L_diffusion.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pyh5md\n",
    "from transforms3d import quaternions\n",
    "from transforms3d.utils import normalized_vector\n",
    "import scipy.integrate\n",
    "import itertools\n",
    "import tidynamics\n",
    "from glob import glob\n",
    "from matplotlib.figure import SubplotParams\n",
    "import os.path\n",
    "\n",
    "π = np.pi\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (8*.7, 6*.7)\n",
    "plt.rcParams['figure.subplot.hspace'] = .25\n",
    "plt.rcParams['figure.subplot.wspace'] = .3\n",
    "plt.rcParams['figure.subplot.left'] = .24\n",
    "plt.rcParams['figure.subplot.bottom'] = .15\n",
    "plt.rcParams['figure.subplot.top'] = 0.95\n",
    "plt.rcParams['figure.subplot.right'] = 0.95\n",
    "\n",
    "plt.rcParams['font.size'] = 12\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [],
   "source": [
    "TYPE = 'h'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20 runs found\n"
     ]
    }
   ],
   "source": [
    "# bead indices defining directions \"1\" and \"2\"\n",
    "\n",
    "idx_1, idx_2 = 5, 33\n",
    "\n",
    "runs = glob('/home/share/nanomotors/20190[45]*/lpart_*/lpart_2019_nosp_noh.h5')\n",
    "runs.sort()\n",
    "\n",
    "if TYPE == 'h':\n",
    "    runs = glob('/home/share/nanomotors/20190[45]*/lpart_2*/lpart_2019_nosp.h5')\n",
    "else:\n",
    "    runs = glob('/home/share/nanomotors/20190[45]*/lpart_2*/lpart_2019_nosp_noh.h5')\n",
    "    \n",
    "runs.sort()\n",
    "print(len(runs), \"runs found\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/share/nanomotors/20190417/lpart_21087167/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190417/lpart_21087168/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190417/lpart_21087169/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190417/lpart_21087170/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190417/lpart_21087171/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190417/lpart_21087172/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190429/lpart_21097760/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190429/lpart_21097761/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190429/lpart_21097762/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190429/lpart_21097763/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190429/lpart_21097764/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190429/lpart_21097765/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100255/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100256/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100257/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100258/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100259/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100260/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100261/lpart_2019_nosp.h5',\n",
       " '/home/share/nanomotors/20190505/lpart_21100262/lpart_2019_nosp.h5']"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "runs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read and analyze simulation data\n",
    "\n",
    "For every simulation:\n",
    "1. Compute the \"body frame\" velocity vB of the L particle\n",
    "2. Integrate vB to obtain the \"body frame\" trajectory\n",
    "3. Compute the cross-displacements and fit the slope to obtain the diffusion matrix\n",
    "\n",
    "Run the cell below onces with `custom_TP = False`, obtain d1 and d2, then re-run\n",
