Add linear leaf models to json output (fixes #4186) (#4329)

* Add linear leaf models to json output

* Add closing bracket

* Move test into test_engine.py and add asserts

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

include/LightGBM/tree.h

@@ -243,6 +243,9 @@ class Tree {
   /*! \brief Serialize this object to json*/
   std::string ToJSON() const;
 
+  /*! \brief Serialize linear model of tree node to json*/
+  std::string LinearModelToJSON(int index) const;
+
   /*! \brief Serialize this object to if-else statement*/
   std::string ToIfElse(int index, bool predict_leaf_index) const;
 

src/io/tree.cpp

@@ -417,11 +417,39 @@ std::string Tree::ToJSON() const {
   str_buf << "\"num_cat\":" << num_cat_ << "," << '\n';
   str_buf << "\"shrinkage\":" << shrinkage_ << "," << '\n';
   if (num_leaves_ == 1) {
-    str_buf << "\"tree_structure\":{" << "\"leaf_value\":" << leaf_value_[0] << "}" << '\n';
+    if (is_linear_) {
+      str_buf << "\"tree_structure\":{" << "\"leaf_value\":" << leaf_value_[0] << ", " << "\n";
+      str_buf << LinearModelToJSON(0) << "}" << "\n";
+    } else {
+      str_buf << "\"tree_structure\":{" << "\"leaf_value\":" << leaf_value_[0] << "}" << '\n';
+    }
   } else {
     str_buf << "\"tree_structure\":" << NodeToJSON(0) << '\n';
   }
+  return str_buf.str();
+}
 
+std::string Tree::LinearModelToJSON(int index) const {
+  std::stringstream str_buf;
+  Common::C_stringstream(str_buf);
+  str_buf << std::setprecision(std::numeric_limits<double>::digits10 + 2);
+  str_buf << "\"leaf_const\":" << leaf_const_[index] << "," << "\n";
+  int num_features = static_cast<int>(leaf_features_[index].size());
+  if (num_features > 0) {
+    str_buf << "\"leaf_features\":[";
+    for (int i = 0; i < num_features - 1; ++i) {
+      str_buf << leaf_features_[index][i] << ", ";
+    }
+    str_buf << leaf_features_[index][num_features - 1] << "]" << ", " << "\n";
+    str_buf << "\"leaf_coeff\":[";
+    for (int i = 0; i < num_features - 1; ++i) {
+      str_buf << leaf_coeff_[index][i] << ", ";
+    }
+    str_buf << leaf_coeff_[index][num_features - 1] << "]" << "\n";
+  } else {
+    str_buf << "\"leaf_features\":[],\n";
+    str_buf << "\"leaf_coeff\":[]\n";
+  }
   return str_buf.str();
 }
 
@@ -479,10 +507,14 @@ std::string Tree::NodeToJSON(int index) const {
     str_buf << "\"leaf_index\":" << index << "," << '\n';
     str_buf << "\"leaf_value\":" << leaf_value_[index] << "," << '\n';
     str_buf << "\"leaf_weight\":" << leaf_weight_[index] << "," << '\n';
-    str_buf << "\"leaf_count\":" << leaf_count_[index] << '\n';
+    if (is_linear_) {
+      str_buf << "\"leaf_count\":" << leaf_count_[index] << "," << '\n';
+      str_buf << LinearModelToJSON(index);
+    } else {
+      str_buf << "\"leaf_count\":" << leaf_count_[index] << '\n';
+    }
     str_buf << "}";
   }
-
   return str_buf.str();
 }
 

tests/python_package_test/test_engine.py

@@ -2793,3 +2793,28 @@ def test_reset_params_works_with_metric_num_class_and_boosting():
     expected_params = dict(dataset_params, **booster_params)
     assert bst.params == expected_params
     assert new_bst.params == expected_params
+
+
+def test_dump_model():
+    X, y = load_breast_cancer(return_X_y=True)
+    train_data = lgb.Dataset(X, label=y)
+    params = {
+        "objective": "binary",
+        "verbose": -1
+    }
+    bst = lgb.train(params, train_data, num_boost_round=5)
+    dumped_model_str = str(bst.dump_model(5, 0))
+    assert "leaf_features" not in dumped_model_str
+    assert "leaf_coeff" not in dumped_model_str
+    assert "leaf_const" not in dumped_model_str
+    assert "leaf_value" in dumped_model_str
+    assert "leaf_count" in dumped_model_str
+    params['linear_tree'] = True
+    train_data = lgb.Dataset(X, label=y)
+    bst = lgb.train(params, train_data, num_boost_round=5)
+    dumped_model_str = str(bst.dump_model(5, 0))
+    assert "leaf_features" in dumped_model_str
+    assert "leaf_coeff" in dumped_model_str
+    assert "leaf_const" in dumped_model_str
+    assert "leaf_value" in dumped_model_str
+    assert "leaf_count" in dumped_model_str