Demo of my codes

delays analysis.ipynb

Eq-review.ipynb

{
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   "metadata": {
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   },
   "source": [
    "Loading dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "%matplotlib notebook\n",
    "import datetime\n",
    "import obspy\n",
    "from obspy.clients.fdsn import Client\n",
    "from imp import reload\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "This will add necessary method to obspy objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
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   "source": [
    "#import sys\n",
    "#sys.path.append(\"/Users/massin/Google Drive/Projects/NaiNo-Kami/Py/obspy_addons\")\n",
    "#import obspy_addons\n",
    "#reload(obspy_addons)\n",
    "#obspy.core.event.catalog.Catalog.plot_eventsections = obspy_addons.plot_eventsections\n",
    "#obspy.core.inventory.Inventory.hasdata = obspy_addons.hasdata\n",
    "#obspy.core.event.catalog.Catalog.evfind = obspy_addons.evfind\n",
    "#obspy.core.event.catalog.Catalog.plot_Mfirst = obspy_addons.plot_Mfirst\n",
    "#obspy.core.event.catalog.Catalog.plot_eew = obspy_addons.plot_eew\n",
    "\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.patheffects\n",
    "import numpy\n",
    "from math import radians, cos, sin, asin, sqrt\n",
    "def plot_Mfirst(self=obspy.core.event.catalog.Catalog()):\n",
    "    mags =          [e.magnitudes[-1].mag                        for e in self.events ]\n",
    "    profs =         [e.origins[-1].depth/1000.                   for e in self.events ]\n",
    "    mags_stations = [e.magnitudes[-1].station_count              for e in self.events ]\n",
    "    m1_errors =     [e.magnitudes[-1].mag-e.magnitudes[0].mag    for e in self.events ]\n",
    "    m1_types =      [e.magnitudes[0].magnitude_type              for e in self.events ]\n",
    "    m1_times =      [e.magnitudes[0].creation_info.creation_time for e in self.events ]\n",
    "    m1_origint =    [e.origins[-1].time                          for e in self.events ]\n",
    "    m1_delays = numpy.asarray(m1_times)-numpy.asarray(m1_origint)\n",
    "    \n",
    "    if len(mags) >0:\n",
    "        f, (ax) = matplotlib.pyplot.subplots(1, 1)\n",
    "        matplotlib.pyplot.ylabel('Error in first M')\n",
    "        matplotlib.pyplot.xlabel('Reference M')\n",
    "        matplotlib.pyplot.title('First M, with delays')\n",
    "        matplotlib.pyplot.grid()\n",
    "\n",
    "        for m in [min(mags_stations),numpy.median(mags_stations),max(mags_stations)]:\n",
    "            sc = ax.scatter(numpy.mean(mags), 0, \n",
    "                            (m-min(mags_stations)+1)/(max(mags_stations)-min(mags_stations))*500, \n",
    "                            'w', 'o', label=str(int(m))+' stat.',alpha=0.7 )\n",
    "\n",
    "        ax.axhline(0, linestyle='--', color='k') # horizontal lines\n",
    "\n",
    "        if len(m1_delays)<64:\n",
    "            for i, txt in enumerate(m1_delays):\n",
    "                ax.text(mags[i], m1_errors[i], str(int(txt))+'s', weight=\"heavy\",\n",
    "                        color=\"k\", zorder=100,\n",
    "                        path_effects=[\n",
    "                            matplotlib.patheffects.withStroke(linewidth=3,\n",
    "                                                   foreground=\"white\")])\n",
    "        types = ['M*','MLv','MVS']\n",
    "        for i,m in enumerate(['+','^','o']):\n",
    "            matches = [ j for j,t in enumerate(m1_types) if t == types[i] ]\n",
    "            if matches:\n",
    "                sc = ax.scatter([mags[j] for j in matches] , \n",
    "                                [m1_errors[j] for j in matches] , \n",
    "                                [(mags_stations[j]-min(mags_stations)+1)/(max(mags_stations)-min(mags_stations))*500 for j in matches] ,\n",
    "                                [profs[j] for j in matches], \n",
    "                                m, \n",
    "                                norm=matplotlib.colors.LogNorm(vmin=0.1, vmax=numpy.max(profs)),\n",
    "                                label=types[i],alpha=0.5,zorder=150,edgecolors='k')\n",
    "        cb=matplotlib.pyplot.colorbar(sc)\n",
    "        cb.set_label('Reference depth (km)')\n",
    "        lg = matplotlib.pyplot.legend()\n",
