11–20 of 36 posts
I find manually laying out graphs and digraphs tedious. It seems like a problem that should be amenable to machine learning approaches. Basically, training a machine as to what is an aesthetically pleasing layout and what is not. Are there layout engines that use machine learning for layout, as against being implemented in terms of specific tree or graph layout algorithms?
I loved using Tikz for my Discrete Math homework. I was so proud of how pretty the DFA's looked :)
DFAs and NFAs may seem like academic novelties but they are amazingly powerful for certain problems. For example, naively searching a string of length N for P different substrings will yield an algorithm that has roughly O(N * P) worst case time complexity. But implementing that algorithm as a DFA yields an efficient construction that has O(N) worst case time complexity. This results in considerable speedups for comp…
They are the same thing as regular expressions. It's safe to say they're not being dismissed as academic novelties.
So repulsed by this. Learning custom DSL with opaque semantics that will leave you scratching your head when something goes wrong and tool behaves not like you expect. Why people opt into such tools at all?
I haven't looked at that field for a good while but I'm still genuinely interested. And so I'd like to better understand your comment. It is unclear to me whether you are arguing in favor of using another similar tool using a better syntax, or using an automatic graph layout engine, or a manual general purpose vector drawing tool. How would you recommend one to draw such diagrams?
So repulsed by this. Learning custom DSL with opaque semantics that will leave you scratching your head when something goes wrong and tool behaves not like you expect. Why people opt into such tools at all?
So repulsed by this. Learning custom DSL with opaque semantics that will leave you scratching your head when something goes wrong and tool behaves not like you expect. Why people opt into such tools at all?
Tikz also allows a tight integration to LaTeX documents that no external tools achieve so easily. The drawing inherits colors and fonts, and bits can be reused across the document and can be shared with other documents too.
High learning curve but long term efficiency with quality results.
Tikz is not perfect but it has the great characteristic of existing.
I find manually laying out graphs and digraphs tedious. It seems like a problem that should be amenable to machine learning approaches. Basically, training a machine as to what is an aesthetically pleasing layout and what is not. Are there layout engines that use machine learning for layout, as against being implemented in terms of specific tree or graph layout algorithms?
If anyone writes a Graphviz tutorial, it would be doing the world a service to prefix it with "But seriously, note that Tikz exists".