coolbutuseless, 2 months ago to random

Now that this pkg is actually in a state where it can do something useful, I can quickly realize some ideas for rendering. From idea to proof-of-concept render was ~15 minutes.

This is a ggplot object rendered into isometric layers.

It's just a shear + foreshortening transformation applied to the geometry, with points further offset in the y axis.

#RStats

#RStats

Isometric transformed ggplot with layer separation.

coolbutuseless, 2 months ago to random

This was a lot of work to get this new graphics device package to this point.

Yet it looks like I've done nothing at all :)

#RStats

animation of layers of a simple ggplot in R

coolbutuseless, 2 months ago to random

#RStats hivemind:

What's the current preferred solution for running multiple R versions on macOS?

rig?
rswitch?

something else?

coolbutuseless, 2 months ago to random

{zstdlite} update: cran has removed package after approval yesterday. :(

#RStats #JustCRANThings

coolbutuseless, 2 months ago to random

#RStats #RStatsMemes

The {R6} package is a godsend for turning my ad-hoc buffoonery into something tame and delightful!

Should I be converting to {S7} ?

https://cran.r-project.org/package=R6

coolbutuseless, 2 months ago to random

{xxhashlite} is now on CRAN!

Extremely fast hashing of R objects, files and raw vectors using 'xxHash'. R objects are hashed via the standard serialization mechanism in R. Raw byte vectors and strings can be handled directly for compatibility with hashes created on other systems.

https://cran.r-project.org/package=xxhashlite

#RStats

{xxhashlite} supports returning the hash as a raw vector, and all the xxHash algorithms are available
xxhash() uses R’s serialization mechanism to handle any R object. When you only require a hash of the raw contents of a file, a raw vector or a string, then use xxhash_raw() and xxhash_file(). Rather than serializing the data first, the hash is calculated on the raw bytes

coolbutuseless, 2 months ago to random

{zstdlite} is now on CRAN!

Fast compression/decompression of R objects, raw vectors, strings to/from memory and files.

Includes support for training and using compression dictionaries. Dictionaries offer significant compression and speed benefits for small data

A typical comparison against various settings for 'saveRDS()' is shown in the graph below

Executive summary: zstd can be extremely fast, but compression ratio can't match 'xz'

https://cran.r-project.org/web/packages/zstdlite/index.html

https://github.com/coolbutuseless/zstdlite

#RStats

coolbutuseless, 2 months ago to random

Survey: what new bit of syntax would you like in base #RStats?

What should the following bits of syntax do?

• ===
• ++ And --
• +=
• //
• ?
• {{ }}
• [[[ ]]]
• <<==
• (?: X)

henrikbengtsson, 2 months ago to random

FYI, CRAN requires package titles to be of length < 65 characters. Just received the following feedback for a new package:

> Please reduce the length of the title to less than 65 characters.

Do we have a community-driven place where we track these "hidden" CRAN requirements? I think there was a discussion about it, but I cannot remember if it happened.

#RStats

coolbutuseless, 2 months ago to random

My data workflow

#RStats

coolbutuseless, 3 months ago to random

Does someone know of a tarball/sqlite/something with lots of info about the packages on CRAN?

E.g. database of information from all DESCRIPTION files

I might just have to start my own CRAN mirror to mine for what I want....

#RStats

tylermorganwall, 3 months ago to random

Got my algorithm improvements working--now that's fast convergence!

#RStats

fast convergence of stippled points into a face

danwwilson, 3 months ago to random

How nice would it be if #RStats gracefully handled trailing commas in lists and vectors.

I bet no one can guess what is giving me the most grief today. 🤦‍♂️

coolbutuseless, 3 months ago to random

How to name your #RStats package: the complete guide. Part 2

coolbutuseless, 3 months ago to random

How to name your #RStats package: the complete guide.

coolbutuseless, 3 months ago to random

#RStats hypothetical: what would happen if I

• manually allocated some memory in C (with malloc)
• Crafted the memory to be an R object by writing a proper SEXP header for it
• Returned this to R

Would R consider this cuckoo object to be real? It wouldn't appear in the list of objects to be garbage collected - would that impact its validity?

#InvasionOfTheBodySnatchers

MattCrumpLab, 3 months ago to random

Had a bunch of fun with this one. Got some drum beats working with euclidean rhythms, and started on some compositional ideas with notes and stuff.

I put one 3-track sequence into Ableton and it didn't sound half bad. #midi #rstats #generativemusic

Too much coding for one day though, brain melt has set in.

https://homophony.quest/blog/44_2_10_24_euclid/

coolbutuseless, 3 months ago to cooking

#RStats #Cooking with {rhub2}

Package passing valgrind and clang-ASAN ! Woo!

https://github.com/r-hub/rhub2

odr_k4tana, 3 months ago to random

Do yourself a favour and don't use the {likert} package in #rstats. It apparently isn't maintained anymore, uses close to EOL functions (even whe it still was maintained) and its documentation + usability is crappy as heck.