diff --git a/stride/physics/common/devito.py b/stride/physics/common/devito.py
index a5e688d1..4dba6bed 100644
--- a/stride/physics/common/devito.py
+++ b/stride/physics/common/devito.py
@@ -238,7 +238,7 @@ def __init__(self, space_order, time_order, time_dim=None, **kwargs):
 
         if space is None:
             origin = (0,)
-            extended_shape = (1,)
+            extended_shape = (2,)
             extended_extent = (1,)
         else:
             extra = space.absorbing
@@ -286,7 +286,7 @@ def __init__(self, space_order, time_order, time_dim=None, **kwargs):
         if parent_grid is not None:
             dimensions = parent_grid.dimensions
             time_dimension = devito.TimeDimension(name='time_inner',
-                                                  spacing=devito.types.Scalar(name='dt_inner', is_const=True))
+                                                  spacing=devito.Scalar(name='dt_inner', is_const=True))
             self.num_inner = kwargs.pop('num_inner', 1)
         else:
             self.num_inner = None
@@ -691,7 +691,7 @@ def sparse_function(self, name, num=1, space_order=None,
 
             reference_gridpoints, coefficients = self._calculate_hicks(coordinates)
 
-            fun = devito.PrecomputedSparseFunction(r=r,
+            fun = devito.PrecomputedSparseFunction(r=r+1,
                                                    gridpoints=reference_gridpoints,
                                                    interpolation_coeffs=coefficients,
                                                    **sparse_kwargs)
diff --git a/stride/physics/common/import_devito.py b/stride/physics/common/import_devito.py
index 043740c4..896cb375 100644
--- a/stride/physics/common/import_devito.py
+++ b/stride/physics/common/import_devito.py
@@ -1,7 +1,8 @@
 
 from devito import *  # noqa: F401
-from devito.types import Symbol  # noqa: F401
+from devito.types import Symbol, Scalar  # noqa: F401
 from devito.symbolics import INT, IntDiv  # noqa: F401
+from devito import TimeFunction as TimeFunctionOSS  # noqa: F401
 
 try:
     from devitopro import *  # noqa: F401
diff --git a/stride/physics/iso_acoustic/devito.py b/stride/physics/iso_acoustic/devito.py
index 6a357531..e58ae550 100644
--- a/stride/physics/iso_acoustic/devito.py
+++ b/stride/physics/iso_acoustic/devito.py
@@ -381,7 +381,7 @@ def before_forward(self, wavelets, vp, rho=None, alpha=None, **kwargs):
                     # ValueError: Cannot access `shape_allocated` as unfinalized - so no size estimate
                     pass
 
-                if self._needs_grad(wavelets, rho, alpha):
+                if self._needs_grad(wavelets, rho, alpha, **kwargs):
                     p_saved_expr = p
                 else:
                     p_saved_expr = self._forward_save(p)
@@ -1595,8 +1595,9 @@ def _weights(self):
     def _dt_max(self, k, h, vp_max):
         return k * h / vp_max * 1 / np.sqrt(self.space.dim)
 
-    def _needs_grad(self, *wrt):
-        return any(v is not None and v.needs_grad for v in wrt)
+    def _needs_grad(self, *wrt, **kwargs):
+        force_raw_wavefield = kwargs.pop('force_raw_wavefield', False)
+        return any(v is not None and v.needs_grad for v in wrt) or force_raw_wavefield
 
     def _forward_save(self, field):
         return field.dt2
diff --git a/stride/physics/marmottant/devito.py b/stride/physics/marmottant/devito.py
index bbd61b7b..5eff28ae 100644
--- a/stride/physics/marmottant/devito.py
+++ b/stride/physics/marmottant/devito.py
@@ -174,7 +174,10 @@ def run_forward(self, *args, **kwargs):
         """
         functions = dict()
 
+        time_bounds = kwargs.get('time_bounds', (0, self.time.extended_num))
         self.state_operator.run(dt=self.time.step,
+                                time_m=1,
+                                time_M=time_bounds[1]-1,
                                 **functions,
                                 **kwargs.pop('devito_args', {}))
 
@@ -286,7 +289,7 @@ def sub_stencil(self, **kwargs):
             rho = parent_grid.vars.rho
         except AttributeError:
             rho = self.dev_grid.vars.rho_sparse
-        vp2 = parent_grid.vars.vp2
+        vp2 = parent_grid.vars.vp**2
 
         inject_term = v_inject.inject(field=p_out.forward, expr=vp2 * self.time.step**2 * rho * inject_scale * v_inject)
 
@@ -481,6 +484,7 @@ def _make_saved_time_function(self, name, num, **kwargs):
                                            shape=(self.time.num, num),
                                            space_order=self.space_order,
                                            time_order=self.time_order,
+                                           layers=devito.NoLayers,
                                            **kwargs)
 
     def _make_interp_function(self, name, value, x_0, num, **kwargs):
@@ -519,7 +523,7 @@ def _make_interp_function(self, name, value, x_0, num, **kwargs):
         return fun, dense_fun, interp_term
 
     def _make_interp_time_function(self, name, value, x_0, num, **kwargs):
-        if not isinstance(value, devito.TimeFunction):
+        if not isinstance(value, devito.TimeFunctionOSS):
             fun = self._make_saved_time_function(name, num=num, save=self.time.num)
             fun.data[:] = value.data.T
 
@@ -541,7 +545,7 @@ def _make_interp_time_function(self, name, value, x_0, num, **kwargs):
 
             dense_fun = value
 
-            interp_term = fun.interpolate(expr=dense_fun.forward)
+            interp_term = fun.interpolate(expr=dense_fun)
 
