Mathematically producing sphere-shaped hexagonal grid - algorithm

I am trying to create a shape similar to this, hexagons with 12 pentagons, at an arbitrary size.
(Image Source)
The only thing is, I have absolutely no idea what kind of code would be needed to generate it!
The goal is to be able to take a point in 3D space and convert it to a position coordinate on the grid, or vice versa and take a grid position and get the relevant vertices for drawing the mesh.
I don't even know how one would store the grid positions for this. Does each "triagle section" between 3 pentagons get their own set of 2D coordinates?
I will most likely be using C# for this, but I am more interested in which algorithms to use for this and an explanation of how they would work, rather than someone just giving me a piece of code.

The shape you have is one of so called "Goldberg polyhedra", is also a geodesic polyhedra.
The (rather elegant) algorithm to generate this (and many many more) can be succinctly encoded in something called a Conway Polyhedron Notation.
The construction is easy to follow step by step, you can click the images below to get a live preview.
The polyhedron you are looking for can be generated from an icosahedron -- Initialise a mesh with an icosahedron.
We apply a "Truncate" operation (Conway notation t) to the mesh (the sperical mapping of this one is a football).
We apply the "Dual" operator (Conway notation d).
We apply a "Truncate" operation again. At this point the recipe is tdtI (read from right!). You can already see where this is going.
Apply steps 3 & 4 repeatedly until you are satisfied.
For example below is the mesh for dtdtdtdtI.
This is quite easy to implement. I would suggest using a datastructure that makes it easy to traverse the neighbourhood give a vertex, edge etc. such as winged-edge or half-edge datastructures for your mesh. You only need to implement truncate and dual operators for the shape you are looking for.

First some analysis of the image in the question: the spherical triangle spanned by neighbouring pentagon centers seems to be equilateral. When five equilateral triangles meet in one corner and cover the whole sphere, this can only be the configuration induced by a icosahedron. So there are 12 pentagons and 20 patches of a triangular cutout of a hexongal mesh mapped to the sphere.
So this is a way to construct such a hexagonal grid on the sphere:
Create triangular cutout of hexagonal grid: a fixed triangle (I chose (-0.5,0),(0.5,0),(0,sqrt(3)/2) ) gets superimposed a hexagonal grid with desired resolution n s.t. the triangle corners coincide with hexagon centers, see the examples for n = 0,1,2,20:
Compute corners of icosahedron and define the 20 triangular faces of it (see code below). The corners of the icosahedron define the centers of the pentagons, the faces of the icosahedron define the patches of the mapped hexagonal grids. (The icosahedron gives the finest regular division of the sphere surface into triangles, i.e. a division into congruent equilateral triangles. Other such divisions can be derived from a tetrahedron or an octahedron; then at the corners of the triangles one will have triangles or squares, resp. Furthermore the fewer and bigger triangles would make the inevitable distortion in any mapping of a planar mesh onto a curved surface more visible. So choosing the icosahedron as a basis for the triangular patches helps minimizing the distortion of the hexagons.)
Map triangular cutout of hexagonal grid to spherical triangles corresponding to icosaeder faces: a double-slerp based on barycentric coordinates does the trick. Below is an illustration of the mapping of a triangular cutout of a hexagonal grid with resolution n = 10 onto one spherical triangle (defined by one face of an icosaeder), and an illustration of mapping the grid onto all these spherical triangles covering the whole sphere (different colors for different mappings):
Here is Python code to generate the corners (coordinates) and triangles (point indices) of an icosahedron:
from math import sin,cos,acos,sqrt,pi
s,c = 2/sqrt(5),1/sqrt(5)
topPoints = [(0,0,1)] + [(s*cos(i*2*pi/5.), s*sin(i*2*pi/5.), c) for i in range(5)]
bottomPoints = [(-x,y,-z) for (x,y,z) in topPoints]
icoPoints = topPoints + bottomPoints
icoTriangs = [(0,i+1,(i+1)%5+1) for i in range(5)] +\
[(6,i+7,(i+1)%5+7) for i in range(5)] +\
[(i+1,(i+1)%5+1,(7-i)%5+7) for i in range(5)] +\
[(i+1,(7-i)%5+7,(8-i)%5+7) for i in range(5)]
And here is the Python code to map (points of) the fixed triangle to a spherical triangle using a double slerp:
# barycentric coords for triangle (-0.5,0),(0.5,0),(0,sqrt(3)/2)
def barycentricCoords(p):
x,y = p
# l3*sqrt(3)/2 = y
l3 = y*2./sqrt(3.)
# l1 + l2 + l3 = 1
# 0.5*(l2 - l1) = x
l2 = x + 0.5*(1 - l3)
l1 = 1 - l2 - l3
return l1,l2,l3
from math import atan2
def scalProd(p1,p2):
return sum([p1[i]*p2[i] for i in range(len(p1))])
# uniform interpolation of arc defined by p0, p1 (around origin)
# t=0 -> p0, t=1 -> p1
def slerp(p0,p1,t):
assert abs(scalProd(p0,p0) - scalProd(p1,p1)) < 1e-7
ang0Cos = scalProd(p0,p1)/scalProd(p0,p0)
ang0Sin = sqrt(1 - ang0Cos*ang0Cos)
ang0 = atan2(ang0Sin,ang0Cos)
l0 = sin((1-t)*ang0)
l1 = sin(t *ang0)
return tuple([(l0*p0[i] + l1*p1[i])/ang0Sin for i in range(len(p0))])
# map 2D point p to spherical triangle s1,s2,s3 (3D vectors of equal length)
def mapGridpoint2Sphere(p,s1,s2,s3):
l1,l2,l3 = barycentricCoords(p)
if abs(l3-1) < 1e-10: return s3
l2s = l2/(l1+l2)
p12 = slerp(s1,s2,l2s)
return slerp(p12,s3,l3)

