。
为了扩展一个多边形,可以实现“通过计算绕组数进行多边形偏移”的算法article。
该算法的步骤如下:
以下是一个示例。 这里输入多边形为虚线蓝色,左侧为红色 - 移动边缘,右侧为在连续自相交曲线中连接它们后的结果:
曲线将平面分成许多连通的部分,需要计算每个部分中的绕数,然后取所有绕数为正的连通部分的边界: 本文证明该算法与竞争对手相比非常快速且同时具有鲁棒性。GLU_TESS_BOUNDARY_ONLY=GL_TRUE
(跳过三角剖分)和GLU_TESS_WINDING_RULE=GLU_TESS_WINDING_POSITIVE
(输出正绕数组件的边界)。