1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
|
#!/usr/bin/env python
#
# Author: Patrick Hung (patrickh @caltech)
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 1997-2016 California Institute of Technology.
# Copyright (c) 2016-2024 The Uncertainty Quantification Foundation.
# License: 3-clause BSD. The full license text is available at:
# - https://github.com/uqfoundation/mystic/blob/master/LICENSE
"""
Adapted from DETest.py by Patrick Hung
Sets up Storn and Price's Polynomial 'Fitting' Problem.
Exact answer: Chebyshev Polynomial of the first kind. T8(x)
Reference:
[1] Storn, R. and Price, K. Differential Evolution - A Simple and Efficient
Heuristic for Global Optimization over Continuous Spaces. Journal of Global
Optimization 11: 341-359, 1997.
"""
from test_ffit import *
def plot_solution(func):
try:
import Gnuplot, numpy
g = Gnuplot.Gnuplot(debug = 1)
x = numpy.arange(-1.2, 1.2001, 0.01)
x2 = numpy.array([-1.0, 1.0])
p = poly1d(func)
chebyshev = poly1d(Chebyshev8)
y = p(x)
exact = chebyshev(x)
# g('set style line lw 5')
g('set xrange[-1.4:1.4]')
g('set yrange[-2:8]')
g.plot(Gnuplot.Data(x, y, with_='line', inline=1, title="Storn and Price's Function Fitting problem"), \
Gnuplot.Data(x, exact, with_='l 4 4'), \
Gnuplot.Data(x, 0*x-1, with_='l 2 2'), \
Gnuplot.Data(x2, 0*x2+1, with_='l 2 2'), \
Gnuplot.Data([-1.2, -1.2], [-1, 10], with_='l 2 2'), \
Gnuplot.Data([1.2, 1.2], [-1, 10], with_='l 2 2'), \
Gnuplot.Data([-1.0, -1.0], [1, 10], with_='l 2 2'), \
Gnuplot.Data([1.0, 1.0], [1, 10], with_='l 2 2') \
)
getch('Press any key to exit plot')
except ImportError:
print("Install Gnuplot and Gnuplot.py for visualization")
pass
if __name__ == '__main__':
solution = main()
print_solution(solution)
plot_solution(solution)
# end of file
|