             if x_0 is None:
                 raise ValueError('Bubble location x_0 needs to be provided when'
diff --git a/stride_examples/examples/marmottant/01_isolated_bubble.ipynb b/stride_examples/examples/marmottant/01_isolated_bubble.ipynb
index c41acdf7..6518c720 100644
--- a/stride_examples/examples/marmottant/01_isolated_bubble.ipynb
+++ b/stride_examples/examples/marmottant/01_isolated_bubble.ipynb
@@ -35,7 +35,7 @@
    "outputs": [],
    "source": [
     "from stride import *\n",
-    "%matplotlib notebook\n",
+    "%matplotlib widget\n",
     "\n",
     "import numpy as np"
    ]
@@ -142,976 +142,24 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\n",
-       "        'matplotlib',\n",
-       "        mpl.mpl_figure_comm\n",
-       "    );\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "05355492d8574467a4644d158a624a94",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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\" width=\"640\">"
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
       ],
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -1155,15 +203,8 @@
       "\t * develop-mode=False\n",
       "\t * mpi=False\n",
       "\t * log-level=DEBUG\n",
-      "\t * language=openmp\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/carlos/anaconda3/envs/stride/lib/python3.10/site-packages/devito/types/grid.py:259: RuntimeWarning: divide by zero encountered in true_divide\n",
-      "  spacing = (np.array(self.extent) / (np.array(self.shape) - 1)).astype(self.dtype)\n"
+      "\t * language=openmp\n",
+      "(1,) (2,) (0,) None None\n"
      ]
     }
    ],
@@ -1192,23 +233,25 @@
      "text": [
       "Preparing to run state for shot\n",
       "Operator `marmottant_state` instance configuration:\n",
-      "\t * subs={h_x: inf}\n",
+      "\t * name=marmottant_state\n",
+      "\t * subs={h_x: 1.0, dt: 1e-09}\n",
       "\t * opt=advanced\n",
-      "\t * platform=None\n",
-      "Operator `marmottant_state` generated in 1.45 s\n",
-      "  * lowering.Clusters: 1.08 s (74.6 %)\n",
-      "     * specializing.Clusters: 0.92 s (63.5 %)\n",
-      "        * factorize: 0.73 s (50.4 %)\n",
-      "Flops reduction after symbolic optimization: [630 --> 416]\n",
-      "Operator `marmottant_state` fetched `/tmp/devito-jitcache-uid1000/42d2540bcb52f6a80e3aef4063241c7306ce6d08.c` in 0.05 s from jit-cache\n",
+      "Operator `marmottant_state` generated in 1.31 s\n",
+      "  * lowering.Clusters: 0.72 s (55.1 %)\n",
+      "     * specializing.Clusters: 0.54 s (41.3 %)\n",
+      "  * lowering.IET: 0.30 s (23.0 %)\n",
+      "Flops reduction after symbolic optimization: [630 --> 256]\n",
+      "Operator `marmottant_state` fetched `/tmp/devito-jitcache-uid1000/e9e3f685842ec174ed3869ab97a7d760599c89d0.c` in 0.12 s from jit-cache\n",
       "Running state equation for shot\n",
       "AutoTuner: could not perform any runs\n",
-      "Operator `marmottant_state` ran in 0.02 s\n",
-      "Global performance: [OI=3.39, 0.22 GFlops/s, 0.01 GPts/s]\n",
+      "Operator `marmottant_state` ran in 0.06 s\n",
+      "Global performance: [OI=2.05, 0.05 GFlops/s, 0.01 GPts/s]\n",
+      "Global performance <w/o setup>: [0.06 s, 0.01 GPts/s]\n",
       "Local performance:\n",
-      "  * section0<1> ran in 0.01 s [OI=0.63, 0.01 GFlops/s]\n",
-      "  * section1<9999,1> ran in 0.02 s [OI=3.39, 0.33 GFlops/s, 0.01 GPts/s]\n",
-      "Performance[mode=advanced] arguments: {'nthreads': 6}\n",
+      "  * section0 ran in 0.03 s [OI=0.63, 0.01 GFlops/s]\n",
+      "  * section1 ran in 0.04 s [OI=2.05, 0.08 GFlops/s, 0.01 GPts/s]\n",
+      "Performance[mode=advanced] arguments: {'nthreads': 6, 'pthreads': 0}\n",
+      "Completing state equation run for shot\n",
       "Completed state equation run for shot\n"
      ]
     }
@@ -1237,976 +280,24 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\n",
-       "        'matplotlib',\n",
-       "        mpl.mpl_figure_comm\n",
