My goal is to have labels in the center of polygons.
Currently the polygons are being added via a vector tile source.
In order to have labels centered on polygons, it seems I must add a point source that has geometries representing the polygon centroids. (based on this answer)
When getting geometries via vector tiles, would it possible to dynamically create this point source, or must it be another vector source, one dedicated solely to centroid points?
The usual approach is to generate the labels separately, using geojson-polygon-labels.
Attempting to do it dynamically would be pretty tricky, although perhaps not impossible.
Related
I'm facing issues when trying to create voronoi regions in MATLAB and handle infinite vertices. I am relatively inexperienced in programming which I feel is hampering my ability to solve this problem.
I want to trace specific locations near the central nodes of the voronoi sub-polygons using the function inpolygon. I can not utilise the function if one of the vertices is Infinite (INF). Therefore, I wanted to create a grid around the voronoi split (As seen in image), and only consider the region within this grid, thereby neglecting the infinite vertices.
What I have done so far:
I already have a certain 100 pairs of Latitudes and Longitudes of nodes, around which I create a voronoi split using voronoi(x_coordinates, y_coordinates) function.
When I have to determine the various coordinates of the sub-polygons within this split, I use the
[V,C] = voronoin([x_coordinates, y_coordinates]);
Till now, this gives me all the of voronoi regions in V and all indexes of vertices for all sub-polygons (voronoi regions) in C.
Then I have implemented a function which uses inpolygon and takes x and y coordinates of the point that has to be traced within one of the voronoi regions. And here is where I am stuck. I am trying to implement a grid all around, but can not find the new intersecting vertices of the grid and the voronoi sub-region to find the new vertices of the voronoi sub-polygons.
Also, if there is any other way to achieve the same task, any help would be highly appreciated.
Many Thanks.
Context: I want to create an interactive heatmap with areas separated by a ZIP code. I've found no way of displaying it directly (i.e. using Google Maps or OSM), so I want to create curves or lines that are separating those areas, and visualize it in maps.
I have a set of points, represented by their coordinates and their according class (ZIP code). I want to get a curve separating them. The problem is that these points are not linearly separable.
I tried to use softmax regression, but that doesn't work well with non-linearly separable classes. The only methods I know which are able to separate non-linearly are nearest neighbors and neural networks. But such classifiers only classify, they don't tell me the borders between classes.
Is there a way to get the borders somehow?
If you have a dense cloud of known points within each Zip code with coordinates [latitude. longitude, zip code], using machine learning to find the boundary enclosing those points sounds like overkill.
You could probably get a good approximation of the boundary by using computational geometry, e.g finding the 2D convex hull of each Zip code's set of points using the Matlab convhull function
K = convhull(X,Y)
The result K would be a vector of points enclosing the input X, Y vector of points, that could be used to draw a polygon.
The only complication would be what coordinate system to work in, you might need to do a bit of work going between (lat, lon) and map (x,y) coordinates. If you do not have the Matlab Mapping Toolbox, you could look at the third party library M_Map M_Map home page, which offers some of the same functionality.
Edit: If the cloud of points for Zip codes has a bounding region that is non convex, you may need a more general computational geometry technique to find a better approximation to the bounding region. Performing a Voronoi tesselation of the region, as suggested in the comments, is one such possibility.
I have an .obj file representing a 3D object.
I need to extract from this 3D object the contour that is obtained by intersection with a plane. So for example, I have an object representing a cylinder oriented with vertical axis, then I want to extract a circle contour when the intersecting plane is horizontal or a rectangular contour when the intersection plane is vertical. Any suggestion about how to do it?
Since I didn't know how to visualise this obj file, I have converted to a patch with the following code (some function taken from loadawobj from Matlab file exchange).
modelname='file.obj';
S=loadawobj(modelname);
mtl=loadawmtl(['obj/' S.mtllib]);
p3=patch('Vertices',S.v','Faces',S.f3');
for ii=1:length(S.umat3)
mtlnum=S.umat3(ii);
fvcd3(ii,:)=mtl(1).Kd';
end
p3.FaceVertexCData=fvcd3;
p3.FaceColor='flat';
But I don't necessarily need to extract the contour from the resulting patch if this is too complex to accomplish. If there is an easier procedure starting from the obj file, it's also fine and acceptable. Thank you!
That's the way I solved the problem, after collecting information all around the web. I couldn't find anything ready on line so I had to implement an algorithm on my own. The basic idea is very simple but there are many steps required. I start from two info: one array containing the coordinates of the cloud point and another array containing a bunch of tuples about how the 3 vertex are connected to form a triangle.
First of all you need to find a representation of the plane you want to use for your cutting. That means you just use one point and the normal to the plane to represent it. That plane is required in order to identify the cutting point on the structure.
Second step is to identify the triangles on the plane. In few words you just need to scroll over all the triangles of the structure and find those having one corner above the cutting plane and another corner below the cutting plane. Also don't forget to account for the condition where one corner is on the plane or two are on the plane. All the other triangles are not needed, since they are totally above or below the cutting plane.
Now you have a subset of all your triangles. You need to extract points of the contour. So for each triangle you have 3 vertex: in general case you can imagine that one vertex is above the plane and the other two are below. Then you have two lines cutting the plane. You can extract two point by simply intersecting these lines with the cutting plane.
By repeating this operation you get a series of points on 2D space. But they have no order and if you plot them as a continuous plot, you get lines jumping up and down since the points you have extracted are randomly located in the array. So, it's required to order them in a proper way. The method I used is the very simple: start from one point and connect to the closest one. There are some bad situations where that doesn't work but you can probably avoid it by adding some more rules on the algorithm.
Using CGAL, I have a 3D Delaunay Triangulation of a set of random points on the unit sphere, that I obtained via:
Delaunay T(points.begin(), points.end());
Now, what I would like to be able to do is query T (using locate() or something like that) to find the three vertices of the surface facet that an arbitrary point (also on the unit sphere) is contained inside.
When I use locate(), I get interior cells as results sometimes, which include the infinite vertex. I don't want any of these. I just want the surface facets and to be able to do this for any arbitrary point I try to find that is also on the unit sphere. Trying to figure this out has taken a lot longer than I thought it would.
Any help would be much obliged. Thanks.
So I would use find_conflit(), with CGAL::Emptyset_iterator for cit because you don't need these.
In bfit, you will get the facets of the boundary of the "hole", and the hole is all tetrahedra in conflict with your point (whose circumscribing sphere contains the point, with a natural extension to the infinite vertex).
So, for bfit, put them in a standard container using std::back_inserter for example. Then, iterate over these, tests if they are finite facets. The finite facets you get are those that separate your point from the rest of the triangulation, so, you can then do orientation() tests with the center of the sphere to get the one you are interested in.
I have a cloud of points in the 3d matrix. Each column of this matrix contains different coordinate (x,y,z) of the point. I need to find a way to obtain only external points which are visible from one direction of view and put them to another matrix. Or in other way I need to remove a points which are overshadowed. I haven't got the slightest idea how to do it. If anyone could help,I would be grateful.
Would convhull do what you need?