diff --git a/docs/indicator-info.md b/docs/indicator-info.md
new file mode 100644
index 0000000..a57a569
--- /dev/null
+++ b/docs/indicator-info.md
@@ -0,0 +1,33 @@
+# Indicator info meta-data
+
+
+## Model
+
+Info attributes are stored as dictionary items in the `info` attribute of an indicator when available, or else as regular attributes of the indicator. 
+
+Most metadata attributes are treated as read-only except for `default_pane` which can be modifed by some primitives/modifiers ...
+
+
+
+## Retrieve metadata with `get_info`
+
+```python
+from mplchart.utils import get_info
+
+default_pane = get_info(indicator, 'default_pane')
+```
+
+## Known attributes
+
+```python
+same_scale: bool        # wether the output uses same scale as input
+defaul_pane: str        # wich pane to use for a new scale
+overbought: float       # overbought level
+oversold: float         # oversold level
+yticks: tuple           # force major ticks
+```
+
+## Design Questions 
+
+- Should we split main attributes like `same_scale`, `default_pane` from the other optional read-only attibutes ?
+- Should we have a `force_pane` uopdatable attribute to override `default_pane` read-only attribute. Main logic is in the `Chart.get_axes` method.
diff --git a/examples/matplotlib-backend.ipynb b/examples/matplotlib-backend.ipynb
new file mode 100644
index 0000000..f515465
--- /dev/null
+++ b/examples/matplotlib-backend.ipynb
@@ -0,0 +1,181 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-23T14:17:42.522901Z",
+     "start_time": "2024-08-23T14:17:42.505801Z"
+    },
+    "collapsed": true,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'module://matplotlib_inline.backend_inline'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import matplotlib as mpl\n",
+    "mpl.get_backend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-23T14:17:43.165847Z",
+     "start_time": "2024-08-23T14:17:43.061194Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# %matplotlib on its own will make the plot outside the notebook  \n",
+    "\n",
+    "%matplotlib inline\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(range(10));"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-23T14:17:44.831218Z",
+     "start_time": "2024-08-23T14:17:44.794557Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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(\n            '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\nmpl.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 = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(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 (fig.ratio !== 1) {\n            fig.send_message('set_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\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\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute('tabindex', '0');\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;' +\n            'z-index: 2;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute(\n        'style',\n        'box-sizing: content-box;' +\n            'pointer-events: none;' +\n            'position: relative;' +\n            'z-index: 0;'\n    );\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box;' +\n            'left: 0;' +\n            'pointer-events: none;' +\n            'position: absolute;' +\n            'top: 0;' +\n            'z-index: 1;'\n    );\n\n    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n    if (this.ResizeObserver === undefined) {\n        if (window.ResizeObserver !== undefined) {\n            this.ResizeObserver = window.ResizeObserver;\n        } else {\n            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n            this.ResizeObserver = obs.ResizeObserver;\n        }\n    }\n\n    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n        // There's no need to resize if the WebSocket is not connected:\n        // - If it is still connecting, then we will get an initial resize from\n        //   Python once it connects.\n        // - If it has disconnected, then resizing will clear the canvas and\n        //   never get anything back to refill it, so better to not resize and\n        //   keep something visible.\n        if (fig.ws.readyState != 1) {\n            return;\n        }\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            /* This rescales the canvas back to display pixels, so that it\n             * appears correct on HiDPI screens. */\n            canvas.style.width = width + 'px';\n            canvas.style.height = height + 'px';\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    this.resizeObserverInstance.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        /* User Agent sniffing is bad, but WebKit is busted:\n         * https://bugs.webkit.org/show_bug.cgi?id=144526\n         * https://bugs.webkit.org/show_bug.cgi?id=181818\n         * The worst that happens here is that they get an extra browser\n         * selection when dragging, if this check fails to catch them.\n         */\n        var UA = navigator.userAgent;\n        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n        if(isWebKit) {\n            return function (event) {\n                /* This prevents the web browser from automatically changing to\n                 * the text insertion cursor when the button is pressed. We\n                 * want to control all of the cursor setting manually through\n                 * the 'cursor' event from matplotlib */\n                event.preventDefault()\n                return fig.mouse_event(event, name);\n            };\n        } else {\n            return function (event) {\n                return fig.mouse_event(event, name);\n            };\n        }\n    }\n\n    canvas_div.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    canvas_div.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    canvas_div.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    canvas_div.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    canvas_div.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    canvas_div.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    canvas_div.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\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\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.canvas_div.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.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.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\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                img.type = 'image/png';\n            }\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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\nfunction getModifiers(event) {\n    var mods = [];\n    if (event.ctrlKey) {\n        mods.push('ctrl');\n    }\n    if (event.altKey) {\n        mods.push('alt');\n    }\n    if (event.shiftKey) {\n        mods.push('shift');\n    }\n    if (event.metaKey) {\n        mods.push('meta');\n    }\n    return mods;\n}\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    // from https://stackoverflow.com/q/1114465\n    var boundingRect = this.canvas.getBoundingClientRect();\n    var x = (event.clientX - boundingRect.left) * this.ratio;\n    var y = (event.clientY - boundingRect.top) * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        modifiers: getModifiers(event),\n        guiEvent: simpleKeys(event),\n    });\n\n    return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\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        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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 / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div id='0fb7daf6-6347-4298-b167-3bac8aa2d8cb'></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib notebook\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(range(10));\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-23T13:41:06.276578Z",
