code: public VarTensor getMarginal(VarSet vars, boolean normalize) {
          VarSet margVars = new VarSet(this.vars);
          margVars.retainAll(vars);
          
          VarTensor marg = new VarTensor(s, margVars, s.zero());
          if (margVars.size() == 0) {
              return marg;
          }
          
          IntIter iter = margVars.getConfigIter(this.vars);
          for (int i=0; i<this.values.length; i++) {
              int j = iter.next();
              marg.values[j] = s.plus(marg.values[j], this.values[i]);
          }
          
          if (normalize) {
              marg.normalize();
          }
          
          return marg;
      }
docs: Gets the marginal distribution over a subset of the variables in this
  factor, optionally normalized.
  
  @param vars The subset of variables for the marginal distribution. This will sum over all variables not in this set.
  @param normalize Whether to normalize the resulting distribution.
  @return The marginal distribution.