compound_Plots.ipynb 569 KB
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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "from scipy.stats import rv_continuous\n",
    "from scipy.interpolate import interp1d\n",
    "from matplotlib.patches import Circle\n",
    "from scipy.special import gamma\n",
    "import numpy as np\n",
    "import emcee\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "from numpy import exp, sqrt\n",
    "from scipy.integrate import quad, dblquad, nquad\n",
    "import matplotlib.patches as patches\n",
    "from itertools import product\n",
    "from scipy.integrate import quad\n",
    "import scipy.optimize as optimize\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "from sklearn.neighbors import KDTree\n",
    "import sys\n",
    "import lmfit\n",
    "from py_unsio import *\n",
    "import pymc\n",
    "import os\n",
    "from scipy.integrate import simps\n",
    "from pymodelfit import FunctionModel1DAuto\n",
    "import wkbl\n",
    "from wkbl.astro.halo_info import *\n",
    "from mpl_toolkits.mplot3d import axes3d\n",
    "from matplotlib import cm\n",
    "import wkbl.astro.nbody_essentials as nbe\n",
    "import cfalcon\n",
    "CF =cfalcon.CFalcon()\n",
    "import iminuit\n",
    "from iminuit import Minuit, describe, Struct\n",
    "import probfit\n",
    "from matplotlib.colors import LogNorm\n",
    "from matplotlib.ticker import FormatStrFormatter\n",
    "import warnings\n",
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    "import wkbl.astro.halo_info as h\n",
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    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# S and T"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 68,
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   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "def readSnT(datafile):\n",
    "    myfile = open(datafile)\n",
    "    r = S = T = np.array([])\n",
    "    for l in myfile:\n",
    "        row =  l.split(\" \")\n",
    "        if l[0]==\"#\" and row[1]=='r200':\n",
    "            r200 = np.float(row[3] )\n",
    "        if l[0]==\"#\":continue\n",
    "        r = np.append(r,row[0])\n",
    "        S = np.append(S,row[1])\n",
    "        T = np.append(T,row[2])\n",
    "    return r, S, T,r200\n",
    "HaloB_r, HaloB_S, HaloB_T,HaloB_r200 = readSnT(\"../../datafiles/HALO_B_S_and_T.txt\")\n",
    "HaloC_r, HaloC_S, HaloC_T,HaloC_r200 = readSnT(\"../../datafiles/HALO_C_S_and_T.txt\")\n",
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    "Mochima_r, Mochima_S, Mochima_T, Mochima_r200 = readSnT(\"../../datafiles/Mochima_S_and_T.txt\")\n",
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    "Adicora_r, Adicora_S, Adicora_T, Adicora_r200 = readSnT(\"../../datafiles/Adicora_S_and_T.txt\")\n",
    "\n",
    "\n",
    "HaloB_r_DMO, HaloB_S_DMO, HaloB_T_DMO,HaloB_r200_DMO = readSnT(\"../../datafiles/HALOB_S_and_T_DMO.txt\")\n",
    "HaloC_r_DMO, HaloC_S_DMO, HaloC_T_DMO,HaloC_r200_DMO = readSnT(\"../../datafiles/HALOC_S_and_T_DMO.txt\")\n",
    "Mochima_r_DMO, Mochima_S_DMO, Mochima_T_DMO, Mochima_r200_DMO = readSnT(\"../../datafiles/Mochima_S_and_T_DMO.txt\")\n",
    "Adicora_r_DMO, Adicora_S_DMO, Adicora_T_DMO, Adicora_r200_DMO = readSnT(\"../../datafiles/Adicora_S_and_T_DMO.txt\")\n"
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   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 69,