    "        lg.set_title('Marker & Sizes')\n",
    "        lg.get_frame().set_alpha(0.1)\n",
    "        lg.get_frame().set_color('k')\n",
    "        matplotlib.pyplot.axis('equal')\n",
    "        print(self)\n",
    "\n",
    "def plot_eew(self=obspy.core.event.catalog.Catalog()):\n",
    "    mags =          [e.magnitudes[-1].mag                        for e in self.events ]\n",
    "    profs =         [e.origins[-1].depth/1000.                   for e in self.events ]\n",
    "    mags_stations = [e.magnitudes[-1].station_count              for e in self.events ]\n",
    "    m1_errors =     [e.magnitudes[-1].mag-e.magnitudes[0].mag    for e in self.events ]\n",
    "    m1_types =      [e.magnitudes[0].magnitude_type              for e in self.events ]\n",
    "    m1_times =      [e.magnitudes[0].creation_info.creation_time for e in self.events ]\n",
    "    m1_origint =    [e.origins[-1].time                          for e in self.events ]\n",
    "    m1_delays = numpy.asarray(m1_times)-numpy.asarray(m1_origint)\n",
    "    \n",
    "    if len(mags) >0:\n",
    "        f, (ax1,ax2) = matplotlib.pyplot.subplots(2, 1, sharex=True)\n",
    "        ax1.set_ylabel('Error in location (km)')\n",
    "        ax2.set_ylabel('Error in magnitude')\n",
    "        ax1.set_xlabel('Time after origins (s)')\n",
    "        ax2.set_xlabel('Time after origins (s)')\n",
    "        ax2.set_xscale('log')\n",
    "        ax1.set_xscale('log')\n",
    "        ax1.set_yscale('log')\n",
    "        ax1.xaxis.set_label_position('top') \n",
    "        ax1.xaxis.set_ticks_position('top') \n",
    "        ax1.grid()\n",
    "        ax2.grid()\n",
    "\n",
    "\n",
    "        dmins=[]\n",
    "        for e in self.events:\n",
    "            for o in e.origins:\n",
    "                if len(o.arrivals)>0:\n",
    "                    dmins.append(numpy.min([a.distance for a in o.arrivals]))\n",
    "\n",
    "\n",
    "        for e in self.events:\n",
    "\n",
    "            el =  [numpy.sqrt(haversine(e.origins[-1].longitude,e.origins[-1].latitude,o.longitude,o.latitude)**2+(e.origins[-1].depth-o.depth)**2)/1000 for o in e.origins]\n",
    "            dtl = [o.creation_info.creation_time-e.origins[-1].time for o in e.origins]   \n",
    "\n",
    "            picks = e.picks.copy()\n",
    "            plist = []\n",
    "            for i,o in reversed(list(enumerate(e.origins))):\n",
    "                picks_creationtime = []\n",
    "                picks_time = []\n",
    "                picks_el = []\n",
    "                if i<len(e.origins):\n",
    "                    for a in o.arrivals:                 \n",
    "                        if a.time_weight < 4 : #abs(a.time_residual)<(a.distance)/5./3:\n",
    "                            for p in picks:\n",
    "                                if a.pick_id == p.resource_id and p.time-e.origins[-1].time > .5 and p.time not in plist and p.time>e.origins[-1].time:\n",
    "                                    picks_time.append(p.time-e.origins[-1].time)\n",
    "                                    picks_creationtime.append(p.creation_info.creation_time-e.origins[-1].time)\n",
    "                                    picks_el.append(el[i])\n",
    "                                    picks.remove(p)\n",
    "                                    plist.append(p.time)\n",
    "                                    break\n",
    "                    if len(picks_time)>1:\n",
    "                        ax1.scatter(picks_time,picks_el,10,\n",
    "                                    numpy.repeat(e.magnitudes[-1].mag,len(picks_el)),#marker='+',\n",
    "                                    norm=matplotlib.colors.PowerNorm(1,vmin=0.01, vmax=numpy.max(mags)),\n",
    "                                    zorder=-99,alpha=0.3, edgecolors='none')\n",
    "\n",
    "\n",
    "            ax1.scatter(dtl[:-1],el[:-1],10,marker='o',edgecolors='k') \n",
    "            sc1 = ax1.scatter(dtl[:-1],el[:-1],10,\n",
    "                        numpy.repeat(e.magnitudes[-1].mag,len(dtl)-1),marker='o',\n",
    "                        norm=matplotlib.colors.PowerNorm(1,vmin=0.01, vmax=numpy.max(mags)),\n",
    "                        label=e.short_str(),linewidths=0,zorder=999)\n",
    "\n",
    "\n",
    "            em =  [e.magnitudes[-1].mag-m.mag           for m in e.magnitudes]\n",
