pyEPR.reports module

Module for reporting utility functions

@author: Zlatko K Minev

pyEPR.reports.plot_convergence_f_vspass(ax, s, kw={})

For a single pass

pyEPR.reports.plot_convergence_max_df(ax, s, kw={}, color='r')

For a single pass

pyEPR.reports.plot_convergence_maxdf_vs_sol(ax, s, s2, kw={})

ax, ‘Max Δf %’, ‘Solved elements’, kw for plot

pyEPR.reports.plot_convergence_solved_elem(ax, s, kw={}, color='b')

For a single pass

pyEPR.reports.plot_q3d_convergence_chi_f(RES)

Plot EPR convergence: χ (dispersive shift) and g (coupling) vs. pass number.

Parameters:

RES (dict) – Results dictionary from QuantumAnalysis.analyze_all_variations, containing "chi_in_MHz" and "gbus" as columns of numeric values indexed by pass number.

Returns:

Figure with two subplots: χ convergence (left) and g convergence (right), both in MHz.

Return type:

matplotlib.figure.Figure

pyEPR.reports.plot_q3d_convergence_main(epr, RES)

Plot EPR convergence: loss (alpha) and frequency vs. pass number.

Parameters:

• epr (QuantumAnalysis) – A pyEPR QuantumAnalysis object with HFSS convergence data available.

• RES (dict) – Results dictionary from QuantumAnalysis.analyze_all_variations, containing "alpha" (loss rate, MHz) and "fQ" (frequency, GHz) as pandas Series indexed by pass number.

Returns:

Figure with alpha (blue, left axis) and frequency in MHz (red, right axis) plotted vs. simulation pass number.

Return type:

matplotlib.figure.Figure