Policy_evalution_TD(0)_assignment.ipynb

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    "# Assignment: Policy Evaluation in Cliff Walking Environment\n",
    "\n",
    "Welcome to the Course 2 Module 2 Programming Assignment! In this assignment, you will implement one of the fundamental sample and bootstrapping based model free reinforcement learning agents for prediction. This is namely one that uses one-step temporal difference learning, also known as TD(0). The task is to design an agent for policy evaluation in the Cliff Walking environment. Recall that policy evaluation is the prediction problem where the goal is to accurately estimate the values of states given some policy.\n",
    "\n",
    "### Learning Objectives\n",
    "- Implement parts of the Cliff Walking environment, to get experience specifying MDPs [Section 1].\n",
    "- Implement an agent that uses bootstrapping and, particularly, TD(0) [Section 2].\n",
    "- Apply TD(0) to estimate value functions for different policies, i.e., run policy evaluation experiments [Section 3]."
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    "## The Cliff Walking Environment\n",
    "\n",
    "The Cliff Walking environment is a gridworld with a discrete state space and discrete action space. The agent starts at grid cell S. The agent can move (deterministically) to the four neighboring cells by taking actions Up, Down, Left or Right. Trying to move out of the boundary results in staying in the same location. So, for example, trying to move left when at a cell on the leftmost column results in no movement at all and the agent remains in the same location. The agent receives -1 reward per step in most states, and -100 reward when falling off of the cliff. This is an episodic task; termination occurs when the agent reaches the goal grid cell G. Falling off of the cliff results in resetting to the start state, without termination.\n",
    "\n",
    "The diagram below showcases the description above and also illustrates two of the policies we will be evaluating.\n",
    "\n",
    "<img src=\"cliffwalk.png\" style=\"height:400px\">"
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    "## Packages.\n",
    "\n",
    "We import the following libraries that are required for this assignment. We shall be using the following libraries:\n",
    "1. jdc: Jupyter magic that allows defining classes over multiple jupyter notebook cells.\n",
    "2. numpy: the fundamental package for scientific computing with Python.\n",
    "3. matplotlib: the library for plotting graphs in Python.\n",
    "4. RL-Glue: the library for reinforcement learning experiments.\n",
    "5. BaseEnvironment, BaseAgent: the base classes from which we will inherit when creating the environment and agent classes in order for them to support the RL-Glue framework.\n",
    "6. Manager: the file allowing for visualization and testing.\n",
    "7. itertools.product: the function that can be used easily to compute permutations.\n",
    "8. tqdm.tqdm: Provides progress bars for visualizing the status of loops.\n",
    "\n",
    "**Please do not import other libraries** this will break the autograder.\n",
    "\n",
    "**NOTE: For this notebook, there is no need to make any calls to methods of random number generators. Spurious or missing calls to random number generators may affect your results.**"
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    "# Do not modify this cell!\n",
    "\n",
    "import jdc\n",
    "import numpy as np\n",
    "from rl_glue import RLGlue\n",
    "from Agent import BaseAgent \n",
    "from Environment import BaseEnvironment  \n",
    "from manager import Manager\n",
    "from itertools import product\n",
    "from tqdm import tqdm"
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    "## Section 1. Environment\n",
    "\n",
    "In the first part of this assignment, you will get to see how the Cliff Walking environment is implemented. You will also get to implement parts of it to aid your understanding of the environment and more generally how MDPs are specified. In particular, you will implement the logic for:\n",
    " 1. Converting 2-dimensional coordinates to a single index for the state,\n",
    " 2. One of the actions (action up), and,\n",
    " 3. Reward and termination.\n",
    " \n",
    "Given below is an annotated diagram of the environment with more details that may help in completing the tasks of this part of the assignment. Note that we will be creating a more general environment where the height and width positions can be variable but the start, goal and cliff grid cells have the same relative positions (bottom left, bottom right and the cells between the start and goal grid cells respectively).\n",
    "\n",
    "<img src=\"cliffwalk-annotated.png\" style=\"height:400px\">\n",
    "\n",
    "Once you have gone through the code and begun implementing solutions, it may be a good idea to come back here and see if you can convince yourself that the diagram above is an accurate representation of the code given and the code you have written."
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    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "# Create empty CliffWalkEnvironment class.\n",
    "# These methods will be filled in later cells.\n",
    "class CliffWalkEnvironment(BaseEnvironment):\n",
    "    def env_init(self, env_info={}):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def env_start(self):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def env_step(self, action):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def env_cleanup(self):\n",
    "        raise NotImplementedError\n",
    "    \n",
    "    # helper method\n",
    "    def state(self, loc):\n",
    "        raise NotImplementedError"
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    "## env_init()\n",
    "\n",
    "The first function we add to the environment is the initialization function which is called once when an environment object is created. In this function, the grid dimensions and special locations (start and goal locations and the cliff locations) are stored for easy use later."
