docstr: ...Test HawkesSumExpKern setting of parameter of
  elastic_net_ratio
docstr_tok: ["...","Test","HawkesSumExpKern","setting","of","parameter","of","elastic_net_ratio"]
code: def test_HawkesSumExpKern_penalty_elastic_net_ratio(self):
      """...Test HawkesSumExpKern setting of parameter of
      elastic_net_ratio
      """
      ratio_1 = 0.6
      ratio_2 = 0.3
  
      for penalty in penalties:
          if penalty == "elasticnet":
              learner = HawkesSumExpKern(
                  self.decays,
                  penalty=penalty,
                  C=self.float_1,
                  elastic_net_ratio=ratio_1,
              )
              self.assertEqual(learner.C, self.float_1)
              self.assertEqual(learner.elastic_net_ratio, ratio_1)
              self.assertEqual(
                  learner._prox_obj.strength, 1.0 / self.float_1
              )
              self.assertEqual(learner._prox_obj.ratio, ratio_1)
  
              learner.elastic_net_ratio = ratio_2
              self.assertEqual(learner.C, self.float_1)
              self.assertEqual(learner.elastic_net_ratio, ratio_2)
              self.assertEqual(learner._prox_obj.ratio, ratio_2)
  
          else:
              learner = HawkesSumExpKern(self.decays, penalty=penalty)
              msg = (
                  '^Penalty "%s" has no elastic_net_ratio attribute$$'
                  % penalty
              )
              with self.assertWarnsRegex(RuntimeWarning, msg):
                  learner.elastic_net_ratio = ratio_1
  
imports: import unittest
  import numpy
  from tick.base.inference import InferenceTest
  from tick.hawkes import SimuHawkesSumExpKernels, SimuHawkesMulti
  from tick.hawkes.inference import HawkesSumExpKern
  from tick.prox import ProxNuclear
  from tick.prox import ProxPositive, ProxL1, ProxL2Sq, ProxElasticNet
  from tick.solver import AGD, GD, BFGS, SGD, SVRG
label_desc: Use image node_id 13 for calling the Test obj's underlying member method code with example usage: obj.test_HawkesSumExpKern_penalty_elastic_net_ratio() without return types