code: def test_univariate_classifier_mixin(sample_weight):
      clf = SAXVSM().fit(X_uni, y_uni)
      assert isinstance(
          clf.score(X_uni, y_uni, sample_weight), (float, np.floating)
      )
  
file_path: pyts/pyts/tests/test_base.py
imports: import numpy
  import pytest
  from sklearn.base import clone
  from pyts.classification import SAXVSM
  from pyts.datasets import load_gunpoint, load_basic_motions
  from pyts.multivariate.image import JointRecurrencePlot
  from pyts.multivariate.classification import MultivariateClassifier
  from pyts.approximation import SymbolicFourierApproximation
label_desc: Use image node_id 3 for calling a global function with example usage: test_univariate_classifier_mixin(sample_weight) without return types