-       "    );\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6eb9a293335b4e7aafc5484d368b1e3d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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\" width=\"640\">"
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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i5S21E2uFsBIYAAAACJAFKuHD58WPHx8Tp06JC6d++uqVOnymKxeH2+06dPq1u3bvr777/VqlUrzZ8/XyEhIR6do169epoxY4aaN2+uv/76SzNmzCh035CQEIWHh+d5oPxztwJCFywAACARQMqNEydOKD4+Xjt37lSHDh00a9YsBQUFeX2+zMxM9ejRQ2vXrlWzZs20ePFiValSxatzBQQE6Oabb5Z0vnsY/IuzCghdsAAAQH4EkHLAWqnYtGmT2rRpowULFhRp6t3s7GzdcccdWr58uWJiYrR06VJFREQUqY3Wm1BnXbBwYXJW5aALFgAAyI8AUsbZVyri4uKKVKmQzk/fO2DAAM2fP19RUVFatmyZoqKiitTG7Oxsfffdd5LOz4gF/0IFBAAAeIIAUobl5OSob9++Wr58uRo1aqSlS5eqRo0aLo+bOHGioqOj1bdv3wLbhg0bpunTpysiIkLLli1Tw4YN3WrLgAEDtG7dOhlj8ry+efNm9ejRQ1u3blXt2rV1++23u/fmcMFgDAgAAPAE64CUYTNnzrStzREQEKA+ffo43C8yMtK2KKEknTx5Unv37lV0dHSe/X755RdNmjRJ0vnVzu+///5Cr71q1ao8z6dNm6Zp06apSpUqiomJUYUKFXTgwAEdOXJExhjVrFlT8+fPZ2C5H3JWAclf9TDGFGniBAAAUP4RQMow+0X7kpKSlJSU5HC/Bg0aeHy+5ORkj6bB/fTTT/XDDz/ot99+U3JystLS0hQeHq5rrrlG3bp108MPP6zq1au7fT5cODwJILm5uQoMDCyVdgEAgLLJYvL3qQFKSVpamqpWrarU1FQqJ+XY/Pnz1aNHD0lSpUqVdPr0adu2hx9+WO+//77teWZmpoKDg0u9jQAAFBfuX4qOMSAAisTTCggAAPBvBBAAReJsoDkBBAAA5EcAAVAkziog+Xt4EkAAAAABBECR5F/rwz505A8cTMULAAAIIACKxL4CIuUNHXTBAgAA+RFAABRJ/gDibPVzAggAACCAACgSZwPPCSAAACA/AgiAIvGkAsIYEAAAQAABUCT5QwVdsAAAgDMEEABu2blzp3bv3l3gdQIIAADwRAVfNwBA2Zeenq7Y2Fjb16GhobZtzrpZ0QULAADkRwUEgEvJyckOv5Y8CyBUQAAAAAEEgEuHDh2yfZ2WlpZnGwEEAAB4ggACwKUzZ87Yvk5NTc2zjQACAAA8QQAB4FJmZqbt6/T09DzbGAMCAAA8QQAB4FJGRobta/swIjkPGcYYp/sCAAD/QwAB4JJ96Dh37lyebflDBl2wAACAMwQQAC7ZBxBPKiB0wQIAAPkRQAC4ZN8FK38FhEHoAADAEwQQAC55UgGxf04AAQAA+RFAALjkSQWEAAIAAJwhgABwqbgqIIwBAQAABBAALjmbBYsKCAAA8AQBBIBLnqwDQgABAADOEEAAuGQfOrKysvJsowsWAADwBAEEgEv2FZD8IYIKCAAA8AQBBIBL9hWQ7OzsPNvyr4ROAAEAAM4QQAC4ZB868gcQKiAAAMATBBAALtmHDk+6YOWvjjAGBAAAEEAAuEQFBAAAFBcCCACX7CsXriog9lUPZsECAAD5EUAAuFRcFZD8XbIAAID/IYAAcIkuWAAAoLgQQAC45O0gdCogAAAgPwIIAJeKWgGxWCwO9wUAAP6HAALApaIGkMDAQIf7AgAA/0MAAeCSs1mw3FkJvUKFCg73BQAA/ocAAsAlKiAAAKC4EEDKMGOMVq1apZEjR6pdu3aqVq2agoODFRUVpd69e2vFihUen3PDhg169tln1aFDB0VERCgoKEg1a9ZU165dNWfOnEKP2759uyZMmKAuXbqodu3aCgoKUo0aNdSpUyd98skn3Fhe4Io6CJ0KCAAAsKrg6wagcMuXL1fnzp0lSQEBAYqNjVWlSpWUlJSk2bNna/bs2RozZozGjRvn1vl27typli1b2p43bNhQ0dHR2rVrlxYvXqzFixerf//++vjjjxUQ8L9smpOTo8aNG9ue161bV1deeaX27dunlStXauXKlZoxY4bmzZun0NDQYnr3KEuKWgGxBhCCKgAAoAJShhljFBsbq8mTJ+v48ePatm2bEhMTlZKSolGjRkmSxo8fr2+//dbt80VGRurll1/WwYMHtWvXLq1fv17Hjx/XpEmTZLFYNG3aNE2ePLnAcdWqVdOYMWO0c+dOJScn67ffftORI0f01VdfKSwsTEuWLNGYMWOK/XuAsoEuWAAAoLgQQMqwtm3basuWLXr44YdVvXp12+vBwcF66aWX1LVrV0nSlClT3Dpf3bp1tWPHDj355JOKjIy0vR4QEKChQ4fqwQcfdHi+wMBA7dq1S+PGjVNMTEyebXfccYeee+45SdLHH3/MDeYFytsuWNYuV3TBAgAAVgSQMiw8PNx24+ZIfHy8pPPjM9wRGhqqihUrFrq9S5cuDs9nsVjyBKDCjvvnn3907Ngxt9qC8sU+dNAFCwAAFAUBpBzLyMiQJIWFhfn0fNbjirMtKFuKOgidLlgAAMCKAFJOGWM0a9YsSVL79u2L5ZwzZ8706nzW4y677DKFh4cXS1tQthTXIHS6YAEAAGbBKqemTJmiDRs2KDg4WMOHDy/y+ZYsWaK5c+dKkkaOHOn2cZs2bbINWn/yySed7puZmanMzEzb87S0NM8bCp9gFiwAAFBcqICUQ4mJiRo2bJik87NgNWrUqEjn27dvn+666y5J0pAhQ3T99de7ddzJkyfVu3dvnTt3Tt26ddM999zjdP8JEyaoatWqtke9evWK1G6UHmddsNxZCZ0uWAAAwIoAUs7s3r1bCQkJysjIUL9+/TRixIgine/EiRPq2rWrjh8/ro4dO+qNN95w67jMzEzddttt2r59u+Li4vT555+7PGbUqFFKTU21PZKTk4vUdpSe4pqGly5YAACALljlyOHDhxUfH69Dhw6pe/fumjp1qiwWi9fnO336tLp166a///5brVq10vz58xUSEuLyuOzsbN1555368ccfFR0drSVLljidJcsqJCTErfOj7CnqLFhUQAAAgBUVkHLixIkTio+P186dO9WhQwfNmjVLQUFBXp8vMzNTPXr00Nq1a9WsWTMtXrxYVapUcXmcMUb33Xef5s2bp8jISC1btkxRUVFetwNlX25ubp7KhatZsOz3ZRA6AADIjwBSDlgrFZs2bVKbNm20YMGCIk13m52drTvuuEPLly9XTEyMli5dqoiICLeOHTp0qD7//HNddNFFWrp0aZHHn6Ds86Tikf85g9ABAEB+BJAyzr5SERcX53alojDGGA0YMEDz589XVFSURxWM0aNHa/LkyapSpYoWL16suLg4r9uB8iN/ACmsAmLtDkgXLAAA4AwBpAzLyclR3759tXz5cjVq1EhLly5VjRo1XB43ceJERUdHq2/fvgW2DRs2TNOnT1dERISWLVumhg0butWWN954Qy+99JLCwsL07bffqnXr1h6/H5RP7lZAHFU56IIFAADyYxB6GTZz5kzb2hwBAQHq06ePw/0iIyNtixJK56fH3bt3r6Kjo/Ps98svv2jSpEmSzq9Yfv/99xd67VWrVtm+PnjwoG22rSpVqujpp58u9Livv/5atWvXdvq+UL64u/J5hQoVlJWVRRcsAADgFAGkDLNftC8pKUlJSUkO92vQoIHH50tOTnZ7Gtxz587ZPrk+evSojh