if __name__ == '__main__':
print("Differential Evolution")
print("======================")
# set range for random initial guess
ndim = 9
x0 = [(-100, 100)] * ndim
random_seed(321)
# draw frame and exact coefficients
plot_exact()
# use DE to solve 8th-order Chebyshev coefficients
npop = 10 * ndim
solution = diffev(chebyshev8cost, x0, npop)
# use pretty print for polynomials
print(poly1d(solution))
# compare solution with actual 8th-order Chebyshev coefficients
print("\nActual Coefficients:\n %s\n" % poly1d(chebyshev8coeffs))
# plot solution versus exact coefficients
plot_solution(solution)
getch()
# end of file
def cost_function(params):
x = data(params)[1] - datapts
return numpysum(real((conjugate(x)*x)))
if __name__ == '__main__':
plotview = [-60,60, 0,2500]
target = [1., 2., 1.]
x,datapts = data(target)
#myCost = cost_function
##myCost = PolyCostFactory(target,x)
F = CostFactory()
F.addModel(ForwardPolyFactory,'poly',len(target))
myCost = F.getCostFunction(evalpts=x, observations=datapts)
import pylab
pylab.ion()
print "target: ",target
plot_sol(target,'r-')
solution, stepmon = de_solve(myCost)
print "solution: ",solution
plot_sol(solution,'g-')
print ""
# print "at step 10: ",stepmon.x[10]
getch()
# End of file
#!/usr/bin/env python
#
# Author: Patrick Hung (patrickh @caltech)
# Copyright (c) 1997-2016 California Institute of Technology.
# Copyright (c) 2016-2022 The Uncertainty Quantification Foundation.
# License: 3-clause BSD. The full license text is available at:
# - https://github.com/uqfoundation/mystic/blob/master/LICENSE
from mystic.tools import getch
import Gnuplot, numpy
g = Gnuplot.Gnuplot(debug = 1)
g.clear()
x = numpy.arange(-4, 4, 0.01)
y = numpy.cos(x)
y2 = numpy.cos(2* x)
kwds = {'with':'line'}
g.plot(Gnuplot.Data(x, y, **kwds))
getch('next: any key')
g.plot(Gnuplot.Data(x, y2, **kwds))
getch('any key to quit')
# end of file
if __name__ == '__main__':
print("Powell's Method")
print("===============")
# initial guess
import random
from mystic.tools import random_seed
random_seed(123)
ndim = 9
x0 = [random.uniform(-100, 100) for i in range(ndim)]
# draw frame and exact coefficients
plot_exact()
# use Powell's method to solve 8th-order Chebyshev coefficients
solution = fmin_powell(chebyshev8cost, x0)
# use pretty print for polynomials
print(poly1d(solution))
# compare solution with actual 8th-order Chebyshev coefficients
print("\nActual Coefficients:\n %s\n" % poly1d(chebyshev8coeffs))
# plot solution versus exact coefficients
plot_solution(solution)
getch() #XXX: or plt.show() ?
# end of file
Testing the Corana parabola in 1D. Requires sam.
