Geometry - convex flanked by two circle rotate around geometrical center - algorithm

I want to do it that a convex(consist of some line or arc) rotate around it's geometrical center(Cx,Cy). Meanwhile the convex flanked by two circle (given by radius: R and left center:(Lx,Cy), right center:(Rx,Cy) ). It means the circle center with same X axis as geometrical(Cy).
The model picture:
The algorithm aims to calculate the Lx and Rx when rotate theta(0 to 360 degree) and the convex with two circle only have one contact point separately. How can I achieve it?
Assume we can get the convex discretization points by given delta distance or delta theta around geometrical center.

To provide contact between rotated convex and circle, it is worth to define convex pieces analytically.
For example, if straight segment has parametric equation
X = X0 + t * (X1-X0)
Y = Y0 + t * (Y1-Y0)
then solve equation system
(X - Lx)^2 + (Y - Cy)^2 = R^2 //distance
(X - Lx) * (X1 - X0) + (Y - Cy) * (Y1 - Y0) = 0 //tangent perpendicularity to radius
for unknowns t and Lx and check that t lies in range 0..1. If true - circle touches this segment, Lx if valid
If curved segment is analytical curve, then normal to the curve in touch point should be collinear with radius.
For circle arc segment with radius aR and center ax, ay tangency condition is:
(ax - Lx)^2 + (ay - Cy)^2 = (aR + R)^2
again - one need to check whether tangent point is inside arc limits

Related

Algorithm to align a rectangle when a point is dragged?

I am trying to implement an algorithm that will align a rectangle on an ellipse when a point is dragged.
The data I have is:
I know what corner is being dragged
the starting position of it
the ending position of it
My old algorithm was to align the adjacent corners, but that only worked if the ellipse or rectangle weren't at an angle.
I am trying to implement something like Figma does:
My current idea is to take the sides that were changed on drag and match the other sides that weren't changed to the size of the changed sides. Though I'm not sure if that's correct.
Let rectangle is described by center point (CX, CY) and two unit direction vectors (WX, WY) and (HX, HY), also W is half-width, H is half-height.
As far as I understand, rectangle slope is preserved, so direction vectors remain the same.
When corner number k was shifted, it's new position is (NX, NY). Opposite vertex has number (k+2)%4 and it's position is (PX, PY) (doesn't change)
New center is
CX' = (PX + NX) / 2
CY' = (PY + NY) / 2
New half-width and half-height
W' = 0.5 * Abs(WX * (NX - PX) + WY * (NY - PY))
H' = 0.5 * Abs(HX * (NX - PX) + HY * (NY - PY))

Intersection points between 2 discs in 3d

i am trying to find a algorithm or a way to find the intersection between two circle on a sphere (in 3d). For example if i have two circles center at two pointsA(latitude1,longitude1) and B(latidude2,longitude2)
assuming that they intersect, how can i find the intersection between those two circles? is there an algorithm to do that?
Thank you
Convert from latitude/longitude to 3D Cartesian
coordinates.
For each circle, find the equation nx x + ny y + nz z = d of the
plane whose intersection with the sphere is the circle. Assuming
that the sphere is centered at the origin, the normal vector
(nx, ny, nz) is the circle center (cx, cy, cz) (projected or
not) after normalization.
(cx, cy, cz)
(nx, ny, nz) = -----------------
||(cx, cy, cz)||
2
The distance d is computed using Pythagoras. Let r be the radius
of the circle and R be the radius of the sphere.
2 2 2
R = d + r
_______ _______________
| 2 2 |
d = \|R - r = \|(R + r) (R - r)
The second expression is preferred for numerical stability.
If we know only the length r' on the surface of the sphere from
the projected center of the circle to the circle, then compute
d = R cos(r'/R)
r = R sin(r'/R).
We actually don’t need r in this case.
Find the intersection of the two planes, a
line.
Find the intersection of the line and the sphere, between zero and two
points.
Convert the points to
latitude/longitude.

