The PP plot (probability-probability plot) consists of plotting the CDF of one distribution against the CDF of another distribution. If the distributions are similar, the PP plot will lie on the diagonal. This version of a PP plot is the fully parametric form in which we plot one distribution against another distribution. There is also a semi-parametric form offered in PP_plot_semiparametric.
- X_dist (object) – A probability distribution object created using the reliability.Distributions module. The CDF of this distribution will be plotted along the X-axis.
- Y_dist (object) – A probability distribution object created using the reliability.Distributions module. The CDF of this distribution will be plotted along the Y-axis.
- y_quantile_lines (array, list, optional) – Starting points for the trace lines to find the X equivalent of the Y-quantile. Optional input. Default = None
- x_quantile_lines (array, list, optional) – Starting points for the trace lines to find the Y equivalent of the X-quantile. Optional input. Default = None
- show_diagonal_line (bool, optional) – If True the diagonal line will be shown on the plot. Default = False
- downsample_scatterplot (bool, int, optional) – If True or None, and there are over 1000 points, then the scatterplot will be downsampled by a factor. The default downsample factor will seek to produce between 500 and 1000 points. If a number is specified, it will be used as the downsample factor. Default is False which will result in no downsampling. This functionality makes plotting faster when there are very large numbers of points. It only affects the scatterplot not the calculations.
- kwargs – Plotting keywords that are passed directly to matplotlib (e.g. color, label, linestyle).
figure (object) – The figure handle of the PP plot is returned as an object
If your plot does not appear automatically, use plt.show() to show it.