stacie.plot module

Plot various aspects of the results of the autocorrelation integral estimate.

fixformat(s)[source]

Replace standard scientific notation with prettier unicode formatting.

Return type:

str

Parameters:

s (str)

plot_acint_estimates(ax, uc, rs)[source]

Plot the sorted autocorrelation integral estimates and their uncertainties.

Parameters:
plot_all_models(ax, uc, r)[source]

Plot all fitted model spectra (for all tested cutoffs).

Parameters:
plot_cutoff_weight(ax, uc, r)[source]

Plot the cutoff criterion as a function of cutoff frequency.

Parameters:
plot_evals(ax, uc, r)[source]

Plot the eigenvalues of the Hessian as a function of the cutoff frequency.

Parameters:
plot_extras(axs, uc, r)[source]
Parameters:
plot_fitted_spectrum(ax, uc, r, *, legend=True)[source]

Plot the fitted model spectrum.

Parameters:
plot_qq(ax, uc, rs)[source]

Make a qq-plot between the predicted and expected distribution of AC integral estimates.

This plot function assumes the true integral is known.

Parameters:
plot_results(path_pdf, rs, uc=None, *, figsize=(7.5, 4.21875), legend=True)[source]

Generate a multi-page PDF with plots of the autocorrelation integral estimation.

Parameters:

  • path_pdf (str) – The PDF file where all the figures are stored.

  • rs (Result | list[Result]) – A single Result instance or a list of them. If the (first) result instance has spectrum.amplitudes_ref set, theoretical expectations are included. When multiple results instances are given, only the first one is plotted in blue. All remaining ones are plotted in light grey.

  • uc (UnitConfig | None) – The configuration of the units used for plotting.

  • figsize (tuple) – The figure size tuple for matplotlib

  • legend (bool)

plot_sanity(ax, uc, r)[source]
Parameters:
plot_spectrum(ax, uc, s, nplot=None)[source]

Plot the empirical spectrum.

Parameters:
plot_uncertainty(ax, uc, r)[source]

Plot the autocorrelation integral and uncertainty as a function fo cutoff frequency.

Parameters:
rms(x)[source]