Convex-hull | Convex hull of given 3D points | 3D Animation library
kandi X-RAY | Convex-hull Summary
kandi X-RAY | Convex-hull Summary
There is a method named Quickhull. The steps are mentioned in the wikipedia page.
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- Generate a simplex .
- Check if two planes are equal
- Calculate the horizon of a plane .
- Calculate to_do .
- Calculate the starting point .
- Calculates the distance between two points .
- Returns the maximum distance between two points .
- Calculate the maximum distance from a plane to a plane .
- Find the closest point in to_do_list .
- Sets the orientation of a plane .
Convex-hull Key Features
Convex-hull Examples and Code Snippets
Community Discussions
Trending Discussions on Convex-hull
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
I am trying to plot species range areas using convex hulls to then calculate the area and create a figure.
There is a well known issue with the 180 degree international dateline that I have been trying to remedy following many examples on SE, e.g:
How to remedy a path that crosses the international dateline with R
This comes close to what I am aiming for but plots in mapview not ggplot2: How to construct/plot convex hulls of polygons from points by factor using sf?
Here is my attempt:
...ANSWER
Answered 2021-Nov-13 at 13:56Please find below a solution to your problem. I used the function st_shift_longitude()
from the package sf
.
Reprex
- Your data (no changes)
QUESTION
I'm trying to build species distribution polygons for use in the R program rase. The program requires an owin object but sample data also includes a SpatialPolygonDataFrame. You can get the data yourself with: data(rase_data, package = 'rase')
I'm starting with a list of coordinates (lat/long per species). Thanks to this answer here, I've been able to make a polygon per element of the list (each species). I need to get to an owin object. Here's the dput of some test data and then code I've used to get where I'm at.
...ANSWER
Answered 2021-May-09 at 19:54I do not know sf
enough to fix this, so I show it via terra
but the important part is the sequence of operations. You can implement that in sf
again if you wish. There should be no need to revert to the old Spatial*
objects
Your data
QUESTION
I have an image which I'm using skimage to try and detect:
how many images are actually within the page - I'm expecting it to 'count' 5
find the corners of each image - so if it counts 5 above our maxCorners should be 5*4=20
draw straight lines between each corner and 'mask' each of the 5 images
right now all I got is the image being read, doing a fill holes and thats about it - guidance on the rest?
...ANSWER
Answered 2021-Jan-15 at 23:45This Answer was the key to solve this problem.
Coords:
[[(38, 11), (251, 364)], [(254, 62), (592, 266)], [(254, 312),
(592, 518)], [(46, 456), (247, 797)], [(346, 557), (526, 797)]]
QUESTION
I need to find whether some of my points are inside or outside a convex hull and I was using this answer: (enter link description here).
But when I test it, the array that is returned is slightly confusing. For example if I create two identical arrays, use one to create a hull and then test whether points of the second are in that hull I get the following:
...ANSWER
Answered 2020-Oct-12 at 02:18tl;dr: It returns the index of a triangle containing the point. And it does not always pick the same index if there are multiple triangles containing it.
I think you misunderstood "It returns:Indices of simplices containing each point. Points outside the triangulation get the value -1."
My interpretation is that Delaunay(pts_outer)
triangulates your rectangle with two triangles with the indices 0 and 1 respectively. Then hull.find_simplex(pts_inner)
retruning [0, 0, 1, 1]
means that your first two points are in triangle 0 and the 2nd two are in triangle one.
Finally it is a bit odd that find_simplex
now tells you your point [5, 5]
is in triangle 1. But that is not incorrect since the point [5, 5]
is in both triangles.
QUESTION
TLDR: I need to construct a python object for fast interior point testing, similar to a SciPy ConvexHull
or DelaunayTriangulation
. The catch is that I know ahead of time the order in which the triangulation of the points must be constructed: (6 points, 8 triangular faces, with a specific ordering of each face). In effect, I already know what the convex hull should be, but I need it in a form that I can use with existing (and optimised!) libraries (eg Scipy spatial). How can I do this?
Context: I need to construct a triangular prism (imagine a Toblerone bar - 2 end faces, 6 side faces, all triangular) in order to do some interior point testing. As I will have many such prisms lying adjacent to each other (adjacent on their side faces, imagine many Toblerone bars stood on their ends and next to each other), I need to be careful to ensure that no region in space is contained by two adjacent prisms. The cross section of the prism will not generally be uniform, hence the possibility of overlap between adjacent prisms, as illustrated by this diagram of the approximately planar face between two adjacent prisms:
...ANSWER
Answered 2020-May-02 at 12:55Half a solution... Not an exact solution to the original question, but a different way of achieving the same outcome. Any triangular prism can be split into exactly three tetrahedra (see http://www.alecjacobson.com/weblog/?p=1888). This is a specific case of the fact that any polyhedron may be split into tetrahedra by connecting all faces to one vertex, if the faces does not already include it.
Knowing exactly how I would like the face triangles of my prism to be arranged, I can work out what three tetrahedra would reproduce the same configuration of triangles (with extra faces of course being added inside the original prism itself). I then form Delaunay triangulations around each of these three tetrahedra (ie, collections of 4 points) in turn and perform the original interior point tests: if it matches on any then I have a positive result for the whole prism. The key point is that by only giving four points to the Delaunay constructor at a time, I know exactly what triangulation it will return as there is only one way of forming such a tetrahedra (assuming no geometric degeneracy).
It's a bit longwinded, and involves 3x as many tests as I would like, but it's a start. If anyone in the future does know how I could do this better please do let me know.
QUESTION
ANSWER
Answered 2020-Feb-03 at 12:57Thanks to shapely polygons, on which trimesh is built you don't need to go over the vertices. You can use some of the inbuilt functions. After creating your 2D path you are almost there. The path has two attributes: polygons_full
and polygons_closed
. The first one is the outmost polygon without the inner ones and the second one are all polygons of your path.
You can simply do:
QUESTION
When I build PCL library on Jetson TX2 from source via CMAKE, I get the following debug logs among other msgs:
...ANSWER
Answered 2020-Feb-03 at 06:11I found a file which was causing the CMAKE to include 10 sm_arch in compatibility list. Here's the link. I will re-compile after editing the file for just 1 sm_arch and compare the size of binaries generated. – Anuj Patil Jan 22 at 18:10
So findCUDA was the culprit here. Editing the files to required sm_arch does the trick!
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Install Convex-hull
You can use Convex-hull like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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