code: def test_plot_split_value_histogram(
      params, breast_cancer_split, train_data
  ):
      X_train, _, y_train, _ = breast_cancer_split
  
      gbm0 = lgb.train(params, train_data, num_boost_round=10)
      ax0 = lgb.plot_split_value_histogram(gbm0, 27)
      assert isinstance(ax0, matplotlib.axes.Axes)
      assert (
          ax0.get_title()
          == "Split value histogram for feature with index 27"
      )
      assert ax0.get_xlabel() == "Feature split value"
      assert ax0.get_ylabel() == "Count"
      assert len(ax0.patches) <= 2
  
      gbm1 = lgb.LGBMClassifier(
          n_estimators=10, num_leaves=3, verbose=-1
      )
      gbm1.fit(X_train, y_train)
  
      ax1 = lgb.plot_split_value_histogram(
          gbm1,
          gbm1.booster_.feature_name()[27],
          figsize=(10, 5),
          title="Histogram for feature @index/name@ @feature@",
          xlabel="x",
          ylabel="y",
          color="r",
      )
      assert isinstance(ax1, matplotlib.axes.Axes)
      title = f"Histogram for feature name {gbm1.booster_.feature_name()[27]}"
      assert ax1.get_title() == title
      assert ax1.get_xlabel() == "x"
      assert ax1.get_ylabel() == "y"
      assert len(ax1.patches) <= 2
      for patch in ax1.patches:
          assert patch.get_facecolor() == (1.0, 0, 0, 1.0)  # red
  
      ax2 = lgb.plot_split_value_histogram(
          gbm0,
          27,
          bins=10,
          color=["r", "y", "g", "b"],
          title=None,
          xlabel=None,
          ylabel=None,
      )
      assert isinstance(ax2, matplotlib.axes.Axes)
      assert ax2.get_title() == ""
      assert ax2.get_xlabel() == ""
      assert ax2.get_ylabel() == ""
      assert len(ax2.patches) == 10
      assert ax2.patches[0].get_facecolor() == (1.0, 0, 0, 1.0)  # r
      assert ax2.patches[1].get_facecolor() == (0.75, 0.75, 0, 1.0)  # y
      assert ax2.patches[2].get_facecolor() == (0, 0.5, 0, 1.0)  # g
      assert ax2.patches[3].get_facecolor() == (0, 0, 1.0, 1.0)  # b
  
      with pytest.raises(ValueError):
          lgb.plot_split_value_histogram(gbm0, 0)
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.model_selection import train_test_split
  import lightgbm
  from lightgbm.compat import GRAPHVIZ_INSTALLED, MATPLOTLIB_INSTALLED, PANDAS_INSTALLED, pd_DataFrame
  from .utils import load_breast_cancer, make_synthetic_regression
label_desc: Use image node_id 6 for calling a global function with example usage: test_plot_split_value_histogram(params, breast_cancer_split, train_data) without return types