code: def clf_predict_proba(self, clust, covmats, n=None):
      if n is None:
          n_matrices = len(covmats)
          clf = clust()
      else:  # PotatoField
          n_matrices = len(covmats[0])
          clf = clust(n_potatoes=n)
      clf.fit(covmats)
      probabilities = clf.predict(covmats)
      assert probabilities.shape == (n_matrices,)
  
imports: from conftest import get_metrics
  import numpy
  from numpy.testing import assert_array_equal
  import pytest
  from pyriemann.clustering import Kmeans, KmeansPerClassTransform, Potato, PotatoField
label_desc: Use image node_id 6 for calling the TestRiemannianClustering obj's underlying member method code with example usage: obj.clf_predict_proba(clust, covmats, n) without return types