4

任何人都可以提出修复或替代路线来找到此系统的解决方案吗? 特别是我只关心[0,1] x [0,1]中的解(s,t)求解三次多项式系统(找到贝塞尔曲线的交点)

注意:我正在寻找两个三次贝塞尔曲线的交点。我需要保证找到所有解决方案的方法,并希望在合理的时间内(对于我的使用,这意味着每对曲线只需几秒钟)。

我试过使用sympy,但solve()和solve_poly_system()返回空列表。

这里是我的代码:

from sympy.solvers import solve_poly_system, solve 
from sympy.abc import s,t 

#here are two cubics. I'm looking for their intersection in [0,1]x[0,1]: 
cub1 = 600*s**3 - 1037*s**2 + 274*s + 1237*t**3 - 2177*t**2 + 642*t + 77 
cub2 = -534*s**3 + 582*s**2 + 437*s + 740*t**3 - 1817*t**2 + 1414*t - 548 

#I know such a solution exists (from plotting these curves) and fsolve finds an  approximation of it no problem: 
from scipy.optimize import fsolve 
fcub1 = lambda (s,t): 600*s**3 - 1037*s**2 + 274*s + 1237*t**3 - 2177*t**2 + 642*t + 77 
fcub2 = lambda (s,t):-534*s**3 + 582*s**2 + 437*s + 740*t**3 - 1817*t**2 + 1414*t - 548 
F = lambda x: [fcub1(x),fcub2(x)] 
print 'fsolve gives (s,t) = ' + str(fsolve(F,(0.5,0.5))) 
print 'F(s,t) = ' + str(F(fsolve(F,(0.5,0.5)))) 

#solve returns an empty list 
print solve([cub1,cub2]) 

#solve_poly_system returns a DomainError: can't compute a Groebner basis over RR 
print solve_poly_system([cub1,cub2]) 

此输出:

fsolve gives (s,t) = [ 0.35114023 0.50444115] 
F(s,t) = [4.5474735088646412e-13, 0.0] 
[] 
[] 

感谢您的阅读!

+0

我认为这不能由sympy解决。例外是因为您在评估中使用了浮点值。在'solve_poly_system'的源代码中有一行检查顺序:'如果a <= 2且b <= 2且c <= 2且d <= 2:' – HYRY

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@HYRY:哦,你说得对DomainError。我的意思是删除所有的小数来检查,但我错过了一个! 另外,你是否说你相信solve_poly_system只能用于每个多项式的阶数<3的系统? – AndyP

回答

4

对于贝济耶的交点,有更好的方法。 (http://pomax.github.io/bezierinfo/#curveintersectionhttp://www.tsplines.com/technology/edu/CurveIntersection.pdf)。

我对一个简单的解决方案的建议:实现贝塞尔细分算法(http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/spline/Bezier/bezier-sub.html)。对于这两条曲线,计算控制顶点的边界框。如果它们重叠,则可以使用交叉点进行细分并重复该过程(这次将进行四次比较)。继续递归。

你不能害怕指数爆炸(1,4,16,256 ...比较),因为很快很多盒子会停止重叠。

请注意,从理论上讲,您可以使用控制点的凸包,但实际上一个简单的边界框就足够了,而且更容易处理。

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我认为这将适合我的目的。我会尽力实施它,今晚看到。谢谢。 – AndyP

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很好,谢谢!我在下面粘贴了我的代码。 – AndyP

+0

很高兴为您服务。贝塞尔曲线具有很好的性质。 –

0

如何简化系统?

通过适当的线性组合,您可以消除s^3t^3中的一个,并求解剩余的二阶方程。通过在另一个方程中插入结果,您可以在单个未知数中得到单个方程。

或者解决由生成物得到的代数方程:

36011610661302281 - 177140805507270756*s - 201454039857766711*s^2 + 1540826307929388607*s^3 + 257712262726095899*s^4 - 4599101672917940010*s^5 + 1114665205197856508*s^6 + 6093758014794453276*s^7 - 5443785088068396888*s^8 + 1347614193395309112*s^9 = 0 

http://www.dr-mikes-maths.com/polynomial-reduction.html

+0

我相信我不熟悉这种方法,我会检查出来。所以你认为这将适用于找到任何两个立方(特别是贝塞尔)曲线的交集? – AndyP

+0

是的,但我没有注意到它是贝齐尔的交集。有更合适的方法解决这个问题,利用船体属性。 –

1

伊夫的解决方案运行良好。这里是我的情况下,代码可以帮助任何人:

