# Copyright 2017 The dm_control Authors.
#
# 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.
# ============================================================================

"""Planar Manipulator domain."""

import collections

from dm_control import mujoco
from dm_control.rl import control
from dm_control.suite import base
from dm_control.suite import common
from dm_control.utils import containers
from dm_control.utils import rewards
from dm_control.utils import xml_tools

from lxml import etree
import numpy as np

_CLOSE = .01    # (Meters) Distance below which a thing is considered close.
_CONTROL_TIMESTEP = .01  # (Seconds)
_TIME_LIMIT = 10  # (Seconds)
_P_IN_HAND = .1  # Probabillity of object-in-hand initial state
_P_IN_TARGET = .1  # Probabillity of object-in-target initial state
_ARM_JOINTS = ['arm_root', 'arm_shoulder', 'arm_elbow', 'arm_wrist',
               'finger', 'fingertip', 'thumb', 'thumbtip']
_ALL_PROPS = frozenset(['ball', 'target_ball', 'cup',
                        'peg', 'target_peg', 'slot'])
_TOUCH_SENSORS = ['palm_touch', 'finger_touch', 'thumb_touch',
                  'fingertip_touch', 'thumbtip_touch']

SUITE = containers.TaggedTasks()


def make_model(use_peg, insert):
  """Returns a tuple containing the model XML string and a dict of assets."""
  xml_string = common.read_model('manipulator.xml')
  parser = etree.XMLParser(remove_blank_text=True)
  mjcf = etree.XML(xml_string, parser)

  # Select the desired prop.
  if use_peg:
    required_props = ['peg', 'target_peg']
    if insert:
      required_props += ['slot']
  else:
    required_props = ['ball', 'target_ball']
    if insert:
      required_props += ['cup']

  # Remove unused props
  for unused_prop in _ALL_PROPS.difference(required_props):
    prop = xml_tools.find_element(mjcf, 'body', unused_prop)
    prop.getparent().remove(prop)

  return etree.tostring(mjcf, pretty_print=True), common.ASSETS


@SUITE.add('benchmarking', 'hard')
def bring_ball(fully_observable=True, time_limit=_TIME_LIMIT, random=None,
               environment_kwargs=None):
  """Returns manipulator bring task with the ball prop."""
  use_peg = False
  insert = False
  physics = Physics.from_xml_string(*make_model(use_peg, insert))
  task = Bring(use_peg=use_peg, insert=insert,
               fully_observable=fully_observable, random=random)
  environment_kwargs = environment_kwargs or {}
  return control.Environment(
      physics, task, control_timestep=_CONTROL_TIMESTEP, time_limit=time_limit,
      **environment_kwargs)


@SUITE.add('hard')
def bring_peg(fully_observable=True, time_limit=_TIME_LIMIT, random=None,
              environment_kwargs=None):
  """Returns manipulator bring task with the peg prop."""
  use_peg = True
  insert = False
  physics = Physics.from_xml_string(*make_model(use_peg, insert))
  task = Bring(use_peg=use_peg, insert=insert,
               fully_observable=fully_observable, random=random)
  environment_kwargs = environment_kwargs or {}
  return control.Environment(
      physics, task, control_timestep=_CONTROL_TIMESTEP, time_limit=time_limit,
      **environment_kwargs)


@SUITE.add('hard')
def insert_ball(fully_observable=True, time_limit=_TIME_LIMIT, random=None,
                environment_kwargs=None):
  """Returns manipulator insert task with the ball prop."""
  use_peg = False
  insert = True
  physics = Physics.from_xml_string(*make_model(use_peg, insert))
  task = Bring(use_peg=use_peg, insert=insert,
               fully_observable=fully_observable, random=random)
  environment_kwargs = environment_kwargs or {}
  return control.Environment(
      physics, task, control_timestep=_CONTROL_TIMESTEP, time_limit=time_limit,
      **environment_kwargs)


@SUITE.add('hard')
def insert_peg(fully_observable=True, time_limit=_TIME_LIMIT, random=None,
               environment_kwargs=None):
  """Returns manipulator insert task with the peg prop."""
  use_peg = True
  insert = True
  physics = Physics.from_xml_string(*make_model(use_peg, insert))
  task = Bring(use_peg=use_peg, insert=insert,
               fully_observable=fully_observable, random=random)
  environment_kwargs = environment_kwargs or {}
  return control.Environment(
      physics, task, control_timestep=_CONTROL_TIMESTEP, time_limit=time_limit,
      **environment_kwargs)


class Physics(mujoco.Physics):
  """Physics with additional features for the Planar Manipulator domain."""

  def bounded_joint_pos(self, joint_names):
    """Returns joint positions as (sin, cos) values."""
    joint_pos = self.named.data.qpos[joint_names]
    return np.vstack([np.sin(joint_pos), np.cos(joint_pos)]).T

  def joint_vel(self, joint_names):
    """Returns joint velocities."""
    return self.named.data.qvel[joint_names]

  def body_2d_pose(self, body_names, orientation=True):
    """Returns positions and/or orientations of bodies."""
    if not isinstance(body_names, str):
      body_names = np.array(body_names).reshape(-1, 1)  # Broadcast indices.
    pos = self.named.data.xpos[body_names, ['x', 'z']]
    if orientation:
      ori = self.named.data.xquat[body_names, ['qw', 'qy']]
      return np.hstack([pos, ori])
    else:
      return pos

  def touch(self):
    return np.log1p(self.named.data.sensordata[_TOUCH_SENSORS])

  def site_distance(self, site1, site2):
    site1_to_site2 = np.diff(self.named.data.site_xpos[[site2, site1]], axis=0)
    return np.linalg.norm(site1_to_site2)


class Bring(base.Task):
  """A Bring `Task`: bring the prop to the target."""

  def __init__(self, use_peg, insert, fully_observable, random=None):
    """Initialize an instance of the `Bring` task.