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    "%%add_to CliffWalkEnvironment\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def env_init(self, env_info={}):\n",
    "        \"\"\"Setup for the environment called when the experiment first starts.\n",
    "        Note:\n",
    "            Initialize a tuple with the reward, first state, boolean\n",
    "            indicating if it's terminal.\n",
    "        \"\"\"\n",
    "        \n",
    "        # Note, we can setup the following variables later, in env_start() as it is equivalent. \n",
    "        # Code is left here to adhere to the note above, but these variables are initialized once more\n",
    "        # in env_start() [See the env_start() function below.]\n",
    "        \n",
    "        reward = None\n",
    "        state = None # See Aside\n",
    "        termination = None\n",
    "        self.reward_state_term = (reward, state, termination)\n",
    "        \n",
    "        # AN ASIDE: Observation is a general term used in the RL-Glue files that can be interachangeably \n",
    "        # used with the term \"state\" for our purposes and for this assignment in particular. \n",
    "        # A difference arises in the use of the terms when we have what is called Partial Observability where \n",
    "        # the environment may return states that may not fully represent all the information needed to \n",
    "        # predict values or make decisions (i.e., the environment is non-Markovian.)\n",
    "        \n",
    "        # Set the default height to 4 and width to 12 (as in the diagram given above)\n",
    "        self.grid_h = env_info.get(\"grid_height\", 4) \n",
    "        self.grid_w = env_info.get(\"grid_width\", 12)\n",
    "        \n",
    "        # Now, we can define a frame of reference. Let positive x be towards the direction down and \n",
    "        # positive y be towards the direction right (following the row-major NumPy convention.)\n",
    "        # Then, keeping with the usual convention that arrays are 0-indexed, max x is then grid_h - 1 \n",
    "        # and max y is then grid_w - 1. So, we have:\n",
    "        # Starting location of agent is the bottom-left corner, (max x, min y). \n",
    "        self.start_loc = (self.grid_h - 1, 0)\n",
    "        # Goal location is the bottom-right corner. (max x, max y).\n",
    "        self.goal_loc = (self.grid_h - 1, self.grid_w - 1)\n",
    "        \n",
    "        # The cliff will contain all the cells between the start_loc and goal_loc.\n",
    "        self.cliff = [(self.grid_h - 1, i) for i in range(1, (self.grid_w - 1))]\n",
    "        \n",
    "        # Take a look at the annotated environment diagram given in the above Jupyter Notebook cell to \n",
    "        # verify that your understanding of the above code is correct for the default case, i.e., where \n",
    "        # height = 4 and width = 12."
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    "## *Implement* state()\n",
    "    \n",
    "The agent location can be described as a two-tuple or coordinate (x, y) describing the agentâ€™s position. \n",
    "However, we can convert the (x, y) tuple into a single index and provide agents with just this integer.\n",
    "One reason for this choice is that the spatial aspect of the problem is secondary and there is no need \n",
    "for the agent to know about the exact dimensions of the environment. \n",
    "From the agentâ€™s viewpoint, it is just perceiving some states, accessing their corresponding values \n",
    "in a table, and updating them. Both the coordinate (x, y) state representation and the converted coordinate representation are thus equivalent in this sense.\n",
    "\n",
    "Given a grid cell location, the state() function should return the state; a single index corresponding to the location in the grid.\n",
    "\n",
    "\n",
    "```\n",
    "Example: Suppose grid_h is 2 and grid_w is 2. Then, we can write the grid cell two-tuple or coordinate\n",
    "states as follows (following the usual 0-index convention):\n",
    "|(0, 0) (0, 1)| |0 1|\n",
    "|(1, 0) (1, 1)| |2 3|\n",
    "Assuming row-major order as NumPy does,  we can flatten the latter to get a vector [0 1 2 3].\n",
    "So, if loc = (0, 0) we return 0. While, for loc = (1, 1) we return 3.\n",
    "```"
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    "%%add_to CliffWalkEnvironment\n",
    "\n",
    "# -----------\n",
    "# Graded Cell\n",
    "# -----------\n",
    "\n",
    "# Modify the return statement of this function to return a correct single index as \n",
    "# the state (see the logic for this in the previous cell.)\n",
    "def state(self, loc):\n",
    "    # your code here\n",
    "    return self.grid_w * loc[0] + loc[1]\n",
    "    "
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    "# --------------\n",
    "# Debugging Cell\n",
    "# --------------\n",
    "# Feel free to make any changes to this cell to debug your code\n",
    "\n",
    "env = CliffWalkEnvironment()\n",
    "env.env_init({ \"grid_height\": 4, \"grid_width\": 12 })\n",
    "\n",
    "coords = [(0, 0), (0, 11), (1, 5), (3, 0), (3, 9), (3, 11)]\n",
    "correct_outputs = [0, 11, 17, 36, 45, 47]\n",
    "\n",
    "got = [env.state(s) for s in coords]\n",
    "assert got == correct_outputs"
   ]
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    "# -----------\n",
    "# Tested Cell\n",
    "# -----------\n",
    "# The contents of the cell will be tested by the autograder.\n",
    "# If they do not pass here, they will not pass there.\n",
    "\n",
    "np.random.seed(0)\n",
    "\n",
    "env = CliffWalkEnvironment()\n",
    "for n in range(100):\n",
    "    # make a gridworld of random size and shape\n",
    "    height = np.random.randint(2, 100)\n",
    "    width = np.random.randint(2, 100)\n",
    "    env.env_init({ \"grid_height\": height, \"grid_width\": width })\n",
    "    \n",
    "    # generate some random coordinates within the grid\n",
    "    idx_h = np.random.randint(height)\n",
    "    idx_w = np.random.randint(width)\n",
    "    \n",
    "    # check that the state index is correct\n",
    "    state = env.state((idx_h, idx_w))\n",
    "    correct_state = width * idx_h + idx_w\n",
    "    \n",
    "    assert state == correct_state"
   ]
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    "## env_start()\n",
    "\n",
    "In env_start(), we initialize the agent location to be the start location and return the state corresponding to it as the first state for the agent to act upon. Additionally, we also set the reward and termination terms to be 0 and False respectively as they are consistent with the notion that there is no reward nor termination before the first action is even taken."
