"""
This module hosts common configurations for the Cartpole problem as
described in some of the popular papers around the problem.
"""
from __future__ import annotations

from typing import Type, TypedDict

import numpy as np

from commander.ml.agent.agent import CartpoleAgent
from commander.ml.agent.goal import AgentGoalMixinBase
from commander.ml.agent.state_specification import AgentStateSpecificationBase
from commander.ml.agent.type_aliases import GoalParams
from commander.network.constants import DEFAULT_BAUDRATE, DEFAULT_PORT


class Configuration(TypedDict, total=False):
    agent: AgentConfiguration


class AgentConfiguration(TypedDict, total=False):
    name: str
    goal_params: GoalParams

    agent: Type[CartpoleAgent]
    goal: Type[AgentGoalMixinBase]
    state_spec: Type[AgentStateSpecificationBase]


class SimulatedConfiguration(Configuration):
    agent: SimulatedAgentConfiguration  # type: ignore[misc]


class SimulatedAgentConfiguration(AgentConfiguration, total=False):
    integration_resolution: int
    max_steps: int
    start_pos: float
    start_pos_velo: float
    start_angle: float
    start_angle_velo: float
    grav_acc: float
    mass_cart: float
    mass_pole: float
    friction_cart: float
    friction_pole: float
    pole_length: float
    force_mag: float
    tau: float


DefaultSimulatedConfiguration: SimulatedConfiguration = {
    "agent": {
        "integration_resolution": 2,
        "max_steps": 5000,
    }
}

# DeepPILCO
# See: http://mlg.eng.cam.ac.uk/yarin/PDFs/DeepPILCO.pdf
# See: https://github.com/zuoxingdong/DeepPILCO/blob/master/cartpole_swingup.py
DeepPILCOConfiguration = DefaultSimulatedConfiguration.copy()
DeepPILCOConfiguration["agent"].update(
    {
        "start_pos": 0.0,
        "start_pos_velo": 0.0,
        "start_angle": 0.0,
        "start_angle_velo": 0.0,
        "grav_acc": 9.82,  # m/s
        "mass_cart": 0.5,  # kg
        "mass_pole": 0.5,  # kg
        "friction_cart": 0.1,  # coeff
        "friction_pole": 0.0,  # coeff
        "pole_length": 0.6,  # m
        "force_mag": 10.0,  # N,
        "tau": 0.02,  # s
        "goal_params": {
            "failure_position": (-2.4, 2.4),
            "failure_position_velo": (-np.inf, np.inf),
            "failure_angle": (-12 * 2 * np.pi / 360, 12 * 2 * np.pi / 360),
            "failure_angle_velo": (-np.inf, np.inf),
        },
    }
)


class ExperimentConfiguration(Configuration):
    agent: ExperimentAgentConfiguration  # type: ignore[misc]


class ExperimentAgentConfiguration(AgentConfiguration, total=False):
    port: str
    baudrate: int


DefaultExperimentConfiguration: ExperimentConfiguration = {
    "agent": {
        "port": DEFAULT_PORT,
        "baudrate": DEFAULT_BAUDRATE,
    }
}

CartpoleMLExperimentConfiguration = DefaultExperimentConfiguration.copy()

ff55c1e655743772e791d5d5bde127015de29d70
<mask token>


class AgentConfiguration(TypedDict, total=(False)):
    name: str
    goal_params: GoalParams
    agent: Type[CartpoleAgent]
    goal: Type[AgentGoalMixinBase]
    state_spec: Type[AgentStateSpecificationBase]


class SimulatedConfiguration(Configuration):
    agent: SimulatedAgentConfiguration


class SimulatedAgentConfiguration(AgentConfiguration, total=(False)):
    integration_resolution: int
    max_steps: int
    start_pos: float
    start_pos_velo: float
    start_angle: float
    start_angle_velo: float
    grav_acc: float
    mass_cart: float
    mass_pole: float
    friction_cart: float
    friction_pole: float
    pole_length: float
    force_mag: float
    tau: float


<mask token>


class ExperimentConfiguration(Configuration):
    agent: ExperimentAgentConfiguration


class ExperimentAgentConfiguration(AgentConfiguration, total=(False)):
    port: str
    baudrate: int


<mask token>

<mask token>


class Configuration(TypedDict, total=(False)):
    agent: AgentConfiguration


class AgentConfiguration(TypedDict, total=(False)):
    name: str
    goal_params: GoalParams
    agent: Type[CartpoleAgent]
    goal: Type[AgentGoalMixinBase]
    state_spec: Type[AgentStateSpecificationBase]


class SimulatedConfiguration(Configuration):
    agent: SimulatedAgentConfiguration


class SimulatedAgentConfiguration(AgentConfiguration, total=(False)):
    integration_resolution: int
    max_steps: int
    start_pos: float
    start_pos_velo: float
    start_angle: float
    start_angle_velo: float
    grav_acc: float
    mass_cart: float
    mass_pole: float
    friction_cart: float
    friction_pole: float
    pole_length: float
    force_mag: float
    tau: float


