code: def test_blend_raises_on_oversampling():
      """[Base] BlendIndex: check raises error on float sums > 1.0."""
      for tup in [(1.2, None), (0.6, 0.6)]:
          with np.testing.assert_raises(ValueError):
              BlendIndex(*tup, X=X)
  
imports: import os
  import subprocess
  import numpy
  from mlens import config
  from mlens.utils import IdTrain
  from mlens.index import FoldIndex, BlendIndex, SubsetIndex, TemporalIndex, ClusteredSubsetIndex, FullIndex
  from mlens.index.base import partition, prune_train
label_desc: Use image node_id 25 for calling a global function with example usage: test_blend_raises_on_oversampling() without return types