Run_DQN.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adaptive WiFi Load Balancing using Deep Q-learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we are trying to map STAs to APs considering an enterprise network model."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "State of the art STA AP mapping is done by the means of maximum signal strength or based on the minimum distance between STA and AP in an enterprise network. But when several STAs connected with different applications based on the distance/RSSI, the network cannot achieve maximum aggregated network throughput. So, in this work, we have considered Deep-Reinforcement learning based approach to map STAs to APs based on the bitrate information."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Importing modules "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\h5py\\__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import os\n",
    "import itertools\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.io import loadmat,savemat\n",
    "from numpy import random\n",
    "from random import uniform\n",
    "import shutil # to copy files to a speicific folder\n",
    "''' import custom modules '''\n",
    "from algorithms import Station_map,STA_clustering\n",
    "''' copy file to desired folder'''\n",
    "copy = False\n",
    "filenum=5\n",
    "import DQN_v2 as rl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Import STA bitrate data\n",
    "This bitrate are considered as upload bit rate and download bitrate per station and those are fed and fetched from APs.\n",
    "Here we have the bitrate data for 200 Stations over a period of 2 days approximately."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "UL_Rate = loadmat('UL_Rate.mat')\n",
    "UL_R =  UL_Rate['UL_Rate'].T\n",
    "DL_Rate = loadmat('DL_Rate.mat')\n",
    "DL_R =  DL_Rate['DL_Rate'].T\n",
    "NTs,N_STA = DL_R.shape # N_STA : Number of stations, NTs : Number of Timestames (length of the data for each station)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set NS3 network directory "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since NS3 can only be run from the directory \"Scratch\" , hence if we have any NS3 network model we should store it in \"$ns-3/ns-3.28/scratch$\" folder.\n",
    "\n",
    "$Note:$ the folder names could vary according to the NS3 installation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "os.chdir('/home/koushik/ns-3/ns-3.28/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize network simulation parameters "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "nSTAs= 6 #int(N_STA) # number of stations in the network\n",
    "nAPs = 2  # numbe of APs in the network\n",
    "area = 15 # cross section area of the network, ex: 200X200 # parameter in meters\n",
    "sim_Time =  2 # in seconds\n",
    "visualize = False # visualize simulation \n",
    "MCS = -7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "''' a simple mapping of STA to AP: we get this from our algorithm '''\n",
    "random.seed(1)\n",
    "xloc  = random.randint(area,size=nSTAs)#random.uniform(area,size=nSTAs) #\n",
    "random.seed(10)\n",
    "yloc  = random.randint(area,size=nSTAs)#random.uniform(area,size=nSTAs)#\n",
    "x =  xloc.reshape([nSTAs,1])\n",
    "y =  yloc.reshape([nSTAs,1])\n",
    "STA_loc =  np.append(x,y,axis=1);\n",
    "AP_loc = np.array([[0,0],[area/2,0],[area,0],[area,area/2],[area,area],\n",
    "                   [area/2,area],[0,area],[0,area/2],[area/2,area/2]]);\n",
    "res={}\n",
    "random.seed()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "S_map = Station_map(area,nAPs,nSTAs,AP_loc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initializing RL parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "actions ={} # collect all possible actions based on station mapping\n",
    "n_states  =  nAPs**nSTAs # totoal number of states in load balancing\n",
    "#actions =  RL_model.get_action() # combined actions for all the agents \n",
    "n_actions =  nAPs**nSTAs# len(actions) # total number of combined actions \n",
    "epoch = 5000;\n",
    "epoch1=1;\n",
    "lst =  list(itertools.product(np.arange(nAPs), repeat=nSTAs)) # generate all possible mappings of STA--> AP\n",
    "actions = dict(zip(np.arange(n_actions),np.array(lst)))\n",
    "action =  random.randint(0,n_actions-1)\n",
    "STA_map=actions[(action)];"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Setting up UAV environment parameters. We run DQN for epoch iterations and we take the mean average of running   epoch1 iterations over epoch iterations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "}\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 overriden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "FileNotFoundError",
     "evalue": "[WinError 3] The system cannot find the path specified: '/home/koushik/ns-3/ns-3.28/'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-7-66f002ddf555>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[0magent\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrl\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAgent\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mUL_R\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mDL_R\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mxloc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0myloc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mAP_loc\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0marea\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mnSTAs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mnAPs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msim_Time\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvisualize\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mMCS\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mn_actions\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mactions\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mepoch\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mepoch1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmodel_dir\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrender\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     