    "            dtm = [m.creation_info.creation_time-e.origins[-1].time for m in e.magnitudes]\n",
    "\n",
    "            ax2.scatter(dtm[:-1],em[:-1],10,marker='o',edgecolors='k')      \n",
    "            sc2 = ax2.scatter(dtm[:-1],em[:-1],10,\n",
    "                        numpy.repeat(e.magnitudes[-1].mag,len(dtm)-1),marker='o',\n",
    "                        norm=matplotlib.colors.PowerNorm(1,vmin=0.01, vmax=numpy.max(mags)),\n",
    "                        label=e.short_str(),linewidths=0,zorder=999)  \n",
    "\n",
    "        cb=matplotlib.pyplot.colorbar(sc1, ax=[ax1,ax2])\n",
    "        cb.set_label('Reference magnitude')\n",
    "        ob2 = ax2.scatter(20,0,10,marker='o',alpha=0.1,color='b', edgecolors='none',zorder=-999)\n",
    "        ob1 = ax2.scatter(20,0,10,marker='o',color='b',edgecolors='k',zorder=-999)\n",
    "        ax2.scatter(20,0,10,marker='o',color='w',edgecolors='w',linewidths=3,zorder=-99)\n",
    "        lg = matplotlib.pyplot.legend((ob1, ob2), ('Solutions (loc. or M)', 'Picks (t or A)'))\n",
    "\n",
    "def evfind(self=obspy.core.event.catalog.Catalog(),tofind=obspy.core.event.catalog.Catalog(),v=False,x=True):\n",
    "    \n",
    "    matchs = obspy.core.event.catalog.Catalog()\n",
    "    extras = obspy.core.event.catalog.Catalog()\n",
    "    matchs.description = 'Intersections of '+str(self.description)+' and '+str(tofind.description)\n",
    "    missed = obspy.core.event.catalog.Catalog()\n",
    "    missed.description = 'Part of '+str(self.description)+' not in '+str(tofind.description)\n",
    "    \n",
    "    for e in tofind.events:\n",
    "        o = e.preferred_origin() or e.origins[-1]\n",
    "        found=False     \n",
    "        if v:\n",
    "            print('---- event',e.short_str(),'...')\n",
    "        for ref in self.events: \n",
    "            refo = ref.preferred_origin() or ref.origins[-1]\n",
    "            if abs(o.time-refo.time) < 60 and abs(o.latitude-refo.latitude)<=.5 and abs(o.longitude-refo.longitude)<=.5: \n",
    "                found=True  \n",
    "                if v:\n",
    "                    print('fits input catalog ',tofind.description,':\\n  ', ref.short_str())                \n",
    "                matchs.events.append(ref)\n",
    "            \n",
    "            elif abs(o.time-refo.time) < 60 and abs(o.latitude-refo.latitude)<1 and abs(o.longitude-refo.longitude)<1: \n",
    "                found=True  \n",
    "                if v:\n",
    "                    print('poorly fits input catalog ',tofind.description,':\\n  ', ref.short_str())                \n",
    "                matchs.events.append(ref)\n",
    "                \n",
    "        if not found:\n",
    "            if v:\n",
    "                print('does not exist in current catalog')            \n",
    "            missed.events.append(e)\n",
    "    if x :\n",
    "        matchs_otherversion, extras, trash = tofind.evfind(self,v=v,x=False)\n",
    "    return matchs, missed, extras\n",
    "\n",
    "def hasdata(self,data=obspy.core.stream.Stream()):\n",
    "    inv_ok = obspy.core.inventory.Inventory(networks=[],source=[])\n",
    "    inv_dead = obspy.core.inventory.Inventory(networks=[],source=[])\n",
    "    l = []\n",
    "    ld = []\n",
    "    for t in data.traces:\n",
    "        if t.stats.network+t.stats.station not in l:\n",
    "            toadd = self.select(network=t.stats.network,station=t.stats.station)\n",
    "            if len(toadd.networks) >0:\n",
    "                found = False\n",
    "                for n in inv_ok.networks:\n",
    "                    if n.code == t.stats.network:\n",
    "                        n.stations.append(toadd.networks[0].stations[0])\n",
    "                        found = True\n",
    "                if not found:\n",
    "                    inv_ok.__iadd__(toadd)\n",
    "                l.append(t.stats.network+t.stats.station)\n",
    "        for n in self.networks:\n",
    "            for s in n.stations:\n",
    "                code = str(n.code)+str(s.code)\n",
    "                if code not in l and code not in ld:\n",
    "                    toadd = self.select(network=str(n.code),station=str(s.code))\n",
    "                    if len(toadd.networks) > 0:\n",
    "                        found = False\n",
    "                        for nd in inv_dead.networks:\n",
