Here are some of the things I use to increase the range of programs for which I can use vi keybindings:
* vscodevim extension for Vscode
* "set -o vi" in Bash
* Vim Vixen plugin for Firefox
* you can use ctrl-alt-j in gdb. And that might (should?) work in other programs which use GNU Readline to get vi keybindings. The only thing I miss with the vi bindings in bash/readline is "ge/gE" from vim (move backwards to the end of the word).
Chapter 4 of "The Art of Prolog" ("The Computation Model of Logic
Programs") is about that very topic. It doesn't go into gory details on how to optimize an interpreter for fast execution, but it does go into enough detail that I was able to create a Prologish interpreter in ~30 lines of Haskell many years ago. Apparently "The Art of Prolog" is a free download now (there is a PDF link on the left side of the page).
...since you have been interested in the matrix form of sqrt(-1), I thought you might also be interested in the book I recently came across as well, "The Naked Spinor: A Rewrite of Clifford Algebra".
...I can't recommend it, since I haven't read it yet. But from the introduction it sounds pretty interesting:
"Some ten years ago, your author stubled upon a change in the notation we use to write complex numbers. Instead of writing a complex number as a+ib, your author began to write a complex number as a 2x2 matrix. From nothing more than this change of notation, your author discovered the higher dimensional complex numbers. The higher dimensional complex numbers include the whole of Cliffor algebra and, with that, the whole of spinor theory. The change of notation simplifies and generalizes Clifford algebra and spinor theory."
Sorry for derailing your GitHub thread with an off-topic comment.
What is so special about transistors? There are many non-linear active devices that are relatively unexplored due to the local maximum of transistors. How about homemade flame triodes or magnetic amplifiers or memristor.. I think you are going to love these guys:
That sounds like the traditional method of learning math. I was wondering if we could leverage technology and our experiences with teaching/learning the formal systems of programming languages to make more math more accessable. For instance, I'm thinking this little instance of geometric algebra:
...might be easier for me to understand if I could use Haskell to implement the wedge and geometric product operators on an algebraic data type describing the scalar/vector/bi-vector thingy. There is probably an applied vs. pure thing here as well. My motivations for investigating geometric algebra is to see if geometric algebra makes synthesizing mechanical linkages easier, whereas maybe most expositions on geometric algebra are focused on teaching geometric algebra to advance the state of geometric algebra. That's probably a long winded way of saying that mathematicans are writing for mathematicians (whether by design or accident). I suppose I should re-read Mindstorms again, but this time in the context of adult learning.
I also what a running commentary would do for authors. Would they get ideas for improving their next paper, by looking at what had people confused? Surprised by who is reading their papers (especially those outside of their field)? Would they merely be horrified by YouTube style commenters?
I'll accept the premise, but I still wonder if there are things that can be done to make it easier for someone. In my case, I've been trying to learn some more mathematics recently, and one of the most annoying things is coming across notation that isn't defined in a paper, presumably because "everyone" who can read the paper is familiar with the context and knows what the "skinny long arrow" means (good luck with that internet search). I wonder if there could be a wiki-like / forum / stackoverflowish site, which people could use to discuss and provide running commentary on a paper/book. Especially useful would be the ability for people to be able to annotate the paper by translating the formulas in to a formal language where you could track down the definition of the various operators, and try to figure out why the author used both of → and ↦ in the paper, when they both appear to be for functions/maps. (Just to preempt the easy objections, I'm not trying to suggest that each paper be formalized and proven in something like Isabelle/Coq).
In the ideal form, this website would allow you to see the paper or book page in question, and then see all the people who commented or had questions on each particular sentence (in the margin?). There could be filtering and voting so that experts could bypass the newbie commentary, etc..
I suppose part of my problem would be solved by getting a book like:
...(which I just came across when composing this message).
Maybe someone has a other suggestions for something like this? Maybe a site similar to this already exists?
And on a slightly related note to making things easier to learn, I think learning programming is much easier than math, because even though both are abstract, at least with programming you get a tangible, concrete thing (the program) that you can run and modify and extend, and the computer will tell you when you went wrong (e.g. won't compile, output result is unexpected, etc.).
Your mention of deliberate practice prompted me reinvestigate the guy who was doing the 10,000 hours of deliberate practice to become a golf pro. Unfortunately, from what I can tell, he did get to 10,000 hours, but it doesn't seem like it panned out. Anyone have further sources of information?
https://duckduckgo.com/?q=realsense+"failed+to+recconect"