def main():
solver = DifferentialEvolutionSolver(ND, NP)
solver.SetRandomInitialPoints()
solver.SetEvaluationLimits(generations=MAX_GENERATIONS)
solver.SetGenerationMonitor(VerboseMonitor(10))
#strategy = Best1Exp
#strategy = Best1Bin
#strategy = Best2Bin
strategy = Best2Exp
solver.Solve(ChebyshevCost, termination=VTR(0.0001), strategy=strategy, \
CrossProbability=1.0, ScalingFactor=0.6)
solution = solver.Solution()
print("\nsolved: ")
print(poly1d(solution))
print("\ntarget: ")
print(poly1d(Chebyshev16))
#print("actual coefficients vs computed:")
#for actual,computed in zip(Chebyshev16, solution):
# print("%f %f" % (actual, computed))
plot_solution(solution, Chebyshev16)
def main():
solver = DifferentialEvolutionSolver(ND, NP)
solver.SetRandomInitialPoints()
solver.SetEvaluationLimits(generations=MAX_GENERATIONS)
solver.SetGenerationMonitor(VerboseMonitor(10))
#strategy = Best1Exp
#strategy = Best1Bin
#strategy = Best2Bin
strategy = Best2Exp
solver.Solve(ChebyshevCost, termination=VTR(0.0001), strategy=strategy, \
CrossProbability=1.0, ScalingFactor=0.6)
solution = solver.Solution()
print("\nsolved: ")
print(poly1d(solution))
print("\ntarget: ")
print(poly1d(Chebyshev16))
#print("actual coefficients vs computed:")
#for actual,computed in zip(Chebyshev16, solution):
# print("%f %f" % (actual, computed))
plot_solution(solution, Chebyshev16)
#!/usr/bin/env python
#
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 1997-2014 California Institute of Technology.
# License: 3-clause BSD. The full license text is available at:
# - http://trac.mystic.cacr.caltech.edu/project/mystic/browser/mystic/LICENSE
"""
Testing the polynomial fitting problem of [1] using scipy's Nelder-Mead algorithm.
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 Chebyshev8, ChebyshevCost, plot_solution, print_solution
if __name__ == '__main__':
from mystic.solvers import fmin
#from mystic._scipyoptimize import fmin
import random
random.seed(123)
x = [random.uniform(-100,100) + Chebyshev8[i] for i in range(9)]
solution = fmin(ChebyshevCost, x)
print_solution(solution)
plot_solution(solution)
# end of file
[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 mystic.solvers import diffev
from test_ffit import plot_solution, print_solution, Chebyshev8, ChebyshevCost
from mystic.tools import random_seed
random_seed(123)
ND = 9
NP = ND * 10
MAX_GENERATIONS = ND * NP
def main():
range = [(-100.0, 100.0)] * ND
solution = diffev(ChebyshevCost,range,NP,bounds=None,ftol=0.01,\
maxiter=MAX_GENERATIONS,cross=1.0,scale=0.9)
return solution
if __name__ == '__main__':
#plot_solution(Chebyshev8)
solution = main()
print_solution(solution)
plot_solution(solution)
# end of file
