The playlist is perfect. Can I look forward to a video of you making a simple/complex CAM (Computer Aided Manufacturing) tool path. It's something I'm constantly learning and being exposed to.
It is a bit unrelated to CAD-like modeling, but is there an efficient way to build a Delaunay triangulation for 3D simplices (4 vertices forming a tetrahedron) and even ND simplices (ND-hypertetrahedrons)? It seems like the algorithm would be similar, I am just not quite sure about the condition of diagonal swapping. Instead of the conditions proposed by Sloan (COSA, COSB, etc), I derived a more general condition that a couple of triangles must swap a diagonal if the centers of mass of the new triangles are going to be further from each other than in the original triangles. I implemented such triangulation, it seems to give nice triangles in 2D case similar to the classical algorithm. Now I am stuck at a multidimensional case, I cannot prove that maximizing the distances from the centers of mass is equivalent to the original Delaunay condition. For those who might wonder why would I need ND-simplices - they are related to phase diagrams and naturally appear if I have chemical compounds A, B, C, D mixed together forming a mesh of compositions AxByCzDw with x+y+z+w = 1. Even more, some compositions are joined by an equilibrium condition (for example, a complex liquid composition coexisting with a complex solid composition) which is identical to having constraining edges.
I'm doing a project where I have to find the MST with 205000 nodes with latitude and longitude coordinate, the only solution that I've found to avoid doing a complet graph is to implement this. I've tested your implementation with a part of my data and I don't understand why it stucks with some precise points ... Maybe we can discuss about this ? Thanks ! PS : By the way don't forget to free you malloc/calloc
And here I am in 3:56AM watching how random guy has coded triangulation in ancient programming language. Why? Because I need proximity input mode for my VR keyboard.
no books explicitly, mostly academic papers on the different topics (check google scholar). i do have 1 very good book on "old-fashioned" computational geometry: "Computational Geometry for Design and Manufacture" by Faux & Pratt which I found in a dumpster. PM me on discord for a electronic copy: pacelli#5727
![CAD From Scratch [17] | Constrained Delaunay Triangulations](http://i.ytimg.com/vi/_Pe-Raurn34/mqdefault.jpg)
![CAD From Scratch [17] | Constrained Delaunay Triangulations](/img/tr.png)
this is the only video that is worth watching about Delaunay triangulation. I also love the unique style. thank you!
Exactly this explanation + coding I am finding whole day... thank you!
The playlist is perfect. Can I look forward to a video of you making a simple/complex CAM (Computer Aided Manufacturing) tool path. It's something I'm constantly learning and being exposed to.
It is a bit unrelated to CAD-like modeling, but is there an efficient way to build a Delaunay triangulation for 3D simplices (4 vertices forming a tetrahedron) and even ND simplices (ND-hypertetrahedrons)? It seems like the algorithm would be similar, I am just not quite sure about the condition of diagonal swapping. Instead of the conditions proposed by Sloan (COSA, COSB, etc), I derived a more general condition that a couple of triangles must swap a diagonal if the centers of mass of the new triangles are going to be further from each other than in the original triangles. I implemented such triangulation, it seems to give nice triangles in 2D case similar to the classical algorithm. Now I am stuck at a multidimensional case, I cannot prove that maximizing the distances from the centers of mass is equivalent to the original Delaunay condition. For those who might wonder why would I need ND-simplices - they are related to phase diagrams and naturally appear if I have chemical compounds A, B, C, D mixed together forming a mesh of compositions AxByCzDw with x+y+z+w = 1. Even more, some compositions are joined by an equilibrium condition (for example, a complex liquid composition coexisting with a complex solid composition) which is identical to having constraining edges.
I'm doing a project where I have to find the MST with 205000 nodes with latitude and longitude coordinate, the only solution that I've found to avoid doing a complet graph is to implement this. I've tested your implementation with a part of my data and I don't understand why it stucks with some precise points ... Maybe we can discuss about this ? Thanks !
PS : By the way don't forget to free you malloc/calloc
Hi. Thanks for your video!
How do you handle the case when point is located on an existing edge, which belongs two triangles?
Now I know. The algorithm handle both point located within triangle and on triangle edge similarly. No modifications required
And here I am in 3:56AM watching how random guy has coded triangulation in ancient programming language. Why? Because I need proximity input mode for my VR keyboard.
Very impressive content on your channel. Who are you?
Wow awesome
What books do you use to create your CAD?
no books explicitly, mostly academic papers on the different topics (check google scholar). i do have 1 very good book on "old-fashioned" computational geometry: "Computational Geometry for Design and Manufacture" by Faux & Pratt which I found in a dumpster. PM me on discord for a electronic copy: pacelli#5727