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    "%%add_to CliffWalkEnvironment\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def env_start(self):\n",
    "    \"\"\"The first method called when the episode starts, called before the\n",
    "    agent starts.\n",
    "\n",
    "    Returns:\n",
    "        The first state from the environment.\n",
    "    \"\"\"\n",
    "    reward = 0\n",
    "    # agent_loc will hold the current location of the agent\n",
    "    self.agent_loc = self.start_loc\n",
    "    # state is the one dimensional state representation of the agent location.\n",
    "    state = self.state(self.agent_loc)\n",
    "    termination = False\n",
    "    self.reward_state_term = (reward, state, termination)\n",
    "\n",
    "    return self.reward_state_term[1]"
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    "## *Implement* env_step()\n",
    "\n",
    "Once an action is taken by the agent, the environment must provide a new state, reward and termination signal. \n",
    "\n",
    "In the Cliff Walking environment, agents move around using a 4-cell neighborhood called the Von Neumann neighborhood (https://en.wikipedia.org/wiki/Von_Neumann_neighborhood). Thus, the agent has 4 available actions at each state. Three of the actions have been implemented for you and your first task is to implement the logic for the fourth action (Action UP).\n",
    "\n",
    "Your second task for this function is to implement the reward logic. Look over the environment description given earlier in this notebook if you need a refresher for how the reward signal is defined."
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    "%%add_to CliffWalkEnvironment\n",
    "\n",
    "# -----------\n",
    "# Graded Cell\n",
    "# -----------\n",
    "\n",
    "def isInBounds(x, y, width, height):\n",
    "    # your code here\n",
    "    bounds_list = [x, y]\n",
    "    \n",
    "    if x >= height:\n",
    "        x = height - 1\n",
    "    elif x < 0:\n",
    "        x = 0\n",
    "    elif y >= width:\n",
    "        y = width - 1\n",
    "    elif y < 0:\n",
    "        y = 0\n",
    "    \n",
    "    if bounds_list[0] == x and bounds_list[1] == y:\n",
    "        return True\n",
    "    else:\n",
    "        return False\n",
    "    \n",
    "    \n",
    "\n",
    "# Fill in the code for action UP and implement the logic for reward and termination.\n",
    "def env_step(self, action):\n",
    "    \"\"\"A step taken by the environment.\n",
    "\n",
    "    Args:\n",
    "        action: The action taken by the agent\n",
    "\n",
    "    Returns:\n",
    "        (float, state, Boolean): a tuple of the reward, state,\n",
    "            and boolean indicating if it's terminal.\n",
    "    \"\"\"\n",
    "    \n",
    "    x, y = self.agent_loc\n",
    "\n",
    "    # UP\n",
    "    if action == 0:\n",
    "        # Hint: Look at the code given for the other actions and think about the logic in them.\n",
    "        # your code here\n",
    "        x = x-1\n",
    "       \n",
    "        \n",
    "    # LEFT\n",
    "    elif action == 1:\n",
    "        y = y - 1\n",
    "        \n",
    "    # DOWN\n",
    "    elif action == 2:\n",
    "        x = x + 1\n",
    "        \n",
    "    # RIGHT\n",
    "    elif action == 3:\n",
    "        y = y + 1\n",
    "        \n",
    "    # Uh-oh\n",
    "    else: \n",
    "        raise Exception(str(action) + \" not in recognized actions [0: Up, 1: Left, 2: Down, 3: Right]!\")\n",
    "\n",
    "    # if the action takes the agent out-of-bounds\n",
    "    # then the agent stays in the same state\n",
    "    if not isInBounds(x, y, self.grid_w, self.grid_h):\n",
    "        x, y = self.agent_loc\n",
    "        \n",
    "    # assign the new location to the environment object\n",
    "    self.agent_loc = (x, y)\n",
    "    \n",
    "    # by default, assume -1 reward per step and that we did not terminate\n",
    "    reward = -1\n",
    "    terminal = False\n",
    "    \n",
    "    # assign the reward and terminal variables \n",
    "    # - if the agent falls off the cliff (don't forget to reset agent location!)\n",
    "    # - if the agent reaches the goal state\n",
    "    # your code here\n",
    "    \n",
    "    if self.agent_loc in self.cliff:\n",
    "        reward = -100 \n",
    "        self.agent_loc = self.start_loc\n",
    "    \n",
    "    if self.agent_loc == (self.grid_h -1, self.grid_w -1):\n",
    "        reward = -1\n",
    "        terminal = True\n",
    "    \n",
    "    self.reward_state_term = (reward, self.state(self.agent_loc), terminal)\n",
    "    return self.reward_state_term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --------------\n",
    "# Debugging Cell\n",
    "# --------------\n",
    "# Feel free to make any changes to this cell to debug your code\n",
    "\n",
    "def test_action_up():\n",
    "    env = CliffWalkEnvironment()\n",
    "    env.env_init({\"grid_height\": 4, \"grid_width\": 12})\n",
    "    env.agent_loc = (0, 0)\n",
    "    env.env_step(0)\n",
    "    assert(env.agent_loc == (0, 0))\n",
    "    \n",
    "    env.agent_loc = (1, 0)\n",
    "    env.env_step(0)\n",
    "    assert(env.agent_loc == (0, 0))\n",
    "    \n",
    "def test_reward():\n",
    "    env = CliffWalkEnvironment()\n",
    "    env.env_init({\"grid_height\": 4, \"grid_width\": 12})\n",
    "    env.agent_loc = (0, 0)\n",
    "    reward_state_term = env.env_step(0)\n",
    "    assert(reward_state_term[0] == -1 and reward_state_term[1] == env.state((0, 0)) and\n",
    "           reward_state_term[2] == False)\n",
    "    \n",
    "    env.agent_loc = (3, 1)\n",
    "    reward_state_term = env.env_step(2)\n",
    "    assert(reward_state_term[0] == -100 and reward_state_term[1] == env.state((3, 0)) and\n",
    "           reward_state_term[2] == False)\n",
    "    \n",
    "    env.agent_loc = (2, 11)\n",
    "    reward_state_term = env.env_step(2)\n",
    "    assert(reward_state_term[0] == -1 and reward_state_term[1] == env.state((3, 11)) and\n",
    "           reward_state_term[2] == True)\n",
    "    \n",
    "test_action_up()\n",