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   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "HB_color = \"#097220\"\n",
    "HC_color = \"#4c0972\"\n",
    "Mo_color = \"#094272\"\n",
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    "Ad_color = \"#C70039\"\n",
    "\n",
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    "font=15"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 70,
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   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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": {
      "text/html": [
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\">"
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
906
    "fig, [[ax,ax1],[ax2,ax3]] = plt.subplots(2,2,figsize=[10,10])\n",
907
    "ax.set_ylabel(r\"$\\rm S$\",fontsize=1.5*font)\n",
908 909 910 911 912
    "ax2.set_ylabel(r\"$\\rm T$\",fontsize=1.5*font)\n",
    "ax2.set_xlabel(r\"$\\rm r [kpc]$\",fontsize=1.5*font)\n",
    "ax3.set_xlabel(r\"$\\rm r [kpc]$\",fontsize=1.5*font)\n",
    "\n",
    "ax.set_xlabel(r\"$\\rm r [kpc]$\",fontsize=1.5*font)\n",
913 914 915 916 917
    "ax1.set_xlabel(r\"$\\rm r [kpc]$\",fontsize=1.5*font)\n",
    "\n",
    "ax.plot(HaloB_r,HaloB_S,ls='--',lw=2,color=HB_color)\n",
    "ax.plot(HaloC_r,HaloC_S,ls='--',lw=2,color=HC_color)\n",
    "ax.plot(Mochima_r,Mochima_S,ls='--',lw=2,color=Mo_color)\n",
918
    "ax.plot(Adicora_r,Adicora_S,ls='--',lw=2,color=Ad_color)\n",
919 920 921 922 923
    "ax2.plot(HaloB_r,HaloB_T,ls='-',lw=2,color=HB_color)\n",
    "ax2.plot(HaloC_r,HaloC_T,ls='-',lw=2,color=HC_color)\n",
    "ax2.plot(Mochima_r,Mochima_T,ls='-',lw=2,color=Mo_color)\n",
    "ax2.plot(Adicora_r,Adicora_T,ls='-',lw=2,color=Ad_color)\n",
    "\n",
924 925 926
    "ax.plot(1,1000,ls='-',lw=2,color=HB_color,label=r\"$\\rm HALO\\,\\,B$\")\n",
    "ax.plot(1,1000,ls='-',lw=2,color=HC_color,label=r\"$\\rm HALO\\,\\,C$\")\n",
    "ax.plot(1,1000,ls='-',lw=2,color=Mo_color,label=r\"$\\rm Mochima$\")\n",
927
    "ax.plot(1,1000,ls='-',lw=2,color=Ad_color,label=r\"$\\rm Adicora$\")\n",
928 929
    "\n",
    "\n",
930
    "ax.set_ylim(0.45,1)\n",
931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951
    "ax1.set_ylim(0.45,1)\n",
    "ax.set_xlim(0,249)\n",
    "ax2.set_xlim(0,249)\n",
    "\n",
    "ax1.set_xlim(1,250)\n",
    "ax3.set_xlim(1,250)\n",
    "ax2.set_ylim(0,1)\n",
    "ax3.set_ylim(0,1)\n",
    "\n",
    "ax1.plot(HaloB_r_DMO,HaloB_S_DMO,ls='--',lw=2,color=HB_color)\n",
    "ax1.plot(HaloC_r_DMO,HaloC_S_DMO,ls='--',lw=2,color=HC_color)\n",
    "ax1.plot(Mochima_r_DMO,Mochima_S_DMO,ls='--',lw=2,color=Mo_color)\n",
    "ax1.plot(Adicora_r_DMO,Adicora_S_DMO,ls='--',lw=2,color=Ad_color)\n",
    "\n",
    "\n",
    "\n",
    "ax3.plot(HaloB_r_DMO,HaloB_T_DMO,ls='-',lw=2,color=HB_color)\n",
    "ax3.plot(HaloC_r_DMO,HaloC_T_DMO,ls='-',lw=2,color=HC_color)\n",
    "ax3.plot(Mochima_r_DMO,Mochima_T_DMO,ls='-',lw=2,color=Mo_color)\n",
    "ax3.plot(Adicora_r_DMO,Adicora_T_DMO,ls='-',lw=2,color=Ad_color)\n",
    "legend = ax.legend(loc='lower left', ncol=2, shadow=False, fontsize=font)\n",
952 953 954
    "frame = legend.get_frame()\n",
    "ax.tick_params(axis='y', which='major', labelsize=15, size=5,width=1.2)\n",
    "ax.tick_params(axis='y', which='minor', labelsize=15, size=3,width=1.2)\n",
955 956 957 958 959 960 961 962 963 964 965 966
    "ax.tick_params(axis='x', which='major', labelsize=15, size=5,width=1.2)\n",
    "ax.tick_params(axis='x', which='minor', labelsize=15, size=3,width=1.2)\n",
