homogenized model simplified circuit-zenodo-v1.0.0.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Homogenized model simplified circuit-Object oriented V1.0.0\n",
    "**E is electrolyte potential $\\phi$**\n",
    "+ with controlled Eref range\n",
    "+ updated guess from previous scan point\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from __future__ import division"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class corrparam:\n",
    "    \"\"\"E i properties object, use butler-volmer equation, could be extented with more complex kinetics\"\"\"\n",
    "    def __init__(self,Eeq,i0,Ba,Bc):\n",
    "        self.Eeq = Eeq\n",
    "        self.i0 = i0\n",
    "        self.Ba = Ba\n",
    "        self.Bc = Bc\n",
    "    def ia(self, E):\n",
    "        return self.i0*10**((E-self.Eeq)/self.Ba)\n",
    "\n",
    "    def ic(self, E):\n",
    "        return -self.i0*10**((E-self.Eeq)/self.Bc)    \n",
    "\n",
    "    def inet(self, E):\n",
    "        return self.ia(E)+self.ic(E)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def itot(E1,E2,par1,par2,A1,A2):\n",
    "    \"\"\"High-level net current\"\"\"\n",
    "    itot = par1.inet(E1)*A1 + par2.inet(E2)*A2\n",
    "    return itot\n",
    "\n",
    "def E_homo(E1,E2,A1,A2):\n",
    "    \"\"\"area-averaged homogenized potential\"\"\"\n",
    "    return (E1*A1 + E2*A2)/(A1+A2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# objective function finding E1,E2 at Open circuit\n",
    "def E1E2_OC_obj_f(E1E2,model):\n",
    "    E1 = E1E2[0]\n",
    "    E2 = E1E2[1]\n",
    "    obj1 = model.par1.inet(-E1)*model.A1*model.Area+model.par2.inet(-E2)*model.A2*model.Area\n",
    "    obj2 = E1-E2-(model.par1.inet(-E1)*model.A1*model.Area)*1/(1/(model.R1+model.R2)+1/model.R0)\n",
    "    return [obj1,obj2]\n",
    "\n",
    "\n",
    "# objective function Krichhoff's law\n",
    "def objective_f(unknowns,model,Ec):\n",
    "    # E1,E2,Ec are all electrolyte potential\n",
    "\n",
    "    E1,E2,I1,I2,I1_e,I2_e,I0 = unknowns\n",
    "\n",
    "\n",
    "    obj1 = I1 -I0-I1_e\n",
    "    obj2 = I2 +I0-I2_e\n",
    "\n",
    "    obj3 = I1_e*model.R1 -I2_e*model.R2-I0*model.R0\n",
    "    obj4 = 0-E1 + I0*model.R0 +E2 -0\n",
    "\n",
    "    obj5 = Ec-0+(0-E1)+I1_e*model.R1\n",
    "\n",
    "    obj6 = I1 - model.par1.inet(-E1)*model.Area*model.A1\n",
    "    obj7 = I2 - model.par2.inet(-E2)*model.Area*model.A2\n",
    "    return [obj1,obj2,obj3,obj4,obj5,obj6,obj7]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "class model_set:\n",
    "    \"\"\"set mode parameters and solve properties\"\"\"\n",
    "    def __init__(self,par1,par2,Area,A1,A2,R0,Re):\n",
    "        self.par1 = par1\n",
    "        self.par2 = par2\n",
    "        self.Area = Area\n",
    "        self.A1 = A1\n",
    "        self.A2 = A2\n",
    "        self.R0 = R0\n",
    "        self.Re = Re\n",
    "        self.R1 = Re*(A1+A2)/A1\n",
    "        self.R2 = Re*(A1+A2)/A2\n",
    "        self.comment = ''\n",
    "        \n",
    "    def find_OCP_icorr(self): \n",
    "        from scipy.optimize import fsolve\n",
    "        ini_guess = [self.par1.Eeq, self.par2.Eeq]\n",
    "\n",
    "        E1E2 = fsolve(E1E2_OC_obj_f,ini_guess, args=(self),xtol=1e-12)\n",
    "        self.OCP = - (E1E2[0]*self.A1 + E1E2[1]*self.A2)\n",
