docs: def aligned_residuals(pca):
      """
      Plots error components along with bootstrap
      resampled error surface. Provides another
      statistical method to estimate the variance
      of a dataset.
      """
      A = pca.rotated()
      fig, axes = P.subplots(2,1,
              sharex=True, frameon=False)
      fig.subplots_adjust(hspace=0, wspace=0.1)
      kw = dict(c="#555555", s=40, alpha=0.5)
  
      #lengths = attitude.pca.singular_values[::-1]
      lengths = (A[:,i].max()-A[:,i].min() for i in range(3))
  
      titles = (
          "Long cross-section (axis 3 vs. axis 1)",
          "Short cross-section (axis 3 vs. axis 2)")
  
      for title,ax,(a,b) in zip(titles,axes,
              [(0,2),(1,2)]):
  
          seaborn.regplot(A[:,a], A[:,b], ax=ax)
          ax.text(0,1,title,
              verticalalignment='top',
              transform=ax.transAxes)
          ax.autoscale(tight=True)
          for spine in ax.spines.itervalues():
              spine.set_visible(False)
      ax.set_xlabel("Meters")
      return fig