[Complete re-edit 18.10.2017]
the geometry storage is on you. Either you store it in some kind of Mesh or you generate it on the fly. I prefer to store it. In form of 2 tables. One holding all the vertexes (no duplicates) and the other holding 6 indexes of used points per each hex you got and some aditional info like spherical position to ease up the post processing.
Now how to generate this:
create hex triangle
the size should be radius of your sphere. do not include the corner hexess and also skip last line of the triangle (on both radial and axial so there is 1 hex gap between neighbor triangles on sphere) as that would overlap when joining out triangle segments.
convert 60deg hexagon triangle to 72deg pie
so simply convert to polar coordiantes (radius,angle), center triangle around 0 deg. Then multiply radius by cos(angle)/cos(30); which will convert triangle into Pie. And then rescale angle with ratio 72/60. That will make our triangle joinable...
copy&rotate triangle to fill 5 segments of pentagon
easy just rotate the points of first triangle and store as new one.
compute z
based on this Hexagonal tilling of hemi-sphere you can convert distance in 2D map into arc-length to limit the distortions as much a s possible.
However when I tried it (example below) the hexagons are a bit distorted so the depth and scaling needs some tweaking. Or post processing latter.
copy the half sphere to form a sphere
simply copy the points/hexes and negate z axis (or rotate by 180 deg if you want to preserve winding).
add equator and all of the missing pentagons and hexes
You should use the coordinates of the neighboring hexes so no more distortion and overlaps are added to the grid. Here preview:
Blue is starting triangle. Darker blue are its copies. Red are pole pentagons. Dark green is the equator, Lighter green are the join lines between triangles. In Yellowish are the missing equator hexagons near Dark Orange pentagons.
Here simple C++ OpenGL example (made from the linked answer in #4):
//$$---- Form CPP ----
//---------------------------------------------------------------------------
#include <vcl.h>
#include <math.h>
#pragma hdrstop
#include "win_main.h"
#include "gl/OpenGL3D_double.cpp"
#include "PolyLine.h"
//---------------------------------------------------------------------------
#pragma package(smart_init)
#pragma resource "*.dfm"
TMain *Main;
OpenGLscreen scr;
bool _redraw=true;
double animx= 0.0,danimx=0.0;
double animy= 0.0,danimy=0.0;
//---------------------------------------------------------------------------
PointTab pnt; // (x,y,z)
struct _hexagon
{
int ix[6]; // index of 6 points, last point duplicate for pentagon
int a,b; // spherical coordinate
DWORD col; // color
// inline
_hexagon() {}
_hexagon(_hexagon& a) { *this=a; }
~_hexagon() {}
_hexagon* operator = (const _hexagon *a) { *this=*a; return this; }
//_hexagon* operator = (const _hexagon &a) { ...copy... return this; }
};
List<_hexagon> hex;
//---------------------------------------------------------------------------
// https://stackoverflow.com/a/46787885/2521214
//---------------------------------------------------------------------------
void hex_sphere(int N,double R)
{
const double c=cos(60.0*deg);
const double s=sin(60.0*deg);
const double sy= R/(N+N-2);
const double sz=sy/s;
const double sx=sz*c;
const double sz2=0.5*sz;
const int na=5*(N-2);
const int nb= N;
const int b0= N;
double *q,p[3],ang,len,l,l0,ll;
int i,j,n,a,b,ix;
_hexagon h,*ph;
hex.allocate(na*nb);
hex.num=0;
pnt.reset3D(N*N);
b=0; a=0; ix=0;
// generate triangle hex grid
h.col=0x00804000;
for (b=1;b<N-1;b++) // skip first line b=0
for (a=1;a<b;a++) // skip first and last line
{
p[0]=double(a )*(sx+sz);
p[1]=double(b-(a>>1))*(sy*2.0);
p[2]=0.0;
if (int(a&1)!=0) p[1]-=sy;
ix=pnt.add(p[0]+sz2+sx,p[1] ,p[2]); h.ix[0]=ix; // 2 1
ix=pnt.add(p[0]+sz2 ,p[1]+sy,p[2]); h.ix[1]=ix; // 3 0
ix=pnt.add(p[0]-sz2 ,p[1]+sy,p[2]); h.ix[2]=ix; // 4 5
ix=pnt.add(p[0]-sz2-sx,p[1] ,p[2]); h.ix[3]=ix;
ix=pnt.add(p[0]-sz2 ,p[1]-sy,p[2]); h.ix[4]=ix;
ix=pnt.add(p[0]+sz2 ,p[1]-sy,p[2]); h.ix[5]=ix;
h.a=a;
h.b=N-1-b;
hex.add(h);
} n=hex.num; // remember number of hexs for the first triangle
// distort points to match area
for (ix=0;ix<pnt.nn;ix+=3)
