fix feature index in Dataset::AddFeaturesFrom (fixes #5410)

src/io/dataset.cpp

@@ -1495,7 +1495,7 @@ void Dataset::AddFeaturesFrom(Dataset* other) {
                    other->max_bin_by_feature_, other->num_total_features_, -1);
   num_total_features_ += other->num_total_features_;
   for (size_t i = 0; i < (other->numeric_feature_map_).size(); ++i) {
-    int feat_ind = numeric_feature_map_[i];
+    int feat_ind = other->numeric_feature_map_[i];
     if (feat_ind > -1) {
       numeric_feature_map_.push_back(feat_ind + num_numeric_features_);
     } else {

tests/python_package_test/test_basic.py

@@ -376,6 +376,29 @@ def test_add_features_from_different_sources():
             assert d1.feature_name == res_feature_names
 
 
+def test_add_features_does_not_fail_if_initial_dataset_has_zero_informative_features(capsys):
+
+    arr_a = np.zeros((100, 1), dtype=np.float32)
+    arr_b = np.random.normal(size=(100, 5))
+
+    dataset_a = lgb.Dataset(arr_a).construct()
+    expected_msg = (
+        '[LightGBM] [Warning] There are no meaningful features which satisfy '
+        'the provided configuration. Decreasing Dataset parameters min_data_in_bin '
+        'or min_data_in_leaf and re-constructing Dataset might resolve this warning.\n'
+    )
+    log_lines = capsys.readouterr().out
+    assert expected_msg in log_lines
+
+    dataset_b = lgb.Dataset(arr_b).construct()
+
+    original_handle = dataset_a.handle.value
+    dataset_a.add_features_from(dataset_b)
+    assert dataset_a.num_feature() == 6
+    assert dataset_a.num_data() == 100
+    assert dataset_a.handle.value == original_handle
+
+
 def test_cegb_affects_behavior(tmp_path):
     X = np.random.random((100, 5))
     X[:, [1, 3]] = 0