How to use the cma.utilities.utils.rglen function in cma

raise ValueError(
                    "bounds must be None, empty, or a list of length 2"
                    " where each element may be a scalar, list, array,"
                    " or None; type(bounds) was: %s" % str(type(bounds)))
            l = [None, None]  # figure out lengths
            for i in [0, 1]:
                try:
                    l[i] = len(bounds[i])
                except TypeError:
                    bounds[i] = [bounds[i]]
                    l[i] = 1
                if all([bounds[i][j] is None or not np.isfinite(bounds[i][j])
                        for j in rglen(bounds[i])]):
                    bounds[i] = None
                if bounds[i] is not None and any([bounds[i][j] == (-1)**i * np.inf
                                                  for j in rglen(bounds[i])]):
                    raise ValueError('lower/upper is +inf/-inf and ' +
                                     'therefore no finite feasible solution is available')
            self.bounds = bounds

def grad_numerical(self, x, func, epsilon=None):
        """symmetric gradient"""
        eps = 1e-8 * (1 + abs(x)) if epsilon is None else epsilon
        grad = np.zeros(len(x))
        ei = np.zeros(len(x))  # float is 1.6 times faster than int
        for i in rglen(x):
            ei[i] = eps[i]
            grad[i] = (func(x + ei) - func(x - ei)) / (2*eps[i])
            ei[i] = 0
        return grad
    def elliconstraint(self, x, cfac=1e8, tough=True, cond=1e6):

def repair(self, x, copy_if_changed=True):
        """projects infeasible values on the domain bound, might be
        overwritten by derived class """
        copy = copy_if_changed
        if self.bounds is None:
            return x
        for ib in [0, 1]:
            if self.bounds[ib] is None:
                continue
            for i in rglen(x):
                idx = min([i, len(self.bounds[ib]) - 1])
                if self.bounds[ib][idx] is not None and \
                        (-1)**ib * x[i] < (-1)**ib * self.bounds[ib][idx]:
                    if copy:
                        x = np.array(x, copy=True)
                        copy = False
                    x[i] = self.bounds[ib][idx]

def is_in_bounds(self, x):
        """not yet tested"""
        if self.bounds is None:
            return True
        for ib in [0, 1]:
            if self.bounds[ib] is None:
                continue
            for i in rglen(x):
                idx = min([i, len(self.bounds[ib]) - 1])
                if self.bounds[ib][idx] is not None and \
                        (-1)**ib * x[i] < (-1)**ib * self.bounds[ib][idx]:
                    return False
        return True

def lineard(self, x):
        if 1 < 3 and any(array(x) < 0):
            return np.nan
        if 1 < 3 and sum([(10 + i) * x[i] for i in rglen(x)]) > 50e3:
            return np.nan
        return -sum(x)
    def sphere(self, x):

max_i = min((len(self.bounds) - 1, length - 1))
        self._lb = array([self.bounds[min((i, max_i))][0]
                          if self.bounds[min((i, max_i))][0] is not None
                          else -np.Inf
                          for i in range(length)], copy=False)
        self._ub = array([self.bounds[min((i, max_i))][1]
                          if self.bounds[min((i, max_i))][1] is not None
                          else np.Inf
                          for i in range(length)], copy=False)
        lb = self._lb
        ub = self._ub
        # define added values for lower and upper bound
        self._al = array([min([(ub[i] - lb[i]) / 2, (1 + np.abs(lb[i])) / 20])
                             if isfinite(lb[i]) else 1 for i in rglen(lb)], copy=False)
        self._au = array([min([(ub[i] - lb[i]) / 2, (1 + np.abs(ub[i])) / 20])
                             if isfinite(ub[i]) else 1 for i in rglen(ub)], copy=False)

bounds = self.bounds
        if bounds not in (None, [None, None], (None, None)):  # solely for effiency
            if copy:
                x = np.array(x, copy=True)
            if bounds[0] is not None:
                if np.isscalar(bounds[0]):
                    for i in rglen(x):
                        x[i] = max((bounds[0], x[i]))
                else:
                    for i in rglen(x):
                        j = min([i, len(bounds[0]) - 1])
                        if bounds[0][j] is not None:
                            x[i] = max((bounds[0][j], x[i]))
            if bounds[1] is not None:
                if np.isscalar(bounds[1]):
                    for i in rglen(x):
                        x[i] = min((bounds[1], x[i]))
                else:
                    for i in rglen(x):
                        j = min((i, len(bounds[1]) - 1))
                        if bounds[1][j] is not None:
                            x[i] = min((bounds[1][j], x[i]))
        return x

"""sets out-of-bounds components of ``x`` on the bounds.

        """
        # TODO (old data): CPU(N,lam,iter=20,200,100): 3.3s of 8s for two bounds, 1.8s of 6.5s for one bound
        # remark: np.max([bounds[0], x]) is about 40 times slower than max((bounds[0], x))
        copy = copy_if_changed
        bounds = self.bounds
        if bounds not in (None, [None, None], (None, None)):  # solely for effiency
            if copy:
                x = np.array(x, copy=True)
            if bounds[0] is not None:
                if np.isscalar(bounds[0]):
                    for i in rglen(x):
                        x[i] = max((bounds[0], x[i]))
                else:
                    for i in rglen(x):
                        j = min([i, len(bounds[0]) - 1])
                        if bounds[0][j] is not None:
                            x[i] = max((bounds[0][j], x[i]))
            if bounds[1] is not None:
                if np.isscalar(bounds[1]):
                    for i in rglen(x):
                        x[i] = min((bounds[1], x[i]))
                else:
                    for i in rglen(x):
                        j = min((i, len(bounds[1]) - 1))
                        if bounds[1][j] is not None:
                            x[i] = min((bounds[1][j], x[i]))
        return x

if length is None:
            length = len(self.bounds)
        max_i = min((len(self.bounds) - 1, length - 1))
        self._lb = array([self.bounds[min((i, max_i))][0]
                          if self.bounds[min((i, max_i))][0] is not None
                          else -np.Inf
                          for i in range(length)], copy=False)
        self._ub = array([self.bounds[min((i, max_i))][1]
                          if self.bounds[min((i, max_i))][1] is not None
                          else np.Inf
                          for i in range(length)], copy=False)
        lb = self._lb
        ub = self._ub
        # define added values for lower and upper bound
        self._al = array([min([(ub[i] - lb[i]) / 2, (1 + np.abs(lb[i])) / 20])
                             if isfinite(lb[i]) else 1 for i in rglen(lb)], copy=False)
        self._au = array([min([(ub[i] - lb[i]) / 2, (1 + np.abs(ub[i])) / 20])
                             if isfinite(ub[i]) else 1 for i in rglen(ub)], copy=False)