docstr: ...Test RobustLinearRegression setting of basic parameters of solver
          
docstr_tok: ["...","Test","RobustLinearRegression","setting","of","basic","parameters","of","solver"]
code: def test_RobustLinearRegression_solver_basic_settings(self):
      """...Test RobustLinearRegression setting of basic parameters of solver"""
      for solver in RobustLinearRegression._solvers.keys():
          # tol
          learner = RobustLinearRegression(
              C_sample_intercepts=1.0,
              solver=solver,
              tol=self.float_1,
              **Test.specific_solver_kwargs(solver),
          )
          self.assertEqual(learner.tol, self.float_1)
          self.assertEqual(learner._solver_obj.tol, self.float_1)
          learner.tol = self.float_2
          self.assertEqual(learner.tol, self.float_2)
          self.assertEqual(learner._solver_obj.tol, self.float_2)
  
          # max_iter
          learner = RobustLinearRegression(
              C_sample_intercepts=1.0,
              solver=solver,
              max_iter=self.int_1,
              **Test.specific_solver_kwargs(solver),
          )
          self.assertEqual(learner.max_iter, self.int_1)
          self.assertEqual(learner._solver_obj.max_iter, self.int_1)
          learner.max_iter = self.int_2
          self.assertEqual(learner.max_iter, self.int_2)
          self.assertEqual(learner._solver_obj.max_iter, self.int_2)
  
          # verbose
          learner = RobustLinearRegression(
              C_sample_intercepts=1.0,
              solver=solver,
              verbose=True,
              **Test.specific_solver_kwargs(solver),
          )
          self.assertEqual(learner.verbose, True)
          self.assertEqual(learner._solver_obj.verbose, True)
          learner.verbose = False
          self.assertEqual(learner.verbose, False)
          self.assertEqual(learner._solver_obj.verbose, False)
  
          learner = RobustLinearRegression(
              C_sample_intercepts=1.0,
              solver=solver,
              verbose=False,
              **Test.specific_solver_kwargs(solver),
          )
          self.assertEqual(learner.verbose, False)
          self.assertEqual(learner._solver_obj.verbose, False)
          learner.verbose = True
          self.assertEqual(learner.verbose, True)
          self.assertEqual(learner._solver_obj.verbose, True)
  
          # print_every
          learner = RobustLinearRegression(
              C_sample_intercepts=1.0,
              solver=solver,
              print_every=self.int_1,
              **Test.specific_solver_kwargs(solver),
          )
          self.assertEqual(learner.print_every, self.int_1)
          self.assertEqual(learner._solver_obj.print_every, self.int_1)
          learner.print_every = self.int_2
          self.assertEqual(learner.print_every, self.int_2)
          self.assertEqual(learner._solver_obj.print_every, self.int_2)
  
          # record_every
          learner = RobustLinearRegression(
              C_sample_intercepts=1.0,
              solver=solver,
              record_every=self.int_1,
              **Test.specific_solver_kwargs(solver),
          )
          self.assertEqual(learner.record_every, self.int_1)
          self.assertEqual(learner._solver_obj.record_every, self.int_1)
          learner.record_every = self.int_2
          self.assertEqual(learner.record_every, self.int_2)
          self.assertEqual(learner._solver_obj.record_every, self.int_2)
  
imports: import itertools
  import unittest
  import numpy
  from tick.base.inference import InferenceTest
  from tick.robust import RobustLinearRegression
  from tick.simulation import weights_sparse_gauss, features_normal_cov_toeplitz
  from tick.metrics import support_fdp, support_recall
label_desc: Use image node_id 13 for calling the Test obj's underlying member method code with example usage: obj.test_RobustLinearRegression_solver_basic_settings() without return types