random_walk.rb

class RandomWalk
    attr_accessor :outcome, :step_count

    def initialize(upper_bound, lower_bound, step_size, win_probability)
        @step_count = 0
        @current_position = 0

        @upper_bound = upper_bound
        @lower_bound = lower_bound
        @step_size = step_size
        @win_probability = win_probability

        simulate
    end

    def simulate
        while outcome.nil?
            @step_count += 1

            if rand(0) < @win_probability
                @current_position += @step_size
            else
                @current_position -= @step_size
            end
        end
    end

    def outcome
        if @current_position >= @upper_bound
            :win
        elsif @current_position <= @lower_bound
            :loss
        end
    end

    def win?
        outcome == :win
    end
end

class MonteCarlo
    def initialize(trials, params)
        @trials = trials
        @trial_count = 0
        @step_count = 0
        @win_count = 0
        @params = params

        run
    end

    def run
        while(@trial_count < @trials)
            random_walk = RandomWalk.new(*@params.values)
            @step_count += random_walk.step_count
            @win_count += 1 if random_walk.win?
            @trial_count += 1
        end
    end

    def avg_steps
        @step_count / @trials
    end

    def win_walkaway_probability
        @win_count * 1.0 / @trials
    end

    def loss_walkaway_probability
        1 - win_walkaway_probability
    end

    def print_results
        puts "Average steps: #{avg_steps}"
        puts "Probability to walkaway with win: #{win_walkaway_probability}"
        puts "Probability to walkaway with loss: #{loss_walkaway_probability}"
    end
end

params = {win_walkaway: 333, loss_walkaway: -1000, bet_size: 1, win_probability: 0.50}
m = MonteCarlo.new(1000, params)
m.print_results

# r = RandomWalk.new(win_walkaway, loss_walkaway, bet_size, win_probability)
# puts r.outcome
# puts r.step_count