    "        self.icorr = self.par1.inet(-E1E2[0])*self.A1\n",
    "        return E1E2\n",
    "\n",
    "        \n",
    "    def solve(self,plot_residual=False,cathodic_range=-0.15,anodic_range=0.15, scan_step=0.005):\n",
    "        # open circuit\n",
    "        E1E2 = self.find_OCP_icorr()\n",
    "        \n",
    "        # Potentio-dynamic scan\n",
    "        from scipy.optimize import fsolve        \n",
    "               \n",
    "        # inital step initial guess, \n",
    "        sol = [E1E2[0], E1E2[1], \n",
    "               self.icorr*self.Area, -self.icorr*self.Area,\n",
    "               0.,0,self.icorr*self.Area] #E1,E2,I1,I2,I1_e,I2_e,I0\n",
    "        \n",
    "        sol_list = []\n",
    "        Eapp_list = []\n",
    "        \n",
    "        # cathodic branch\n",
    "        Ec = -self.OCP-0.001\n",
    "        while -E_homo(sol[0],sol[1],self.A1,self.A2) >= (self.OCP+cathodic_range): #Eref->Eref-150mV\n",
    "            Ec += scan_step\n",
    "         \n",
    "            sol = fsolve(objective_f,sol, args=(self,Ec),xtol=1e-12) # use previous sol as initial guess\n",
    "            sol_list.append(sol)\n",
    "            Eapp_list.append(Ec)\n",
    "        \n",
    "        sol_list = list(reversed(sol_list))# reverse squence to have one direction from cathode to anode\n",
    "        Eapp_list = list(reversed(Eapp_list))\n",
    "        \n",
    "        # anodic branch\n",
    "        Ec = -self.OCP+0.001\n",
    "        while -E_homo(sol[0],sol[1],self.A1,self.A2) <= (self.OCP+anodic_range): #Eref->Eref+150mV\n",
    "            Ec -= scan_step\n",
    "            sol = fsolve(objective_f,sol, args=(self,Ec),xtol=1e-12)\n",
    "            sol_list.append(sol)\n",
    "            Eapp_list.append(Ec)\n",
    "\n",
    "            \n",
    "        # add solution to model\n",
    "        self.E1 = np.array([this[0]for this in sol_list])\n",
    "        self.E2 = np.array([this[1]for this in sol_list])\n",
    "        self.I1 = np.array([this[2]for this in sol_list])\n",
    "        self.I2 = np.array([this[3]for this in sol_list])\n",
    "        self.I1_e = np.array([this[4]for this in sol_list])\n",
    "        self.I2_e = np.array([this[5]for this in sol_list])\n",
    "        self.I0 = np.array([this[6]for this in sol_list])\n",
    "        \n",
    "        self.Eapp_list = np.array(Eapp_list)\n",
    "        self.Eref = -E_homo(self.E1,self.E2,self.A1,self.A2)\n",
    "        self.IRcomp = (self.I1_e+self.I2_e)*self.Re\n",
    "\n",
    "        residu = np.array([objective_f(sol_list[i],self,self.Eapp_list[i]) for i in range(len(self.Eapp_list))])\n",
    "        print 'total residual', np.sum(np.abs(residu))\n",
    "        if plot_residual:\n",
    "            plt.figure(figsize=(8,4))\n",
    "\n",
    "            for i in range(7):\n",
    "                r_obj = [r[i] for r in residu]\n",
    "                plt.plot(self.Eref,r_obj,'-',label=str(i))\n",
    "            plt.xlabel('$E_{ref}$ [V]')    \n",
    "            plt.title('residual')\n",
    "            plt.legend(['E1','E2','I1','I2','I1_e','I2_e','I0'])\n",
    "\n",
    "    def unpack_solution(self):\n",
    "        return (self.E1, self.E2,self.I1,self.I2,\n",
    "                self.I1_e, self.I2_e, self.I0,\n",
    "                self.Eapp_list,self.Eref, self.IRcomp)\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot function\n",
