jonathanBieler

using Plots, Statistics, ImageFiltering

##

N = 200
img = zeros(N,N) 
img[80:120,80:120] .= 1
img = img .+ rand(N,N)*0.5

heatmap(img)

jonathanBieler

#=
# Port of Peter Norvig's Common Lisp program from http://norvig.com/java-lisp.html.
#
# - Julia version: 1.6.2
# - Author: Renato Athaydes
# - Date: 2021-07-24
=#
const emptyStrings = String[]

function printTranslations(io, dict, num, digits, start=1, words=String[])

jonathanBieler

using Clang
import Clang, Clang.cindex

#include("gtk_get_set_gen.jl")

extension(f::String) = splitext(f)[2]
filename(f::String) = splitext(f)[1]

include_path = "/Users/bieler/Downloads/SDL2-2.0.5/include/"

jonathanBieler

using MacroTools, MLStyle, Test

subst(a) = MLStyle.@match a begin
    :(sin($x)) => :(cos($x + 1))
    _ => a
end
MacroTools.prewalk(subst, quote
    sin(x + sin(x))
end)
 

jonathanBieler

using ApplicationBuilder, GtkREPL, Compat
cd("/Users/jbieler/.julia/dev/GtkREPL/")

builddir = "/Users/jbieler/.julia/dev/GtkREPL/builddir/GtkREPL.app/Contents/Libraries/"
r = s->joinpath("/Users/jbieler/.julia/",s)

#Gtk libs
gtk_libs = [
    :libgdk,
    :libgdk_pixbuf,

jonathanBieler

module CMAES

    using Optim, Distributions, Parameters
    import Optim: ZerothOrderOptimizer, ZerothOrderState, initial_state, update_state!,
                  trace!, assess_convergence, AbstractOptimizerState, update!, value, value!, pick_best_x,
                  pick_best_f

    struct CMA <: Optim.ZerothOrderOptimizer
        λ::Int
        σ::Float64

jonathanBieler

module RemoteEval

    @enum Messages DONE=1

    function start_server()
        port, server = listenany(8000)

        @async begin
            while true
                sock = accept(server)

jonathanBieler

using BinDeps
using Compat

@BinDeps.setup

sdl2 = library_dependency("sdl2", aliases=["sdl2-2.0"])

# package managers
if is_linux()
    provides(AptGet, Dict("sdl2-2.0"=>sdl2))

jonathanBieler

module CMAES

    using Distributions

    ∑(x) = sum(x)
    
    function init_constants(xinit,λ,w,μ)
        D = length(xinit)
    
        μ_w = 1.0 / sum(w.^2)

jonathanBieler

module A

    using Optim
    import Optim: ZerothOrderOptimizer, ZerothOrderState, initial_state, update_state!, trace!, assess_convergence, AbstractOptimizerState, update!, value

    struct RandomSampler <: ZerothOrderOptimizer
        σ::Float64
    end

    RandomSampler(; σ=1e-1) = RandomSampler(σ)