Distance between 2 points in a circle

I am given 2 points inside a circle. I have to find a point on the circle (not inside, not outside) so that the sum of the distances between the given 2 points and the point i found is minimum. I only have to find the minimum distance, not the position of the point.
It is a minimization problem:
minimize sqrt((x1-x0)^2 + (y1-y0)^2) + sqrt((x2-x0)^2 + (y2-y0)^2)
^ ^
(distance from point1) (distance from point 2)
subject to constraints:
x1 = C1
y1 = C2
x2 = C3
x4 = C4
x0^2 + y0^2 = r^2
(assuming the coordinates are already aligned to the center of the circle as (0,0)).
(C1,C2,C3,C4,r) are given constants, just need to assign them.
After assigning x1,y1,x2,y2 - you are given a minimization problem with 2 variables (x0,y0) and a constraint. The minimization problem can be solved using lagrange multiplier.
Let (x1, y1) and (x2, y2) be the points inside the circle, (x, y) be the point on the circle, r be the radius of the circle.
Your problem reduces to a Lagrange conditional extremum problem, namely:
extremum function:
f(x, y) = sqrt((x-x1)^2 + (y-y1)^2) + sqrt((x-x2)^2 + (y-y2)^2)
condition:
g(x, y) = x^2 + y^2 = r^2 (1)
Introduce an auxiliary function(reference):
Λ(x, y, λ) = f(x, y) + λ(g(x, y) - r^2)
Let ∂Λ / ∂x = 0, we have:
(x-x1)/sqrt((x-x1)^2 + (y-y1)^2) + (x-x2)/sqrt((x-x2)^2 + (y-y2)^2) + 2λx = 0 (2)
Let ∂Λ / ∂y = 0, we have:
(y-y1)/sqrt((x-x1)^2 + (y-y1)^2) + (y-y2)/sqrt((x-x2)^2 + (y-y2)^2) + 2λy = 0 (3)
Now we have 3 variables(i.e. x, y and λ) and 3 equations(i.e. (1), (2) and (3)), so it's solvable.
Please be noted that there should be two solutions(unless two inside points happen to be the center of the circle). One is the minimal value(which is what you need), the other is the maximal value(which will be ignored).
just another approach(which is more directly):
for simplicity, assume the circle is at (0,0) with radius r
and suppose two points are P1(x1,y1) and P2(x2,y2)
we can calculate the polar angle of these two points, suppose they are alpha1 and alpha2
obviously, the point which is on the circle and having the minimum sum of distance to P1 and P2 is within the circular sector composed of alpha1 and alpha2
meanwhile, the sum of distance between the point on the circle within that sector and P1 and P2 is a quadratic function. so, the minimum distance can be found by using trichotomy.

How to stop a bezier spline from going beyond the coordinate axes?