{
// point pointer
q=pnt.pnt.dat+ix;
// convert to polar coordinates
ang=atan2(q[1],q[0]);
len=vector_len(q);
// match area of pentagon (72deg) triangle as we got hexagon (60deg) triangle
ang-=60.0*deg; // rotate so center of generated triangle is angle 0deg
while (ang>+60.0*deg) ang-=pi2;
while (ang<-60.0*deg) ang+=pi2;
len*=cos(ang)/cos(30.0*deg); // scale radius so triangle converts to pie
ang*=72.0/60.0; // scale up angle so rotated triangles merge
// convert back to cartesian
q[0]=len*cos(ang);
q[1]=len*sin(ang);
}
// copy and rotate the triangle to cover pentagon
h.col=0x00404000;
for (ang=72.0*deg,a=1;a<5;a++,ang+=72.0*deg)
for (ph=hex.dat,i=0;i<n;i++,ph++)
{
for (j=0;j<6;j++)
{
vector_copy(p,pnt.pnt.dat+ph->ix[j]);
rotate2d(-ang,p[0],p[1]);
h.ix[j]=pnt.add(p[0],p[1],p[2]);
}
h.a=ph->a+(a*(N-2));
h.b=ph->b;
hex.add(h);
}
// compute z
for (q=pnt.pnt.dat,ix=0;ix<pnt.nn;ix+=pnt.dn,q+=pnt.dn)
{
q[2]=0.0;
ang=vector_len(q)*0.5*pi/R;
q[2]=R*cos(ang);
ll=fabs(R*sin(ang)/sqrt((q[0]*q[0])+(q[1]*q[1])));
q[0]*=ll;
q[1]*=ll;
}
// copy and mirror the other half-sphere
n=hex.num;
for (ph=hex.dat,i=0;i<n;i++,ph++)
{
for (j=0;j<6;j++)
{
vector_copy(p,pnt.pnt.dat+ph->ix[j]);
p[2]=-p[2];
h.ix[j]=pnt.add(p[0],p[1],p[2]);
}
h.a= ph->a;
h.b=-ph->b;
hex.add(h);
}
// create index search table
int i0,i1,j0,j1,a0,a1,ii[5];
int **ab=new int*[na];
for (a=0;a<na;a++)
{
ab[a]=new int[nb+nb+1];
for (b=-nb;b<=nb;b++) ab[a][b0+b]=-1;
}
n=hex.num;
for (ph=hex.dat,i=0;i<n;i++,ph++) ab[ph->a][b0+ph->b]=i;
// add join ring
h.col=0x00408000;
for (a=0;a<na;a++)
{
h.a=a;
h.b=0;
a0=a;
a1=a+1; if (a1>=na) a1-=na;
i0=ab[a0][b0+1];
i1=ab[a1][b0+1];
j0=ab[a0][b0-1];
j1=ab[a1][b0-1];
if ((i0>=0)&&(i1>=0))
if ((j0>=0)&&(j1>=0))
{
h.ix[0]=hex[i1].ix[1];
h.ix[1]=hex[i0].ix[0];
h.ix[2]=hex[i0].ix[1];
h.ix[3]=hex[j0].ix[1];
h.ix[4]=hex[j0].ix[0];
h.ix[5]=hex[j1].ix[1];
hex.add(h);
ab[h.a][b0+h.b]=hex.num-1;
}
}
// add 2x5 join lines
h.col=0x00008040;
for (a=0;a<na;a+=N-2)
for (b=1;b<N-3;b++)
{
// +b hemisphere
h.a= a;
h.b=+b;
a0=a-b; if (a0< 0) a0+=na; i0=ab[a0][b0+b+0];
a0--; if (a0< 0) a0+=na; i1=ab[a0][b0+b+1];
a1=a+1; if (a1>=na) a1-=na; j0=ab[a1][b0+b+0];
j1=ab[a1][b0+b+1];
if ((i0>=0)&&(i1>=0))
if ((j0>=0)&&(j1>=0))
{
h.ix[0]=hex[i0].ix[5];
h.ix[1]=hex[i0].ix[4];
h.ix[2]=hex[i1].ix[5];
h.ix[3]=hex[j1].ix[3];
h.ix[4]=hex[j0].ix[4];
h.ix[5]=hex[j0].ix[3];
hex.add(h);
}
// -b hemisphere
h.a= a;
h.b=-b;
a0=a-b; if (a0< 0) a0+=na; i0=ab[a0][b0-b+0];
a0--; if (a0< 0) a0+=na; i1=ab[a0][b0-b-1];
a1=a+1; if (a1>=na) a1-=na; j0=ab[a1][b0-b+0];
j1=ab[a1][b0-b-1];
if ((i0>=0)&&(i1>=0))
if ((j0>=0)&&(j1>=0))
{
h.ix[0]=hex[i0].ix[5];
h.ix[1]=hex[i0].ix[4];
h.ix[2]=hex[i1].ix[5];
h.ix[3]=hex[j1].ix[3];
h.ix[4]=hex[j0].ix[4];
h.ix[5]=hex[j0].ix[3];
hex.add(h);
}
}
// add pentagons at poles
_hexagon h0,h1;
h0.col=0x00000080;
h0.a=0; h0.b=N-1; h1=h0; h1.b=-h1.b;
p[2]=sqrt((R*R)-(sz*sz));
for (ang=0.0,a=0;a<5;a++,ang+=72.0*deg)
{
p[0]=2.0*sz*cos(ang);
p[1]=2.0*sz*sin(ang);
h0.ix[a]=pnt.add(p[0],p[1],+p[2]);
h1.ix[a]=pnt.add(p[0],p[1],-p[2]);
}
h0.ix[5]=h0.ix[4]; hex.add(h0);
h1.ix[5]=h1.ix[4]; hex.add(h1);
// add 5 missing hexagons at poles
h.col=0x00600060;
for (ph=&h0,b=N-3,h.b=N-2,i=0;i<2;i++,b=-b,ph=&h1,h.b=-h.b)
{
a = 1; if (a>=na) a-=na; ii[0]=ab[a][b0+b];
a+=N-2; if (a>=na) a-=na; ii[1]=ab[a][b0+b];
a+=N-2; if (a>=na) a-=na; ii[2]=ab[a][b0+b];
a+=N-2; if (a>=na) a-=na; ii[3]=ab[a][b0+b];
a+=N-2; if (a>=na) a-=na; ii[4]=ab[a][b0+b];
for (j=0;j<5;j++)
{
h.a=((4+j)%5)*(N-2)+1;
h.ix[0]=ph->ix[ (5-j)%5 ];
h.ix[1]=ph->ix[ (6-j)%5 ];
h.ix[2]=hex[ii[(j+4)%5]].ix[4];
h.ix[3]=hex[ii[(j+4)%5]].ix[5];
h.ix[4]=hex[ii[ j ]].ix[3];
h.ix[5]=hex[ii[ j ]].ix[4];
hex.add(h);
}
}
// add 2*5 pentagons and 2*5 missing hexagons at equator
h0.a=0; h0.b=N-1; h1=h0; h1.b=-h1.b;
for (ang=36.0*deg,a=0;a<na;a+=N-2,ang-=72.0*deg)
{
p[0]=R*cos(ang);
p[1]=R*sin(ang);
p[2]=sz;
i0=pnt.add(p[0],p[1],+p[2]);
i1=pnt.add(p[0],p[1],-p[2]);
a0=a-1;if (a0< 0) a0+=na;
a1=a+1;if (a1>=na) a1-=na;
ii[0]=ab[a0][b0-1]; ii[2]=ab[a1][b0-1];
ii[1]=ab[a0][b0+1]; ii[3]=ab[a1][b0+1];
// hexagons
h.col=0x00008080;
h.a=a; h.b=0;
h.ix[0]=hex[ii[0]].ix[0];
h.ix[1]=hex[ii[0]].ix[1];
h.ix[2]=hex[ii[1]].ix[1];
h.ix[3]=hex[ii[1]].ix[0];