    "\n",
    "def potential_plot(model):\n",
    "    E1,E2,I1,I2,I1_e,I2_e,I0,Eapp_list, Eref,IRcomp = model.unpack_solution()\n",
    "    \n",
    "    plt.figure()\n",
    "    plt.plot(Eref,-E2,'C0',label='Passive unit potential, $E^{pas}$')\n",
    "    plt.plot(Eref,-E1,'C1',label='Active unit potential, $E^{act}$')\n",
    "    plt.plot(Eref,Eref,'C2',label='Homogenized rebar potential,$<E_{rebar}>$')\n",
    "    plt.plot(Eref,-Eapp_list,'C3',label='Concrete cover potential, $-\\phi_{app}$')\n",
    "    plt.plot(Eref,-(Eapp_list+IRcomp),':C3',label='Rebar potential with IRcomp, $E_{rebar}^{IRcomp}$',linewidth=2)\n",
    "\n",
    "    plt.xlabel('Homogenized rebar potential, [V]',fontsize=8)\n",
    "    plt.ylabel('Electrode potential [V]',fontsize=8)\n",
    "#     plt.axis('equal')\n",
    "    plt.legend(bbox_to_anchor=(1,1))\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "    \n",
    "def plot_cover_potential_subplot(model, title, subplot):\n",
    "    E1,E2,I1,I2,I1_e,I2_e,I0,Eapp_list, Eref,IRcomp = model.unpack_solution()\n",
    "    \n",
    "#     subplot.plot(Eref,-E2,'C0',label='Passive unit potential, $E^{pas}$')\n",
    "#     subplot.plot(Eref,-E1,'C1',label='Active unit potential, $E^{act}$')\n",
    "    subplot.plot(Eref,Eref,'C2',label='Homogenized rebar potential,$<E_{rebar}>$')\n",
    "    subplot.plot(Eref,-Eapp_list,'C3',label='Concrete cover potential, $-\\phi_{app}$')\n",
    "#     subplot.plot(Eref,-(Eapp_list+IRcomp),':C3',\n",
    "#                  label='Rebar potential with IRcomp, $E_{rebar}^{IRcomp}$',linewidth=2)\n",
    "\n",
    "#     subplot.set_xlabel('Homogenized rebar potential, [V]',fontsize=9)\n",
    "#     subplot.set_ylabel('Electrode potential [V]',fontsize=9)\n",
    "#     subplot.axis('equal')\n",
    "#     subplot.set_xlim((model.OCP-0.3,model.OCP+0.3))\n",
    "\n",
    "    subplot.xaxis.set_major_locator(ticker.MultipleLocator(0.2))\n",
    "#     subplot.xaxis.set_minor_locator(ticker.MultipleLocator(0.05))\n",
    "#     subplot.yaxis.set_major_locator(ticker.MultipleLocator(0.1))\n",
    "#     subplot.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    subplot.set_title(title,fontsize=10)\n",
    "    \n",
    "def plot_potential_subplot(model, title, subplot):\n",
    "    E1,E2,I1,I2,I1_e,I2_e,I0,Eapp_list, Eref,IRcomp = model.unpack_solution()\n",
    "    \n",
    "    subplot.plot(Eref,-E2,'C0',label='Passive unit potential, $E^{pas}$')\n",
    "    subplot.plot(Eref,-E1,'C1',label='Active unit potential, $E^{act}$')\n",
    "    subplot.plot(Eref,Eref,'C2',label='Homogenized rebar potential,$<E_{rebar}>$')\n",
    "#     subplot.plot(Eref,-Eapp_list,'C3',label='Concrete cover potential, $-\\phi_{app}$')\n",
    "    subplot.plot(Eref,-(Eapp_list+IRcomp),':C3',\n",
    "                 label='Rebar potential with IRcomp, $E_{rebar}^{IRcomp}$',linewidth=2)\n",
    "\n",
    "#     subplot.set_xlabel('Homogenized rebar potential, [V]',fontsize=9)\n",
    "#     subplot.set_ylabel('Electrode potential [V]',fontsize=9)\n",
    "#     subplot.axis('equal')\n",
    "#     subplot.set_xlim((model.OCP-0.3,model.OCP+0.3))\n",
    "\n",
    "    subplot.xaxis.set_major_locator(ticker.MultipleLocator(0.1))\n",
    "    subplot.xaxis.set_minor_locator(ticker.MultipleLocator(0.05))\n",
