docs: def dissimilarities(feature_names, fcs):
      '''Computes the pairwise dissimilarity matrices.
  
      This returns a dictionary mapping each name in ``feature_names``
      to a pairwise dissimilarities matrix. The dissimilaritiy scores
      correspond to ``1 - kernel`` between each feature of each
      pair of feature collections in ``fcs``.
  
      (The kernel used is currently fixed to ``cosine`` distance.)
      '''
      dis = {}
      for count, name in enumerate(feature_names, 1):
          logger.info('computing pairwise dissimilarity matrix '
                      'for %d of %d features (current feature: %s)',
                      count, len(feature_names), name)
          # opportunity to use joblib is buried down inside call to
          # pairwise_distances...
          # And it's fixed to `n_jobs=1` because running multiprocessing
          # inside py.test causes weird problems. It also doesn't seem like a
          # good idea to do it inside a web server either. ---AG
          dis[name] = 1 - pairwise_distances(
              dict_vector().fit_transform([get_feat(fc, name) for fc in fcs]),
              metric='cosine', n_jobs=1)
      return dis