code: def test_2d_custom_ranks_incorrect_dimension(
      ploomber_value_error_message,
  ):
      ranks = np.array([1.0, -0.076, 0.71, 0.65])
      with pytest.raises(
          ValueError, match=ploomber_value_error_message
      ) as e:
          Rank2D(
              features=["Feature1", "Feature2", "Feature3", "Feature4"],
              figsize=(9, 12),
          ).feature_ranks_custom_algorithm(ranks)
          assert "Ranks must be 2-dimensional" in str(e.value)
  
imports: import matplotlib.pyplot
  import pytest
  import pandas
  import numpy
  from sklearn.datasets import load_iris
  from matplotlib.testing.decorators import image_comparison
  from sklearn_evaluation.plot import Rank1D, Rank2D
label_desc: Use image node_id 24 for calling a global function with example usage: test_2d_custom_ranks_incorrect_dimension(ploomber_value_error_message) without return types