Mifration Rossia

Migration.ipynb

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    "# Russian Federation, international migration to and from country\n",
    "\n",
    "Some interestion results of international migration in Russain Federation.\n",
    "\n",
    "## Links\n",
    "\n",
    "<ol>\n",
    "<li>Russian Federation Federal State Statistics Service\n",
    "<ul>\n",
    "<li>http://www.gks.ru/free_doc/new_site/population/demo/migr1.xls - General results of migration</li>\n",
    "<li>http://www.gks.ru/free_doc/new_site/population/demo/migr2.xls - Migration by countries</li>\n",
    "</ul>\n",
    "<li>http://www.homeenglish.ru/Othercountry.htm - for translate country name from russian to english</li>\n",
    "<li>Ministry of Internal Affairs of the Russian Federation\n",
    "<ul>\n",
    "<li>https://мвд.рф/upload/site1/document_news/009/359/228/stst_2016.xlsx - Statistical information on the migration situation in the Russian Federation for 12 months of 2016 with distribution and regions (converted localy to xls)</li>\n",
    "\n",
    "</ul>\n",
    "</li>\n",
    "</li></ol>\n",
    "\n",
    "## Assumption\n",
    "\n",
    "Pr. Putin third election case large migration increase, mainly out from Russia to Europe. \n",
    "\n",
    "## Conclusion\n",
    " The assumption is NOT confirmed. But we have some Interesting results about quality and quantity migrants\n",
    " "
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    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# sources for some reason is not always available from the Сoursera system - Rosstat's site very \"heavy\"\n",
    "# so I use local (Coursera) files copy, but if you switch local on online code will work, too.\n",
    "\n",
    "# GENERAL RESULTS OF MIGRATION OF THE POPULATION OF THE RUSSIAN FEDERATION, 1990 - 2015\n",
    "strSumMigration='http://www.gks.ru/free_doc/new_site/population/demo/migr1.xls' \n",
    "#strSumMigration='migr1.xls' \n",
    "\n",
    "# INTERNATIONAL MIGRATION, 1997 - 2015\n",
    "strSumMigrationByCountry='http://www.gks.ru/free_doc/new_site/population/demo/migr2.xls' \n",
    "#strSumMigrationByCountry='migr2.xls' \n",
    "\n",
    "#Internal registration of migrants, from Ministry of Internal Affairs of the Russian Federation, 2016 only\n",
    "strInternalViewByCountry='stst_2016.xls'\n",
    "\n",
    "iBaseYear=1990\n",
    "\n",
    "strXlabel100='Hundreds of thousands of people'\n",
    "strXlabel10='Tens of thousands of people'\n",
    "strYLavel='Years'\n",
    "strMainTitle='General results of migration'\n",
    "strInTitle='Migration to Russia'\n",
    "strOutTitle='Migration from Russia'\n",
    "\n",
    "fBarWidth=0.6\n",
    "fAplha=0.5\n",
    "fKeyLineWidth=0.2\n",
    "\n",
    "iTickLabelSize=8\n",
    "iAxisTitleSize=10\n",
    "iCaptionSize=14\n",
    "fScale=1e4\n",
    "\n",
    "strColorIn='maroon'\n",
    "strColorOut='navy'"
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    "# %%writefile migr_service.py\n",
    "# %load migr_service.py\n",
    "import re\n",
    "\n",
    "def read_sum_migration(strSource):\n",
