docs: def lp10(self, subset_k, subset_p, weights={}):
          """Force reactions in K above epsilon while minimizing support of P.
  
          This program forces reactions in subset K to attain flux > epsilon
          while minimizing the sum of absolute flux values for reactions
          in subset P (L1-regularization).
          """
  
          if self._z is None:
              self._add_minimization_vars()
  
          positive = set(subset_k) - self._flipped
          negative = set(subset_k) & self._flipped
  
          v = self._v.set(positive)
          cs = self._prob.add_linear_constraints(v >= self._epsilon)
          self._temp_constr.extend(cs)
  
          v = self._v.set(negative)
          cs = self._prob.add_linear_constraints(v <= -self._epsilon)
          self._temp_constr.extend(cs)
  
          self._prob.set_objective(self._z.expr(
              (rxnid, -weights.get(rxnid, 1)) for rxnid in subset_p))
  
          self._solve()