In my iOS app I draw a bezier spline through a set of 2D points using an algorithm that calculates set of first and second control points for each bezier curve joining two consecutive points.
The algorithm works brilliantly but the my problem is that now I am displaying this curve on a graph with X and Y axes.
Whenever there are couple of points or on the axes, and rest of them inside, the curve seems to take a U-turn and go beyond the axis and come back in two go through both the points and the ones that are inside.
From the algorithm perspective there is nothing wrong n that. Controls point in such case will be generated out side the coordinate axes.
Is there a way that I can go through the points and see if some of them are on the axes and modify the controls points such that the curve instead of going outside the curve just passes through both points on the axis as a straight line coinciding with coordinate axis.
Detecting a curve that goes off-screen
Bezier curves are actually just polynomial equations. There are multiple types of Bezier curves, corresponding to the differing degrees of the curve.
So, just take the equations that are generated (one for x, one for y), and find the roots (points where they pass through 0). If the roots exist, the curve passes the axis.
For example, for a quadratic (degree=2) Bezier curve, given our three points (x0, y0), (x1, y1), (x2, y2) the equations are
x(t) = (x0 - 2x1 + x2)t2 - 2(x0 + x1)t + x0
y(t) = (y0 - 2y1 + y2)t2 - 2(y0 + y1)t + y0
0 <= t <= 1
At this point, we could use the quadratic formula to solve for t, and check that the solution either doesn't exist or is outside our domain of [0,1] for t. However, there is another method that generalizes for cubic Bezier curves, without having to touch the complicated cubic formula - just check the extrema-points. These are the points where the derivative = 0. Since the derivative is
x'(t) = 2(x0 - 2x1 + x2)t - 2(x0 + x1)
y'(t) = 2(y0 - 2y1 + y2)t - 2(y0 + y1)
This means the extrema are at
textrema-x = (x0 + x1) / (x0 - 2x1 + x2)
textrema-y = (y0 + y1) / (y0 - 2y1 + y2)
Thus, just check that x(textrema-x) > 0 and y(textrema-y) > 0 (We are assuming the endpoints x0 and x2 are known to be on the screen aka > 0). For cubic Bezier curves, do the same thing, but use the quadratic-formula to solve for the extremas (there are two extremas for each of x and y in that case).
Preventing the curve from going off-screen
If we solve for x(textrema-x) > 0 by taking our equation above for textrema-x and plugging it into x(t), we find after a bit of algebra that, to prevent crossing the x-axis, we need
-4x0x1 + x0x2 - x12 > 0 if (x0 + x2) > 2x1
-4x0x1 + x0x2 - x12 < 0 if (x0 + x2) < 2x1
(if (x0 + x2) = 2x1, we are moving linearly from x0 to x2 so, assuming both are positive, we can't cross the x-axis)
A bit of staring at these equations should convince you that if (x0 + x2) > 2x1, we can simply decrease x1 until the lefthand condition is met; and if (x0 + x2) < 2x1, we can simply increase x1 until the condition is met. The equations for y are analogous.
This tells us how to prevent the curve from going off the left (x=0) and top (y=0) portions of the screen - what about the right (x=screen_width) and bottom (y=screen_height)?
We can do this easily by imagining we are flipping the screen to its mirror-image, so that the right-side is x=0 and the left-side is x=screen_width. This can be done by replacing every instance of x with (screen_width-x) in all equations above, and checking our conditions. Then, for example, when before in the first case we'd decrease x1, in this case we'd want to decrease (screen_width-x1), which is the same as increasing x1. The same logic holds for replacing y with (screen_height-y).

