code: def solve(self, S, dimK=None):
          
  
          # Use dimK specified in __init__ as default
          if dimK is None and self.dimK is not None:
              dimK = self.dimK
  
          # Start solve timer
          self.timer.start(['solve', 'solve_wo_eval'])
  
          # Solve CSC problem on S and do dictionary step
          self.init_vars(S, dimK)
          self.xstep(S, self.lmbda, dimK)
          self.dstep()
  
          # Stop solve timer
          self.timer.stop('solve_wo_eval')
  
          # Extract and record iteration stats
          self.manage_itstat()
  
          # Increment iteration count
          self.j += 1
  
          # Stop solve timer
          self.timer.stop('solve')
  
          # Return current dictionary
          return self.getdict()
docs: Compute sparse coding and dictionary update for training
          data `S`.