WaveFunctionCollapse VS PowerToys

Thank you! And yes, I agree. I was looking at uh https://github.com/mxgmn/WaveFunctionCollapse and wondering if that were applicable here :)

Have a good day!

Intuitively, it measures the difference between two probability distributions. It's not symmetric, so it's not quite that, but in my opinion, it's good intuition.

As motivation, say you're an internet provider, providing internet service to a business. You naturally want to save money, so you perhaps want to compress packets before they go over the wire. Let's say the business you're providing service to also compresses their data, but they've made a mistake and do it inefficiently.

Let's say the business has, incorrectly, determined the probability distribution for their data to be $q(x)$. That is, they assign probability of seeing symbol $x$ to be $q(x)$. Let's say you've determined the "true" distribution to be $p(x)$. The entropy, or number of bits, they expect to transmit per packet/symbol will be $-\sum p(x) lg(q(x))$. Meaning, they'll compress their stream under the assumption that the distribution is $q(x)$ but the actually probability of seeing a packet, $x$, is $p(x)$, which is why the term $p(x) lg(q(x))$ shows up.

The number of bits you're transmitting is just $-\sum p(x) lg(p(x))$. Now we ask, how many bits, per packet, is the savings of your method over the businesses? This is $-\sum p(x) lg(q(x)/p(x))$, which is exactly the Kullback-Leibler divergence (maybe up to a sign difference).

In other words, given a "guess" at a distribution and the "true" distribution, how bad is it between them? This is the Kullback-Leibler distribution and why it shows up (I believe) in machine learning and fitness functions.

As a more concrete example, I just ran across a paper talking [0] about using WFC [1] to asses how well it, and other algorithms, do when trying to create generative "super mario brothers" like levels. Take a 2x2 or 3x3 grid, make a library of tiles, use that to generate a random level, then use the K-L divergence to determine how well your generative algorithm has done compared to the observed distribution from an example image.

[0] https://arxiv.org/pdf/1905.05077.pdf

[1] https://github.com/mxgmn/WaveFunctionCollapse

Reminds me of wave function collapse - a programmatic way to generate mazes.

I am using WFC to generate the terrain, with pretty much a copy-paste implementation of the original WFC implemented into Unity.

If you still want to go the WFC route, the original WFC repository is a great place to start. There's also a (relatively barebones looking) Godot plugin you could take a look at.

wave function collapse studies - this is done with the https://github.com/mxgmn/WaveFunctionCollapse algorithm after I saw https://github.com/CodingTrain/Wave-Function-Collapse mention it. done in P5! IG https://www.instagram.com/ronivonu/

There’s an interesting approach similar to this called [Wave Function Collapse](https://github.com/mxgmn/WaveFunctionCollapse) (no relation to wfc in physics idea besides inspiration). It can infer the probabilistic constraints from one input example, and it seems to generalize quite well. Here’s a [little demo](https://oskarstalberg.com/game/wave/wave.html)

Windows PowerToys GitHub Repo

RunFlow is a cross-platform productivity tool which can launch apps and search files and more, that similar to Wox and PowerToys on Windows, and also similar like Alfred and Raycast on macOS. But we have differences with these tools, and we have our own unique new features. Right now, at the below, we will introduce you what features of RunFlow have been implemented in more details. It's an amazing journey, let's start.

I'm curious - when you were doing research into the mechanics of hinting options, did you stumble onto any relevant discussion around allowing custom pixel geometries to be defined, to enable hinting on modern OLED / WRBG displays? There's a good thread on the topic here[0], with some people referring to it as 'ClearType 2' on the MS side [1]. On the oss side I know FreeType theoretically supports this[2], but I can't quite figure out how relevant the FreeType backend is to this most recent work.

This is great work btw.

[0]: https://github.com/snowie2000/mactype/issues/932

[1]: https://github.com/microsoft/PowerToys/issues/25595

[2]: https://freetype.org/freetype2/docs/reference/ft2-lcd_render...

Thank you all for the informative advices. Here is the summary for those who are in the same situation:

1. Run Windows on Linux by using VM

for the applications you can’t run on Linux

Risks:

* some softwares may attempt to detect VMs and refuse running

* Anything what needs to touch hardware may not work.

2. separate "data" partition on D:

3. back up %APPDATA% and %USERPROFILE%

4. learn chocolatey, scoop or winget

Winget should be good enough

5. Don’t worry about C:\Program Files

6. (Mixed) Use/Don’t use Ansible (or saltstack/salt)

Use:

* Allows you to setup a new machine quickly and consistently when one breaks, get stolen, or lost in an inconvenient time.

* You can get a clean and consistent development environment so that you do not depend on anything accidentally installed on the machine.

* If you define specialised roles, create test playbooks for those individual roles, use these roles to compose more complex playbooks, and offload logic to custom ansible modules that are written in python, you won't wrestle with heavy logic in the template or playbook layer.

* installing software and pulling some configs and scripts down is fine

Don’t use:

* You will spend your days fighting a mix of yaml and Jinja.

* You will end up looking at Python errors because there are no static types.

* errors are cryptic.

7. Use WSL2

You need 32gb of ram, but ram is cheap so choose a good thinkpad

8. Debloat with Recommended Tweaks

Run

irm christitus.com/win | iex

from Administrator Terminal (Powershell)

The link leads to https://raw.githubusercontent.com/ChrisTitusTech/winutil/mai...

VirusTotal

https://www.virustotal.com/gui/file/709834b0e003b6bb546cf16e...

9. Get [PowerToys](https://github.com/microsoft/PowerToys)

10. Use Devbox for containered environment

https://www.jetpack.io/devbox

11. Dual-Booting Linux and Windows

If you use physically separated drives, you don’t need partitioning.

12. Dedicated Windows machine for class

Yes it sure would be the cleanest solution but I prefer one device for everything

13. keep a git repository with all dot files in it

Many people suggested me to use virtualization, otherwise just let Windows be Windows.

Also, backing up seems to be a good practice.

I’m planning to write a blog about this, if it worked.

Again, thank you all for the helps!

Powertoys Run (https://github.com/microsoft/powertoys) can do this. There are not that many plugins as Alfred but Window Switcher is built-in.

For sharing a mouse/keyboard between Windows PCs, there is Mouse Without Borders. It's included in PowerToys nowadays.

https://github.com/microsoft/PowerToys

- https://github.com/microsoft/PowerToys

If you’re on Windows, download PowerToys. It’s an app published by Microsoft officially. Then enable Quick Accent in the settings of PowerToys. Now all you have to do is hold down the key you want accented until the switch shows up, then add an accent with your arrow keys.

microsoft/PowerToys: Windows system utilities to maximize productivity (github.com)