How to detect if an ellipse intersects(collides with) a circle

I want to improve a collision system.
Right now I detect if 2 irregular objects collide if their bounding rectangles collide.
I want to obtain the for rectangle the corresponding ellipse while for the other one to use a circle. I found a method to obtain the ellipse coordinates but I have a problem when I try to detect if it intersects the circle.
Do you know a algorithm to test if a circle intersects an ellipse?
Short answer: Solving exactly for whether the two objects intersect is complicated enough to be infeasible for the purpose of collision detection. Discretize your ellipse as an n-sided polygon for some n (depending on how accurate you need to be) and do collision detection with that polygon.
Long answer: If you insist on determining if the smooth ellipse and circle intersect, there are two main approaches. Both involve solving first for the closest point to the circle's center on the ellipse, and then comparing that distance to the circle's radius.
Approach 1: Use a parametrization of the ellipse. Transform your coordinates so that the ellipse is at the origin, with its axes aligned to the x-y axes. That is:
Center of ellipse: (0,0)
Center of circle: c = (cx, cy)
Radius of circle: r
Radius of x-aligned axis of ellipse: a
Radius of y-aligned axis of ellipse: b.
The equation of the ellipse is then given by a cos(t), b sin(t). To find the closest point, we want to minimize the square distance
|| (a cos t, b sin t) - c ||^2. As Jean points out, this is "just calculus": take a derivative, and set it equal to 0. Unless I'm missing something, though, solving the resulting (quite nasty) equation for t is not possible analytically, and must be approximated using e.g. Newton's Method.
Plug in the t you find into the parametric equation to get the closest point.
Pro: Numerical solve is only in one variable, t.
Con: You must be able to write down a parametrization of the ellipse, or transform your coordinates so that you can. This shouldn't be too hard for any reasonable representation you have of the ellipse. However, I'm going to show you a second method, which is much more general and might be useful if you have to generalize your problem to, say, 3D.
Approach 2: Use multidimensional calculus. No change of coordinates is necessary.
Center of circle: c = (cx, cy)
Radius of cirlce: r
Ellipse is given by g(x, y) = 0 for a function g. For instance, per Curd's answer you might use g(x,y) = distance of (x,y) from focus 1 + distance of (x,y) from focus 2 - e.
Finding the point on the ellipse closest to the center of the circle can then be phrased as a constrained minimization problem:
Minimize ||(x,y) - c||^2 subject to g(x,y) = 0
(Minimizing the square distance is equivalent to minimizing the distance, and much more pleasant to deal with since it's a quadratic polynomial in x,y.)
To solve the constrained minimization problem, we introduce Lagrange multiplier lambda, and solve the system of equations
2 * [ (x,y) -c ] + lambda * Jg(x,y) = 0
g(x,y) = 0
Here Jg is the gradient of g. This is a system of three (nonlinear) equations in three unknowns: x, y, and lambda. We can solve this system using Newton's Method, and the (x,y) we get is the closest point to the circle's center.
Pro: No parametrization needs to be found
Pro: Method is very general, and works well whenever writing g is easier than finding a parametric equation (such as in 3D)
Con: Requires a multivariable Newton solve, which is very hairy if you don't have access to a numerical method package.
Caveat: both of these approaches technically solve for the point which extremizes the distance to the circle's center. Thus the point found might be the furthest point from the circle, and not the closest. For both methods, seeding your solve with a good initial guess (the center of the circle works well for Method 2; you're on your own for Method 1) will reduce this danger.
Potential Third Approach?: It may be possible to directly solve for the roots of the system of two quadratic equations in two variables representing the circle and ellipse. If a real root exists, the objects intersect. The most direct way of solving this system, again using a numerical algorithm like Newton's Method, won't help because lack of convergence does not necessary imply nonexistence of a real root. For two quadratic equations in two variables, however, there may exist a specialized method that's guaranteed to find real roots, if they exist. I myself can't think of a way of doing this, but you may want to research it yourself (or see if someone on stackoverflow can elaborate.)
An ellipse is defined a the set of points whose
sum of the distance to point A and the distance to point B is constant e.
(A and B are called the foci of the ellipse).
All Points P, whose sum AP + BP is less than e, lie within the ellipse.
A circle is defined as the set of points whose
distance to point C is r.
A simple test for intersection of circle and ellipse is following:
Find