+     "start_time": "2024-08-23T13:41:05.399379Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x900 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "\n",
+    "import yfinance as yf\n",
+    "\n",
+    "from mplchart.chart import Chart\n",
+    "from mplchart.primitives import Candlesticks, Volume\n",
+    "from mplchart.indicators import ROC, SMA, EMA, RSI, MACD\n",
+    "\n",
+    "ticker = 'AAPL'\n",
+    "prices = yf.Ticker(ticker).history('5y')\n",
+    "\n",
+    "max_bars = 250\n",
+    "\n",
+    "indicators = [\n",
+    "    Candlesticks(), SMA(50), SMA(200), Volume(),\n",
+    "    RSI(),\n",
+    "    MACD(),\n",
+    "]\n",
+    "\n",
+    "chart = Chart(title=ticker, max_bars=max_bars)\n",
+    "chart.plot(prices, indicators)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.9.20"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/examples/mplchart-interact.ipynb b/examples/mplchart-interact.ipynb
new file mode 100644
index 0000000..09c74ee
--- /dev/null
+++ b/examples/mplchart-interact.ipynb
@@ -0,0 +1,321 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-11T13:54:44.279373Z",
+     "start_time": "2024-08-11T13:54:44.260581Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from mplchart.chart import Chart\n",
+    "from mplchart.samples import sample_prices\n",
+    "from mplchart.primitives import Volume, Candlesticks\n",
+    "\n",
+    "from mplchart.indicators import SMA, RSI, MACD, PPO, SLOPE\n",
+    "\n",
+    "from ipywidgets import widgets, interact\n",
+    "\n",
+    "from IPython.display import clear_output\n",
+    "\n",
+    "from matplotlib_inline.backend_inline import flush_figures, set_matplotlib_formats\n",
+    "\n",
+    "set_matplotlib_formats(\"svg\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-11T13:54:44.960029Z",
+     "start_time": "2024-08-11T13:54:44.939083Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plt.isinteractive()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-11T13:54:45.510770Z",
+     "start_time": "2024-08-11T13:54:45.484905Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "ticker = widgets.Text(\n",
+    "    value=\"AAPL\",\n",
+    "    placeholder=\"Enter ticker ...\",\n",
+    "    description=\"Ticker:\",\n",
+    "    continuous_update=False,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-11T13:54:46.502627Z",
+     "start_time": "2024-08-11T13:54:46.393654Z"
+    },
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "is_executing": true
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "749dedf630af4eb8826ed8ad76553e09",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(Text(value='AAPL', continuous_update=False, description='Ticker:', placeholder='Enter ti…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "indicators = [Candlesticks(), SMA(50), SMA(200), Volume(), RSI(), PPO(), SLOPE()]\n",
+    "\n",
+    "\n",
+    "@interact(ticker=ticker, max_bars=250)\n",
+    "def draw_chart(ticker, max_bars=250):\n",
+    "    if not ticker:\n",
+    "        return \"Nothing to show!\"\n",
+    "    data = sample_prices()\n",
+    "    chart = Chart(title=ticker, max_bars=max_bars)\n",
+    "    chart.plot(data, indicators)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-11T13:54:47.437858Z",
+     "start_time": "2024-08-11T13:54:47.418412Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0a53e81d7b5446dfb1657f13ee53e790",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(Button(description='Next Chart!', style=ButtonStyle()), Output()), _dom_classes=('widget…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tickers = \"AAPL,MSCI,AMZN\".split(\",\")\n",
+    "tickers = iter(tickers)\n",
+    "\n",
+    "\n",
+    "@interact.options(manual=True, manual_name=\"Next Chart!\")\n",
+    "def next_chart():\n",
+    "    ticker = next(tickers, None)\n",
+    "    return draw_chart(ticker)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-08-11T13:54:48.374827Z",
+     "start_time": "2024-08-11T13:54:48.332475Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7ce3f05f8cc049468adfac72c88249d7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(Text(value='AAPL', continuous_update=False, description='Ticker:', placeholder='…"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "output = widgets.Output()\n",
+    "\n",
+    "\n",
+    "def update_chart(*args):\n",
+    "    symbol = ticker.value\n",
+    "    with output:\n",
+    "        clear_output()\n",
+    "        draw_chart(symbol)\n",
+    "        flush_figures()\n",
+    "\n",
+    "\n",
+    "button = widgets.Button(description=\"Plot\")\n",
+    "button.on_click(update_chart)\n",
+    "header = widgets.HBox([ticker, button])\n",
+    "vbox = widgets.VBox([header, output])\n",
+    "vbox"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.12.7"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {
+     "1e4070fbc1ad4e2b972efa0c26cb1f69": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.2.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "57268dea02f74c879e57c489d206afed": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.5.0",
+      "model_name": "DescriptionStyleModel",
+      "state": {
+       "description_width": ""
+      }
+     },
+     "6e2d7204349549afa6f8bdc84746d79b": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.2.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "84227a48a7f248b9b823403ad5343ab7": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.5.0",
+      "model_name": "VBoxModel",
+      "state": {
+       "_dom_classes": [
+        "widget-interact"
+       ],
+       "children": [
+        "IPY_MODEL_d6816ca749c54810802e943cebab03c1",
+        "IPY_MODEL_8e80e884c5d3462f8beb41ce742f539a"
+       ],
+       "layout": "IPY_MODEL_1e4070fbc1ad4e2b972efa0c26cb1f69"
+      }
+     },
+     "8e80e884c5d3462f8beb41ce742f539a": {
+      "model_module": "@jupyter-widgets/output",
+      "model_module_version": "1.0.0",
+      "model_name": "OutputModel",
+      "state": {
+       "layout": "IPY_MODEL_a14d29c88a1445f3bef0774e5bc12849",
+       "outputs": [
+        {
+         "name": "stdout",
+         "output_type": "stream",
+         "text": "Plotting MSFT 190 ...\nlocator <charting.DateIndexLocator object at 0x000002008CB03B08>\nformatter <charting.DateIndexFormatter object at 0x000002008CB03A08>\n"
+        },
+        {
+         "data": {
+          "image/png": 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Ov53Hejnb4etqR05pFasPZfCHWzq0YLRCCHH9kaTUZcjwseYnj7kQQoi25mR2KV/sSyMx30ByvoGM4kosVuWi7U5kl7JtxjA0avmsFKK5xKYWcSa3HEOVGUO1peZ3lZnyKgsV1WYKDdXsTSoEoIOXE6Oj/dBrLx6xEO3vRk5pLl8dSOPxwWFyziuEEBeQpJQQQgghRDMzW6x8siORf29OwGSpm4TSqlW4O+pwd9Dj7qgjPqOEtMJKtp7MZWSUbwtFLETbYTRZeHvdcZbtSa3X9n1C2zGgg+dlk02d/JzZcTqP07nlxKYVc1NIO1uGK4QQrZokpYQQQrRJiqKQV15Fcn4FSfnlJJ37bbIo/PWurvi7ObR0iOIGlZRv4IWv4ohNrZnlN8zLiQ7eTrg76HB31OOk19S5uFUUOJhaxJJfkyUpJUQTS8o3MH35IY5nlQIQ3M4Be50GnUaNXqNGp1XV/q3XqvFw0uPran/FNu20GiJ8nDmZXcZX+9MkKSWEEBeQpJQQQog2oaTSxHexGRxIKSIpv5zk/ArKq8yX3Pa1b+NZOKWPDLEQNqUoCsv2pPDO+pNUmizoNWqGdvYm0s/lisdatyA3DqUWsfN0Pmdyy4jwcWmC2GzepBCtztrDmcz8Np7yKjMOOg2jon0J9XSySdvRAa6czC5j7eFM3rg9Cic7uQwTQgiA1jlNm7ikp556Co2m5ttVrVZLSEgITz75JEVFRbXbxMbGcvvtt+Pj44O9vT2hoaHcf//95OfnA5CcnIxKpSIuLu6y+zEajUyZMoWYmBi0Wi0TJky4Yly7du1Cq9XSo0cP29xRIYRogKMZJby66gj93/mZN9ccY+3hTI5mlNYmpFzttYR4ONItyI1B4Z5oVCq2nspj7ZGsFo5c3EiySip5ZOE+3vj+GJUmC8HtHHiofwhd/F2vmvx0ddAR5lVzYbxkd4rNY1uxL40X92r4+WSuzdsWojUwmiz83+p4nlkZS3mVmQB3eyb1DbFZQgog0N0BNwcdhmoL6+Ll80UIIc6TFP0NZvTo0SxevBiz2czx48eZNm0axcXFrFy5ktzcXEaOHMn48ePZuHEj7u7uJCUlsWbNGioqKuq9D4vFgoODA88++yyrVq264rYlJSU88sgjjBgxgpycnGu9e0IIUS9Gk4UfjmSxbE8KcWnFtcs9nfR09nPBw0lPO0c9rg5atOq6389YrAp7kgqZs/YYt3T0wt1R39zhC6DQUM3O03mM7OLbYj0KrFaFAylFlFSarridXqvG2U6Ds50OJzsNznZanOy06DRqFEXhu7gMZn1/jDKjGa1axaAIL7oHuTWoJ173YHcS8w2sOpTOS2M642pvm1lqs0uM/H1jAhZFxYJfkhkTE2iTdoVoaaVGEweTi/B3t6e9hxMOes0lt0vMK2f6ilhOnBuu1ye0Hf3DPFHbeFIBlUpFdIAru88W8PWBNO7rHWzT9oUQorWSpFQ9KIpCpcnSIvt20GkadNJqZ2eHn58fAEFBQdx///0sXrwYgN27d1NaWsqCBQvQamue+rCwMIYPH96gmJycnPj444+Bml5QxcXFl932T3/6E5MmTUKj0fDdd981aD9CCNFQKQUGlu1J4esD6RSfSySoVRDh40y3IHcC3Oyv+p7aO9SDhNxyCsqreWf9Cf5xb/fmCF2cYzRZWLgriXlbz1JeZWZQhCdLp/Vr9lnnqs1Wnv8y7pp6NNhp1TjoNRRX1ByLvq52jI7yo51TwxOdwe0c8HDSU2io5psD6Uy7OazRcV3obxtOUFFdc45zIKWYtMIKgj0cbdK2EC2l2mxl8oK9HE4vqV3m52pPe09HwrycaO/pRKinIyWVJv7yw3EM1RYcdBpGR/vS3oa9o36vi58rv54tYH9yEWfzygn3dm6yfQkhRGshSal6qDRZiJq1sUX2ffyt0TjqG/c0JSYm8uOPP6LT1Xyb6ufnh9lsZvXq1dx7771NXitl0aJFnD17lmXLlvH222836b6EEGLt4Uye/zIOs7WmOI6LvZaYQDei/F0b1NNGo1YxItKHrw+m89WBdCb0DGRguFdThS3OsVoVVsdm8P6mU2SWGGuX7zpTwH+3nOG5kR2bLZaKajNPLDvEjoQ81Crwcbl8EWMFBYtVodpsxWRRqLZYsZw7BqvMVqrMVtQq6BfmSe/27Rrd+0KlUtE9yI2tp/JY+msyUwaGXnNPjn1JhXwflwmAo1ahwqziu9gMnhnRfI91W1NttlJSacLLWS8165rQPzee5HB6CVq1Cq1ahdFsJbvUSHapkb1JhRdtH+juwJhoP5ztm/bSyNleS3tPR5ILKvjqQBozx3Zp0v0JIURrIEmpG8y6detwdnbGYrFgNNac1H/wwQcA9O/fn9dee41JkybxxBNP0LdvX4YPH84jjzyCr69tZ/M5ffo0r776Kjt37qztlSWEEE1l1cF0XvrmMFYFgto50DPEnVBPJ9SNvOgLcHcgJtCN+IwS/m/1UTY8Nxh73aWHfohr98vpfN5Zf6J2titnOy0Dwz1RgJ+O5/CfnxPoE9auWZKDJZUmpi3ez8GUIrRqFbd3829wzwmLtSY5ZTJbqbZYcdBpbDIEMdLPlV1nC0guqGB7Qh7DIn0a3ZbFqvDmmmMARAe4oK4sIb5IxbexGTw9PEISJjZksSrsSSxgTVwmG45mUWo0Mzral7/c2RWfq8zaJhpuy8kcPt2ZBMDYrn508HbGaLJQXGGiuLL63G8TJRUmKqrNRPq70i/Uw+bD9S4nOsCN5IIKVh3MYMaozug0UuJXCNG2SbagHhx0Go6/NbrF9t0QQ4cOZf78+VRUVLBgwQISEhJ45plnatf/9a9/5YUXXmDLli3s2bOH+fPn884777Bjxw5iYmIuai86OpqUlJqiqoMHD2bDhg1XjcFisTBp0iTmzJlDp06dGhS/EEI01Mp9qby2Oh5FqZndaHikT6OTURcaFOFJYn45SfkGPtpympdGR9ogWnGhk9ml/G39SbYn5AGg16jpE9qOHsHuaM9dqGUUVXI8q5Tnvohj/bOD8Xaxa7J48sqqeGThPk5klWKnVXNnjwD83Rwa3I5GrcJBrWnwZ/jV6LVqov1diU0rZvHu5GtKSq3Yl1p7PweEeZCcVMKJEhVJ+Qbi0orpKVPWXxNFUYhNK2ZNXCbr4rPIK6uqs37jsRx+PVvArPHR3HNToCQBbSS7xMiLXx0GoEeQOx3ODY+z12nwc9Pg59byScAwLyccdBryy6vYejKXUdF+LR2SEEK0KElK1YNKpWr0ELrm5uTkREREBAAffvghw4YNY86cOfzlL3+p3cbT05OJEycyceJE/va3v9GzZ0/ee+89lixZclF769evx2SqqYXh4FC/E/OysjIOHDhAbGwsTz/9NABWqxVFUdBqtWzatKnBdayEEC3LaLKQXlSJ0WTBZDk3TMlsxWSpGZ5kOjdkqVuQW+1FQHNYsju5trdHtyA3hnbyttnFnZ1Ww9BOPqyLz+KT7YmM7x5ApJ+rTdpu60wWK3/fcJKFu5KwKjV1v7oFutM3zOOiYsRDO3uTU2okr6yK57+MY8m0vk1SXyqtsILJn+0luaACR72GCT0CmzQB1ljdgtyITStme0IeiXnljXq9FRmqeX/jKQAGdPDEQa9Bq4ZwbydO5ZSzOjZDklKNlF5UwfK9qaw9nEl6UWXtcjutmo4+znTydcFep2HziRxyy6qY8fVh1h7O5J27Ywh0b3gCVPzGYlV47otYiipM+LjYMaijZ0uHdEkatYou/i4cSi3mqwPp131Sqspc8/nv4ahvVD08IYS4mtaRaRGN9uabbzJ27FiefPJJAgICLlqv1+sJDw/HYDBc8vbt27dv8D5dXV2Jj4+vs2zevHls2bKFb775hrAw2xRnFULYnsWqkFpYwansUk5ll3Mqp5ST2WUk5xs4VybnqnqGuHPPTUGM7xaAm6NtZgi7lE93JPLX9Sdq9zk4wsvmvQ0ifJwJ93bibJ6BV1fFs+rJgc1ecPtGU1BexdMrYvk1sQCoeYwHhXtedpZDnUbN2K5+fLE/jV/O5DN36xmetXHNo9M5ZUz+bB/ZpUZc7bXc1TPwup110d1RT5iXE0n5Bpb+msLsO6Ib3Mb7P52iuNKEp7OemEA3wApApJ8zp3LKWROXyevjotBrZVhRQ2SVVHLnf3dRYKgGQKdR0cHLmU5+zrT3cKrz3nF/72AOpRaxJ6mQ7Ql5jPpgOzNv68KkviHNNozsRvPhz6fZm1SITqNiTFe/i2ZWvZ5EB7hxKLWYradyyS01tvgwzjKjiaR8AykFFaQWVpBS8Nvf2aVGFAU8nfVsfn6IJKaEEDYnSakb3NChQ4mOjuadd95hzJgxfPHFFzzwwAN06tQJRVFYu3Yt69evZ9GiRQ1q9/jx41RXV1NYWEhZWRlxcXEA9OjRA7VaTdeuXets7+Pjg729/UXLhRDXh+V7U/hiXxqnc8swmqyX3EavUaPTqtCoVGjUKtTq3/7WqFRYFIXsUiOxqcXEphbz1g/HubWLL/f0CuSWjt61w7Fs4b9bTvPepgSgZvruAR08m2z4y9BOPqQVphCXVsyyPSk8OjC0SfbTFhzLLOGPSw+SUVyJTqNiVJQfET5X7+nj6WzH8EgfNh3P4d+bE+gT6sGAcNv0gjicVsyURfsoqjDh4aTnrh6BTV7s+Fp1D3IjKd/ANwfTmTG6M84NqFd1LLOEFXtTARjayRu1WoX13Es+qJ0DTnoNxZUmtp2SYUUNYbJYmb78EAWGajyc9PQL8yDMy+my9YLUahW9Qz0I93bmpxM5ZJUYef27o/xwJJO/39OtSWeAux4YTRY2HstmZBdfm9Rb+/VsAR9tOQ3A8Egf2l2nSeXzPJz0+LvZk1ViZNWhDJ4cGt4icZzJLWP+9kS+j8vAZLnyN08F5dXM3XqG12+PaqbohBBtxfV91iVs4oUXXmDq1KlMnDgRR0dHXnzxRdLS0rCzs6Njx44sWLCAyZMnN6jN2267rbbWFEDPnj2BmhoKQojWQ1EU/vPzaf69+XTtMo1ahaeTHk9nPV5Odng66/F0tsNJr7lq4sdQZeZUdhnHs0spKK9mXXwW6+Kz8HK2Y0KPAMbG+BMd4NroouGKovDBTwl8tOUMAP07eNAvrGmHaDjbaxkY4cm2U3n848eT3BrlS4AMs2mwNYczefmbwxhNVtwcdIzv5o+nc/2Hx3XxdyWtqIITWWU8+0WsTepL7T6bzx+WHMBQbcHX1Y47ewTavA5UUwjxcKSdo46iChOrDqbXO1GqKAqz1xzDqkAnH2eC2jnWWa9WqejsVzOsaHVshiSlGuDdDSc5lFqMXqtmfDf/eve0a+ek595eQRxJL2HXmXz2JBYy+t87mD0+mgf6hjRx1C3n/1YfZdWhdMZ3D+CjB3teU1sFhmqe+yIWqwJR/q6tZph1VIArWSVGvj6QxhNDOjRrXbGDKYV8vC2RzSdyapc56jW4Oehwd9Dh5qDDzfHcbwcduWVVfB+XyZJfk3l0YCjBHo6Xb1wIIRpIklI3kHnz5uHqevEH8aRJk5g0aRIAQ4YMuWIboaGh9UosJScnNyi22bNnM3v27AbdRgjRtBRF4b1Np5i79SwAfUM9iPR3wc1B1+hC4U52Wm5q346eIe7klVdxIquMU9ll5JdXseCXJBb8koROo6KLvyvdgtzoHuROj+CaYrRXGhZntlgpNZr5ZPtZPtmRCNQUIu/d3qNRcTZUt0A3TmWXkVViZNb3R/n0kd5SmLieLFaFf2w8ySfba5639p6OjIn2a1RiclhnH3JKq2xSX+r7uAxmfH0Yk0UhqJ0D47sFtJrhaiqViu5B7mxLyGPJr8lM7t++XkO+1hzOZH9yzayCN3e89EyGkX6uHEot5ucTuZRUmJp0CO6NYkN8Fp/9UjPb26go3wYP/VSrVPQIdifMy4nNJ3JIL6rk1W/jSS6o4OXRnW+44Xx7EwtYdSgdgLWHM3n85jC6B7s3qi2rAq+sOkpuWRUejnqGdva2ZahNqpOPCzsS8kjMN/B9XCZ+bvaUGc2UVpooNZpq/y4zmuns58JD/UOw0zY+aW61Kmw9lcv87WfZn1xUuzzc24ne7T2uWAS+vYeGYA8H0lvUzIsAACAASURBVAoreX/TKf79wLUlEoUQ4kKSlBJCiDZIURT+tuEk/zuX4Bnc0YubbFjYWKVS4eNij4+LPTdHeJFSYOBEdhkZRZVUmiwcSS/hSHoJy6gZRuSk1xAT5EaYlxNlRjMllaY603eXGc112h/SyZsejbyIaez9GRHpw4p9qWw+kcuPR7MZG+PfbPtvrUoqTDzzRSw7zs2u16t9OwaGezY66anTqLntgvpS87ae4ZkG1pdSFIVPdiTy7oaTQE1Nq9FRvjYdXtocuvi7svtsAYl5Bn45k88tna58MW6oMvPOuRpsfUI9cLG/dLLJ28UOL2c9+eXV/BCfyUP9Gl5b8npltljJLjVe1EPsWiTlG3jpmyMA9AppR/g1TPTg5qDj7p6B7E0qZG9SIfO3nyWtqIL3J3ZvdO/S643JYuWN748CNUPCqy1W3ll/gi/+2L9Rif5tWSq2p+SjUasYG+N32eGS1yO9Vk1HHxeOZ5Xy5y/jrrr90l+TefOOaIZ1btism9VmK2sPZ/LJjrMk5JQDoFGpiPR3oVdIu3rViFKpVNwc7sXKwjS+i8vk8cEd6Bro1qA4hBDXn9DQ0Dqjn8576qmnmDt3LlVVVcyYMYOVK1dSWVnJiBEjmDdvHkFBQTaNQ5JSQgjRxiiKwpy1x1m8OxmoqSvT2G+p60OjVtHB25kO3s4oikKZ0Ux2qZGcUiM5pVXklhkxVFvYk1jInsTCK7bloNMwMMKTrgHNfzLs6WxHr/bt2J9cxMfbz0pS6ioScsr4w9IDpBRUoFWruDXKl06+LtfcrqezHcM6+/DTiRz+tTmBniHtLtvr5/csVoW31h5jya81J2A9g90Z3NH2BfKbg16rJsrflbj0YpbsTr5qUuq/W8+QU1qFm4OOm0Ku/Hrv4ufKzjP5fHso47pKSmWXGHF31DUqQVNkqOaRhfuIzyjhrTujeWRA6DXHU1lt4cllBymvMhPgbm+TOmcqlYr+HTxxc9Cx+UQO645kkV1i5NNHeuNRj+SB0WThu9gMCiuq+cPgDtddkmbRriQScspx0Gm4q2cgXx5IY29SIVtO5jKii2+D2jqcXsLa1Jr7N6SjN14NGA58vbgpxJ20ogosVgU7rRo7rQY7rRq9Vl3zv06DRqXiaGYJyQUVTF20n5FdfJl1exQhnldOruaWGlm+N5UV+1LJK6sCahKBMYFu9Ahxb1AtOgAfV3s6+7lwKruMv204wbLH+rXK904hxG/279+PxWKp/f/o0aPceuutTJw4EYA///nPrF27li+++AJPT09efPFFbr/9dg4ePIhGY7svSyQpJYQQbYjVqvDG90dZfq7Q8fBIn3OzbzUPlUqFq4MOVwddbYLCqigUGqrJKTVSZjRjr9Ngf+5k3F6nPvd/zYl6Sw9j6RHszsGUIo6kl3Aiq5Qu/q2jdklzS8gp456Pd1NmNONir2V8t4Brrv90oagAV9KLa+pLPfzZXsZ29ePZER2v+HwYTRaeXRnLpuM1NVRs3TuwJXQLdiMuvZgtp3JJKTBctjh2Ur6BBTtrekXe0tHrqr3COvu58MuZfA6mFF2x3ea0OjadF786TIC7A5892ofOfvVPcOaVVfHwgr2cyikDYM7a40T4ODMwvH7JzMuZ9f1RTmaX4aDTMLarv01n5uzi74qznZYf4rM4mFLE3fN2sWhqX8K8Lv1cVFSbWbE3lU93JpJT+lsC4vHBHWwW07XKLK6srV94c4QX3i52te+p7244yZBO9Z8Qo6TCxJ+/OoJVURHh7UTXwNb5XuzpbMe0QVeflfqm9u7sSyokLq2YzSdy2HE6jyeGhPPkkHAc9L9dGCqKwqHUIhbvTmFDfBbmc9PmOuk1dA92p1ugG3bX0OtuYAdPzuSUs+tMATtO5zPkKslwIcT1zdu77mv43XffJTw8nCFDhlBSUsJnn33G559/zsiRIwFYtmwZwcHBbN68mdGjR9ssjjadlDKZTJhMpouWKYqC1WrFar30DFTXo/N1oM7H3hpZrVYURcFkMtk08ypubOdfw79/LYuLWawKr39/nG8OZaACxnf3o2czDoG7Eg9HLRHe13/hVHcHDZ19nTmRXc6X+1L4v9siL9qmrR+TeWVVTFm4jzKjmSB3ex7sG4Sj3vanGxO6+6NRwdHMMjYczWbD0Wxu7eLD08M6EPW75FShoZonlscSm1aCVq1iQo+agvutnbuDAxHeTpzJMzB7zVFiAt0oqjBRXFFNUYWJoopqigwm8g3VmCwKEd5O9Ax2vah3g8UCzjoFN3sNGo0GdwcNHbydOJtnYNWBNJ4Z3jIzg5234Wg2L351BKsC6UWV3P3xLv59XzeG1uOCOKvEyKOLDpBUUIGznZYAd3sScsqZvvwQq57oR3Ajh/J9fTCDrw+mowIm9gogyN32vXTcA13wc9WzYl86yQUV3DV3Fx8/1IPe7X9LppYZzSzfm8rC3SkUVdS859hp1VSZrfzn59PcHuOLZz16WDWHOWuOUlFtIcTDgQEd3FGpVIyM9OJ4Zgmnc2veU+/rffUhIVarwvNfxpFeVImTVmFCd1+crvMZM6+dhvHd/Ogf1o4NR3NIKqjgw59Ps+pgGq+N7cyQjl78EJ/N53tTOZZZVnur4HYO9A1tRxd/F5skTd0dNPQJc2dPYhF/W3+Cfu3dbJqMvd619c93cf07f2yWlpbWWW5nZ4ed3ZU/p6qrq1m2bBkvvPACKpWKgwcPYjKZGDVqVO02AQEBdO3ald27d9s0KaVS2uB0aaWlpbi5ubFixQocHeuejGi1Wvz8/AgKCrrqEydsq6qqivT0dLKzszGbzVe/gRCi3qwKrDijZn++GhUKD0VY6ePd5t7+beJYkYr/ndTgpFV4q5eFVlIbu1lUWeCjYxrSDCq87RWe72rBqYnrZGdWwKZ0NXEFKhRqLo5i2lkZHWQl2BnyjTD/hIY8owpHjcLjkRbCW38+qtbxIhWfnLz6FzkOGoXnYyz41nPiyAN5Kj4/o8HLTuH1nhZaapROfKGKhQlqrIqKPt5WiqrgTGnN+9id7a0M9VcuG1uBEeYe11BQpaKdXmF6lAU3PXx47hgNcFT4c1cLdg38HizdAP+O12BSVIwLtjAqqGnfS0ur4dOTGlINKjSqmvfvSDeF7VlqdmSrqLTUPACedgojA6309lL491ENGRUqBvlaua9Dy39Zef44VaPwUjcLARd0+NqWpWJ1sgZXXc2xdrXnY3OGirWpGrSqmucvuPFlvFolRYHDhSpWJ6sprq557vVqhWprzd9alUIvL4XBftYmeWwMJvhLrIZKi4qHIiz0lXMJIa4bFRUVtROcXejNN9+86qRjX331FZMmTSI1NZWAgABWrFjB1KlTqaqqqrPdqFGjCAsL45NPPrFZ3Df61wpXNGrUqItmq7NarSQlJVFaWoq3tzc6na5VjJdWFAWDwYCTk1OriPf3FEWhtLQUR0dHRowYIT2lRL2ZTCZ++uknbr31VnQ6mSXqUpLyDfxz02n25+eiUat4/95ujIuRqd4ba5TFyvfv7ySnrApd6E2M7Vr3sWyrx6TFqjB9ZRxphjzaOepY+cd+tL9KzRNbeRw4nVvO3G2JrD+aTXyRmvgiNUM7eRGfUUqBsZoAN3s+e+QmInxurCvYMVYFNp8hMd+Ah5MeD0cd7o462jnqaedUM717Oyc9vi52l63FdKljdmi1mVV/305+lQX/mIFXrUPVFHaezmfJ8lisisL4bn78854YLFaFOT+c4KuDGXyXosHOO5BZ47pcNHNiYp6BRxYfoKCqihAPB5ZO7U2ge01Grt8tRu76eA+Zhmq2GgL5z/3d6n3uVGY0MeHjPZiUSoZ08uKDh3o2y7DiO6stvPhNPD+dyGXpaQ0OOjWVpppkUwcvJ54aEsa4GL/a4W/+XQt5eOEBfs1V89rEQTap59ZYRpOF9z7aDVQydVAoj4/pXGf9SLOVAx/uIq2okkyXSKYPvfyQw71JhazbcwCAN8ZF4l5wrM291wKMA/5cbWb+jiQW/JJMtQX83ex5qG8wE3sF1qv+2LUo8kjin5tOsyXPiZmTBl3TkMDWpK1+vovW43wPqbS0tDp5jvp0tvnss88YO3YsAQEBV9xOURSb5xvadFJKp9Nd8g2lQ4cOZGVlkZWV1QJRNY6iKFRWVuLg4NAqk1JQU2smODgYe/vLT0krxOVc7vXcVlmtCtsT8li8O5nt52Y+02lUfPRgT8Z0lQLd10Kng3t6BTFv21lWxWZxR8/gy2zXto7Jd9Ye4+eTeei1ahY82psIv+YtRh8V2I65D/XiTG4Z/91yhjWHM9mWkF+zzt+VRVP74Ot6Y36+zBwXZZN2Ljxm3XQ6xnT149tDGaw5kk2/8OatHfPr2QKeXBGHyaIwtqsf/7q/Z23C5e/3dqeTnyvvrD/BlwcySCms5OOHetXOInYyu5SHF+4nv7yaCB9nlj/er85zH+KlY/7kXkz6dA8bjuXQdVcq04dFXDWmimozr6w+TmphJYHuDvzngZ7Y2TXP0DidTsf8yb15Z/0JPvsliUqTlSh/V54eHsGYaL+LEmM3d/JlTLQfPx7L5m8/nubzx/q22Pnhf7clkVZUiZ+rPc+PikSnq3v5odPBy2MieWZlLJ/uTOKh/qGXrEGXW2rkz1/FY1Xg7psCebBvCBs2HGtz77Xnuel0vDI2ikn9QkkpqKB/B49mm0X0scHhLNubRlaJkeX7M/jTkJYd4tvc2uoxJ65/549LV1fXizrfXElKSgqbN2/m22+/rV3m5+dHdXU1RUVFtGv327Dx3NxcBg4caLugaeNJqcvR6/WEhIRgNpvrVKO/nplMJnbs2MEtt9zSat8kdTqd9JAS4hqVGk18cyCdpb8mk1xQAYBKBSMifXhyaAS92rfuws7Xi/t6BzNv21l2nM4js7iSAPd6jolqJkn5BnQaFUGNrJfTUIt2JbFoVzIAH9zXnV7tPZplv5cS4ePCvx/oyTMjOvLpjkSsisIbt0fhYt86Pxtb0t09g/j2UAY/HMli1vgo7LTN8xl9MKWQx5bsp8psZUSkD/95oGedi22VSsXjgzvQwduJZ1fGsSexkAnzdvHZo32orLYweeFeiitMRPm78vljffG8xKxsfUI9mHNHV15bHc97m04R6edy2dnfzBYrXx9M518/JZBbVoVOo2LeQzfh7ti8tZo0ahVv3B7FzRFeaNSqq84c+dptXdhyMpdfzuTz84lcRkY1bHY7W0jKN/Dx9rMAzBofddkZ38bF+LNgZyKH00v48OfT/GVC1zrrzRYrz6yMJb+8is6+Lrw9oSsqlQwbAwj2cCTYo3lrMtrrNLw4qjMzvj7M3K1nuL9PcLO/HoQQtrNo0SJ8fHwYN25c7bJevXqh0+n46aefuO+++wDIysri6NGj/OMf/7Dp/iUpdRkqlapVZcE1Gg1msxl7e/tWE7MQwjasVoUzeeUs35PCNwfTMVTXJNNd7LXc3zuYyQPaXxezZ91IQr2c6Bvmwb6kQlYdTOeZER1bOqRaR9KLuefj3VgVmNy/Pc+P7ISbY9N9Lmw6ls1bPxwH4JUxkdze7crdvptLuLcz797TraXDaNUGhHvi52pPdqmRrSdzm6WX5ZH0YqYs3E9FtYXBHb2Y+9BNFw3NO294pC+rnhzIY0v2k1JQwV3zdoECZVVmegS7s2Rq3yse+5P6hXA8q4Rle1J57os4vps+kAif34a5KYrCT8dz+PuPJzmbZwAg2MOBt+7oSvcWnCRiWKRPvbYL8XRk2s1hzN9+lr+uP8Etnbwv+1g2BUVReHPNMarNVm7p5H3RUOcLqdUqXh3bhQc/3cOKfalMGRRKuPdvQ23f/ymBvUmFOOk1zHv4Jhz1Wik23cLu6hnIgp2JnMwuY+7WM/yfjXpsCiGal9VqZdGiRTz66KNotb+lh9zc3Hjsscd48cUX8fT0xMPDgxkzZhATE1M7G5+tSFJKCCFaAaPJQnpRBSkFFaQWXvjbQFpRJdXm3wrZRvg48+jAUO7uGYjTZb6VFtfu/t7B7Esq5OuD6UwfFtEsdWWuxmiy8MJXhzFZanoQLN6dzPdxGbw4qjMP9g2x+SxJR9KLee6LOBQFHuwbzBNDrp/p58W106hV3NkzgE+2J7LqUMYlk1IWq0J8Rgl7EwsI9nDktpjGJ65OZJUy+bN9lFWZ6Rvmwf8m975sHazzOvu58P30QTyx7CD7k4sA6BvmwcIpfS7bK+dCs26PJiG7nH3Jhfxh6UG+mz4INwcdB1MK+dv6kxxIqWmznaOOZ4Z35KH+Ic3WY8wWpg8L55uD6STlG1j6azKPD26+1+iGo9nsSKgZ0vvWHdFXHT44INyTEZE+/Hwyl3/+eIr5k3sBsPl4Dh9vq+lt9Y97u9dJVomWo1GreHVsJFMW7WfJ7hQeGRDa7D22hBDXbvPmzaSmpjJt2rSL1v3rX/9Cq9Vy3333UVlZyYgRI1i8eLHNRzfJ1YoQQlzHUgsq+OemU6w7kon1CiMVtGoVQzt7M2VgGIMiPFttbbnWZGyMH2+uOUZqYQV7kwoZEO7Z0iHx3sZTnMktx9vFjrfuiOaDnxI4nVvO698dZfneVN4cH0X/DraJM72ogmmLD1BpqunR8tadXeW4uwHd3TOIT7Ynsu1ULkWGatwddZzNK2fXmQJ2ncnn18QCyoy/zZi7+qmB9Axp+DDhxLxyHl6wl5JKEz1D3Fk4pQ8O+vqd9Ho627Hs8X7866fTlBlNvD4uqt631WvVzHv4Ju746BeS8g1MX34IJzsNG4/lAGCvU/PYzWH8aUg4rq1wCKiLvY6XRnfilVXx/Ofn09zVM/CSwxltrbzKzFtra3pQPjkknFCv+vXWfXVsJFtP5fLjsWwOJBfi42LPC1/FATB1UCjjuklNxOvJkE7eDAz3ZPfZAj74KYF/3d+jpUMSQjTQqFGjUJRLX2TY29vz0Ucf8dFHHzVpDJKUEkKI61CRoZqPtpzh8z3Jtb1enPQaQjydaO/hSHtPR0I8HQnxcKS9hxMB7vbNVuBU1HDUaxnfPYCV+1L56kBaiyel9iQW8NmuJAD+fk8MwyN9uTXKl2V7UvjgpwROZJXywP/2MC7Gn5m3RV5TvanjmaU890VNfZdIPxfmPXQTOjn+bkid/VyIDnDlWGYp05bsJ6OoktyyutNDu9pr8XS2IynfwFs/HOfbJwc2KEFptSq89M0RCgzVdA10ZfHUvvXq5XQhO62GV8dGNug253k52/G/R3pz7/zd/HKmpji+WlVTO+7PIzvh59a6C+Tf2yuYpb+mcCyzlH9tTuDtCTFNvs9//niS7FIj7T0deXJo/Ytgd/R14f4+wazcl8bb605gtlopNZrpGeLOzLFdmjBi0RgqlYqZY7sw/r+/8F1cBk8MCaezX8vN9CiEaJ0kKSWEENcRo8nCol3JzNt2prb3wS2dvHl5dGeiA1ylJ8p15r7eQazcl8r6+Czm3BndYj0pyqvMzPj6MIpSM6xweGRNQWOtRs2UQWHc0SOQD346xYq9qayLz2LziRweHxzG/b1DCPGsf3IqLq2Y/245zeYTuQD4utqxcEofKSJ+g7urZyDHMkuJTS0GwE6rpk+oBwMjPBkU7kXXQDfyy6sY9t42YlOLWXM4kzt7BNa7/W8OpXMwpQhHvYb/Te6Nm0PzH09dA914f2IPXll1hP4dPHllTGc6+t4YF9catYpZt0dx///2sGJvKg/3b0+kX/1nZWqoFXtTWfJrCgBz7oi+6hDM3/vzyE58F5tJXFrN8dbOUcfcSZevLSZaVkyQG6OifNl0PIfVsRmNTg4LIdouSUoJIcR1wGJVWB2bwfubTpFVYgRqprGfeVskgzs271Tsov56BLvTydeZhJxy1sRl8nD/9i0Sx1/XHSe9qGaa+tdvv7g3gYeTnrcnxPBQv/bMWXuMPYmFzN16lrlbz9Ij2J07ugdwezd/fFwv3SNkX1IhH205zc7TNb1IVCq4vVsAM0Z1uu5mHhS291C/9qQXVeJkp2FQuBc3tW93UaLB19Wep4aG896mBN7dcJJRUX71GkJXZKjmb+tPAPDnkR1b9Hga182f22L8bsjkf78OntwW48f6+Gz+8sNxlj3Wr0nu546EPN74/igAz4/sxNDO9SvKfiFfV3v+MDiMD7ecQaWCfz/QU95nrnMTegay6XgO6+IzeWVM5xvyNSSEaDqSlBJCiGZktSoUV5ooKK8iv7yaAkMVeWVVfLk/jZPZZQAEuNkzY3RnJvQIvC6KZ4vLU6lU3Nc7mLfXneDrA2ktkpTaeiqXlfvSAHhvYvcr9lrq4u/Kyj/0Z+OxbJbtSWX32Xzi0oqJSyvm7XXHGRDuyR3dAxgT7Y+rg5ZdZwr4cMtp9iUVAjU9Lib0COSpYeFSbLgNcdBrmH1H9FW3e3xwB1buSyOjuJL/7UjkuZFXn5XyHxtPUVRhopOvM1MHhdki3GtyI19Mzxzbhc3Hc9l1poDNJ3K5NcrXpu2fyi7jqeWHsFgV7u4ZyLMjIhrd1hNDw8kuNdKrfTuGdJIvZq53wzr74KDTkFZYSXxGCd2CWm52SiFE6yNJKSGEaEKlRhNvrT1OfHoJBYYqCg3Vly1Y7mKv5elhETw6MLTBwx1Ey7mrZyDvbjjJ4fQSTmaXEu7ZfN/oF1dU88o3RwCYNiisXnWtVCoVY7r6M6arP7llRtYdyWLN4UxiU4vPFa8u4PXvjhLs4UhingEAvUbNvb2DeHJIuMyuJC7LXqdh5m2RPL0ilvnbz3JfnyD83S7/ejiUWsQX+1MBeHtCjNQla2LBHo48NjiMj7ed5a/rjjOkk7fNhsTllhqZtng/5VVm+oV58Ld7Yq4pweeo1/KPe7vbJDbR9Bz0GoZ38WHdkSzWHcmSpJQQokHk018IIZpIqdHEI5/t45uD6ZzKKSO//LeElLujjg7eTvQN9WBsVz+eHdGRHS8N409DwiUh1cp4OtsxsktNj4Ov9qc3675nfX+M3LIqOng78fKYzg2+vY+LPVMHhbH6qUHsfHkYL43uTKSfCyaLQmKeATutmqmDQtn+8lDeuStGElLiqsbF+NO7fTsqTRb+8eOpy25ntlh547ujKArc2yuIvmEezRhl2zV9WAReznYkF1Swcl+qTdqsqDbz2JIDZBRX0sHbiU8m98JOK59jbc3tMTUzI66Lz7rsTF5CCHEp0lNKCNEoJ7JKWbQriamDwuji33QFU1urMqOJRxfuIy6tGHdHHe/eHUOIhxNeznraOemlR8AN5v4+wfx4LJvVsem8OLL+M01di/M9nDRqFR/c1+Oak5nBHo5MHxbB9GERJOSUcTyzlEERXni7NP308eLGoVKpmDU+ijv+u4vVsRk8MqA9PUPaXbTdsj01s8G5OeiYKYWRm42znZbnRkTwxvfHWLI7mcn921/TMHGLVeG5L+KIzyjBw0nPoil9cHfU2zBi0VoM7eyDo15DelElR9JL6B4svaWEEPUjV0VCiAYzWaxMX3GIrw6k88D/9nA0o6RR7cSlFTf6ttez8iozjy7cR2xqMW4OOpY/3o8xXf2JCnDFx9VeElI3oMEdvfB1taOowsTPJ3ObfH+5ZUZe/y4egKeGhtPDxif/nXxdmNAzUBJSolG6Bblzb68gAN764fhFvSZyS428vykBgJfHdMbTWY6z5nT3TUG42GlJzDfwy5n8a2rrnfUn+Ol4Dnqtmk8f6UV7TycbRSlaGwe9hhHneg2vi89q4WiEEK2JXBkJIRps6a8ptbVmSipNPLRgb4OSS4qi8NHPp5kwdxd3/PcXVuy1zRCC60F5lZkpC/dx6IKEVHSAW0uHJZqYVqOuvQhfdSizSfahKAplRhNphRXMXBVPUYWJKH9Xnhl+9WLSQjS3l0Z3xlGvITa1mDWH674m3l53grIqM92D3XmgT0gLRdh2Odlpuefc+9XSX1Ma3c7SX5P57JckAN6f2J1e7WUIZls3LsYPqOnJK0P4hBD1JcP3hBANUmio5j+ba77hfu22SDYczSY2tZiHFuxl+eP96Bp45QSM0WThlVVH+D6u5iLFqsBrq+PJK6vi2RERrXrmI0OVmamL9nEgpQhXe229Hg9x45jYK5i5W8+y80w+w10a14bVqrD5RA6bjudQZKimuNJEcUU1xRUmiitNWC6okq/XqPng/u42K1QshC35utozfVgE/9x4inc3nGRUlB8Oeg27zuSz5nAmahW8fWdXNDLDaIuYPKA9i3cn8/PJHNIKKxpcL27ryVxmrzkG1CQgx3cPaIowRStzfghfRnElcWnFlxy6K4QQvydJKSFEg/zrpwRKjWa6+Lvy2M0deLBvCI+e6xl0tcRUbpmRPy49SFxaMVq1ijl3RpNTYuTDLWf41+YEcsuMvGWji5SC8ipW7kvlm4PpVJmtuDvqaeeoo53Tud+O+pofJx0dvJzpFuR2TQmxmoTUfvYnn09I9ZeEVBsT6uVEvzAP9iYVsidXxaQG3NZksfJ9XCbzt5/lTG75FbfVa9V4O9sxY3QnIv2knpu4fj12cxgr9qaSUVzJJzvO8uTQcN74/igAk/u3JyZI3iNbSri3M4M7erHzdD7L9qYwc2yXet82t8zIMytjsSpwX+8gnhraPHX0xPXPXqdhZBdf1hzOZH18liSlhBD1IkkpIUS9ncouY/nemq7+s26PQqNW4WKvY8m0vkxZtJ+DKUVM+nQPyx/vf9HFxrHMEv6w5ACZJUbcHHR8/NBNDIzwAsDLxY431xxj+d5UCsqr+fcDjS/aHJ9ewuLdyaw9nEm1xVq7PKvEeMXbBXs4cEf3AO7sEUgn34Z1c6moNjN18X72JRfiYq/l88f6ycVWG3Vf72D2JhWyIV3D+P/uZlS0HyOjfIkJvHTSs7Lawhf7U/l0RyKZ545RFzst9/cJJsLHGXdHHW4OetzPJVLdHXUyO6NoNex1GmbeFsnTK2KZv/0snHM++gAAIABJREFUhYZqEvMMeDnb8eLohs8WKWzrkQGh7Dydz1f703h+ZKd6v7f866cEyqvMdAty4693xbTqHs7C9sZ182fN4UzWHcnitdu6yPEhhLgqSUoJIepFURT+8sNxrAqMif5/9u47ruqyfeD45ywOG2SDDPdAxIHiTM2ZK82RPzO1tEfbmZZlZfqU9fS0rEytnjRHQ0tTK1NTU1y4UFQQFRURkSl7H875/v44SpGooCjrer9evIrzXdf3eAPnXOe+rtuDLo2dS7bZWepY9njHksTUuK/38+0TnQj0Njdf3hKZyLRV4eQbjDRysWHJYx1p6PJXM9QJXRrgbKPnxdXhbI5MZOLSg3w1oQMOVrpyxWY0wW/HE/j24CXCYtNLHm/j7cDErg1o4mZLWq65BCo9r4j0PAPpuUWk5xWRlltEeFwGcWn5LNxxjoU7ztHCw45hbesztI0n3vXKLmnIzDdwKT2PS+n5LN0Tw8GYNOz05oSUrDhTdw1p48mfUUlsikjgVFIOp5LO8tmfZ/Gwt6Svvxv9/D3o3MiJ/CIjK0JjWbbvAmm5RQC42OqZ3L0h4zr7Ym9ZvrEvRHU3uLUnyxtc4NCF9JL+RbOHtJQxXg30buFGfUcr4jPy+fXYZUZ38LnlMacSs1h9KA4wfzglC3eIf+rZzBUbCw2XMws4GpdBe5ktJYS4BUlKCfEP2QUGTCZwsJYXzH+3LSqZPWdTsdCoeW3Q9dP8r82Ymrj0IGGx6Tz69QG+faITe89e4f0tp1AU6N7EhYWPtC/zuR0c6Ek9Gx1TVoRxICaNMV+GsnxSMO72lmXGk5lv4HRiNnuik1l+REPmAfNKZDqNikGtPXmsa4NyTxvPKypme1QyG8IvE3ImmVOJ2ZzafIr/bj5Fxwb1uK+pK2m5RVxKz+dSeh7x6flkFxaXOoetXsuKycGVvgqaqFn0Wg2fjAmkm+UldH5t+fN0KiFnUkjMKuDb/Rf5dv9FbPVaTIpCXpERAF8na6b2bMTI9t4yC0rUOiqVijeHtOLBhXtQFOjSyJkHpf9QtaBRq3i0sx//3XyKFaGxjAryvuWslnc2RmFSYFBrDzo0kMbm4nqWOg19/d3ZEG6eLSVJKSHErUhSSoi/iUvL46FF+8gtLGbhuHb0buFe1SFVC4XFRt7ZeBKAyfc1xNe57NlDtnqtuZRvqbnZ94hF+yi+2ph5Qhc/3hzij/Ymn6p2bezCqimdeeybQ5xKzGbEon1883hHFMX86eypxGxOJWRxOjG7pNTJTIWLrQXjOvkxrpMvbjdIZN2ItYWWoW28GNrGi4y8IjZFJLIhPJ4DMWkcupDOoQvpZR7nbGOBdz0rfJ1tmNqjkfSQEiVsdDCorRejO/pRYDASeu4KW6OS2HYyieTsQgBaetrzVK/GDArwuOnPhRA1XWtvB57q2ZhNEYm881CAlPNUI2M6+jB/2xlOxGfesjH1ztPJ7I5ORadR8coDLe5hlKKmGdzakw3h5r5Srw9qiVoWNBBC3IQkpYS4KqvAwKRlh0jNMb9h/NeKMN4fGViybHJdtnzfBS5cycPVTs8z9ze56b62ei3L/paY0qhVzBnqz4QuDcp1rYD6Dvz8VFcmLD3AhSt59J+/64b71ne0opm7Dd7GJF4d1wMbK31FbqtMjtYWjA32ZWywL4mZBfx67DInE7Jwt7ekfj0rvOtZ4VPPCi9HK6wt5FeouDVLnYb7W7hxfws35g0L4ER8JsUmhfa+jvLmXNQZMx9owUxJZFQ7TjYWDA30Yu2RS6wMjb1hUqrYaOLd36MAmNilAX7ONmXuJwRAj2au2Oq1JFwt4Qvyk9lSQogbk3dUQmB+sfXMd0eITs7Bw96SDg3q8dvxBGb8dIwruYVM6VF3V5ZJzSlkwfazgHnZZ1v9rX9tXEtMLd93geCGTnSs4BR/X2dr1jzVlX+tOMzRixnY6rU097CjxbUvT3uaudvhYKXDYDDw+++/Y6Gt/JkmHg6W/KtHo0o/r6i71GqV9BwTQlQrE7r4sfbIJX47nsBrg1viYnv9BzyrD8dxJikHR2sdz/VuWgVRiprEUqehn787647Gs/F4giSlhBA3JUkpIYC3fjvJ7uhUrHQavp7YAX9PezwdLPnf7hje/f0UKdmFzBpYN6cff/THabILiwmob8+o9uWfNWar195yVtXNuNjq+fmprqTlFuFkYyEzSoQQQoi7oI2PI218HDkWl8HqQ3HX/e3OLjAwf+sZAF7o01R6bopyGdTak3VH4/n9RAJvDK6br6GFEOUjTSxEnbd83wVWhMaiUsEn/9eWgPoOqNUqXh/sz6yB5lKD/+2O4aWfjmEwmqo42nsr8nImq0pW2Wl1z19QqFQqnG31kpASQggh7qIJnf0A+G5/LMX/eK3zRcg5UnOKaOhiw7hOflURnqiB7mvqgp1eS2JWAUcult2bUwghQJJSoo7beTqZf/8aCcArD7RgQCuPUtun9mzMh6PboFGr+PloPFNWHCavqLisU9U6iqLw9m8nURTzynjBDWWVHSGEEKI2GhzoiZONBZczC9gWlVzyeHxGPl/vjgFg1sAWd6VUXtRO10r4AH47nlDF0QghqjP5yyLqrNOJ2Tz7/VFMCowO8mbqDXoHjQry5qvxQVjq1Ow4ncK4rw+Qnlt0j6O99zZHJLL/fBp6rbpkxpgQQgghah9LnYYxHX0AWLn/QsnjH2w+RWGxiU4NnUoSDEKU1+BATwA2RSRguroasxBC/JMkpUSdlJpTyOTlh8gpLCa4oRPvPNT6piVifVq6890TnXCw0nH0YgajvwwlPC7jHkZ87xy/lMEz3x/hme+PADClRyO861lXcVRCCCGEuJvGdfJFrYK9Z69wNjmbY3EZrA+/DMAbg/2llF5UWPemLthZaknKKiRMSviEEDcgSSlRqxiMJk5eziIuLY8Cg7HMfQoMRqauDONSej5+ztZ8+WhQuaajB/k58dOTXfCwt+Rscg7DF+7lme+PEHslt7Jv455TFIUdp5L5v69CefDzvWw8noBJgb4t3XmqV91deVAIIYSoK7zrWdO3pXk21IrQWN7ZGAXAiPb1ae3tUJWhiRpKr/2rhG+jlPAJIW5AVt+7C4qKTSRnF5CQaf5KzMwnPc/AmA4+NHCxqerwap1io4n959PYeOIymyMSSc8zlGyzs9TiZqfH1U6Pm50lbnZ6zqbkEBabjp2lliUTO1LPxqLc12rmbscvz3bj/S2nWXvkEhuPJ/BHZCLjOvnxfJ+mOFXgXNVBUbGJDeHx/G/3ec4k5QCgVasY2saLf93XCH8v+yqOUAghhBD3yoQuDfjjZBLfHbiI0aRgqVPz8oDmVR2WqMGGBHry8xHzKnyzh/ijkVX4hBD/UOeTUgajiXc2RtGjmQu9W9xerXxYbBpf744hPiOfhMwCUnMKUcoom950IoFfnuuOvaUspXunjCaFA+ev8NuJBDZHJJL2tx5PtnotRUYTRcUmsguKyS4o5lxK6dlMGrWKxeOCaOJmW+Fru9lb8uHoNkzu3pD3Np0i5EwKy/ZdYG3YJZ7s1ZhJ3RpiZaG543u8277dH8uCP6NJyioEzM/b2GAfHu/WEC9HqyqOTgghhBD3WrcmzjRyteH81ddN/7qvEZ4O8ppA3L7uTVyxs9SSnF3I4QtpdGrkXNUhCSGqmTqflFq+74I5oXDkEr88252GFZzJdDY5hwlLDpJbVLpUzEKjxsPBEg8HSzwdLDlwPo0LV/J4Zc1xFo1rL3X5tykiPpNVhy6yOSKR1Jy/ElH1rHU8EODJkEBPOjV0QqNWkVVQTEp2AcnZhaRkF5KcVUhydgFXcoro38qd7k1d7iiWlp72LJ8UzJ7oVP6zKYrIy1l8sOU0K0Njmd6/GSPbe1fbT4N2nErmjfURALjb63m8W0PGBvviYCUJUyGEEKKuUqlUTOjsx9xfT+Jqp+fJnlLCL+6MhVbNgFYerAm7xG/HEyQpJYS4Tp1PSk3o0oBNEYmExaYzZcVh1j3TDVt9+Z6W7AIDU1YeJrfISMcG9fjXfY3wcrTCw8ESJ2sL1H9LSBy9mM7DX4ayKSKRpXsvMLl7w7t1S7XS8UsZfLotmu2n/lqm2NFaxwOtPBgc6EnnRs7oNKX7QjlY6XCw0tHEze6uxta9qQu/Nu7OL8cu88GW08Rn5DNzzXEi4zP597CAu3rt21FUbOLt304C8EgnX+YObSVLPAshhBACgHGd/cgzGOnW2AWbcr4mFuJmHmzjdTUpdZk3h/pf95pdCFG31fnfCBZaNYvHtcfdXk90cg4zfgwv15KlJpPCjB+PcT4lFw97SxY/GkT/Vh4E1HfAxVZfKiEF0M63Hm8M9gfgP79HERabVu4Y84qKmbnmGI9/c5DMfMOtD6hFwuMyePybgzz4+V62n0pGrYKhbbxYPimYQ6/35b2RgdzX1LXK/7ip1SqGt6vP9hk9eXVgCwCWh8Zy6EL5/53vlRWhFzifmouLrQWzBraQhJQQQgghSug0ap7u1YQ2Po5VHYqoJbo2dsbVTk96noFdZ1KqOhwhag1FUYiIz6zqMO6YvBvF3CPoi0eDsNCo2RKZxMIdZ295zOKQc/xxMgkLjZovxgfhYqu/5TETuvgxJNCTYpPCM98d5UpO4S2PSc4qYMyX+/nx8CV2nE7hlTXHUcpqWFXLHLmYzsSlBxm+cC87TqegVsGIdvXZNr0nC8a2o2ezqk9ElcVSp+HJno0Z08EHgNd+PkFRsamKo/rLlZxCPt0eDcDLA5pjJ/3NhBBCCCHEXaTVqHmwjRcA647GV3E0QtQeS/deYOjne1hw9f1dTVX93tVXkXa+9Xh7eCsAPt52hu1RSTfcN+RMCh/+cRqAt4a1om05P0lSqVS8NzKQRq42JGYVMG11OMabzMo6nZjNQ4v2cSI+k3rWOnQaFZsjE1m+70L5b6yGOXEpk/FLDjBi0T5CzqSgUasY2d6b7TN68fGYtjRyrXhj8qowa1ALXGwtiE7O4cuQc1UdTomPtp4hu6CYgPr2jAryqepwhBBCCCFEHfBQu/oAbD2ZRHZB3ar8EOJuOBaXwXubolAUcLCu2RMNJCn1N2M6+jK+sx+KAtNWhXMuJee6feLS8nj+h6MoCowN9uH/gn0rdA1bvZbF44Kw1KnZHZ3Kgj/Lzmrujk5h1OJ9xGfk08jFhvXPdOP1QS0BeOf3KI5fyqj4Dd6h3MJi4tLy7tr5z6fkMOqLfeyOTkWjVjE6yJs/Z/Tko4fbVLgBfVVztLZg9hBzueaCHWc5X8ZYutdOXs5i1cGLALw5pFW1bcIuhBBCCCFql1Ze9jRxs6Ww2MTmiMSqDkeIGi2rwMCzPxzBYFR4oJUH4zv7VXVId0SSUv8we4g/HRvUI7uwmCkrDpfK5OcXGZm6MozMfANtfByZ+2Cr27pGcw873n2oNQCfbo++rrZ69aGLPP7NIbILiwlu6MTPT3fFz9mGiV0b8EArDwxGhWe+P3JP+0ul5RYxZMEe7nt/B6+uPU5mXuVeW1EUZm+IoLDYRMcG9dgxoxcfjG6Dn3PNSkb93YNtvOjRzJWiYhOvrTtRpWWXiqLw1m+RmBQYEuhJcEOnKotFCCGEEELULSqVqmS21PpwKeET4nYpisKra48Tl5aPdz0r/jsqEJXq9iYbzJ07F5VKVerLw8Oj1LXmzp2Ll5cXVlZW9OrVi8jIyMq6lRKSlPoHC62aReOC8LC35FxKLtN/PIbJpKAoCq+tO8HJhCycbSxYPK49eq3mtq8zor03Y4N9URR4YdVRLmfkYzIpvL/5FK+sPUGxSWF4Wy9WTg7G0doCMP8y/++oQLzrWRGXls+ra+9Nf6kCg5EpKw4Tk5oLwKpDcfT5eCcbwuMr7fq/HLvM3rNX0GvVfDS6Lb7O1pVy3qqkUql4Z3gAljo1+8+n8VPYpSqLZXNEIvvPp6HXqpl1dcadEEIIIYQQ98q1vlL7zl0hMbOgiqMRomopisLyfRf48XBchd5Tf3vgIr+fSESrVvH5I+1xsLqz0r1WrVqRkJBQ8nXixImSbe+//z4ff/wxn3/+OYcOHcLDw4N+/fqRnZ19R9f8J0lKlcHVTs8X44Ow0KrZejKJBX+eZfm+C6w7Go/m6j++l6PVHV9nzlB/WnnZk55n4Jnvj/DC6nAW7TT3H3q+T1Pmj2l7XeLLwUrHwkfao9Oo2BSRyIrQ2DuO42YURWHmmuMcjk3HzlLLR6Pb0MTNltScIl5YFc7Ebw5x8cqdlfRl5huYtzEKgGfvb1IrElLX+DhZM71fMwDe2RhFajma2ydlFfDkyjAe/jKUtNyiO46hwGDknd/Nz+/Uno2pXwljVwghhBBCiIrwcbImuIETigK/HKt5s6UiL2dxIk3aX4jKsTjkHHN+iWTmmuO8sCqc/CLjLY+JvJzJ27+dBODVgS3K3dv6ZrRaLR4eHiVfrq6ugDkP8Mknn/D6668zYsQIAgICWL58OXl5eXz//fd3fN1SMVTq2WoYg8GAwVB2GVorDxv+PbQls9ZFMn/bmZL+O68MaEYHX/sbHlcRGuCzMYEMX7yfoxczOHoxA61axTvD/RnRrj7FxcVlHufvYcMrA5ox7/fTzNt4ktZetrRwsy65p8r0yfaz/HLsMlq1ioVj29ClkTMD/F353+4YFu+KYdeZFPp/EsKzvRozqZvfba2I98HmKFKyC2nkYs3jXX0r/R6q2vhgb9YdiScqMZu3fonko9Gtb7jvlsgk3thwkoyrpZkvrjrKV4+2Q30H/Z++CjnPpfR8POz1TO7qU+ue32v3U9vuS9RcMiZFTSNjVtREMm5rpqGBHhy8kMbPR+J5vEvFevNWJYPRxKTlYaTlaWgfmUC/Vp5VHZKowULOpPDBFvPCaWqVuWroXEo2i8a2veHkl5zCYp757ghFxSbub+7ChE7e1/3+u/Z9VlZWqcf1ej16vb7M80ZHR+Pl5YVer6dTp068++67NGrUiJiYGBITE+nfv3+p8/Ts2ZN9+/YxderU277/f1IpVdnopopkZWXh4ODA999/j7X1zWflrIlRszvRnGhp72xiQlMTt1myeUMn0lR8fVqDlUZhUnMTzRxu/U+iKLD0jJrjaWqc9QovBxqxquQU48EUFd+dNc/UGtvYSGe30nEl58OP59VEZ5mfH09rhf9rZKSBXfmvcTEHPj6hQUHFM/7Gct17TRSbA/Ov3ueTLY20dCx9nwVG+DlGzYEU83NZ31ohOR8Mioohvkb61b+95yWzCOYd1VBkUjG+iZEOrrXz+RVCCCGEENVfXjG8cViDUVHxSmAxXjWkfeypDBWLo8zvi9wsFV5tY+Q2PosXguR88/vffKOKru4mglxMLD2tIbdYha1OYVIzI43tSx+jKLDyrJqwVDWOFgozA43YlFG1l5eXxyOPPHLd43PmzGHu3LnXPb5p0yby8vJo1qwZSUlJzJs3j1OnThEZGcnp06fp1q0b8fHxeHl5lRwzZcoUYmNj2bJly50+FSXq9Eyp/v37Y29vf9N9+hlNzPk1iuyCYv47ohXWFpX/lA0CRiTl4GSjw9m27AxmWbr3NjB8USiXMgr4M8eTQQ4J9O/fD53uzpeEPBCTxo8HwwCFJ3s0ZEa/pmXuN1FRWBd+mfc2nyEhz8AnkVpe7NOEJ3s0vGXDNaNJYdSXB1DI4sFAT6bdZAZRbXDF9hTLQy/yW6ItT4/qipWF+Q/b0bgMXlpzgotp+ahUMPW+hjx3f2M2HEvgtfWR/B6n4f/6dqDTbTQnn7n2BEWmBNr7OjJ7QsfbboJXnRkMBrZu3Uq/fpUz9oW4UzImRU0jY1bURDJua64/c8LZGpVMmn0TnhjQrKrDKZf9v5wEzP1hkwtUZLgEML5zxWZ6ZRcUsyw0lu6NnWnne+dlV6LmySksZtSXB8g35hLk68j/Hu+AhVbNyIx8nvwunFOJ2Sw+pWPOkJaM6eBdctxPYfGE7Y9Eo1axeEJHOvjVK/P812ZIxcXFlcpz3GiW1MCBA0v+v3Xr1nTp0oXGjRuzfPlyOnfuDHDd+0dFUSr9PWWdTkrpdLpb/hHT6eCD0W3veiz+3mUPrJtx0en4fFwQo7/Yxx9RKdg3VDG4HPd0K+dScnjmh2MYjAqDAz2Z+UDLm5aPjQluQL9WXszbeJKfj8Tz8bazxGcUMu+hgJuW832/7wIRl7Ows9Qye2irWv+C4uUHWrL1ZDKX0vNZuCuGl/s35/MdZ1nw51mMJoX6jlZ8/HAbOjVyBmBsJz/CLmay9sglXvzpBBuf746bnWW5r3f0YjrrwhMAmDO0FRYWFnflvqqL8vw8C3EvyZgUNY2MWVETybiteUYGebM1Kplfjycya5D/HbWpuBeMJoWtUebV0gOdTBxPU7NgxzlGBvniYF2+sacoCrN/PcHG4wksDjnP+6MCeaid960PFLWGyaQw8+djnEvJxd1ez+LxQdhYmZNFDVx1/Px0V15ec5yNxxN4Y8NJziTnMnuIPzGpubx1tf/y9H7N6NLE7YbXuPa70N7e/paTb8piY2ND69atiY6OZvjw4QAkJibi6flXuWpycjLu7u4VPvfNyKTDGq6tjyOzBppXU1t3QU3k5axbHHFzablFTFp2iMx8A+18HflodJty/aFwsrHg44fb8tawVqhVsPpwHJOWHSK7oOw6/+SsAj68Wkc784EWuNqVf4ZYTWWr1/LWsAAAvt4dw0OL9vHJtmiMV1da/P2F+0oSUmDOSs8bHkBzdztSsgt54YdwjKbyld+ZTAr//tXcBG9UkDdtKqEJnhBCCCGEEHeqV3M37C21JGYVsD/mSlWHc0thsemk5hRiZ6llfBMTTVxtSM8z8PmO6HKfY314PBuPmz8sNhgVXlx9jAXbo+/JSuqievjsz2i2nkzCQqPmy/EdrptsYG2h5fOx7Xh5QHNUKlgRGsv4JQd45rsjFBhM3NfUhad6Nr6rMRYWFhIVFYWnpycNGzbEw8ODrVu3lmwvKioiJCSErl27Vup1JSlVCzzerQH9WrphVFRM/+l4uTr3l6XAYGTKisPEXsnDx8mK/03ogKVOc+sD/2ZClwb8b0IHrHQadkenMvqLUC5n5F+337yNUWQXFtPG24FHgmtOk8M71dffnUGtPTCaFE7EZ2JnqeXT/2vLJ//XrszlPK0sNCwc1x5rCw2h56/w6bYzt7xGYmYBT393hPC4DGwsNMwc0Pxu3IoQQgghhBAVZqnTMDjQPPNi/dHqvwrf5ohEAPo0d8VCA7MGml9bL9t3gdgrubc8/lJ6Hm+ujwTgxb7NmNqzEQAfbT3DrJ9PYDCa7lLkorr4IzKRT7aZk5jvPBRww1XzVCoVz9zfhP+N74CtXsv+82lEJ+fgaqdn/pi2lT6r8KWXXiIkJISYmBgOHDjAqFGjyMrKYuLEiahUKqZNm8a7777LunXriIiI4LHHHsPa2rrMvlV3QpJStYBKZV6xz0GncD41j3kbT1b4HIqi8Mra4xyOTcfeUss3j3XEpQL9rf6uT0t3fpzaBVc7PacSsxm+cC8R8Zkl23dHp/DLscuoVfDOQ61LVjasK+YObUVLT3t6NXdl0wv3Maxt/Zvu38TNlv+MMPfbWrDjLCFnUsrcz2hSWL7vAn0/DmFzZCIatYo3h/rjZl/+kj8hhBBCCCHutuFXX/9uOpFIgeH2PlC/FxRFYUukOSnV399cstSjqQs9mrliMCq8t+nUTY83mhRm/HiM7MJi2vk68sz9jZk1sCVvX60uWXUojsnLD5NTWPaq66Lmi07K5sXV4QA81rUBozv43PKYvv7urHu6Kw1dbNBr1Xz6f21v+735zVy6dImxY8fSvHlzRowYgYWFBfv378fPzw+AmTNnMm3aNJ5++mk6dOhAfHw8f/zxB3Z2FVjZrBwkKVVL1LO2YFwTc5b9uwMX2XYyqULHf7DlNBvCL6NVq/ji0SCauN3ZQGvt7cD6Z7rRzN2W5OxCHv4ylB2nkikwGHlzg/mTggldGhBQ3+GOrlMTudlbsumF+1j2eDDe9W6++uM1w9rWZ1wnXxQFXlwdTkJm6dlnkZczGbFoL3N+iSSnsJi2Po789lx3xnSsO7PQhBBCCCFEzdCxgRP1Ha3ILixme1RyVYdzQyfiM4nPyMdKp+G+pn+12Xh9UEvUKtgUkcjBmLQbHv/17vMciEnD2kLDJ2Paor3ab3d8lwZ8Nd5cXbLrTAoPfxFKUlbBXb+fe2Hv2VSC3t5aUq5YWx2MSeOJ5Yd4c0MEK/fHcuD8FdJzi0rtk5lvYMrKMHKLjHRu5MTrg1uW+/xN3e3Y+mIP9s/qQ9fGLpUdPgCrVq3i8uXLFBUVER8fz9q1a/H39y/ZrlKpmDt3LgkJCRQUFBASEkJAQEClxyFJqVqkuaPCpK7mrOYra4+Tkl1YruO+OxDLop3nAPjPiNZ0bVI5g76+oxVrnupKtybO5BUZmbz8EJOXHyImNRc3Oz3T+9eM1Taqi9lD/Amob09abhHPfn8Ug9FEbmEx72w8yYOf7+XYpUzs9FreHh7A2qe60tKz4s3thBBCCCGEuNvUahXD25mXmV9XjUv4Nl0t3bu/hWuptibNPez4v6stSOZtPImpjL6vJy9n8eEf5h66bw7xx8/ZptT2vv7urJ7aGRdbC04mZPHQwr2cTsy+W7dyz3yz9wJXcov48I/TZT4vtUGBwciLq8PZFpXMitBYZq+PYMxX+2n39lY6zNvG2K/2M2dDBFNWHCYmNZf6jlYsfKT9TRcBK4tWo6aeTe1erAokKVXrTO/XlBYedlzJLeLlNcdu2Txve1QSs9dHAOYa5/JMJ6wIe0sd3zwWzKggb0wK7D1rbmY4e4g/9payUkpFWOo0LHokCDtLLWGx6Tz/w1H6z9/F/3bHYDSZV0rcPqMn4zv71bmSSCGEEEIIUbNcK+HbeTqZtH/MMKkOFEUp6Sf1QIDnddtf7NsMW72W45fHe6jRAAAgAElEQVQy2XCsdGKtwGBk2uqjGIwKfVu6M6Zj2e+xAr0dWfd0Nxq72nA5s4BRi/ex92xq5d/MPVJgMJbEH5Oay95zNfdebmbZvgvEZ+TjYW/J1J6N6N3CDe96VgCk5hQSev4Ky0NjORCThqVOzZfjg3C+C+V3tYUkpWoZvVbNZ2Pbodeq2Xk6hRWhsTfc91hcBs9+fxSTAg938Ob5Pk3uSkwWWjUfjApkRj/zzKh+/u4MCbz+F7u4NV9naz4Y1QYwf3ITn5FPfUcrvnmsIwsfaS/9o4QQQgghRI3Q1N2OgPr2FJsUNp6ofqVeZ5JyiEnNxUKj5v7mrtdtd7XT8/T95tXQ3t98utRiUx9sOc2ZpBxcbC14b2RrVKobf2Ds42TN2qe6EtzAiezCYiYuPcjasEuVf0P3wIGYNPL/1iPsZu9Fa6orOYUs/PMsAC8PaM6sgS1Z+lhH9rzSm8h/D2DDM934cHQbpvZoxAOtPFg0rn2dbFlTEZKUqoWaudsxa2ALAN79PYropOungcal5TF5+SHyDUZ6NHPlnYdu/svyTqlUKp7r05SwN/ry5aNBd/Vatd0DAR4836cpVjoNU3s0Yuv0Htzfwq2qwxJCCCGEEKJCrs2Wqo6r8F2bJXVfUxfsblDhMalbQ+o7WpGQWcDXu88D5p5KS/bEAPD+qMByNah2tLZgxeRghrbxotikMOOnY3y6LfqWVS+3IzPfcNfK6nacMvcHC27oBJircuLLWIm9JvtsezTZhcW08rLnoXalF6yy0Wtp4+PIqCBvZg1qyRfjg+jdwr2KIq05JClVS03s2oCezVwpLDbx/KpwCov/ylin5xYx8ZuDpOYU4e9pz6JxFa9vvV3OtvpKX8qyLprerxmR/x7ArEEtsbbQVnU4QgghhBBCVNiDbbxQqyAsNp2LV/KqOpxSNkWYZ289EOBxw30sdRpeuToZYHHIOaKTspnx4zEAHunkW6GEhKVOw6dj2vJkT/Psq/nbzjBzzXEMRtPt3sJ1jl/KoMO8rTy65EClr3qoKAp/Xk1KTe7ekK6NnTEp8P2B2jNb6lxKDt8duAhcbXYv72srhSSlaimVSsUHowNxsrEgKiGLj/44A5jrfP+14jDnU8wN1755vCO2eklq1ETyS1AIIYQQQtRkbvaWdLu6yNL68NufLfXnqSRm/XyczDxDpcR1ITWXU4nZaNQq+ra8eWJpaKAn7XwdySsyMnzhXhKzCmjoYsMbFVhp7Rq1WsWrA1swb3gAahX8FHaJScsOkV1QOff1Rcg5DEaFfeeu8Oz3Ryo14XUuJZeLaXlYaNR0b+LChC7mBbhWH4orNUGiJntv0ymKTQp9WrhV2uJgQpJStZqbnSX/HRkIwFe7zrM7OoUZPx7jcGw6dpZavnm8I+7Sg0gIIYQQQghRRa6VQH0Zco4tkYkVOlZRFBbtPMukZYf54WAcy/ZdqJSYNl+No0sj51uufqZSqXhjsD8AuUVGNGoV88e0vaNqhkc7+/G/CR2w0mnYHZ3K6C9CScwsuO3zAcRn5LMlMgkw9/zdFpXMK2uOV1op37XSvU6NnLDRa+nb0h13ez2pOUUlpZDltSE8nsU7z1VaMq4y7D9/ha0nk9CoVcwa1KKqw6lVJClVy/Xzd+eRTublSictO8TGEwnoNCq+HB9EM3e7Ko5OCCGEEEIIUZcNDvSkWxNncouMTF0ZxqfbosuVKCkqNjFzzXHe33y65LEN4fGV0odp09UkyoCblO79XZBfPYa39QLghT5NaevjeMcx9GnpzuqpnXGx1XMqMZuHFu3lVGLWbZ9vZWgsRpNCl0bOLHqkPRq1ip+PxjNvY1SlPGfXSvfub27udavVqHkk2K/k2uUVeu4KL6wK57+bT3H/hyH8dDjurvXAKi+TSeGdjVEAjA32oYmbvI+uTJKUqgPeGNySRi42GIzmH+YPR7eha2OZbiiEEEIIIYSoWnqthmWPB/NY1waAuZfSU9+FkVNYfMNj0nOLGL/kAD+FXUKtglcHtkCvVXM+NZcT8Zl3FM/ljHyOxWWgUsEA//L3hPrvqEB+ebYbz/WuvBXNA70dWfd0Vxq72pCQWcDoxaHsiU6t8Hnyi4ysOmTuhfR4twb09Xfng1Hmipqle2NYtPPcHcWZVWDg0IU0AHr/bQGmscE+aNUqDsemc/LyrRNqeUXFvLL2OABWOg2pOYW8vOY4Dy3ex9GL6eWO50JqLhvC44lLq5w+ZRuOxXMiPhNbvZZpfZtVyjnFXyQpVQdYW2j5/JH2BPnVY97wAIa1rX/rg4QQQgghhBDiHtBp1Mx9sBXvjwrEQqNmS2QSIxbtJfZK7nX7xqTmMmLxPg7EpGGr17LksY482bMxfa8mkDaEX76jWK6VEAb51sOtAq1O9FoNgd6Olb7KuI+TNT8/1Y3ghk5kFxbz2DcHiahg4m19eDwZeQZ8nKzoc7VH1oj23rw5xFx2+MGW03y7//Ybku+NTqXYpNDIxYYGLjYlj7vZW5bMNltZjvN/sOU0F9Py8HKwZO+rvXltUAts9VqOxWXw0KJ9TP8xnOSs68sYFUUh8nImH289w4D5u+j14U5eWBVO7492MveXSFJzCm/73goMRj64Ohvv6fsbl2s1RVExkpSqI/y97Fn7VFce7exX1aEIIYQQQgghxHUe7uDDqqmdcbPTcyYphwc/31tqZlDouSsMX7iXmFTzok1rn+paUi42/OoH778eu4zxDsq9rvU/utmqe/eag7WOlZOD6d3CjWKTwpxfIstdcqcoCt/sjQFgYpcGaP62WNKk7g1LZnbN3hDBb8dvL6FXUrr3t1lS14y/+v5z/dF4sm7SI+rwhbSSnmD/GWlesGtKj8b8+VJPRgd5A/DzkXju/3Ani3eeo8Bg5GBMGm//dpL73t/B4M/28Nn2aE4nZaNVq2jiZovBqLBs3wV6vr+D+VvP3FaPqiV7YricWUB9RysmdWtY4ePFrUlSSgghhBBCCCFEtdDetx6/Ptedtj6OZOYbmLD0AF/vPs+Ph+OYsPQAmfkG2vo4sv6ZbjT3+Ku3T89mrjha60jOLiT03JXbunZqTmFJGdqAVtUnKQXmmVjvPBSAlU5DWGx6uWeEhZ67wpmkHKwtNIzu4HPd9un9mjGuky+KAi+uDmfXmZQKxWUyKew4bT6mdxlJqU4NnWjmbku+wcjPYZfKPEeBwcjLa46jKDA6yJuezVxLtrnZWfLB6DZseKYb7XwdyS0y8t/NpwiYs4WHvwxlyZ4YLqXnY6lT09/fnY8fbkPYG/3YNr0n307uRKC3A7lFRj7dHk3PD3ayZE9MuVcDTM0pZPHV0saXBzTHUqep0HMjykeSUkIIIYQQQgghqg13e0tWTenMqCBvTArM2xjFzDXHMRgVhgR6smpKZ1ztSpdRWWjVDGrtCZjL1W7H1pNJmBRoXd8BHyfrO76PyubpYMWzV2c2/WdTFLk36bt1zdK9FwAY2d4bByvdddtVKhVvDQtgSKAnBqPC1JVhHKlA/6aIy5mk5hRiY6GhYwOnMs9/bbbUyv2xZc7w+uiP08Sk5uJur+eNqyWF/9TGx5G1T3blo9FtcLXTU2xSsLfUMqJdfb54NIijs/vz1YQOjGjvjYO1+T67N3VhwzPdWDSuPY1cbEjLLeLt307S+8MQ1oRduuWMuk+2nSGnsJhAbwcebONV7udEVMztr1MphBBCCCGEEELcBZY6DR+MCqSVlz3zNkZhNCk837sJ0/o2Q60uu2/T8Lb1+f7ARTZHJDJveECFZ7Zsqoale/80uXtDVh+K42JaHgt3nGXmAy1uuG/slVy2n0oCYOLVRvJl0ahVfPxwWzLzDeyOTmXyskP8OaMX9WwsbhnPtdK97k1dsNCWPedleLv6vLfpFOdScgk9d4WuTf5adOvIxXSW7DGXF/5nROsyE2fXqNUqRgZ5M7C1B7FX8mjiZotOc/N5NiqVikGtPenv785PYZf4ZNsZ4jPyeemnY8xeH4GvkzW+ztb4OVnj52yNr7MNfk7W5BuM/HAwDoDXBrW84ZgTd06SUkIIIYQQQgghqh2VSsXj3RrSuZEzuYXFdChjJs7fdfCrR31HK+Iz8tkelczgQM9yXysz38C+s+b+VdU5KWWp0/DG4JZMWRnG17tjeLiDT6nm4n+3IjQWRYEezVxp4mZ70/NaaNV8OT6I4Qv3ciYph0+2neHfwwJuGc+Oq0mpskr3rrGz1DGivTcr98eyIjS2JClVYDDy8k/HMCkwol19erco32qH1hZaWnral2vfa7QaNWODfXmoXX2W77vA4pBzZOQZOJ2Uzemk7Bse18/fnc6NnCt0LVExUr4nhBBCCCGEEKLaaulpf8uEFJhn0gy9Wma1oYIlfNujkig2KTRzt6Wx680TOFWtn7879zV1ochoYt7GqDL3ySks5sdD5pk+j3drUK7zWltomTu0FQDfHrjImZskawBSsgs5dsm8EuC1hvM3Mr6LuYRva1QSCZn5AHy6PZpzKbm42ul5c2jZZXuVzVKnYWrPxhx6vS87XurFssc78tawVkzu3pC+Ld1p6maL/uqML2sLDbMG3ngmmqgcMlNKCCGEEEIIIUStMLydF1+EnGPn6RQy8wwl/YVupWTVvWrW4LwsKpWKOUP9eeCT3WyLSmLn6WR6/SMp9PORS2QXFtPIxYaeTV1vcKbrdW3iQn9/d/44mcTbv51kxaRgVKqyS9d2njbPkgqob4+bveVNz9vM3Y5ODZ04EJPGDwfj6NPCjS9DzE3E5w0PwNH61qWClUmnUdPQxYaGZcwyM5kUkrMLsdCqcSpHCaO4MzJTSgghhBBCCCFErdDCw54WHnYUGU38HpFQrmMy8w2EXF117oGA8pf8VaUmbnY8drVP1Fu/naSo2FSyzWRSWHa1wfnErg0q3A/p9cEt0WlU7I5OLekZVZYdV5NSvW8xS+qaa7Olfjh4kZfXmMv2hrbxqnYrHarVKjwcLCUhdY9IUkoIIYQQQgghRK0xrG19ANYfvXUJn6IovLkhgsJiE03cbGnpaXe3w6s0z/dtioutBedTclkReqHk8ZDoFM6n5mKn1zIyyLvC5/VztmFSt4aAeeXDvye8rjEYTew+Y+7Bdf9N+kn9XX9/D1zt9KRkF3ImKQdnGwv+/WCrCscnahdJSgkhhBBCCCGEqDUebGvuK3UgJo3LGfk33Xfd0Xg2hF9Go1bx35GBNyxVq47sLXXMHGDuefTptmhSsgsBSmZJje7gg63+9jr2PNu7CS62FsSklk54XXPoQhrZhcU421jQxtuxXOe00