    "    '''make DataFrame with GENERAL RESULTS OF MIGRATION from 1990, simply in and out, by all countries'''\n",
    "    migr=pd.read_excel(strSource, sheetname=0, names=['MigrationIn', 'MigrationOut'],\n",
    "                     parse_cols=[0,5,10], header=None, skiprows =8, skip_footer=54, index_col=0)\n",
    "    migr.index.name='years'\n",
    "    return migr\n",
    "\n",
    "#print (read_sum_migration(strSumMigration))\n",
    "\n",
    "def make_translate_dict(strSource):\n",
    "    '''Make translation DICT, for rus-eng translation '''\n",
    "    return pd.read_csv('countries_rus_eng.csv', names=['Country', 'CountryEng'], index_col=0).squeeze()\n",
    "\n",
    "#print(make_translate_dict(r'/home/egor/git/jupyter/Migration/coutries.txt'))\n",
    "\n",
    "lst_CIS=[ 'Азербайджан', 'Армения', 'Беларусь', 'Казахстан', 'Киргизия', \n",
    "         'Республика Молдова', 'Таджикистан', 'Туркмения', 'Узбекистан', 'Украина', 'Молдова, Республика']\n",
    "\n",
    "lst_exUSSR= lst_CIS + ['Латвия', \"Литва\", \"Эстония\", \"Грузия\"]\n",
    "\n",
    "lst_exUSSR_nr = lst_exUSSR + ['Южная Осетия', 'Абхазия']\n",
    "\n",
    "def make_dict(source_list, key='CIS', src_lst=lst_CIS):\n",
    "    dct={ k.strip(): key if k.strip() in src_lst else 'FOREIGN' for k in source_list }\n",
    "    return dct\n",
    "\n",
    "def read_sum_migration_country(strSource, lstSplitRegion=lst_exUSSR):\n",
    "    '''nake DataFrame with general results of migration by countries, from 1997'''\n",
    "    migr=pd.read_excel(strSource, sheetname=0, header=0, skiprows =4, index_col=0).dropna()\n",
    "        \n",
    "    migr.index.rename('Country', inplace=True)\n",
    "\n",
    "    dEx=make_dict(migr.index.tolist(), key='exUSSR', src_lst=lstSplitRegion)\n",
    "    migr.reset_index(inplace=True)\n",
    "    \n",
    "    #print(dEx)\n",
    "    \n",
    "    migr['AREA2']=migr['Country'].map(dEx)\n",
    "    migr['CountryEng']=migr['Country'].map(make_translate_dict('coutries.txt'))\n",
    "    migr['DIRECTION']='in'\n",
    "    \n",
    "    migr['CountryEng']=migr['CountryEng'].str.strip()\n",
    "    \n",
    "    migr.set_index('Country', inplace=True)\n",
    "    \n",
    "    l=migr.index.get_loc('Выбыло из Российской Федерации - всего')\n",
    "    migr.loc['Выбыло из Российской Федерации - всего':, 'DIRECTION']='out'\n",
    "    migr.reset_index(inplace=True)\n",
    "    \n",
    "    m_del=migr[migr['CountryEng'].isnull()]\n",
    "    \n",
    "    m_del=m_del.where(m_del['Country'].str.contains('в|из\\s'))\n",
    "    migr.drop(m_del['Country'].dropna().index, inplace=True)\n",
    "    \n",
    "    migr.set_index('CountryEng', inplace=True)\n",
    "\n",
    "    return migr\n",
    "\n",
    "def make_plot_dataframe(dtfMain, strDirection, strArea, fScale):\n",
    "    '''cleaning data from unrecognized states'''\n",
    "    def cleaning_unrecognized_states(dtf, list_col):\n",
    "        k2=dtf.loc[('Georgia', 'Abkhazia', 'South Ossetia'), list_col].sum()\n",
    "        dtf.loc['Georgia', list_col]=k2\n",
    "        drp=dtf.drop(['Abkhazia', 'South Ossetia'], inplace=True)\n",