    "    subplot.yaxis.set_major_locator(ticker.MultipleLocator(0.1))\n",
    "    subplot.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    subplot.set_title(title,fontsize=10)\n",
    "    \n",
    "def plot_Ei_log_subplot(model,title,subplot):\n",
    "    E1,E2,I1,I2,I1_e,I2_e,I0,Eapp_list, Eref,IRcomp = model.unpack_solution()\n",
    "    AREA, A1, A2 = model.Area, model.A1, model.A2\n",
    "    \n",
    "    subplot.plot(np.abs(I1)/(AREA),Eref,'C1',label='Active unit, averaged over whole area')\n",
    "    subplot.plot(np.abs(I1)/(A1*AREA),-E1,'C1:',label='Active, localized')\n",
    "\n",
    "    subplot.plot(np.abs(I2)/(AREA),Eref,'C0',label='Active unit, averaged over whole area')\n",
    "    subplot.plot(np.abs(I2)/(A2*AREA),-E2,'C0:',label='Passive, localized')\n",
    "\n",
    "    subplot.plot(np.abs(I1+I2)/(AREA),Eref,'C2',alpha=1,label='Homogenized')\n",
    "\n",
    "    subplot.semilogx()\n",
    "#     subplot.set_xlabel('Current density $[A/m^2]$',fontsize=9)\n",
    "#     subplot.set_ylabel('Potential$[V]$',fontsize=9)\n",
    "    \n",
    "#     plt.legend(bbox_to_anchor=(1,1))\n",
    "    subplot.set_xlim([1e-5,1e1])\n",
    "    subplot.xaxis.set_major_locator(ticker.LogLocator(base=10.0, numticks=5))\n",
    "\n",
    "    #subplot.xaxis.set_minor_locator()\n",
    "\n",
    "    subplot.yaxis.set_major_locator(ticker.MultipleLocator(0.1))\n",
    "    subplot.yaxis.set_minor_locator(ticker.MultipleLocator(0.05))\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    subplot.set_title(title,fontsize=10)\n",
    "    \n",
    "def Ei_plot_log(model):\n",
    "    E1,E2,I1,I2,I1_e,I2_e,I0,Eapp_list, Eref,IRcomp = model.unpack_solution()\n",
    "    AREA, A1, A2 = model.Area, model.A1, model.A2\n",
    "\n",
    "    plt.figure()\n",
    "\n",
    "    plt.plot(np.abs(I1)/(AREA),Eref,'C1',label='activated, averaged over whole area')\n",
    "    plt.plot(np.abs(I1)/(A1*AREA),-E1,'C1:',label='activated, averaged over activated area')\n",
    "\n",
    "    plt.plot(np.abs(I2)/(AREA),Eref,'C0',label='passivated, averaged over whole area')\n",
    "    plt.plot(np.abs(I2)/(A2*AREA),-E2,'C0:',label='passivated, averaged over passivated area')\n",
    "\n",
    "    plt.plot(np.abs(I1+I2)/(AREA),Eref,'C2',alpha=1,label='Rebar overall')\n",
    "\n",
    "    plt.gca().semilogx()\n",
    "    plt.xlabel('Current density $[A/m^2]$')\n",
    "    plt.ylabel('Potential$[V]$')\n",
    "    plt.legend(bbox_to_anchor=(1,1))\n",
    "    plt.tight_layout()\n",
    "\n",
    "def Ei_plot_linear(model):\n",
    "    E1,E2,I1,I2,I1_e,I2_e,I0,Eapp_list, Eref,IRcomp = model.unpack_solution()\n",
    "    AREA, A1, A2 = model.Area, model.A1, model.A2\n",
    "\n",
    "    plt.figure()\n",
    "\n",
    "    plt.plot((I1)/(AREA),Eref,'C1',label='activated, averaged over whole area')\n",
    "    plt.plot((I1)/(A1*AREA),-E1,'C1:',label='activated, averaged over activated area')\n",
    "\n",
    "    plt.plot((I2)/(AREA),Eref,'C0',label='passivated, averaged over whole area')\n",
    "    plt.plot((I2)/(A2*AREA),-E2,'C0:',label='passivated, averaged over passivated area')\n",
    "\n",
    "    plt.plot((I1+I2)/(AREA),Eref,'C2',alpha=1,label='Rebar overall')\n",
    "\n",
    "\n",
    "    plt.xlabel('Current density $[A/m^2]$')\n",
    "    plt.ylabel('Potential$[V]$')\n",
    "    plt.legend(bbox_to_anchor=(1,1))\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R0 10000.0\n",
