code: def test_sparse(self):
      X = scipy.sparse.csc_matrix(
          ([1, 2, 0, 4], ([0, 1, 2, 1], [3, 2, 1, 0])), shape=(3, 4)
      )
      Y = CategoryShift().fit_transform(X)
      X.data += 3
      self.assertTrue((Y.todense() == X.todense()).all())
      # Check if the sparsity stays the same before and after the transformation
      self.assertEqual(X.data.shape, Y.data.shape)
      self.assertTrue((X.indices == Y.indices).all())
      self.assertTrue((X.indptr == Y.indptr).all())
  
file_path: auto-sklearn/test/test_pipeline/implementations/test_CategoryShift.py
imports: import numpy
  import scipy.sparse
  from autosklearn.pipeline.implementations.CategoryShift import CategoryShift
  import unittest
label_desc: Use image node_id 2 for calling the CategoryShiftTest obj's underlying member method code with example usage: obj.test_sparse() without return types