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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 divide_chain(self, chain=0):
 """ Returns a ChainConsumer instance containing all the walks of a given chain as individual chains themselves. This method might be useful if, for example, your chain was made using MCMC with 4 walkers. To check the sampling of all 4 walkers agree, you could call this to get a ChainConsumer instance with one chain for ech of the four walks. If you then plot, hopefully all four contours you would see agree. Parameters chain : int|str, optional The index or name of the chain you want divided Returns ------- ChainConsumer A new ChainConsumer instance with the same settings as the parent instance, containing ``num_walker`` chains. """

        indexes = self._get_chain(chain)
        con = ChainConsumer()

        for index in indexes:
            chain = self.chains[index]
            assert chain.walkers is not None, "The chain you have selected was not added with any walkers!"
            num_walkers = chain.walkers
            data = np.split(chain.chain, num_walkers)
            ws = np.split(chain.weights, num_walkers)
            for j, (c, w) in enumerate(zip(data, ws)):
                con.add_chain(c, weights=w, name="Chain %d" % j, parameters=chain.parameters)
        return con