Source code for EELSFitter.plotting.training_perf

import matplotlib.pyplot as plt


[docs] def plot_cost_dist(cost_trains, cost_tests, cost_tests_std, title=r"$\rm{Cost\;distribution\;}$"): r""" Parameters ---------- cost_trains: numpy.ndarray, shape=(M,) Cost values of the training set with M trained NNs cost_tests: numpy.ndarray, shape=(M,) Cost values of the test set with M trained NNs cost_tests_std: float 68% CL of the test costs title: str, optional Title of the plot Returns ------- fig: matplotlib.figure.Figure """ fig, ax = plt.subplots(dpi=200) ax.hist(cost_trains, bins=40, label=r"$\rm{Training}$", range=(0, 5 * cost_tests_std), alpha=0.4) ax.hist(cost_tests, bins=40, label=r"$\rm{Validation}$", range=(0, 5 * cost_tests_std), alpha=0.4) ax.set_title(title) ax.set_xlabel(r"$\rm{\chi^2\;}$") ax.legend(frameon=False, loc='upper right') ax.set_xlim((0, 0.4)) return fig