code: def test_univariate_multivariate_consistency(p):
      X = pd.DataFrame(np.random.random((30, p)), columns=range(p))
  
      multi = proba.MultivariateGaussian()
      single = {c: proba.Gaussian() for c in X.columns}
  
      for x in X.to_dict(orient="records"):
          multi.update(x)
          for c, s in single.items():
              s.update(x[c])
  
      for c in X.columns:
          assert math.isclose(multi.mu[c], single[c].mu)
          assert math.isclose(multi.sigma[c][c], single[c].sigma)
  
imports: from __future__ import annotations
  import math
  import numpy
  import pandas
  import pytest
  from river import proba
label_desc: Use image node_id 1 for calling a global function with example usage: test_univariate_multivariate_consistency(p) without return types