<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def get_ordered_values(self, keypath, distance_from, open_interval=True):
 """ Retrieves the referents's values sorted by their distance from the min, max, or mid value. """


        values = []
        if keypath[0] == 'target':
            # instances start with 'target' prefix, but 
            # don't contain it, so we remove it here.
            keypath = keypath[1:]
        for _, instance in self.iter_singleton_referents():
            value = instance.get_value_from_path(keypath)
            if hasattr(value, 'low') and value.low != value.high:
                return []
            values.append(float(value))

        if len(values) == 0:
            return []
        values = np.array(values)
        anchor = values.min()
        diffs = values - anchor
        if distance_from == 'max':
            anchor = values.max()
            diffs = anchor - values
        if distance_from == 'mean':
            anchor = values.mean()
            diffs = abs(anchor - values)

        sdiffs = np.unique(diffs)
        sdiffs.sort()
        results = []
      
        for ix, el in enumerate(sdiffs):
            mask = diffs <= el
            vals = values[mask]
            if False:
                # when vagueness has been made precise through an ordinal
                results.append(IntervalCell(vals.min(), vals.max()))
            elif distance_from == 'max':
                if open_interval:
                    results.append(IntervalCell(vals.min(), np.inf))
                else:
                    results.append(IntervalCell(vals.min(), vals.min()))
            elif distance_from == 'min':
                if open_interval:
                    results.append(IntervalCell(-np.inf, vals.max()))
                else:
                    results.append(IntervalCell(vals.max(), vals.max()))
            elif distance_from == 'mean':
                if ix+1 == len(sdiffs): continue  # skip last
                results.append(IntervalCell(vals.min(), vals.max()))
        return results