    "                            if str(nd.code) == str(n.code):\n",
    "                                nd.stations.append(toadd.networks[0].stations[0])\n",
    "                                found = True\n",
    "                        if not found:\n",
    "                            inv_dead.__iadd__(toadd)\n",
    "                        ld.append(code)\n",
    "                    \n",
    "    return inv_ok, inv_dead\n",
    "\n",
    "def plot_eventsections(self, client_wf, afterpick = 30):\n",
    "        \n",
    "    for e in self:\n",
    "        \n",
    "        pmax = max([p.time for p in e.picks])\n",
    "        \n",
    "        picks = []\n",
    "        arrivals = [] \n",
    "        st = obspy.core.stream.Stream()\n",
    "        o = e.preferred_origin() or e.origins[-1]\n",
    "        for p in e.picks:\n",
    "            try:\n",
    "                toadd = client_wf.get_waveforms(p.waveform_id.network_code,\n",
    "                                                p.waveform_id.station_code,\n",
    "                                                p.waveform_id.location_code,\n",
    "                                                p.waveform_id.channel_code,\n",
    "                                                starttime = o.time,\n",
    "                                                endtime = pmax+afterpick )\n",
    "            except:\n",
    "                toadd = obspy.core.stream.Stream()\n",
    "                \n",
    "            for t in toadd:\n",
    "                found=False\n",
    "                for a in o.arrivals:\n",
    "                    if a.pick_id == p.resource_id:\n",
    "                        t.stats.distance = a.distance*11000.   \n",
    "                        picks.append(p)\n",
    "                        arrivals.append(a)\n",
    "                        found=True\n",
    "                if not found:\n",
    "                    toadd.remove(t)\n",
    "                    \n",
    "            st += toadd\n",
    "        if len(st)>0:\n",
    "            st.detrend()\n",
    "            tmp=st.slice(starttime=o.time, endtime=pmax+afterpick ) \n",
    "            tmp.merge(method=1)\n",
    "            \n",
    "            fig = matplotlib.pyplot.figure()\n",
    "            tmp.plot(type='section', # starttime=o.time-10,\n",
    "                     reftime=o.time,\n",
    "                     time_down=True,\n",
    "                     linewidth=.25,\n",
    "                     grid_linewidth=.25,                  \n",
    "                     show=False, \n",
    "                     fig=fig,\n",
    "                     color='network')\n",
    "            ax = matplotlib.pyplot.gca()\n",
    "            transform = matplotlib.transforms.blended_transform_factory(ax.transData, ax.transAxes)\n",
    "            transform_picks = matplotlib.transforms.blended_transform_factory(ax.transData, ax.transData)\n",
    "            for i,tr in enumerate(st):\n",
    "                ax.text(tr.stats.distance / 1e3, 1.0, tr.stats.station, rotation=270,\n",
    "                        va=\"bottom\", ha=\"center\", transform=transform, zorder=10)\n",
    "                ax.plot(tr.stats.distance / 1e3,\n",
    "                        picks[i].time - o.time, \n",
    "                        '+k',\n",
    "                        transform=transform_picks,\n",
    "                        zorder=10)\n",
    "                ax.text(tr.stats.distance / 1e3,\n",
    "                        picks[i].time - o.time,\n",
    "                        str(picks[i].phase_hint), \n",
    "                        weight=\"heavy\",\n",
    "                        color=\"k\", \n",
    "                        horizontalalignment='right',\n",
    "                        verticalalignment='bottom',\n",
    "                        zorder=20,\n",
    "                        path_effects=[matplotlib.patheffects.withStroke(linewidth=3,\n",
    "                                                                        foreground=\"white\")])\n",
    "\n",
    "            l = ax.get_legend()    \n",
    "            la = [ text.get_text() for text in l.get_texts()]\n",
    "            [line.set_linewidth(3) for line in l.get_lines()]\n",
    "            li = l.get_lines()\n",
    "            l.remove()\n",
