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

    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

#!/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