def UpAndOutCallPrototype(Spot):
    
    #look at times
    look_at_times = list(np.linspace(start=0, stop=Expiry, num=12))
    
    #generate a path
    
    
    market_params = {'spot':Spot, 'rate':rate, 'vol':Vol}
    path_generator = GeneratorGBM(market_params)
    path_generator.generator.set_seed(seed=0)
    path_generator.sim_setup(look_at_times)
    
    sum = 0.
    Knockout = 108.
    for i in range(0,num_paths):
        
        path = path_generator.do_one_path() 
        # plt.plot(look_at_times,path)
        # plt.show()
        
        #Evaluate the payoff for path
        #Check if knocks out above barrier
        if any(map(lambda(x): x >= Knockout,path)):
            this_payoff = 0
        else:
            #Calc payoff
            po = VanillaCall(Strike=Strike)
            this_payoff = po.po(path[-1]) #Get last element of path
        
        sum += this_payoff
def AsianPrototype(Spot):
    
    #look at times
    look_at_times = list(np.linspace(start=0, stop=Expiry, num=12))
    
    #generate a path
    
    market_params = {'spot':Spot, 'rate':rate, 'vol':Vol}
    path_generator = GeneratorGBM(market_params)
    path_generator.sim_setup(look_at_times)
    sum = 0.
    
    for i in range(0,num_paths):
        
        path = path_generator.do_one_path() 
        #plt.plot(look_at_times,path)
        #plt.show()
        
        #Evaluate the payoff for path
        #Average of price - K
        average_price = np.mean(path)

        #Calc payoff
        po = VanillaCall(Strike=Strike)
        this_payoff = po.po(average_price)
        
        sum += this_payoff
    
    #Average and discount    
    price = math.exp(-rate*Expiry)*sum/num_paths
    
    return price