    "            l = ax.legend(li,la,ncol=7,prop={'size':6},title=e.short_str()+' \\n '+str(e.resource_id))\n",
    "            l.get_title().set_fontsize('6')\n",
    "            ax.set_ylabel('Time after origin [s]')\n",
    "\n",
    "def haversine(lon1, lat1, lon2, lat2):\n",
    "    \"\"\"\n",
    "    Calculate the great circle distance between two points \n",
    "    on the earth (specified in decimal degrees)\n",
    "    \"\"\"\n",
    "    # convert decimal degrees to radians \n",
    "    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])\n",
    "\n",
    "    # haversine formula \n",
    "    dlon = lon2 - lon1 \n",
    "    dlat = lat2 - lat1 \n",
    "    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2\n",
    "    c = 2 * asin(sqrt(a)) \n",
    "    r = 6371000 # Radius of earth in meters. Use 3956 for miles\n",
    "    return c * r \n",
    "\n",
    "obspy.core.event.catalog.Catalog.plot_eventsections = plot_eventsections\n",
    "obspy.core.inventory.Inventory.hasdata = hasdata\n",
    "obspy.core.event.catalog.Catalog.evfind = evfind\n",
    "obspy.core.event.catalog.Catalog.plot_Mfirst = plot_Mfirst\n",
    "obspy.core.event.catalog.Catalog.plot_eew = plot_eew"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Loading parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "client_eew = Client('http://localhost:18080')\n",
    "client_eq = Client('http://165.98.224.52:8081')\n",
    "#client_wf = Client('http://165.98.224.59:8081')\n",
    "client = Client('IRIS')\n",
    "\n",
    "N=[14,15]\n",
    "minM = 4.9\n",
    "lon=[-95,-80]\n",
    "lat=[10,15]\n",
    "net='NU'\n",
    "end = (datetime.datetime.now()-datetime.timedelta(days=N[0])).isoformat()\n",
    "start = (datetime.datetime.now()-datetime.timedelta(days=sum(N))).isoformat()\n",
    "endsample = (datetime.datetime.now()-datetime.timedelta(days=sum(N))+datetime.timedelta(seconds=1)).isoformat()\n",
    "\n",
    "eq_specs = {'starttime':start,\n",
    "            'endtime':end,\n",
    "            'minlatitude':lat[0],\n",
    "            'maxlatitude':lat[1],\n",
    "            'minlongitude':lon[0],\n",
    "            'maxlongitude':lon[1],\n",
    "            'orderby':'magnitude-asc',\n",
    "            'includearrivals':True}\n",
    "\n",
    "lq_specs = {'starttime':start,\n",
    "            'endtime':end,\n",
    "            'minlatitude':lat[0]-1,\n",
    "            'maxlatitude':lat[1]+1,\n",
    "            'minlongitude':lon[0]-1,\n",
    "            'maxlongitude':lon[1]+1,\n",
    "            'orderby':'magnitude-asc',\n",
    "            'includearrivals':True}\n",
    "\n",
    "eew_specs = eq_specs.copy()\n",
    "eew_specs['includeallorigins']=True\n",
    "eew_specs['includeallmagnitudes']=True\n",
    "\n",
    "sta_specs = {'starttime':start,\n",
    "             'endtime':end,\n",
    "             'minlatitude':lat[0],\n",
    "             'maxlatitude':lat[1],\n",
    "             'minlongitude':lon[0],\n",
    "             'maxlongitude':lon[1],\n",
    "             'level':'station'}\n",
    "\n",
    "sta_eqspecs = {'starttime':start,\n",
    "               'endtime':end,\n",
    "               'level':'station'}\n",
    "\n",
    "map_specs={'projection':'local','resolution':'i','color_per_network':True}\n",
    "\n",
    "# ssh -N -L 18080:localhost:8080  sysop@165.98.224.44"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "0862bd46-fa1e-4471-bfe6-eb8a09051fba"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Review of the earthquake early warning system for the N days. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "bba41df5-322a-462a-ae2b-c209005ce7fb"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N: [14, 15]\n",
      "into area [10, 15]°N [-95, -80]°E\n",
      "from 2017-02-13T08:33:56.113917\n",
      "  to 2017-02-28T08:33:56.113678\n",
      "for network NU.\n"
     ]
    }
   ],
   "source": [
    "print('N: %s' % str(N))\n",
    "print('into area %s°N %s°E' % (str(lat), str(lon)))\n",
    "print(\"from %s\" % start )\n",
    "print(\"  to %s\" % end )\n",
    "print('for network %s.' % net)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "e0700f9e-845c-4def-afd5-f506f9dc4a5b"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## INETER observations\n",
    "### Available network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "6a80637e-3815-4cf0-82ef-500f1826e7b7"
    },
