@property
def parameters(self):
    'Current parameter values.\n\n        Fixed parameters are returned as is, free parameters represented by\n        :class:`.Variable` instances are replaced by their\n        current numerical value.\n\n        Returns:\n            list[Any]: parameter values\n        '

    def evaluate(p):
        'Evaluate a single parameter.'
        if isinstance(p, np.ndarray):
            if (p.dtype == object):
                temp = np.array([(x.val if isinstance(x, Variable) else x) for x in p.flat])
                return temp.reshape(p.shape)
            return p
        if isinstance(p, list):
            evaled_list = []
            for arr in p:
                if (arr.dtype == object):
                    temp = np.array([(x.val if isinstance(x, Variable) else x) for x in arr.flat])
                    evaled_list.append(temp.reshape(arr.shape))
                    return evaled_list
            return p
        if isinstance(p, Variable):
            p = self.check_domain(p.val)
        return p
    return [evaluate(p) for p in self.data]
Current parameter values.

Fixed parameters are returned as is, free parameters represented by
:class:`.Variable` instances are replaced by their
current numerical value.

Returns:
    list[Any]: parameter values
@property
def parameters(self):
    'Current parameter values.\n\n        Fixed parameters are returned as is, free parameters represented by\n        :class:`.Variable` instances are replaced by their\n        current numerical value.\n\n        Returns:\n            list[Any]: parameter values\n        '

    def evaluate(p):
        'Evaluate a single parameter.'
        if isinstance(p, np.ndarray):
            if (p.dtype == object):
                temp = np.array([(x.val if isinstance(x, Variable) else x) for x in p.flat])
                return temp.reshape(p.shape)
            return p
        if isinstance(p, list):
            evaled_list = []
            for arr in p:
                if (arr.dtype == object):
                    temp = np.array([(x.val if isinstance(x, Variable) else x) for x in arr.flat])
                    evaled_list.append(temp.reshape(arr.shape))
                    return evaled_list
            return p
        if isinstance(p, Variable):
            p = self.check_domain(p.val)
        return p
    return [evaluate(p) for p in self.data]