Compare.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# I will add drop down list to handle all the slider in one slider as it is shown in the proposal by the drawing.\n",
    "# Plus a more feature that will hide the other comparison if the user wanted if he clicks on the Label."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[starkit.gridkit.base][INFO   ]  Reading index (base.py:266)\n",
      "[starkit.gridkit.base][INFO   ]  Discovered columns teff, logg, mh (base.py:269)\n",
      "[starkit.gridkit.base][INFO   ]  Reading Fluxes (base.py:272)\n",
      "[starkit.gridkit.base][INFO   ]  Fluxes shape (688L, 13184L) (base.py:275)\n",
      "[starkit.gridkit.base][INFO   ]  Initializing spec grid (base.py:309)\n",
      "[starkit.gridkit.base][WARNING]  **** NO WAVELENGTH TYPE SET DEFAULTING TO GRID (vacuum) ****\n",
      "\n",
      " (base.py:75)\n",
      "[starkit.gridkit.base][INFO   ]  Reading index (base.py:266)\n",
      "[starkit.gridkit.base][INFO   ]  Discovered columns teff, logg, mh (base.py:269)\n",
      "[starkit.gridkit.base][INFO   ]  Reading Fluxes (base.py:272)\n",
      "[starkit.gridkit.base][INFO   ]  Fluxes shape (688L, 13184L) (base.py:275)\n",
      "[starkit.gridkit.base][INFO   ]  Initializing spec grid (base.py:309)\n",
      "[starkit.gridkit.base][WARNING]  **** NO WAVELENGTH TYPE SET DEFAULTING TO GRID (vacuum) ****\n",
      "\n",
      " (base.py:75)\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 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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2fd0ad5d8c6a4c6f9df7f3d0536fba59",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "aW50ZXJhY3RpdmUoY2hpbGRyZW49KEZsb2F0U2xpZGVyKHZhbHVlPTcwMDAuMCwgZGVzY3JpcHRpb249dSd0ZWZmJywgbWF4PTEwMDAwLjAsIG1pbj00MDAwLjApLCBGbG9hdFNsaWRlcih2YWzigKY=\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from starkit.gridkit import load_grid\n",
    "grid = load_grid('C:\\Users\\pabla\\OneDrive\\Documents\\p.h5')\n",
    "grid1 = load_grid('C:\\Users\\pabla\\OneDrive\\Documents\\p.h5')\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "grid.teff = 5780.\n",
    "grid.logg = 4.4\n",
    "grid.mh = 0.0\n",
    "wave, flux = grid()\n",
    "grid1.teff = 5780.\n",
    "grid1.logg = 4.4\n",
    "grid1.mh = 0.0\n",
    "wave,flux=grid1()\n",
    "plt.plot(wave, flux)\n",
    "\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib nbagg\n",
    "\n",
    "x = np.linspace(0, 2, 1000)\n",
    "fig, ax = plt.subplots(1, figsize=(10, 4))\n",
    "plt.suptitle('Teff Logg Mh Sliding')\n",
    "\n",
    "\n",
    "def update_plot(teff, logg, mh,t,l,m):\n",
    "    \n",
    "    ax.clear()\n",
    "    handles, labels = ax.get_legend_handles_labels()\n",
    "    for h in handles: h.set_linestyle(\"\")\n",
    "    ax.legend(handles, labels)\n",
    "    \n",
    "    grid.teff=teff\n",
    "    grid.logg=logg\n",
    "    grid.mh=mh\n",
    "    wave,flux=grid()\n",
    "    ax.plot(wave, flux,'ro',label='first plot')\n",
    "    \n",
    "    grid1.teff=t\n",
    "    grid1.logg=l\n",
    "    grid1.mh=m\n",
    "    wave,flux=grid1()\n",
    "    ax.plot(wave,flux,'bx',label='Second plot')\n",
    "    plt.legend()\n",
    "    #This are the extra features that include label which is also updated as the input is changed.\n",
    "    '''\n",
    "    units = 'teff = {}  \\nlogg = {}  \\n mh = {} '\n",
    "    ax.plot(wave, flux , label=units.format(teff, logg, grid))\n",
    "    ax.plot(x, wave,flux, label=units.format(teff, logg, grid))\n",
    "    ax.set_xlim(x[0], x[-1])\n",
    "    ax.legend(loc=1)\n",
    "    ax.set_xlabel('$(s)$')\n",
    "    '''\n",
    "\n",
    "\n",
    "teff = widgets.FloatSlider(min=1, max=10, value=1, description='Teff 1:')\n",
    "logg = widgets.FloatSlider(min=0, max=5, value=0, description='Logg 1:')\n",
    "mh = widgets.FloatSlider(min=1, max=10, value=1, description='Mh 1:')\n",
    "t= widgets.FloatSlider(min=1, max=10, value=1, description='Teff 2:')\n",
    "l= widgets.FloatSlider(min=0, max=5, value=0, description='Logg 2:')\n",
    "m= widgets.FloatSlider(min=1, max=10, value=1, description='Mh 2:')\n",
    "    \n",
    "widgets.interactive(update_plot, teff=grid.teff.bounds, logg=grid.logg.bounds, mh=grid.mh.bounds, t=grid1.teff.bounds, l=grid1.logg.bounds, m=grid1.mh.bounds)"
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