    "scrolled": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
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      ]
     },
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     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inventory created at 2017-03-14T07:25:32.000000Z\n",
      "\tSending institution: SeisComP3 (INETER)\n",
      "\tContains:\n",
      "\t\tNetworks (1):\n",
      "\t\t\tNU\n",
      "\t\tStations (103):\n",
      "\t\t\tNU.AAHN (Alcaldia de Achuapa)\n",
      "\t\t\tNU.ABCN (SMA Banco Central, Nicaragua)\n",
      "\t\t\tNU.ACBN (SMA Campo Bello, Nicaragua)\n",
      "\t\t\tNU.ACON (Acoyapa, Nicaragua)\n",
      "\t\t\tNU.ACSN (SMA Ciudad Sandino, Nicaragua)\n",
      "\t\t\tNU.ADRN (SMA Diriamba, Nicaragua)\n",
      "\t\t\tNU.AERN (SMA Aeropuerto Managua, Nicaragua)\n",
      "\t\t\tNU.AESN (EL SAUCE LEON)\n",
      "\t\t\tNU.ALEN (SMA Leon, Nicaragua)\n",
      "\t\t\tNU.ALLN (SMA Telcor Managua, Nicaragua)\n",
      "\t\t\tNU.ALTN (Altagracia, Isla de ometepe)\n",
      "\t\t\tNU.AMTN (SMA Mateare, Nicaragua)\n",
      "\t\t\tNU.AMYN (SMA CODE Masaya, Nicaragua)\n",
      "\t\t\tNU.APQ2 (Apoyeque, Nicaragua)\n",
      "\t\t\tNU.APQ3 (Volcan Apoyeque sitio 3, Nicaragua)\n",
      "\t\t\tNU.APQ4 (Volcan Apoyeque sitio 4, Nicaragua)\n",
      "\t\t\tNU.APQ5 (Volcan Apoyeque sitio 5, Nicaragua)\n",
      "\t\t\tNU.APQN (BB Volcan Apoyeque, Nicaragua)\n",
      "\t\t\tNU.APYN (Volcan Apoyeque)\n",
      "\t\t\tNU.ARIN (SMA Rivas, Nicaragua)\n",
      "\t\t\tNU.AZCN (Norte del Volcan Masaya)\n",
      "\t\t\tNU.BC84 (SMA Volcan Momotombo, Nicaragua)\n",
      "\t\t\tNU.BC86 (SMA Nagarote, Nicaragua)\n",
      "\t\t\tNU.BC87 (SMA San Francisco Libre, Nicaragua)\n",
      "\t\t\tNU.BC8A (SMA INETER, Nicaragua)\n",
      "\t\t\tNU.BILN (EQUIPO DE PRUEBA EN INETER)\n",
      "\t\t\tNU.BLUN (Bluefields, Entresa, Nicaragua)\n",
      "\t\t\tNU.BRAN (ENATREL Los Brasiles)\n",
      "\t\t\tNU.CHNN (SMA Chinadega, Nnicaragua)\n",
      "\t\t\tNU.CNGA (Al SSO del Volcan Cerro Negro)\n",
      "\t\t\tNU.CNGN (Volcan Cerro Negro, Nicaragua)\n",
      "\t\t\tNU.CONN (Central Sismica - INETER)\n",
      "\t\t\tNU.COPN (Copaltepe)\n",
      "\t\t\tNU.CPAN (SMA Conchita Palacios, Nicaragua)\n",
      "\t\t\tNU.CRIN (volcan San Cristobal, Nicaragua)\n",
      "\t\t\tNU.CRUN (El Crucero)\n",
      "\t\t\tNU.CSAN (BB Ciudad Sandino, Nicaragua)\n",
      "\t\t\tNU.CSGN (COSIGUINA)\n",
      "\t\t\tNU.DECN (SMA CODE-SINAPRED Managua, Nicaragua)\n",
      "\t\t\tNU.ENAN (SMA ENATREL Managua, Nicaragua)\n",
      "\t\t\tNU.ESPN (Las Esperanzas, Nicaragua)\n",
      "\t\t\tNU.ESTN (Esteli, Nicaragua)\n",
      "\t\t\tNU.GRNN (SMA Granada, Nicaragua)\n",
      "\t\t\tNU.HB11 (Al NO del Volcan Momotombo)\n",
      "\t\t\tNU.HERN (Volcan Telica, Nicaragua)\n",
      "\t\t\tNU.HM03 (Oeste Volcan Momotombo)\n",
      "\t\t\tNU.HOYN (Al Sur del Volcan Telica)\n",
      "\t\t\tNU.HUEN (BB Puenta Huete, Nicaragua)\n",
      "\t\t\tNU.HUGN (San Franciso LIbre, San Jeronimo)\n",
      "\t\t\tNU.ICAN (Isla Campuzano)\n",
      "\t\t\tNU.ILCN (San Idelfonso, Volcan Cerro Negro)\n",
      "\t\t\tNU.INE2 (INETER, Estacion de Prueba)\n",
      "\t\t\tNU.JAPN (Al SSO del Volcan Masaya)\n",
      "\t\t\tNU.LEVN (Ruinas Leon Viejo, Nicaragua)\n",
      "\t\t\tNU.LIMN (Finca el Limon)\n",
      "\t\t\tNU.MAC2 (El Madrono, SAT Cerro Negro 2)\n",
      "\t\t\tNU.MACN (El Madrono, SAT Cerro Negro)\n",
      "\t\t\tNU.MAFN (Magfor)\n",
      "\t\t\tNU.MAFN (SMA MAGFOR Managua, Nicaragua)\n",
      "\t\t\tNU.MAS3 (Al N del Volcan Masaya)\n",
      "\t\t\tNU.MASN (Volcan Masaya, Nicaragua)\n",
      "\t\t\tNU.MATN (Matagalpa City, Nicaragua)\n",
      "\t\t\tNU.MGAN (Managua, Nicaragua)\n",
      "\t\t\tNU.MIRN (Asentamiento de Miramar)\n",
      "\t\t\tNU.MOM1 (Volcan Momotombo, Nicaragua)\n",
      "\t\t\tNU.MOM2 (El cardon, Momotombo, NIcaragua)\n",
      "\t\t\tNU.MOM3 (MOM3)\n",
      "\t\t\tNU.MOMN (al SSO del Volcan Momtombo)\n",
      "\t\t\tNU.MORN (Al O del Volcan Concepcion)\n",
      "\t\t\tNU.MSHP (Al O del Volcan Concepcion)\n",
      "\t\t\tNU.NADN (ENATREL Nandaime)\n",
      "\t\t\tNU.NANN (Nandasmo, Nicaragua)\n",
      "\t\t\tNU.OCON (Estacion meteorologica de Ocatal)\n",
      "\t\t\tNU.OMEN (Al SSO del Volcan Concepcion)\n",
      "\t\t\tNU.PACN (Al O del Volcan Cerro Negro)\n",
      "\t\t\tNU.PLMN (La Palma, Nicaragua)\n",
