@staticmethod
    def plot_module_classification_sequence_performance(module, dataset, sequence_index, bounds=(0, 1)):
        outputs = []
        valid_output = []
        module.reset()
        for sample in dataset.getSequenceIterator(sequence_index):
            out = module.activate(sample[0])
            outputs.append(out)
            valid_output.append(out[sample[1].argmax()])
        plt.fill_between(list(range(len(valid_output))), 1, valid_output, facecolor='k', alpha=0.8)
        plt.plot(outputs, linewidth=4, alpha=0.7)
        plt.yticks(bounds)
Analogous to the :meth:`pandas.DataFrame.reset_index` function, see
dataset/ETHPy150Open pybrain/pybrain/pybrain/tools/plotting/classification.py/ClassificationDataSetPlot.plot_module_classification_sequence_performance--crossover with--dataset/ETHPy150Open pydata/pandas/pandas/core/series.py/Series.reset_index