    "with `custom_TP = True`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/share/nanomotors/20190417/lpart_21087167/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190417/lpart_21087168/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190417/lpart_21087169/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190417/lpart_21087170/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190417/lpart_21087171/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190417/lpart_21087172/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190429/lpart_21097760/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190429/lpart_21097761/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190429/lpart_21097762/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190429/lpart_21097763/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190429/lpart_21097764/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190429/lpart_21097765/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100255/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100256/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100257/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100258/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100259/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100260/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100261/lpart_2019_nosp.h5\n",
      "/home/share/nanomotors/20190505/lpart_21100262/lpart_2019_nosp.h5\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "custom_TP = True\n",
    "if custom_TP:\n",
    "    delta_pos = np.array([d1, d2, 0])\n",
    "else:\n",
    "    delta_pos = np.zeros(3)\n",
    "\n",
    "all_cdisp = []\n",
    "all_coh_pos = []\n",
    "v_mean = []\n",
    "all_skip = 2\n",
    "comh_vacf = []\n",
    "\n",
    "u_check = []\n",
    "\n",
    "for r in runs[:]:\n",
    "    try:\n",
    "        tmp_try = pyh5md.File(r, 'r')\n",
    "    except:\n",
    "        continue\n",
    "    with pyh5md.File(r, 'r') as a:\n",
    "        #if a['parameters/probability'][()] != 0.: continue\n",
    "        #if a['parameters/do_hydro'][()] != 1: continue\n",
    "        print(r)\n",
    "        L = a['particles/janus/box/edges'][:]\n",
    "\n",
    "        g = a.particles_group('janus')\n",
    "        el = pyh5md.element(g, 'position')\n",
    "        pos_dt = el.time\n",
    "        pos = el.value[:]\n",
    "        el = pyh5md.element(g, 'image')\n",
    "        im = el.value[:]\n",
    "        im_dt = el.time\n",
    "        pos += im*L\n",
    "        pos_0 = pos[0,:,:]\n",
    "\n",
    "        obs = a['observables']\n",
    "        janus_pos = pyh5md.element(obs, 'janus_pos')\n",
    "        janus_pos_dt = janus_pos.time*all_skip\n",
    "        janus_pos = janus_pos.value[::all_skip]\n",
    "        janus_vel = pyh5md.element(obs, 'janus_vel')\n",
    "        janus_vel_dt = janus_vel.time*all_skip\n",
    "        janus_vel = janus_vel.value[::all_skip]\n",
    "        omega_body = pyh5md.element(obs, 'omega_body')\n",
    "        omega_body_dt = omega_body.time*all_skip\n",
    "        omega_body = omega_body.value[::all_skip]\n",
    "        q = pyh5md.element(obs, 'q')\n",
    "        q_qt = q.time*all_skip\n",
    "        q = q.value[::all_skip]\n",
    "        u = pyh5md.element(obs, 'u')\n",
    "        u_dt = u.time*all_skip\n",
    "        u = u.value[::all_skip]\n",
    "\n",
    "    tmp_s = q[:,3].copy()\n",
    "    tmp_v = q[:,:3].copy()\n",
    "    q[:,1:4] = tmp_v\n",
    "    q[:,0] = tmp_s\n",
    "    del tmp_s, tmp_v\n",
    "\n",
    "    omega = np.array([quaternions.rotate_vector(omega_body_i, q_i) for omega_body_i, q_i in zip(omega_body, q)])\n",
