strengthen xlim and max_num_features tests

Author: DeborahOlaboye

tests/python_package_test/test_plotting.py

@@ -122,9 +122,18 @@ def test_plot_importance(params, breast_cancer_split, train_data):
         lgb.plot_importance(gbm0, title=None, xlabel=None, ylabel=None, figsize="not a tuple")
 
     # test max_num_features parameter
+    total_features = len(gbm0.feature_importance())
+    assert total_features > 5, "model must have more than 5 features to test max_num_features"
     ax7 = lgb.plot_importance(gbm0, max_num_features=5)
     assert isinstance(ax7, matplotlib.axes.Axes)
     assert len(ax7.patches) == 5
+    # verify the 5 displayed features are the top 5 by importance
+    importance = gbm0.feature_importance()
+    feature_names = gbm0.feature_name()
+    sorted_pairs = sorted(zip(feature_names, importance), key=lambda x: x[1])
+    top5_names = [name for name, _ in sorted_pairs[-5:]]
+    displayed_labels = [label.get_text() for label in ax7.get_yticklabels()]
+    assert displayed_labels == top5_names
 
     gbm2 = lgb.LGBMClassifier(n_estimators=10, num_leaves=3, verbose=-1, importance_type="gain")
     gbm2.fit(X_train, y_train)
@@ -193,10 +202,16 @@ def test_plot_split_value_histogram(params, breast_cancer_split, train_data):
     assert ax2.patches[3].get_facecolor() == (0, 0, 1.0, 1.0)  # b
 
     # test xlim parameter
-    ax3 = lgb.plot_split_value_histogram(gbm0, 27, xlim=(0, 100))
+    ax3 = lgb.plot_split_value_histogram(gbm0, 27, xlim=(0, 100), title=None, xlabel=None, ylabel=None)
     assert isinstance(ax3, matplotlib.axes.Axes)
+    assert ax3.get_title() == ""
+    assert ax3.get_xlabel() == ""
+    assert ax3.get_ylabel() == ""
     assert ax3.get_xlim() == (0, 100)
 
+    with pytest.raises(TypeError, match="xlim must be a tuple of 2 elements."):
+        lgb.plot_split_value_histogram(gbm0, 27, xlim="not a tuple")
+
     with pytest.raises(
         ValueError, match="Cannot plot split value histogram, because feature 0 was not used in splitting"
     ):
@@ -569,6 +584,12 @@ def test_plot_metrics(params, breast_cancer_split, train_data):
     assert legend_items[0].get_text() == "valid_0"
 
     # test xlim parameter
-    ax5 = lgb.plot_metric(evals_result0, metric="binary_logloss", xlim=(0, 15))
+    ax5 = lgb.plot_metric(evals_result0, metric="binary_logloss", xlim=(0, 15), title=None, xlabel=None, ylabel=None)
     assert isinstance(ax5, matplotlib.axes.Axes)
+    assert ax5.get_title() == ""
+    assert ax5.get_xlabel() == ""
+    assert ax5.get_ylabel() == ""
     assert ax5.get_xlim() == (0, 15)
+
+    with pytest.raises(TypeError, match="xlim must be a tuple of 2 elements."):
+        lgb.plot_metric(evals_result0, metric="binary_logloss", xlim="not a tuple")