Yes, I know that it is a popular problem. But I found nowhere the full clear implementing code without using OpenGL classes or a lot of headers files.
Okay, the math solution is to transfer ellipsoid to sphere. Then find intersections dots (if they exist of course) and make inverse transformation. Because affine transformation respect intersection.
But I have difficulties when trying to implement this.
I tried something for sphere but it is completely incorrect.
double CountDelta(Point X, Point Y, Sphere S)
{
double a = 0.0;
for(int i = 0; i < 3; i++){
a += (Y._coordinates[i] - X._coordinates[i]) * (Y._coordinates[i] - X._coordinates[i]);
}
double b = 0.0;
for(int i = 0; i < 3; i++)
b += (Y._coordinates[i] - X._coordinates[i]) * (X._coordinates[i] - S._coordinates[i]);
b *= 2;
double c = - S.r * S.r;
for(int i = 0; i < 3; i++)
c += (X._coordinates[i] - S._coordinates[i]) * (X._coordinates[i] - S._coordinates[i]);
return b * b - 4 * a * c;
}
Let I have start point P = (Px, Py, Pz), direction V = (Vx, Vy, Vz), ellipsoid = (Ex, Ey, Ec) and (a, b, c). How to construct clear code?
Let a line from P to P + D intersecting a sphere of center C and radius R.
WLOG, C can be the origin and R unit (otherwise translate by -C and scale by 1/R). Now using the parametric equation of the line and the implicit equation of the sphere,
(Px + t Dx)² + (Py + t Dy)² + (Pz + t Dz)² = 1
or
(Dx² + Dy² + Dz²) t² + 2 (Dx Px + Dy Py + Dz Pz) t + Px² + Py² + Pz² - 1 = 0
(Vectorially, D² t² + 2 D P t + P² - 1 = 0 and t = (- D P ±√((D P)² - D²(P² - 1))) / D².)
Solve this quadratic equation for t and get the two intersections as P + t D. (Don't forget to invert the initial transformations.)
For the ellipsoid, you can either plug the parametric equation of the line directly into the implicit equation of the conic, or reduce the conic (and the points simultaneously) and plug in the reduced equation.
How can I check if a vector that starts at one point passes through another one point?
It is on two-dimensional coordinates.
Mainly uses c ++, but other languages are possible.
float2 startToTarget = target - start;
if ((startToTarget.x) * vec.y - (startToTarget.y) * vec.x >= -floatingPoint && (startToTarget.x) * vec.y - (startToTarget.y) * vec.x <= floatingPoint)
if ((startToTarget.x) * vec.x + (startToTarget.y) * vec.y >= -floatingPoint && (startToTarget.x) * vec.x + (startToTarget.y) * vec.y <= floatingPoint) intersecting = true;
Calculate cross product of vector d (direction) and AB vector. If result is zero, then these vectors are collinear, so B point lies on the line, defined by point A and direction vector d.
To check direction, evaluate also dot product, it's sign is positive, when direction d coincides with direction AB
abx = B.x - A.x;
aby = B.y - A.y;
//cross product //dot product
if (abs(abx*dy - aby*dx) < 1.0e-10 and abx*dx + aby*dy>0)
{B lies on the ray A+d}
I'm trying to write an algorithm to determine if point is located inside a triangle or on it's edge in 3D coordinate space.
For example, I try to reach such results for different cases
I've figured out how to check if point P inside the triangle, I calculated normal vectors for triangles ABP, BCP, CAP and checked if they are similar.
Can someone explain how to check if a point is on the edge of a triangle (but not outside of a triangle)? You can provide formulas or code as you wish.
Make vectors:
r = p - A (r.x = p.x - A.x, r.y = p.y - A.y, r.z = p.z - A.z)
s = B - A
q = C - A
Calculate normal to ABC plane:
n = s x q (vector product)
Check if p lies in ABC plane using dot product:
dp = n.dot.r
If dp is zero (or has very small value like 1.0e-10 due to the floating point errors, then p is in the plane, and we can continue
Decompose vector p by base vectors s and q. At first check if z-component of normal (n.z) is non-zero. If so, use the next pair of equations (otherwise choose equations for x/z or y/z components):
px = a * sx + b * qx
py = a * sy + b * qy
Solve this system
a = (sy * qx - sx * qy) / (py * qx - px * qy)
b = (px - a * sx) / qx
If resulting coefficients a and b fulfill limits:
a >= 0
b >= 0
a + b <= 1.0
then point p lies in triangle plane inside it.
I am currently working on a project of drawing thick polylines and I am using interpolation in OpenGL. I managed to calculate all the necessary points but I need to draw two more points. I need to translate one point orthogonally to the line connecting two points. The scatch below shows what are the points. Point L is to be translated for the distance between L and nJ orthogonally to the line AB (B is the central point). Similar thing is with translation to the nK.