    Args:
      use_peg: A `bool`, whether to replace the ball prop with the peg prop.
      insert: A `bool`, whether to insert the prop in a receptacle.
      fully_observable: A `bool`, whether the observation should contain the
        position and velocity of the object being manipulated and the target
        location.
      random: Optional, either a `numpy.random.RandomState` instance, an
        integer seed for creating a new `RandomState`, or None to select a seed
        automatically (default).
    """
    self._use_peg = use_peg
    self._target = 'target_peg' if use_peg else 'target_ball'
    self._object = 'peg' if self._use_peg else 'ball'
    self._object_joints = ['_'.join([self._object, dim]) for dim in 'xzy']
    self._receptacle = 'slot' if self._use_peg else 'cup'
    self._insert = insert
    self._fully_observable = fully_observable
    super().__init__(random=random)

  def initialize_episode(self, physics):
    """Sets the state of the environment at the start of each episode."""
    # Local aliases
    choice = self.random.choice
    uniform = self.random.uniform
    model = physics.named.model
    data = physics.named.data

    # Find a collision-free random initial configuration.
    penetrating = True
    while penetrating:

      # Randomise angles of arm joints.
      is_limited = model.jnt_limited[_ARM_JOINTS].astype(bool)
      joint_range = model.jnt_range[_ARM_JOINTS]
      lower_limits = np.where(is_limited, joint_range[:, 0], -np.pi)
      upper_limits = np.where(is_limited, joint_range[:, 1], np.pi)
      angles = uniform(lower_limits, upper_limits)
      data.qpos[_ARM_JOINTS] = angles

      # Symmetrize hand.
      data.qpos['finger'] = data.qpos['thumb']

      # Randomise target location.
      target_x = uniform(-.4, .4)
      target_z = uniform(.1, .4)
      if self._insert:
        target_angle = uniform(-np.pi/3, np.pi/3)
        model.body_pos[self._receptacle, ['x', 'z']] = target_x, target_z
        model.body_quat[self._receptacle, ['qw', 'qy']] = [
            np.cos(target_angle/2), np.sin(target_angle/2)]
      else:
        target_angle = uniform(-np.pi, np.pi)

      model.body_pos[self._target, ['x', 'z']] = target_x, target_z
      model.body_quat[self._target, ['qw', 'qy']] = [
          np.cos(target_angle/2), np.sin(target_angle/2)]

      # Randomise object location.
      object_init_probs = [_P_IN_HAND, _P_IN_TARGET, 1-_P_IN_HAND-_P_IN_TARGET]
      init_type = choice(['in_hand', 'in_target', 'uniform'],
                         p=object_init_probs)
      if init_type == 'in_target':
        object_x = target_x
        object_z = target_z
        object_angle = target_angle
      elif init_type == 'in_hand':
        physics.after_reset()
        object_x = data.site_xpos['grasp', 'x']
        object_z = data.site_xpos['grasp', 'z']
        grasp_direction = data.site_xmat['grasp', ['xx', 'zx']]
        object_angle = np.pi-np.arctan2(grasp_direction[1], grasp_direction[0])
      else:
        object_x = uniform(-.5, .5)
        object_z = uniform(0, .7)
        object_angle = uniform(0, 2*np.pi)
        data.qvel[self._object + '_x'] = uniform(-5, 5)

      data.qpos[self._object_joints] = object_x, object_z, object_angle

      # Check for collisions.
      physics.after_reset()
      penetrating = physics.data.ncon > 0

    super().initialize_episode(physics)

  def get_observation(self, physics):
    """Returns either features or only sensors (to be used with pixels)."""
    obs = collections.OrderedDict()
    obs['arm_pos'] = physics.bounded_joint_pos(_ARM_JOINTS)
    obs['arm_vel'] = physics.joint_vel(_ARM_JOINTS)
    obs['touch'] = physics.touch()
    if self._fully_observable:
      obs['hand_pos'] = physics.body_2d_pose('hand')
      obs['object_pos'] = physics.body_2d_pose(self._object)
      obs['object_vel'] = physics.joint_vel(self._object_joints)
      obs['target_pos'] = physics.body_2d_pose(self._target)
    return obs

  def _is_close(self, distance):
    return rewards.tolerance(distance, (0, _CLOSE), _CLOSE*2)

  def _peg_reward(self, physics):
    """Returns a reward for bringing the peg prop to the target."""
    grasp = self._is_close(physics.site_distance('peg_grasp', 'grasp'))
    pinch = self._is_close(physics.site_distance('peg_pinch', 'pinch'))
    grasping = (grasp + pinch) / 2
    bring = self._is_close(physics.site_distance('peg', 'target_peg'))
    bring_tip = self._is_close(physics.site_distance('target_peg_tip',
                                                     'peg_tip'))
    bringing = (bring + bring_tip) / 2
    return max(bringing, grasping/3)

  def _ball_reward(self, physics):
    """Returns a reward for bringing the ball prop to the target."""
    return self._is_close(physics.site_distance('ball', 'target_ball'))

  def get_reward(self, physics):
    """Returns a reward to the agent."""
    if self._use_peg:
      return self._peg_reward(physics)
    else:
      return self._ball_reward(physics)
