Voronoi | Voronoi grid generator | Graphics library
kandi X-RAY | Voronoi Summary
kandi X-RAY | Voronoi Summary
Voronoi grid generator Creates 2D DXF voronoi pattern which can be used for 3D modelling, laser cutting, 3D printing and so on... Demonstration how this application looks & works:
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Trending Discussions on Voronoi
QUESTION
I have a data frame that looks like this and I want to create a circular voronoi diagram with it
...ANSWER
Answered 2022-Apr-08 at 16:55The linked picture is a Voronoi treemap. There is an R package called voronoiTreemap
you can use to create one yourself:
QUESTION
I would really appreciate it if someone can help me with the code below. I am trying to plot Voronoi cells for some random data points and I want to assign some colours. The to reproduce my work is provided below. As you can see in the plot, there are thick lines. I completely want to eliminate those lines. Is there any way to get rid of them? I want to fill the polygon but not have the line. Any recommendation is greatly appreciated.
I took most of the code from here
...ANSWER
Answered 2022-Mar-09 at 04:05You can pass linewidth=0
to plt.fill()
to get rid of the lines.
QUESTION
I need to calculate the distance between the furthest vertex of a Voronoi polygon and the point that generated it. I need to calculate this distance for all Voronoi polygons.
Is there a way to do it automatically in Python?
To generate the Polygon, I used Scipi. Do you have any tips or hints for me?
...ANSWER
Answered 2022-Feb-04 at 13:24Something like this could work:
QUESTION
I've build a graph with networkx, that looks like this: Graph
I want to fill every singel cell with a specified color. The Graph was drawn by nx.draw_networkx_edges() (returns a LineCollection). I found a similar question here (Fill area between lines), but the solution in the comments, doesn't worked for me.
I've also used plt.fill_between with a simpler graph and manually set the values:
...ANSWER
Answered 2022-Jan-26 at 17:10Using the first code block from the question that shows filling the simpler graph, I constructed an example network. The edges are listed below:
QUESTION
I have some points which illustrates heads of pedestrians during an experiment in each frame. I need to calculate which Voronoi Cells are in specific area - measurement square:
...ANSWER
Answered 2021-Dec-05 at 21:48I believe that your best bet is to use some kind of multiple polygon intersection algorithm using the cell vertices to describe the polygons.
You can whittle down the number of polygons by discarding those whose rightmost vertex is left of the blue rectangle, those whose leftmost vertex is to the right, and so on for up and down. This leaves you with the yellow polygons only.
You can also quickly eliminate (only, in this case you mark them as "intersecting") all those whose center or vertex lies inside the rectangle. This also is very quick.
In this example this is enough to locate all cells.
In other cases (for example, in the figure below, if the bottom-left yellow cell was shifted slightly upwards) you will have cells that have all vertices and the Delaunay center outside the rectangle, and yet one edge crosses it, so there is an intersection. To recognize those, you can exploit the fact that a rectangle is a convex figure, and check whether, among the cells you've left, there is one that contains at least one of the rectangle's corners. This is a slightly more complex check ("whether a point lies inside a convex polygon"), but not too complex since the cell is also convex and can be trivially decomposed in triangles.
The pseudo algorithm would be:
- for all Voronoi cells:
- get list of vertices.
- are they all left/below/above/right of the rectangle?
- YES: this cell does not intersect. Continue.
- for all the vertices plus the cell center:
- is this point inside the rectangle?
- YES: we have intersection. Report this cell and continue.
- decompose the cell in a list of triangles with vertex in the Delaunay center, taking ordered vertex pairs.
- for each triangle
- for each vertex of the rectangle
- is the vertex inside the triangle?
- YES: we have intersection. Report and continue
- for each vertex of the rectangle
- this cell does not intersect the rectangle.
QUESTION
I am trying to generate Voronoi split polygons and not able to understand the parameter 'furthest_site=True' in Voronoi's Scipy's implementation.
from scipy.spatial import Voronoi, voronoi_plot_2d
points = np.array([[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2], [2, 0], [2, 1], [2, 2]])
vor = Voronoi(points,furthest_site=True)
import matplotlib.pyplot as plt
fig = voronoi_plot_2d(vor) plt.show()
What is the explanation for attribute "furthest_site=True"
...ANSWER
Answered 2021-Oct-04 at 20:15scipy says it uses QHull to compute voronoi diagrams, and they have this in their documentation:
The furthest-site Voronoi diagram is the furthest-neighbor map for a set of points. Each region contains those points that are further from one input site than any other input site.
Furthest (or "farthest")-site diagrams are described in plenty of other places, including example diagrams; for example, in other stackexchange posts: 1, 2.
Your plot looks odd because your pointset is somewhat degenerate; only the four corner points ever serve as the furthest reference point.
QUESTION
I have a figure object returned by a function.
...ANSWER
Answered 2021-Oct-03 at 22:13You should create a fig, ax
object, and pass the ax
argument to the voronoi_plot_2d
as suggested in the comments by @Jody Klymak, like:
QUESTION
I would like to know how Delaunay triangulation can be done to find the connectivity of the cells formed by voronoi tessellation
The following is the code that I'm using to generate voronoi cells.
...ANSWER
Answered 2021-Oct-03 at 02:38vor.ridge_points
is a Nx2 array containing all the Delaunay edges. The values are the indices into the input array points
. For example, one edge goes from point number vor.ridge_points[0,0]
to point number vor.ridge_points[0,1]
.
QUESTION
I don't understand the return format of the ridge vertices for the function scipy.spatial.Voronoi. When using this function in 2D, the vertices are in pairs for one ridge, which is the format I expect, but in 3D, the number of vertices in ridges tends to have more than 2 points.
Why would a ridge need more than 2 points?
With some post-processing, can I simplify the format into 2 points per ridge?
Examples(The int in vor.ridge_vertices
refer to a point index in vor.vertices
)
ANSWER
Answered 2021-Aug-29 at 20:08In 2D, regions are separated by a single line segment, thus always 2 points per ridge. In 3D and up, regions separation "plane segments" are typically triangular, but they can have 4+ edges, too.
For sceletonization purposes, one approach would be to show the outline of the separation region, skipping virtual (-1) points. So, [3, 0, -1]
would translate to one line between points 3 and 0. [1, 0, 3, 2]
will generate segments 1-0, 0-3, 3-2, 2-1. As an additional improvement, ridges with 4+ points can be further split into trianges, so in case of [1, 0, 3, 2]
another segment would be 0-2 or 1-3.
I am still not sure if I got the question right, let me know if I didn't
QUESTION
How can we use D3.js, d3-delaunay
, to create a Voronoi background? The guide from the official page is really hard to follow. The example page is even worst. For example:
ANSWER
Answered 2021-Aug-10 at 19:11Here is a possible converted code. Notice that you can easily connect the DOM API with Observablehq abstractions, losing the reactivity from the Observablehq runtime.
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