1"""
2
3This file illustrated the use of the workbench for using dimensional
4stacking for scenario discovery
5
6
7.. codeauthor:: jhkwakkel <j.h.kwakkel (at) tudelft (dot) nl>
8
9"""
10
11import matplotlib.pyplot as plt
12
13from ema_workbench import ema_logging, load_results
14from ema_workbench.analysis import dimensional_stacking
15
16ema_logging.log_to_stderr(level=ema_logging.INFO)
17
18# load data
19fn = "./data/1000 flu cases no policy.tar.gz"
20x, outcomes = load_results(fn)
21
22y = outcomes["deceased_population_region_1"][:, -1] > 1000000
23
24fig = dimensional_stacking.create_pivot_plot(x, y, 2, bin_labels=True)
25
26plt.show()