    "test_reward()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "930e2f004e7f5bc157d4ade45c186185",
     "grade": true,
     "grade_id": "cell-cc53e967d108b33c",
     "locked": true,
     "points": 5,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "# -----------\n",
    "# Tested Cell\n",
    "# -----------\n",
    "# The contents of the cell will be tested by the autograder.\n",
    "# If they do not pass here, they will not pass there.\n",
    "np.random.seed(0)\n",
    "\n",
    "env = CliffWalkEnvironment()\n",
    "for n in range(100):\n",
    "    # create a cliff world of random size\n",
    "    height = np.random.randint(2, 100)\n",
    "    width = np.random.randint(2, 100)\n",
    "    env.env_init({\"grid_height\": height, \"grid_width\": width})\n",
    "    \n",
    "    # start the agent in a random location\n",
    "    idx_h = 0 if np.random.random() < 0.5 else np.random.randint(height)\n",
    "    idx_w = np.random.randint(width)\n",
    "    env.agent_loc = (idx_h, idx_w)\n",
    "    \n",
    "    env.env_step(0)\n",
    "    assert(env.agent_loc == (0 if idx_h == 0 else idx_h - 1, idx_w))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "085778d845e6e8259013f384c9c71fc7",
     "grade": true,
     "grade_id": "cell-a883fea60cb72354",
     "locked": true,
     "points": 10,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "# -----------\n",
    "# Tested Cell\n",
    "# -----------\n",
    "# The contents of the cell will be tested by the autograder.\n",
    "# If they do not pass here, they will not pass there.\n",
    "np.random.seed(0)\n",
    "\n",
    "env = CliffWalkEnvironment()\n",
    "for n in range(100):\n",
    "    # create a cliff world of random size\n",
    "    height = np.random.randint(4, 10)\n",
    "    width = np.random.randint(4, 10)\n",
    "    env.env_init({\"grid_height\": height, \"grid_width\": width})\n",
    "    env.env_start()\n",
    "    \n",
    "    # start the agent near the cliff\n",
    "    idx_h = height - 2\n",
    "    idx_w = np.random.randint(1, width - 2)\n",
    "    env.agent_loc = (idx_h, idx_w)\n",
    "    \n",
    "    r, sp, term = env.env_step(2)\n",
    "    assert(r == -100 and sp == (height - 1) * width and term == False)\n",
    "\n",
    "for n in range(100):\n",
    "    # create a cliff world of random size\n",
    "    height = np.random.randint(4, 10)\n",
    "    width = np.random.randint(4, 10)\n",
    "    env.env_init({\"grid_height\": height, \"grid_width\": width})\n",
    "    env.env_start()\n",
    "    \n",
    "    # start the agent near the goal\n",
    "    idx_h = height - 2\n",
    "    idx_w = width - 1\n",
    "    env.agent_loc = (idx_h, idx_w)\n",
    "    \n",
    "    r, sp, term = env.env_step(2)\n",
    "    assert(r == -1 and sp == (height - 1) * width + (width - 1) and term == True)\n",
    "\n",
    "for n in range(100):\n",
    "    # create a cliff world of random size\n",
    "    height = np.random.randint(4, 10)\n",
    "    width = np.random.randint(4, 10)\n",
    "    env.env_init({\"grid_height\": height, \"grid_width\": width})\n",
    "    env.env_start()\n",
    "    \n",
    "    # start the agent in a random location\n",
    "    idx_h = np.random.randint(0, height - 3)\n",
    "    idx_w = np.random.randint(0, width - 1)\n",
    "    env.agent_loc = (idx_h, idx_w)\n",
    "    \n",
    "    r, sp, term = env.env_step(2)\n",
    "    assert(r == -1 and term == False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "75a723b12d51aa479c9820a827f78105",
     "grade": false,
     "grade_id": "cell-097d028e4c6b9ff2",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## env_cleanup()\n",
    "\n",
    "There is not much cleanup to do for the Cliff Walking environment. Here, we simply reset the agent location to be the start location in this function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "2239673e0e1e0ce4adb6f2d4a6a703e3",
     "grade": false,
     "grade_id": "cell-d5ff562d7edc277d",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%%add_to CliffWalkEnvironment\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def env_cleanup(self):\n",
    "    \"\"\"Cleanup done after the environment ends\"\"\"\n",
    "    self.agent_loc = self.start_loc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "3143490bb273c21183bb0c2397ed4b53",
     "grade": false,
     "grade_id": "cell-fc714f9c0311d966",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## Section 2. Agent\n",
    "\n",
    "In this second part of the assignment, you will be implementing the key updates for Temporal Difference Learning. There are two cases to consider depending on whether an action leads to a terminal state or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "2ecf4ec36550b6e56088c40cb4c6cf63",
     "grade": false,
     "grade_id": "cell-8dcd58cfaa9b1391",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "# Create empty TDAgent class.\n",
    "# These methods will be filled in later cells.\n",
    "\n",
    "class TDAgent(BaseAgent):\n",
    "    def agent_init(self, agent_info={}):\n",
    "        raise NotImplementedError\n",
    "        \n",
    "    def agent_start(self, state):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def agent_step(self, reward, state):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def agent_end(self, reward):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def agent_cleanup(self):        \n",
    "        raise NotImplementedError\n",
    "        \n",
    "    def agent_message(self, message):\n",
    "        raise NotImplementedError"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "6ad6054dcb773c2b268b93cb01194d61",
     "grade": false,
     "grade_id": "cell-fb86d23d3049ba9a",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## agent_init()\n",
    "\n",
    "As we did with the environment, we first initialize the agent once when a TDAgent object is created. In this function, we create a random number generator, seeded with the seed provided in the agent_info dictionary to get reproducible results. We also set the policy, discount and step size based on the agent_info dictionary. Finally, with a convention that the policy is always specified as a mapping from states to actions and so is an array of size (# States, # Actions), we initialize a values array of shape (# States,) to zeros."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "7b2bd8f7421b260e24fb2ffea9831ee3",
