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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 precision(self):
 """ Inverse of posterior covariance """

        if self._precision is None:
            cov = np.atleast_3d(self.covariance)
            self._precision = np.zeros(cov.shape)  # if one covariance per dimension
            for p in range(cov.shape[-1]):
                self._precision[:, :, p] = pdinv(cov[:, :, p])[0]
        return self._precision