def hidden_abstraction(trace_graph, settings):
    """
    Identify hidden abstractions and print those
    that occured with a percentage more than "threashold".
    """
    threashold = settings.HIDDEN_ABSTR_THREASHOLD
    for posix_call, stat in trace_graph.posix_calls.items():
        total = sum(map(lambda x: x[1], stat.items()))
        # group stats by libraries
        local_stat = {}
        for call, count in stat.items():
            lib = call.split(':')[1]
            if lib in local_stat:
                local_stat[lib] += count
            else:
                local_stat[lib] = count
        # in case you want to check function callers, instead of
        # library callers, uncomment the following line.
        #local_stat = stat
        for lib in sorted(local_stat, key=local_stat.get, reverse=True):
            if threashold >= 100 * local_stat[lib] / total:
                yield posix_call, lib, local_stat[lib], total
dataset/ETHPy150Open columbia/libtrack/libtrack/parser/src/telesphorus/abstractions.py/hidden_abstraction/swapped operands of `>=`