    "\n",
    "    # Compute the basis vectors for the L at initial data point\n",
    "\n",
    "    if custom_TP:\n",
    "        basis_u_perp = normalized_vector(pos_0[idx_2] - pos_0[0])\n",
    "        basis_u_para = normalized_vector(pos_0[idx_1] - pos_0[0])\n",
    "\n",
    "        q_0_inv_mat = quaternions.quat2mat(quaternions.qinverse(q[0]))\n",
    "\n",
    "        basis_u_perp = q_0_inv_mat @ basis_u_perp\n",
    "        basis_u_para = q_0_inv_mat @ basis_u_para\n",
    "\n",
    "        # Compute the trajectory of the CoH based on the CoM data\n",
    "        coh_pos = []\n",
    "        for i in range(u.shape[0]):\n",
    "            shift_para = quaternions.quat2mat(q[i]) @ basis_u_para\n",
    "            shift_perp = quaternions.quat2mat(q[i]) @ basis_u_perp\n",
    "            coh_pos.append(janus_pos[i] + d1*shift_para + d2*shift_perp)\n",
    "\n",
    "        all_coh_pos.append(np.array(coh_pos))\n",
    "    \n",
    "    d_20_0 = np.sqrt(np.sum((pos_0[idx_2]-pos_0[0])**2))\n",
    "    d_4_0 = np.sqrt(np.sum((pos_0[idx_1]-pos_0[0])**2))\n",
    "    u_perp = (pos_0[idx_2,:]-pos_0[0,:])/d_20_0\n",
    "    u_para = (pos_0[idx_1,:]-pos_0[0,:])/d_4_0\n",
    "\n",
    "    u_perp = np.array([quaternions.rotate_vector(u_perp, q_i) for q_i in q])\n",
    "    u_para = np.array([quaternions.rotate_vector(u_para, q_i) for q_i in q])\n",
    "\n",
    "    u_check.append(np.einsum('...i,...i', u_perp, u_para))\n",
    "\n",
    "    v1 = np.array([np.dot(v, u1) for v, u1 in zip(janus_vel, u_para)])\n",
    "    v2 = np.array([np.dot(v, u2) for v, u2 in zip(janus_vel, u_perp)])\n",
    "\n",
    "    if custom_TP:\n",
    "        v_rel = np.cross(omega_body, delta_pos[None,:])\n",
    "\n",
    "        v1 += v_rel[:,0]\n",
    "        v2 += v_rel[:,1]\n",
    "        \n",
    "    comh_vacf.append(tidynamics.acf(v1)+tidynamics.acf(v2))\n",
    "    \n",
    "    disp1 = scipy.integrate.cumtrapz(v1)*janus_vel_dt\n",
    "    disp2 = scipy.integrate.cumtrapz(v2)*janus_vel_dt\n",
    "    dispt = scipy.integrate.cumtrapz(omega[:,2])*omega_body_dt\n",
    "\n",
    "    disp_stride = 32\n",
    "    disp1 = disp1[::disp_stride]\n",
    "    disp2 = disp2[::disp_stride]\n",
    "    dispt = dispt[::disp_stride]\n",
    "\n",
    "    xyz = np.array(list(zip(disp1, disp2, dispt)))\n",
    "    cdisp = tidynamics.cross_displacement(xyz)\n",
    "\n",
    "    all_cdisp.append(cdisp)\n",
    "\n",
    "    v_mean.append((v1.mean(), v2.mean(), omega[:,2].mean()))\n",
    "\n",
    "comh_vacf = np.array(comh_vacf)\n",
    "v_mean = np.array(v_mean)\n",
    "\n",
    "if custom_TP:\n",
    "    cdisp_cus = all_cdisp.copy()\n",
    "else:\n",
    "    cdisp_com = all_cdisp.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(runs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [
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       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
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       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * 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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "START, STOP = 5, 50\n",
    "\n",
    "N_disp = 100\n",
    "\n",
    "disp_time = np.arange(N_disp)*janus_vel_dt*disp_stride\n",
    "\n",
    "cd = np.mean(cdisp_com, axis=0)\n",
    "Ddata = np.zeros((3,3))\n",
    "\n",
    "params = SubplotParams(wspace=0.40, left=.15)\n",
    "plt.figure(figsize=(10, 6), subplotpars=params)\n",
    "\n",
    "for i, j in itertools.product(range(3), range(3)):\n",
