Python 流浪星-codeabbey任务
我正在努力解决这个问题，但我不知道下一步该怎么办Python 流浪星-codeabbey任务,python,algorithm,vector,puzzle,Python,Algorithm,Vector,Puzzle,我正在努力解决这个问题，但我不知道下一步该怎么办 问题陈述： 假设已经完成了一些初步的图像预处理，并且在两张图片上有恒星坐标形式的数据。这些图片约为100x100毫米，坐标也以毫米为单位，相对于它们的中心。请看下面的示意图： 你可以看到，在这两张照片中，恒星都显示在大致的圆形区域（可以把它看作是我们望远镜的外观），你可以发现它们代表着同一片天空——略微旋转和移动 您还可以看到其中一颗星星（用红色箭头标记）改变了相对于其他星星的位置 你的任务是找出这样一颗“游荡的恒星”，因为它很可能是彗星或小行
问题陈述：
假设已经完成了一些初步的图像预处理，并且在两张图片上有恒星坐标形式的数据。这些图片约为100x100毫米，坐标也以毫米为单位，相对于它们的中心。请看下面的示意图： 你可以看到，在这两张照片中，恒星都显示在大致的圆形区域（可以把它看作是我们望远镜的外观），你可以发现它们代表着同一片天空——略微旋转和移动 您还可以看到其中一颗星星（用红色箭头标记）改变了相对于其他星星的位置 你的任务是找出这样一颗“游荡的恒星”，因为它很可能是彗星或小行星 请注意，一些靠近边缘的恒星可能会从其中一张图片中消失（由于偏移），但“游荡恒星”离中心不远，因此在两张图片上都会出现 输入数据包含对应于两个图像的两个部分。 每个序列都以一个整数开始，即列出的星星数。 然后恒星的坐标（X和Y）随之变化 答案应在第一节和第二节分别给出游荡星的两个指数（基于0） 示例与上面的图片相同。第一部分坐标为（-18.2,11.1）的星29与第二部分坐标为（-19.7,6.9）的星3相同。 输入数据示例：
94#第1节包含94颗星
-47.5-10.4
19.1 25.9
18.9-10.4
-2.1-47.6
…
…
92#第2节包含92颗星
-14.8 10.9
18.8-0.1
-11.3.5.7
-19.7.6.9
-11.5-16.7
-45.4-15.3
6.0-46.9
-24.1-26.3
30.2 27.4
…
... 我面临的问题
问题是向量不匹配，甚至大小也不相同。例如，第一节中的第一个向量与第二节中的第一个向量不匹配，所以我无法基于此计算旋转矩阵。我还尝试根据每个截面的质心计算它，但边缘上的一些点可能不存在，因此它们将具有不同的质心（我尝试只包括长度小于40的向量，大小仍然不匹配） 所以我的问题是我的计算应该基于什么？如何找到一些匹配向量，以便计算它们的旋转矩阵？我需要往正确的方向推 我所做的是实现函数来找到两个给定向量之间的旋转矩阵。我使用的公式：
变换的_向量=R*原始_向量+t
其中R是旋转矩阵，因为向量也沿轴移动了一点，所以我还要加上t
现在我只需要两个向量来计算 编辑：我可能应该提到，我实际上得到了两个向量数组，每个图像一个，我实际上没有得到图像。我需要找到根据这些向量移动的恒星
谢谢 [edit2]完成重新编辑 我已经为此找到了一些时间/心情，使其更加健壮
- 让
作为输入星列表xy0[]，xy1[] - 让
成为附近的搜索区域treshldmax\u r - 将
设为最大可接受的群集匹配错误max_err
- 这使得搜索更快更容易
xy0[]中查找星团
- 环游全明星
- 并将它们与附近的恒星进行对照
- 由于排序的原因，附近的星星也将接近当前的星星索引
- 所以只需搜索阵列中这颗星前后的近距离区域
- 直到x距离穿过
max\u r
- 将集群添加到
cl0[]
集群列表（如果找到）
- （星团由两颗或更多近距离恒星组成）
- 在添加新群集之前
- 检查附近是否没有群集
- 如果离另一个集群太近，则合并
- 平均坐标
- 内部所有恒星之间的距离
- 按距离asc对它们进行排序
xy1[]，cl1[]- 因此，检查内部的距离列表是否相同
- （记住abs误差的最小和）
