<jupyter_start><jupyter_text>Create Some Fake Entires That demonstrates PlottingIn the constructor, give a title, number of total datasets that you want to plot side by side, a list of methods for which you are plotting results. logit_y will logit transforms the y axis for emphasis on low and high end part of the metric. eval_type simply is for naming purposes, and will appear in y-axis titles.In the following block we just create fake SNR and metrics just fo demonstration purposes.If you want to compute SNR of a templates (np.ndarray of shape ( time samples,  channels,  units)) just call main_channels(templates).<jupyter_code>plot = ChristmasPlot('Fake', n_dataset=3, methods=['yass', 'kilosort', 'spyking circus'], logit_y=True, eval_type="Accuracy")

for method in plot.methods:
    for i in range(plot.n_dataset):
        x = (np.random.rand(30) - 0.5) * 10
        y = 1 / (1 + np.exp(-x + np.random.rand()))
        plot.add_metric(x, y, dataset_number=i, method_name=method)<jupyter_output><empty_output><jupyter_text>Generate SNR vs MetricChange save_to to a file path to save it to file.<jupyter_code>plot.generate_snr_metric_plot(save_to=None)<jupyter_output><empty_output><jupyter_text>Generate the curve plotsSimilar to the other plot, give path to file in save_to for saving to file.<jupyter_code>plot.generate_curve_plots(save_to=None)<jupyter_output><empty_output>
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