Monte Carlo Pi

buffon.jl

function buffon_one()
   mp = rand()
   phi = (rand() * pi) - pi / 2
   xrechts = mp + cos(phi)/2
   xlinks = mp - cos(phi)/2
   xrechts >= 1 || xlinks <= 0
end

function buffon(m)
    hit = 0
    for l = 1:m
        buffon_one() && (hit += 1)
    end
    miss = m - hit
    piapprox = m / hit * 2
end

function buffon_par(m)
    hit = @parallel (+) for l = 1:m
        buffon_one() ? 1 : 0
    end
    miss = m - hit
    piapprox = m / hit * 2
end

dart.jl

function dart_one()
    xrand = rand()
    yrand = rand()
    r = sqrt(xrand^2 + yrand^2)
    r <= 1
end

function dart(m)
    hit = 0
    for i in 1:m
        dart_one() && (hit += 1)
    end
    piapprox = 4 * hit / m
end

function dart_par(m)
    hit = @parallel (+) for i in 1:m
        dart_one() ? 1 : 0
    end
    piapprox = 4 * hit / m
end