- 如果错误大于最大错误，则拒绝此群集匹配
- 这是一种强匹配，我们在许多集群（大max_r）上进行了测试，但没有在此数据集上出现不匹配
cl0[]xy0[]，xy1[]之间的转换
- 我使用了集群的平均坐标，它非常匹配
- 左侧是
setxy0[] - 中间是
setxy1[] - 在右边，蓝色的大点是
xy0[] - 绿色的小点被变换
xy1[] - 这些数字是群集匹配的错误（-1表示未找到匹配项）
列表- 它只是动态地重新分配线性阵列
与列表xintx[]相同- 其中
是项目访问x[i]
是数组中的项数x.num
与x.add（5）x[x.num]=5相同；x、 num++
//---------------------------------------------------------------------------
// answer: 29 3
// input data:
const int n0=94; double xy0[n0][2]=
{
-47.5,-10.4,19.1,25.9,18.9,-10.4,-2.1,-47.6,41.8,-12.1,-15.7,12.1,-11.0,-0.6,
-15.6,-7.6,14.9,43.5,16.6,0.1,3.6,-33.5,-14.2,20.8,17.8,-29.8,-2.2,-12.8,
44.6,19.7,17.9,-41.3,24.6,37.0,43.9,14.5,23.8,19.6,-4.2,-40.5,32.0,17.2,
22.6,-26.9,9.9,-33.4,-13.6,6.6,48.5,-3.5,-9.9,-39.9,-28.2,20.7,7.1,15.5,
-36.2,-29.9,-18.2,11.1,-1.2,-13.7,9.3,9.3,39.2,15.8,-5.2,-16.2,-34.9,5.0,
-13.4,-31.8,24.7,-29.1,1.4,24.0,-24.4,18.0,11.9,-29.1,36.3,18.6,30.3,38.4,
4.8,-20.5,-46.8,12.1,-44.2,-6.0,-1.4,-39.7,-1.0,-13.7,13.3,23.6,37.4,-7.0,
-22.3,37.8,17.6,-3.3,35.0,-9.1,-44.5,13.1,-5.1,19.7,-12.1,1.7,-30.9,-1.9,
-19.4,-15.0,10.8,31.9,19.7,3.1,29.9,-16.6,31.7,-26.8,38.1,30.2,3.5,25.1,
-14.8,19.6,2.1,29.0,-9.6,-32.9,24.8,4.9,-2.2,-24.7,-4.3,-37.4,-3.0,37.4,
-34.0,-21.2,-18.4,34.6,9.3,-45.2,-21.1,-10.3,-19.8,29.1,31.3,37.7,27.2,19.3,
-1.6,-45.6,35.3,-23.5,-39.9,-19.8,-3.8,40.6,-15.7,12.5,-0.8,-16.3,-5.1,13.1,
-13.8,-25.7,43.8,5.6,9.2,38.6,42.2,0.2,-10.0,-48.6,14.1,-6.5,34.6,-26.8,
11.1,-6.7,-6.1,25.1,-38.3,8.1,
};
const int n1=92; double xy1[n1][2]=
{
-14.8,10.9,18.8,-0.1,-11.3,5.7,-19.7,6.9,-11.5,-16.7,-45.4,-15.3,6.0,-46.9,
-24.1,-26.3,30.2,27.4,21.4,-27.2,12.1,-36.1,23.8,-38.7,41.5,5.3,-8.7,25.5,
36.6,-5.9,43.7,-14.6,-9.7,-8.6,34.7,-19.3,-15.5,19.3,21.4,3.9,34.0,29.8,
6.5,19.5,28.2,-21.7,13.4,-41.8,-25.9,-6.9,37.5,27.8,18.1,44.7,-43.0,-19.9,
