code: def test_1d_custom_ranks():
      ranks = np.array([0.96784323, 0.79394983, 0.47927427])
      Rank1D(
          features=["Feature1", "Feature2", "Feature3"],
          orient="h",
          figsize=(13, 7),
      ).feature_ranks_custom_algorithm(ranks)
  
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 9 for calling a global function with example usage: test_1d_custom_ranks() without return types