JqbjV/z9vAAmY0kJCklhBBCCCGEEKL2qO9oRXBDc2P0X45dvuF+F1Jzmb0+AoBpfZoS5FfvnsRXmUYFeRPo7UB2YTEfbDnF2eQcQs6koFJRUt53O+wsdbzUvzlgbkh+Jaew1PZrq+71bO5aofLA8Z39aOFhx4QufgxqXTNKJcXdJUkpIYQQQgghhBC1yrC211bhKzspVVRs4oVVR8ktMhLc0Imn729yL8OrNGq1irlXS+B+PHyJN9afAKBPC3d8na3v6NyjO/jg72lPdkExH209U2rbtV5TvctZuneNq52ezdN68NawgDuKTdQekpQSQgghhBBCCFGrDG7tiU6jIiohizNJ2ddtn7/tDMcuZeJgpeOTMW3RVLAZeHXS3rceI9qb+2jtP58GwOPdGtzxeTVq8yp/AKsOXiQqIQuAi1fyOJeSi0at4r4KrOwnRFkkKSWEEEIIIYQQolZxtLagZzPzLJ5/NjzfdzaVL0LOAfDfka3xcrS65/FVtlcfaIGNhQaA5u52dG3sXCnn7dTImUGtPTAp8NavJ1EUhT9PJQHQwa8eDla6SrmOqLskKSWEEEIIIYQQotYZ3u6vEj6TSQEgLbeIaavDURQYG+zLAwG1o6+Rm70lrw/2R6dR8WK/ppXasH3WwJZYaNWEnr/CHyeT+PN0ClDx0j0hyiJJKSGEEEIIIYQQtU7flu7Y6rXEZ+QTdjEdRVGYueY4ydmFNHa1YfaQllUdYqV6pJMvZ+YNrPREm4+TNU90bwjAvI0n2X/+CiBJKVE5JCklhBBCCCGEEKLWsdRpGNDKA4AN4fF8uz+WbVFJWGjULBjbHmsLbRVHWPkqc4bU3z19fxNc7fTEpeVTVGzCu54VTdxs78q1RN0iSSkhhBBCCCGEELXS31fhm7cxCoBXB7bA38u+KsOqcWz1WmYOaF7yfe8WbnctASbqFklKCSGEEEIIIYSolbo2dsbFVk92QTGFxSZ6NXetlJXp6qKR7b1p5+sImFc3FKIy1L75ikIIIYQQQgghBKDVqBnaxpNv9l7AxVbPh6PbyAyf26RWq1g5uRNxaXm09JSZZqJySFJKCCGEEEIIIUSt9cz9TcgvMjI22BcXW31Vh1Oj2eq1kpASlUrK94QQQgghhBBC1FoutnreGxlIGx/Hqg5FiGpj8eLFBAYGYm9vj729PV26dGHTpk0l2wsLC3nuuedwcXHBxsaGBx98kEuXLlV6HJKUEkIIIYQQQgghhKhDvL29ee+99zh8+DCHDx+md+/eDBs2jMjISACmTZvGunXrWLVqFXv27CEnJ4chQ4ZgNBorNQ4p3xNCCCGEEEIIIYSoQ4YOHVrq+3feeYfFixezf/9+vL29WbJkCStXrqRv374AfPvtt/j4+LBt2zYGDBhQaXHUyaSUwWAA4MSJE9jb14562OLiYuLi4oiIiECrrZP/rKKOkrEvqhsZk6KmkTEraiIZt+JekzEnqrusrCwArly5UupxvV6PXn/zXmpGo5GffvqJ3NxcunTpQlhYGAaDgf79+5fs4+XlRUBAAPv27ZOk1J0KDQ0FoHv37lUciRBCCCGEEEIIIUTlaNSoUanv58yZw9y5c8vc98SJE3Tp0oWCggJsbW1Zt24d/v7+hIeHY2FhQb169Urt7+7uTmJiYqXGWyeTUgEBAQAcPHgQT0/PKo6mchQXF7N9+3b69OkjmXtRp8jYF9WNjElR08iYFTWRjFtxr8mYE9VdQkICwcHBHD9+HD8/v5LHbzZLqnnz5oSHh5ORkcHatWuZOHEiISEhN9xfURRUKlWlxl0nf5qu/RLx9PTE29u7iqOpHAaDARcXF+rXr49Op6vqcIS4Z2Tsi+pGxqSoaWTMippIxq2412TMiZqiXr165W5TZGFhQZMmTQDo0KEDhw4d4tNPP2XMmDEUFRWRnp5earZUcnIyXbt2rdR4ZfU9IYQQQgghhBBCiDpOURQKCwsJCgpCp9OxdevWkm0JCQlERERUelKqTs6UEkIIIYQQQgghhKirXnvtNQYOHIiPjw/Z2dmsWrWKnTt3snnzZhwcHJg8eTIzZszA2dkZJycnXnrpJVq3bl2yGl9lkaSUEEIIIYQQQgghRB2SlJTE+PHjSUhIwMHBgcDAQDZv3ky/fv0AmD9/Plqtlocffpj8/Hz69OnDsmXL0Gg0lRqHJKVuwmg0YjAYqjqMcjEYDGi1WgoKCjAajVUdTo2n0+kq/YdNCCGEEEIIIYSoDpYsWXLT7ZaWlixYsIAFCxbc1TgkKVUGRVFITEwkIyOjqkMpN0VR8PDwIC4urtK74ddVjo6OeHh4yPMphBBCCCGEEELcBZKUKsO1hJSbmxvW1tY1IilhMpnIycnB1tYWtVr6198JRVHIy8sjOTkZMK/SKIQQQgghhBBCiMolSal/MBqNJQkpZ2fnqg6n3EwmE0VFRVhaWkpSqhJYWVkB5iUv3dzcpJRPCCGEEEIIIYSoZJK9+IdrPaSsra2rOBJR1a6NgZrSV0wIIYQQQgghhKhJJCl1AzWhZE/cXTIGhBBCCCGEEEKIu0eSUkIIIYQQQgghhBDinpOklBBCCCGEEEIIIYS45yQpVcskJyczdepUfH190ev1eHh4MGDAAEJDQwFo0KABKpWKVatWXXdsq1atUKlULFu27Lpt7777LhqNhvfee69ccSxbtgyVSnXdV0FBQan9Fi1aRMOGDbG0tCQoKIjdu3dX/KaFEEIIIYQQQghR40hSqpYZPXo0x44dY/ny5Zw5c4ZffvmFXr16kZaWVrKPj48P33zzTanj9u/fT2JiIjY2NmWe95tvvmHmzJksXbq03LHY29uTkJBQ6svS0rJk++rVq5k2bRqvv/46R48e5b777mPgwIFcvHixgncthBBCCCGEEEKImkZb1QHUBIqikG8wVsm1rXSacjfczszMZM+ePezcuZOePXsC4OfnR3BwcKn9xo0bx/z584mLi8PHxweApUuXMm7cOFasWHHdeUNCQsjPz+ett95ixYoV7Nq1ix49etwyHpVKhYeHxw23f/zxx0yePJknnngCgE8++YQtW7awePFi/vOf/5TrnoUQQgghhBBCCFEzSVKqHPINRvzf3FIl1z751gCsLcr3z2RjY4OtrS3r16+nc+fO6PX6Mvdzd3dnwIABLF++nDfeeIO8vDxWr15NSEhImUmpJUuWMHbsWHQ6HWPHjmXJkiXlSkrl5OTg5+eH0Wikbdu2vP3227Rr1w6AoqIiwsLCePXVV0sd079/f/bt21eu+xVCCCGEEEIIIUTNJeV7tYhWq2Xp0qUsX74cR0dHunXrxmuvvcbx48ev23fSpEksW7YMRVFYs2YNjRs3pm3bttftl5WVxdq1a3n00UcBePTRR1mzZg1ZWVk3jaVFixYsW7aMX375hR9++AFLS0u6detGdHQ0AKmpqRiNRtzd3Usd5+7uTmJi4u0+BUIIIYQQQgghhKghZKZUOVjpNJx8a0CVXbsiRo4cydChQ9m9ezehoaFs3ryZ999/n6+//prHHnusZL/BgwczdepUdu3axdKlS5k0aVKZ5/v+++9p1KgRbdq0AaBt27Y0atSIVatWMWXKFC5evIi/v3/J/q+99hqvvfYanTt3pnPnziWPd+vWjfbt27NgwQI+++yzksf/WZqoKEq5yxWFEEIIIYQQQghRc0lSqhxUKlW5S+iqA0tLS/r160e/fv148803eeKJJ5gzZ06ppJRWq2X8+PHMmTOHAwcOsG7dujLPtXTpUiIjI9Fq/7p/k8nEkiVLmDJlCl5eXoSHh5dsc3JyKvM8arWajh07lsyUcnFxQaPRXDcrKjk5+brZU0IIIYQQQgghhKh9pHyvDvD39yc3N/e6xydNmkRISAjDhg2jXr16120/ceIEhw8fZufOnYSHh5d87dq1i0OHDhEREYFWq6VJkyYlXzdKSimKQnh4OJ6engBYWFgQFBTE1q1bS+23detWunbtWgl3LYQQQgghhBBCiOqs5kz/EbeUlpbGiBEjmDRpEoGBgdjZ2XH48GHef/99hg0bdt3+LVu2JDU1FWtr6zLPt2TJEoKDg8tsat6lSxeWLFnC/Pnzyzz23//+N507d6Zp06ZkZWXx2WefER4ezsKFC0v2mT59OuPHj6dDhw506dKFr776iosXL/Lkk0/e5jMghBBCCCGEEEKImkJmStUiNjY2BAcHM3/+fHr06EFAQACzZ8/mX//6F59//nmZxzg7O2NlZXXd40VFRXz77beMHDmyzONGjhzJt99+S1FRUZnbMzIymDJlCi1btqR///7Ex8eza9cugoODS/YZM2YMn3zyCW+99RZt27Zl165d/P777/j5+d3G3QshhBBCCCGEEKI8du3axdChQ/Hy8kKlUrF+/fpS25OSknjsscfw8vLC2tqaBx54oKQdzzWFhYU899xzuLi4YGNjw4MPPsilS5cqFIfMlKpF9Ho97777Lu+9994N97lw4cJNz5GRkVHy/6mpqTfcb/r06UyfPv2G2+fPn3/DWVR/9/TTT/P000/fcj8hhBBCCCGEEEJUjtzcXNq0acPjjz9+3WQURVEYPnw4Op2ODRs2YG9vz8cff0zfvn05efIkNjY2AEybNo1ff/2VVatW4ezszIwZMxgyZAhhYWFoNOVbtE2SUkIIIYQQQgghhBB1yMCBAxk4cGCZ26Kjo9m/fz8RERG0atUKgEWLFuHm5sYPP/zAE088QWZmJkuWLGHlypX07dsXgG+//RYfHx+2bdvGgAEDyhVHnU5KFRcXYzAYSj1mMBhQFAWTyYTJZKqiyCpOUZSS/9akuKszk8mEoigYDIZyZ3nFvXftZ/ifP8tCVBUZk6KmkTEraqKaPm61rVrBxYvmb0wmUKvB15fiyMiqDUzcUE0fc6L2Ky4uBiA7O5usrKySx/V6PXq9vkLnKiwsBMDS0rLkMY1Gg4WFBXv27OGJJ54gLCwMg8FA//79S/bx8vIiICCAffv2SVKqPLZv346Li0upx7RaLR4eHuTk5NywX1J1lp2dXdUh1BpFRUXk5+eza9eukh9wUX39cyVHIaqajElR08iYFTVRTR23Q2NjUV9903eNSa/n999/r6KIRHnV1DEnar9r7Xf8/f1LPT5nzhzmzp1boXO1aNECPz8/Zs2axZdffomNjQ0ff/wxiYmJJCQkAJCYmIiFhQX16tUrday7uzuJiYnlvladTkr16dOH+vXrl3qsoKCAuLg4bG1tS2UFqztFUcjOzsbOzg6VSlXV4dQKBQUFWFlZ0aNHjxo1Fuoag8HA1q1b6devHzqdrqrDEULGpKhxZMyKmqimj9uyXq+rVCoGDRpUBdGI8qjpY07UfvHx8QCcPHmyVJ6jorOkAHQ6HWvXrmXy5Mk4OTmh0Wjo27fvDcv9/k5RlArlJOp0Ukqr1V73C8VoNKJSqVCr1ajVNWdxwmsle9diF3dOrVajUqnQ6XTyh6cGkH8nUd3ImBQ1jYxZURPVpnGrglpzL7VZbRpzonbRas3pHTs7O+zt7e/4fEFBQYSHh5OZmUlRURGurq506tSJDh06AODh4UFRURHp6emlZkslJyfTtWvXcl9HshdCCCGEEEIIIYQQ4joODg64uroSHR3N4cOHGTZsGGBOWul0ulIlrQkJCURERFQoKegvCq4AACAASURBVFWnZ0oJIYQQQgghhBBC1DU5OTmcPXu25PuYmBjCw8NxcnLC19eXn376CVdXV3x9fTlx4gQvvPACw4cPL2ls7uDgwOTJk5kxYwbOzs44OTnx0ksv0bp165LV+MpDklJCCCGEEEIIIYQQdcjhw4e5//77S76fPn06ABMnTmTZsmUkJCQwffp0kpKS8PT0ZMKECcyePbvUOebPn49Wq+Xhhx8mPz+fPn36sGzZsgqtXi9JKSGEEEIIIYQQQog6pFevXiiKcsPtzz//PM8///xNz2FpacmCBQtYsGDBbcchPaWEEEIIIYQQQgghxD0nSalaJjk5malTp+Lr68v/s3fn8VHV9/7H35OZJJOEkBCWZAIzbBJlx4IIqCxlR1ErVX9KcaEVe7X2UlRaKVbaRmqpSutWvBYEF6RWxfZeKRSXgAoooKDIEoFAEpywZiHLJDMn8/tjzEhIAklIMktez8cjj0nO+c45n5N8MzDvfL/fEx0drZSUFE2cOFGbN2+WJHXr1k0mk0mrVq2q8dy+ffvKZDJp+fLlNfYtXLhQZrNZjz32WL3qeOGFF3TVVVepXbt2ateuncaNG6dPP/20Whuv16sFCxYoNTVVMTExGj16tL766qtqbfLz8zVjxgwlJCQoISFBM2bMUEFBQT2/GwAAAAAAIFgRSoWZG2+8UTt37tSKFSuUmZmpf/3rXxo9erROnTrlb2O32/Xiiy9We96WLVuUl5enuLi4Wo/74osvau7cuVq2bFm96sjIyNAtt9yiDz74QJs3b5bD4dCECRN05MgRf5tFixbpySef1DPPPKOtW7cqJSVF48eP1+nTp/1tbr31Vu3YsUNr167V2rVrtWPHDs2YMaMh3xIAAAAAABCEWFOqPrxeyV0amHNHxkomU72aFhYW6qOPPlJGRoZGjRolSeratauGDh1ard306dO1ePFi5eTkyG63S5KWLVum6dOn66WXXqpx3A0bNqisrEy/+93v9NJLL2njxo0aOXLkOWt59dVXq339wgsv6I033tB7772n2267TV6vV3/+85/161/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\n",
+          "text/plain": "<Figure size 1200x900 with 4 Axes>"
+         },
+         "metadata": {},
+         "output_type": "display_data"
+        }
+       ]
+      }
+     },
+     "a14d29c88a1445f3bef0774e5bc12849": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.2.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "d6816ca749c54810802e943cebab03c1": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.5.0",
+      "model_name": "TextModel",
+      "state": {
+       "continuous_update": false,
+       "description": "Ticker:",
+       "layout": "IPY_MODEL_6e2d7204349549afa6f8bdc84746d79b",
+       "placeholder": "Enter ticker ...",
+       "style": "IPY_MODEL_57268dea02f74c879e57c489d206afed",
+       "value": "MSFT"
+      }
+     }
+    },
+    "version_major": 2,
+    "version_minor": 0
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/misc/areplot-primitive.ipynb b/misc/areaplot-primitive.ipynb
similarity index 100%
rename from misc/areplot-primitive.ipynb
rename to misc/areaplot-primitive.ipynb
diff --git a/pyproject.toml b/pyproject.toml
index 24f08ea..fff459c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -19,7 +19,7 @@ classifiers = [
 ]
 
