code: def explained_variance(self):
          
          v = N.diagonal(self.covariance_matrix)
          return v[0:2].sum()/v.sum()
docs: Proportion of variance that is explained by the
          first two principal components (which together
          represent the planar fit). Analogous to R^2 of
          linear least squares.