# Path: osim/redis/messages.py
# class OSIM_RL:
#     PING = "OSIM_RL.PING"
#     PONG = "OSIM_RL.PONG"
#     ENV_CREATE = "OSIM_RL.ENV_CREATE"
#     ENV_CREATE_RESPONSE = "OSIM_RL.ENV_CREATE_RESPONSE"
#     ENV_RESET = "OSIM_RL.ENV_RESET"
#     ENV_RESET_RESPONSE = "OSIM_RL.ENV_RESET_RESPONSE"
#     ENV_STEP = "OSIM_RL.ENV_STEP"
#     ENV_STEP_RESPONSE = "OSIM_RL.ENV_STEP_RESPONSE"
#     ENV_SUBMIT = "OSIM_RL.ENV_SUBMIT"
#     ENV_SUBMIT_RESPONSE = "OSIM_RL.ENV_SUBMIT_RESPONSE"
#     ERROR = "OSIM_RL.ERROR"


import redis
import json
import numpy as np
import msgpack
import msgpack_numpy as m
import osim
import os
import timeout_decorator
import time
    import argparse
from osim.redis import messages
from osim.env import *
                    _payload = command['payload']

                    if self.env: #If env already exists, throw an error
                        _error_message = "Attempt to create environment when one already exists."
                        if self.verbose: print("Responding with : ", self._error_template(_error_message))
                        _redis.rpush( command_response_channel, self._error_template(_error_message))
                        return self._error_template(_error_message)
                    else:
                        self.env = L2M2019Env(  visualize = self.visualize,
                                                    difficulty = self.difficulty,
                                                    seed = self.seed_map[self.simulation_count],
                                                    report = self.report
                        )
                        _observation = self.env.reset(project=False)
                        self.begin_simulation = time.time()
                        self.simualation_rewards.append(0)
                        self.env_available = True
                        self.current_step = 0
                        #_observation = np.array(_observation).tolist()
                        if self.report:
                            """
                                In case of reporting mode, truncate to the first
                                41 observations.
                                (The rest are extra activations which are used only for reporting
                                and should not be available to the agent)
                            """
                            #_observation = _observation[:41]
                            pass

                        _command_response = {}

# Path: osim/redis/messages.py
# class OSIM_RL:
#     PING = "OSIM_RL.PING"
#     PONG = "OSIM_RL.PONG"
#     ENV_CREATE = "OSIM_RL.ENV_CREATE"
#     ENV_CREATE_RESPONSE = "OSIM_RL.ENV_CREATE_RESPONSE"
#     ENV_RESET = "OSIM_RL.ENV_RESET"
#     ENV_RESET_RESPONSE = "OSIM_RL.ENV_RESET_RESPONSE"
#     ENV_STEP = "OSIM_RL.ENV_STEP"
#     ENV_STEP_RESPONSE = "OSIM_RL.ENV_STEP_RESPONSE"
#     ENV_SUBMIT = "OSIM_RL.ENV_SUBMIT"
#     ENV_SUBMIT_RESPONSE = "OSIM_RL.ENV_SUBMIT_RESPONSE"
#     ERROR = "OSIM_RL.ERROR"


# Path: osim/redis/service.py
import redis
import json
import numpy as np
import msgpack
import msgpack_numpy as m
import osim
import os
import timeout_decorator
import time
    import argparse
from osim.redis import messages
from osim.env import *

                    _payload = command['payload']

                    if self.env: #If env already exists, throw an error
                        _error_message = "Attempt to create environment when one already exists."
                        if self.verbose: print("Responding with : ", self._error_template(_error_message))
                        _redis.rpush( command_response_channel, self._error_template(_error_message))
                        return self._error_template(_error_message)
                    else:
                        self.env = L2M2019Env(  visualize = self.visualize,
                                                    difficulty = self.difficulty,
                                                    seed = self.seed_map[self.simulation_count],
                                                    report = self.report
                        )
                        _observation = self.env.reset(project=False)
                        self.begin_simulation = time.time()
                        self.simualation_rewards.append(0)
                        self.env_available = True
                        self.current_step = 0
                        #_observation = np.array(_observation).tolist()
                        if self.report:
                            """
                                In case of reporting mode, truncate to the first
                                41 observations.
                                (The rest are extra activations which are used only for reporting
                                and should not be available to the agent)
                            """
                            #_observation = _observation[:41]
                            pass

                        _command_response = {}

                        _command_response['type'] = messages.OSIM_RL.ENV_CREATE_RESPONSE