    "    plt.subplot(3, 3, 3*i+j+1)\n",
    "\n",
    "    m = cd[i][j]\n",
    "    plt.plot(disp_time, m[:N_disp], label='sim')\n",
    "    fit = np.polyfit(disp_time[START:STOP], m[START:STOP], 1)\n",
    "    plt.plot(disp_time, np.poly1d(fit)(disp_time), label='fit', ls='--')\n",
    "\n",
    "    if i==j==0:\n",
    "        plt.legend()\n",
    "    Ddata[i, j] = fit[-2]/2\n",
    "\n",
    "    if j==0:\n",
    "        plt.ylabel(r'$\\langle \\Delta x_i(\\tau) \\Delta x_j(\\tau) \\rangle$')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correction from CoM to CoH - from Chakrabarty et al 2014, Eq. 33\n",
      "0.35481791912132477 0.48831794686816077\n"
     ]
    }
   ],
   "source": [
    "d1, d2 = -Ddata[1,2]/Ddata[2,2], Ddata[0,2]/Ddata[2,2]\n",
    "\n",
    "print(\"Correction from CoM to CoH - from Chakrabarty et al 2014, Eq. 33\")\n",
    "print(d1, d2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correction from CoM to CoH - from Chakrabarty et al 2014, Eq. 33\n",
      "0.5901373893548949 0.46167031912155465\n"
     ]
    }
   ],
   "source": [
    "d1, d2 = -Ddata[1,2]/Ddata[2,2], Ddata[0,2]/Ddata[2,2]\n",
    "\n",
    "print(\"Correction from CoM to CoH - from Chakrabarty et al 2014, Eq. 33\")\n",
    "print(d1, d2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 3.125, 37.5  ])"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array([20, 240]) / (disp_stride*janus_vel_dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * 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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "START, STOP = 5, 50\n",
    "\n",
    "N_disp = 75\n",
    "\n",
    "disp_time = np.arange(N_disp)*janus_vel_dt*disp_stride\n",
    "\n",
    "cd_com = np.mean(cdisp_com, axis=0)\n",
    "cd_cus = np.mean(cdisp_cus, axis=0)\n",
    "D_com = np.zeros((3,3))\n",
    "D_cus = np.zeros((3,3))\n",
    "\n",
    "idx_list = [(0,0), (1, 1), (2, 2), (0, 1), (0, 2), (1, 2)]\n",
    "label_list = [r'$\\langle X_1(\\tau)^2 \\rangle / a^2$',\n",
    "              r'$\\langle X_2(\\tau)^2 \\rangle / a^2$',\n",
    "              r'$\\langle \\theta(\\tau)^2 \\rangle$',\n",
    "              r'$\\langle X_1(\\tau)\\ X_2(\\tau) \\rangle / a^2$',\n",
    "              r'$\\langle X_1(\\tau)\\ \\theta(\\tau) \\rangle / a$',\n",
    "              r'$\\langle X_2(\\tau)\\ \\theta(\\tau) \\rangle / a$',\n",
    "             ]\n",
    "letter_list = 'abcdef'\n",
    "\n",
    "params = SubplotParams(wspace=0.55, left=.15, hspace=0.4)\n",
    "fig = plt.figure(figsize=(10, 6), subplotpars=params)\n",
    "\n",
    "\n",
    "subplot_idx = 0\n",
    "for i, j in idx_list:\n",
    "    subplot_idx += 1\n",
    "    ax = plt.subplot(2, 3, subplot_idx)\n",
    "\n",
    "    m = cd_com[i][j]\n",
    "    plt.plot(disp_time, m[:N_disp], label='CoM sim.', ls='-', lw=2)\n",
    "    fit = np.polyfit(disp_time[START:STOP], m[START:STOP], 1)\n",
    "    plt.plot(disp_time, np.poly1d(fit)(disp_time), label='CoM fit', ls='-', alpha=0.4, color='k')\n",
    "    D_com[i, j] = D_com[j, i] = fit[-2]/2\n",
    "\n",
    "    m = cd_cus[i][j]\n",
    "    plt.plot(disp_time, m[:N_disp], label='CoH sim.', ls='--', lw=2)\n",
    "    fit = np.polyfit(disp_time[START:STOP], m[START:STOP], 1)\n",
    "    plt.plot(disp_time, np.poly1d(fit)(disp_time), label='CoH fit', ls='--', alpha=0.4, color='k')\n",
    "    D_cus[i, j] = D_cus[j, i] = fit[-2]/2\n",
    "\n",
    "    if subplot_idx==1:\n",
    "        plt.legend(fontsize=10)\n",
    "    plt.text(0., 1.05, '('+letter_list[subplot_idx-1]+')', transform=ax.transAxes)\n",