h.ix[4]=i0;
h.ix[5]=i1;
hex.add(h);
h.a=a; h.b=0;
h.ix[0]=hex[ii[2]].ix[2];
h.ix[1]=hex[ii[2]].ix[1];
h.ix[2]=hex[ii[3]].ix[1];
h.ix[3]=hex[ii[3]].ix[2];
h.ix[4]=i0;
h.ix[5]=i1;
hex.add(h);
// pentagons
h.col=0x000040A0;
h.a=a; h.b=0;
h.ix[0]=hex[ii[0]].ix[0];
h.ix[1]=hex[ii[0]].ix[5];
h.ix[2]=hex[ii[2]].ix[3];
h.ix[3]=hex[ii[2]].ix[2];
h.ix[4]=i1;
h.ix[5]=i1;
hex.add(h);
h.a=a; h.b=0;
h.ix[0]=hex[ii[1]].ix[0];
h.ix[1]=hex[ii[1]].ix[5];
h.ix[2]=hex[ii[3]].ix[3];
h.ix[3]=hex[ii[3]].ix[2];
h.ix[4]=i0;
h.ix[5]=i0;
hex.add(h);
}
// release index search table
for (a=0;a<na;a++) delete[] ab[a];
delete[] ab;
}
//---------------------------------------------------------------------------
void hex_draw(GLuint style) // draw hex
{
int i,j;
_hexagon *h;
for (h=hex.dat,i=0;i<hex.num;i++,h++)
{
if (style==GL_POLYGON) glColor4ubv((BYTE*)&h->col);
glBegin(style);
for (j=0;j<6;j++) glVertex3dv(pnt.pnt.dat+h->ix[j]);
glEnd();
}
if (0)
if (style==GL_POLYGON)
{
scr.text_init_pixel(0.1,-0.2);
glColor3f(1.0,1.0,1.0);
for (h=hex.dat,i=0;i<hex.num;i++,h++)
if (abs(h->b)<2)
{
double p[3];
vector_ld(p,0.0,0.0,0.0);
for (j=0;j<6;j++)
vector_add(p,p,pnt.pnt.dat+h->ix[j]);
vector_mul(p,p,1.0/6.0);
scr.text(p[0],p[1],p[2],AnsiString().sprintf("%i,%i",h->a,h->b));
}
scr.text_exit_pixel();
}
}
//---------------------------------------------------------------------------
void TMain::draw()
{
scr.cls();
int x,y;
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
glTranslatef(0.0,0.0,-5.0);
glRotated(animx,1.0,0.0,0.0);
glRotated(animy,0.0,1.0,0.0);
hex_draw(GL_POLYGON);
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
glTranslatef(0.0,0.0,-5.0+0.01);
glRotated(animx,1.0,0.0,0.0);
glRotated(animy,0.0,1.0,0.0);
glColor3f(1.0,1.0,1.0);
glLineWidth(2);
hex_draw(GL_LINE_LOOP);
glCirclexy(0.0,0.0,0.0,1.5);
glLineWidth(1);
scr.exe();
scr.rfs();
}
//---------------------------------------------------------------------------
__fastcall TMain::TMain(TComponent* Owner) : TForm(Owner)
{
scr.init(this);
hex_sphere(10,1.5);
_redraw=true;
}
//---------------------------------------------------------------------------
void __fastcall TMain::FormDestroy(TObject *Sender)
{
scr.exit();
}
//---------------------------------------------------------------------------
void __fastcall TMain::FormPaint(TObject *Sender)
{
_redraw=true;
}
//---------------------------------------------------------------------------
void __fastcall TMain::FormResize(TObject *Sender)
{
scr.resize();
glMatrixMode(GL_PROJECTION);
glLoadIdentity();
gluPerspective(60,float(scr.xs)/float(scr.ys),0.1,100.0);
_redraw=true;
}
//-----------------------------------------------------------------------
void __fastcall TMain::Timer1Timer(TObject *Sender)
{
animx+=danimx; if (animx>=360.0) animx-=360.0; _redraw=true;
animy+=danimy; if (animy>=360.0) animy-=360.0; _redraw=true;
if (_redraw) { draw(); _redraw=false; }
}
//---------------------------------------------------------------------------
void __fastcall TMain::FormKeyDown(TObject *Sender, WORD &Key, TShiftState Shift)
{
Caption=Key;
if (Key==40){ animx+=2.0; _redraw=true; }
if (Key==38){ animx-=2.0; _redraw=true; }
if (Key==39){ animy+=2.0; _redraw=true; }
if (Key==37){ animy-=2.0; _redraw=true; }
}
//---------------------------------------------------------------------------
I know it is a bit of a index mess and also winding rule is not guaranteed as I was too lazy to made uniform indexing. Beware the a indexes of each hex are not linear and if you want to use them to map to 2D map you would need to recompute it using atan2 on x,y of its center point position.
Here previews:
Still some distortions are present. They are caused by fact that we using 5 triangles to connect at equator (so connection is guaranteed). That means the circumference is 5*R instead of 6.28*R. How ever this can be still improved by a field simulation. Just take all the points and add retractive forces based on their distance and bound to sphere surface. Run simulation and when the oscillations lower below threshold you got your sphere grid ...
Another option would be find out some equation to remap the grid points (similarly what I done for triangle to pie conversion) that would have better results.

