def evaluate(aligned_traces, parameters=None):
    """
    Transforms the alignment result to a simple dictionary
    including the percentage of fit traces and the average fitness

    Parameters
    ----------
    aligned_traces
        Alignments calculated for the traces in the log
    parameters
        Possible parameters of the evaluation

    Returns
    ----------
    dictionary
        Containing two keys (percFitTraces and averageFitness)
    """
    if parameters is None:
        parameters = {}
    str(parameters)
    no_traces = len(aligned_traces)
    no_fit_traces = 0
    sum_fitness = 0.0
    for tr in aligned_traces:
        if tr['fitness'] == 1.0:
            no_fit_traces = no_fit_traces + 1
        sum_fitness = sum_fitness + tr['fitness']
    perc_fit_traces = 0.0
    average_fitness = 0.0
    if no_traces > 0:
        perc_fit_traces = 100.0 * float(no_fit_traces) / float(no_traces)
        average_fitness = float(sum_fitness) / float(no_traces)
    return {'percFitTraces': perc_fit_traces, 'averageFitness': average_fitness
        }