-15.7,18.0,2.4,-31.6,9.6,-37.6,15.4,-28.8,43.6,-11.2,4.6,-10.2,-8.8,38.2,
8.7,-34.6,-4.7,14.1,-1.7,31.3,0.6,27.9,26.3,13.7,-1.2,26.3,32.1,-17.7,
15.5,32.6,-14.4,-12.6,22.3,-22.5,7.0,48.5,-6.4,20.5,-42.9,4.2,-23.0,31.6,
-24.6,14.0,-30.2,-26.5,-29.0,15.7,6.0,36.3,44.3,13.5,-27.6,33.7,13.4,-43.9,
10.5,28.9,47.0,1.4,10.2,14.0,13.3,-15.9,-3.4,-25.6,-14.7,10.5,21.6,27.6,
21.8,10.6,-37.8,-14.2,7.6,-21.8,-8.6,1.3,6.8,-13.3,40.9,-15.3,-10.3,41.1,
6.0,-10.8,-1.5,-31.4,-35.6,1.0,2.5,-14.3,24.4,-2.6,-24.1,-35.3,-29.9,-34.7,
15.9,-1.0,19.5,7.0,44.5,19.1,39.7,2.7,2.7,42.4,-23.0,25.9,25.0,28.2,31.2,-32.8,
3.9,-38.4,-44.8,2.7,-39.9,-19.3,-7.0,-0.6,5.8,-10.9,-44.5,19.9,-31.5,-1.2,
};
//---------------------------------------------------------------------------
struct _dist // distance structure
{
int ix; // star index
double d; // distance to it
_dist(){}; _dist(_dist& a){ *this=a; }; ~_dist(){}; _dist* operator = (const _dist *a) { *this=*a; return this; }; /*_dist* operator = (const _dist &a) { ...copy... return this; };*/
};
struct _cluster // star cluster structure
{
double x,y; // avg coordinate
int iy; // ix of cluster match in the other set or -1
double err; // error of cluster match
List<int> ix; // star ix
List<double> d; // distances of stars ix[] against each other
_cluster(){}; _cluster(_cluster& a){ *this=a; }; ~_cluster(){}; _cluster* operator = (const _cluster *a) { *this=*a; return this; }; /*_cluster* operator = (const _cluster &a) { ...copy... return this; };*/
};
const double max_r=5.0; // find cluster max radius
const double max_err=0.2; // match cluster max distance error treshold
const double max_rr=max_r*max_r;
const double max_errr=max_err*max_err;
int wi0,wi1; // result wandering star ix ...
