class_docstr: Unit test consistency
class_docstr_tok: ["Unit","test","consistency"]
code: def setUp(self):
      self.df = pd.DataFrame(
          data=np.array(
              [[1, 2, 3, 0], [2, 4, 6, 1], [2, 2, 1, 0], [2, 4, 1, 1]]
          ),
          columns=["X1", "X2", "X3", "y"],
      )
      self.X = self.df.iloc[:, :-1]
      self.y = self.df.iloc[:, -1]
  
      self.w1 = pd.DataFrame(
          np.array(
              [
                  [0.14, 0.04, 0.17],
                  [0.02, 0.01, 0.33],
                  [0.56, 0.12, 0.29],
                  [0.03, 0.01, 0.04],
              ]
          ),
          columns=["X1", "X2", "X3"],
      )
      self.w2 = pd.DataFrame(
          np.array(
              [
                  [0.38, 0.35, 0.01],
                  [0.01, 0.30, 0.05],
                  [0.45, 0.41, 0.12],
                  [0.07, 0.30, 0.21],
              ]
          ),
          columns=["X1", "X2", "X3"],
      )
      self.w3 = pd.DataFrame(
          np.array(
              [
                  [0.49, 0.17, 0.02],
                  [0.25, 0.12, 0.25],
                  [0.01, 0.06, 0.06],
                  [0.19, 0.02, 0.18],
              ]
          ),
          columns=["X1", "X2", "X3"],
      )
      self.contributions = {
          "contrib_1": self.w1,
          "contrib_2": self.w2,
          "contrib_3": self.w3,
      }
  
      self.cns = Consistency()
      self.cns.compile(contributions=self.contributions, x=self.X)
  
file_path: shapash/tests/unit_tests/explainer/test_consistency.py
imports: import itertools
  import numpy
  import pandas
  from sklearn.ensemble import RandomForestClassifier
  import unittest
  from shapash.explainer.consistency import Consistency
label_desc: Use image node_id 1 for calling the TestConsistency obj's underlying member method code with example usage: obj.setUp() without return types