devel-LtL-speedtest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "##THE FIRST RUN IS LONGER BECAUSE OF LOADING OF SCIPY\n",
    "\n",
    "%matplotlib notebook\n",
    "#%matplotlib inline\n",
    "\n",
    "#https://stackoverflow.com/questions/20961287/what-is-pylab\n",
    "#%pylab\n",
    "##import matplotlib.pylab as p13 \n",
    "##import pylab as p14\n",
    "##from matplotlib.pylab import *\n",
    "from pylab import *\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "#parameters are described at  https://github.com/martin12333/PyMartinCA/blob/master/PARAMETERS.txt\n",
    "\n",
    "r=2\n",
    "\n",
    "bmin=7\n",
    "smin=7\n",
    "\n",
    "xlo=7; dx52=6;  ylo=9; dy52=3\n",
    "\n",
    "#\n",
    "\n",
    "xhi=xlo+dx52\n",
    "yhi=ylo + dy52\n",
    "\n",
    "#=============================\n",
    "\n",
    "w=1000 #1850 #2000 #2250 #1800\n",
    "h=1000 #950 #1300 #1400 #950\n",
    "\n",
    "#\n",
    "####################\n",
    "##np.random.seed()      \n",
    "\n",
    "p=0.5 #0.25 #0.16\n",
    "a = (rand( h, w )<p) \n",
    "\n",
    "#=============================\n",
    "\n",
    "###x11 = floor(linspace(xlo, xhi + 0.999, w))\n",
    "###y11 = floor(linspace(yhi + 0.999 , ylo, h))\n",
    "x11 = (linspace(xlo, xhi , w))\n",
    "y11 = (linspace(yhi  , ylo, h))\n",
    "xx, yy = meshgrid(x11, y11)\n",
    " \n",
    "bmax=xx\n",
    "smax=yy\n",
    "\n",
    "#\n",
    "\n",
    "niter =  200 #400 #200 #1000 #3000   \n",
    "sleep1=    0 #0.3      #0.1 #0 #0.01\n",
    "step1=12 #4 #20 #8 #15 #5 #1 #37 #2\n",
    "step2=60 #120 #1\n",
    "\n",
    "bfade = False#True  # False\n",
    "q = 0.1#0.9 #0.8#0.7 #0.3 #0.1 \n",
    "###qqq=0.2 ###0 #0.5 #1#2 #4 #8 #1.8\n",
    "#q2=0.7\n",
    "#\n",
    "\n",
    "afade = 0.1 * a\n",
    "averyold = a \n",
    "\n",
    "diam = 2*r + 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 0.500 0.000\n",
      "60 0.500 0.000\n",
      "120 0.500 0.000\n",
      "180 0.500 0.000\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",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "        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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.01 s, sys: 4.02 ms, total: 2.02 s\n",
      "Wall time: 10.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "import scipy.ndimage \n",
    "\n",
    "from scipy.ndimage import filters\n",
    "\n",
    "import time\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "#plt.ion()\n",
    "\n",
    "\n",
    "#img_plot = plt.imshow(a)\n",
    "\n",
    "\n",
    "#plt.show(block=False)\n",
    "\n",
    "\n",
    "\n",
    "kr=np.ones((diam,diam), dtype=np.uint8)\n",
    "\n",
    "\n",
    "\n",
    "OR = logical_or\n",
    "AND = logical_and\n",
    "\n",
    "for i in range(niter):\n",
    "\n",
    "    ################\n",
    "    \n",
    "    ####n=scipy.ndimage.convolve(a,kr)\n",
    "    #n=scipy.ndimage.convolve(0+a,kr)\n",
    "\n",
    "    ###################\n",
    "    \n",
    "    #n41 =   diam*diam*filters.uniform_filter(0.0+a,diam )   ##,mode='wrap')  )  \n",
    "    #n=n41.round()   \n",
    "    \n",
    "    #################\n",
    "\n",
    "    n=smin*(0+a)\n",
    "    \n",
    "    #################\n",
    "    \n",
    "    birth = AND(  n>=bmin,  AND( n<=bmax, logical_not(a) )  )\n",
    "    survi = AND(  n>=smin,  AND( n<=smax, a )  )\n",
    "    a =  OR( birth , survi )  \n",
    "    if (i % step1)==0:\n",
    "\n",
    "        \n",
    "        ###########################################\n",
    "        \n",
    "        \n",
    "        if bfade:\n",
    "            ###asho = np.maximum( a , qqq*afade )\n",
    "            ##asho = np.maximum( 1 , q2*afade/q )\n",
    "            #asho = np.minimum( 1 , q2*afade/q )\n",
    "            asho = np.minimum( 1 , afade/q )\n",
    "            afade = q*a + (1-q)*afade\n",
    "            ####asho=afade\n",
    "        else:\n",
    "            asho=0+a\n",
    "            \n",
    "\n",
    "        ###########################################\n",
    "\n",
    "            \n",
    "        ada51= logical_xor(a, averyold)  \n",
    "        averyold =a \n",
    "        \n",
    "        #adaimage = transpose( ( ( asho)))\n",
    "        #b = array(255*clip(adaimage,0,1),'B')\n",
    "\n",
    "        #img_plot.set_data(asho)\n",
    "        ###imshow(asho)\n",
    "        ##show()\n",
    "        #plt.draw()\n",
    "\n",
    "\n",
    "        #time.sleep(sleep1)\n",
    "\n",
    "        if (i % step2)==0:\n",
    "            am51=(0.0+a).mean()\n",
    "            sam51='{:.3f}'.format(am51)\n",
    "            dam51=ada51.mean()\n",
    "            sdam51='{:.3f}'.format(dam51)\n",
    "            print( i, sam51, sdam51)\n",
    "\n",
    "###########################################\n",
    "\n",
    "            \n",
    "#plt.figure(figsize = (11,5.5))\n",
    " \n",
    "img_plot = plt.imshow(asho)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('bool')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       ...,\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]], dtype=uint8)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(n,dtype=np.uint8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "*int*?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "int*?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.rc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config DisplayFormatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}