using Plots

#plotlyjs()
# Use the PyPlot interface
pyplot(size=(800,500), leg=false)

iters = 500   # play N = 500 rounds
init_pot = 100  # starting pot
num_runs = 1000 # Number of times to run the simulation


if !isfile("1-lin-sim.png")
	gamb_run = Array{Float64}(undef,iters+1)
	x = 1:iters+1
	model = 100:5:100+5*iters

	lin_gamb_plot = plot(x, model, linestyle=:dash, linecolor=:red, linewidth=3)

	for i = 1:num_runs
		gamb_run[1] = init_pot
		for j = 2:iters+1
			if rand(Bool)
				gamb_run[j] = gamb_run[j-1] - 30
			else
				gamb_run[j] = gamb_run[j-1] + 40
			end
		end
		plot!(lin_gamb_plot, x, gamb_run, linecolor=:green, linealpha=0.03)
		if i % 80 ==0
			plot!(lin_gamb_plot, x, gamb_run, linecolor=:green, linealpha=1)
		end
	end

	png( lin_gamb_plot, "1-lin-sim.png" )
end

if !isfile("2-mul-sim.png") || !isfile("2-mul-sim-log.png")
	m_model = 100*sqrt(1.4*0.7).^x

	m_gamb_plot = plot(x, m_model, linestyle=:dash, linecolor=:red, linewidth=3, ylims=(0,100000))
	m_gamb_plot_log = plot(x, m_model, linestyle=:dash, linecolor=:red, linewidth=3, yaxis=:log)

	for i = 1:num_runs
		gamb_run[1] = init_pot
		for j = 2:iters+1
			if rand(Bool)
				gamb_run[j] = gamb_run[j-1] * 1.4
			else
				gamb_run[j] = gamb_run[j-1] * 0.7
			end
		end
		plot!(m_gamb_plot, x, gamb_run, linecolor=:green, linealpha=0.03)
		plot!(m_gamb_plot_log, x, gamb_run, linecolor=:green, linealpha=0.03)

		if i % 80 == 0
			plot!(m_gamb_plot, x, gamb_run, linecolor=:green, linealpha=1)
			plot!(m_gamb_plot_log, x, gamb_run, linecolor=:green,       linealpha=1)
		end
	end

	png( m_gamb_plot, "2-mul-sim.png")
	png( m_gamb_plot_log, "2-mul-sim-log.png")
end