visualization_utils/plotting-ying.py [2558:2595]:
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    """" 
    # combine the results
    combined_area_power = []
    for results_combined in itertools.product(*list(workload_pareto_points.values())):
        combined_power_area_tuple = [0,0]
        for el in results_combined:
            combined_power_area_tuple[0] += el[0]
            combined_power_area_tuple[1] += el[1]
        combined_area_power.append(combined_power_area_tuple[:])
    """


    all_points_in_isolation = []
    all_points_cross_workloads = []

    workload_in_isolation = {}
    for workload, points in workload_results.items():
        if "cava" in workload and "audio" in workload and "edge_detection" in workload:
            for point in points:
                all_points_cross_workloads.append(point)
        else:
            workload_in_isolation[workload] = points


    ctr = 0
    workload_in_isolation_pareto = {}
    for workload, points in workload_in_isolation.items():
        optimal_points = find_pareto_points(list(set(points)))
        workload_in_isolation_pareto[workload] = optimal_points


    combined_area_power_in_isolation= []
    combined_area_power_in_isolation_with_sys_char = []

    s = time.time()
    for results_combined in itertools.product(*list(workload_in_isolation_pareto.values())):
        # add up all the charactersitics
        combined_sys_chars = {}
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visualization_utils/plotting.py [3735:3773]:
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    """" 
    # combine the results
    combined_area_power = []
    for results_combined in itertools.product(*list(workload_pareto_points.values())):
        combined_power_area_tuple = [0,0]
        for el in results_combined:
            combined_power_area_tuple[0] += el[0]
            combined_power_area_tuple[1] += el[1]
        combined_area_power.append(combined_power_area_tuple[:])
    """


    all_points_in_isolation = []
    all_points_cross_workloads = []

    workload_in_isolation = {}
    for workload, points in workload_results.items():
        if "cava" in workload and "audio" in workload and "edge_detection" in workload:
            for point in points:
                all_points_cross_workloads.append(point)
        else:
            workload_in_isolation[workload] = points


    ctr = 0
    workload_in_isolation_pareto = {}
    for workload, points in workload_in_isolation.items():
        optimal_points = find_pareto_points(list(set(points)))
        workload_in_isolation_pareto[workload] = optimal_points
        #workload_in_isolation_pareto[workload] = points  # show all points instead


    combined_area_power_in_isolation= []
    combined_area_power_in_isolation_with_sys_char = []

    s = time.time()
    for results_combined in itertools.product(*list(workload_in_isolation_pareto.values())):
        # add up all the charactersitics
        combined_sys_chars = {}
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