    "        return dtf\n",
    "    \n",
    "    mTemp=mgr[mgr['DIRECTION']==strDirection]\n",
    "    mTemp=cleaning_unrecognized_states(mTemp, lstWorkCol)\n",
    "    mRet=mTemp[mTemp['AREA2']==strArea]\n",
    "    return mRet[lstWorkCol].div(fScale)\n",
    "\n",
    "\n",
    "def set_spines(ax, *varg):\n",
    "    '''turn out axes spines'''\n",
    "    for pl in varg[0]:\n",
    "        ax.spines[pl].set_visible(False)\n",
    "        \n",
    "def plot2bars(dfOut, dfIn, axOut, axIn, bar_colors_in=None, ano_lines=None, ano_lines_x=3.5, \n",
    "              bar_colors_out=None, stacked_bars=False, ax_legend=None, legend_labels=None, \n",
    "              strXLabel=strXlabel100, strYLabel=strXlabel100):\n",
    "    '''plot two hor-bar sets, one against other'''\n",
    "    def drw_ano_lines(axO, axI, dctLines, x_off):\n",
    "        for key, val in dctLines.items():\n",
    "            axO.axhline(color=strColorOut, linestyle='-', linewidth=fKeyLineWidth, y=key-iBaseYear)\n",
    "            axI.axhline(color=strColorIn, linestyle='-', linewidth=fKeyLineWidth, y=key-iBaseYear)\n",
    "            axI.annotate(val, xy=(axI.get_xlim()[0], key-iBaseYear), \n",
    "                     xytext=(axI.get_xlim()[0]+x_off, key-iBaseYear+0.2), ha='center', fontsize=8)\n",
    "\n",
    "    \n",
    "    dfOut.plot(kind='barh', ax=axOut, fontsize=iTickLabelSize, \n",
    "                           alpha=fAplha, color=bar_colors_out, width=fBarWidth, \n",
    "                           stacked=stacked_bars, legend=False)\n",
    "    axOut.set_title(strOutTitle, fontsize=iAxisTitleSize, color=strColorOut)\n",
    "    axOut.set_xlabel(strXLabel, fontsize=iTickLabelSize, color=strColorOut)\n",
    "    axOut.get_yaxis().set_tick_params(labelsize=iTickLabelSize, colors=strColorOut)\n",
    "\n",
    "    set_spines(axOut, ['top', 'right'])\n",
    "\n",
    "    dfIn.plot(kind='barh', ax=axIn, fontsize=iTickLabelSize, \n",
    "                          alpha=fAplha, color=bar_colors_in, width=fBarWidth, stacked=stacked_bars, \n",
    "              legend=ax_legend != None)\n",
    "    axIn.set_title(strInTitle, fontsize=iAxisTitleSize, color=strColorIn)\n",
    "\n",
    "    axIn.invert_xaxis()\n",
    "    set_spines(axIn, ['top'])\n",
    "    axIn.spines['top'].set_visible(False)\n",
    "    axIn.spines['left'].set_position('zero')\n",
    "    axIn.get_yaxis().set_tick_params(direction='out', labelsize=iTickLabelSize, colors=strColorIn)\n",
    "    axIn.get_yaxis().set_ticks_position('right')\n",
    "    axIn.set_xlabel(strXLabel, fontsize=iTickLabelSize, color=strColorIn)\n",
    "    axIn.get_yaxis().set_label_position('right')\n",
    "    \n",
    "    axOut.set_xlim([axIn.get_xlim()[1], axIn.get_xlim()[0]])\n",
    "    \n",
    "    if ano_lines:\n",
    "        drw_ano_lines(axOut, axIn, ano_lines, ano_lines_x)\n",
    "    \n",
    "    \n",
    "    axIn.set_xlim([axIn.get_xlim()[0]+2, axIn.get_xlim()[1]])\n",
    "\n",
    "    axOut.set_xlim([axIn.get_xlim()[1], axIn.get_xlim()[0]])\n",
    "    if ax_legend:\n",