Related

Algorithm for connecting points in a graph with curved lines

I need to develop an algorithm that connects points in a non-linear way, that is, with smooth curves, as in the image below:
The problem is that I can not find the best solution, either using Bezier Curves, Polimonial Interpolation, Curve Adjustment, among others.
In short, I need a formula that interpolates the points according to the figure above, generating N intermediate points between one coordinate and another.
In the image above, the first coordinate (c1) is (x = 1, y = 220) and the second (c2) is (x = 2, y = 40).
So if I want to create for example 4 intermediate coordinates between c1 and c2 I will have to get an array (x, y) of 4 elements something like this:
    
[1.2, 180], [1.4, 140], [1.6, 120], [1.8, 80]
Would anyone have any ideas?
I think any Piecewise curve interpolation should do it. Here small C++ example:
//---------------------------------------------------------------------------
const int n=7; // points
const int n2=n+n;
float pnt[n2]= // points x,y ...
{
1.0, 220.0,
2.0, 40.0,
3.0,-130.0,
4.0,-170.0,
5.0,- 40.0,
6.0, 90.0,
7.0, 110.0,
};
//---------------------------------------------------------------------------
void getpnt(float *p,float t) // t = <0,n-1>
{
int i,ii;
float *p0,*p1,*p2,*p3,a0,a1,a2,a3,d1,d2,tt,ttt;
// handle t out of range
if (t<= 0.0f){ p[0]=pnt[0]; p[1]=pnt[1]; return; }
if (t>=float(n-1)){ p[0]=pnt[n2-2]; p[1]=pnt[n2-1]; return; }
// select patch
i=floor(t); // start point of patch
t-=i; // parameter <0,1>
i<<=1; tt=t*t; ttt=tt*t;
// control points
ii=i-2; if (ii<0) ii=0; if (ii>=n2) ii=n2-2; p0=pnt+ii;
ii=i ; if (ii<0) ii=0; if (ii>=n2) ii=n2-2; p1=pnt+ii;
ii=i+2; if (ii<0) ii=0; if (ii>=n2) ii=n2-2; p2=pnt+ii;
ii=i+4; if (ii<0) ii=0; if (ii>=n2) ii=n2-2; p3=pnt+ii;
// loop all dimensions
for (i=0;i<2;i++)
{
// compute polynomial coeficients
d1=0.5*(p2[i]-p0[i]);
d2=0.5*(p3[i]-p1[i]);
a0=p1[i];
a1=d1;
a2=(3.0*(p2[i]-p1[i]))-(2.0*d1)-d2;
a3=d1+d2+(2.0*(-p2[i]+p1[i]));
// compute point coordinate
p[i]=a0+(a1*t)+(a2*tt)+(a3*ttt);
}
}
//---------------------------------------------------------------------------
void gl_draw()
{
glClearColor(1.0,1.0,1.0,1.0);
glClear(GL_COLOR_BUFFER_BIT);
glDisable(GL_DEPTH_TEST);
glDisable(GL_TEXTURE_2D);
// set 2D view
glMatrixMode(GL_PROJECTION);
glLoadIdentity();
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
glScalef(1.0/5.0,1.0/500.0,1.0);
glTranslatef(-4.0,0.0,0.0);
// render lines
glColor3f(1.0,0.0,0.0);
glBegin(GL_LINE_STRIP);
float p[2],t;
for (t=0.0;t<=float(n-1);t+=0.1f)
{
getpnt(p,t);
glVertex2fv(p);
}
glEnd();
// render points
glPointSize(4.0);
glColor3f(0.0,0.0,1.0);
glBegin(GL_POINTS);
for (int i=0;i<n2;i+=2) glVertex2fv(pnt+i);
glEnd();
glPointSize(1.0);
glFinish();
SwapBuffers(hdc);
}
//---------------------------------------------------------------------------
Here preview:
As you can see it is simple you just need n control points pnt (I extracted from your graph) and just interpolate ... The getpnt functions will compute any point on the curve addressed by parameter t=<0,n-1>. Internally it just select which cubic patch to use and compute as single cubic curve. In gl_draw you can see how to use it to obtain the points in between.
As your control points are uniformly distributed on the x axis:
x = <1,7>
t = <0,6>
I can write:
x = t+1
t = x-1
so you can compute any point for any x too...
The shape does not match your graph perfectly because the selected control points are not the correct ones. Any local minimum/maximum should be a control point and sometimes is safer to use also inflex points too. The starting and ending shape of the curve suggest hidden starting and ending control point which is not showed on the graph. You can use any number of points you need but beware if you break the x uniform distribution then you lose the ability to compute t from x directly!
As we do not know how the graph was created we can only guess ...

