marmakoide’s gists

marmakoide / network.sh

Last active January 4, 2021 11:02

Shell script that generates a string describing network connection status, to use with dwmblocks and Font Awesome

	#!/bin/sh

	ETH_IT=enp3s0
	WLAN_IT=wlan0

	is_eth_used=$(cat /sys/class/net/${ETH_IT}/carrier)
	is_wlan_used=$(cat /sys/class/net/${WLAN_IT}/carrier)

	if [ "$is_eth_used" -eq 1 ]; then # wired network is carrying
	icon="" #uF6FF

marmakoide / solarized_rgb_map.py

Last active March 17, 2021 06:46

The solarized color scheme as a Python map associating a color name to a RGB triplet

	solarized_rgb_map = {
	"base03" : (0x00, 0x2b, 0x36),
	"base02" : (0x07, 0x36, 0x42),
	"base01" : (0x58, 0x6e, 0x75),
	"base00" : (0x65, 0x7b, 0x83),
	"base0" : (0x83, 0x94, 0x96),
	"base1" : (0x93, 0xa1, 0xa1),
	"base2" : (0xee, 0xe8, 0xd5),
	"base3" : (0xfd, 0xf6, 0xe3),
	"yellow" : (0xb5, 0x89, 0x00),

marmakoide / nord_rgb_map.py

Last active March 17, 2021 06:46

The nord color scheme as a Python map associating a color name to a RGB triplet

	nord_rgb_map = {
	"nord0" : (0x2e, 0x34, 0x40), # dark 1 (darkest)
	"nord1" : (0x3b, 0x42, 0x52), # dark 2
	"nord2" : (0x43, 0x4c, 0x5e), # dark 3
	"nord3" : (0x4c, 0x56, 0x6a), # dark 4
	"nord4" : (0xd8, 0xde, 0xe9), # bright 1
	"nord5" : (0xe5, 0xe9, 0xf0), # bright 2
	"nord6" : (0xec, 0xef, 0xf4), # bright 3 (brightest)
	"nord7" : (0x8f, 0xbc, 0xbb), # blue 1 (closest to green)
	"nord8" : (0x88, 0xc0, 0xd0), # blue 2

marmakoide / base16_rgb_map.py

Created March 17, 2021 07:12

The base16 color scheme as a Python map associating a color name to a RGB triplet

	base16_rgb_map = {
	"base00" : (0x15, 0x15, 0x15), # Default Background
	"base01" : (0x20, 0x20, 0x20), # Lighter Background (Used for status bars, line number and folding marks)
	"base02" : (0x30, 0x30, 0x30), # Selection Background
	"base03" : (0x50, 0x50, 0x50), # Comments, Invisibles, Line Highlighting
	"base04" : (0xb0, 0xb0, 0xb0), # Dark Foreground (Used for status bars)
	"base05" : (0xd0, 0xd0, 0xd0), # Default Foreground, Caret, Delimiters, Operators
	"base06" : (0xe0, 0xe0, 0xe0), # Light Foreground (Not often used)
	"base07" : (0xf5, 0xf5, 0xf5), # Light Background (Not often used)
	"base08" : (0xac, 0x41, 0x42), # Variables, XML Tags, Markup Link Text, Markup Lists, Diff Deleted

marmakoide / zyx-quaternion.py

Created February 10, 2022 08:04

Quaternion from ZYX intrisic Euler angles (Z rot, then local -Y rot, then local X rot)

	import numpy


	def zyx_to_quaternion(z_angle, y_angle, x_angle):
	cos_x, sin_x = numpy.cos(x_angle / 2), numpy.sin(x_angle / 2)
	cos_y, sin_y = numpy.cos(y_angle / 2), numpy.sin(y_angle / 2)
	cos_z, sin_z = numpy.cos(z_angle / 2), numpy.sin(z_angle / 2)

	return numpy.array([
	cos_x * cos_y * cos_z - sin_x * sin_y * sin_z,

marmakoide / voxelize.py

Last active February 21, 2022 18:24

Voxelize a watertight mesh as a Numpy NxNxN array. All the mesh interior is filled, no spatial acceleration structures, as vectorized as I could make it. Works only if all the triangles are within the cube 0x0x0 => NxNxN

	def get_z_line_triangles_intersections_generator(triangles):
	# Precompute everything that is independent from the ray origin
	Z = numpy.array([0., 0., 1.])

	tri_AB = triangles[:, 1] - triangles[:, 0]
	tri_AC = triangles[:, 2] - triangles[:, 0]
	tri_H = numpy.cross(Z, tri_AC)
	tri_a = numpy.sum(tri_AB * tri_H, axis = 1) # dot product along axis 0

	# Remove all triangles on a plane parallel to the ray

marmakoide / antialiased_disk_mask.py

Created July 18, 2022 15:24

Generates a very accurate antialiased disk, without super sampling a very large bitmap. Works correctly only for even values of N.

	import numpy
	import scipy.integrate as integrate

	def get_disk_mask(N):
	def F(x):
	return (1 - x 2) .5

	# Build a quarter
	M = N // 2
	quarter = numpy.zeros((M, M))

marmakoide / power-circumcenter.py

Last active September 8, 2022 12:50

Computes the N-dimension circumcenter of N + 1 points (the S array) and their N + 1 radiis (the R array)

	import numpy

	def get_power_circumcenter(S, R):
	R_sqr = R ** 2

	Sp = S[1:] - S[0]
	Sp_norm_sqr = numpy.sum(Sp ** 2, axis = 1)

	U = ((Sp_norm_sqr + R_sqr[0] - R_sqr[1:]) / (2 * Sp_norm_sqr))[:, None] * Sp + S[0]

marmakoide / power-triangulation.py

Last active September 19, 2022 09:53

Computes power triangulation in N dimensions

	import numpy
	from scipy.spatial import ConvexHull


	def is_oriented_simplex(S):
	M = numpy.concatenate([S, numpy.ones((S.shape[0], 1))], axis = 1)
	return numpy.linalg.det(M) > 0


	def get_power_triangulation(S, R):

marmakoide / vectorized-julia.py

Created September 12, 2022 19:32

Demonstrates how to compute a Julia fractal efficiently in pure Python + Numpy

	import numpy
	from matplotlib import pyplot as plot

	N = 256
	C = -0.4 + 0.6j
	max_epoch_count = 1024

	# Initialization
	T = numpy.linspace(-2., 2., N)
	X = numpy.tile(T, (N, 1))

Devert Alexandre marmakoide