      "Re 10000.0\n"
     ]
    }
   ],
   "source": [
    "# Global var\n",
    "\n",
    "AREA = 1e-4 #m^2\n",
    "\n",
    "# more active\n",
    "par1 = corrparam(-0.650, 0.86e-2, 0.224, -0.260) \n",
    "# more passive\n",
    "par2 = corrparam(-0.2,0.05e-2, 0.505, -0.130)\n",
    "\n",
    "# area ratio \n",
    "A1 = 0.5\n",
    "A2 = 0.5\n",
    "# Resistance\n",
    "\n",
    "R0=10000.\n",
    "Re=10000.\n",
    "\n",
    "print 'R0',R0\n",
    "print 'Re',Re\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/gangli/anaconda2/lib/python2.7/site-packages/scipy/optimize/minpack.py:161: RuntimeWarning: The iteration is not making good progress, as measured by the \n",
      "  improvement from the last ten iterations.\n",
      "  warnings.warn(msg, RuntimeWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total residual 1.5031670659443836e-13\n"
     ]
    },
    {
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       "            }\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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Example\n",
    "model = model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=100, Re=10000)\n",
    "model.solve(cathodic_range=-0.300,anodic_range=0.300,scan_step=0.005,plot_residual=True)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "potential_plot(model)\n",
    "Ei_plot_log(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.4660788595782458\n",
      "0.027432139464796366\n"
     ]
    }
   ],
   "source": [
    "print model.OCP\n",
    "print model.icorr\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# parametric scan of Resistance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total residual 1.5151993657757377e-14\n",
      "total residual 1.0076858081402651e-13\n",
      "total residual 1.0316769037072334e-12\n",
      "total residual 2.83949401758518e-15\n",
      "total residual 6.7968680364270114e-15\n",
      "total residual 2.2462809709837293e-14\n",
      "total residual 2.6813250206561925e-15\n",
      "total residual 3.2000099187088174e-15\n",
      "total residual 4.0434028746864795e-15\n"
     ]
    }
   ],
   "source": [
    "# set senario\n",
    "model_list = [\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=10000., Re=10000.),\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=1000., Re=10000.),\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=100., Re=10000.),\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=10000., Re=1000.),\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=1000., Re=1000.),\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=100., Re=1000.),\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=10000., Re=100.),\n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=1000., Re=100.), \n",
    "              model_set(par1=par1, par2=par2 ,Area=AREA, A1=A1, A2=A2, R0=100., Re=100.),\n",
    "                ]\n",
    "comment_list = [\n",
    "              'Case 1', \n",
    "              'Case 2',\n",
    "              'Case 3',\n",
    "              'Case 4',\n",
    "              'Case 5', \n",
    "              'Case 6',\n",
    "              'Case 7',\n",
    "              'Case 8',\n",
    "              'Case 9',\n",
    "               ]\n",
    "\n",
    "for this_model, this_comment in zip(model_list,comment_list):\n",