 [dependency-groups]
-dev = ["numpy<2.0.0", "yfinance", "pytest", "nbmake", "ipykernel", "ta-lib", "ruff"]
+dev = ["numpy<2.0.0", "yfinance", "ta-lib", "pytest", "nbmake", "ipykernel", "jinja2", "ipywidgets", "ruff"]
 
 
 [tool.hatch.build]
diff --git a/src/mplchart/chart.py b/src/mplchart/chart.py
index edeba7b..3f4537b 100644
--- a/src/mplchart/chart.py
+++ b/src/mplchart/chart.py
@@ -11,7 +11,7 @@
 
 from .wrappers import get_wrapper
 from .colors import closest_color
-from .utils import series_xy, same_scale
+from .utils import series_xy, same_scale, get_info
 from .layout import make_twinx, StandardLayout
 from .mapper import RawDateMapper, DateIndexMapper
 
@@ -297,7 +297,7 @@ def get_target(self, indicator):
         if indicator is None:
             return "same"
 
-        default_pane = getattr(indicator, "default_pane", None)
+        default_pane = get_info(indicator, "default_pane", None)
         if default_pane is not None:
             return default_pane
 
@@ -433,7 +433,7 @@ def plot_indicator(self, data, indicator):
             indicator = wrapper
 
         # Select axes according to indicator properties (default_pane, same_scale)
-        # target = self.default_pane(indicator)
+        # target = self.get_target(indicator)
         # ax = self.get_axes(target)
         ax = None
 
diff --git a/src/mplchart/utils.py b/src/mplchart/utils.py
index 0bbbad8..97ab434 100644
--- a/src/mplchart/utils.py
+++ b/src/mplchart/utils.py
@@ -7,6 +7,19 @@
 TALIB_SAME_SCALE = "Output scale same as input"
 
 
+
+def get_info(indicator, name: str, default=None):
+    """get indicator info"""
+
+    if hasattr(indicator, "info"):  # talib
+        info = indicator.info
+    else:
+        info = vars(indicator)
+
+    return info.get(name, default)
+
+
+
 def same_scale(indicator):
     """Whether indicator uses the same scale as inputs"""
 
@@ -14,7 +27,7 @@ def same_scale(indicator):
         flags = indicator.function_flags or ()
         return TALIB_SAME_SCALE in flags
 
-    return getattr(indicator, "same_scale", False)
+    return get_info(indicator, "same_scale", False)
 
 
 def get_name(indicator):
diff --git a/src/mplchart/wrappers.py b/src/mplchart/wrappers.py
index 380da24..889f92e 100644
--- a/src/mplchart/wrappers.py
+++ b/src/mplchart/wrappers.py
@@ -7,7 +7,7 @@
 from functools import singledispatch
 
 from .model import Wrapper
-from .utils import get_name, get_label
+from .utils import get_name, get_label, get_info
 
 
 @singledispatch
@@ -107,12 +107,12 @@ def plot_result(self, data, chart, ax=None):
             )
             counter += 1
 
-        yticks = getattr(self.indicator, "yticks", ())
+        yticks = get_info(self.indicator, "yticks", ())
         if yticks:
             ax.set_yticks(yticks)
             ax.grid(axis="y", which="major", linestyle="-", linewidth=2)
 
-        oversold = getattr(self.indicator, "oversold", None)
+        oversold = get_info(self.indicator, "oversold", None)
         if oversold is not None:
             color = chart.get_color("oversold", ax, self.indicator, fallback="fill")
             with np.errstate(invalid="ignore"):
@@ -126,7 +126,7 @@ def plot_result(self, data, chart, ax=None):
                     alpha=0.5,
                 )
 
-        overbought = getattr(self.indicator, "overbought", None)
+        overbought = get_info(self.indicator, "overbought", None)
         if overbought is not None:
             color = chart.get_color("overbought", ax, self.indicator, fallback="fill")
             with np.errstate(invalid="ignore"):
diff --git a/uv.lock b/uv.lock
index f1b8b4e..4affbea 100644
--- a/uv.lock
+++ b/uv.lock
@@ -554,6 +554,22 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/47/6b/d9fdcdef2eb6a23f391251fde8781c38d42acd82abe84d054cb74f7863b0/ipython-8.18.1-py3-none-any.whl", hash = "sha256:e8267419d72d81955ec1177f8a29aaa90ac80ad647499201119e2f05e99aa397", size = 808161 },
 ]
 
+[[package]]
+name = "ipywidgets"
+version = "8.1.5"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "comm" },
+    { name = "ipython" },
+    { name = "jupyterlab-widgets" },
+    { name = "traitlets" },
+    { name = "widgetsnbextension" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c7/4c/dab2a281b07596a5fc220d49827fe6c794c66f1493d7a74f1df0640f2cc5/ipywidgets-8.1.5.tar.gz", hash = "sha256:870e43b1a35656a80c18c9503bbf2d16802db1cb487eec6fab27d683381dde17", size = 116723 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/22/2d/9c0b76f2f9cc0ebede1b9371b6f317243028ed60b90705863d493bae622e/ipywidgets-8.1.5-py3-none-any.whl", hash = "sha256:3290f526f87ae6e77655555baba4f36681c555b8bdbbff430b70e52c34c86245", size = 139767 },
+]
+
 [[package]]
 name = "jedi"
 version = "0.19.2"
@@ -566,6 +582,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9", size = 1572278 },
 ]
 
+[[package]]
+name = "jinja2"
+version = "3.1.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "markupsafe" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ed/55/39036716d19cab0747a5020fc7e907f362fbf48c984b14e62127f7e68e5d/jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369", size = 240245 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/31/80/3a54838c3fb461f6fec263ebf3a3a41771bd05190238de3486aae8540c36/jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d", size = 133271 },
+]
+
 [[package]]
 name = "jsonschema"
 version = "4.23.0"
@@ -624,6 +652,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c9/fb/108ecd1fe961941959ad0ee4e12ee7b8b1477247f30b1fdfd83ceaf017f0/jupyter_core-5.7.2-py3-none-any.whl", hash = "sha256:4f7315d2f6b4bcf2e3e7cb6e46772eba760ae459cd1f59d29eb57b0a01bd7409", size = 28965 },
 ]
 
+[[package]]
+name = "jupyterlab-widgets"
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 version = "3.9.3"
@@ -914,6 +1019,8 @@ dependencies = [
 [package.dev-dependencies]
 dev = [
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+    { name = "ipywidgets" },
+    { name = "jinja2" },
     { name = "nbmake" },
     { name = "numpy" },
     { name = "pytest" },
@@ -932,6 +1039,8 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
     { name = "ipykernel" },
+    { name = "ipywidgets" },
+    { name = "jinja2" },
     { name = "nbmake" },
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