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from openopt.kernel.baseSolver import baseSolver
from openopt.kernel.setDefaultIterFuncs import SMALL_DELTA_X, IS_MAX_ITER_REACHED
from numpy import nan

class goldenSection(baseSolver):
    __name__ = 'goldenSection'
    __optionalDataThatCanBeHandled__ = ['lb', 'ub']
    __license__ = "BSD"
    __authors__ = 'Dmitrey'
    __alg__ = "golden section"
    __info__ = '1-dimensional minimizer for finite box-bound problems'
    __isIterPointAlwaysFeasible__ = lambda self, p: True
    useOOiterfcn = True
    rightLocalization = 0 # stop criterium, should be between 0.0 and 1.0
    leftLocalization = 0 # stop criterium, should be between 0.0 and 1.0
    rightBorderForLocalization = None
    leftBorderForLocalization = None
#    solutionType = 'best'# 'right', 'left' are also allowed

    def __init__(self):pass
    def __solver__(self, p):
        if p.n != 1: p.err('the solver ' + self.__name__ +' can handle singe-variable problems only')
        if not p.__isFiniteBoxBounded__(): p.err('the solver ' + self.__name__ +' requires finite lower and upper bounds')
        if SMALL_DELTA_X in p.kernelIterFuncs.keys(): p.kernelIterFuncs.pop(SMALL_DELTA_X)
        a,  b,  f = p.lb,  p.ub,  p.f
        if self.rightBorderForLocalization is None: self.rightBorderForLocalization = p.ub
        if self.leftBorderForLocalization is None: self.leftBorderForLocalization = p.lb

        if self.leftLocalization * (b - self.leftBorderForLocalization) > b - a:
            p.istop,  p.msg = 23, 'right localization has been reached (objFunc evaluation is skipped)'
        elif self.rightLocalization * (a - self.rightBorderForLocalization) > b - a :
            p.istop,  p.msg = 24, 'left localization has been reached (objFunc evaluation is skipped)'
        if p.istop:
            p.xk,  p.fk = 0.5*(a+b), nan
            return

        #if hasattr(p, )
        #phi = 1.6180339887498949 # (1+sqrt(5)) / 2
        s1 = 0.3819660112501051# (3-sqrt(double(5)))/2
        s2 = 0.6180339887498949# (sqrt(double(5))-1)/2
        x1 = a+s1*(b-a)
        x2 = a+s2*(b-a)
        y1,  y2 = f(x1),  f(x2)
        for i in range(p.maxIter):
            p.xk,  p.fk = 0.5*(x1+x2), 0.5*(y1+y2)
            if y1 <= y2:
                xmin,  ymin = x1,  y1
                b,  x2 = x2,  x1
                x1 = a + s1*(b - a)
                y2, y1 = y1,  f(x1)
            else:
                xmin,  ymin = x2,  y2
                a,  x1 = x1,  x2
                x2 = a + s2*(b - a)
                y1, y2 = y2,  f(x2)
            #TODO: handle fEnough criterium for min(y1, y2), not for 0.5*(y1+y2)
            if self.useOOiterfcn: p.iterfcn()
            if -p.xtol < b - a < p.xtol: # p.iterfcn may be turned off
                p.xf,  p.ff = xmin,  ymin
#                if self.solutionType == 'best':
#                    p.xf,  p.ff = xmin,  ymin
#                elif self.solutionType == 'left':
#                    p.xf,  p.ff = x1,  y1
#                elif self.solutionType == 'right':
#                    p.xf,  p.ff = x2,  y2
#                else:
#                    p.err('incorrect solutionType, should be "best", "right" or "left"')
                p.istop,  p.msg = SMALL_DELTA_X, '|| X[k] - X[k-1] || < xtol'
            elif self.leftLocalization * (b - self.leftBorderForLocalization) > b - a:
                p.istop,  p.msg = 25, 'right localization has been reached'
            elif self.rightLocalization * (a - self.rightBorderForLocalization) > b - a :
                p.istop,  p.msg = 26, 'left localization has been reached'
            if y2 > y1:
                p.special.leftXOptBorder = a
                p.special.rightXOptBorder = x2
            else:
                p.special.leftXOptBorder = x1
                p.special.rightXOptBorder = b
            if p.istop:
                return
        p.istop, p.msg = IS_MAX_ITER_REACHED, 'Max Iter has been reached'