code: def test_precision_one_many_same():
      one = covariance.EmpiricalPrecision()
      many = covariance.EmpiricalPrecision()
  
      X = np.random.random((100, 5))
  
      for x, _ in stream.iter_array(X):
          one.update(x)
      many.update_many(pd.DataFrame(X))
  
      for i, j in one._inv_cov:
          assert math.isclose(one[i, j], many[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 9 for calling a global function with example usage: test_precision_one_many_same() without return types