    "    this_model.comment = this_comment\n",
    "\n",
    "\n",
    "# get solved model list\n",
    "for model in model_list:\n",
    "    model.solve(cathodic_range=-0.400,anodic_range=0.400,scan_step=0.01)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"1100\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.02,0.6,'Potential [V]')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# applied potential vs homogenized\n",
    "\n",
    "fig, subaxes = plt.subplots(1, 9, figsize=(11, 4),sharex=False, sharey=True)\n",
    "\n",
    "for this_model, this_axis in zip(model_list, subaxes.flatten()):\n",
    "    title = '{}\\nRe = {:.0f} $\\Omega$\\nR0 = {:.0f} $\\Omega$'.format(this_model.comment,this_model.Re, this_model.R0)\n",
    "    plot_cover_potential_subplot(this_model, title, subplot=this_axis)\n",
    "\n",
    "fig.legend(*this_axis.get_legend_handles_labels(), ncol=2, labelspacing=0.5,loc='lower center' ,fontsize=12)\n",
    "fig.tight_layout(pad=1.08, w_pad=0.6, h_pad=1.0)\n",
    "fig.subplots_adjust(left=0.06,bottom=0.25,hspace=0.5,wspace=0.2)\n",
    "fig.text(0.5, 0.15, 'Rebar potential with IR compensation [V]', ha='center',fontsize=10)\n",
    "fig.text(0.02, 0.6, 'Potential [V]', va='center', rotation='vertical')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"700\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.02,0.6,'Electrode potential [V]')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, subaxes = plt.subplots(3, 3, figsize=(7, 9),sharex=False, sharey=True)\n",
    "\n",
    "for this_model, this_axis in zip(model_list, subaxes.flatten()):\n",
    "    title = '{}\\nRe = {:.0f} $\\Omega$, R0 = {:.0f} $\\Omega$'.format(this_model.comment,this_model.Re, this_model.R0)\n",
    "    plot_potential_subplot(this_model, title, subplot=this_axis)\n",
    "\n",
    "fig.legend(*this_axis.get_legend_handles_labels(), ncol=2, labelspacing=0.5,loc='lower center' ,fontsize=8)\n",
    "fig.tight_layout(pad=1.08, w_pad=0.7, h_pad=0.7)\n",
    "fig.subplots_adjust(left=0.12,bottom=0.25,hspace=0.5,wspace=0.2)\n",
    "fig.text(0.5, 0.2, 'Homogenized rebar potential [V]', ha='center')\n",
    "fig.text(0.02, 0.6, 'Electrode potential [V]', va='center', rotation='vertical')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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"
    },
    {
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\" width=\"700\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.02,0.5,'Electrode potential [V]')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, subaxes = plt.subplots(3, 3, figsize=(7, 9),sharex=False, sharey=True)\n",
    "\n",
    "for this_model, this_axis in zip(model_list, subaxes.flatten()):\n",
    "    title = '{}\\nRe = {:.0f} $\\Omega$, R0 = {:.0f} $\\Omega$'.format(this_model.comment,this_model.Re, this_model.R0)\n",
    "    plot_Ei_log_subplot(this_model, title, subplot=this_axis)\n",
    "\n",
    "fig.legend(*this_axis.get_legend_handles_labels(), ncol=2, labelspacing=0.5,loc='lower center' ,fontsize=8)\n",
    "fig.tight_layout(pad=1.08, w_pad=0.7, h_pad=0.7)\n",
    "fig.subplots_adjust(left=0.12,bottom=0.25,hspace=0.5,wspace=0.2)\n",
    "\n",
    "fig.text(0.5, 0.10, 'Current density $[A/m^2]$', ha='center')\n",
    "fig.text(0.02, 0.5, 'Electrode potential [V]', va='center', rotation='vertical')\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}