docstr: Fitting gauss data should produce percentile splits of standard normal distribution
code: def test_fit_gauss_data(self):
      """Fitting gauss data should produce percentile splits of standard normal distribution"""
  
      arr = np.random.normal(loc=0, scale=1, size=100001)
      np.random.shuffle(arr)
      d = Discretiser(
          method="percentiles", percentile_split_points=[0.1, 0.4, 0.85]
      )
      d.fit(arr)
      assert math.isclose(
          -1.2815, d.numeric_split_points[0], abs_tol=0.025
      )
      assert math.isclose(
          -0.253, d.numeric_split_points[1], abs_tol=0.025
      )
      assert math.isclose(
          1.036, d.numeric_split_points[2], abs_tol=0.025
      )
  
imports: import math
  import numpy
  import pytest
  from causalnex.discretiser import Discretiser
label_desc: Use image node_id 2 for calling the TestPercentile obj's underlying member method code with example usage: obj.test_fit_gauss_data() without return types