    "        move_legend(axIn, ax_legend, legend_labels)\n",
    "        \n",
    "def move_legend(axFrom, axTo, lstLabels=None):\n",
    "    '''move legend to external axes'''\n",
    "    axTo.axis('off')\n",
    "    hdl, lbl = axFrom.get_legend_handles_labels()\n",
    "    axTo.legend(hdl, lbl if not lstLabels else lstLabels, loc='center')\n",
    "    axFrom.legend_.remove()\n",
    "\n",
    "def print_text(ax, df, y_pos=0, step=12):\n",
    "    '''print text for DataFrame with CULT colomn '''\n",
    "    lstAnno=['Group members:']\n",
    "    lst_cat=list(df['CULT'].unique().dropna())\n",
    "\n",
    "    for i in range(len(lst_cat)):\n",
    "        i_step=step\n",
    "        lst_c=sorted(df[df['CULT']==lst_cat[i]].index.unique().dropna().tolist())\n",
    "        lst_c[::i_step]=list(map(lambda x:x+'\\n', lst_c[::i_step]))\n",
    "        lst_c[0]=lst_c[0].strip()\n",
    "        lstAnno.append('\"{}\": {}\\n'.format(lst_cat[i], ', '.join(lst_c).replace('\\n, ', ',\\n')))\n",
    "    ax.text(0, y_pos, '\\n'.join(lstAnno), color='black', fontsize=8)     \n",
    "    \n",
    "def sum_and_sort(pdFrame, lstCols):\n",
    "    pdFrame['sum']=pdFrame[lstCols].sum(axis=1)\n",
    "    pdFrame.sort(columns='sum', inplace=True, ascending=False)\n",
    "    return pdFrame\n",
    "\n",
    "def read_mvd_data(str_source , lstSplitRegion=lst_exUSSR_nr):\n",
    "    '''read mvd data - tourism, work migration etc, by countries, only 2016'''\n",
    "    df_mvd=pd.read_excel(str_source, sheetname=1, header=None, \n",
    "                     skiprows =13, index_col=0, \n",
    "                     names=['invitation', 'visa', 'reg_all', 'reg_location', 'reg_residence', 'base', 'tourism', \n",
    "                            'study', 'work', 'personal', 'other', 'reg_out', 'des_rvp', 'rvp', 'des_pmg', 'pmg', \n",
    "                            'get_citi', 'for_del']).dropna()\n",
    "    df_mvd.index.name='Country'\n",
    "    df_mvd.drop('for_del', inplace=True, axis=1)\n",
    "\n",
    "    dEx=make_dict(df_mvd.index.tolist(), key='exUSSR', src_lst=lstSplitRegion)\n",
    "    #print(dEx)\n",
    "    df_mvd.reset_index(inplace=True)\n",
    "    df_mvd['Country']=df_mvd['Country'].str.strip()\n",
    "\n",
    "    df_mvd['AREA2']=df_mvd['Country'].map(dEx)\n",
    "    df_mvd['AREA2'].fillna('FOREIGN', inplace=True)\n",
    "    df_mvd['CountryEng']=df_mvd['Country'].map(make_translate_dict('coutries.txt'))\n",
    "\n",
    "    ddd=df_mvd[['Country', 'CountryEng']].where(df_mvd['CountryEng'].isnull())\n",
    "    d=df_mvd[ddd['Country'].notnull() & ddd['CountryEng'].isnull()].sum()\n",
    "    d['Country']='Другие'\n",
    "    d.name='Other'\n",
    "    \n",
    "    df_mvd.set_index('CountryEng', inplace=True)\n",
    "    df_mvd=df_mvd.append(d)\n",
    "    df_mvd.loc['Other', 'AREA2']='FOREIGN'\n",
    "    return df_mvd.drop('CountryEng', axis=1)"
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       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "dfSum=read_sum_migration(strSumMigration).div(1e5)\n",
    "\n",
    "iBaseYear=dfSum.index[0]\n",
    "\n",
