process_wrf_data.ipynb

{
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   "execution_count": 2,
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   },
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   "source": [
    "# Import a bunch of python sub packages\n",
    "import matplotlib.image as mpimg\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import xray\n",
    "import xray.ufuncs as xu\n",
    "import dask\n",
    "import seaborn as sn\n",
    "from datetime import datetime\n",
    "from dask.diagnostics import ProgressBar\n",
    "import warnings\n",
    "import os\n",
    "\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Mo1_2013-11.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-07.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-08.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-09.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-10.nc']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a file list of all the netCDF files\n",
    "import glob\n",
    "fileList = glob.glob('/Users/carina/desktop/WRF_data/*.nc')\n",
    "fileList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# This cell converts concatenates the netCDF files and creates new ones that are better organized\n",
    "\n",
    "# Create a function that will take the way the time is stored as a variable in the \n",
    "# WRF netCDF files and decode it\n",
    "# Build a function to go from numpy.bytes_ to a string - WRF files were compressed\n",
    "def decode(d):\n",
    "    decoded = datetime.strptime(d.decode(encoding='UTF-8'),  \"%Y-%m-%d_%H:%M:%S\")\n",
    "    return decoded\n",
    "\n",
    "first = True # create a boolean for the loop below\n",
    "\n",
    "\n",
    "# Stores the creates a new netCDF files with coordinat\n",
    "for file in fileList:\n",
    "    if first:      \n",
    "        ds = xray.open_dataset(file , engine = 'netcdf4') # may not need enginer = 'netcdf4' others are using engine = 'scipy'\n",
    "        dates = ds.Times.to_series().apply(decode) # this creates a list of the varaibles Times in the netCDF file ds and then applies the decode function to each element\n",
    "        dsTotal = xray.Dataset({'prec': (['time','x','y'], ds.prehourly.values),\n",
    "                      'temp2m':(['time','x','y'], ds.t2.values)},\n",
    "                       coords = {'longitude': (['x','y'], ds.lon.values),\n",
    "                              'latitude': (['x','y'], ds.lat.values),\n",
    "                              'time': xray.DataArray.from_series(dates).values})\n",
    "                # first the prec and temp2m variables are created\n",
    "                # then we add coordinates\n",
    "        \n",
    "    \n",
    "        first = False # now that new 'clean' netCDF file is created switch the boolean operator so the below is run and we finally concatenate\n",
    "    \n",
    "    # the rest does the same as above but concatenates the end\n",
    "    else:\n",
    "        ds = xray.open_dataset(file, engine = 'netcdf4' )\n",
    "        dates = ds.Times.to_series().apply(decode)\n",
    "        dsTemp = xray.Dataset({'prec': (['time','x','y'], ds.prehourly.values),\n",
    "                      'temp2m':(['time','x','y'], ds.t2.values)},\n",
    "                       coords = {'longitude': (['x','y'], ds.lon.values),\n",
    "                              'latitude': (['x','y'], ds.lat.values),\n",
    "                              'time': xray.DataArray.from_series(dates).values})\n",
    "        \n",
    "        dsTotal = xray.concat([dsTotal, dsTemp], dim = 'time') # this is concatenating\n",
    "\n",
    "        \n",
    "# add attributes to the netCDF\n",
    "dsTotal.attrs['prec'] = 'Precipitation Hourly [mm]'\n",
    "dsTotal.attrs['temp2m'] = 'Two Meter Temperature [deg K]'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xray.Dataset>\n",
       "Dimensions:    (time: 3672, x: 180, y: 150)\n",
       "Coordinates:\n",
       "    latitude   (x, y) float32 32.5872 32.588 32.5887 32.5894 32.5901 32.5907 ...\n",
       "    longitude  (x, y) float32 -125.395 -125.331 -125.267 -125.203 -125.139 ...\n",
       "  * x          (x) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ...\n",
       "  * y          (y) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ...\n",
       "  * time       (time) datetime64[ns] 2013-11-01 2013-11-01T01:00:00 ...\n",
       "Data variables:\n",
       "    temp2m     (time, x, y) float32 290.044 290.06 290.073 290.095 290.122 ...\n",
       "    prec       (time, x, y) float32 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n",
       "Attributes:\n",
       "    prec: Precipitation Hourly [mm]\n",
       "    temp2m: Two Meter Temperature [deg K]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dsTotal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "    fig.ondownload(fig, format);\n",