     "grade": false,
     "grade_id": "cell-7e6fb425c17b2222",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%%add_to TDAgent\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def agent_init(self, agent_info={}):\n",
    "    \"\"\"Setup for the agent called when the experiment first starts.\"\"\"\n",
    "\n",
    "    # Create a random number generator with the provided seed to seed the agent for reproducibility.\n",
    "    self.rand_generator = np.random.RandomState(agent_info.get(\"seed\"))\n",
    "\n",
    "    # Policy will be given, recall that the goal is to accurately estimate its corresponding value function. \n",
    "    self.policy = agent_info.get(\"policy\")\n",
    "    # Discount factor (gamma) to use in the updates.\n",
    "    self.discount = agent_info.get(\"discount\")\n",
    "    # The learning rate or step size parameter (alpha) to use in updates.\n",
    "    self.step_size = agent_info.get(\"step_size\")\n",
    "\n",
    "    # Initialize an array of zeros that will hold the values.\n",
    "    # Recall that the policy can be represented as a (# States, # Actions) array. With the \n",
    "    # assumption that this is the case, we can use the first dimension of the policy to\n",
    "    # initialize the array for values.\n",
    "    self.values = np.zeros((self.policy.shape[0],))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "10f2140cd14944a73134fd6b27355332",
     "grade": false,
     "grade_id": "cell-6d3d7cea2ae55708",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "# agent_start()\n",
    "\n",
    "In agent_start(), we choose an action based on the initial state and policy we are evaluating. We also cache the state so that we can later update its value when we perform a Temporal Difference update. Finally, we return the action chosen so that the RL loop can continue and the environment can execute this action."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "6f2f7c78f1156b50a122f009d908a1f3",
     "grade": false,
     "grade_id": "cell-b7179e38fe75348d",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%%add_to TDAgent\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def agent_start(self, state):\n",
    "    \"\"\"The first method called when the episode starts, called after\n",
    "    the environment starts.\n",
    "    Args:\n",
    "        state (Numpy array): the state from the environment's env_start function.\n",
    "    Returns:\n",
    "        The first action the agent takes.\n",
    "    \"\"\"\n",
    "    # The policy can be represented as a (# States, # Actions) array. So, we can use \n",
    "    # the second dimension here when choosing an action.\n",
    "    action = self.rand_generator.choice(range(self.policy.shape[1]), p=self.policy[state])\n",
    "    self.last_state = state\n",
    "    return action"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "0a30618c839091f6b549cbdecdf64542",
     "grade": false,
     "grade_id": "cell-70200563dea310fa",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## *Implement* agent_step()\n",
    "\n",
    "In agent_step(), the agent must:\n",
    "\n",
    "- Perform an update to improve the value estimate of the previously visited state, and\n",
    "- Act based on the state provided by the environment.\n",
    "\n",
    "The latter of the two steps above has been implemented for you. Implement the former. Note that, unlike later in agent_end(), the episode has not yet ended in agent_step(). in other words, the previously observed state was not a terminal state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "bc6bb81efeca49f2fbbe857b53c911c1",
     "grade": false,
     "grade_id": "cell-54079abb73dd10b4",
     "locked": false,
     "schema_version": 3,
     "solution": true,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%%add_to TDAgent\n",
    "\n",
    "# -----------\n",
    "# Graded Cell\n",
    "# -----------\n",
    "\n",
    "def agent_step(self, reward, state):\n",
    "    \"\"\"A step taken by the agent.\n",
    "    Args:\n",
    "        reward (float): the reward received for taking the last action taken\n",
    "        state (Numpy array): the state from the\n",
    "            environment's step after the last action, i.e., where the agent ended up after the\n",
    "            last action\n",
    "    Returns:\n",
    "        The action the agent is taking.\n",
    "    \"\"\"\n",
    "    \n",
    "    # Hint: We should perform an update with the last state given that we now have the reward and\n",
    "    # next state. We break this into two steps. Recall for example that the Monte-Carlo update \n",
    "    # had the form: V[S_t] = V[S_t] + alpha * (target - V[S_t]), where the target was the return, G_t.\n",
    "    \n",
    "    self.values[self.last_state] = self.values[self.last_state] + self.step_size * (reward + self.discount * self.values[state]- self.values[self.last_state])\n",
    "    \n",
    "\n",
    "    # Having updated the value for the last state, we now act based on the current \n",
    "    # state, and set the last state to be current one as we will next be making an \n",
    "    # update with it when agent_step is called next once the action we return from this function \n",
    "    # is executed in the environment.\n",
    "\n",
    "    action = self.rand_generator.choice(range(self.policy.shape[1]), p=self.policy[state])\n",
    "    self.last_state = state\n",
    "\n",
    "    return action"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "489573a07301536614c0c3a68d74f0b1",
     "grade": false,
     "grade_id": "cell-b66d9ed60950f928",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## *Implement* agent_end() \n",
    "\n",
    "Implement the TD update for the case where an action leads to a terminal state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "21b0563eedd718ae37cc451cfe50423a",
     "grade": false,
     "grade_id": "cell-f47463c94223a7fa",