P as the intersection of the circle and the line AC and
Q as the intersection of the circle and the line BC.
Circle and ellipse intersect (or the circle lies completely within the ellipse) if
AP + BP <= e or AQ + BQ <= e
EDIT:
After the comment of Martin DeMello and adapting my answer accordingly I thought more about the problem and found that the answer (with the 2nd check) still doesn't detect all intersections:
If circle and ellipse are intersecting only very scarcely (just a little more than being tangent) P and Q will not lie within the ellipse:
So the test described above detects collision only if the overlap is "big enough".
Maybe it is good enough for your practical purposes, although mathematically it is not perfect.
I know that it's too late but I hope it would help somebody. My approach to solve this problem was to interpolate the ellipse into an n-dimensions polygon, then to construct a line between every 2 points and find whether the circle intersects with any of the lines or not. This doesn't provide the best performance, but it is handy and easy to implement.
To interpolate the ellipse to an n-dimensions polygon, you can use:
float delta = (2 * PI) / n;
std::vector<Point*> interpolation;
for(float t = 0; t < (2 * PI); t += delta) {
float x = rx * cos(t) + c->get_x();
float y = ry * sin(t) + c->get_y();
interpolation.push_back(new Point(x, y));
}
c: The center of the ellipse.
rx: The radius of x-aligned axis of the ellipse.
ry: The radius of y-aligned axis of the ellipse.
Now we have the interpolation points, we can find the intersection between the circle and the lines between every 2 points.
One way to find the line-cricle intersection is described here,
an intersection occurs if an intersection occurred between any of the lines and the circle.
Hope this helps anybody.
find the point on the ellipse closest to the center of the circle
and then check if the distance from this point is smaller than the radius of the circle
if you need help doing this just comment, but it's simply calculus
edit: here's a ways towards the solution, since there is something wrong with curds
given center α β on the ellipse
and (for lack of remembering the term) x radius a, y radius b
the parametrization is
r(Θ) = (ab)/( ( (BcosΘ)^2 + (asinΘ)^2 )^.5)
x(Θ) = α + sin(Θ)r(Θ)
y(Θ) = β + cos(Θ)r(Θ)
and then just take the circle with center at (φ, ψ) and radius r
then the distance d(Θ) = ( (φ - x(Θ))^2 + (ψ - y(Θ) )^2)^.5
the minimum of this distance is when d'(Θ) = 0 (' for the derivative)
d'(Θ) = 1/d(Θ) * (-φx'(Θ) + x(Θ)x'(Θ) - ψy'(Θ) + y(Θ)y'(Θ) )
==>
x'(Θ) * (-φ + x(Θ)) = y'(Θ) * (ψ - y(Θ))
and keep going and going and hopefully you can solve for Θ
The framework you're working in might have things to help you solve this, and you could always take the easy way out and approximate roots via Newton's Method
if a circle and an ellipse collide, then either their boundaries intersect 1, 2, 3, or 4 times(or infinitely many in the case of a circular ellipse that coincides with the circle), or the circle is within the ellipse or vice versa.
I'm assuming the circle has an equation of (x - a)^2 + (y - b)^2 <= r^2 (1) and the ellipse has an equation of [(x - c)^2]/[d^2] + [(y - e)^2]/[f^2] <= 1 (2)
To check whether one of them is inside the other, you can evaluate the equation of the circle at the coordinates of the center of the ellipse(x=c, y=e), or vice versa, and see if the inequality holds.
to check the other cases in which their boundaries intersect, you have to check whether the system of equations described by (1) and (2) has any solutions.
you can do this by adding (1) and (2), giving you
(x - a)^2 + (y - b)^2 + [(x - c)^2]/[d^2] + [(y - e)^2]/[f^2] = r^2 + 1
next you multiply out the terms, giving
x^2 - 2ax + a^2 + y^2 - 2by + b^2 + x^2/d^2 - 2cx/d^2 + c^2/d^2 + y^2/f^2 - 2ey/f^2 + e^2/f^2 = r^2 + 1
collecting like terms, we get
(1 + 1/d^2)x^2 - (2a + 2c/d^2)x + (1 + 1/f^2)y^2 - (2b + 2e/f^2)y = 1 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2
now let m = (1 + 1/d^2), n = -(2a + 2c/d^2), o = (1 + 1/f^2), and p = -(2b + 2e/f^2)
the equation is now mx^2 + nx + oy^2 + py = 1 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2
now we need to complete the squares on the left hand side
m[x^2 + (n/m)x] + o[y^2 + (p/o)y] = 1 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2
m[x^2 + (n/m)x + (n/2m)^2 - (n/2m)^2] + o[y^2 + (p/o)y + (p/2o)^2 - (p/2o)^2] = 1 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2
m[(x + n/2m)^2 - (n/2m)^2] + o[(y + p/2o)^2 - (p/2o)^2] = 1 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2
m(x + n/2m)^2 - m(n/2m)^2 + o(y + p/2o)^2 - o(p/2o)^2 = 1 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2
m(x + n/2m)^2 + o(y + p/2o)^2 = 1 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2 + m(n/2m)^2 + o(p/2o)^2
this system has a solution iff 11 + r^2 - a^2 - b^2 - c^2/d^2 - e^2/f^2 + m(n/2m)^2 + o(p/2o)^2 >= 0
There you have it, if I didn't make any algebraic mistakes. I don't know how much you can simplify the resulting expression, so this solution might be quite computationally expensive if you're going to check for many circles/ellipses