Basic space carving algorithm

I have the following problem as shown in the figure. I have point cloud and a mesh generated by a tetrahedral algorithm. How would I carve the mesh using the that algorithm ? Are landmarks are the point cloud ?
Pseudo code of the algorithm:
for every 3D feature point
convert it 2D projected coordinates
for every 2D feature point
cast a ray toward the polygons of the mesh
get intersection point
if zintersection < z of 3D feature point
for ( every triangle vertices )
cull that triangle.
Here is a follow up implementation of the algorithm mentioned by the Guru Spektre :)
Update code for the algorithm:
int i;
for (i = 0; i < out.numberofpoints; i++)
{
Ogre::Vector3 ray_pos = pos; // camera position);
Ogre::Vector3 ray_dir = (Ogre::Vector3 (out.pointlist[(i*3)], out.pointlist[(3*i)+1], out.pointlist[(3*i)+2]) - pos).normalisedCopy(); // vertex - camea pos ;
Ogre::Ray ray;
ray.setOrigin(Ogre::Vector3( ray_pos.x, ray_pos.y, ray_pos.z));
ray.setDirection(Ogre::Vector3(ray_dir.x, ray_dir.y, ray_dir.z));
Ogre::Vector3 result;
unsigned int u1;
unsigned int u2;
unsigned int u3;
bool rayCastResult = RaycastFromPoint(ray.getOrigin(), ray.getDirection(), result, u1, u2, u3);
if ( rayCastResult )
{
Ogre::Vector3 targetVertex(out.pointlist[(i*3)], out.pointlist[(3*i)+1], out.pointlist[(3*i)+2]);
float distanceTargetFocus = targetVertex.squaredDistance(pos);
float distanceIntersectionFocus = result.squaredDistance(pos);
if(abs(distanceTargetFocus) >= abs(distanceIntersectionFocus))
{
if ( u1 != -1 && u2 != -1 && u3 != -1)
{
std::cout << "Remove index "<< "u1 ==> " <<u1 << "u2 ==>"<<u2<<"u3 ==> "<<u3<< std::endl;
updatedIndices.erase(updatedIndices.begin()+ u1);
updatedIndices.erase(updatedIndices.begin()+ u2);
updatedIndices.erase(updatedIndices.begin()+ u3);
}
}
}
}
if ( updatedIndices.size() <= out.numberoftrifaces)
{
std::cout << "current face list===> "<< out.numberoftrifaces << std::endl;
std::cout << "deleted face list===> "<< updatedIndices.size() << std::endl;
manual->begin("Pointcloud", Ogre::RenderOperation::OT_TRIANGLE_LIST);
for (int n = 0; n < out.numberofpoints; n++)
{
Ogre::Vector3 vertexTransformed = Ogre::Vector3( out.pointlist[3*n+0], out.pointlist[3*n+1], out.pointlist[3*n+2]) - mReferencePoint;
vertexTransformed *=1000.0 ;
vertexTransformed = mDeltaYaw * vertexTransformed;
manual->position(vertexTransformed);
}
for (int n = 0 ; n < updatedIndices.size(); n++)
{
int n0 = updatedIndices[n+0];
int n1 = updatedIndices[n+1];
int n2 = updatedIndices[n+2];
if ( n0 < 0 || n1 <0 || n2 <0 )
{
std::cout<<"negative indices"<<std::endl;
break;
}
manual->triangle(n0, n1, n2);
}
manual->end();
Follow up with the algorithm:
I have now two versions one is the triangulated one and the other is the carved version.
It's not not a surface mesh.
Here are the two files
http://www.mediafire.com/file/cczw49ja257mnzr/ahmed_non_triangulated.obj
http://www.mediafire.com/file/cczw49ja257mnzr/ahmed_triangulated.obj
I see it like this:
So you got image from camera with known matrix and FOV and focal length.
From that you know where exactly the focal point is and where the image is proected onto the camera chip (Z_near plane). So any vertex, its corresponding pixel and focal point lies on the same line.
So for each view cas ray from focal point to each visible vertex of the pointcloud. and test if any face of the mesh hits before hitting face containing target vertex. If yes remove it as it would block the visibility.
Landmark in this context is just feature point corresponding to vertex from pointcloud. It can be anything detectable (change of intensity, color, pattern whatever) usually SIFT/SURF is used for this. You should have them located already as that is the input for pointcloud generation. If not you can peek pixel corresponding to each vertex and test for background color.
Not sure how you want to do this without the input images. For that you need to decide which vertex is visible from which side/view. May be it is doable form nearby vertexes somehow (like using vertex density points or corespondence to planar face...) or the algo is changed somehow for finding unused vertexes inside mesh.
To cast a ray do this:
ray_pos=tm_eye*vec4(imgx/aspect,imgy,0.0,1.0);
ray_dir=ray_pos-tm_eye*vec4(0.0,0.0,-focal_length,1.0);
where tm_eye is camera direct transform matrix, imgx,imgy is the 2D pixel position in image normalized to <-1,+1> where (0,0) is the middle of image. The focal_length determines the FOV of camera and aspect ratio is ratio of image resolution image_ys/image_xs
Ray triangle intersection equation can be found here:
Reflection and refraction impossible without recursive ray tracing?
If I extract it:
vec3 v0,v1,v2; // input triangle vertexes
vec3 e1,e2,n,p,q,r;
float t,u,v,det,idet;
//compute ray triangle intersection
e1=v1-v0;
e2=v2-v0;
// Calculate planes normal vector
p=cross(ray[i0].dir,e2);
det=dot(e1,p);
// Ray is parallel to plane
if (abs(det)<1e-8) no intersection;
idet=1.0/det;
r=ray[i0].pos-v0;
u=dot(r,p)*idet;
if ((u<0.0)||(u>1.0)) no intersection;
q=cross(r,e1);
v=dot(ray[i0].dir,q)*idet;
if ((v<0.0)||(u+v>1.0)) no intersection;
t=dot(e2,q)*idet;
if ((t>_zero)&&((t<=tt)) // tt is distance to target vertex
{
// intersection
}
Follow ups:
To move between normalized image (imgx,imgy) and raw image (rawx,rawy) coordinates for image of size (imgxs,imgys) where (0,0) is top left corner and (imgxs-1,imgys-1) is bottom right corner you need:
imgx = (2.0*rawx / (imgxs-1)) - 1.0
imgy = 1.0 - (2.0*rawy / (imgys-1))
rawx = (imgx + 1.0)*(imgxs-1)/2.0
rawy = (1.0 - imgy)*(imgys-1)/2.0
[progress update 1]
I finally got to the point I can compile sample test input data for this to get even started (as you are unable to share valid data at all):
I created small app with hard-coded table mesh (gray) and pointcloud (aqua) and simple camera control. Where I can save any number of views (screenshot + camera direct matrix). When loaded back it aligns with the mesh itself (yellow ray goes through aqua dot in image and goes through the table mesh too). The blue lines are casted from camera focal point to its corners. This will emulate the input you got. The second part of the app will use only these images and matrices with the point cloud (no mesh surface anymore) tetragonize it (already finished) now just cast ray through each landmark in each view (aqua dot) and remove all tetragonals before target vertex in pointcloud is hit (this stuff is not even started yet may be in weekend)... And lastly store only surface triangles (easy just use all triangles which are used just once also already finished except the save part but to write wavefront obj from it is easy ...).
[Progress update 2]
I added landmark detection and matching with the point cloud
as you can see only valid rays are cast (those that are visible on image) so some points on point cloud does not cast rays (singular aqua dots)). So now just the ray/triangle intersection and tetrahedron removal from list is what is missing...

How to Compute OBB of Multiple Curves?

