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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _calc_dic(self):
 """Calculates deviance information Criterion"""


        # Find mean deviance
        mean_deviance = np.mean(self.db.trace('deviance')(), axis=0)

        # Set values of all parameters to their mean
        for stochastic in self.stochastics:

            # Calculate mean of paramter
            try:
                mean_value = np.mean(
                    self.db.trace(
                        stochastic.__name__)(
                    ),
                    axis=0)

                # Set current value to mean
                stochastic.value = mean_value

            except KeyError:
                print_(
                    "No trace available for %s. DIC value may not be valid." %
                    stochastic.__name__)
            except TypeError:
                print_(
                    "Not able to calculate DIC: invalid stochastic %s" %
                    stochastic.__name__)
                return None

        # Return twice deviance minus deviance at means
        return 2 * mean_deviance - self.deviance