Wolf, Wings optional

@wolfwings
6 Followers
2 Following
12 Posts
🇮🇹Hanno torto e non lasceremo che questo accada.🇺🇸They are wrong and we are not going to let this happen.🇲🇽Están equivocados y no vamos a dejar que esto suceda.
@anthracite Ask the facility the x-ray was taken at about their FOI process to get your own records. Often times they can e-mail a high-res scan of imaging taken.
@anthracite ...I do not understand why any website thinks "infinite scrolling" is remotely a good thing. No state, no bookmarks, no ability to pause. It's like a PvP-only MMO of web design. XD
@anthracite Also thank you, holy wow thats a different approach than I muddled through for that one! O.O
@anthracite Its ALMOST a binary tree, just four possible directions instead of two, and one of them is where you just came from so you'll never need to go that way at least!
@anthracite Thankfully its nowhere near as brutal as the credit-card one once I dug into it, that CC validation one still gives me headaches and your solution stomps all over the pitiful squeak-by I managed on that one! XD
@noxypaws Aaaah, yeah your waaay before needing to understand big-O math yet. Go learn/implement a heapsort, mergesort, and quicksort, research those and big-O tradeoffs will make more sense.
@noxypaws Or are you more wondering "Why is QuickSoft n² worst-case but MergeSort is n log(n) but they're BOTH n log(n) best-case?" to understand how you figure out the complexity of an algo?

@noxypaws In the case of programming, "Big O" is mostly adopting existing math terms because they fit, but a lot of the complex 'Big O math-theory' stuff doesn't actually help.

It really is as simple as my first toot, there's literally nothing more to it when discussing algo complexity.

http://bigocheatsheet.com/ is the 'building block' list for low-level algo components including storage to pick-and-choose.

Big-O Algorithm Complexity Cheat Sheet (Know Thy Complexities!) @ericdrowell

@noxypaws Well it sounds like you're reading mostly a book approaching things from a hard-math perspective, which isn't usually helpful from a programming perspective?

From programming it's pretty straight-forward: "Soak it in wood." I.E. More log = better algo as long as you can understand how to implement said 'better' algo.

@noxypaws Basically if there's any ∴ involved it's the mathematical meaning which is purely simplifying an equation to a single 'piece' in a (mathematically) well-defined way.