from math import sqrt 
def cubicCurve(P,t): 
    return P[0]*(1-t)**3 + 3*P[1]*t*(1-t)**2 + 3*P[2]*(1-t)*t**2 + P[3]*t**3 
def cubicMinMax_x(points): 
    local_extremizers = [0,1] 
    a = [p.real for p in points] 
    delta = a[1]**2 - (a[0] + a[1]*a[2] + a[2]**2 + (a[0] - a[1])*a[3]) 
    if delta>=0: 
     sqdelta = sqrt(delta)/(a[0] - 3*a[1] + 3*a[2] - a[3]) 
     tau = a[0] - 2*a[1] + a[2] 
     r1 = tau+sqdelta 
     r2 = tau-sqdelta 
     if 0<r1<1: 
      local_extremizers.append(r1) 
     if 0<r2<1: 
      local_extremizers.append(r2) 
    localExtrema = [cubicCurve(a,t) for t in local_extremizers] 
    return min(localExtrema),max(localExtrema) 
def cubicMinMax_y(points): 
    return cubicMinMax_x([-1j*p for p in points]) 
def intervalIntersectionWidth(a,b,c,d): #returns width of the intersection of intervals [a,b] and [c,d] (thinking of these as intervals on the real number line) 
    return max(0, min(b, d) - max(a, c)) 
def cubicBoundingBoxesIntersect(cubs):#INPUT: 2-tuple of cubics (given bu control points) #OUTPUT: boolean 
    x1min,x1max = cubicMinMax_x(cubs[0]) 
    y1min,y1max = cubicMinMax_y(cubs[0]) 
    x2min,x2max = cubicMinMax_x(cubs[1]) 
    y2min,y2max = cubicMinMax_y(cubs[1]) 
    if intervalIntersectionWidth(x1min,x1max,x2min,x2max) and intervalIntersectionWidth(y1min,y1max,y2min,y2max): 
     return True 
    else: 
     return False 
def cubicBoundingBoxArea(cub_points):#INPUT: 2-tuple of cubics (given bu control points) #OUTPUT: boolean 
    xmin,xmax = cubicMinMax_x(cub_points) 
    ymin,ymax = cubicMinMax_y(cub_points) 
    return (xmax-xmin)*(ymax-ymin) 
def halveCubic(P): 
    return ([P[0], (P[0]+P[1])/2, (P[0]+2*P[1]+P[2])/4, (P[0]+3*P[1]+3*P[2]+P[3])/8],[(P[0]+3*P[1]+3*P[2]+P[3])/8,(P[1]+2*P[2]+P[3])/4,(P[2]+P[3])/2,P[3]]) 
class Pair(object): 
    def __init__(self,cub1,cub2,t1,t2): 
     self.cub1 = cub1 
     self.cub2 = cub2 
     self.t1 = t1 #the t value to get the mid point of this curve from cub1 
     self.t2 = t2 #the t value to get the mid point of this curve from cub2 
def cubicXcubicIntersections(cubs): 
#INPUT: a tuple cubs=([P0,P1,P2,P3], [Q0,Q1,Q2,Q3]) defining the two cubic to check for intersections between. See cubicCurve fcn for definition of P0,...,P3 
#OUTPUT: a list of tuples (t,s) in [0,1]x[0,1] such that cubicCurve(cubs[0],t) - cubicCurve(cubs[1],s) < Tol_deC 
#Note: This will return exactly one such tuple for each intersection (assuming Tol_deC is small enough) 
    Tol_deC = 1 ##### This should be set based on your accuracy needs. Making it smaller will have relatively little effect on performance. Mine is set to 1 because this is the area of a pixel in my setup and so the curve (drawn by hand/mouse) is only accurate up to a pixel at most. 
    maxIts = 100 ##### This should be something like maxIts = 1-log(Tol_deC/length)/log(2), where length is the length of the longer of the two cubics, but I'm not actually sure how close to being parameterized by arclength these curves are... so I guess I'll leave that as an exercise for the interested reader :) 
    pair_list = [Pair(cubs[0],cubs[1],0.5,0.5)] 
    intersection_list = [] 
    k=0 
    while pair_list != []: 
     newPairs = [] 
     delta = 0.5**(k+2) 
     for pair in pair_list: 
      if cubicBoundingBoxesIntersect((pair.cub1,pair.cub2)): 
       if cubicBoundingBoxArea(pair.cub1)<Tol_deC and cubicBoundingBoxArea(pair.cub2)<Tol_deC: 
        intersection_list.append((pair.t1,pair.t2)) #this is the point in the middle of the pair 
        for otherPair in pair_list: 
         if pair.cub1==otherPair.cub1 or pair.cub2==otherPair.cub2 or pair.cub1==otherPair.cub2 or pair.cub2==otherPair.cub1: 
          pair_list.remove(otherPair) #this is just an ad-hoc fix to keep it from repeating intersection points 
       else: 
        (c11,c12) = halveCubic(pair.cub1) 
        (t11,t12) = (pair.t1-delta,pair.t1+delta) 
        (c21,c22) = halveCubic(pair.cub2) 
        (t21,t22) = (pair.t2-delta,pair.t2+delta) 
        newPairs += [Pair(c11,c21,t11,t21), Pair(c11,c22,t11,t22), Pair(c12,c21,t12,t21), Pair(c12,c22,t12,t22)] 
     pair_list = newPairs 
     k += 1 
     if k > maxIts: 
      raise Exception ("cubicXcubicIntersections has reached maximum iterations without terminating... either there's a problem/bug or you can fix by raising the max iterations or lowering Tol_deC") 
    return intersection_list 

而且万一有人想它,我写了编码德卡斯特里奥算法为分裂任意程度的贝塞尔曲线。在上面的代码中,我只是用halveCubic来代替它,这只是de Casteljau的方法,但是明确地将其限制为立方案(t = 0.5)。

def splitBezier(points,t): 
#returns 2 tuples of control points for the two resulting Bezier curves 
    points_left=[] 
    points_right=[] 
    (points_left,points_right) = splitBezier_deCasteljau_recursion((points_left,points_right),points,t) 
    points_right.reverse() 
    return (points_left,points_right) 
def splitBezier_deCasteljau_recursion(cub_lr,points,t): 
    (cub_left,cub_right)=cub_lr 
    if len(points)==1: 
     cub_left.append(points[0]) 
     cub_right.append(points[0]) 
    else: 
     n = len(points)-1 
     newPoints=[None]*n 
     cub_left.append(points[0]) 
     cub_right.append(points[n]) 
     for i in range(n): 
      newPoints[i] = (1-t)*points[i] + t*points[i+1] 
     (cub_left, cub_right) = splitBezier_deCasteljau_recursion((cub_left,cub_right),newPoints,t) 
    return (cub_left, cub_right) 

我希望能帮助那里的人! 再次感谢你帮助伊夫!