I have written the code:
float alpha = atan2(B.y - A.y,B.x - A.x) - deg90;
float alpha2 = atan2(C.y - B.y, C.x - B.x) - deg90;
nJ.x = L.x + w*cos(alpha); // w is distance between A1 and A2
nJ.y = L.y + w*sin(alpha);
nK.x = L.x + w*cos(alpha2);
nK.y = L.y + w*sin(alpha2);
The code works only for some points, not all. I need to fix + sing in above calculations of nJ and nK, but I do not know how. Anyone having suggestion?
First you need the left-hand-side function:
lhs(v) = [-v.y, v.x]
This turns a vector 90 degrees counter-clockwise.
Now you need the turn function:
turn(u, v, w) = sign(lhs(v - u), w - v)
If you have a polyline from u to v to w, turn(u,v,w) tells you whether it's a left turn (counter-clockwise turn) (positive), right turn (clockwise turn) (negative), or colinear (0).
There are four infinite lines in your picture that run parallel to ab and bc, with a distance of w between each pair.
The lines on the lower part are:
f(s) = (a + 0.5 * w * normalize(lhs(b - a))) + (b - a) * s
g(t) = (b + 0.5 * w * normalize(lhs(c - b))) + (c - b) * t
You want to find the intersection of the two lines; i.e., you want to solve for s and t in f(s) = g(t). This is just a system of two linear equations with two unknowns.
The solution is your point L = f(s) = g(t) in the picture.
To compute I you can use the exact same idea:
f(s) = (a - 0.5 * w * normalize(lhs(b - a))) + (b - a) * s
g(t) = (b - 0.5 * w * normalize(lhs(c - b))) + (c - b) * t
Solve for I = f(s) = g(t).
Update
Once you have L you can compute Kn and Jn as follows.
Kn = L - w * normalize(lhs(b - a))
Jn = L - w * normalize(lhs(c - b))
In computational geometry code, trigonometry is usually a code smell - it's not always wrong, but it usually is wrong. Try to stick to linear algebra.
I am writing a 3d vector class for OpenGL. How do I rotate a vector v1 about another vector v2 by an angle A?
You may find quaternions to be a more elegant and efficient solution.
After seeing this answer bumped recently, I though I'd provide a more robust answer. One that can be used without necessarily understanding the full mathematical implications of quaternions. I'm going to assume (given the C++ tag) that you have something like a Vector3 class with 'obvious' functions like inner, cross, and *= scalar operators, etc...
#include <cfloat>
#include <cmath>
...
void make_quat (float quat[4], const Vector3 & v2, float angle)
{
// BTW: there's no reason you can't use 'doubles' for angle, etc.
// there's not much point in applying a rotation outside of [-PI, +PI];
// as that covers the practical 2.PI range.
// any time graphics / floating point overlap, we have to think hard
// about degenerate cases that can arise quite naturally (think of
// pathological cancellation errors that are *possible* in seemingly
// benign operations like inner products - and other running sums).
Vector3 axis (v2);
float rl = sqrt(inner(axis, axis));
if (rl < FLT_EPSILON) // we'll handle this as no rotation:
{
quat[0] = 0.0, quat[1] = 0.0, quat[2] = 0.0, quat[3] = 1.0;
return; // the 'identity' unit quaternion.
}
float ca = cos(angle);
// we know a maths library is never going to yield a value outside
// of [-1.0, +1.0] right? Well, maybe we're using something else -
// like an approximating polynomial, or a faster hack that's a little
// rough 'around the edge' cases? let's *ensure* a clamped range:
ca = (ca < -1.0f) ? -1.0f : ((ca > +1.0f) ? +1.0f : ca);
// now we find cos / sin of a half-angle. we can use a faster identity
// for this, secure in the knowledge that 'sqrt' will be valid....
float cq = sqrt((1.0f + ca) / 2.0f); // cos(acos(ca) / 2.0);
float sq = sqrt((1.0f - ca) / 2.0f); // sin(acos(ca) / 2.0);
axis *= sq / rl; // i.e., scaling each element, and finally:
quat[0] = axis[0], quat[1] = axis[1], quat[2] = axis[2], quat[3] = cq;
}
Thus float quat[4] holds a unit quaternion that represents the axis and angle of rotation, given the original arguments (, v2, A).