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       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
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       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
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       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
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       "}\n",
       "\n",
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       "\n",
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       "\n",
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       "    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",
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       "\n",
       "            /* Free the memory for the previous frames */\n",
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       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x130798080>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook \n",
    "# this is needed before plotting in python3\n",
    "dsTotal.temp2mC=dsTotal.temp2m-273.15 # convert temperature to deg C\n",
    "ds_by_month = dsTotal.temp2mC.groupby('time.month').mean('time') # group temperatures by month\n",
    "ds_by_month[1].plot() # plot mean August temperatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x118c95208>]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook \n",
    "xycord = np.where(dsTotal.coords['longitude'].values == -125.07546997) # similar to MATLAB's 'find' function. Insert longitude which is unique due to the warped nature of the WRF grid and find the indices assosciated with it\n",
    "xcord = xycord[0][0] # find xcord from the tuple\n",
    "ycord = xycord[1][0]\n",
    "dsTotal.temp2m.isel(x = xcord, y = ycord).plot() # select the coordiante location and plot a time-series of temperature\n",
    "# note use isel when grouping by index values and sel when grouping by times or lat and long values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1317b1860>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook \n",
    "DataArray = dsTotal.temp2m.sel(time = '2013-07-02T02:00:00')\n",
    "DataArray.plot(levels=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x107369390>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook \n",
    "dsTotal.temp2m[:,0,0].plot() # a simple way to plot a time-series if you know the indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-125.39456177, -125.33074951, -125.266922  , -125.20309448,\n",
       "       -125.13928223, -125.07546997, -125.01165771, -124.9478302 ,\n",
       "       -124.88400269], dtype=float32)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#this is for testing, because we dont have the final list of WRF nodes that are within the watershed - this reads the latof the top 9 nodes\n",
    "shortLongList = dsTotal.coords['longitude'].values[0,0:9]\n",
    "shortLongList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3, 4, 5, 6, 7, 8]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#this loops through the lon list and back calculates the x and y indices needed to plot or extract data\n",
    "xcord = []\n",
    "ycord = []\n",
    "\n",
    "#this is not working yet because the list of lat - long is old from old WRF runs - need to identify the nodes in my watershed\n",
    "#need to update the csv file\n",
    "for Lon in shortLongList:\n",
    "    xycord = np.where(dsTotal.coords['longitude'].values == Lon) # similar to MATLAB's 'find' function. Insert longitude which is unique due to the warped nature of the WRF grid and find the indices assosciated with it\n",
    "    xcord.append(xycord[0][0]) # find xcord from the tuple\n",
    "    ycord.append(xycord[1][0])\n",
    "    \n",
    "ycord"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xray.DataArray 'temp2m' (points: 9, time: 3672)>\n",
       "array([[ 290.04446411,  289.70251465,  288.94180298, ...,  290.21450806,\n",
       "         290.23049927,  290.18441772],\n",
       "       [ 290.05984497,  289.74081421,  289.04653931, ...,  290.20788574,\n",
       "         290.22393799,  290.18963623],\n",
       "       [ 290.07324219,  289.78927612,  289.16171265, ...,  290.18011475,\n",
       "         290.20965576,  290.1882019 ],\n",
       "       ..., \n",
       "       [ 290.1918335 ,  290.02316284,  289.73822021, ...,  290.11224365,\n",
       "         290.20162964,  290.24057007],\n",
       "       [ 290.22180176,  290.06787109,  289.85028076, ...,  290.10317993,\n",
       "         290.20736694,  290.25274658],\n",
       "       [ 290.20632935,  290.07546997,  289.90557861, ...,  290.05148315,\n",
