code: def estimators(request):
      space, initialisation_method = request.param
  
      request.cls.estimator = RiemannianEM(
          space,
          initialisation_method=initialisation_method,
          n_gaussians=random.randint(2, 4),
      )
  
file_path: geomstats/tests/tests_geomstats/test_learning/test_expectation_maximization.py
imports: import random
  import pytest
  import geomstats.backend
  from geomstats.geometry.hypersphere import Hypersphere
  from geomstats.geometry.poincare_ball import PoincareBall
  from geomstats.learning.expectation_maximization import GaussianMixtureModel, RiemannianEM
  from geomstats.test.parametrizers import DataBasedParametrizer
  from geomstats.test.test_case import autograd_backend, autograd_only
  from geomstats.test_cases.learning.expectation_maximization import GaussianMixtureModelTestCase, RiemannianEMTestCase
  from .data.expectation_maximization import GaussianMixtureModelTestData, RiemannianEMTestData
label_desc: Use image node_id 1 for calling a global function with example usage: estimators(request) without return types