    "dKeyYears={2000:'Putin I', 2004:'Putin II', 2012:'Putin III', 2008:'Medvedev I\\nWorld financial crisis', 2014:'Ukranian war\\noil price fall', \n",
    "          1991:'The collapse of the USSR\\nYeltsin I', 1996:'Yeltsin II'}\n",
    "\n",
    "fig1, (axSumOut, axSumIn)=plt.subplots(1, 2, sharey=True, figsize=(8,7), facecolor='moccasin')\n",
    "fig1.suptitle(strMainTitle, fontsize=iCaptionSize)\n",
    "    \n",
    "\n",
    "plot2bars(dfSum['MigrationOut'], dfSum['MigrationIn'], axSumOut, axSumIn, \n",
    "          bar_colors_in='maroon', bar_colors_out='navy', ano_lines=dKeyYears, strXLabel=strXlabel100)\n",
    "    \n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#read migration by countries from source \n",
    "\n",
    "#mgr=read_sum_migration_country(strSumMigrationByCountry)\n",
    "mgr=read_sum_migration_country(strSumMigrationByCountry, lstSplitRegion=lst_exUSSR_nr)\n",
    "lstWorkCol=[i for i in mgr.columns.tolist() if str(i).isdigit()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/egor/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py:477: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[item] = s\n",
      "/home/egor/anaconda3/lib/python3.6/site-packages/ipykernel/__main__.py:68: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.gridspec as gSpc\n",
    "\n",
    "#plt.style.use('seaborn-notebook')\n",
    "\n",
    "cstrTitle4_exUSSR = 'Migration with exUSSR countries'\n",
    "\n",
    "mOut_USSR=make_plot_dataframe(mgr, 'out', 'exUSSR', 10e4)\n",
    "mIn_USSR=make_plot_dataframe(mgr, 'in', 'exUSSR', 10e4)\n",
    "\n",
    "fig2=plt.figure(figsize=(10,6))\n",
    "fig2.suptitle(cstrTitle4_exUSSR, fontsize=iCaptionSize)\n",
    "\n",
    "gs=gSpc.GridSpec(2, 4, width_ratios=[0.2, 2.8, 2.8, 1.2]) #, height_ratios=[])\n",
    "\n",
    "ax_t=fig2.add_subplot(gs[0, 0])\n",
    "ax_t.text(0.5, 0.25, strXlabel10, rotation='vertical', fontsize=iTickLabelSize)\n",
    "ax_t.axis('off')\n",
    "\n",
    "ax_UOut=fig2.add_subplot(gs[0, 1:3])\n",
    "ax_UIn=fig2.add_subplot(gs[1, 1:3], sharex=ax_UOut)\n",
    "ax_USSR_legend=fig2.add_subplot(gs[0:, -1], sharex=None)\n",
    "\n",
    "lst_colors1=['navy', 'orange', 'lightgreen', 'lightblue', 'red', 'blue', 'green', \n",
    "            'darkgreen', 'teal', 'gold', 'silver', 'purple', 'maroon', 'gray']\n",
    "\n",
    "#mOut_USSR.T.plot.bar(stacked=True, alpha=0.7, color=lst_colors1, width=0.8, \n",
    "#                     ax=ax_UOut, legend=None, fontsize=8)\n",
    "#mIn_USSR.T.plot.bar(stacked=True, alpha=0.7, color=lst_colors1, width=0.8, \n",
    "#                    ax=ax_UIn, legend=True, fontsize=8)\n",
    "\n",
    "mOut_USSR.T.plot.area(stacked=False, alpha=fAplha, color=lst_colors1,\n",
    "                     ax=ax_UOut, legend=None, fontsize=iTickLabelSize)\n",
    "mIn_USSR.T.plot.area(stacked=False, alpha=fAplha, color=lst_colors1,\n",
    "                    ax=ax_UIn, legend=True, fontsize=iTickLabelSize)\n",
    "\n",
    "\n",
    "set_spines(ax_UIn, ['top', 'right'])\n",
    "ax_UIn.invert_yaxis()\n",
    "\n",
    "set_spines(ax_UOut, ['top', 'right'])\n",
    "\n",