Given a number of curves,include line segments and circular arcs, how to compute the total OBB of all curves?
It seems that the union of each OBB of the individual curves does not right, it's not the minimal coverage.
Check this picture, how to compute the red box?
you should also add the input in vector form so we can test on your data ... I would approach like this:
find center of axis aligned bbox O(n)
compute max distance in each angle O(n)
just create table for enough m angles (like 5 deg step so m = 360/5) where for each angle section you remember max distant point distance only.
compute max perpendicular distance for each rotation O(m^2)
so for each angle section compute value that is:
value[actual_section] = max(distance[i]*cos(section_angle[i]-section_angle[actual_section]))
where i covers +/- 90 deg around actual section angle so now you got max perpendicular distances for each angle...
pick best solution O(m)
so look all rotations from 0 to 90 degrees and remember the one that has minimal OBB area. Just to be sure the OBB is aligned to section angle and size of axises is the value of that angle and all the 90 deg increments... around center
This will not result in optimal solution but very close to it. To improve precision you can use more angle sections or even recursively search around found solution with smaller and smaller angle step (no need to compute the other angle areas after first run.
[Edit1]
I tried to code this in C++ as proof of concept and use your image (handled as set of points) as input so here the result so you got something to compare to (for debugging purposes)
gray are detected points from your image, green rectangle is axis aligned BBox the red rectangle is found OBBox. The aqua points are found max distance per angle interval and green dots are max perpendicular distance for +/-90deg neighbor angle intervals. I used 400 angles and as you can see the result is pretty close ... 360/400 deg accuracy so this approach works well ...
Here C++ source:
//---------------------------------------------------------------------------
struct _pnt2D
{
double x,y;
// inline
_pnt2D() {}
_pnt2D(_pnt2D& a) { *this=a; }
~_pnt2D() {}
_pnt2D* operator = (const _pnt2D *a) { *this=*a; return this; }
//_pnt2D* operator = (const _pnt2D &a) { ...copy... return this; }
};
struct _ang
{
double ang; // center angle of section
double dis; // max distance of ang section
double pdis; // max perpendicular distance of +/-90deg section
// inline
_ang() {}
_ang(_ang& a) { *this=a; }
~_ang() {}
_ang* operator = (const _ang *a) { *this=*a; return this; }
//_ang* operator = (const _ang &a) { ...copy... return this; }
};
const int angs=400; // must be divisible by 4
const int angs4=angs>>2;
const double dang=2.0*M_PI/double(angs);
const double dang2=0.5*dang;
_ang ang[angs];
List<_pnt2D> pnt;
_pnt2D bbox[2],obb[4],center;
//---------------------------------------------------------------------------
void compute_OBB()
{
_pnt2D ppp[4];
int i,j; double a,b,dx,dy;
_ang *aa,*bb;
_pnt2D p,*pp; DWORD *q;
// convert bmp -> pnt[]
pnt.num=0;
Graphics::TBitmap *bmp=new Graphics::TBitmap;
bmp->LoadFromFile("in.bmp");
bmp->HandleType=bmDIB;
bmp->PixelFormat=pf32bit;
for (p.y=0;p.y<bmp->Height;p.y++)
for (q=(DWORD*)bmp->ScanLine[int(p.y)],p.x=0;p.x<bmp->Width;p.x++)
if ((q[int(p.x)]&255)<20)
pnt.add(p);
delete bmp;
// axis aligned bbox
bbox[0]=pnt[0];
bbox[1]=pnt[0];
for (pp=pnt.dat,i=0;i<pnt.num;i++,pp++)
{
if (bbox[0].x>pp->x) bbox[0].x=pp->x;
if (bbox[0].y>pp->y) bbox[0].y=pp->y;
if (bbox[1].x<pp->x) bbox[1].x=pp->x;
if (bbox[1].y<pp->y) bbox[1].y=pp->y;
}
center.x=(bbox[0].x+bbox[1].x)*0.5;
center.y=(bbox[0].y+bbox[1].y)*0.5;
// ang[] table init
for (aa=ang,a=0.0,i=0;i<angs;i++,aa++,a+=dang)
{
aa->ang=a;
aa-> dis=0.0;
aa->pdis=0.0;
}
// ang[].dis
for (pp=pnt.dat,i=0;i<pnt.num;i++,pp++)
{
dx=pp->x-center.x;
dy=pp->y-center.y;
a=atan2(dy,dx);
j=floor((a/dang)+0.5); if (j<0) j+=angs; j%=angs;
a=(dx*dx)+(dy*dy);
if (ang[j].dis<a) ang[j].dis=a;
}
for (aa=ang,i=0;i<angs;i++,aa++) aa->dis=sqrt(aa->dis);
// ang[].adis
for (aa=ang,i=0;i<angs;i++,aa++)
for (bb=ang,j=0;j<angs;j++,bb++)
{
a=fabs(aa->ang-bb->ang);
if (a>M_PI) a=(2.0*M_PI)-a;
if (a<=0.5*M_PI)
{
a=bb->dis*cos(a);
if (aa->pdis<a) aa->pdis=a;
}
}
// find best oriented bbox (the best angle is ang[j].ang)
for (b=0,j=0,i=0;i<angs;i++)
{
dx =ang[i].pdis; i+=angs4; i%=angs;
dy =ang[i].pdis; i+=angs4; i%=angs;
dx+=ang[i].pdis; i+=angs4; i%=angs;
dy+=ang[i].pdis; i+=angs4; i%=angs;
a=dx*dy; if ((b>a)||(i==0)) { b=a; j=i; }
}
// compute endpoints for OBB
i=j;
ppp[0].x=ang[i].pdis*cos(ang[i].ang);
ppp[0].y=ang[i].pdis*sin(ang[i].ang); i+=angs4; i%=angs;
ppp[1].x=ang[i].pdis*cos(ang[i].ang);
ppp[1].y=ang[i].pdis*sin(ang[i].ang); i+=angs4; i%=angs;
ppp[2].x=ang[i].pdis*cos(ang[i].ang);
ppp[2].y=ang[i].pdis*sin(ang[i].ang); i+=angs4; i%=angs;
ppp[3].x=ang[i].pdis*cos(ang[i].ang);
ppp[3].y=ang[i].pdis*sin(ang[i].ang); i+=angs4; i%=angs;
obb[0].x=center.x+ppp[0].x+ppp[3].x;
obb[0].y=center.y+ppp[0].y+ppp[3].y;
obb[1].x=center.x+ppp[1].x+ppp[0].x;
obb[1].y=center.y+ppp[1].y+ppp[0].y;
obb[2].x=center.x+ppp[2].x+ppp[1].x;
obb[2].y=center.y+ppp[2].y+ppp[1].y;
obb[3].x=center.x+ppp[3].x+ppp[2].x;
obb[3].y=center.y+ppp[3].y+ppp[2].y;
}
//---------------------------------------------------------------------------
I used mine dynamic list template so:
List<double> xxx; is the same as double xxx[];
xxx.add(5); adds 5 to end of the list
xxx[7] access array element (safe)
xxx.dat[7] access array element (unsafe but fast direct access)
xxx.num is the actual used size of the array
xxx.reset() clears the array and set xxx.num=0
xxx.allocate(100) preallocate space for 100 items
You can ignore the // convert bmp -> pnt[] VCL part as you got your data already.
I recommend to also take a look at my:
3D OBB approximation

Algorithm: How to disperse smaller spheres into a direction within a large sphere

I am trying to write a C source code visualization program which I expect to draw out function hierarchy using spheres inside spheres.
For a simple example, in code like this:
#include "stdio.h"
int pow(int base, int power) {
while(--power) {
base*=base;
}
return base;
}
int checkOdd(int i) {
if (i%2==0) return 0;
else return 1;
}
int checkPrime(int i) {
int j = i;
if (!checkOdd(i)) {
return 0;
}
for(j=1; j<i/2; j++) {
if (i%j==0) {
return 0;
}
}
return 1;
}
int main() {
int a = 3;
int b = 2;
int res = pow(a,b);
int bl = checkPrime(res);
printf("%d",res);
return 1;
}
The largest sphere which is the main function has two functions inside it, pow and checkPrime, which are two spheres inside main's sphere. Checkprime function's sphere has checkOdd's sphere in it.
I would like it so that the children spheres are somewhat clumped together in one side of the larger sphere, because I would like some space left out for putting in other things. However, the spheres must not touch each other, and the radius of the spheres are pre-determined and can not change to accomodate drawing accurately. I need an algorithm which determines the perfect center coordinates which would allow the smaller spheres not to touch each other while still being collected to one side of the larger sphere.
I have a 3D vector which shows the direction at which the smaller spheres must be concentrated in, looking from the center of the larger sphere. In the case of the picture, my 3D vector is facing bottom-down in a 2D-sense looking at the screen.
Currently my algorithm produces this by dispersing the sphere's center around a circle projected onto the larger sphere's surface, but it fails as the spheres overlap. Can anyone enlighten me with a way to disperse smaller spheres to one direction within the larger sphere?
I am using OpenGL and I prepared a function which can draw those transparent mesh spheres by feeding center coordinate and radius. I have knowledge of parent sphere's center and radius in designing this algorithm.

