如何在这段代码中增加将获取到的点根据点的分数剔除比例再次筛选void DyConcentricArc::RansacCircleFiler(const vector<Point2d>& points, vector<Point2d>& vpdExceptPoints, double sigma) { unsigned int n = points.size(); if (n < 3) { return; } RNG random; double bestScore = -1.; vector<Point2d>vpdTemp; int iterations = log(1 - 0.99) / (log(1 - (1.00 / n))); for (int k = 0; k < iterations; k++) { int i1 = 0, i2 = 0, i3 = 0; Point2d p1(0, 0), p2(0, 0), p3(0, 0); while (true) { i1 = random(n); i2 = random(n); i3 = random(n); if ((i1 != i2 && i1 != i3 && i2 != i3)) { if ((points[i1].y != points[i2].y) && (points[i1].y != points[i3].y)) { break; } } } p1 = points[i1]; p2 = points[i2]; p3 = points[i3]; //use three points to caculate a circle Point2d pdP12 = GetPPCenter(p1, p2); double dK1 = -1 / GetLineSlope(p1, p2); double dB1 = pdP12.y - dK1 * pdP12.x; Point2d pdP13 = GetPPCenter(p1, p3); double dK2 = -1 / GetLineSlope(p1, p3); double dB2 = pdP13.y - dK2 * pdP13.x; Point2d pdCenter(0, 0); pdCenter.x = (dB2 - dB1) / (dK1 - dK2); pdCenter.y = dK1 * pdCenter.x + dB1; double dR = GetPPDistance(pdCenter, p1); double score = 0; vpdTemp.clear(); for (int i = 0; i < n; i++) { double d = dR - GetPPDistance(points[i], pdCenter); if (fabs(d) < sigma) { score += 1; } else { vpdTemp.push_back(points[i]); } } if (score > bestScore) { bestScore = score; vpdExceptPoints = vpdTemp; } } }

可以在函数中增加一个参数，表示剔除分数较低的点的比例，比如设为ratio。在每次迭代的时候，先计算出剔除的点数为n*ratio，然后将点按照得分从小到大排序，再依次将得分较低的n*ratio个点删除，剩下的点作为下一次迭代的输入点。可以在函数中增加如下代码：

void DyConcentricArc::RansacCircleFiler(const vector<Point2d>& points, vector<Point2d>& vpdExceptPoints, double sigma, double ratio) {
    unsigned int n = points.size();
    if (n < 3) {
        return;
    }

    RNG random;
    double bestScore = -1.;
    vector<Point2d>vpdTemp;
    int iterations = log(1 - 0.99) / (log(1 - (1.00 / n)));
    
    for (int k = 0; k < iterations; k++) {
        int i1 = 0, i2 = 0, i3 = 0;
        Point2d p1(0, 0), p2(0, 0), p3(0, 0);
        while (true) {
            i1 = random(n);
            i2 = random(n);
            i3 = random(n);
            if ((i1 != i2 && i1 != i3 && i2 != i3)) {
                if ((points[i1].y != points[i2].y) && (points[i1].y != points[i3].y)) {
                    break;
                }
            }
        }
        p1 = points[i1];
        p2 = points[i2];
        p3 = points[i3];

        //use three points to caculate a circle
        Point2d pdP12 = GetPPCenter(p1, p2);
        double dK1 = -1 / GetLineSlope(p1, p2);
        double dB1 = pdP12.y - dK1 * pdP12.x;
        Point2d pdP13 = GetPPCenter(p1, p3);
        double dK2 = -1 / GetLineSlope(p1, p3);
        double dB2 = pdP13.y - dK2 * pdP13.x;
        Point2d pdCenter(0, 0);
        pdCenter.x = (dB2 - dB1) / (dK1 - dK2);
        pdCenter.y = dK1 * pdCenter.x + dB1;
        double dR = GetPPDistance(pdCenter, p1);

        double score = 0;
        vpdTemp.clear();
        for (int i = 0; i < n; i++) {
            double d = dR - GetPPDistance(points[i], pdCenter);
            if (fabs(d) < sigma) {
                score += 1;
            }
            else {
                vpdTemp.push_back(points[i]);
            }
        }

        // sort points by score
        sort(vpdTemp.begin(), vpdTemp.end(), [&](Point2d a, Point2d b) {
            return GetPPDistance(a, pdCenter) < GetPPDistance(b, pdCenter);
        });

        // remove low-score points
        int numToRemove = (int)(vpdTemp.size() * ratio);
        for (int i = 0; i < numToRemove; i++) {
            vpdTemp.erase(vpdTemp.begin());
        }

        if (score > bestScore) {
            bestScore = score;
            vpdExceptPoints = vpdTemp;
        }
    }
}