map_viewer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "%reload_ext autoreload\n",
    "%autoreload 2\n",
    "# %matplotlib widget\n",
    "# %matplotlib notebook\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import geopandas\n",
    "import os\n",
    "import georasters as gr\n",
    "\n",
    "from geo_scripts.process_height import *\n",
    "from matplotlib.colors import LinearSegmentedColormap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "water = np.load(\"./data/underwater_mask.npy\")\n",
    "polity_map = np.load(\"./outputs/polity_map_-1400.npy\")\n",
    "size_map = np.load(\"./outputs/size_map_-1400.npy\")\n",
    "ultra_map = np.load(\"./outputs/ultra_-1400.npy\")\n",
    "mil_map = np.load(\"./outputs/military_-1400.npy\")\n",
    "ultra_map = np.ma.array(ultra_map, mask=water)\n",
    "mil_map = np.ma.array(mil_map, mask=water)\n",
    "size_map = np.ma.array(size_map, mask=water)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "water = np.load(\"./data/underwater_mask.npy\")\n",
    "polity_map = np.load(\"./outputs/polity_map_-1000.npy\")\n",
    "size_map = np.load(\"./outputs/size_map_-1000.npy\")\n",
    "ultra_map = np.load(\"./outputs/ultra_-1000.npy\")\n",
    "mil_map = np.load(\"./outputs/military_-1000.npy\")\n",
    "ultra_map = np.ma.array(ultra_map, mask=water)\n",
    "mil_map = np.ma.array(mil_map, mask=water)\n",
    "size_map = np.ma.array(size_map, mask=water)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "water = np.load(\"./data/underwater_mask.npy\")\n",
    "polity_map = np.load(\"./outputs/polity_map_-500.npy\")\n",
    "size_map = np.load(\"./outputs/size_map_-500.npy\")\n",
    "ultra_map = np.load(\"./outputs/ultra_-500.npy\")\n",
    "mil_map = np.load(\"./outputs/military_-500.npy\")\n",
    "ultra_map = np.ma.array(ultra_map, mask=water)\n",
    "mil_map = np.ma.array(mil_map, mask=water)\n",
    "size_map = np.ma.array(size_map, mask=water)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "water = np.load(\"./data/underwater_mask.npy\")\n",
    "polity_map = np.load(\"./outputs/polity_map_1000.npy\")\n",
    "size_map = np.load(\"./outputs/size_map_1000.npy\")\n",
    "ultra_map = np.load(\"./outputs/ultra_1000.npy\")\n",
    "mil_map = np.load(\"./outputs/military_1000.npy\")\n",
    "ultra_map = np.ma.array(ultra_map, mask=water)\n",
    "mil_map = np.ma.array(mil_map, mask=water)\n",
    "size_map = np.ma.array(size_map, mask=water)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "water = np.load(\"./data/underwater_mask.npy\")\n",
    "polity_map = np.load(\"./outputs/polity_map_1500.npy\")\n",
    "size_map = np.load(\"./outputs/size_map_1500.npy\")\n",
    "ultra_map = np.load(\"./outputs/ultra_1500.npy\")\n",
    "mil_map = np.load(\"./outputs/military_1500.npy\")\n",
    "ultra_map = np.ma.array(ultra_map, mask=water)\n",
    "mil_map = np.ma.array(mil_map, mask=water)\n",
    "size_map = np.ma.array(size_map, mask=water)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "water = np.load(\"./data/underwater_mask.npy\")\n",
    "polity_map = np.load(\"./outputs/polity_map_0.npy\")\n",
    "size_map = np.load(\"./outputs/size_map_0.npy\")\n",
    "ultra_map = np.load(\"./outputs/ultra_0.npy\")\n",
    "mil_map = np.load(\"./outputs/military_0.npy\")\n",
    "ultra_map = np.ma.array(ultra_map, mask=water)\n",
    "mil_map = np.ma.array(mil_map, mask=water)\n",
    "size_map = np.ma.array(size_map, mask=water)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "96"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_polities = np.ma.max(polity_map) + 1\n",
    "size_counts = np.zeros((num_polities,), dtype=np.int)\n",
    "for x in np.nditer(polity_map):\n",
    "    if x != -1:\n",
    "        size_counts[x] += 1\n",
    "np.max(size_counts)\n",
    "# plt.imshow(ultra_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = [(0, .5, 0), (1, 1, 0), (1, 0, 0)]\n",
    "cm = LinearSegmentedColormap.from_list(\n",
    "        \"turchin\", colors, N=6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
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       "        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",
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       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
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       "\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",
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       "\n",
       "\n",
       "\n",
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       "\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",
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       "        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",
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       "\n",
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       "        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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff16b75fd30>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# [20:90, 160:330]\n",
    "plt.imshow(mil_map, vmin=0, vmax=5, cmap=cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.0"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "100000/100**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1296 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "years = [-1400, -1000, -500, 0, 500, 1000]#, 1500]\n",
    "\n",
    "water = np.load(\"./data/underwater_mask.npy\")\n",
    "water_color = (135, 206, 235)\n",
    "water_image = np.zeros((*ultra_map.shape, 3))\n",
    "water_image[:,:] = water_color\n",
    "\n",
    "fig = plt.figure(figsize=(16,18))\n",
    "\n",
    "for i, year in enumerate(years):\n",
    "    i += 1\n",
    "    ultra_map = np.load(\"./outputs/ultra_%s.npy\" % (year,))\n",
    "    size_map = np.load(\"./outputs/size_map_%s.npy\" % (year,))\n",
    "\n",
    "    ultra_map = np.ma.array(ultra_map, mask=water)\n",
    "    size_map = np.ma.array(size_map, mask=water)\n",
    "    ultra_map = ultra_map[:130, 160:]\n",
    "    size_map = size_map[:130, 160:]\n",
    "    sub = fig.add_subplot(3, 2, i)\n",
    "    sub.imshow(water_image/256)\n",
    "    sub.imshow(size_map, vmin=0, vmax=5, cmap=cm)\n",
    "    sub.set_title(year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}