    "ax_UIn.spines['bottom'].set_position('zero')\n",
    "ax_UIn.get_xaxis().set_tick_params(direction='out', labelsize=iTickLabelSize)\n",
    "ax_UIn.get_xaxis().set_ticks_position('top')\n",
    "\n",
    "ax_UOut.set_title(strOutTitle, fontsize=iAxisTitleSize, color=strColorOut, position=(0.5, 0.9))\n",
    "ax_UIn.set_title(strInTitle, fontsize=iAxisTitleSize, color=strColorIn, position=(0.5, 0.1))\n",
    "    \n",
    "move_legend(ax_UIn, ax_USSR_legend)\n",
    "\n",
    "fig2.tight_layout(pad=2.8, w_pad=0.01, h_pad=1)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dv=mIn_USSR-mOut_USSR\n",
    "#print(dv)\n",
    "plt.style.use('seaborn-dark')\n",
    "axSaldo=dv.T.plot(subplots=True, figsize=(8, 17), fontsize=8, color=lst_colors1, grid=True, rot=0)\n",
    "\n",
    "for ax in axSaldo:\n",
    "    hdl, lbl = ax.get_legend_handles_labels()\n",
    "    ax.set_title(lbl[0], fontsize=8, color='black', position=(0.5, 0.75))\n",
    "    ax.legend_.remove()\n",
    "    ax.axhline(color='black', linestyle='-', linewidth=0.5, y=0)\n",
    "\n",
    "axSaldo[0].get_figure().tight_layout()\n",
    "axSaldo[0].get_figure().subplots_adjust(top=0.96)\n",
    "axSaldo[0].get_figure().suptitle('Migration balance with exUSSR countries', fontsize=iCaptionSize);\n",
    "#print(axSaldo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/egor/anaconda3/lib/python3.6/site-packages/ipykernel/__main__.py:150: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "/home/egor/anaconda3/lib/python3.6/site-packages/ipykernel/__main__.py:151: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "/home/egor/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py:3304: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  na_position=na_position)\n"
     ]
    }
   ],
   "source": [
    "mgrF=mgr\n",
    "\n",
    "#mgrF.drop(mgrF.loc[['Abkhazia', 'South Osetia']].index, inplace=True)\n",
    "\n",
    "m_F=mgrF[mgrF['AREA2']=='FOREIGN']\n",
    "\n",
    "mOut_F=m_F[m_F['DIRECTION']=='out']\n",
    "mIn_F=m_F[m_F['DIRECTION']=='in']\n",
    "\n",
    "mOut_F=sum_and_sort(mOut_F, lstCols=lstWorkCol)\n",
    "ddO=mOut_F[mOut_F['sum']>9500]\n",
    "mIn_F=sum_and_sort(mIn_F, lstCols=lstWorkCol)\n",
    "dd=mIn_F[mIn_F['sum']>9500]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/egor/anaconda3/lib/python3.6/site-packages/ipykernel/__main__.py:150: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "/home/egor/anaconda3/lib/python3.6/site-packages/ipykernel/__main__.py:151: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "/home/egor/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py:3304: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  na_position=na_position)\n"
     ]
    }
   ],
   "source": [
    "#import matplotlib.pyplot as plt\n",
    "#import matplotlib.gridspec as gSpc\n",
    "\n",
    "plt.style.use('seaborn-notebook')\n",
    "\n",
    "    \n",
    "#mgrPlot=read_sum_migration_country(strSumMigrationByCountry, lstSplitRegion=lst_exUSSR_nr)\n",
    "mgrPlot=mgr\n",
    "lstPlot= lstWorkCol + ['DIRECTION', 'AREA2']\n",
    "\n",
    "iBaseYear=1997\n",
    "\n",