Here's a routine for quaternion multiplication. SSE/SIMD can probably speed this up, but complicated transform & lighting are typically GPU-driven in most scenarios. If you remember complex number multiplication as a little weird, quaternion multiplication is more so. Complex number multiplication is a commutative operation: a*b = b*a. Quaternions don't even preserve this property, i.e., q*p != p*q :
static inline void
qmul (float r[4], const float q[4], const float p[4])
{
// quaternion multiplication: r = q * p
float w0 = q[3], w1 = p[3];
float x0 = q[0], x1 = p[0];
float y0 = q[1], y1 = p[1];
float z0 = q[2], z1 = p[2];
r[3] = w0 * w1 - x0 * x1 - y0 * y1 - z0 * z1;
r[0] = w0 * x1 + x0 * w1 + y0 * z1 - z0 * y1;
r[1] = w0 * y1 + y0 * w1 + z0 * x1 - x0 * z1;
r[2] = w0 * z1 + z0 * w1 + x0 * y1 - y0 * x1;
}
Finally, rotating a 3D 'vector' v (or if you prefer, the 'point' v that the question has named v1, represented as a vector), using the quaternion: float q[4] has a somewhat strange formula: v' = q * v * conjugate(q). Quaternions have conjugates, similar to complex numbers. Here's the routine:
static inline void
qrot (float v[3], const float q[4])
{
// 3D vector rotation: v = q * v * conj(q)
float r[4], p[4];
r[0] = + v[0], r[1] = + v[1], r[2] = + v[2], r[3] = +0.0;
glView__qmul(r, q, r);
p[0] = - q[0], p[1] = - q[1], p[2] = - q[2], p[3] = q[3];
glView__qmul(r, r, p);
v[0] = r[0], v[1] = r[1], v[2] = r[2];
}
Putting it all together. Obviously you can make use of the static keyword where appropriate. Modern optimising compilers may ignore the inline hint depending on their own code generation heuristics. But let's just concentrate on correctness for now:
How do I rotate a vector v1 about another vector v2 by an angle A?
Assuming some sort of Vector3 class, and (A) in radians, we want the quaternion representing the rotation by the angle (A) about the axis v2, and we want to apply that quaternion rotation to v1 for the result:
float q[4]; // we want to find the unit quaternion for `v2` and `A`...
make_quat(q, v2, A);
// what about `v1`? can we access elements with `operator [] (int)` (?)
// if so, let's assume the memory: `v1[0] .. v1[2]` is contiguous.
// you can figure out how you want to store and manage your Vector3 class.
qrot(& v1[0], q);
// `v1` has been rotated by `(A)` radians about the direction vector `v2` ...
Is this the sort of thing that folks would like to see expanded upon in the Beta Documentation site? I'm not altogether clear on its requirements, expected rigour, etc.
This may prove useful:
double c = cos(A);
double s = sin(A);
double C = 1.0 - c;
double Q[3][3];
Q[0][0] = v2[0] * v2[0] * C + c;
Q[0][1] = v2[1] * v2[0] * C + v2[2] * s;
Q[0][2] = v2[2] * v2[0] * C - v2[1] * s;
Q[1][0] = v2[1] * v2[0] * C - v2[2] * s;
Q[1][1] = v2[1] * v2[1] * C + c;
Q[1][2] = v2[2] * v2[1] * C + v2[0] * s;
Q[2][0] = v2[0] * v2[2] * C + v2[1] * s;
Q[2][1] = v2[2] * v2[1] * C - v2[0] * s;
Q[2][2] = v2[2] * v2[2] * C + c;
v1[0] = v1[0] * Q[0][0] + v1[0] * Q[0][1] + v1[0] * Q[0][2];
v1[1] = v1[1] * Q[1][0] + v1[1] * Q[1][1] + v1[1] * Q[1][2];
v1[2] = v1[2] * Q[2][0] + v1[2] * Q[2][1] + v1[2] * Q[2][2];
Use a 3D rotation matrix.
The easiest-to-understand way would be rotating the coordinate axis so that vector v2 aligns with the Z axis, then rotate by A around the Z axis, and rotate back so that the Z axis aligns with v2.
When you have written down the rotation matrices for the three operations, you'll probably notice that you apply three matrices after each other. To reach the same effect, you can multiply the three matrices.
I found this here:
http://steve.hollasch.net/cgindex/math/rotvec.html
let
[v] = [vx, vy, vz] the vector to be rotated.
[l] = [lx, ly, lz] the vector about rotation
| 1 0 0|
[i] = | 0 1 0| the identity matrix
| 0 0 1|
| 0 lz -ly |
[L] = | -lz 0 lx |
| ly -lx 0 |
d = sqrt(lx*lx + ly*ly + lz*lz)
a the angle of rotation
then
matrix operations gives:
[v] = [v]x{[i] + sin(a)/d*[L] + ((1 - cos(a))/(d*d)*([L]x[L]))}
I wrote my own Matrix3 class and Vector3Library that implemented this vector rotation. It works absolutely perfectly. I use it to avoid drawing models outside the field of view of the camera.
I suppose this is the "use a 3d rotation matrix" approach. I took a quick look at quaternions, but have never used them, so stuck to something I could wrap my head around.