      "\t\t\tNU.PLRN (Al O del Volcan Concepcion)\n",
      "\t\t\tNU.PMON (Puerto Morazan)\n",
      "\t\t\tNU.POLN (Al Sur del Volcan Telica)\n",
      "\t\t\tNU.POZN (Al N del Volcan Momotombo)\n",
      "\t\t\tNU.QUEN (Al S del Volcan Telica)\n",
      "\t\t\tNU.RCFN (Al S de San Juan del Rio Coco)\n",
      "\t\t\tNU.RCON (San Jose del Ojoche, San Juan de Rio Coco, Nicaragua)\n",
      "\t\t\tNU.RCPN (Sur Rio San Juan del Rio Coco)\n",
      "\t\t\tNU.RCVN (varillal2)\n",
      "\t\t\tNU.ROCN (ROTA CERRO NEGRO)\n",
      "\t\t\tNU.SABN (Asentamiento de Miramar)\n",
      "\t\t\tNU.SAPN (BB Ciudad Sandino San Andres de las Palancas, Nicaragua)\n",
      "\t\t\tNU.SBEN (SMA San Benito, Nicaragua)\n",
      "\t\t\tNU.SIUN (SIUNA)\n",
      "\t\t\tNU.SIX1 (Esquipula temporal)\n",
      "\t\t\tNU.SIX9 (Prueba central sismica)\n",
      "\t\t\tNU.SIXTM (Santiago Volcan (SANN))\n",
      "\t\t\tNU.SJON (San Jose del Obraje)\n",
      "\t\t\tNU.SOMN (Somoto, Nicaragua)\n",
      "\t\t\tNU.TEL3 (Al SSE del Volcan Telica)\n",
      "\t\t\tNU.TELN (Al E del Volcan Telica)\n",
      "\t\t\tNU.TIPN (SMA Tipitapa, Nicaragua)\n",
      "\t\t\tNU.TISN (Estado Mayor, Ejercito Nacional)\n",
      "\t\t\tNU.UBNT (Urbait 2, Isla de Ometepe)\n",
      "\t\t\tNU.USIN (SMA UNAN Managua)\n",
      "\t\t\tNU.WILN (Casa de Wilfried Americas Dos, Nicaragua)\n",
      "\t\t\tNU.XILN (SMA Xiloa, Nicaragua)\n",
      "\t\tChannels (0):\n",
      "\n"
     ]
    }
   ],
   "source": [
    "inventory = client_eq.get_stations( **sta_specs )\n",
    "inventory.plot( **map_specs )\n",
    "print( inventory.select( network = net ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "###  Network with data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inventory created at 2017-03-14T07:28:57.731290Z\n",
      "\tCreated by: ObsPy 1.0.3\n",
      "\t\t    https://www.obspy.org\n",
      "\tSending institution: SeisComP3 (INETER)\n",
      "\tContains:\n",
      "\t\tNetworks (1):\n",
      "\t\t\tNU\n",
      "\t\tStations (58):\n",
      "\t\t\tNU.ABCN (SMA Banco Central, Nicaragua)\n",
      "\t\t\tNU.ACON (Acoyapa, Nicaragua)\n",
      "\t\t\tNU.ADRN (SMA Diriamba, Nicaragua)\n",
      "\t\t\tNU.AERN (SMA Aeropuerto Managua, Nicaragua)\n",
      "\t\t\tNU.AESN (EL SAUCE LEON)\n",
      "\t\t\tNU.ALLN (SMA Telcor Managua, Nicaragua)\n",
      "\t\t\tNU.AMTN (SMA Mateare, Nicaragua)\n",
      "\t\t\tNU.AMYN (SMA CODE Masaya, Nicaragua)\n",
      "\t\t\tNU.APQ2 (Apoyeque, Nicaragua)\n",
      "\t\t\tNU.APQ3 (Volcan Apoyeque sitio 3, Nicaragua)\n",
      "\t\t\tNU.ARIN (SMA Rivas, Nicaragua)\n",
      "\t\t\tNU.BC84 (SMA Volcan Momotombo, Nicaragua)\n",
      "\t\t\tNU.BC87 (SMA San Francisco Libre, Nicaragua)\n",
      "\t\t\tNU.BC8A (SMA INETER, Nicaragua)\n",
      "\t\t\tNU.BLUN (Bluefields, Entresa, Nicaragua)\n",
      "\t\t\tNU.CHNN (SMA Chinadega, Nnicaragua)\n",
      "\t\t\tNU.CNGA (Al SSO del Volcan Cerro Negro)\n",
      "\t\t\tNU.CNGN (Volcan Cerro Negro, Nicaragua)\n",
      "\t\t\tNU.CONN (Central Sismica - INETER)\n",
      "\t\t\tNU.COPN (Copaltepe)\n",
      "\t\t\tNU.CRIN (volcan San Cristobal, Nicaragua)\n",
      "\t\t\tNU.CRUN (El Crucero)\n",
      "\t\t\tNU.DECN (SMA CODE-SINAPRED Managua, Nicaragua)\n",
      "\t\t\tNU.ENAN (SMA ENATREL Managua, Nicaragua)\n",
      "\t\t\tNU.ESPN (Las Esperanzas, Nicaragua)\n",
      "\t\t\tNU.HERN (Volcan Telica, Nicaragua)\n",
      "\t\t\tNU.HUEN (BB Puenta Huete, Nicaragua)\n",
      "\t\t\tNU.ILCN (San Idelfonso, Volcan Cerro Negro)\n",
      "\t\t\tNU.JAPN (Al SSO del Volcan Masaya)\n",
      "\t\t\tNU.LIMN (Finca el Limon)\n",
      "\t\t\tNU.MACN (El Madrono, SAT Cerro Negro)\n",
      "\t\t\tNU.MAFN (SMA MAGFOR Managua, Nicaragua)\n",
      "\t\t\tNU.MAS3 (Al N del Volcan Masaya)\n",
      "\t\t\tNU.MASN (Volcan Masaya, Nicaragua)\n",
      "\t\t\tNU.MATN (Matagalpa City, Nicaragua)\n",
      "\t\t\tNU.MGAN (Managua, Nicaragua)\n",
      "\t\t\tNU.MOM1 (Volcan Momotombo, Nicaragua)\n",
      "\t\t\tNU.MOM3 (MOM3)\n",
      "\t\t\tNU.MOMN (al SSO del Volcan Momtombo)\n",
      "\t\t\tNU.MORN (Al O del Volcan Concepcion)\n",
      "\t\t\tNU.MSHP (Al O del Volcan Concepcion)\n",
      "\t\t\tNU.NADN (ENATREL Nandaime)\n",
      "\t\t\tNU.NANN (Nandasmo, Nicaragua)\n",
      "\t\t\tNU.OCON (Estacion meteorologica de Ocatal)\n",
      "\t\t\tNU.OMEN (Al SSO del Volcan Concepcion)\n",
      "\t\t\tNU.PACN (Al O del Volcan Cerro Negro)\n",
