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Cake day: June 16th, 2023

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  • Ig thats where most of my confusion comes from, to me saying sth is a “spectrum” always evokes sth along the lines of gay <--------------------> straight (ie one dimensional) with things mapping into this interval. But ig if you also include more than one axis in your meaning of “spectrum” there wouldn’t be as straight forward of an ordering for any given “spectrum”. + Like @[email protected] said technically even the 1 dimensional spectrum can have more than one order and the “obvious” one is just obvious because we are used to it from another context not because its specifically relevant to this situation.




  • It’s fixed in 6.8.10 and 6.9 if you have the ability to upgrade to those.

    Honestly idk how id even begin to do that lol, and id also maybe rather not start my first week of linux use by immediately trying to change the kernel version on my own XD (either down or up). I did hear about an issue with rdr2 and kernel 6.8.9 from a reddit post which i found through someone writing about problems with the game on its protondb page. But i thought i was fine as my game worked normally until i encountered the crash & because the reddit and protondb post say its solved by enabling rebar which (iirc) i already have.

    However idk if that reddit posts issue is the same/related to the one you linked. Since the rest of the game and my system seem to be mostly fine i think ill either just not play the game or specifically avoid the cutscene when i do (its in an optional quest luckily). And then ill maybe return to it after the updated kernel arrives on fedora to see if it solves the crash or not.




  • Ti_Ka@lemmy.blahaj.zonetoScience Memes@mander.xyzCalculus made easy
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    6 months ago

    I feel like this isn’t quite fair to math, most of these can apply to school math (when taught in a very bad way) but not even always there imo.

    Its true that math notation generally doesn’t give things very descriptive names, but most of the time, depending on where you are learning and what you are learning, symbols for variables/functions do hint at what the object is supposed to be E.g.: When working in linear algebra capital letters (especially A, B, C, D as well as M) are generally Matrices, v, w, u are usually vectors and V, W are vector spaces. Along with conventions that are largely independent of the specific math you are doing, like n, m, k usually being integers, i or j being indices, f and g being functions and x, y, z being unknowns.

    Also math statements should be given comments too. But usually this function is served by the text around the equations or the commentary given along side them, so its not a direct part of the symbolic writing itself (unlike comments being a direct part of source code). And when a long symbolic expression isn’t broken up or given much commentary that is usually an implicit sign that it should be easy/quick for the reader to understand/derive based on previously learned material.

    Finally there’s also the Problem with having to manipulate the symbols. In Code you just write it and then the computer has to deal with it (and it doesn’t care how verbose you made a variable name). But in math you are generally expected to work with your symbolic expressions and manipulate them. And its very cumbersome to keep having to rewrite multi-letter names every time you manipulate an expression. Additionally math is still generally worked on in paper first, and then transferred into a digital/printed format second, so you can’t just copy + paste or rely on auto completion to move long variable names around, like you might when coding.







  • Ok so it seems like they don’t commute? I asked the question in part because i wanted to do something like:

    const base_transform : Transform3D = <some transform>
    
    func get_base_transform(node : Node3D) -> Transform3D:
        return node.transform * base_transform
    
    func set_base_transform(node : Node3D, transform : Transform3D) -> void:
        node.transform = base_transform.affine_inverse() * node.transform
    

    and i wanted to be sure that if i do set_base_transform(some_node, some_transform) i’d be guaranteed to get that get_base_transform(some_node) == some_transform afterwards. But when i tried it the above code did not work out, at least i didnt get the result i expected. But when i flipped it so that set_base_transform did node.transform = node.transform * base_transform.affine_inverse() instead it did work out. Its still not hard proof though, maybe something else was messed up the first time, or it only looks like it works now and i’ll discover the transform still isn’t what i wanted it to be. Or they do commute but only under some constriction like no scale on any axis or something and i just happened to fulfill it with all the ones i used in my test.

    So it would still be good to know for sure whether/when Transform3D’s commute.

    EDIT: I accidentally wrote the first line wrong, it said that they do commute. When actually the experience i had with it working only after both functions did their multiplications in a compatible order should indicate that they don’t commute.