"""
import sam, numpy, mystic
#from test_corana import *
from mystic.solvers import fmin
from mystic.tools import getch
from mystic.models.corana import corana1d as Corana1
x = numpy.arange(-2., 2., 0.01)
y = [Corana1([c]) for c in x]
sam.put('x', x)
sam.put('y', y)
sam.eval("plot(x,y,'LineWidth',1); hold on")
for xinit in numpy.arange(0.1,2,0.1):
sol = fmin(Corana1, [xinit], full_output=1, retall=1)
xx = mystic.flatten_array(sol[-1])
yy = [Corana1([c]) for c in xx]
sam.put('xx', xx)
sam.put('yy', yy)
sam.eval("plot(xx,yy,'r-',xx,yy,'ko','LineWidth',2)")
sam.eval("axis([0 2 0 4])")
getch('press any key to exit')
# end of file
sam.putarray('X', x)
sam.putarray('Y', y)
sam.putarray('C', c)
sam.verbose()
sam.eval("[c,h]=contourf(X,Y,log(C*20+1)+2,100);set(h,'EdgeColor','none')")
sam.eval("title('Zimmermann''s Corner. Min at 7,2')")
sam.eval('hold on')
def run_once():
simplex = Monitor()
solver = fmin(2)
solver.SetRandomInitialPoints([0, 0], [7, 7])
solver.SetGenerationMonitor(simplex)
solver.Solve(CostFunction, termination=CRT())
sol = solver.Solution()
for x in simplex.x:
sam.putarray('x', x)
sam.eval("plot(x([1,2,3,1],1),x([1,2,3,1],2),'k-')")
draw_contour()
for i in range(8):
run_once()
getch("Press any key to quit")
# end of file
sam.putarray('X',x)
sam.putarray('Y',y)
sam.putarray('C',c)
sam.verbose()
sam.eval("[c,h]=contourf(X,Y,C,100);set(h,'EdgeColor','none')")
#sam.eval("[c,h]=contourf(X,Y,log(C*20+1)+2,100);set(h,'EdgeColor','none')")
sam.eval("title('Corana''s Parabola in 2D. Min at 0,0')")
sam.eval('hold on')
def run_once():
simplex = Monitor()
solver = fmin(2)
solver.SetRandomInitialPoints([0,0],[2,2])
solver.SetGenerationMonitor(simplex)
solver.Solve(Corana2, termination=CRT())
sol = solver.Solution()
for x in simplex.x:
sam.putarray('x',x)
sam.eval("plot(x([1,2,3,1],1),x([1,2,3,1],2),'w-')")
draw_contour()
for i in range(8):
run_once()
getch("Press any key to quit")
# end of file
if __name__ == '__main__':
print("Powell's Method")
print("===============")
# initial guess
import random
from mystic.tools import random_seed
random_seed(123)
ndim = 9
x0 = [random.uniform(-100,100) for i in range(ndim)]
# draw frame and exact coefficients
plot_exact()
# use Powell's method to solve 8th-order Chebyshev coefficients
solution = fmin_powell(chebyshev8cost,x0)
# use pretty print for polynomials
print(poly1d(solution))
# compare solution with actual 8th-order Chebyshev coefficients
print("\nActual Coefficients:\n %s\n" % poly1d(chebyshev8coeffs))
# plot solution versus exact coefficients
plot_solution(solution)
getch() #XXX: or plt.show() ?
# end of file
if __name__ == '__main__':
print("Powell's Method")
print("===============")
# initial guess
import random
from mystic.tools import random_seed
random_seed(123)
ndim = 9
x0 = [random.uniform(-100, 100) for i in range(ndim)]
# draw frame and exact coefficients
plot_exact()
# use Powell's method to solve 8th-order Chebyshev coefficients
solution = fmin_powell(chebyshev8cost, x0)
# use pretty print for polynomials
print(poly1d(solution))
# compare solution with actual 8th-order Chebyshev coefficients
print("\nActual Coefficients:\n %s\n" % poly1d(chebyshev8coeffs))
# plot solution versus exact coefficients
plot_solution(solution)
getch() #XXX: or pylab.show() ?
# end of file
if __name__ == '__main__':
print "Powell's Method"
print "==============="
# initial guess
import random
from mystic.tools import random_seed
random_seed(123)
ndim = 9
x0 = [random.uniform(-100,100) for i in range(ndim)]
# draw frame and exact coefficients
plot_exact()
# use Powell's method to solve 8th-order Chebyshev coefficients
solution = fmin_powell(chebyshev8cost,x0)
# use pretty print for polynomials
print poly1d(solution)
# compare solution with actual 8th-order Chebyshev coefficients
print "\nActual Coefficients:\n %s\n" % poly1d(chebyshev8coeffs)
# plot solution versus exact coefficients
plot_solution(solution)
getch() #XXX: or pylab.show() ?
# end of file
#!/usr/bin/env python
#
# Author: Patrick Hung (patrickh @caltech)
# 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
from mystic.tools import getch
import Gnuplot, numpy
g = Gnuplot.Gnuplot(debug = 1)
g.clear()
x = numpy.arange(-4, 4, 0.01)
y = numpy.cos(x)
y2 = numpy.cos(2* x)
g.plot(Gnuplot.Data(x, y, with='line'))
getch('next: any key')
g.plot(Gnuplot.Data(x, y2, with='line'))
getch('any key to quit')
# end of file