int ix0[n0],ix1[n1]; // original star indexes
List<_cluster> cl0,cl1; // found clusters
double txy1[n1][2]; // transformed xy1[]
//---------------------------------------------------------------------------
double atanxy(double x,double y)
{
const double pi=M_PI;
const double pi2=2.0*M_PI;
int sx,sy;
double a;
const double _zero=1.0e-30;
sx=0; if (x<-_zero) sx=-1; if (x>+_zero) sx=+1;
sy=0; if (y<-_zero) sy=-1; if (y>+_zero) sy=+1;
if ((sy==0)&&(sx==0)) return 0;
if ((sx==0)&&(sy> 0)) return 0.5*pi;
if ((sx==0)&&(sy< 0)) return 1.5*pi;
if ((sy==0)&&(sx> 0)) return 0;
if ((sy==0)&&(sx< 0)) return pi;
a=y/x; if (a<0) a=-a;
a=atan(a);
if ((x>0)&&(y>0)) a=a;
if ((x<0)&&(y>0)) a=pi-a;
if ((x<0)&&(y<0)) a=pi+a;
if ((x>0)&&(y<0)) a=pi2-a;
return a;
}
//---------------------------------------------------------------------------
void compute()
{
int i0,i1,e,f;
double a,x,y;
// original indexes (to keep track)
for (e=0;e<n0;e++) ix0[e]=e;
for (e=0;e<n1;e++) ix1[e]=e;
// sort xy0[] by x asc
for (e=1;e;) for (e=0,i0=0,i1=1;i1<n0;i0++,i1++)
if (xy0[i0][0]>xy0[i1][0])
{
e=ix0[i0] ; ix0[i0] =ix0[i1] ; ix0[i1] =e; e=1;
a=xy0[i0][0]; xy0[i0][0]=xy0[i1][0]; xy0[i1][0]=a;
a=xy0[i0][1]; xy0[i0][1]=xy0[i1][1]; xy0[i1][1]=a;
}
// sort xy1[] by x asc
for (e=1;e;) for (e=0,i0=0,i1=1;i1<n1;i0++,i1++)
if (xy1[i0][0]>xy1[i1][0])
{
e=ix1[i0] ; ix1[i0] =ix1[i1] ; ix1[i1] =e; e=1;
a=xy1[i0][0]; xy1[i0][0]=xy1[i1][0]; xy1[i1][0]=a;
a=xy1[i0][1]; xy1[i0][1]=xy1[i1][1]; xy1[i1][1]=a;
}
_dist d;
_cluster c,*pc,*pd;
List<_dist> dist;
// find star clusters in xy0[]
for (cl0.num=0,i0=0;i0<n0;i0++)
{
for (dist.num=0,i1=i0+1;(i1<n0)&&(fabs(xy0[i0][0]-xy0[i1][0])<=max_r);i1++) // stars nearby
{
x=xy0[i0][0]-xy0[i1][0]; x*=x;
y=xy0[i0][1]-xy0[i1][1]; y*=y; a=x+y;
if (a<=max_rr) { d.ix=i1; d.d=a; dist.add(d); }
}
if (dist.num>=2) // add/compute cluster if found
{
c.ix.num=0; c.err=-1.0;
c.ix.add(i0); for (i1=0;i1<dist.num;i1++) c.ix.add(dist[i1].ix); c.iy=-1;
c.x=xy0[i0][0]; for (i1=0;i1<dist.num;i1++) c.x+=xy0[dist[i1].ix][0]; c.x/=dist.num+1;
c.y=xy0[i0][1]; for (i1=0;i1<dist.num;i1++) c.y+=xy0[dist[i1].ix][1]; c.y/=dist.num+1;
for (e=1,i1=0;i1<cl0.num;i1++)
{
pc=&cl0[i1];
x=c.x-pc->x; x*=x;
y=c.y-pc->y; y*=y; a=x+y;
if (a<max_rr) // merge if too close to another cluster
{
pc->x=0.5*(pc->x+c.x);
pc->y=0.5*(pc->y+c.y);
for (e=0;e<c.ix.num;e++)
{
for (f=0;f<pc->ix.num;f++)