DefaultSimulatedConfiguration: SimulatedConfiguration = {'agent': {
    'integration_resolution': 2, 'max_steps': 5000}}
<mask token>
DeepPILCOConfiguration['agent'].update({'start_pos': 0.0, 'start_pos_velo':
    0.0, 'start_angle': 0.0, 'start_angle_velo': 0.0, 'grav_acc': 9.82,
    'mass_cart': 0.5, 'mass_pole': 0.5, 'friction_cart': 0.1,
    'friction_pole': 0.0, 'pole_length': 0.6, 'force_mag': 10.0, 'tau': 
    0.02, 'goal_params': {'failure_position': (-2.4, 2.4),
    'failure_position_velo': (-np.inf, np.inf), 'failure_angle': (-12 * 2 *
    np.pi / 360, 12 * 2 * np.pi / 360), 'failure_angle_velo': (-np.inf, np.
    inf)}})


class ExperimentConfiguration(Configuration):
    agent: ExperimentAgentConfiguration


class ExperimentAgentConfiguration(AgentConfiguration, total=(False)):
    port: str
    baudrate: int


DefaultExperimentConfiguration: ExperimentConfiguration = {'agent': {'port':
    DEFAULT_PORT, 'baudrate': DEFAULT_BAUDRATE}}
<mask token>

<mask token>


class Configuration(TypedDict, total=(False)):
    agent: AgentConfiguration


class AgentConfiguration(TypedDict, total=(False)):
    name: str
    goal_params: GoalParams
    agent: Type[CartpoleAgent]
    goal: Type[AgentGoalMixinBase]
    state_spec: Type[AgentStateSpecificationBase]


class SimulatedConfiguration(Configuration):
    agent: SimulatedAgentConfiguration


class SimulatedAgentConfiguration(AgentConfiguration, total=(False)):
    integration_resolution: int
    max_steps: int
    start_pos: float
    start_pos_velo: float
    start_angle: float
    start_angle_velo: float
    grav_acc: float
    mass_cart: float
    mass_pole: float
    friction_cart: float
    friction_pole: float
    pole_length: float
    force_mag: float
    tau: float


DefaultSimulatedConfiguration: SimulatedConfiguration = {'agent': {
    'integration_resolution': 2, 'max_steps': 5000}}
DeepPILCOConfiguration = DefaultSimulatedConfiguration.copy()
DeepPILCOConfiguration['agent'].update({'start_pos': 0.0, 'start_pos_velo':
    0.0, 'start_angle': 0.0, 'start_angle_velo': 0.0, 'grav_acc': 9.82,
    'mass_cart': 0.5, 'mass_pole': 0.5, 'friction_cart': 0.1,
    'friction_pole': 0.0, 'pole_length': 0.6, 'force_mag': 10.0, 'tau': 
    0.02, 'goal_params': {'failure_position': (-2.4, 2.4),
    'failure_position_velo': (-np.inf, np.inf), 'failure_angle': (-12 * 2 *
    np.pi / 360, 12 * 2 * np.pi / 360), 'failure_angle_velo': (-np.inf, np.
    inf)}})


class ExperimentConfiguration(Configuration):
    agent: ExperimentAgentConfiguration


class ExperimentAgentConfiguration(AgentConfiguration, total=(False)):
    port: str
    baudrate: int


DefaultExperimentConfiguration: ExperimentConfiguration = {'agent': {'port':
    DEFAULT_PORT, 'baudrate': DEFAULT_BAUDRATE}}
CartpoleMLExperimentConfiguration = DefaultExperimentConfiguration.copy()

<mask token>
from __future__ import annotations
from typing import Type, TypedDict
import numpy as np
from commander.ml.agent.agent import CartpoleAgent
from commander.ml.agent.goal import AgentGoalMixinBase
from commander.ml.agent.state_specification import AgentStateSpecificationBase
from commander.ml.agent.type_aliases import GoalParams
from commander.network.constants import DEFAULT_BAUDRATE, DEFAULT_PORT


class Configuration(TypedDict, total=(False)):
    agent: AgentConfiguration


class AgentConfiguration(TypedDict, total=(False)):
    name: str
    goal_params: GoalParams
    agent: Type[CartpoleAgent]
    goal: Type[AgentGoalMixinBase]
    state_spec: Type[AgentStateSpecificationBase]


class SimulatedConfiguration(Configuration):
    agent: SimulatedAgentConfiguration


class SimulatedAgentConfiguration(AgentConfiguration, total=(False)):
    integration_resolution: int
    max_steps: int
    start_pos: float
    start_pos_velo: float
    start_angle: float
    start_angle_velo: float
    grav_acc: float
    mass_cart: float
    mass_pole: float
    friction_cart: float
    friction_pole: float
    pole_length: float
    force_mag: float
    tau: float


