I'm not sure machine learning is appropriate for graph layout. What a good graph looks like is already well known: no overlapping nodes, minimum line crosses, not too much 'white space'. But doing this layout automatically is very hard (NP complete?).
But, honestly, that kind of thing is the only valuable future for AI that I see, as a creative. I don't need it to write my code for me, but I could sure as hell use it to handle all the tedious bullshit that we've cobbled together as far as tooling, CI, formatting and any other "had to do it this way to make machines understand it" half-measure we've had to take in the past century. The AIs that we see, now, which learn from a huge dataset and then stay mostly inert until the next big update are more toy-like in my figuring. They are standards to measure against and proofs of all kinds of very interesting and useful concepts. But the lasting/useful AIs will be the ones that train alongside your work and ONLY on your work (or, let's face it, the work done in your company that will be shared amongst all corporate employees so that all work can be done more efficiently) in order to provide you with what you would be trying to do anyway.
Do you have any references besides Graphviz? I haven't seen much that does anything interesting in terms of weighted or constraint-based layouts.
https://saturncloud.io/blog/what-is-a-graph-autolayout-algor...
https://github.com/microsoft/automatic-graph-layout
https://github.com/kevtiq/digl
https://www.mindfusion.eu/graph-layout.html
https://reactflow.dev/docs/examples/layout/auto-layout/
What do you think 'tensor-based learning' or 'training data' would do for graph layout?
> What do you think 'tensor-based learning' or 'training data' would do for graph layout?
I didn't and don't have a comment on that.
I didn't and don't have a comment on that.
That's what I replied to and the question I asked.
If you want to group nodes by some context, why not just do it? This doesn't seem complicated to me. I don't know why there would need to be 'tensor based learning' 'machine learning' or even some one else's algorithm.
which I think is what is really required for interactive graphs.
Why would this be required for 'interactive graphs' and what does that mean? If you don't know of any graph that does this and you think it's required, do you have some definition of 'interactive graphs' that has never been done?
Ergo, vis-a-vi have you ever actually tried making a graph that is rearranging itself while you're using it?
Also what is the "AI" doing that can't be done with a normal algorithm? Positioning nodes in a graph would just be determining their x and y positions. How much time have you spent working with node graphs? Arranging the nodes is easier than arranging your keyboard and mouse, it's trivial.
People did; you didn't.
> Ergo, vis-a-vi have you ever actually tried making a graph that is rearranging itself while you're using it?
No one said anything about "while you're using it". Linters don't fuck up your text as you type it. It's a utility like anything else. And, YES, I have built a working version of one. It doesn't use machine learning/tensors at all, and it's a fucking nightmare to develop. I can see exactly where those things would help me. It's too abstract, to you, to understand? That's a shame! But other people seem to get it, so if you are having trouble, maybe try approaching your ignorance with openness and curiosity instead of cynicism and trivialization ('uncross some lines').
If you want to know how much time I've spent working on node edge graphs, you wouldn't believe me. But I can at least point you to the start of the web-component version I'm porting: https://github.com/catapart/Magnit.NodeGraph It's probably two years out of date at this point, as I've been integrating some of the algorithms for the specific need I have for these graphs (interactive dialog), but even from that anemic demo you can see that I know how to build the damn things. Again, you're trivializing for...some reason? I don't know. You seem to think you know more about me on this, and that's fine, but you don't really ever demonstrate that so I can't see your commentary as anything other than intransigent ignorance. Which was obvious from your first response, which is why this is my first (and last) direct response to you.
I hope you feel better about whatever it is that is causing you to have this reaction to a pretty obvious benefit that you, for whatever reason, seem too stubborn to engage with.
Your comment: cleaning up your graph as you code it,
I have built a working version of one. It doesn't use machine learning/tensors at all
Your comment: we could employ tensor-based learning methodology, like ChatGPT uses
How would that work on a technical level?
You keep throwing around insults like:
those that don't seek answers with an open mind will often fulfill their own disillusion
if the person you're responding to can't intrinsically understand what would be good
It's too abstract, to you, to understand? That's a shame!
But you seem to be melting down instead of answering the most basic questions about what you're talking about. How and why would you use "tensor-based learning" to layout a graph?
Again, you're trivializing for...some reason?
Because graph layout features were invented essentially right after people started using node graphs. If a node to the right of another node is connected to an input to the left and the node to the left is connected to the input on the right, their wires will cross.
so I can't see your commentary as anything other than intransigent ignorance
I asked the most basic follow up question to what you said and you think you're being persecuted. Where does the expectation come from to make some sort of wild claim and have no one at least ask how it's supposed to work?
What is all this stuff about being "stubborn" and "closed minded" when you haven't explained anything? Just back up what you're saying somehow.
whatever it is that is causing you to have this reaction
You mean asking basic follow up questions?