Hall effect sensors may be slightly temperature sensitive and if that is the case, that information would be in the sensors datasheet. (This wouldn’t be an issue on a hall effect counter where the sensor would be connected to a Schmitt trigger and the signal is either on or off.)
For a precision application like yours, there could be a few problems stacking up from a possible software issue combined with temperature drift.
If there are software issues, it could be as simple as a min/max issue with the buffer that stores the stick position. (It’s fairly easy to get rounding errors that stack up after a while.)
Obviously, I am spitballing some theories to why your calibration gets corrupted, so take them with a grain of salt. My limited experience with hall effect sensors has been that they are hyper-sensitve and I have usually had to code around any kind of drift or sporadic readings. Hell, anything that has a magnetic field (just about everything) can upset the readings on those things.
Gots any datasheets or specific part numbers for the hall effect sensors you are using? (I believe you listed some module types, but actual part numbers could change from module to module.)
There is very little information on the Hall Effect sensors on these modules!
www.youtube.com/ is one good (excellent!) source on installing these modules (problems and correct ways on installing them).
I forgot to say the exact modules in my post. They are the Ubituitous Ginfull sensors. These ones have L-8L (yellow) or R-8L (black) on the PCB, which is red and black text on it. Early Ginfull modules have problems with jitter (a non-issue, really), which was fixed in later batches but at the same time introducing an even worse problem, huge lag (presumably because of the filtering they’ve used to counteract the jitter). But these [LR]-8L’s should be better in terms of lag again.
The chips itself have markings “93L35”, they are 6-bin chips and tiny. I could not find their datasheets.
The well-known problem with these Hall Effect modules is that they only allow adjusting centering. So they will “work” in practically any controller out there, but more often than not there will be huge lopsided deadzone(s) caused by the H/W in combination with the previous calibration data. The SC is not that bad since it has some intelligence (I’ve deduced by test) but this can bring it’s own problems.
I’m not aware of any of the problems you’ve mentioned (but haven’t personally used DIY Hall Effect sensors in any controllers before).
There are calibration boards out there, which add a calibration mode between the controller and the module to also get the full range of movement in use. But Steam Controller has no room for those (the shell already has indentations for soldering spots and a mechanism for the back button, so this is feasible only if one is willing to sacrifice a back button or mod around it). Asides from centering and calibration (which needs to be manual!) there is no large issues AFAIK. They are widely installed in modern console controllers. PS4 and PS5 contorllers can even be calibrated (by undocumented USB commands), so they don’t need the boards.
Thanks for the additional info as it gave me a little more clarity on what kind of undertaking this is. I know electronics, but I really didn’t know the specifics of controllers. It didn’t take me long to get caught up, TBH.
That sucks. Before I was finished reading your full comment, I was already thinking of a way to intercept the signal for calibration. It seems that is already quite common and not easily possible for you.
My next thought was to 3D scan and print out a modified shell with a bit more room for electronics. Based on your description, that sounds tricky as well.
Whelp! I am effectively useless here and was hoping I could’ve helped a little. Doing extensive modifications to things is something I really enjoy, too.
Soju is the same thing as what we used to call “fortified” wine like Great White. It lures you in with 20% alcohol being sneaky enough to not immediately buzz you like liquor which then lowers your guard until suddenly you’re black-out drunk singing 80s Nami songs in the nearest noraebang. OH YEONG WON HAN CHINGU! OH HAENGBOK HAN MAEUM! OH JEUL GEO EUN INSAENG! YEAH!
3-4 beers isn’t even enough for me to get tipsy, much less drunk. I literally can’t understand how people get drunk off beer. I can drink the stuff until I’m literally full and just get nicely buzzed at best no matter how strong they make it. Which is fine, I prefer sweet stuff anyway. Mixed drinks and shots can actually get the job done on the rare occasion I actually feel like getting drunk.
ok so I don’t really drink alcohol, but some online friends got me to try soju. Grabbed some from the store and… I don’t get it. very much an alcohol taste to it. I can taste the plum in it, but it’s just not that great imo.
As an alcoholic, alcohol literally tastes bad and your brain only starts liking it once it recognizes the high. I mean it’s literally ethanol, a poison
I’m not an alcoholic, but used to drink wodka regularly when going out like decades ago. Even today when I smell non scented hand sanitizer, I can feel a little buzz in my brain.
Yeah and of the entire subgroup they pick furry talk to be drunk? Near every one of those cat fuckers are alcoholics. At minimum triple this. To really get that meow meow talk you’d need to convince one of those teetotaler tiny girls to drink but you know she won’t. Instead you’re trying to get an alcoholic 190lb man named Blaze drunk enough to start that kitty babble? Try six lol.
I had a good friend in college who had never touched alcohol before, finally convinced him to come out for a beer and he threw up wasted all over the table after 1 pint of beer
This might be happening because of the ‘elegant’ (incredibly hacky) way openai encodes multiple languages into their models. Instead of using all character sets, they use a modulo operator on each character, to make all Unicode characters represented by a small range of values. On the back end, it somehow detects which language is being spoken, and uses that character set for the response. Seeing as the last line seems to be the same mathematical expression as what you asked, my guess is that your equation just happened to perfectly match some sentence that would make sense in the weird language.
Can’t find the exact source–I’m on mobile right now–but the code for the gpt-2 encoder uses a utf-8 to unicode look up table to shrink the vocab size. github.com/openai/gpt-2/blob/master/…/encoder.py
There are bindings in java and c++, but python is the industry standard for AI. The libraries for machine learning are actually written in c++, but use python language bindings. Python doesn’t tend to slow things down since machine learning is gpu-bound anyway. There are also library specific programming languages which urges the user to make pythonic code that can be compiled into c++.
I suppose it’s conceivable that there’s a bug in converting between different representations of Unicode, but I’m not buying and of this “detected which language is being spoken” nonsense or the use of character sets. It would just use Unicode.
The modulo idea makes absolutely no sense, as LLMs use tokens, not characters, and there’s soooooo many tokens. It would make no sense to make those tokens ambiguous.
I completely agree that it’s a stupid way of doing things, but it is how openai reduced the vocab size of gpt-2 & gpt-3. As far as I know–I have only read the comments in the source code– the conversion is done as a preprocessing step. Here’s the code to gpt-2: github.com/openai/gpt-2/blob/master/…/encoder.py I did apparently make a mistake, as the vocab reduction is done through a lut instead of a simple mod.
This is flavored soju, which is usually around 10-12% abv and is sweetened. Very drinkable. Unflavored soju is a little less friendly if you don’t like tasting alcohol.
I’ve never had the flavored ones, but not really. It’s actually a very smooth drink. It’s a neutral spirit made from sweet potato so it tastes kind of like vodka, but without the bite because it’s half the alcohol content.
Look brother I don’t agree with your lifestyle but I will defend to the death your right to rawdog seventeen other anonymous partners in the local motel 6.
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