DefaultSimulatedConfiguration: SimulatedConfiguration = {'agent': {
    'integration_resolution': 2, 'max_steps': 5000}}
DeepPILCOConfiguration = DefaultSimulatedConfiguration.copy()
DeepPILCOConfiguration['agent'].update({'start_pos': 0.0, 'start_pos_velo':
    0.0, 'start_angle': 0.0, 'start_angle_velo': 0.0, 'grav_acc': 9.82,
    'mass_cart': 0.5, 'mass_pole': 0.5, 'friction_cart': 0.1,
    'friction_pole': 0.0, 'pole_length': 0.6, 'force_mag': 10.0, 'tau': 
    0.02, 'goal_params': {'failure_position': (-2.4, 2.4),
    'failure_position_velo': (-np.inf, np.inf), 'failure_angle': (-12 * 2 *
    np.pi / 360, 12 * 2 * np.pi / 360), 'failure_angle_velo': (-np.inf, np.
    inf)}})


class ExperimentConfiguration(Configuration):
    agent: ExperimentAgentConfiguration


class ExperimentAgentConfiguration(AgentConfiguration, total=(False)):
    port: str
    baudrate: int


DefaultExperimentConfiguration: ExperimentConfiguration = {'agent': {'port':
    DEFAULT_PORT, 'baudrate': DEFAULT_BAUDRATE}}
CartpoleMLExperimentConfiguration = DefaultExperimentConfiguration.copy()

"""
This module hosts common configurations for the Cartpole problem as
described in some of the popular papers around the problem.
"""
from __future__ import annotations

from typing import Type, TypedDict

import numpy as np

from commander.ml.agent.agent import CartpoleAgent
from commander.ml.agent.goal import AgentGoalMixinBase
from commander.ml.agent.state_specification import AgentStateSpecificationBase
from commander.ml.agent.type_aliases import GoalParams
from commander.network.constants import DEFAULT_BAUDRATE, DEFAULT_PORT


class Configuration(TypedDict, total=False):
    agent: AgentConfiguration


class AgentConfiguration(TypedDict, total=False):
    name: str
    goal_params: GoalParams

    agent: Type[CartpoleAgent]
    goal: Type[AgentGoalMixinBase]
    state_spec: Type[AgentStateSpecificationBase]


class SimulatedConfiguration(Configuration):
    agent: SimulatedAgentConfiguration  # type: ignore[misc]


class SimulatedAgentConfiguration(AgentConfiguration, total=False):
    integration_resolution: int
    max_steps: int
    start_pos: float
    start_pos_velo: float
    start_angle: float
    start_angle_velo: float
    grav_acc: float
    mass_cart: float
    mass_pole: float
    friction_cart: float
    friction_pole: float
    pole_length: float
    force_mag: float
    tau: float


DefaultSimulatedConfiguration: SimulatedConfiguration = {
    "agent": {
        "integration_resolution": 2,
        "max_steps": 5000,
    }
}

# DeepPILCO
# See: http://mlg.eng.cam.ac.uk/yarin/PDFs/DeepPILCO.pdf
# See: https://github.com/zuoxingdong/DeepPILCO/blob/master/cartpole_swingup.py
DeepPILCOConfiguration = DefaultSimulatedConfiguration.copy()
DeepPILCOConfiguration["agent"].update(
    {
        "start_pos": 0.0,
        "start_pos_velo": 0.0,
        "start_angle": 0.0,
        "start_angle_velo": 0.0,
        "grav_acc": 9.82,  # m/s
        "mass_cart": 0.5,  # kg
        "mass_pole": 0.5,  # kg
        "friction_cart": 0.1,  # coeff
        "friction_pole": 0.0,  # coeff
        "pole_length": 0.6,  # m
        "force_mag": 10.0,  # N,
        "tau": 0.02,  # s
        "goal_params": {
            "failure_position": (-2.4, 2.4),
            "failure_position_velo": (-np.inf, np.inf),
            "failure_angle": (-12 * 2 * np.pi / 360, 12 * 2 * np.pi / 360),
            "failure_angle_velo": (-np.inf, np.inf),
        },
    }
)


class ExperimentConfiguration(Configuration):
    agent: ExperimentAgentConfiguration  # type: ignore[misc]


class ExperimentAgentConfiguration(AgentConfiguration, total=False):
    port: str
    baudrate: int


DefaultExperimentConfiguration: ExperimentConfiguration = {
    "agent": {
        "port": DEFAULT_PORT,
        "baudrate": DEFAULT_BAUDRATE,
    }
}

CartpoleMLExperimentConfiguration = DefaultExperimentConfiguration.copy()
