I have two 2D convex polygons. I want to
subtract one from the other one and
add one to the other one
The resulting polygon must be either concave or a - better - a set of convex polygons (e.g. triangles).
Do you have any idea how I can accomplish this?
Related
I'm trying to create this in Gamemaker. I already know the Voronoi vertices but i'm stuck with how to create polygons for each seed object. I need them to be independent so i can split it up later to apply texture mapping to them.
I've tried delaunay already but it doesn't seem as accurate as my voronoi generation. But being that the cicrumradius is the voronoi vertices anyways i feel like i don't need it. The problem with the Delaunay is that it only returns the points near the center of the diagram and doesn't return any points towards the Borders of the Box. The only good thing is that delaunay did skip an extra step and made it easier to return if the the seeds x and y are within the circumradius then just add them to the list of vertices
Is there any way to make a polygon from a plot of points from a data structure?
Pick the midpoint of each edge and the distance to each site then sort the result and pick the first and second (when they are equal) and save them into polygons. For the borders there is of course only 1 edge.
Duplicate:Getting polygons from voronoi edges
I'm starting with a single 2D triangle that I want to clip with a (potentially) convex 2D polygon. It's not self-intersecting, but may 'keep' or 'discard' the intersecting area based on the winding order.
I want to end up with a triangulation, i.e. a list of n vertices and m triangles, defined by 3 vertices each, of the clipped region in 2D space.
What would be the easiest (for me as a developer), and what the fastest (in terms of computation) way to achieve this?
If I a right, you want to clip inside the polygon, i.e. get the intersection between the triangle and the polygon.
As the triangle is a convex shape, the Sutherland-Hodgman algorithm is appropriate and no too difficult to implement (https://en.wikipedia.org/wiki/Sutherland%E2%80%93Hodgman_algorithm).
Notice that if the intersection is not simply connected, the resulting polygon will be connected, with double edges joining the would-be parts. Some cleanup might be required.
After finding the intersection, you re-triangulate using the ear-clipping method or a more efficient one (https://en.wikipedia.org/wiki/Polygon_triangulation).
Alternatively, you can triangulate the polygon and perform the clipping of every triangle with the original one.
The triangle-triangle clipping problem is again solved with Sutherland-Hodgman, somewhat simplified as the input polygons have a constant size, and their intersection is convex and at worse an hexagon. Trigulation of a convex polygon is immediate.
I am trying to compute a Voronoi tesselation in 2D with the Manhattan distance in R.
Ideally this would be a function that takes a set of two-dimensional points and outputs a list of polygons that partition the space. I am not certain what representations of Voronoi tesselations are standard.
There are of course many ways to do this with the Euclidean metric (packages like deldir and qhull make this very easy), but I haven't found a way to do this for the manhattan distance. A search using sos's findFn('voronoi') also yielded no results.
Info: taxicabgeometry.net
Interactive: Manhattan-metric Voronoi diagram(Click version)
I've been rolling my own in python, and can sum up the basics here:
Between neighboring centroids is a perpendicular line, in manhattan metric - two rays and a 45 degree diagonal most likely, if the centroids are randomly generated, but a straight horizontal, vertical, or 45 degree diagonal line may also occur. Given a set of such lines for every centroid pair, the edges separating the regions are among them. Collect intersect points of each pair of lines which are equal-distant (within an epsilon), in manhattan metric, to it's 3 nearest centroids. Also collect the two mid points of the 45 degree diagonal which are similarly equal-distant to their nearest two centroids. The outer polies won't be closed. How to deal with them depends on what you need. The poly borders and border verts will need sorting, so your polies aren't a zigzagged mess. Winding order can be determined if they should be clockwise or other. More can be done, just depends on what you need.
Unfortunately, this gets exponentially slower the more points are involved. The intersecting of every bisector to every other bisector is the bottleneck. I've been attempting an insertion method, with some success, but . Now I'm thinking to try first creating a nearest-neighbor linkage between the centroids. If the neighbors are known, the bisectors to intersect will be minimal, and many centroids can be computed quickly.
Anyway, the brute-force approach does work:
The point near the cursor is actually 2 points of a tiny diagonal. It's a precise method, but more complicated than it first seems. The java code from the interactive link above may be faster, but was difficult to get solid and precise geometry from.
Sorry, I dont know R.
Maybe the question is about finding the maximum area of a square that match inside a circumcircle (of a triangle). The equation for such a square abs(x)+abs(y)=r (www.mathematische-basteleien.de/taxicabgeometry.htm). When you have a mesh of triangles the voronoi diagram is the dual.
I am trying to implement in C++ a function that determines the cut of any given polygon and pyramid.
This has actually turned out to be far simpler than I had first imagined.
Firstly for each edge of the pyramid, test line-plane intersection (the given polygon is a plane, made up of 3 points). This will result in the new vertices at the cutting plane.
Secondly, since the polygon is not an infinite plane one needs to test for line-line intersection between the polygon edges (three) and each of the edges.
Indeed, this is not a simple problem. For simplicity, let's assume that there are no parallel line segments.
First determine the plane where your convex polygon is in. Then detemerine the intersection of that plane with the pyramid. This results in a second convex polygon.
Now you should find the intersection of the two convex polygons. How this can be done, you can find here.
I have a set of dense, irregurarly distributed 2D points ("scattered all over the place"). They can be stored in a single MULTIPOINT WKT object including "holes" or - if needed - as delaunay triangles.
How would you convert this into a polygon, i.e. one outer boundary and zero, one or more inner boundaries?
P.S. It's not the largest enclosing polygon I'm looking for (that would be solved by ConvexHull or ConcaveHull). I'm looking for a true polygon with the same shape as the scattered point set (including inner boundary).
Your question reads to me like “find a polygon which has a given set of points as vertices.” Is that interpretation correct?
If so, you can do the following: Create the convex hull of your points. Remove those points from consideration, and take the convex hull of the remaining points. Proceed in this fashion until there are no more remaining points. The intermediate result will be a sequence of convex polygones nested inside one another. You can turn them into a single polygon by connecting each subsequent pair of polygons. You connect two polygons by removing an edge from each, and connecting the resulting endpoints ”the other way round”. Some care has to be taken that these connections don't overlap anything else, but that shouldn't be too hard.
Note that there are many possible results fulfilling the specification as I read it. If you need a specific one, you'll have to give details on the criteria for that choice.
Use QHull: http://www.qhull.org/
It is the de facto standard for this sort of thing.