P-P plot of the empirical CDFs of values in two lists.

pp_plot.py

import numpy as np
import matplotlib.pyplot as plt


def pp_plot(f, p, nbins, ax=None):
    """ P-P plot of the empirical CDFs of values in two lists, f and p. """
    if ax is None:
        ax = plt.gca()

    uniqe_vals_f = list(set(f))
    uniqe_vals_p = list(set(p))

    combine = uniqe_vals_f
    combine.extend(uniqe_vals_p)
    combine = list(set(combine))

    if len(uniqe_vals_f) > nbins:
        bins = nbins
    else:
        bins = sorted(combine)
        bins.append(bins[-1]+bins[-1]-bins[-2])

    ff, edges = np.histogram(f, bins=bins, density=True)
    fp, _ = np.histogram(p, bins=edges, density=True)

    Ff = np.cumsum(ff*(edges[1:]-edges[:-1]))
    Fp = np.cumsum(fp*(edges[1:]-edges[:-1]))

    plt.plot([0, 1], [0, 1], c='dodgerblue', lw=2, alpha=.8)
    plt.plot(Ff, Fp, c='black', lw=2, alpha=.9)
    plt.xlim([0, 1])
    plt.ylim([0, 1])