def six_3():

	# Process input and returns graph dictionary
	G = ip.process_input_6_3()

        # Changing attributes of the graph to maintain different terms used; 
	# Pass boolean value to tell the method if a 'min' value is wanted in the graph
	newG = ip.changeGraphAttributes(G, False, 'ToCapFlow')

	ts1 = datetime.datetime.now()
	resG = FF1.fordfulkersan(newG)
	ts2 = datetime.datetime.now()
	ft.write('\n 6.3 FF :'+ str((ts2 - ts1).microseconds)+ 'ms')
	
	# Modify result graph to 'max' 
	newResG = ip.changeGraphAttributes(resG, False, 'ToMaxMin')

	A, B = mc.create_min_cut_sets(newResG, [], 'S', [])
	
	profit, output = mc.computeProfit_Output(A, B, G)
	
	file_result = open('Result_File_6.3.txt', 'ab')
	file_result.write('\nFF Tasks Chosen and Profit: \n')
	file_result.write('6.3: Tasks Chosen: '+ str(output)+'\n')
	file_result.write('6.3: Total Profit: ' + str(profit)+ '\n')
def six_3():

    #process input and returns graph dictionary
    G = ip.process_input_6_3()
    #ip.draw_graph(G, 'Original Graph_6.3')

    ts1 = datetime.datetime.now()
    max_flow, F, nim, RG = EK.edmond_karp(G, '6.3', None)
    ts2 = datetime.datetime.now()
    ft.write('\n 6.3 EK : ' + str((ts2 - ts1).microseconds) + 'ms')

    #ip.draw_graph(RG, 'Residual Graph_6.3')

    #print RG, F
    A, B = mc.create_min_cut_sets(RG, F, 'S', nim)

    profit, output = mc.computeProfit_Output(A, B, G)

    file_result = open('Result_File_6.3.txt', 'ab')
    file_result.write('EK Tasks Chosen and Profit: \n')
    file_result.write('6.3: Tasks Chosen: ' + str(output) + '\n')
    file_result.write('6.3: Total Profit: ' + str(profit) + '\n')