text: /******************************************************************************
   * Copyright 2017 The Apollo Authors. All Rights Reserved.
   *
   * Licensed under the Apache License, Version 2.0 (the "License");
   * you may not use this file except in compliance with the License.
   * You may obtain a copy of the License at
   *
   * http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   *****************************************************************************/
  
  #include "modules/prediction/evaluator/vehicle/mlp_evaluator.h"
  
  #include "cyber/common/file.h"
  #include "modules/prediction/common/kml_map_based_test.h"
  #include "modules/prediction/container/obstacles/obstacles_container.h"
  
  namespace apollo {
  namespace prediction {
  
  class MLPEvaluatorTest : public KMLMapBasedTest {
   public:
    void SetUp() override {
      const std::string file =
          "modules/prediction/testdata/single_perception_vehicle_onlane.pb.txt";
      ACHECK(cyber::common::GetProtoFromFile(file, &perception_obstacles_));
    }
  
   protected:
    apollo::perception::PerceptionObstacles perception_obstacles_;
  };
  
  TEST_F(MLPEvaluatorTest, OnLaneCase) {
    EXPECT_DOUBLE_EQ(perception_obstacles_.header().timestamp_sec(),
                     1501183430.161906);
    apollo::perception::PerceptionObstacle perception_obstacle =
        perception_obstacles_.perception_obstacle(0);
    EXPECT_EQ(perception_obstacle.id(), 1);
    MLPEvaluator mlp_evaluator;
    ObstaclesContainer container;
    container.Insert(perception_obstacles_);
    container.BuildLaneGraph();
    Obstacle* obstacle_ptr = container.GetObstacle(1);
    EXPECT_NE(obstacle_ptr, nullptr);
    mlp_evaluator.Evaluate(obstacle_ptr, &container);
    const Feature& feature = obstacle_ptr->latest_feature();
    const LaneGraph& lane_graph = feature.lane().lane_graph();
    for (const auto& lane_sequence : lane_graph.lane_sequence()) {
      EXPECT_TRUE(lane_sequence.has_probability());
    }
    mlp_evaluator.Clear();
  }
  
  }  // namespace prediction
  }  // namespace apollo
  