     "locked": false,
     "schema_version": 3,
     "solution": true,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%%add_to TDAgent\n",
    "\n",
    "# -----------\n",
    "# Graded Cell\n",
    "# -----------\n",
    "\n",
    "def agent_end(self, reward):\n",
    "    \"\"\"Run when the agent terminates.\n",
    "    Args:\n",
    "        reward (float): the reward the agent received for entering the terminal state.\n",
    "    \"\"\"\n",
    "    \n",
    "    # Hint: Here too, we should perform an update with the last state given that we now have the \n",
    "    # reward. Note that in this case, the action led to termination. Once more, we break this into \n",
    "    # two steps, computing the target and the update itself that uses the target and the \n",
    "    # current value estimate for the state whose value we are updating.\n",
    "    \n",
    "    self.values[self.last_state] =self.values[self.last_state] + self.step_size * (reward - self.values[self.last_state])\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "0c53e1942168f1f625116dcf4445852a",
     "grade": false,
     "grade_id": "cell-29b13c18d6b94737",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## agent_cleanup()\n",
    "\n",
    "In cleanup, we simply reset the last state to be None to ensure that we are not storing any states past an episode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "5ddea78d8e68fcbc0210e88d35eb84dd",
     "grade": false,
     "grade_id": "cell-35c6057f39236706",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%%add_to TDAgent\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def agent_cleanup(self):\n",
    "    \"\"\"Cleanup done after the agent ends.\"\"\"\n",
    "    self.last_state = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "0b976f8ba3941c94436c3e56b440a600",
     "grade": false,
     "grade_id": "cell-ea675d282349503b",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## agent_message()\n",
    "\n",
    "agent_message() can generally be used to get different kinds of information about an RLGlue agent in the interaction loop of RLGlue. Here, we conditonally check for a message matching \"get_values\" and use it to retrieve the values table the agent has been updating over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "661f3a352859f22e5581f2953a6738ec",
     "grade": false,
     "grade_id": "cell-8bac91a36a2cab6f",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%%add_to TDAgent\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def agent_message(self, message):\n",
    "    \"\"\"A function used to pass information from the agent to the experiment.\n",
    "    Args:\n",
    "        message: The message passed to the agent.\n",
    "    Returns:\n",
    "        The response (or answer) to the message.\n",
    "    \"\"\"\n",
    "    if message == \"get_values\":\n",
    "        return self.values\n",
    "    else:\n",
    "        raise Exception(\"TDAgent.agent_message(): Message not understood!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --------------\n",
    "# Debugging Cell\n",
    "# --------------\n",
    "# Feel free to make any changes to this cell to debug your code\n",
    "\n",
    "# The following test checks that the TD check works for a case where the transition \n",
    "# garners reward -1 and does not lead to a terminal state. This is in a simple two state setting \n",
    "# where there is only one action. The first state's current value estimate is 0 while the second is 1.\n",
    "# Note the discount and step size if you are debugging this test.\n",
    "agent = TDAgent()\n",
    "policy_list = np.array([[1.], [1.]])\n",
    "agent.agent_init({\"policy\": np.array(policy_list), \"discount\": 0.99, \"step_size\": 0.1})\n",
    "agent.values = np.array([0., 1.])\n",
    "agent.agent_start(0)\n",
    "\n",
    "reward = -1\n",
    "next_state = 1\n",
    "agent.agent_step(reward, next_state)\n",
    "\n",
    "assert(np.isclose(agent.values[0], -0.001) and np.isclose(agent.values[1], 1.))\n",
    "\n",
    "# The following test checks that the TD check works for a case where the transition \n",
    "# garners reward -100 and lead to a terminal state. This is in a simple one state setting \n",
    "# where there is only one action. The state's current value estimate is 0.\n",
    "# Note the discount and step size if you are debugging this test.\n",
    "agent = TDAgent()\n",
    "policy_list = np.array([[1.]])\n",
    "agent.agent_init({\"policy\": np.array(policy_list), \"discount\": 0.99, \"step_size\": 0.1})\n",
    "agent.values = np.array([0.])\n",
    "agent.agent_start(0)\n",
    "\n",
    "reward = -100\n",
    "next_state = 0\n",
    "agent.agent_end(reward)\n",
    "\n",
    "assert(np.isclose(agent.values[0], -10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "6afbe1c030cc5d88088b8baf8055d3a5",
     "grade": true,
     "grade_id": "cell-63cd42d5248e7e84",
     "locked": true,
     "points": 20,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "# -----------\n",
    "# Tested Cell\n",
    "# -----------\n",
    "# The contents of the cell will be tested by the autograder.\n",
    "# If they do not pass here, they will not pass there.\n",
    "\n",
    "agent = TDAgent()\n",
    "policy_list = [np.random.dirichlet(np.ones(10), size=1).squeeze() for _ in range(100)]\n",
    "\n",
    "for n in range(100):\n",
    "    gamma = np.random.random()\n",
    "    alpha = np.random.random()\n",
    "    agent.agent_init({\"policy\": np.array(policy_list), \"discount\": gamma, \"step_size\": alpha})\n",
    "    agent.values = np.random.randn(*agent.values.shape)\n",
    "    state = np.random.randint(100)\n",
    "    agent.agent_start(state)\n",
    "    \n",
    "    for _ in range(100):\n",
    "        prev_agent_vals = agent.values.copy()\n",
    "        reward = np.random.random()\n",
    "        if np.random.random() > 0.1:\n",
    "            next_state = np.random.randint(100)\n",
    "            agent.agent_step(reward, next_state)\n",
    "            prev_agent_vals[state] = prev_agent_vals[state] + alpha * (reward + gamma * prev_agent_vals[next_state] - prev_agent_vals[state])\n",