       "         290.17553711,  290.23208618]], dtype=float32)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 2013-11-01 2013-11-01T01:00:00 ...\n",
       "    x          (points) int64 0 0 0 0 0 0 0 0 0\n",
       "    longitude  (points) float32 -125.395 -125.331 -125.267 -125.203 -125.139 ...\n",
       "    latitude   (points) float32 32.5872 32.588 32.5887 32.5894 32.5901 ...\n",
       "    y          (points) int64 0 1 2 3 4 5 6 7 8\n",
       "  * points     (points) int64 0 1 2 3 4 5 6 7 8"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#this is an example of seleting temperature values at the 9 points\n",
    "selectTemp = dsTotal.temp2m.sel_points(x = xcord, y = ycord)\n",
    "selectTemp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "points  time               \n",
       "0       2013-11-01 00:00:00    290.044464\n",
       "        2013-11-01 01:00:00    289.702515\n",
       "        2013-11-01 02:00:00    288.941803\n",
       "        2013-11-01 03:00:00    288.039276\n",
       "        2013-11-01 04:00:00    287.661987\n",
       "        2013-11-01 05:00:00    287.530396\n",
       "        2013-11-01 06:00:00    287.737671\n",
       "        2013-11-01 07:00:00    288.157562\n",
       "        2013-11-01 08:00:00    288.202271\n",
       "        2013-11-01 09:00:00    288.219818\n",
       "        2013-11-01 10:00:00    288.305359\n",
       "        2013-11-01 11:00:00    288.548401\n",
       "        2013-11-01 12:00:00    288.868408\n",
       "        2013-11-01 13:00:00    289.116241\n",
       "        2013-11-01 14:00:00    289.265320\n",
       "        2013-11-01 15:00:00    289.324005\n",
       "        2013-11-01 16:00:00    289.438904\n",
       "        2013-11-01 17:00:00    289.312561\n",
       "        2013-11-01 18:00:00    289.134155\n",
       "        2013-11-01 19:00:00    289.073181\n",
       "        2013-11-01 20:00:00    289.074066\n",
       "        2013-11-01 21:00:00    289.036316\n",
       "        2013-11-01 22:00:00    288.975067\n",
       "        2013-11-01 23:00:00    288.915375\n",
       "        2013-11-02 00:00:00    288.908936\n",
       "        2013-11-02 01:00:00    288.915924\n",
       "        2013-11-02 02:00:00    288.911865\n",
       "        2013-11-02 03:00:00    288.856079\n",
       "        2013-11-02 04:00:00    288.753479\n",
       "        2013-11-02 05:00:00    288.736816\n",
       "                                  ...    \n",
       "8       2013-10-30 18:00:00    290.413757\n",
       "        2013-10-30 19:00:00    290.443542\n",
       "        2013-10-30 20:00:00    290.483337\n",
       "        2013-10-30 21:00:00    290.479248\n",
       "        2013-10-30 22:00:00    290.441528\n",
       "        2013-10-30 23:00:00    290.373566\n",
       "        2013-10-31 00:00:00    290.320038\n",
       "        2013-10-31 01:00:00    290.271240\n",
       "        2013-10-31 02:00:00    290.195831\n",
       "        2013-10-31 03:00:00    290.088623\n",
       "        2013-10-31 04:00:00    289.974579\n",
       "        2013-10-31 05:00:00    289.928070\n",
       "        2013-10-31 06:00:00    289.935699\n",
       "        2013-10-31 07:00:00    289.993713\n",
       "        2013-10-31 08:00:00    290.028931\n",
       "        2013-10-31 09:00:00    290.028015\n",
       "        2013-10-31 10:00:00    290.005096\n",
       "        2013-10-31 11:00:00    289.981262\n",
       "        2013-10-31 12:00:00    289.969025\n",
       "        2013-10-31 13:00:00    289.974701\n",
       "        2013-10-31 14:00:00    290.025177\n",
       "        2013-10-31 15:00:00    289.966400\n",
       "        2013-10-31 16:00:00    289.864868\n",
       "        2013-10-31 17:00:00    289.836761\n",
       "        2013-10-31 18:00:00    289.837006\n",
       "        2013-10-31 19:00:00    289.849823\n",
       "        2013-10-31 20:00:00    289.929779\n",
       "        2013-10-31 21:00:00    290.051483\n",
       "        2013-10-31 22:00:00    290.175537\n",
       "        2013-10-31 23:00:00    290.232086\n",
       "Name: temp2m, dtype: float32"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_nine_nodes = selectTemp.to_series() #converts xray to pandas timeseries\n",
    "final_nine_nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "final_nine_nodes.to_csv('temp_nine_nodes.csv') #this will save data in cvs format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Mo1_2013-11.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-07.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-08.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-09.nc',\n",
       " '/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-10.nc']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# now we want to read all the files and concatenate by model run\n",
    "import glob\n",
    "fileList = glob.glob('/Users/carina/desktop/WRF_data/*.nc')\n",
