docstr: Fitting uniform data should transform to predictable buckets
code: def test_transform_uniform(self):
      """Fitting uniform data should transform to predictable buckets"""
  
      arr = np.array(range(100001))
      np.random.shuffle(arr)
      d = Discretiser(
          method="percentiles",
          percentile_split_points=[0.10, 0.40, 0.85],
      )
      d.fit(arr)
      unique, counts = np.unique(d.transform(arr), return_counts=True)
      # check all 4 buckets are used
      assert np.array_equal([0, 1, 2, 3], unique)
      assert np.array_equal([10000, 30000, 45000, 15001], counts)
  
imports: import math
  import numpy
  import pytest
  from causalnex.discretiser import Discretiser
label_desc: Use image node_id 3 for calling the TestPercentile obj's underlying member method code with example usage: obj.test_transform_uniform() without return types