docstr: Test if the p_value returned by target_binary_feature_real_test is
  low enough for highly significant features.
docstr_tok: ["Test","if","the","p_value","returned","by","target_binary_feature_real_test","is","low","enough","for","highly","significant","features","."]
code: def test_feature_selection_target_binary_features_realvalued_smir(
      self, maximal_p_value_for_significant_features, real_feature
  ):
      """
      Test if the p_value returned by target_binary_feature_real_test is
      low enough for highly significant features.
      """
      y = pd.Series(np.ndarray(250))
      y[real_feature >= 0.3] = 1
      y[real_feature < 0.3] = 0
      y -= pd.Series(np.random.binomial(1, 0.2, 250))
      y[y == -1] = 0
      y[y == 2] = 1
  
      p_value = target_binary_feature_real_test(
          real_feature, y, test="smir"
      )
      assert maximal_p_value_for_significant_features > p_value
  
imports: import numpy
  import pandas
  import pytest
  from tsfresh.defaults import TEST_FOR_BINARY_TARGET_REAL_FEATURE
  from tsfresh.feature_selection.significance_tests import target_binary_feature_binary_test, target_binary_feature_real_test, target_real_feature_binary_test, target_real_feature_real_test
label_desc: Use image node_id 4 for calling the TestSignificant obj's underlying member method code with example usage: obj.test_feature_selection_target_binary_features_realvalued_smir(maximal_p_value_for_significant_features, real_feature) without return types