    "\n",
    "    plt.xlabel(r'$\\tau / {t_0} $')\n",
    "    plt.ylabel(label_list[subplot_idx-1])\n",
    "\n",
    "#plt.savefig('L_eq_cdisp.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12.70 & -0.59 & 0.25 \\cr\n",
      "-0.59 & 13.20 & -0.18 \\cr\n",
      "0.25 & -0.18 & 0.51 \\cr\n"
     ]
    }
   ],
   "source": [
    "# print D_com with LaTeX table formatting\n",
    "for line in D_com:\n",
    "    l1, l2, l3 = map(lambda x: 10000*x, line)\n",
    "    \n",
    "    print('%3.2f & %3.2f & %3.2f \\\\cr' % (l1, l2, l3))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12.58 & -0.50 & -0.00 \\cr\n",
      "-0.50 & 13.13 & 0.00 \\cr\n",
      "-0.00 & 0.00 & 0.51 \\cr\n"
     ]
    }
   ],
   "source": [
    "# print D_cus with LaTeX table formatting\n",
    "for line in D_cus:\n",
    "    l1, l2, l3 = map(lambda x: 10000*x, line)\n",
    "    \n",
    "    print('%3.2f & %3.2f & %3.2f \\\\cr' % (l1, l2, l3))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.48,\n",
       " 0.35481791912132477,\n",
       " array([[ 1.25760062e-03, -5.00282852e-05, -1.96677692e-09],\n",
       "        [-5.00282852e-05,  1.31310931e-03,  1.42908468e-09],\n",
       "        [-1.96677692e-09,  1.42908468e-09,  5.11779636e-05]]),\n",
       " 53.45356081267256,\n",
       " 0.35481791912132477,\n",
       " 0.48831794686816077)"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l, d1, D_cus, D_cus[1,1] / (D_cus[2,2]*l), d1, d2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [],
   "source": [
    "σ = 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "l =  0.5543528189679803\n"
     ]
    }
   ],
   "source": [
    "# Coordinates: x=0 is the bottom-left corner of the L\n",
    "\n",
    "# center of mass of the L\n",
    "x_com = ( 9 * (0 + 1 + 2) + 3 * (3 + 4 + 5) ) * σ / 36\n",
    "\n",
    "# center of the foot of the L\n",
    "x_mid = (0 + 1 + 2 + 3 + 4 + 5) * σ / 6\n",
    "\n",
    "# position of the center of hydrodynamics\n",
    "x_coh = x_com + d1\n",
    "\n",
    "l = x_mid - x_coh\n",
    "print('l = ', l)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.35481791912132477"
      ]
     },
     "execution_count": 277,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-5.00267704e-05  1.31310821e-03 -3.94149214e-05]\n",
      "0.7701820808786755 -33.339171385887724\n"
     ]
    }
   ],
   "source": [
    "# Compute radius from force and torque\n",
    "X_dot = D_cus @ np.array([0, 1, -l])\n",
    "print(X_dot)\n",
    "print(l, np.sqrt(X_dot[0]**2+X_dot[1]**2)/X_dot[2])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * 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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"560\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(-6.375005192649612, 8.625002679169022)"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.subplot(111, aspect=1)\n",
    "\n",
    "TH_0 = np.arctan2(pos_0[33,1]-pos_0[0,1], pos_0[33,0]-pos_0[0,0])\n",
    "TH_0 = π/2 - TH_0\n",
    "\n",
    "rot_m = np.array([[np.cos(TH_0), -np.sin(TH_0)], [np.sin(TH_0), np.cos(TH_0)]])\n",
    "\n",
    "xy = pos_0[:36,:2]\n",
    "\n",
    "xy -= xy.mean(axis=0)\n",
    "xy = np.array([rot_m @ i for i in xy])\n",
    "\n",
    "\n",
    "plt.plot(*xy.T, ls='', marker='o', ms=23, alpha=0.3)\n",
    "plt.plot([0], [0], ls='', marker='^')\n",
    "plt.plot([d1], [d2], ls='', marker='x')\n",
    "\n",
    "plt.axvline(xy[:6,0].mean())\n",
    "\n",
    "plt.xlim(xy[:,0].min()-σ, xy[:,0].max()+σ)\n",
    "plt.ylim(xy[:,1].min()-σ, xy[:,1].max()+σ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}