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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 get_correlations(self, chain=0, parameters=None):
 """ Takes a chain and returns the correlation between chain parameters. Parameters chain : int|str, optional The chain index or name. Defaults to first chain. parameters : list[str], optional The list of parameters to compute correlations. Defaults to all parameters for the given chain. Returns ------- tuple The first index giving a list of parameter names, the second index being the 2D correlation matrix. """

        parameters, cov = self.get_covariance(chain=chain, parameters=parameters)
        diag = np.sqrt(np.diag(cov))
        divisor = diag[None, :] * diag[:, None]
        correlations = cov / divisor
        return parameters, correlations