    "fileList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: NARR\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Mo1_2013-11.nc\"\n",
      "Model: NARR\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-07.nc\"\n",
      "Model: Morr\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-07.nc\"\n",
      "Ignoring file \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-07.nc\"\n",
      "Model: NARR\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-08.nc\"\n",
      "Model: Morr\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-08.nc\"\n",
      "Ignoring file \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-08.nc\"\n",
      "Model: NARR\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-09.nc\"\n",
      "Model: Morr\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-09.nc\"\n",
      "Ignoring file \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-09.nc\"\n",
      "Model: NARR\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-10.nc\"\n",
      "Model: Morr\n",
      "File: \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-10.nc\"\n",
      "Ignoring file \"/Users/carina/desktop/WRF_data/surfoutd02_CONUSnl_WRF_NARR_Morr_2013-10.nc\"\n"
     ]
    }
   ],
   "source": [
    "#this will loop through the files and extract the ones for a particular model run, will rearrange the variables and add attributes to variables \n",
    "#of inteest, in this case precipitation and temperature\n",
    "\n",
    "fileFinder = ['NARR', 'Morr']\n",
    "\n",
    "def decode(d):\n",
    "    decoded = datetime.strptime(d.decode(encoding='UTF-8'),  \"%Y-%m-%d_%H:%M:%S\")\n",
    "    return decoded\n",
    "\n",
    "first = True # create a boolean for the loop below\n",
    "\n",
    "files_read = set()\n",
    "\n",
    "for file in fileList:\n",
    "    for model in fileFinder:\n",
    "        if file.find(model) != -1:\n",
    "                print('Model: {}'.format(model))\n",
    "                print('File: \"{}\"'.format(file))\n",
    "                if file in files_read:\n",
    "                    print('Ignoring file \"{}\"'.format(file))\n",
    "                    break # break out of the model for loop as we already processed the file\n",
    "                files_read.add(file)\n",
    "                if first:      \n",
    "                    ds = xray.open_dataset(file , engine = 'netcdf4') # may not need enginer = 'netcdf4' others are using engine = 'scipy'\n",
    "                    dates = ds.Times.to_series().apply(decode) # this creates a list of the varaibles Times in the netCDF file ds and then applies the decode function to each element\n",
    "                    dsTotal = xray.Dataset({'prec': (['time','x','y'], ds.prehourly.values),\n",
    "                                  'temp2m':(['time','x','y'], ds.t2.values)},\n",
    "                                   coords = {'longitude': (['x','y'], ds.lon.values),\n",
    "                                          'latitude': (['x','y'], ds.lat.values),\n",
    "                                          'time': xray.DataArray.from_series(dates).values})\n",
    "                            # first the prec and temp2m variables are created\n",
    "                            # then we add coordinates\n",
    "\n",
    "\n",
    "                    first = False # now that new 'clean' netCDF file is created switch the boolean operator so the below is run and we finally concatenate\n",
    "\n",
    "                # the rest does the same as above but concatenates the end\n",
    "                else:\n",
    "                    ds = xray.open_dataset(file, engine = 'netcdf4' )\n",
    "                    dates = ds.Times.to_series().apply(decode)\n",
    "                    dsTemp = xray.Dataset({'prec': (['time','x','y'], ds.prehourly.values),\n",
    "                                  'temp2m':(['time','x','y'], ds.t2.values)},\n",
    "                                   coords = {'longitude': (['x','y'], ds.lon.values),\n",
    "                                          'latitude': (['x','y'], ds.lat.values),\n",
    "                                          'time': xray.DataArray.from_series(dates).values})\n",
    "\n",
    "                    dsTotal = xray.concat([dsTotal, dsTemp], dim = 'time') # this is concatenating\n",
    "\n",
    "\n",
    "        # add attributes to the netCDF\n",
    "dsTotal.attrs['prec'] = 'Precipitation Hourly [mm]'        \n",
    "dsTotal.attrs['temp2m'] = 'Two Meter Temperature [deg K]'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x118c85ac8>]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook \n",
    "dsTotal.temp2m[:,0,0].plot() # a simple way to plot a time-series if you know the indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}