1"""
2Created on Jul 8, 2014
3
4@author: jhkwakkel@tudelft.net
5"""
6
7import matplotlib.pyplot as plt
8import numpy as np
9
10from ema_workbench import ema_logging, load_results
11from ema_workbench.analysis import lines, Density
12
13ema_logging.log_to_stderr(ema_logging.INFO)
14
15file_name = r"./data/1000 flu cases with policies.tar.gz"
16experiments, outcomes = load_results(file_name)
17
18# let's specify a few scenarios that we want to show for
19# each of the policies
20scenario_ids = np.arange(0, 1000, 100)
21experiments_to_show = experiments["scenario_id"].isin(scenario_ids)
22
23# the plotting functions return the figure and a dict of axes
24fig, axes = lines(
25 experiments,
26 outcomes,
27 group_by="policy",
28 density=Density.KDE,
29 show_envelope=True,
30 experiments_to_show=experiments_to_show,
31)
32
33# we can access each of the axes and make changes
34for key, value in axes.items():
35 # the key is the name of the outcome for the normal plot
36 # and the name plus '_density' for the endstate distribution
37 if key.endswith("_density"):
38 value.set_xscale("log")
39
40plt.show()