rdtools.plotting.degradation_summary_plots

rdtools.plotting.degradation_summary_plots(yoy_rd, yoy_ci, yoy_info, normalized_yield, hist_xmin=None, hist_xmax=None, bins=None, scatter_ymin=None, scatter_ymax=None, plot_color=None, summary_title=None, scatter_alpha=0.5, detailed=False)

Create plots (scatter plot and histogram) that summarize degradation analysis results.

Parameters

  • yoy_rd (float) -- rate of relative performance change in %/yr

  • yoy_ci (float) -- one-sigma confidence interval of degradation rate estimate

  • yoy_info (dict) --

    a dictionary with keys:

    • YoY_values - pandas series of right-labeled year on year slopes

    • renormalizing_factor - float value used to recenter data

    • exceedance_level - the degradation rate that was outperformed with a probability given by the exceedance_prob parameter in the degradation.degradation_year_on_year()

  • normalized_yield (pandas.Series) -- PV yield data that is normalized, filtered and aggregated

  • hist_xmin (float, optional) -- lower limit of x-axis for the histogram

  • hist_xmax (float, optional) -- upper limit of x-axis for the histogram

  • bins (int, optional) -- Number of bins in the histogram distribution. If omitted, len(yoy_values) // 40 will be used

  • scatter_ymin (float, optional) -- lower limit of y-axis for the scatter plot

  • scatter_ymax (float, optional) -- upper limit of y-axis for the scatter plot

  • plot_color (str, optional) -- color of the summary plots

  • summary_title (str, optional) -- overall title for summary plots

  • scatter_alpha (float, default 0.5) -- Transparency of the scatter plot

  • detailed (bool, optional) -- Color code points by the number of times they get used in calculating Rd slopes. Default color: 2 times (as a start and endpoint). Green: 1 time. Red: 0 times.

Note

It should be noted that the yoy_rd, yoy_ci and yoy_info are the outputs from degradation.degradation_year_on_year().

Returns

fig -- Figure with two axes

Return type

matplotlib.figure.Figure