if (pc->ix[f]==c.ix[e]) { f=-1; break; }
if (f>=0) pc->ix.add(c.ix[e]);
}
e=0; break;
}
}
if (e) cl0.add(c);
}
}
// full recompute clusters
for (f=0,pc=&cl0[f];f<cl0.num;f++,pc++)
{
// avg coordinate
pc->x=0.0; for (i1=0;i1<pc->ix.num;i1++) pc->x+=xy0[pc->ix[i1]][0]; pc->x/=pc->ix.num;
pc->y=0.0; for (i1=0;i1<pc->ix.num;i1++) pc->y+=xy0[pc->ix[i1]][1]; pc->y/=pc->ix.num;
// distances
for (pc->d.num=0,i0= 0;i0<pc->ix.num;i0++)
for ( i1=i0+1;i1<pc->ix.num;i1++)
{
x=xy0[pc->ix[i1]][0]-xy0[pc->ix[i0]][0]; x*=x;
y=xy0[pc->ix[i1]][1]-xy0[pc->ix[i0]][1]; y*=y;
pc->d.add(sqrt(x+y));
}
// sort by distance asc
for (e=1;e;) for (e=0,i0=0,i1=1;i1<pc->d.num;i0++,i1++)
if (pc->d[i0]>pc->d[i1])
{
a=pc->d[i0]; pc->d[i0]=pc->d[i1]; pc->d[i1]=a; e=1;
}
}
// find star clusters in xy1[]
for (cl1.num=0,i0=0;i0<n1;i0++)
{
for (dist.num=0,i1=i0+1;(i1<n1)&&(fabs(xy1[i0][0]-xy1[i1][0])<=max_r);i1++) // stars nearby
{
x=xy1[i0][0]-xy1[i1][0]; x*=x;
y=xy1[i0][1]-xy1[i1][1]; y*=y; a=x+y;
if (a<=max_rr) { d.ix=i1; d.d=a; dist.add(d); }
}
if (dist.num>=2) // add/compute cluster if found
{
c.ix.num=0; c.err=-1.0;
c.ix.add(i0); for (i1=0;i1<dist.num;i1++) c.ix.add(dist[i1].ix); c.iy=-1;
c.x=xy1[i0][0]; for (i1=0;i1<dist.num;i1++) c.x+=xy1[dist[i1].ix][0]; c.x/=dist.num+1;
c.y=xy1[i0][1]; for (i1=0;i1<dist.num;i1++) c.y+=xy1[dist[i1].ix][1]; c.y/=dist.num+1;
for (e=1,i1=0;i1<cl1.num;i1++)
{
pc=&cl1[i1];
x=c.x-pc->x; x*=x;
y=c.y-pc->y; y*=y; a=x+y;
if (a<max_rr) // merge if too close to another cluster
{
pc->x=0.5*(pc->x+c.x);
pc->y=0.5*(pc->y+c.y);
for (e=0;e<c.ix.num;e++)
{
for (f=0;f<pc->ix.num;f++)
if (pc->ix[f]==c.ix[e]) { f=-1; break; }
if (f>=0) pc->ix.add(c.ix[e]);
}
e=0; break;
}
}
if (e) cl1.add(c);
}
}
// full recompute clusters
for (f=0,pc=&cl1[f];f<cl1.num;f++,pc++)
{
// avg coordinate
pc->x=0.0; for (i1=0;i1<pc->ix.num;i1++) pc->x+=xy1[pc->ix[i1]][0]; pc->x/=pc->ix.num;
pc->y=0.0; for (i1=0;i1<pc->ix.num;i1++) pc->y+=xy1[pc->ix[i1]][1]; pc->y/=pc->ix.num;
// distances
for (pc->d.num=0,i0= 0;i0<pc->ix.num;i0++)
for ( i1=i0+1;i1<pc->ix.num;i1++)
{
x=xy1[pc->ix[i1]][0]-xy1[pc->ix[i0]][0]; x*=x;
y=xy1[pc->ix[i1]][1]-xy1[pc->ix[i0]][1]; y*=y;
pc->d.add(sqrt(x+y));
}
// sort by distance asc
for (e=1;e;) for (e=0,i0=0,i1=1;i1<pc->d.num;i0++,i1++)
if (pc->d[i0]>pc->d[i1])
{
a=pc->d[i0]; pc->d[i0]=pc->d[i1]; pc->d[i1]=a; e=1;
}
}
// find matches
for (i0=0,pc=&cl0[i0];i0<cl0.num;i0++,pc++) if (pc->iy<0){ e=-1; x=0.0;
