adamnemecek

For background and further references see: Entity Component Systems on Wikipedia

ECS by Scott Bilas (GDC 2002)

Entity->Components->Update

• entity = class: no logic + no data OR at most small set of frequently used data (ie position)
• component = class: logic + data

foreach entity in allEntities do
    foreach component in entity.components do

adamnemecek

-- credit goes to sigfpe
{-# LANGUAGE MultiParamTypeClasses
    ,TemplateHaskell
    ,GeneralizedNewtypeDeriving
    ,DeriveFunctor
    ,FunctionalDependencies
    ,FlexibleInstances
    ,UndecidableInstances
    ,FlexibleContexts
    ,Rank2Types #-}

adamnemecek

//
// MIT License
// Copyright (c) 2017 Lachlan Hurst
// 
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:

adamnemecek

Keybase proof

I hereby claim:

• I am adamnemecek on github.
• I am adamnemecek (https://keybase.io/adamnemecek) on keybase.
• I have a public key ASAYuMz0BsFIrC7WD0_ZdesQuR0yrAOmRH6ZJlp_7CF-1wo

To claim this, I am signing this object:

adamnemecek

Courses

• Learning from data, course by Professor Yaser Abu-Mostafa

• http://courses.cs.washington.edu/courses/cse446/13sp/

• http://cs.nyu.edu/~dsontag/courses/ml13/

• http://holehouse.org/mlclass/

• ML, level 1 by Prof. Andrew Ng: Machine Learning, Website

• ML, level 1 by Prof. Andrew Ng: Machine Learning, Website, Lecture Notes, Videos

• ML, level 1 by Prof. Nando de Freitas: Machine Learning & Data Mining, Website, Lecture Notes, Videos

• ML, level 2 by Prof. Nando de Freitas: Machine Learning, Website, Lecture Notes, [Videos](https://www.youtube.com/playlist?list=PLE6Wd9FR--EdyJ5lb

adamnemecek

enum Sharp: Int { case C = 0, G, D, A, E, B, F }

func sKeyForNote(n: Sharp) -> [Sharp] {
  return (0..<n.rawValue)
    .map{ n in (n + 6) % 7 }
    .flatMap(Sharp.init)
}

enum Flat: Int { case F = 1, B, E, A, D, G }

adamnemecek

enum Expr {
  case Lit(Int)
  indirect case Neg(Expr)
  indirect case Add(Expr,Expr)
  indirect case Mul(Expr,Expr)
  indirect case Sub(Expr,Expr)
}

let spaces = many(oneof(" \n\r"))
func token<P: ParserType>(p: P) -> Parser<P.A> {

adamnemecek

func encode<T>(var value: T) -> NSData {
    return withUnsafePointer(&value) { p in
        NSData(bytes: p, length: sizeofValue(value))
    }
}

func decode<T>(data: NSData) -> T {
    let pointer = UnsafeMutablePointer<T>.alloc(sizeof(T.Type))
    data.getBytes(pointer)
    

adamnemecek

"""
Exercises for the Markov Chain Monte-Carlo (MCMC) course available at

http://users.aims.ac.za/~ioana/
"""

import numpy as np
import numpy.linalg as la
import pylab
from scipy import stats

adamnemecek

func responderForType<T>(from: UIResponder) -> T? {
  var current = from
  while let next = current.nextResponder() {
    if let result = next as? T { return result }
    current = next
  }
  return nil
}