code: def test_2d_custom_ranks_incorrect_features(
      ploomber_value_error_message,
  ):
      ranks = np.array(
          [
              [1.0, -0.076, 0.71, 0.65],
              [-0.076, 1.0, -0.18, -0.15],
              [0.71, -0.18, 1.0, 0.80],
              [0.65, -0.15, 0.80, 1.0],
          ]
      )
      with pytest.raises(
          ValueError, match=ploomber_value_error_message
      ) as e:
          Rank2D(
              features=["Feature1", "Feature2", "Feature3"]
          ).feature_ranks_custom_algorithm(ranks)
          assert (
              "number of supplied feature names does not match the number "
              "of ranks provided." 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 26 for calling a global function with example usage: test_2d_custom_ranks_incorrect_features(ploomber_value_error_message) without return types