4 ms·

for that matter, i always wonder how people mistake python for numpy :) they have surprisingly little in common. but enough talking about languages that suck.

by kelas 1y ago

for that matter, i always wonder how people mistake python for numpy :) they have surprisingly little in common. but enough talking about languages that suck. let's talk about python! i'm not some braniac on a nerd patrol, i'm a simple guy and i write simple programs, so i need simple things. let's say i want an identity matrix of order x*x. nothing simpler. i just chose one of 6 versions of python found on my system, create a venv, activate it, pip install numpy (and a terabyte of its dependencies), and that's it - i got my matrix straight away. i absolutely love it: np.tile(np.concatenate([[1],x*[0]]),x)[:x*x].reshape(*2*[x]) and now lets see just how obscure and unreadable exactly the same thing looks in k: (2#x)#1,x#0 no wonder innocent people end up with brain aneurisms and nervous breakdowns.

RodgerTheGreat 1y ago
i'm a fan of t=\:t:!x
- kelas 1y ago
  nice :) also see here: https://news.ycombinator.com/item?id=45603661 https://news.ycombinator.com/item?id=45603661 HN is such a sweetheart. i should check in more often.
- kelas 1y ago
  > t=\:t:!x this is of course obvious first idea, but the recipe from above is actually from the official k4 cookbook. t=t is less innocent than it seems, i'm afraid. in k7/k9, we can: 10^@[100#0.;11*!10;1.] /just for more lulz there's also a way to mutate it in place!
seanhunter 1y ago
That is wildly disingenuous. Assuming you've imported numpy as np, you get an nxn identity matrix by doing np.identity(n) http://numpy.org/doc/stable/reference/generated/numpy.identity.html http://numpy.org/doc/stable/reference/generated/numpy.identi...
- kelas 1y ago
  > That is wildly disingenuous. assuming you're referring to numpy as to have anything to do with python spec, i totally agree with you. only it doesn't. so don't pytorch and pandas (and good so, poor python doesn't need any extra help to be completely f). > you get an nxn identity matrix by... no, man, that's how you get it. really advanced technique, kudos! i get it by: id:{...} /there are many ways to implement identity in k, and it's fun! id 3 +1.00 +0.00 +0.00 +0.00 +1.00 +0.00 +0.00 +0.00 +1.00 but if you can keep a secret, more recently we've gotten so lazy and disingenuous in k land, and because we need them bloody matrices so often now, we just do it like so: &3 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 =3 +1.00 +0.00 +0.00 +0.00 +1.00 +0.00 +0.00 +0.00 +1.00 (but of course before we do that we first install python4, numpy, pytorch, pandas and polars - not because we need them, just to feel like seasoned professionals who know what they're doing)

by kelas 1y ago

RodgerTheGreat 1y ago

i'm a fan of t=\:t:!x

kelas 1y ago
nice :) also see here: https://news.ycombinator.com/item?id=45603661 https://news.ycombinator.com/item?id=45603661 HN is such a sweetheart. i should check in more often.
kelas 1y ago
> t=\:t:!x this is of course obvious first idea, but the recipe from above is actually from the official k4 cookbook. t=t is less innocent than it seems, i'm afraid. in k7/k9, we can: 10^@[100#0.;11*!10;1.] /just for more lulz there's also a way to mutate it in place!

seanhunter 1y ago

That is wildly disingenuous. Assuming you've imported numpy as np, you get an nxn identity matrix by doing np.identity(n) http://numpy.org/doc/stable/reference/generated/numpy.identity.html http://numpy.org/doc/stable/reference/generated/numpy.identi...

kelas 1y ago
> That is wildly disingenuous. assuming you're referring to numpy as to have anything to do with python spec, i totally agree with you. only it doesn't. so don't pytorch and pandas (and good so, poor python doesn't need any extra help to be completely f). > you get an nxn identity matrix by... no, man, that's how you get it. really advanced technique, kudos! i get it by: id:{...} /there are many ways to implement identity in k, and it's fun! id 3 +1.00 +0.00 +0.00 +0.00 +1.00 +0.00 +0.00 +0.00 +1.00 but if you can keep a secret, more recently we've gotten so lazy and disingenuous in k land, and because we need them bloody matrices so often now, we just do it like so: &3 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 +1.00 =3 +1.00 +0.00 +0.00 +0.00 +1.00 +0.00 +0.00 +0.00 +1.00 (but of course before we do that we first install python4, numpy, pytorch, pandas and polars - not because we need them, just to feel like seasoned professionals who know what they're doing)