    "ax1.tick_params(axis='y', which='major', labelsize=0, size=5,width=1.2)\n",
    "ax1.tick_params(axis='y', which='minor', labelsize=0, size=3,width=1.2)\n",
    "ax1.tick_params(axis='x', which='major', labelsize=15, size=5,width=1.2)\n",
    "ax1.tick_params(axis='x', which='minor', labelsize=15, size=3,width=1.2)\n",
    "ax2.tick_params(axis='both', which='major', labelsize=15, size=5,width=1.2)\n",
    "ax2.tick_params(axis='both', which='minor', labelsize=15, size=3,width=1.2)\n",
    "ax3.tick_params(axis='y', which='major', labelsize=0, size=5,width=1.2)\n",
    "ax3.tick_params(axis='y', which='minor', labelsize=0, size=3,width=1.2)\n",
    "ax3.tick_params(axis='x', which='major', labelsize=15, size=5,width=1.2)\n",
    "ax3.tick_params(axis='x', which='minor', labelsize=15, size=3,width=1.2)\n",
967
    "ax.axvline(x=HaloB_r200,lw=2,ls='-.',color=HB_color)\n",
968
    "ax1.axvline(x=HaloB_r200_DMO,lw=2,ls='-.',color=HB_color)\n",
969
    "ax.axvline(x=HaloC_r200,lw=2,ls='-.',color=HC_color)\n",
970
    "ax1.axvline(x=HaloC_r200_DMO,lw=2,ls='-.',color=HC_color)\n",
971
    "ax.axvline(x=Mochima_r200,lw=2,ls='-.',color=Mo_color)\n",
972 973
    "ax1.axvline(x=Mochima_r200_DMO,lw=2,ls='-.',color=Mo_color)\n",
    "ax1.axvline(x=Adicora_r200_DMO,lw=2,ls='-.',color=Ad_color)\n",
974
    "ax.axvline(x=Adicora_r200,lw=2,ls='-.',color=Ad_color)\n",
975 976 977 978 979 980 981 982
    "ax2.axvline(x=HaloB_r200,lw=2,ls='-.',color=HB_color)\n",
    "ax3.axvline(x=HaloB_r200_DMO,lw=2,ls='-.',color=HB_color)\n",
    "ax2.axvline(x=HaloC_r200,lw=2,ls='-.',color=HC_color)\n",
    "ax3.axvline(x=HaloC_r200_DMO,lw=2,ls='-.',color=HC_color)\n",
    "ax2.axvline(x=Mochima_r200,lw=2,ls='-.',color=Mo_color)\n",
    "ax3.axvline(x=Mochima_r200_DMO,lw=2,ls='-.',color=Mo_color)\n",
    "ax3.axvline(x=Adicora_r200_DMO,lw=2,ls='-.',color=Ad_color)\n",
    "ax2.axvline(x=Adicora_r200,lw=2,ls='-.',color=Ad_color)\n",
983 984
    "ax.set_title(r\"$\\rm Hydro$\",fontsize=20 )\n",
    "ax1.set_title(r\"$\\rm DMO$\",fontsize=20 )\n",
985
    "fig.tight_layout(w_pad=-2.86)\n",
986
    "plt.savefig(\"/home/arturo/Documents/LAM/LAM2LUPM/General_Plots/S_n_T_all.pdf\")"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# $\\beta(r)$"
   ]
  },
  {
   "cell_type": "code",
998
   "execution_count": 44,
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   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def readbeta(datafile):\n",
    "    myfile = open(datafile)\n",
    "    r = beta = np.array([])\n",
    "    for l in myfile:\n",
    "        row =  l.split(\" \")\n",
    "        if l[0]==\"#\" and row[1]=='r200':\n",
    "            r200 = np.float(row[3] )\n",
    "        if l[0]==\"#\":continue\n",
    "        r = np.append(r,row[0])\n",
    "        beta = np.append(beta,row[1])\n",
    "    return r, beta,r200\n",
    "HaloB_r, HaloB_beta,HaloB_r200 = readbeta(\"../../datafiles/HALO_B_Beta.txt\")\n",
    "HaloC_r, HaloC_beta,HaloC_r200 = readbeta(\"../../datafiles/HALO_C_Beta.txt\")\n",
1017 1018
    "Mochima_r, Mochima_beta, Mochima_r200 = readbeta(\"../../datafiles/Mochima_Beta.txt\")\n",
    "Adicora_r, Adicora_beta, Adicora_r200 = readbeta(\"../../datafiles/Adicora_Beta.txt\")\n"
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   ]
  },
  {
   "cell_type": "code",
1023
   "execution_count": 45,
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   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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": {