    "            assert(np.allclose(prev_agent_vals, agent.values))\n",
    "            state = next_state\n",
    "        else:\n",
    "            agent.agent_end(reward)\n",
    "            prev_agent_vals[state] = prev_agent_vals[state] + alpha * (reward - prev_agent_vals[state])\n",
    "            assert(np.allclose(prev_agent_vals, agent.values))\n",
    "            break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "e4813fc1b7e51343c87bd7ae96d6a199",
     "grade": false,
     "grade_id": "cell-957429a27572ea22",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## Section 3. Policy Evaluation Experiments\n",
    "\n",
    "Finally, in this last part of the assignment, you will get to see the TD policy evaluation algorithm in action by looking at the estimated values, the per state value error and after the experiment is complete, the Mean Squared Value Error curve vs. episode number, summarizing how the value error changed over time.\n",
    "\n",
    "The code below runs one run of an experiment given env_info and agent_info dictionaries. A \"manager\" object is created for visualizations and is used in part for the autograder. By default, the run will be for 5000 episodes. The true_values_file is specified to compare the learned value function with the values stored in the true_values_file. Plotting of the learned value  function occurs by default after every 100 episodes. In addition, when true_values_file is specified, the value error per state and the root mean square value error will also be plotted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "7dd158868b6da83ed2d8af5393fa19e7",
     "grade": false,
     "grade_id": "cell-aa30396771314085",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "def run_experiment(env_info, agent_info,num_episodes=5000, experiment_name=None, plot_freq=100, true_values_file=None, value_error_threshold=1e-8):\n",
    "    env = CliffWalkEnvironment\n",
    "    agent = TDAgent\n",
    "    rl_glue = RLGlue(env, agent)\n",
    "\n",
    "    rl_glue.rl_init(agent_info, env_info)\n",
    "\n",
    "    manager = Manager(env_info, agent_info, true_values_file=true_values_file, experiment_name=experiment_name)\n",
    "    for episode in range(1, num_episodes + 1):\n",
    "        rl_glue.rl_episode(0) # no step limit\n",
    "        if episode % plot_freq == 0:\n",
    "            values = rl_glue.agent.agent_message(\"get_values\")\n",
    "            manager.visualize(values, episode)\n",
    "\n",
    "    values = rl_glue.agent.agent_message(\"get_values\")\n",
    "    return values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
     "checksum": "e726e3aa91859d231913a83be7b376f6",
     "grade": false,
     "grade_id": "cell-f8a8ad5275cc7e7f",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "The cell below just runs a policy evaluation experiment with the determinstic optimal policy that strides just above the cliff. You should observe that the per state value error and RMSVE curve asymptotically go towards 0. The arrows in the four directions denote the probabilities of taking each action. This experiment is ungraded but should serve as a good test for the later experiments. The true values file provided for this experiment may help with debugging as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "c9935c904c8dac62540410b7dc0eb740",
     "grade": false,
     "grade_id": "cell-2a4f093ff50135b8",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [
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       "/* Put everything inside the global mpl namespace */\n",
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       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
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       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
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       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
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       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
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       "    this.header = titletext[0];\n",
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       "\n",
       "\n",
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       "\n",
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       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
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       "\n",
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       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
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       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
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       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
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       "        stop: function(event, ui) {\n",
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       "\n",
       "    function mouse_event_fn(event) {\n",
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       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
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       "\n",
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       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
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       "        canvas_div.focus();\n",
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       "\n",
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       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
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       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
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       "    function toolbar_mouse_event(event) {\n",
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       "\n",
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       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
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       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "env_info = {\"grid_height\": 4, \"grid_width\": 12, \"seed\": 0}\n",
