code: def test_precision_update_many_mini_batches():
      C1 = covariance.EmpiricalPrecision()
      C2 = covariance.EmpiricalPrecision()
  
      X = pd.DataFrame(np.random.random((100, 5)))
  
      C1.update_many(X)
      for Xb in np.split(X, 5):
          C2.update_many(Xb)
  
      for i, j in C1._inv_cov:
          assert math.isclose(C1[i, j], C2[i, j])
  
file_path: river/river/covariance/test_emp.py
imports: from __future__ import annotations
  import math
  import random
  import numpy
  import pandas
  import pytest
  from river import covariance, stream
label_desc: Use image node_id 8 for calling a global function with example usage: test_precision_update_many_mini_batches() without return types