49Wui+GRkZbp0T5Ye3FRD7agddsAAAgBVdsMqwAQMGyBjj8rFnz548x40dO1bGGK1cuTLP6x07dnTrfPm7yURHR7t9XP6qC8o/d8eAOAsgdMECAABWBBAATrmqgFhDRf4AYr8fXbAAAIAVAQSAU952wbLfjy5YAADAigACwCl3u2DlDxmOAghdsAAAAAEEgFOezIJl/5wKCAAAcIQAAsCp4uiCxSB0AABgRQAB4JQ1gNiHCPsg4U4XLAahAwAAKwIIAKesASQkJMT2mjuLDbrTBSsnJ0dvv/221q9fXwItBwAAZRELEQJwyhpAgoKCbK/l5uYWCBXedMH65ptvNGzYMEVFRenAgQMl9A4AAEBZQgUEgFPWABIcHGx7zdMKSGFdsJYvXy5JOnjwIONDAADwEwQQAE5ZZ8Gy74JlPzNWUbpghYaG2r5OTU0tzmYDAIAyigACwClXFRBXK6FbLBYFBATk2dcqKyvL9nVKSkpxNx0AAJRBBBAAThW1C1ZAQIAtgOSvgJw6dcr29enTp4u76QAAoAwigABwytEsWM66YFmrHNY/AwICZLFY8uxrlZaWZvv6zJkzxd10AABQBhFAADhV2CxY+b/2pgsWFRAAAPwP0/AWwdGjR7V3714dO3ZM6enpioiI0MUXX6zGjRvbBt0C5V1xdMEqrAJiX/UggAAA4B8IIB5aunSpvvrqK/3000/auXOnw30qVqyodu3a6aabbtI999yjWrVqlXIrgeJj7W4VFBQki8UiY4xHs2A5GwNy7tw529cEEAAA/AMBxA0ZGRmaNGmS3nvvPe3du9fWjSQsLEw1a9ZUjRo1FBYWphMnTujEiRM6evSofvjhBy1fvlyjR49WQkKCnn76abVq1crH7wTwnLUCUqFCBQUEBCgnJ8dhBST/VLuOAkj+LlgEEAAA/A8BxIWPP/5Yzz33nA4cOKCQkBDdeuutSkhIUNu2bRUXF2e7sbJ34sQJrVu3TqtWrdLMmTM1Z84czZ07V3fccYf+85//qEGDBj54J4B33A0g3nTBsp+GlwACAIB/YBC6C4MHD1ZISIjef/99HTlyRHPmzNGgQYN0+eWXOwwfklSjRg3dfPPNGj9+vLZv367ffvtNd999t7755htNmzatlN8BUDT2AcTRgoKedMFyVgFJT08vieYDAIAyhgqIC9OmTVO/fv2KNKi8VatWmjZtmsaOHav9+/cXY+uAkmcNIIGBgbYgURJjQDIyMkqi+QAAoIwhgLhwzz33FNu5GjZsqIYNGxbb+YDSYA0b1i5YUvHNgkUAAQDA/9AFC4BTrrpgWbtVedMFy34MCAEEAAD/QAAB4FT+QegSXbAAAID36IJVBN9//70WL16sXbt26fTp0wU+3bWyWCz64YcfSrl1QPFwFEDoggUAALxFAPFCWlqabrvtNv3444+Fhg571psvoDwqqVmwcnJy8lRSCCAAAPgHAogXnnrqKa1cuVI1atTQAw88oBYtWujiiy8maOCC5O0sWNawYbFYHFZA7Md/SAQQAAD8BQHEC7Nnz1ZQUJB+/PFHxcXF+bo5QIkqjlmwHB1HAAEAwD8xCN0LZ86cUePGjQkf8AvFMQbEURcs+/EfEgEEAAB/QQDxQpMmTVi1GX7D2RgQY4wtVOTf5moQOgEEAAD/RADxwr/+9S/t3LlTK1eu9HVTgBLnbBpe+4qGswBCBQQAAFgRQLxw33336ZFHHlGvXr00adIknT592tdNAkqMo0Ho+UOG5PkYEAIIAAD+iUHoXnrllVeUnJys4cOHa/jw4br44otVsWJFh/taLBbt3LmzlFsIFA9XXbCsPF0HhEHoAAD4JwKIF44cOaLOnTvr77//tt2AHT16tND9mZ4X5Zm1u5WjaXgdVUCs/yZcdcEigAAA4J8IIF546qmntHnzZsXGxmrkyJG68sorWQcEFyxrBSQoKKhYu2DZryUiEUAAAPAXBBAvLF68WKGhoVq5cqWioqJ83RygRNmPASlsoLnkeRcs69chISHKzMxURkaGjDEEeQAALnAMQvfCmTNn1KRJE8IH/IKjhQiddcHKH0AsFovDLljWc9iPnco/MB0AAFx4CCBeuPzyy5WSkuLrZgClwtlChI4CSP4pegvrgmX9ulKlSrbX6IYFAMCFjwDihZEjRyo5OVkzZ870dVOAEudpFyxHg9CddcEKDQ21vcYCnwAAXPgIIF7o2bOn3n77bQ0ePFhPPPGENm/ezCe3uGA56oLlyRgQV12wAgMDbSEkMzOzxN4HAAAoGwggXggMDNSwYcN05swZTZw4UVdccYUqVapk+4Q4/8N6Y+YpY4xWrVqlkSNHql27dqpWrZqCg4MVFRWl3r17a8WKFR6fc8OGDXr22WfVoUMHRUREKCgoSDVr1lTXrl01Z86cQo87efKkvvrqKz3xxBO69tprVbFiRVksFnXu3Nmr94byw9FChI7GgBS2RoirCkhgYKDCwsIk0QULAAB/wCxYXrD/FLck9rdavny57QY/ICBAsbGxqlSpkpKSkjR79mzNnj1bY8aM0bhx49w6386dO9WyZUvb84YNGyo6Olq7du3S4sWLtXjxYvXv318ff/yx7UbTauXKlerbt69X7wPlm7OFCO0DRWHVkcLWAbGGmICAAFsFhAACAMCFjwqIF3Jzcz1+eMMYo9jYWE2ePFnHjx/Xtm3blJiYqJSUFI0aNUqSNH78eH377bduny8yMlIvv/yyDh48qF27dmn9+vU6fvy4Jk2aJIvFomnTpmny5MkFjg0LC9P111+vESNGaObMmXrppZe8ek8of5x1wXI00Dz/GBD7LliFVUAIIAAA+A8qIGVY27ZttWXLlgJduIKDg/XSSy9p48aNWrRokaZMmaKEhASX56tbt6527NiRZ9pT6fzN49ChQ7V582a9//77mjJlioYOHZpnn5tuukk33XST7fnUqVO9f2MoV9zpguUoZLjqgkUFBAAA/0QFpAwLDw93On4kPj5ekrR9+3a3zhcaGlogfNjr0qWLR+eDf3CnC5ajqXZddcGiAgIAgH8igLhw9uzZMns+682adQBvWTsfLgzOFiJ0ttaHu12wqIAAAOBfCCAuREdH6+WXX9bp06eLdJ41a9bo5ptv1uuvv14s7TLGaNasWZKk9u3bF8s5reuaFNf5cGGw74Jl7UrlaJxH/m5WdMECAACOEEBciImJ0ahRo1SvXj0NGjRIS5cutd04uXLw4EG9+eabat26ta677jqtWrVKl112WbG0a8qUKdqwYYOCg4M1fPjwIp9vyZIlmjt3rqTzCy2WhMzMTKWlpeV5oOxzthK6p4PQ6YIFAAAYhO7Cr7/+qlmzZmn06NH65JNPNHXqVIWGhqpFixZq1aqVIiMjVaNGDYWEhOjkyZM6ceKEtmzZovXr12vv3r0yxqhChQoaPHiwnn/+edWuXbvIbUpMTNSwYcMknZ8Fq1GjRkU63759+3TXXXdJkoYMGaLrr7++yG10ZMKECXr++edL5NwoOfYLBnoy05Wz7ln256UCAgCAfyGAuKFPnz66/fbbtXjxYn3wwQdauHCh1qxZozVr1ti6ltiz3ng1bNhQAwcO1MCBAxUZGVksbdm9e7cSEhKUkZGhfv36acSIEUU634kTJ9S1a1cdP35cHTt21BtvvFEs7XRk1KhRevzxx23P09LSVK9evRK7HoqHpxUQR4PQXS1EaA0g6enpJfpeAACA7xFA3GSxWNS1a1d17dpVZ8+e1S+//KI1a9Zo7969On78uDIyMlSjRg3VrFlTV155pa699lrFxsYWaxsOHz6s+Ph4HTp0SN27d9fUqVMdBiB3nT59Wt26ddPff/+tVq1aaf78+QoJCSnGFucVEhJSoudHybAPIPmDhLMKiKsuWFRAAADwTwQQL1SsWFE33nijbrzxxlK75okTJxQfH6+dO3eqQ4cOmjVrloKCgrw+X2Zmpnr06KG1a9eqWbNmWrx4sapUqVKMLcaFwlkXLGcVEFeD0BkDAgCAf2IQejlgrVRs2rRJbdq00YIFC4o0VW52drbuuOMOLV++XDExMVq6dKkiIiKKscW4kDjrguVsFix31wGhAgIAgH8hgJRx9pWKuLi4IlcqjDEaMGCA5s+fr6ioKC1btkxRUVHF2GJcaJx1wfJ0FiwGoQMAAAJIGZaTk6O+fftq+fLlatSokZYuXaoaNWq4PG7ixImKjo5W3759C2wbNmyYpk+froiICC1btkwNGzYsiabjAuKoC5Y7Y0DoggUAABxhDEgZNnPmTNvaHAEBAerTp4/D/SIjI22LEkrSyZMntXfvXkVHR+fZ75dfftGkSZMknV/t/P777y/02qtWrSrwmn03rczMTEnSTz/9lOf1d955x2HwQfnlqAuWO2NAXHXBogICAIB/IoCUYdabfElKSkpSUlKSw/0aNGjg8fmSk5OVnJzsUXtSUlIKvJaVlZXndW4gLzzWoOBqDIgn2+y/pgICAIB/oQtWGTZgwAAZY1w+9uzZk+e4sWPHyhijlStX5nm9Y8eObp3P/lNqe+4cN2DAgJL5ZsBnrBWQwMBApwPNnY0PcdQFiwoIAAD+iQACwKmS6oJFBQQAAP9EAAHglKeD0POHE1ddsKiAAADgXwggJeSff/7xdROAYuHpNLzudM+S6IIFAIC/IoB4Ydu2bXr77bcLzBR17tw5Pfroo6pcubIiIiLUqFEjLVmyxEetBIqHuwsRelIdsd9OFywAAPwLAcQL7777rh577DGlpaXleX3s2LF65513dPbsWRljtHv3bvXo0UO7d+/2UUuBosnNzbWFBvsuWO6MAfFkEHpYWJgkAggAAP6AAOKFH3/8UaGhobr55pttr2VmZmry5MkKCQnR999/r5MnT2rEiBHKzMzU66+/7sPWAt6zhgTJcRcs+yqHsxmyqIAAAAArAogXDh06pHr16tluqqTzC/elpaWpV69eio+PV3h4uMaPH6+qVavqxx9/9GFrAe9Zu19JjrtgOaqAWF9ztQ4IY0AAAPBPBBAvnDx5UlWrVs3z2s8//yyLxaKuXbvaXgsODlZMTIz27dtX2k0EioV9BcRRFyxnIcNVFywqIAAA+CcCiBeqVq2q/fv353ltxYoVkqTrr78+z+vWGy+gPPKmAuJpFywqIAAA+BcCiBdatmypw4cPa8GCBZKkP//8U6tXr9Yll1yi+vXr59l3165dioyM9EUzgSLLH0CcjQHxZIYsyXEXrMzMzDwhBQAAXHgIIF4YOnSojDG6/fbb1bp1a1177bUyxuhf//pXnv3Wr1+vkydP6sorr/RNQ4Eisu+C5Wqmq+LogiWdDyEAAODCRQDxwi233KK3335blStXVmJiorKysjRixAg98sgjefb78MMPJUldunTxRTOBIrNfA0SS0zEgns6C5agCIknp6ekl82YAAECZUMHXDSivhg4dqocffljHjx/XxRdfnGdGLKthw4bp4Ycf1iWXXOKDFgJFZw0ggYGBkuTWSuj51wgprAuWfQXEOr4kNzeXcSAAAFzgCCBFEBgYqFq1ahW6vWnTpqXYGqD4WasU+SsgnowBcWchQovFotDQUJ09e5YAAgDABY4uWAAK5aoLVnHMgmWtrjATFgAA/oEKiBcGDhzo0f4Wi0UfffRRCbUGKDn5u2B5UgGx74LlbBC69TgCCAAA/oEA4oWpU6e63Md6w2WMIYCg3MrfBcvZGBD7v/P2+7gzCF0igAAA4C8IIF745JNPCt125swZ7dixQzNmzNCJEyc0evToAmuDAOVFYV2wnFVApPNBw9U6IHTBAgDAPxFAvNC/f3+X+4wfP179+/fXe++9p/Xr15dCq4DiV1gXLGdjQKTz4cLVOiBUQAAA8E8MQi8hFStW1JQpU5SamqrRo0f7ujmAV1x1wSqsApKbm8sgdAAA4BABpARVq1ZNzZo10+LFi33dFMArrrpguVMBKawLVmEVEBYiBADgwkYAKWGHDx/WyZMnfd0MwCuuumC5WwFxNguW9dwVK1aURAABAOBCRwApQVOmTNGBAwcUGxvr66YAXvFmFizrdne7YFm3VapUSdL5iRwAAMCFi0HoXnjhhRcK3WaM0bFjx/Tbb79p/fr1slgs+te//lWKrQOKjzfrgEjn/x142gXLGkBOnz5dMm8GAACUCQQQL4wdO1YWiyXPp7mOhIaGavTo0XrooYdKqWVA8cpfAfFkDIinXbAqV64siQoIAAAXOgKIF5577rlCt1ksFlWqVEkxMTHq1KmTqlWrVnoNA4pZYYPQPR0D4s5ChFRAAADwDwQQLzgLIEBZduDAAT377LPq1auXunfv7nL//F2wnI0BcTYLljsVEMaAAADgHxiEDviRUaNG6eOPP9add97p1mxTrrpg2VdA3BmELv0vtOSvgNAFCwAA/0AAAfyEMUbff/+9pPM3+T///LPLYzxZCd3TAFJYBYQuWAAAXNjoguWCdcariIgIDRkyJM9r7rJYLHrmmWeKvW2AJw4cOKCjR4/anicmJqpLly5Oj8nKypIkBQUFSXK+Err1YZ0By1EXLOsxAQEBTMMLAICfIoC4YJ3xqnHjxrYA4u4sWNZ9CCAoC3bv3p3n+caNG10ekz+AOJsFy/pnTk4OXbAAAEChCCAuWAecR0REFHgNKE8OHTqU5/mOHTtcHuMqgNhXQKzbrQHE0Togjo71tgvW1q1btWDBAj3wwAOqWrWqW8cAAADfI4C44ChsEEBQHh0+fFiS1LRpU23ZskW7du1yeUxhAcTRGBD7PwtbB8S6TSp8Gl53KiDGGPXu3Vt///23NmzYoC+++MLlMQAAoGxgEDrgJ6wVkGuuuUaS9M8//+iff/5xeownY0Dyb/d0ELq1C5Y7FZDk5GT9/fffkqSZM2faBssDAICyjwAC+AlrBaRRo0aqXbu2JLmsgngzBsT6uqsuWEWpgKxdu9b2dU5OjlvdyQAAQNlAFywXPv3002I5z7333lss5wG8Za2AREZGqlGjRjp8+LB27typVq1aFXqMqy5YjsaAWF931QWrsDEgGRkZysnJsb3uyL59+/I837Rpk5o0aeLk3QMAgLKCAOLCgAED8tw8eco6CxYBBL5mrYDUrl1bMTExWr16dYGZsfKzdm0qrAuWu2NAnHXByj8LlnS+ChIeHl5ou/IPqN+0aZNuv/12p+8FAACUDQQQF+69916HASQzM1PffPONsrKyVKdOHV166aWqVauWjh49qm3btunAgQMKDg5Wr169FBIS4oOWA3nZV0BiYmIkFb0LlrMKiKddsEJDQ21TV7sbQGrWrGn7NwcAAMoHAogLU6dOLfDamTNn1KFDB9WsWVOTJk1Sjx498oQUY4zmzZunYcOGKSkpST/++GMpthgoKDs7W8eOHZP0vwqI5H4AqVDh/H8V7o4B8aYLlsViUeXKlXXq1CmX40CsAaRjx46aOXMmAQQAgHKEQeheeO6557Rx40YtXLhQt912W4EKicVi0W233aYFCxYoMTFRY8eO9eo6xhitWrVKI0eOVLt27VStWjUFBwcrKipKvXv31ooVKzw+54YNG/Tss8+qQ4cOioiIUFBQkGrWrKmuXbtqzpw5Lo/fsmWL7rrrLkVGRio0NFSNGjXSiBEjdPLkSS/eIUrL0aNHZYxRYGCgIiIiilwBKWwMiCezYOWvgEj/64Z16tQpp+2yDyCStH37dpcLgwIAgLKBAOKFb775Rk2bNtXll1/udL8rrrhCcXFx+vrrr726zvLly3Xdddfptdde02+//aZatWrpsssu06lTpzR79mzdcMMNHq2wvnPnTrVs2VLjxo3TTz/9pPDwcDVv3lzZ2dlavHixevXqpQEDBthuHPNbsWKFWrVqpS+++EI5OTmKi4vT4cOH9frrr6tVq1Y6cuSIV+8T3snJydG+ffsK/XnZs47/qFmzpgIDA20BZO/evU6nsHU1Da+7s2C5UwGRZOt2lZqa6vT9WANI+/btFRgYqDNnzujgwYNOjwEAAGUDAcQLhw8fzvOprTMWi6XAgFl3GWMUGxuryZMn6/jx49q2bZsSExOVkpKiUaNGSZLGjx+vb7/91u3zRUZG6uWXX9bBgwe1a9curV+/XsePH9ekSZNksVg0bdo0TZ48ucCxp06d0p133qn09HQ9+uijOnDggH7//Xft27dP7du3165duzRo0CCv3ic8l5OToy5duqhBgwZKSEhwGULsx39I57thhYaGKicnR8nJyYUeV5QxIPkHmecPL44qINWqVZPkPICkp6fbttevX98WpuiGBQBA+UAA8UJkZKQ2b96srVu3Ot1v69at2rRpk+2mz1Nt27bVli1b9PDDD6t69eq214ODg/XSSy+pa9eukqQpU6a4db66detqx44devLJJ/O0KSAgQEOHDtWDDz5Y6Pnef/99HTt2TE2bNtUbb7xhuyG96KKL9MUXX6hChQr67rvvlJiY6NV7hWemT5+u5cuXS5IWLVrksvucNYBY1/8ICAhQdHS0JOfdsIqyErqz6oh1HylvBaRq1aqSnAcQ63sJDQ1V1apV1bhxY0muA8iRI0f0xhtv6Ndff3W6HwAAKFkEEC/ceeedys3NVffu3fX999873GfJkiVKSEiQJPXt29er64SHh9sG/zoSHx8v6Xz/d3eEhoaqYsWKhW7v0qVLoeebPXu2pPPTEudfn6F+/frq3LmzJHnd3exCcfbsWa1bt87lCuP2pk6dqtq1a6tJkyb64Ycf3Drmk08+yfPcVQi1dsGyD57ujAPxdCV0RxUQR+NDJMcVEE8CSGRkpCwWiy699FJJzgNIdna2br75Zj3xxBO6/vrrtWnTpkL3tWeM0bvvvqvOnTtr6NChJd7N6/Tp01q1apVHf38AAChvCCBeeOaZZ9SmTRvt3r1b3bp1U0xMjLp166b+/furW7duatSokbp27apdu3apVatWGjNmTIm0IyMjQ5IUFhZWoufLzs7W77//Lul8n3tHrK/br1Bdnu3bt0/vvPOOvvzyS7dvBlevXq2YmBhdddVVqlu3rj766COXx/z2228aOHCgjhw5om3btunmm2/WF1984fSY5ORkrVy5UpK0bNky25/WWa4cyV8BkbwLIK5mwSpsELqjY/Nvl/4XQJxNapC/O1n+Ckh2dnaB8UiLFi3Sxo0bbe9p/PjxhZ7f3ksvvaShQ4fqhx9+0LvvvqvGjRvr3//+t1599VVNmjRJaWlpbp3HHQcPHlRcXJyuu+46RUdHa/HixcV2bm8YY/TGG29owIABtvVizp49q7vuukstW7bU6tWrbfseP35cmZmZvmqqUz/++KOGDx+uVatW2V4zxmjOnDn67LPPbH/HpfN/N1auXJmn26wxRp988okGDBign3/+2fZ6SkqKHnroIfXp00ebN2/Os/+6deu0bt06JkYAgEIwDa8XKlasqBUrVmjMmDH64IMPtGfPHu3Zs6fAPvfff7/Gjx/vtOrgLWOMZs2aJanwUOCpmTNnOjzfnj17bL+krTet+VlfT0pKKpa2FJfff/9d27ZtU3p6ujIyMnT8+HGtWbNGf/zxhzIzM9WxY0c9/fTTatOmje2YL774Qg899JBtJqagoCB16dJFcXFx2rx5s3bu3Kn27dvrxRdfVK1atSSdv4nv0aOHUlJSFBQUpLNnz2rw4MHatm2b/vOf/zgcM5Sdna0HHnhAxhglJCSocuXKmjFjhu666y4lJyerX79+ioyMLFAFs/7cr7/+et14441q1aqVfv/9d82cOVP/+te/9M8//+js2bOqU6eO7RhHFZBLLrlEkvT3338X+v3zdgxI/kHo+bfZH+tpF6z878U+gJw8eVLt27fX33//rfHjx2v06NGSpC+//FKSdN111+nnn3/W3LlzlZqaarueI/v379eLL74oSXr00Ue1bt06/frrr3r55Zdt+3z44YdatWqVqlSpUuh5HPntt9/03HPPqWbNmpowYYJq1Kih3r1721Z4T0tLU69evZSYmOj2Cu/Z2dnavHmzVq5cqZ07d+rqq69Wr169tGDBAr388suqVq2aJk2apCZNmignJ0crV65UdHS0GjVqJOn8z+XUqVO2iQC+/PJLPfHEE5LOL/S4bt06vfbaa7aAfMcdd2jLli2aOnWqHnvsMUVEROjHH39UkyZN9Pvvv6tnz56qVKmS5s2bp0svvVQpKSnq37+/tm/frvHjx+uOO+5Qenq6HnroIa1YsUK33HKLXnrpJYWEhGjJkiVKSUlR+/btbRUuV+bPn68xY8YoMDBQr7zyiuLj47V8+XLddNNNys7O1uTJk/X999+rU6dO+s9//qOnn35akvTdd9/pyy+/1Llz59S5c2etWrVKlStX1pIlS3T11Vdr6tSpGjhwoO178tNPP6lVq1bq1auXfvrpJ0nnQ05iYqIiIyM1cOBAffrpp5Kk/v3766OPPlJgYKAWLlyoIUOG6PTp07r//vv17LPPKiwsTBs3btTkyZP1+++/q3HjxurUqZPatWun1NRUbdu2TXv37lWlSpVUs2ZN1a5dWxUrVlROTo6ys7NtQd8Yk+frkgw+pRGqSvoanN/31yjp88fGxqp169Yleg0UkUGRnDp1yixcuNBMnDjRjB8/3kycONEsXLjQpKWlleh1//vf/xpJJjg42OzYsaPI5/v++++NJCPJ/Pjjj3m2rVu3zrYtPT3d4fELFy40kkzlypULvUZGRoZJTU21PZKTk40kk5qaWuT2F+aBBx6wtd3Z48477zQrVqww99xzj+21uLg4c9lllxV6THR0tNm9e7c5efKkiYuLM5JM69atzalTp8zzzz9v269Vq1amQ4cOJiYmxsTHx5uffvrJGGPMa6+9ZiSZ6tWrmyNHjpicnBzzyCOP5LlGQECA6dSpk/n7779t7+nqq682ksykSZOMMca88cYbRpK5+uqrzaZNm0z16tWNJDNt2rQCx3z99de2137++WcjydSpU6fQ79+tt95qJJkPPvjAGGPMjBkzjCTTsWNHY4wxL7/8spFkBgwYYIwxJjo62kgya9euNTfffLORZKZOnWqMMSYsLMxIMrt37zbGGNOoUSMjyaxevdp2vXHjxhlJZvDgwYW26emnnzaSzNChQ40xxhw6dMhIMhaLxYwaNcr2vatQoYLZvXu3OX36tKlYsaKRZH755RfTpEkTI8l8/PHHTv/uWP8uXHvttSY3N9fk5OSYzz77zPTr18/cddddtu/z448/nue4c+fOmYceeshUrVrVtG/f3vz55595ti9cuNDWHkmmUaNGtu9VtWrVzJYtW8yNN95oJJlrrrnG5OTkGGOM+eeff8yDDz5o7rzzTvPXX3/Zzjd//nzTqVMn2/fX/hEYGJjned26dc2OHTvMLbfcYiSZoKAg8+2335qTJ0+a9u3bG4vFYkaOHGlycnIK/N3/8MMPTbVq1fK8du2115qAgADb89atW5v09PQ8x7Zr187k5uaavn375mnXnDlzbO/T+ggPDzfh4eF5XouNjTUdOnQw3bt3N/369TP333+/ufbaa01kZKRp06aNeeqpp8yQIUMKvO9HHnnEVK1aNc/rERER5q233irwfXr//ffN8OHD87xWp04ds27dOlO5cmXb/7WSTL169cygQYOMJFOxYkVTt25d27/z/v37Fzj33XffbZ588skCr9epU8e0bNnSrf+fePDg4dnj4Ycfdvr/e1GlpqYaqWTvXy50VECKqHLlyuratattQHhpSExM1LBhwySdnwXL+gmmt/bt26e77rpLkjRkyBBdf/31ebZbu2ZJ5wfAO2Jd7T09Pb3Q60yYMEHPP/98kdrqqWbNmumGG25QWFiYwsLCVLlyZbVs2VLt2rWTJL3zzjv67LPP9NVXX+mrr76SdP6T+meeeUZjxoxRhQoV9Pfff2vWrFm2LjJRUVH697//bfuUuWbNmtq8ebMiIyM1d+5cVa5cWc8++6xiYmI0cOBAW/c16XylZOnSpbr11lu1ZMkSSdIrr7yimjVrSpLeeustxcbG6p133tHu3buVnZ2tFStWqH379lq2bJkiIiL