for (i1=0,pd=&cl1[i1];i1<cl1.num;i1++,pd++) if (pc->d.num==pd->d.num)
{
for (y=0.0,f=0;f<pc->d.num;f++) y+=fabs(pc->d[f]-pd->d[f]);
if ((e<0)||(x>y)) { e=i1; x=y; }
}
x/=pc->d.num;
if ((e>=0)&&(x<max_err))
{
if (cl1[e].iy>=0) cl0[cl1[e].iy].iy=-1;
pc->iy =e; cl1[e].iy=i0;
pc->err=x; cl1[e].err=x;
}
}
// compute transform
double tx0,tx1,ty0,ty1,tc,ts;
tx0=0.0; tx1=0.0; ty0=0.0; ty1=0.0; tc=1.0; ts=0.0; i0=-1; i1=-1;
for (e=0,f=0,pc=&cl0[e];e<cl0.num;e++,pc++) if (pc->iy>=0) // find 2 clusters with match
{
if (f==0) i0=e;
if (f==1) { i1=e; break; }
f++;
}
if (i1>=0)
{
pc=&cl0[i0]; // translation and offset from xy0 set
pd=&cl0[i1];
tx1=pc->x;
ty1=pc->y;
a =atanxy(pd->x-pc->x,pd->y-pc->y);
pc=&cl1[pc->iy]; // translation and offset from xy1 set
pd=&cl1[pd->iy];
tx0=pc->x;
ty0=pc->y;
a-=atanxy(pd->x-pc->x,pd->y-pc->y);
tc=cos(a);
ts=sin(a);
}
// transform xy1 -> txy1 (in xy0 coordinate system)
for (i1=0;i1<n1;i1++)
{
x=xy1[i1][0]-tx0;
y=xy1[i1][1]-ty0;
txy1[i1][0]=x*tc-y*ts+tx1;
txy1[i1][1]=x*ts+y*tc+ty1;
}
// sort txy1[] by x asc (after transfrm)
for (e=1;e;) for (e=0,i0=0,i1=1;i1<n1;i0++,i1++)
if (txy1[i0][0]>txy1[i1][0])
{
e= ix1[i0] ; ix1[i0] = ix1[i1] ; ix1[i1] =e; e=1;
a=txy1[i0][0]; txy1[i0][0]=txy1[i1][0]; txy1[i1][0]=a;
a=txy1[i0][1]; txy1[i0][1]=txy1[i1][1]; txy1[i1][1]=a;
}
// find match between xy0,txy1 (this can be speeded up by exploiting sorted order)
int ix01[n0],ix10[n1];
for (i0=0;i0<n0;i0++) ix01[i0]=-1;
for (i1=0;i1<n1;i1++) ix10[i1]=-1;
for (i0=0;i0<n0;i0++){ a=-1.0;
for (i1=0;i1<n1;i1++)
{
x=xy0[i0][0]-txy1[i1][0]; x*=x;
y=xy0[i0][1]-txy1[i1][1]; y*=y; x+=y;
if (x<max_errr)
if ((a<0.0)||(a>x)) { a=x; ix01[i0]=i1; ix10[i1]=i0; }
}}
// find the closest stars from unmatched stars
a=-1.0; wi0=-1; wi1=-1;
for (i0=0;i0<n0;i0++) if (ix01[i0]<0)
for (i1=0;i1<n1;i1++) if (ix10[i1]<0)
{
x=xy0[i0][0]-txy1[i1][0]; x*=x;
y=xy0[i0][1]-txy1[i1][1]; y*=y; x+=y;
if ((wi0<0)||(a>x)) { a=x; wi0=i0; wi1=i1; }
}
}
//---------------------------------------------------------------------------
void draw()
{
bmp->Canvas->Font->Charset=OEM_CHARSET;
bmp->Canvas->Font->Name="System";
bmp->Canvas->Font->Pitch=fpFixed;
bmp->Canvas->Font->Color=0x00FFFF00;
bmp->Canvas->Brush->Color=0x00000000;
bmp->Canvas->FillRect(TRect(0,0,xs,ys));
_cluster *pc;
int i,x0,y0,x1,y1,x2,y2,xx,yy,r,_r=4;
double x,y,m;
x0=xs/6; x1=3*x0; x2=5*x0;
y0=ys/2; y1= y0; y2= y0;