    "dKeyYears={2000:'Putin $1^{st.}$ elect.', 2004:'Putin $2^{nd.}$ elect.', 2014:'Ukranian war\\nOil price fall',\n",
    "           2012:'Putin $3^{rd.}$ elect.', 2008:'Medvedev $1^{st.}$ elect.\\nWorld financial crisis'}\n",
    "\n",
    "strColorIn='black'\n",
    "strColorOut='black'\n",
    "\n",
    "#===============================================================\n",
    "\n",
    "\n",
    "d=mgrPlot[lstPlot].groupby(['DIRECTION', 'AREA2']).sum()\n",
    "\n",
    "dfOut=d.loc['out']\n",
    "dfIn=d.loc['in']\n",
    "\n",
    "dfOut=dfOut / fScale\n",
    "dfIn=dfIn / fScale\n",
    "\n",
    "fig1=plt.figure(figsize=(9,8))\n",
    "ttl=fig1.suptitle(strMainTitle, fontsize=iCaptionSize)\n",
    "ttl.set_position([0.42, 0.98])\n",
    "\n",
    "gs=gSpc.GridSpec(2, 3, width_ratios=[4.2, 4.2, 1.6], height_ratios=[7, 3])\n",
    "\n",
    "axSumOut=fig1.add_subplot(gs[0, 0])\n",
    "axSumIn=fig1.add_subplot(gs[0, 1], sharey=axSumOut)\n",
    "\n",
    "ax_legend=fig1.add_subplot(gs[0, 2], sharex=None)\n",
    "ax_legend.axis('off')\n",
    "\n",
    "axForIn=fig1.add_subplot(gs[1, 1])\n",
    "axForOut=fig1.add_subplot(gs[1, 0])\n",
    "\n",
    "ax_empt=fig1.add_subplot(gs[0, 2])\n",
    "ax_empt.axis('off')\n",
    "\n",
    "plot2bars(dfOut.T, dfIn.T, axSumOut, axSumIn, bar_colors_in=['navy', 'maroon'], \n",
    "              bar_colors_out=['navy', 'maroon'], ano_lines=dKeyYears, ano_lines_x=8.5, \n",
    "              stacked_bars=True, ax_legend=ax_legend, strXLabel=strXlabel10, \n",
    "              legend_labels=['The rest\\nof the world', 'Countries\\nfrom former USSR'])\n",
    "\n",
    "#try:\n",
    "   # m_F.drop(m_F.loc[['Abkhazia', 'South Osetia']].index, inplace=True)\n",
    "#except:\n",
    "#    pass\n",
    "\n",
    "mOut_F=m_F[m_F['DIRECTION']=='out']\n",
    "mIn_F=m_F[m_F['DIRECTION']=='in']\n",
    "\n",
    "mOut_F=sum_and_sort(mOut_F, lstCols=lstWorkCol)\n",
    "ddO=mOut_F[mOut_F['sum']>9500]\n",
    "mIn_F=sum_and_sort(mIn_F, lstCols=lstWorkCol)\n",
    "dd=mIn_F[mIn_F['sum']>9500]\n",
    "\n",
    "dd=dd[lstWorkCol] / fScale\n",
    "ddO=ddO[lstWorkCol] / fScale\n",
    "\n",
    "axForIn=dd[lstWorkCol].T.plot.area(stacked=False, fontsize=8, \n",
    "                               color=['red', 'gold', 'silver', 'maroon', 'teal', \n",
    "                                      'y', 'green', 'navy', 'orange'], ax=axForIn)\n",
    "axForIn.legend(title='', fontsize=7, loc=9)\n",
    "set_spines(axForIn, ['top', 'right'])\n",
    "axForOut=ddO[lstWorkCol].T.plot.area(stacked=False, fontsize=8, \n",
    "                               color=['gold', 'teal', 'navy', 'red', 'silver', \n",
    "                                      'maroon', 'blue', 'navy', 'y'], ax=axForOut)\n",
    "axForOut.legend(title='', fontsize=7, loc=0)\n",
    "set_spines(axForOut, ['top', 'right'])\n",
    "\n",
    "fig1.tight_layout()\n",
    "\n",
    "fig1.subplots_adjust(top=0.91)\n",
    "plt.show();"
   ]
  },
  {
   "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",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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