binaryfoundry

Please consider using http://lygia.xyz instead of copy/pasting this functions. It expand suport for voronoi, voronoise, fbm, noise, worley, noise, derivatives and much more, through simple file dependencies. Take a look to https://github.com/patriciogonzalezvivo/lygia/tree/main/generative

Generic 1,2,3 Noise

float rand(float n){return fract(sin(n) * 43758.5453123);}

float noise(float p){
	float fl = floor(p);
  float fc = fract(p);

Using VAAPI's hardware accelerated video encoding on Linux with Intel's hardware on FFmpeg and libav

Hello, brethren :-)

As it turns out, the current version of FFmpeg (version 3.1 released earlier today) and libav (master branch) supports full H.264 and HEVC encode in VAAPI on supported hardware that works reliably well to be termed "production-ready".

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

Gilbert–Johnson–Keerthi (GJK) 3D distance algorithm

The Gilbert–Johnson–Keerthi (GJK) distance algorithm is a method of determining the minimum distance between two convex sets. The algorithm's stability, speed which operates in near-constant time, and small storage footprint make it popular for realtime collision detection.

Unlike many other distance algorithms, it has no requirments on geometry data to be stored in any specific format, but instead relies solely on a support function to iteratively generate closer simplices to the correct answer using the Minkowski sum (CSO) of two convex shapes.

	function [maxtab, mintab]=peakdet(v, delta, x)
	%PEAKDET Detect peaks in a vector
	% [MAXTAB, MINTAB] = PEAKDET(V, DELTA) finds the local
	% maxima and minima ("peaks") in the vector V.
	% MAXTAB and MINTAB consists of two columns. Column 1
	% contains indices in V, and column 2 the found values.
	%
	% With [MAXTAB, MINTAB] = PEAKDET(V, DELTA, X) the indices
	% in MAXTAB and MINTAB are replaced with the corresponding
	% X-values.

	#!/usr/bin/python2


	# Copyright (C) 2016 Sixten Bergman
	# License WTFPL
	#
	# This program is free software. It comes without any warranty, to the extent
	# permitted by applicable law.
	# You can redistribute it and/or modify it under the terms of the Do What The
	# Fuck You Want To Public License, Version 2, as published by Sam Hocevar. See

	#include <iostream>
	#include <vector>
	#include <cmath>
	#include <cstring>
	#include <cstdlib>
	#include <cstdio>
	#include <cassert>

	using namespace std;

	/*
	@geofftnz

	Just mucking around with some fake scattering.
	Trying to come up with a nice-looking raymarched solution for atmospheric
	scattering out to the edge of the atmosphere, plus a fast non-iterative version
	for nearer the viewer.

	Some code pinched from here: http://glsl.heroku.com/e#17563.3
	and here: http://codeflow.org/entries/2011/apr/13/advanced-webgl-part-2-sky-rendering/

	#extension GL_EXT_shader_texture_lod : enable

	uniform samplerCube uRadianceMap;
	uniform samplerCube uIrradianceMap;

	#define saturate(x) clamp(x, 0.0, 1.0)
	#define PI 3.1415926535897932384626433832795


	const float A = 0.15;

	#!python
	def savitzky_golay(y, window_size, order, deriv=0, rate=1):
	r"""Smooth (and optionally differentiate) data with a Savitzky-Golay filter.
	The Savitzky-Golay filter removes high frequency noise from data.
	It has the advantage of preserving the original shape and
	features of the signal better than other types of filtering
	approaches, such as moving averages techniques.
	Parameters
	----------
	y : array_like, shape (N,)