      "text/html": [
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\">"
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.set_ylabel(r\"$\\beta(r)$\",fontsize=1.5*font)\n",
    "ax.set_xlabel(r\"$\\rm r[kpc]$\",fontsize=1.5*font)\n",
    "\n",
    "ax.set_xscale(\"log\")\n",
1811
    "ax.set_ylim([-1.,1])\n",
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    "ax.plot(HaloB_r,HaloB_beta,ls='-',lw=2,color=HB_color,label=r\"$\\rm HALO\\,\\,B$\")\n",
    "ax.plot(HaloC_r,HaloC_beta,ls='-',lw=2,color=HC_color,label=r\"$\\rm HALO\\,\\,C$\")\n",
    "ax.plot(Mochima_r,Mochima_beta,ls='-',lw=2,color=Mo_color,label=r\"$\\rm Mochima$\")\n",
1815
    "ax.plot(Adicora_r,Adicora_beta,ls='-',lw=2,color=Ad_color,label=r\"$\\rm Mochima$\")\n",
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    "#ax.plot(1,1000,ls='-',lw=2,color=HB_color,label=r\"$\\rm HALO\\,\\,B$\")\n",
    "#ax.plot(1,1000,ls='-',lw=2,color=HC_color,label=r\"$\\rm HALO\\,\\,C$\")\n",
    "#ax.plot(1,1000,ls='-',lw=2,color=Mo_color,label=r\"$\\rm Mochima$\")\n",
    "#ax.set_ylim(0.45,1)\n",
    "legend = ax.legend(loc='lower left', ncol=1, shadow=False, fontsize=font)\n",
    "frame = legend.get_frame()\n",
    "ax.tick_params(axis='both', which='major', labelsize=15, size=5,width=1.2)\n",
    "ax.tick_params(axis='both', which='minor', labelsize=15, size=3,width=1.2)\n",
    "\n",
    "ax.axvline(x=HaloB_r200,lw=2,ls='-.',color=HB_color)\n",
    "ax.axvline(x=HaloC_r200,lw=2,ls='-.',color=HC_color)\n",
    "ax.axvline(x=Mochima_r200,lw=2,ls='-.',color=Mo_color)\n",
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    "plt.tight_layout()\n",
    "plt.savefig(\"/home/arturo/Documents/LAM/LAM2LUPM/General_Plots/Beta_r_all.pdf\")"
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   ]
  },
  {
   "cell_type": "code",
1834
   "execution_count": 47,
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   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def readMomemts(datafile):\n",
    "    myfile = open(datafile)\n",
    "    r = m1 = m2 = m3 =  np.array([])\n",
    "    for l in myfile:\n",
    "        row =  l.split(\" \")\n",
    "        if l[0]==\"#\" and row[1]=='r200':\n",
    "            r200 = np.float(row[3] )\n",
    "        if l[0]==\"#\":continue\n",
    "        r = np.append(r,float(row[0]))\n",
    "        m1 = np.append(m1,float(row[1]))\n",
    "        m2 = np.append(m2,float(row[2]))\n",
    "        m3 = np.append(m3,float(row[3]))\n",
    "    return r, m1, m2, m3, r200\n",
    "HaloB_r, HaloB_m1, HaloB_m2,HaloB_m3,HaloB_r200 = readMomemts(\"../../datafiles/HALO_B_Moments.txt\")\n",
    "HaloC_r, HaloC_m1, HaloC_m2,HaloC_m3,HaloC_r200 = readMomemts(\"../../datafiles/HALO_C_Moments.txt\")\n",
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    "Mochima_r, Mochima_m1, Mochima_m2, Mochima_m3, Mochima_r200 = readMomemts(\"../../datafiles/Mochima_Moments.txt\")\n",
    "Adicora_r, Adicora_m1, Adicora_m2, Adicora_m3, Adicora_r200 = readMomemts(\"../../datafiles/Adicora_Moments.txt\")"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {
    "collapsed": false
   },
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   "outputs": [],
   "source": []
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  },
  {
   "cell_type": "code",
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   "execution_count": 48,
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