def ant_glob(self, *k, **kw):

        src = kw.get('src', True)
        dir = kw.get('dir', False)

        excl = kw.get('excl', exclude_regs)
        incl = k and k[0] or kw.get('incl', '**')

        def to_pat(s):
            lst = to_list(s)
            ret = []
            for x in lst:
                x = x.replace('\\', '/').replace('//', '/')
                if x.endswith('/'):
                    x += '**'
                lst2 = x.split('/')
                accu = []
                for k in lst2:
                    if k == '**':
                        accu.append(k)
                    else:
                        k = k.replace('.', '[.]').replace('*','.*').replace('?', '.').replace('+', '\\+')
                        k = '^%s$' % k
                        accu.append(re.compile(k))
                ret.append(accu)
            return ret

        def filtre(name, nn):
            ret = []
            for lst in nn:
                if not lst:
                    pass
                elif lst[0] == '**':
                    ret.append(lst)
                    if len(lst) > 1:
                        if lst[1].match(name):
                            ret.append(lst[2:])
                    else:
                        ret.append([])
                elif lst[0].match(name):
                    ret.append(lst[1:])
            return ret

        def accept(name, pats):
            nacc = filtre(name, pats[0])
            nrej = filtre(name, pats[1])
            if [] in nrej:
                nacc = []
            return [nacc, nrej]

        ret = [x for x in self._ant_iter(accept=accept, pats=[to_pat(incl), to_pat(excl)], maxdepth=25, dir=dir, src=src, remove=kw.get('remove', True))]
        if kw.get('flat', False):
            return ' '.join([x.path_from(self) for x in ret])

        return ret
Event Handler for the nonlinear-parameter scaling bar. FinalUpdate
dataset/ETHPy150Open cournape/Bento/bento/core/node.py/Node.ant_glob--crossover with--dataset/ETHPy150Open enthought/mayavi/tvtk/util/tk_gradient_editor.py/GradientEditor.nonlinear_parameter_scale_changed