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#!/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 The Mathematica Guidebook, Numerics.
"""
from mystic.solvers import DifferentialEvolutionSolver
from mystic.termination import ChangeOverGeneration, VTR
from mystic.strategy import Best1Exp, Best1Bin, Rand1Exp
from mystic.tools import random_seed
random_seed(123)
from mystic.models import fosc3d as fOsc3D
def draw_contour():
import matplotlib.pyplot as plt, numpy
x, y = numpy.mgrid[-1:2:0.02,-0.5:2:0.02]
c = 0*x
s,t = x.shape
for i in range(s):
for j in range(t):
xx,yy = x[i,j], y[i,j]
c[i,j] = fOsc3D([xx,yy])
plt.contourf(x,y,c,100)
ND = 2
NP = ND*10
MAX_GENERATIONS = 2000
def main():
solver = DifferentialEvolutionSolver(ND, NP)
solver.SetRandomInitialPoints(min = [-2.0]*ND, max = [2.0]*ND)
solver.SetEvaluationLimits(generations=MAX_GENERATIONS)
strategy = Best1Exp
#strategy = Best1Bin
solver.Solve(fOsc3D,termination=ChangeOverGeneration(1e-5, 30), \
strategy=strategy,CrossProbability=1.0,ScalingFactor=0.9)
return solver.Solution()
if __name__ == '__main__':
import matplotlib.pyplot as plt
from mystic.solvers import fmin
#from mystic._scipyoptimize import fmin
draw_contour()
solution = main()
print("solution: %s" % solution)
plt.plot([solution[0]],[solution[1]],'wo',markersize=10)
print("Differential Evolution: Min: %s, sol = %s" % (fOsc3D(solution), solution))
print("\nTrying scipy.optimize.fmin (Nelder-Mead Simplex)...")
m = fmin(fOsc3D, [0.1, 0.1])
plt.plot([m[0]],[m[1]],'ro',markersize=5)
print("solution w/ initial conditions (0.1,0.1): %s\n" % m)
m = fmin(fOsc3D, [1, 1])
plt.plot([m[0]],[m[1]],'ro',markersize=5)
print("solution w/ initial conditions (1,1): %s\n" % m)
m = fmin(fOsc3D, [-1, 1])
print("solution w/ initial conditions (-1,1): %s\n" % m)
plt.plot([m[0]],[m[1]],'ro',markersize=5)
# m = fmin(fOsc3D, [0, 2])
# print("solution w/ initial conditions (0,2): %s\n" % m)
# plt.plot([m[0]],[m[1]],'ro',markersize=5)
plt.title('White dot: DE, Red dots: Nelder-Mead')
try:
import Image
plt.savefig('test_fosc3d_out',dpi=72)
im = Image.open('test_fosc3d_out.png')
im.show()
except ImportError:
plt.show()
# end of file
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