code: def test_cov_estimate():
      positions = np.random.randn(10, 2)
      gradients = -2 * positions  # x^2 + y^2
      ret = pathfinder.cov_estimate(
          optimization_path=positions,
          optimization_path_grads=gradients,
          history=3,
      )
      assert len(ret) == 9
  
file_path: probability/discussion/pathfinder/pathfinder_test.py
imports: import jax
  import jax.numpy
  import numpy
  import pytest
  from discussion.pathfinder import pathfinder
  import tensorflow_probability.substrates.jax
label_desc: Use image node_id 2 for calling a global function with example usage: test_cov_estimate() without return types