reox

Here is the best setup (I think so :D) for K-series Keychron keyboards on Linux.

Note: many newer Keychron keyboards use QMK as firmware and most tips here do not apply to them. Maybe the ones related to Bluetooth can be useful, but everything related to Apple's keyboard module (hid_apple) on Linux, won't work. As far as I know, all QMK-based boards use the hid_generic module instead. Examples of QMK-based boards are: Q, Q-Pro, V, K-Pro, etc.

Most of these commands have been tested on Ubuntu 20.04 and should also work on most Debian-based distributions. If a command happens not to work for you, take a look in the comment section.

Make Fn + F-keys work (NOT FOR QMK-BASED BOARDS)

Older Keychron keyboards (those not based on QMK) use the hid_apple driver on Linux, even in the Windows/Android mode, both in Bluetooth and Wired modes.

On my 2014 MacBook Pro (2.5 GHz), this vectorized version is about 250 times faster when used for a large numbers of triangles compared to the original algorithm. You can also parallelize this code over multiple threads, but due to the large overhead of creating a thread pool, this is only really useful when you have a very large number of rays.

I also tried to vectorize the rays, instead of using a loop. I did this by using:

np.reshape(np.array(np.meshgrid(np.arange(0, len(ray_direction), 1), np.arange(0, len(triangles_vertices), 1))), (2, resulting_array_length))

to create all combinations of indices of the rays and the triangles. However, using this process, combined with using np.take() to actually create these combinations is about twice as slow as the code below.

	#!/usr/bin/env bash
	#
	# This script replaces "ro.debuggable=1" with "ro.debuggable=0" in the
	# default.prop file in a ROM's boot.img and gives you the patched boot.img.
	#
	# Prerequisites:
	# - A UNIX system (with `unzip`)
	# - These tools added to your PATH:
	# - Android dev tools (adb/fastboot)
	# - Various tools in "bootimg_tools_7.8.13.zip" from https://goo.gl/48Sszu

	import gnu.trove.map.TObjectLongMap;
	import gnu.trove.map.hash.TObjectLongHashMap;

	import org.jf.dexlib2.Opcode;
	import org.jf.dexlib2.iface.ClassDef;
	import org.jf.dexlib2.iface.DexFile;
	import org.jf.dexlib2.iface.Field;
	import org.jf.dexlib2.iface.Method;
	import org.jf.dexlib2.iface.MethodImplementation;
	import org.jf.dexlib2.iface.instruction.Instruction;

	<?xml version="1.0"?>
	<!DOCTYPE fontconfig SYSTEM "fonts.dtd">
	<!--
	You need Noto Color Emoji installed in your machine.
	Save this file in ~/.config/fontconfig/conf.d/ or /etc/fonts/conf.d/ (system-wide)
	-->
	<fontconfig>

	<match target="scan">
	<test name="family">

	import numpy as np

	def find_closest_orthogonal_matrix(A):
	'''
	Find closest orthogonal matrix to A using iterative method.

	Bases on the code from REMOVE_SOURCE_LEAKAGE function from OSL Matlab package.

	Args:
	A (numpy.array): array shaped k, n, where k is number of channels, n - data points

	<span lang="face with tears of joy"> 😂 </span>
	<span lang="grinning face with smiling eyes"> 😄 </span>
	<span lang="grinning face with sweat"> 😅 </span>
	<span lang="face with rolling eyes"> 🙄 </span>
	<span lang="smirking face"> 😏 </span>
	<span lang="smiling face with halo"> 😇 </span>
	<span lang="grinning face"> 😀 </span>
	<span lang="squinting face with tongue"> 😝 </span>
	<span lang="grinning face with big eyes"> 😃 </span>
	<span lang="unamused face"> 😒 </span>

	<?xml version="1.0" encoding="UTF-16"?>
	<Task version="1.2" xmlns="http://schemas.microsoft.com/windows/2004/02/mit/task">
	<RegistrationInfo>
	<Date>2022-10-23T14:42:10.5827629</Date>
	<Author>handymenny</Author>
	<URI>\WireguardAutomatic</URI>
	</RegistrationInfo>
	<Triggers>
	<EventTrigger>
	<Enabled>true</Enabled>

	def program():
	from itertools import zip_longest
	import zlib
	import subprocess

	class Display:
	def __repr__(self) -> str:
	subprocess.run([
	"feh",
	"-xYFqZ",