16\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 17\u001b[1;33m     \u001b[0mR1\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0magent\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     18\u001b[0m     \u001b[0mR\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mR1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     19\u001b[0m     \u001b[0mdf\u001b[0m\u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mR\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mR\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Dropbox\\Koushik_CL_work\\Simulation\\NS3\\Koushik_code\\DQN_v2.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(self, fig, ax)\u001b[0m\n\u001b[0;32m    810\u001b[0m                                                                  training=self.training)\n\u001b[0;32m    811\u001b[0m                 \u001b[1;34m''' determine reward and new UAV position based on current action taken '''\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 812\u001b[1;33m                 \u001b[0mpos_t\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mreward\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0menv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend_to_nw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0maction\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDL\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mUL\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;31m#(action=action)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    813\u001b[0m                 \u001b[0mR1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreward\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    814\u001b[0m                 \u001b[1;34m''' update state history '''\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Dropbox\\Koushik_CL_work\\Simulation\\NS3\\Koushik_code\\DQN_v2.py\u001b[0m in \u001b[0;36msend_to_nw\u001b[1;34m(self, action, DL, UL)\u001b[0m\n\u001b[0;32m     58\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     59\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0msend_to_nw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0maction\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mDL\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mUL\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 60\u001b[1;33m         \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchdir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'/home/koushik/ns-3/ns-3.28/'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# setting the NS3 directory path\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     61\u001b[0m         \"\"\"\n\u001b[0;32m     62\u001b[0m         \u001b[0mInput\u001b[0m\u001b[1;33m:\u001b[0m  \u001b[1;36m1.\u001b[0m \u001b[0maction\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;33m->\u001b[0m \u001b[0mSTA_map\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 3] The system cannot find the path specified: '/home/koushik/ns-3/ns-3.28/'"
     ]
    }
   ],
   "source": [
    "epoch = 5000*1\n",
    "epoch1=1\n",
    "model_dir= './Model/'\n",
    "import time\n",
    "import pandas as pd\n",
    "x=time.ctime()\n",
    "render = False    \n",
    "R = {}\n",
    "''' real-time plotting '''\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "plt.ion()\n",
    "fig.show()\n",
    "fig.canvas.draw()\n",
    "agent = rl.Agent(UL_R,DL_R,xloc,yloc,AP_loc,area,nSTAs,nAPs,sim_Time,visualize,MCS,n_actions,actions,epoch,epoch1,model_dir,render)   \n",
    "for i in range(5):\n",
    "    R1=agent.run(fig,ax)\n",
    "    R[i] = pd.Series(R1)\n",
    "    df= pd.DataFrame(R,columns=list(R.keys()))\n",
    "    df.to_csv('DQN_'+x+'.csv')   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save the collected reward data to a file in the foleder named \"Data\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import time\n",
    "import pandas as pd\n",
    "x=time.ctime()\n",
    "df= pd.DataFrame(R,columns=list(R.keys()))\n",
    "df.to_csv('DQN_'+x+'.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "%matplotlib inline\n",
    "fig, ax = plt.subplots( nrows=1, ncols=1 )\n",
    "plt.plot(R[0:])\n",
    "plt.ylim([0,np.max(R[0:])+ 1])\n",
    "plt.ylabel('Average of victories per game')\n",
    "plt.xlim([0,len(R[0:])])\n",
    "plt.xlabel('number of iterations')\n",
    "plt.grid()\n",
    "if Jamming:\n",
    "    fig.savefig(filepath+ 'R_Jam'+ x +'.png')\n",
    "else:\n",
    "    fig.savefig(filepath+ 'R_noJ'+ x +'.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R1\n",
    "reward=[0];\n",
    "for i in range(len(R)-1):\n",
    "    reward.append((R[i]+R[i+1])/2) \n",
    "fig, ax = plt.subplots( nrows=1, ncols=1 )\n",
    "plt.plot(reward)\n",
    "plt.ylim([0,np.max(R[2:])+ 1])\n",
    "plt.ylabel('Average of victories per game')\n",
    "plt.xlim([0,len(R[2:])])\n",
    "plt.xlabel('number of iterations')\n",
    "plt.grid()\n",
    "plt.show()\n",
    "fig.savefig(filepath+ 'Rm_'+ x +'.pdf',bbox_inches='tight')"
   ]
  }
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