docstr: ...Test RobustLinearRegression setting of parameter of C
          
docstr_tok: ["...","Test","RobustLinearRegression","setting","of","parameter","of","C"]
code: def test_RobustLinearRegression_fdr(self):
      """...Test RobustLinearRegression setting of parameter of C"""
      fdr1 = 0.33
      fdr2 = 0.78
      learner = RobustLinearRegression(
          C_sample_intercepts=self.float_1, fdr=fdr1
      )
      self.assertEqual(learner.fdr, fdr1)
      self.assertEqual(learner._prox_intercepts_obj.fdr, fdr1)
      learner.fdr = fdr2
      self.assertEqual(learner.fdr, fdr2)
      self.assertEqual(learner._prox_intercepts_obj.fdr, fdr2)
  
      msg = "^``fdr`` must be in \(0, 1\), got -1.0"
      with self.assertRaisesRegex(ValueError, msg):
          RobustLinearRegression(C_sample_intercepts=1.0, fdr=-1.0)
  
      msg = "^``fdr`` must be in \(0, 1\), got 1.5"
      with self.assertRaisesRegex(ValueError, msg):
          RobustLinearRegression(C_sample_intercepts=1.0, fdr=1.5)
  
      msg = "^``fdr`` cannot be `None`$"
      with self.assertRaisesRegex(ValueError, msg):
          RobustLinearRegression(C_sample_intercepts=1.0, fdr=None)
  
      msg = "^``fdr`` must be a finite number, got inf$"
      with self.assertRaisesRegex(ValueError, msg):
          RobustLinearRegression(C_sample_intercepts=1.0, fdr=np.inf)
  
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 10 for calling the Test obj's underlying member method code with example usage: obj.test_RobustLinearRegression_fdr() without return types