source: branches/decorate/test_restarts.py @ 855

#!/usr/bin/env python
#
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 2012-2016 California Institute of Technology.
# License: 3-clause BSD.  The full license text is available at:
#  - http://mmckerns.github.io/project/mystic/browser/mystic/LICENSE

from restarts import sumt
from mystic.penalty import *
from mystic.constraints import *
from mystic.tools import random_seed
random_seed(123)

def test_sumt1(solver, verbose=False):
    def constraint1(x):
        x1,x2 = x[0],x[1]
        return x1**2 + x2**2 - 2.

    def constraint2(x):
        x1,x2 = x[0],x[1]
        return 0.25*x1**2 + 0.75*x2**2 - 1.

    @lagrange_inequality(constraint2)
    @lagrange_equality(constraint1)
    def penalty(x):
        return 0.0

    constraints_string = """
    x1**2 + x2**2 - 2. = 0.
    0.25*x1**2 + 0.75*x2**2 - 1. <= 0.
        """
    if verbose:
        print "constraints equations:%s" % (constraints_string.rstrip(),)

    def cost(x):
        x1 = x[0]
        x2 = x[1]
        return  x1**4 - 2.*x1**2*x2 + x1**2 + x1*x2**2 - 2.*x1 + 4.

    #XXX: Rand1Bin needs randomstate to work properly when no random_seed ?
   #import random
   #randomstate = random.getstate() #XXX: this should be an internal
    solver.SetPenalty(penalty)
    from mystic.termination import VTR
    term = VTR()
    _solver = sumt(cost, solver, term, disp=verbose)#, randomstate=randomstate)
    soln = _solver.Solution()
    satisfied = issolution(penalty, soln)
    if verbose: 
        print "final answer:", soln
        print "constraints satisfied:", satisfied
        print "expected: [1., 1.]", "\n"
    else: assert satisfied


def test_sumt2(solver, verbose=False):
    def constraint1(x):
        x1,x2,x3 = x[0],x[1],x[2]
        return 5. - x2

    def constraint2(x):
        x1,x2,x3 = x[0],x[1],x[2]
        return 4.*x1 - 5*x3 + 1.

    def constraint3(x):
        x1,x2,x3 = x[0],x[1],x[2]
        return (x1 - 10.)**2 + (x2 + 1)**2 - 50.

    @lagrange_inequality(constraint3)
    @lagrange_inequality(constraint2)
    @lagrange_inequality(constraint1)
    def penalty(x):
        return 0.0

    constraints_string = """
    x2 > 5.
    4.*x1-5.*x3 < -1.
    (x1-10.)**2 + (x2+1.)**2 < 50. 
    """
    if verbose:
        print "constraints equations:%s" % (constraints_string.rstrip(),)

    def cost(x):
        return (x[0] - 1.)**2 + (x[1]-2.)**2 + (x[2]-3.)**4

    #XXX: Rand1Bin needs randomstate to work properly when no random_seed ?
   #import random
   #randomstate = random.getstate() #XXX: this should be an internal
    solver.SetPenalty(penalty)
    from mystic.termination import VTR
    term = VTR()
    _solver = sumt(cost, solver, term, disp=verbose)#, randomstate=randomstate)
    soln = _solver.Solution()
    satisfied = issolution(penalty, soln)
    if verbose:
        print "final answer:", soln
        print "constraints satisfied:", satisfied
        print "expected: [ 6.25827968  4.999961    5.20662288]", "\n"
    else: assert satisfied


if __name__ == '__main__':
    from mystic.solvers import DifferentialEvolutionSolver
    from mystic.solvers import DifferentialEvolutionSolver2
    from mystic.solvers import PowellDirectionalSolver
    from mystic.solvers import NelderMeadSimplexSolver
    verbose = True

    x0 = [3., 2.]; ndim = 2; npop = 25
   #solver = DifferentialEvolutionSolver(ndim, npop)
   #solver = DifferentialEvolutionSolver2(ndim, npop)
   #solver = PowellDirectionalSolver(ndim)
    solver = NelderMeadSimplexSolver(ndim)
    solver.SetInitialPoints(x0)
    test_sumt1(solver, verbose=verbose)

    x0 = [0., 0., 0.]; ndim = 3; npop = 40
   #solver = DifferentialEvolutionSolver(ndim, npop)
   #solver = DifferentialEvolutionSolver2(ndim, npop)
   #solver = PowellDirectionalSolver(ndim)
    solver = NelderMeadSimplexSolver(ndim)
    solver.SetInitialPoints(x0)
    test_sumt2(solver, verbose=verbose)


#EOF