Enlarge the ellipse's major and minor radii by the radius of the circle. Then test if the center of the given circle is within this new larger ellipse by summing the distances to the foci of the enlarged ellipse.
This algorithm is quite efficient. You can early-out if the given circle doesn't intersect a circle which circumscribes the ellipse. This is slower than a bounding box test, but finding the bounding box of a non-axis-aligned ellipse is tricky.
Forget about a mathematical solution. As you can easily see by drawing, you can have up to four solutions, and thus likely a fourth grade polynomial.
Instead just do a binary search along the edge of one of the figures. It is easy to determine if a point lies within an ellipse and even more so in a circle (just see if distance is shorter than radius).
If you really want to go for the maths, Wolfram MathWorld has a nice article here: http://mathworld.wolfram.com/Circle-EllipseIntersection.html but be warned, you'll still have to write a polynomial equation solver, probably using something like binary search.
Supposing:
the ellipse is centred at the origin and with the semi-major
axis (of length a) oriented along the x axis, and with a semi-minor
axis of length b; E2 is the eccentricity squared, ie (aa-bb)/(a*a);
the circle is centred at X,Y and of radius r.
The easy cases are:
the circle centre is inside the ellipse (ie hypot(X/a, Y/b) <= 1)
so there is an intersection;
the circle centre is outside a circle centred at 0 of radius a+r
(ie hypot(X,Y) > a+r) so there isn't an intersection.
One approach for the other cases is to compute the geodetic
coordinates (latitude, height) of the circle centre. The circle
intersects the ellipse if and only if the height is less than the radius.
The geodetic latitude of a point on an ellipse is the angle
the normal to the ellipse at the point makes with the x axis, and
the height of a point outside the ellipse is the distance of the
point from the point on the ellipse closest to it. Note the geodetic latitude is not same as the polar angle from the ellipse centre to the point unless the
ellipse is in fact circular.
In formulae the conversion from geodetic coordinates lat,ht to
cartesian coordinates X,Y is
X = (nu+ht)*cos(lat), Y = (nu * (1-E2) + ht)*sin(lat)
where nu = a/sqrt( 1 - E2*sin(lat)sin(lat)).
The point on the ellipse closest to X,Y is the point
with the same latitude, but zero height, ie x = nucos(lat),
y = nu * (1-E2) * sin(lat).
Note that nu is a function of latitude.
Unfortunately the process of finding lat,ht from X,Y is an
iterative one. One approach is to first find the latitude, and then
the height.
A little algebra shows that the latitude satisfies
lat = atan2( Y+ E2*nusin(lat), X)
which can be used to compute successive approximations to the latitude,
starting at lat = atan2( Y, X(1.0-E2)), or (more efficiently) can be
solved using newton's method.
The larger E2 is, ie the flatter the ellipse is, the more
iterations will be required. For example if the ellipse is nearly
circular (say E2<0.1) then five iterations will get x,y below
to within a*1e-12, but if the ellipse is very flat, e.g. E2=0.999
you'll need around 300 iterations to get the same accuracy!
Finally, given the latitude, the height can be computed
by computing (x,y):
x = nucos(lat), y = nu(1-E2)*sin(lat)
and then h is the distance from x,y to the circle centre,
h = hypot( X-x, Y-y)
This isn't that hard. user168715's answer is generally right, but doing calculus isn't necessary. Just trigonometry.
Find the angle between the center of the two objects. Using this you can find the closest point to the circle's center on the ellipse using the polar-form:
(Taken from Wikipedia article on Ellipses)
Now compare the distance between the two object centers, subtracting the ellipse radius and circle radius.
Maybe I'm missing something; maybe ArcTan/Cos/Sin are slow -- but I don't think so, and there should be fast-approximations if needed.
I wanted to provide some input into the more general problem involving contact between two ellipses. Calculating the distance of closest approach of two ellipses was a long standing problem and was only solved analytically within the last ten years-it is by no means simple. The solution to the problem may be found here http://www.e-lc.org/docs/2007_01_17_00_46_52/.
The general method to determine if there is contact between two ellipses is to first calculate the distance of closest approach of the ellipses in their current configuration and then subtract this from their current magnitude of separation. If this result is less than or equal to 0, then they are in contact.
If anyone is interested I can post code that calculates the distance of closest approach--it's in C++. The code is for the general case of two arbitrary ellipses, but you can obviously do it for a circle and ellipse, since a circle is an ellipse with equal minor and major axes.

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