      "\t\t\tNU.PLRN (Al O del Volcan Concepcion)\n",
      "\t\t\tNU.PMON (Puerto Morazan)\n",
      "\t\t\tNU.POLN (Al Sur del Volcan Telica)\n",
      "\t\t\tNU.RCON (San Jose del Ojoche, San Juan de Rio Coco, Nicaragua)\n",
      "\t\t\tNU.RCPN (Sur Rio San Juan del Rio Coco)\n",
      "\t\t\tNU.RCVN (varillal2)\n",
      "\t\t\tNU.ROCN (ROTA CERRO NEGRO)\n",
      "\t\t\tNU.TEL3 (Al SSE del Volcan Telica)\n",
      "\t\t\tNU.TELN (Al E del Volcan Telica)\n",
      "\t\t\tNU.TIPN (SMA Tipitapa, Nicaragua)\n",
      "\t\t\tNU.TISN (Estado Mayor, Ejercito Nacional)\n",
      "\t\t\tNU.WILN (Casa de Wilfried Americas Dos, Nicaragua)\n",
      "\t\tChannels (0):\n",
      "\n"
     ]
    }
   ],
   "source": [
    "samples = client_eq.get_waveforms( '*', '*', '*', '*Z', start, endsample ) \n",
    "inventory_ok, inventory_dead = inventory.hasdata( samples ) \n",
    "inventory_ok.plot( **map_specs ) if len(inventory_ok.networks)>0 else None\n",
    "print(inventory_ok.select( network=net ))\n",
    "#inventory_dead.plot( **map_specs ) if len(inventory_ok.networks)>0 else None\n",
    "#print(inventory_dead.select( network=net ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "39acdc9d-9d7a-4c6b-b1b9-164262d0b057"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observed earthquakes\n",
    "In main earthquake authoritative location system, say **EAL**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "8fd37f6b-405c-49ef-93fb-2b94f78fab2f"
    },
    "scrolled": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "83 Event(s) in Catalog:\n",
      "2017-02-23T11:27:27.298881Z | +12.447,  -86.651 | 1.638089285 M  | manual\n",
      "2017-02-23T06:56:31.334140Z | +12.063,  -86.607 | 1.681117139 M  | manual\n",
      "...\n",
      "2017-02-24T13:41:11.509563Z | +12.487,  -87.841 | 5.328495115 M  | manual\n",
      "2017-02-21T07:15:14.338108Z | +14.613,  -89.548 | 6.184471105 M  | manual\n",
      "To see all events call 'print(CatalogObject.__str__(print_all=True))'\n"
     ]
    }
   ],
   "source": [
    "cat = client_eq.get_events( **eq_specs )\n",
    "cat.plot( **map_specs ) if len(cat)>0 else None\n",
    "print( cat )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "7a43a77a-a1df-466f-ad65-68e98ec897eb"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### The most important earthquakes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "c8f08ad9-71e9-4302-a8ff-45e182ed09bc"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12 Event(s) in Catalog:\n",
      "2017-02-22T22:10:52.931751Z | +11.083,  -86.416 | 4.519285499 M  | automatic\n",
      "2017-02-17T18:20:49.774332Z | +11.819,  -85.549 | 4.54102991 M  | automatic\n",
      "...\n",
      "2017-02-24T13:41:11.509563Z | +12.487,  -87.841 | 5.328495115 M  | manual\n",
      "2017-02-21T07:15:14.338108Z | +14.613,  -89.548 | 6.184471105 M  | manual\n",
      "To see all events call 'print(CatalogObject.__str__(print_all=True))'\n"
     ]
    }
   ],
   "source": [
    "subcat = cat.filter( \"magnitude >= 4.5\" )\n",
    "subcat.plot( **map_specs )\n",
    "print( subcat )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Global observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9 Event(s) in Catalog:\n",
      "2017-02-25T17:58:36.610000Z | +14.810,  -93.835 | 4.1 mb\n",
      "2017-02-27T21:07:14.120000Z | +14.024,  -91.567 | 4.4 mb\n",
      "2017-02-18T23:31:18.220000Z | +13.902,  -91.994 | 4.5 mb\n",
      "2017-02-16T21:48:30.290000Z | +13.536,  -91.454 | 4.5 mb\n",
      "2017-02-23T15:16:12.160000Z | +12.190,  -88.130 | 4.6 mb\n",
      "2017-02-13T20:41:25.190000Z | +15.751,  -94.016 | 4.7 mb\n",
      "2017-02-15T02:47:38.200000Z | +12.152,  -88.276 | 4.8 mb\n",
      "2017-02-24T13:41:14.840000Z | +12.596,  -87.826 | 4.9 mb\n",
      "2017-02-16T13:33:42.450000Z | +14.496,  -90.552 | 4.9 mb\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    cat_glob = client.get_events( **lq_specs ) \n",
    "except:\n",
    "    cat_glob = obspy.core.event.catalog.Catalog()\n",
    "cat_glob.description = 'Global' if len(cat_glob)>0 else None\n",
    "cat_glob.plot( **map_specs ) if len(cat_glob)>0 else None\n",
    "print( cat_glob )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Is something missing in EAL?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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

obspy demonstrating trigger2.ipynb