delaunay | Python script for drawing triangles | Service Mesh library
kandi X-RAY | delaunay Summary
kandi X-RAY | delaunay Summary
Python script for calculating and drawing triangular meshes. The mesh is the Delaunay triangulation of a random assortment of points. For more details on how this works, see
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Top functions reviewed by kandi - BETA
- Construct a Delaunay triangulation of points
- Finds the triangle enclosing a set of points
- Creates a Line from a segment
- Calculate the vertices of two sides
- Calculate the color from the given gradient
- Calculate a color
- Turns a quaternion on a direction
- Draws a list of polys
- Convert cartesian coordinates to screen
- Draw a list of points
- Generate a list of equilateral triangles
- Generates a set of grid points
- Convert a hexadecimal value to a Color object
- Return a list of colors from the given image
- Generate random random points
- Generate the halton points
- Draw polygons
delaunay Key Features
delaunay Examples and Code Snippets
Community Discussions
Trending Discussions on delaunay
QUESTION
Am looking for something that is incremental (with accessible state). So that likely means some merge method is exposed.
So in general I want to start with a set of points, that has a ConvexHull calculated and add a point to it (which trivially has itself as a convex hull). Was looking for alternatives to BowyerWatson through convex hull merges. Not sure if this is a bad idea. Not sure if this should be a question in CS except it's about finding a real solution in the python echosystem.
I see some related content here.
Merging two tangled convex hulls
And Qhull (scipy Delaunay and ConvexHull use this) has a lot of options I do not yet understand
...ANSWER
Answered 2022-Apr-03 at 11:23You can use Andrew's modification of the Graham scan algorithm.
Here is a reference to some short python code implementing it.
What makes it suited for your needs is that after the points are sorted in xy-order, the upper and lower hulls are computed in linear time. Since you already have the convex hull (possibly both convex hulls), the xy-sorting of the convex hull points will take linear time (e.g., reverse the lower hulls and merge-sort four sorted lists). The rest of the algorithm will take linear time (in the number of points on the convex hulls, which may well be much smaller than the original number of points).
All the functionality for this implementation is in the code referenced above, and for the merge you can use the code from this SO answer or implement your own.
QUESTION
Required to turn an image into N triangles with Delaunay triangulation. One color for each triangle, and colors can be repeated. The loss function is given by the square of the difference in the color of each pixel. So how to optimize the color and the vertices of triangles?
...ANSWER
Answered 2022-Mar-13 at 23:09A recursive splitting procedure outline:
QUESTION
Im trying to port this sketch: https://codepen.io/giorgiomartini/pen/JjrOVXq?editors=1010 which uses a similar library: https://cdn.rawgit.com/ironwallaby/delaunay/master/delaunay.js, but I get only one triangle.
Here is my code: https://github.com/GiorgioRemindme/giorgio-martini/blob/main/src/sketches/tris.js
I think this is the problematic part:
...ANSWER
Answered 2021-Dec-27 at 22:19You are re-drawing the background every time you draw a Triangle: https://github.com/GiorgioRemindme/giorgio-martini/blob/main/src/sketches/tris.js#L92
QUESTION
See https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.Delaunay.html
Consider two sets of points. For each point in X_, I would like to find the nearest delaunay neighbours in "points". I think a slow way is to form Delaunay triangulations of points plus a points from X_ one at a time and then do the neighbours lookup somehow. Is there a more efficient way of doing this using scipy (or another tool)?
ANSWER
Answered 2021-Dec-19 at 20:42Ideally, the simplest solution would probably look something like this:
QUESTION
Created simple program based on 8.3 Example: a Constrained Delaunay Triangulation. And just wanna to export it to some common mesh file format like vtk, msh etc, to be able open it in GMesh or ParaView. To do so I found that most straightforward way is to use write_VTU. And at the beginning and at the end of example code I added next:
ANSWER
Answered 2021-Dec-17 at 08:16As documented here the face type of the triangulation must be a model of DelaunayMeshFaceBase_2. You can for example use Delaunay_mesh_face_base_2 like in this example.
QUESTION
I built an application using the Delaunay triangulation from Scypi. In order to validate it, I want to do a Hold-One-Out test, which means that the code snippet mentioned below gets called a lot of times (~1e9). Thus, I want to make it as fast as possible.
Here is the minimum working example I want to speed up:
...ANSWER
Answered 2021-Nov-11 at 20:42It's hard to say what exactly goes under the hood of the find_simplex method, but my guess is that in the first call it constructs some search structure and since you use it just once the construction initialization time isn't amortized on many queries.
A simple solution for this is to run a linear search, without calling the find_simplex method.
Since your code constructs a Delaunay triangulation each iteration, the runtime will be dominated by the triangulation construction and the linear search time is negligible.
Here is a vectorized numpy function that does that.
QUESTION
This is a follow-up to the post here.
I am trying to convert the simplices returned from Scipy's Delaunay Triangulation to a Networkx graph.
Code:
...ANSWER
Answered 2021-Nov-05 at 09:27I think you can remove the simplices from
QUESTION
I'm using Python 3.7.
There is a set of points. I generate Delaunay triangulation through these points.
...ANSWER
Answered 2021-Oct-20 at 08:05Have a look at my previous answer on identifying large edges in a Delaunay triangulation and plotting the results. The figure below was taken from there, where the large edges are colored in cyan. With small modifications it is suitable for your problem.
Note that you cannot remove edges from the Delaunay triangulation itself, as this will invalidate the triangulation.
The set of edges passing your criterion will therefore need to be represented in a separate data structure. In my answer they are represented as a set of (i, j) pairs, i.e., an edge list, which you can then construct a graph with, for example with the networkx library using the G.add_edges_from method.
QUESTION
I'm using Python 3.7. There is a set of points. I generate Delaunay triangulation through these points.
...ANSWER
Answered 2021-Oct-10 at 08:56We need to make three operations: convert triangles from Delaunay object to the set of edges (with removing duplicates), calculate length for each edge and select edges which meets the criterion.
Creating set of edges and calculation of lengths:
QUESTION
I built the Delaunay triangulation in python. Now I have 8 points (black) and generate 14 edges (gray). How can I count the length of the edge associated with each point？ the matrix I want is the edges' length connected by each point, such as
...ANSWER
Answered 2021-Oct-05 at 04:20Here's an approach which will give you a dictionary of points and edge lengths associated with each point:
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Install the requirements with pip install -r requirements.txt
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