    "agent_info = {\"discount\": 1, \"step_size\": 0.01, \"seed\": 0}\n",
    "\n",
    "# The Optimal Policy that strides just along the cliff\n",
    "policy = np.ones(shape=(env_info['grid_width'] * env_info['grid_height'], 4)) * 0.25\n",
    "policy[36] = [1, 0, 0, 0]\n",
    "for i in range(24, 35):\n",
    "    policy[i] = [0, 0, 0, 1]\n",
    "policy[35] = [0, 0, 1, 0]\n",
    "\n",
    "agent_info.update({\"policy\": policy})\n",
    "\n",
    "true_values_file = \"optimal_policy_value_fn.npy\"\n",
    "_ = run_experiment(env_info, agent_info, num_episodes=5000, experiment_name=\"Policy Evaluation on Optimal Policy\",\n",
    "                   plot_freq=500, true_values_file=true_values_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "d288407bc4dd094efc56faebad142e5f",
     "grade": false,
     "grade_id": "cell-41ea2c684571e6e8",
     "locked": false,
     "schema_version": 3,
     "solution": true,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "# -----------\n",
    "# Graded Cell\n",
    "# -----------\n",
    "\n",
    "# The Safe Policy\n",
    "# Hint: Fill in the array below (as done in the previous cell) based on the safe policy illustration \n",
    "# in the environment diagram. This is the policy that strides as far as possible away from the cliff. \n",
    "# We call it a \"safe\" policy because if the environment has any stochasticity, this policy would do a good job in \n",
    "# keeping the agent from falling into the cliff (in contrast to the optimal policy shown before). \n",
    "\n",
    "# build a uniform random policy\n",
    "policy = np.ones(shape=(env_info['grid_width'] * env_info['grid_height'], 4)) * 0.25\n",
    "\n",
    "# build an example environment\n",
    "env = CliffWalkEnvironment()\n",
    "env.env_init(env_info)\n",
    "\n",
    "# modify the uniform random policy\n",
    "# your code here\n",
    "for h in range(env_info['grid_height']):\n",
    "    for w in range(env_info['grid_width']):\n",
    "        state = h * env_info['grid_width'] + w\n",
    "        action = [1, 0, 0, 0]\n",
    "        if h == 0:\n",
    "            action = [0, 0, 0, 1]\n",
    "        if w == env_info['grid_width'] - 1:\n",
    "            action = [0, 0, 1, 0]\n",
    "        policy[state] = action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "7d6c1c46ebd8a20c291b6c485601a7da",
     "grade": true,
     "grade_id": "cell-747a2fdf30624260",
     "locked": true,
     "points": 10,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "# -----------\n",
    "# Tested Cell\n",
    "# -----------\n",
    "# The contents of the cell will be tested by the autograder.\n",
    "# If they do not pass here, they will not pass there.\n",
    "\n",
    "width = env_info['grid_width']\n",
    "height = env_info['grid_height']\n",
    "\n",
    "# left side of space\n",
    "for x in range(1, height):\n",
    "    s = env.state((x, 0))\n",
    "    \n",
    "    # go up\n",
    "    assert np.all(policy[s] == [1, 0, 0, 0])\n",
    "\n",
    "# top of space\n",
    "for y in range(width - 1):\n",
    "    s = env.state((0, y))\n",
    "\n",
    "    # go right\n",
    "    assert np.all(policy[s] == [0, 0, 0, 1])\n",
    "    \n",
    "# right side of space\n",
    "for x in range(height - 1):\n",
    "    s = env.state((x, width - 1))\n",
    "    \n",
    "    # go down\n",
    "    assert np.all(policy[s] == [0, 0, 1, 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "f61945e3fa9693a71c67308e390831f2",
     "grade": false,
     "grade_id": "cell-4cff4aa8310f733e",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "agent_info.update({\"policy\": policy})\n",
    "v = run_experiment(env_info, agent_info, experiment_name=\"Policy Evaluation On Safe Policy\", num_episodes=5000, plot_freq=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "fa33604922343541caab97a67b3d0b97",
     "grade": false,
     "grade_id": "cell-e1cf8e11c672a07e",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "\n",
    "# A Near Optimal Stochastic Policy\n",
    "# Now, we try a stochastic policy that deviates a little from the optimal policy seen above. \n",
    "# This means we can get different results due to randomness.\n",
    "# We will thus average the value function estimates we get over multiple runs. \n",
    "# This can take some time, upto about 5 minutes from previous testing. \n",
    "# NOTE: The autograder will compare . Re-run this cell upon making any changes.\n",
    "\n",
    "env_info = {\"grid_height\": 4, \"grid_width\": 12}\n",
    "agent_info = {\"discount\": 1, \"step_size\": 0.01}\n",
    "\n",
    "policy = np.ones(shape=(env_info['grid_width'] * env_info['grid_height'], 4)) * 0.25\n",
    "policy[36] = [0.9, 0.1/3., 0.1/3., 0.1/3.]\n",
    "for i in range(24, 35):\n",
    "    policy[i] = [0.1/3., 0.1/3., 0.1/3., 0.9]\n",
    "policy[35] = [0.1/3., 0.1/3., 0.9, 0.1/3.]\n",
    "agent_info.update({\"policy\": policy})\n",
    "agent_info.update({\"step_size\": 0.01})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "code",
     "checksum": "b3888898a45dcda0c5420f24132be6d4",
     "grade": false,
     "grade_id": "cell-6038bf336a6d7fd2",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ---------------\n",
    "# Discussion Cell\n",
    "# ---------------\n",
    "env_info['seed'] = 0\n",
    "agent_info['seed'] = 0\n",
    "v = run_experiment(env_info, agent_info,\n",
    "               experiment_name=\"Policy Evaluation On Optimal Policy\",\n",
    "               num_episodes=5000, plot_freq=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "cell_type": "markdown",
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    "## Wrapping Up\n",
    "Congratulations, you have completed assignment 2! In this assignment, we investigated a very useful concept for sample-based online learning: temporal difference. We particularly looked at the prediction problem where the goal is to find the value function corresponding to a given policy. In the next assignment, by learning the action-value function instead of the state-value function, you will get to see how temporal difference learning can be used in control as well."
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