x=x0/60.0; y=y0/60.0; if (x<y) m=x; else m=y;
// clusters match
bmp->Canvas->Pen ->Color=clAqua;
bmp->Canvas->Brush->Color=0x00303030;
for (i=0,pc=&cl0[i];i<cl0.num;i++,pc++)
if (pc->iy>=0)
{
x=pc->x*m; xx=x0+x;
y=pc->y*m; yy=y0-y;
bmp->Canvas->MoveTo(xx,yy);
x=cl1[pc->iy].x*m; xx=x1+x;
y=cl1[pc->iy].y*m; yy=y1-y;
bmp->Canvas->LineTo(xx,yy);
}
// clusters area
for (i=0,pc=&cl0[i];i<cl0.num;i++,pc++)
{
x=pc->x*m; xx=x0+x;
y=pc->y*m; yy=y0-y;
r=pc->d[pc->d.num-1]*m*0.5+_r;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
bmp->Canvas->TextOutA(xx+r,yy+r,AnsiString().sprintf("%.3lf",pc->err));
}
for (i=0,pc=&cl1[i];i<cl1.num;i++,pc++)
{
x=pc->x*m; xx=x1+x;
y=pc->y*m; yy=y1-y;
r=pc->d[pc->d.num-1]*m*0.5+_r;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
bmp->Canvas->TextOutA(xx+r,yy+r,AnsiString().sprintf("%.3lf",pc->err));
}
// stars
r=_r;
bmp->Canvas->Pen ->Color=clAqua;
bmp->Canvas->Brush->Color=clBlue;
for (i=0;i<n0;i++)
{
x=xy0[i][0]*m; xx=x0+x;
y=xy0[i][1]*m; yy=y0-y;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
}
for (i=0;i<n1;i++)
{
x=xy1[i][0]*m; xx=x1+x;
y=xy1[i][1]*m; yy=y1-y;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
}
// merged sets
r=_r;
bmp->Canvas->Pen ->Color=clBlue;
bmp->Canvas->Brush->Color=clBlue;
for (i=0;i<n0;i++)
{
x=xy0[i][0]*m; xx=x2+x;
y=xy0[i][1]*m; yy=y2-y;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
}
r=_r-2;
bmp->Canvas->Pen ->Color=clGreen;
bmp->Canvas->Brush->Color=clGreen;
for (i=0;i<n1;i++)
{
x=txy1[i][0]*m; xx=x2+x;
y=txy1[i][1]*m; yy=y2-y;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
}
// wandering star
r=_r+5;
bmp->Canvas->Pen ->Color=0x00FF8000;
bmp->Canvas->Font ->Color=0x00FF8000;
bmp->Canvas->Brush->Style=bsClear;
x=xy0[wi0][0]*m; xx=x2+x;
y=xy0[wi0][1]*m; yy=y2-y;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
bmp->Canvas->TextOutA(xx+r,yy+r,ix0[wi0]);
bmp->Canvas->Pen ->Color=0x0040FF40;
bmp->Canvas->Font ->Color=0x0040FF40;
x=txy1[wi1][0]*m; xx=x2+x;
y=txy1[wi1][1]*m; yy=y2-y;
bmp->Canvas->Ellipse(xx-r,yy-r,xx+r,yy+r);
bmp->Canvas->TextOutA(xx+r,yy+r,ix1[wi1]);
bmp->Canvas->Brush->Style=bsSolid;
Form1->Canvas->Draw(0,0,bmp);
}
//---------------------------------------------------------------------------
X 10 20 30 40
matches \ / \
Y 11 18 41 50
cost 1 4 20 1 20 Total cost: 46
X 10 20 30 40
matches | | | |
Y 11 18 41 50
cost 1 4 121 100 Total cost: 226