Merge branch '291-converter-for-old-pkl-files' into 'master'

implement loading of legacy static agents and enable unit tests again

Closes #291

See merge request flatland/flatland!267

flatland/envs/agent_utils.py

@@ -103,3 +103,13 @@ class EnvAgent:
                                           speed_datas,
                                           malfunction_datas,
                                           range(len(schedule.agent_positions)))))
+
+    @classmethod
+    def load_legacy_static_agent(cls, static_agents_data: Tuple):
+        agents = []
+        for i, static_agent in enumerate(static_agents_data):
+            agent = EnvAgent(initial_position=static_agent[0], initial_direction=static_agent[1],
+                             direction=static_agent[1], target=static_agent[2], moving=static_agent[3],
+                             speed_data=static_agent[4], malfunction_data=static_agent[5], handle=i)
+            agents.append(agent)
+        return agents

flatland/envs/rail_env.py

@@ -869,7 +869,10 @@ class RailEnv(Environment):
         data = msgpack.unpackb(msg_data, use_list=False, encoding='utf-8')
         self.rail.grid = np.array(data["grid"])
         # agents are always reset as not moving
-        self.agents = [EnvAgent(*d[0:12]) for d in data["agents"]]
+        if "agents_static" in data:
+            self.agents = EnvAgent.load_legacy_static_agent(data["agents_static"])
+        else:
+            self.agents = [EnvAgent(*d[0:12]) for d in data["agents"]]
         # setup with loaded data
         self.height, self.width = self.rail.grid.shape
         self.rail.height = self.height
@@ -887,7 +890,10 @@ class RailEnv(Environment):
         data = msgpack.unpackb(msg_data, use_list=False, encoding='utf-8')
         self.rail.grid = np.array(data["grid"])
         # agents are always reset as not moving
-        self.agents = [EnvAgent(*d[0:12]) for d in data["agents"]]
+        if "agents_static" in data:
+            self.agents = EnvAgent.load_legacy_static_agent(data["agents_static"])
+        else:
+            self.agents = [EnvAgent(*d[0:12]) for d in data["agents"]]
         if "distance_map" in data.keys():
             self.distance_map.set(data["distance_map"])
         # setup with loaded data

flatland/envs/schedule_generators.py

@@ -291,7 +291,10 @@ def schedule_from_file(filename, load_from_package=None) -> ScheduleGenerator:
             with open(filename, "rb") as file_in:
                 load_data = file_in.read()
         data = msgpack.unpackb(load_data, use_list=False, encoding='utf-8')
-        agents = [EnvAgent(*d[0:12]) for d in data["agents"]]
+        if "agents_static" in data:
+            agents = EnvAgent.load_legacy_static_agent(data["agents_static"])
+        else:
+            agents = [EnvAgent(*d[0:12]) for d in data["agents"]]
 
         # setup with loaded data
         agents_position = [a.initial_position for a in agents]

tests/test_flatland_envs_rail_env_shortest_paths.py

 import sys
 
 import numpy as np
-import pytest
 
 from flatland.core.grid.grid4 import Grid4TransitionsEnum
 from flatland.envs.observations import TreeObsForRailEnv
@@ -40,7 +39,6 @@ def test_get_shortest_paths_unreachable():
 
 # todo file test_002.pkl has to be generated automatically
 # see https://gitlab.aicrowd.com/flatland/flatland/issues/279
-@pytest.mark.skip
 def test_get_shortest_paths():
     env = load_flatland_environment_from_file('test_002.pkl', 'env_data.tests')
     env.reset()
@@ -172,7 +170,6 @@ def test_get_shortest_paths():
 
 # todo file test_002.pkl has to be generated automatically
 # see https://gitlab.aicrowd.com/flatland/flatland/issues/279
-@pytest.mark.skip
 def test_get_shortest_paths_max_depth():
     env = load_flatland_environment_from_file('test_002.pkl', 'env_data.tests')
     env.reset()
@@ -204,7 +201,6 @@ def test_get_shortest_paths_max_depth():
 
 # todo file Level_distance_map_shortest_path.pkl has to be generated automatically
 # see https://gitlab.aicrowd.com/flatland/flatland/issues/279
-@pytest.mark.skip
 def test_get_shortest_paths_agent_handle():
     env = load_flatland_environment_from_file('Level_distance_map_shortest_path.pkl', 'env_data.tests')
     env.reset()