Algorithm for shape calculation (Ellipse)

I have n circles that must be perfectly surrounding an ellipse as shown in the picture here :
In this picture I need to find out the position of each circle around the ellipse, and also be able to calculate the ellipse that will fit perfectly inside those surrounding circles.
The information i know is the radius of each circles (all same), and the number of circles.
Hopefully this time the post is clear.
Thanks for your help.
Please let me know if you need more explanation.
OK as i understand you know common radius of circles R0 and their number N and want to know inside ellipse parameters and positions of everything.
If we convert ellipse to circle then we get this:
const int N=12; // number of satelite circles
const double R=10.0; // radius of satelite circles
struct _circle { double x,y,r; } circle[N]; // satelite circles
int i;
double x,y,r,l,a,da;
x=0.0; // start pos of first satelite circle
y=0.0;
r=R;
l=r+r; // distance ang angle between satelite circle centers
a=0.0*deg;
da=divide(360.0*deg,N);
for (i=0;i<N;i++)
{
circle[i].x=x; x+=l*cos(a);
circle[i].y=y; y+=l*sin(a);
circle[i].r=r; a+=da;
}
// inside circle params
_circle c;
r=divide(0.5*l,sin(0.5*da))-R;
c.x=circle[i].x;
c.y=circle[i].y+R+r;
c.r=r;
[Edit 1]
For ellipse its a whole new challenge (took me two hours to find all quirks out)
const int N=20; // number of satelite circles
const double R=10.0; // satelite circles radius
const double E= 0.7; // ellipse distortion ry=rx*E
struct _circle { double x,y,r; _circle() { x=0; y=0; r=0.0; } } circle[N];
struct _ellipse { double x,y,rx,ry; _ellipse() { x=0; y=0; rx=0.0; ry=0.0; } } ellipse;
int i,j,k;
double l,a,da,m,dm,x,y,q,r0;
l=double(N)*R; // circle cener lines polygon length
ellipse.x =0.0; // set ellipse parameters
ellipse.y =0.0;
r0=divide(l,M_PI*sqrt(0.5*(1.0+(E*E))))-R;// aprox radius to match ellipse length for start
l=R+R; l*=l;
m=1.0; dm=1.0; x=0.0;
for (k=0;k<5;k++) // aproximate ellipse size to the right size
{
dm=fabs(0.1*dm); // each k-iteration layer is 10x times more accurate
if (x>l) dm=-dm;
for (;;)
{
ellipse.rx=r0 *m;
ellipse.ry=r0*E*m;
for (a=0.0,i=0;i<N;i++) // set circle parameters
{
q=(2.0*a)-atanxy(cos(a),sin(a)*E);
circle[i].x=ellipse.x+(ellipse.rx*cos(a))+(R*cos(q));
circle[i].y=ellipse.y+(ellipse.ry*sin(a))+(R*sin(q));
circle[i].r=R;
da=divide(360*deg,N); a+=da;
for (j=0;j<5;j++) // aproximate next position to match 2R distance from current position
{
da=fabs(0.1*da); // each j-iteration layer is 10x times more accurate
q=(2.0*a)-atanxy(cos(a),sin(a)*E);
x=ellipse.x+(ellipse.rx*cos(a))+(R*cos(q))-circle[i].x; x*=x;
y=ellipse.y+(ellipse.ry*sin(a))+(R*sin(q))-circle[i].y; y*=y; x+=y;
if (x>l) for (;;) // if too far dec angle
{
a-=da;
q=(2.0*a)-atanxy(cos(a),sin(a)*E);
x=ellipse.x+(ellipse.rx*cos(a))+(R*cos(q))-circle[i].x; x*=x;
y=ellipse.y+(ellipse.ry*sin(a))+(R*sin(q))-circle[i].y; y*=y; x+=y;
if (x<=l) break;
}
else if (x<l) for (;;) // if too short inc angle
{
a+=da;
q=(2.0*a)-atanxy(cos(a),sin(a)*E);
x=ellipse.x+(ellipse.rx*cos(a))+(R*cos(q))-circle[i].x; x*=x;
y=ellipse.y+(ellipse.ry*sin(a))+(R*sin(q))-circle[i].y; y*=y; x+=y;
if (x>=l) break;
}
else break;
}
}
// check if last circle is joined as it should be
x=circle[N-1].x-circle[0].x; x*=x;
y=circle[N-1].y-circle[0].y; y*=y; x+=y;
if (dm>0.0) { if (x>=l) break; }
else { if (x<=l) break; }
m+=dm;
}
}
Well I know its a little messy code so here is some info:
first it try to set as close ellipse rx,ry axises as possible
ellipse length should be about N*R*2 which is polygon length of lines between circle centers
try to compose circles so they are touching each other and the ellipse
I use iteration of ellipse angle for that. Problem is that circles do not touch the ellipse in their position angle thats why there is q variable ... to compensate around ellipse normal. Look for yellowish-golden lines in image
after placing circles check if the last one is touching the first
if not interpolate the size of ellipse actually it scales the rx,ry by m variable up or down
you can adjust accuracy
by change of the j,k fors and/or change of dm,da scaling factors
input parameter E should be at least 0.5 and max 1.0
if not then there is high probability of misplacing circles because on very eccentric ellipses is not possible to fit circles (if N is too low). Ideal setting is 0.7<=E<=1.0 closser to 1 the safer the algorithm is
atanxy(dx,dy) is the same as `atan(dy/dx)
but it handles all 4 quadrants like atan2(dy,dx) by sign analysis of dx,dy
Hope it helps

Resources