code: def setUp(self):
      self.features = np.array(
          [
              [0.00902084, 0.54159776, 0.0, "z"],
              [0.46599565, -0.71875887, 0.0, 2.0],
              [0.52091721, -0.83803094, 1.0, 2.0],
              [0.47315496, 0.0730993, 1.0, 1.0],
              [0.08180209, -1.11447889, 0.0, 0.0],
              [0.45011727, -0.57931684, 0.0, 0.0],
              [2.04347947, -0.10127498, 1.0, 20.0],
              [-0.98909384, 1.36281079, 0.0, 0.0],
              [-0.30637613, -0.19147753, 1.0, 1.0],
              [0.27110903, 0.44583304, 0.0, 0.0],
          ]
      )
      self.columns = [
          "c:continuous",
          "a:continuous",
          "d:discrete",
          "b:discrete",
      ]
      self.df_features = pd.DataFrame(
          self.features, columns=self.columns
      )
  
      self.default_expected_intervals = np.array(
          [
              [0, 3, 0, 4],
              [2, 0, 0, 2],
              [3, 0, 1, 2],
              [2, 2, 1, 1],
              [1, 0, 0, 0],
              [2, 1, 0, 0],
              [3, 2, 1, 3],
              [0, 3, 0, 0],
              [0, 1, 1, 1],
              [1, 2, 0, 0],
          ]
      )
  
file_path: tick/tick/preprocessing/tests/features_binarizer_test.py
imports: import unittest
  import numpy
  import pandas
  from sklearn.preprocessing import OneHotEncoder
  from scipy.sparse import csr
  from tick.preprocessing.features_binarizer import FeaturesBinarizer
label_desc: Use image node_id 1 for calling the Test obj's underlying member method code with example usage: obj.setUp() without return types