0yy+/SJJ69eol6fwYoxEjRuiXX37RZZddZrvWM888o7vvvlsBAQEOKyBXXnmlAgICdODAAR06dMjhZAnFOQtWcQ9Ct7a3Vq1aCg8PV1pamiZMmGDbLzs7Wx9++KGuuOIKnT17Vg0bNtRVV12lu+++W2PGjNFnn32m++67z+E11q1bp88++0yS9MYbb9imEr777rt19913S5IWL16srl276u2339agQYPUrFkzZWVlqW/fvrYxU6tXr9ZVV12l//73v+rTp4/effddPfXUU8rJyVHr1q116NAh7dy5Uzt37lRAQIC+/PJLNWnSRB9//LHi4uK0Zs0affDBBxo0aJD69Olj63L33Xff6b///a/WrFmjd99919bu8PBwtW3bVo0bN9bs2bN16NAhVaxYUQ8++KAWLFigHTt2KDY2Ns/P9/bbb1dkZKStm9Wrr76q48ePa9OmTapSpYoGDhyot956S4MHD5YkNWnSRK+99poSEhJs3ZpuvPFGrV+/XuvXr9ell16aZ2a1X3/9VQMGDNCMGTNksVgUFxenTZs2qWfPnpLO/x86evRoffLJJ7bxZ3Xr1lXDhg3166+/aseOHdqxY0ehfxd+++0323Nr5XL69OmaNGmSpPNVr/nz5+vGG2/M83/nv/71L8XExOiJJ57QQw89ZDvHl19+qbFjx2rbtm1q27atJOnaa6/V/Pnz1bZtW+3YscPWvXLq1Klq3bq1Wrdurd9//932b/3LL79UQECA/u///k+ff/55nvZdd911euqpp7R//34dOHBAFSpU0O23367u3bsrKSlJy5cv18aNGxUREaFLL71UDRs2VHp6uo4ePapDhw4pMzNTFSpUUGBgoAIDA2WxWGxr7Vj/nro7S6O38q99VR6vwfl9f42SPL+1Mo4yzNcJCJ7ZtWuXiYyMNJJMv379TG5ubpHOl5KSYpo1a2ak859qZ2RkFNinPFdA3LFx40aTkJBgIiIiTMeOHc2aNWtcHrN//35b1UOSqVKliklMTCyw344dO8yUKVPM9OnTzQ8//GDuv//+PJ/SJCQkFPozzMnJMdu2bTPt2rUzkkyNGjXMTTfdZCSZTp065dm3Z8+etnPaf+qbmJhocnNzTWhoqJFkdu7cmee4K664wkgy06dPd9iGzp07G0nm888/N8YY8/XXXxvp/Cffxhjz0ksvGUlm0KBBxhhjYmNjjXS+qhEfH28kmc8++8wYY0yVKlWMJFvFrn79+kaSWbdune1606ZNM5JMly5dCv3eW6sF9hWMtm3b2t5zw4YNbZWaWrVqmS5duhhJZtSoUcYYY/bs2WPbd8+ePQXOn5uba9q3b28kmXvvvbfQdhjzvwrRDTfcYDIyMsxtt91mpPOflv/3v/+1/byk8xUa69f33HOPyczMNAcPHjR33HGHadmyZZ7qlDHGvP3227a/W926dTOSTFhYmK2CY/8YPny42bJli61aYowxWVlZ5q+//jL//POPMeb8/x21a9e2/R1ZsmSJ6dixY56/N9bvrfXx5JNPmn/++SfP3ylrZc36aX9cXJxJSUkx77//fp5jP/roI1tFy/p47LHHTEZGhunevbuRZGrWrGn795aVlWVWrlxp1q5da3sfqampZtGiRWbGjBnmww8/NK+//rp57rnnzLRp08zatWvNZ599Zu655x7TqVMn8+WXX9p+fuPHjzdRUVGmd+/e5uTJk7afu/X/zh49ephz586ZnJwc299x2X1q+tdff5lKlSoZSeaiiy6yVe3+/PNPU69ePVOhQgXzwgsv2L7XP/74o6lfv76pVq2a+eijj2yvf/vtt+ayyy4zTZs2NV999ZXt9bNnz5oZM2aYadOmmUOHDjn9Owag7KECUnQEkCLKyckxW7duNWvWrDE//vhjoY/icOjQIVu3le7du5tz584V6XynTp0yV111lZHOdx8orNtYUlKS7Rf0wYMHHe4zffp0I53vnuCu8v4P+PTp0+a1114zTz/9dIEbe2d+/vln88ADD5j//Oc/hQY6e6mpqbafk/Uxf/78PPskJyebq6++2sTGxppVq1bZbnwnTZpkTpw4YTvu7NmzeY6zdme6/fbbHV67Q4cORpLt5mn27NlGkmnfvr0xxpjx48cb6X9dpi699FIjyfz888+27jXWcGPtWrN9+3ZjjLF1Xfn9999t15s7d66RZNq2bVvo96N58+ZGklm0aJHtNWs7JJmJEyeac+fO2QKO9bF582bb/p06dTKSzFNPPWXOnTtnNm7caLsRnDp1qu1mf//+/U5+Mudv6kNCQmwB0Ro+vvvuO2OMMdnZ2Wbs2LG2bkp169Y177//vlsfHGRnZ5s2bdrkCTDz5s0zmZmZ5uGHHzaBgYEmJibGLF682OW5rI4ePWpmzpxpe1/Hjx83ffv2NTfccIP57bffTGZmpu2atWvXNkeOHDHGnO9617hxY/PAAw/YwkFubq7Zs2ePyczMNMac/7/Q+velR48eJjc312RmZtq6/7Vo0cKcPn3aduyOHTvMmTNn3G57cUhNTTV//vlnnu9/amqqmTBhgnnvvfdMdna27fXt27ebKVOmFPg7kJOTY3sf9nJzc4v8gRCA8qG837+UBQQQLx09etQMHDjQVK5c2QQEBDh9BAYGFvl6KSkptn7VHTp0KHAj6amMjAxzww03GEmmWbNm5tixY4Xum5WVZYKCgowks2rVKof7WD/pvOGGG9xuA/+A3ffPP//YPpV/+OGHXd7oWMeg/N///Z/566+/bDfI+a1fv952s33q1KkC26+55hojycyePdsYY8ycOXOMdH68iTH/+7k/8MADxhhjGjdubKTz44isN/nWT6at4we2bdtmjDG2T6M3bNhgu97KlSuNJNO4ceNC31vNmjWNJLNx40bba2fOnDEPPfSQGTVqlMnKyjLGGPPOO+/Ybt5vvvnmPOewBh1JtuqQtXpiDQv/+c9/nH6PrT788ENbdaNq1apm6dKlBfY5duyY2bVrV54KhTt27Nhh2rRpY2rVqmUbS2OVnZ1dIje8p06dMvPnz/fqk/n09HSzadMmh5WYon5gAgBlBfcvRccYEC+kpKToqquu0t69e1W3bl0FBgbq1KlTuuaaa5ScnKwDBw4oJydHYWFhtj7ERXH69Gl169ZNmzZtUps2bbRgwYIiTb2bnZ2tO+64Q8uXL1dMTIyWLl2qiIiIQvevUKGCWrZsqbVr12r16tUOZ92yTsl51VVXed0uFK5atWr6+eeflZaW5nTmJivrGJd169bZ1q6IiooqsF/Lli0VGxurHTt2aN68ebaxQFYlMQuWO9PwFjYGJDs72zbdsP2YlYoVK+q9997Ls+/DDz+sc+fOaffu3QWmwr711ls1cOBAffzxx8rIyFDlypV19uxZ2ziIrl276vHHH3fYhvwGDRqkdu3aafPmzbrhhhsc/luKiIhw+m+sMI0aNdK6descbsu/Hk9xqVy5sm655Ravjg0NDVVcXFye1ypUqJBnbBIAAKwD4oVXXnlFe/bs0dChQ7V3715dfvnlkqSff/5Ze/bs0ZEjR/Tvf/9b2dnZatCggVasWOH1tTIzM9WjRw+tXbtWcXFxWrx4scdTftozxmjAgAGaP3++oqKitGzZMoc3pvlZBzxPnTrVtoCc1b59+2yDY3v37u112+CcxWJxK3xIsk0rvHPnTv3555+SlGdaXvtz9uvXT5Icrj/ibgBxtNZH/m2FLWLoySD0I0eOyBijChUquLyhDwgI0GOPPaa3337bNsjf/n1/+OGH+uOPP7Rp0yalpqYqJSVFc+bM0dy5czV//nzbe3ZHXFyc7rjjDq9CBgAA/oYA4gVrBWLcuHEOt9eoUUMvvfSSpkyZos8++0yTJ0/26jo5OTnq27evli9frkaNGmnp0qWqUaOGy+MmTpyo6OhohyuwDxs2TNOnT1dERISWLVumhg0butWWhx56SBEREdqyZYsef/xx241pSkqK+vXrp+zsbHXt2lWtWrXy7E2iRFSvXt22fsK8efMkOa6ASP8LjStXrlR2dnaebYWthG6tblj/dBRACttmfd3ZSujp6ek6d+5cgbZaZ8CqVatWkWf6sVgsuuKKKxQXF6eAgABVq1ZNt912m3r06FFg7RUAAFB8+C3rhb179yo6Otq2YJf1RigrKyvPp6b33nuvnn76aX300UcaMmSIx9eZOXOm5s6da7tGnz59HO4XGRlpW5xOOr+KtLWN9n755Rfb1JRhYWG6//77C722/arB0vnpPWfMmKGEhAS9/fbb+vLLL1W/fn1t2bJFZ8+eVXR0tD7++GOP3yNKTtu2bbV9+3bbz7JBgwYO94uLi1OVKlV06tQpbdmyxVbRk4pnGl7rNncrIAEBAcrNzdWJEyfyrNwuydadzNGUwQAAoHwggHghKCgoz+rm1i5Rhw8fVr169fLsGxkZqW3btnl1nczMTNvXSUlJha4yXtiNpbPzJScn55mr3x3Wuf7Hjx+v5cuX66+//lKdOnXUs2dPjRkzRtWrV/fofChZbdu2zbMGQWHzogcGBqpVq1ZauXKlfv/9d48CSP4qh33IcNY9S3JcAQkMDFSNGjV0/PhxHTt2rEAAOXDggCTH3ckAAED5QBcsL9StW9fWFUSSravLzz//nGe/M2fOKCkpyevFdgYMGGAbzOvssWfPnjzHjR07VsYYrVy5Ms/rHTt2dOt81ptKR+Li4vTll1/qyJEjyszM1K5du/T6668TPsqg/BMgOFuYqVmzZpJkWwjOyroIpXWhycIWE3RUAXHVBctRBUSSLr74YkmyDTa3RwABAKD8I4B4oW3btjpy5IhOnjwpSbrllltkjNHIkSO1bNkynTlzRrt27dLdd9+tU6dO6eqrr/Ztg+GXmjdvnud5/tmJ7FlDdP4AYq2ahYaGSirYjcpZyHDVBctRBUT6XwA5evRogXZau2ARQAAAKL8IIF7o0aOHcnJytGDBAklSp06d1KNHDx06dEg33XSTwsPDdckll2jevHkKDg7W+PHjfdxi+KPQ0FDdfvvtkqQHHnhAwcHBhe57ySWXSFKBbn7WAJK/AuLJGJDCumA5moZXogICAMCFjgDihVtuuUXJycnq0aOH7bWZM2dq7NixuuSSSxQUFKTw8HB1795dq1evVuvWrX3YWvizzz77TD/99FOBNTLysw8g9l3wXAUQd2bBcrRGiP05vOmC5c7U0QAAoGxiELoXAgICCnwCGxQUpGeffVbPPvusj1oFFBQaGqrrrrvO5X7169eXdH762+PHj+viiy9WTk6ObVpeawDJPw2vJxUQT7tg5Q8gubm52rVrlyQVmOENAACUH1RAvPDCCy9o3LhxDtcpAMqjkJAQ1apVS5Jss6PZz5rmbgXE3Vmw7Cc7cLcCcvDgQaWnp6tChQoEEAAAyjECiBfGjRunGTNmOO1TD5Q31imkHQUQ6yB0d8eA2AcMR9usx9m/bmVdtfzIkSN5XrdOZx0TE+PRKuUAAKBsIYB4oVatWnnWAQEuBIUFEIvFYlsZ3JOV0J11wbIPIPkrINbuYHv37s3z+vr16yVJl112WRHeJQAA8DUCiBc6d+6szZs3KzU11ddNAYpNYQEkJCTE4RgP+z89XQfEOv7D/nWrhg0bSjo/4Dw9PV333nuvatWqpX//+9+SpGuuuaZ43jAAAPAJAogXxo4dq9DQUN13331KT0/3dXOAYpE/gORfhFDybBYsZ+uAOOuCVatWLYWGhio3N1evvPKKPvvsM9uaIAEBAerVq1exvF8AAOAbzILlhZ9++kkPPfSQXn31VcXGxqp3795q2rSpKlWqVOgx9957bym2EPCcswqIVXGtA+KsC5bFYlHDhg21ZcsWjR07VpLUpk0bRUZGqnfv3rYKCQAAKJ8IIF4YMGCALBaLjDE6dOiQ3n33XZfHEEBQ1hUWQKwD0CXXY0DsqxzedsGSpFatWmnLli226y9cuFARERFFfo8AAMD3CCBeuPfee203WsCFwhpADhw4oJycnCJVQOxnunLVBSt/BUSSOnbsqM8//1yS1L9/f8IHAAAXEAKIF6ZOnerrJgDFLioqShUqVFB2drYOHTrkVgDxZBYs+22uKiB33XWXZs2apezsbD333HPF9yYBAIDPEUAASDpfiahbt6727NmjPXv26MyZM5KUZ2yTJyuhe7sOiHS+29XixYuL780BAIAyg1mwANhYVxjfu3evTp8+LUmqXLmybXtRKiD2XbCsFRBH4QMAAFzY+O0PwKZBgwaSzgcQRxUQV2NAHI3zcCecAAAA/0EXLAA21grInj17FBYWJsl5AHE205U7XbAcDUAHAAAXNj5+BGDjqAJi3wXLkzEgdMECAACO8NsfgI2nXbCcjQFxZ3wIFRAAAPwPAQSAjf0g9FOnTklyPgjdnQqIoy5YVEAAAPBf/PYHYFO3bl1ZLBZlZGRo165dkpxPw+vtLFhUQAAA8F8EkGKQm5urY8eOad++fb5uClAkwcHBatiwoSRpzZo1kqQaNWrYtnsyC5azcEIFBAAA/8Vv/yJYuHCh4uPjVaVKFdWuXVsxMTF5tr/44ovq16+fjh075qMWAp5r1qyZJCk1NVWSdNFFF9m2eTILVmHhxH4bAQQAAP/Db38vPfnkk7rlllv0ww8/KCcnR0FBQbabMavIyEh99dVXmjNnjo9aCXguLi4uz/OIiAjb1/YVDvs/3ZkFi0HoAABAIoB45ZtvvtFrr72mqKgoffvttzpz5ozatGlTYL+ePXtKkubPn1/aTQS8lj+AOKqAuDMGhC5YAADAERYi9MK7774ri8WiWbNmqV27doXuV716dTVs2FBJSUml2DqgaK644oo8z61T80pFmwXLURcsKiAAAPgfPn70woYNG1SvXj2n4cPq4osv1oEDB0qhVUDxuPzyy/M8r1Kliu1rV2NAGIQOAABc4be/FzIzM1WtWjW39j179iyf8qJcCQgI0MiRIyVJjz32WJ5t1oAhOR5o7u46IFRAAADwX3TB8kK9evW0Y8cOZWVlKSgoqND9UlNTtXXr1gJ96oGy7uWXX9agQYMUGxub53X7ioUxxq1ZsBxVR6iAAADgv/jt74WbbrpJ6enpevPNN53u98ILLyg7O1sJCQml1DKgeFgsFjVu3LhAhcI+MDircrjqgsU0vAAA+C9++3vhqaeeUpUqVfT0009r5MiR2rp1q21bbm6u/vzzTw0cOFBvvvmmIiIiNGzYMB+2Fig+9l2w3A0ZdMECAAD26ILlhTp16mjevHnq1auX3njjDb3xxhu2bdYuWcYY1ahRQ3PmzMkzjSlQnuXvguXJOiB0wQIAABIVEK916NBBmzZt0vDhw9WgQQNbf3hjjCIjIzV06FD98ccfuuaaa3zdVKDY5O+C5e0sWFRAAADwX1RAiiAyMlKvv/66Xn/9dZ05c0apqamqXLmywsPDfd00oES4OwbEWXXEGEMFBAAAP0YAKSaVKlVSpUqVfN0MoETln4a3sCqHNWDYv2ZfHaECAgCA/+LjRwBuc7cC4iiAsBAhAACQqIC49MILLxT5HBaLRc8880wxtAbwLVdjQKx/Zmdn2/azhhPrn47WCAEAAP6DAOLC2LFjZbFYbDdanrAeRwDBhSL/NLzeVkDoggUAgP8igLjw3HPP+ezaxhitXr1a8+bN088//6ytW7fq7NmzioiI0NVXX62hQ4eqU6dOHp3z8OHDWrJkidatW6d169bpjz/+0Llz5zRo0CB9+OGHTo/NzMzUO++8oy+++ELbtm2TxWJRkyZNdN999+mhhx7i02w/4GoldGsQsa+A0AULAADYI4C44MsAsnz5cnXu3FnS+Ru12NhYVapUSUlJSZo9e7Zmz56tMWPGaNy4cW6fc8aMGXrsscc8bsupU6cUHx+vtWvXymKxqGnTpgoKCtKGDRu0fv16LVq0SHPmzFGFCvyVupB5MwbEWRcsKiAAAPgfPn4sw4wxio2N1eTJk3X8+HFt27ZNiYmJSklJ0ahRoyRJ48eP17fffuv2OcPDwxUfH6/Ro0dr3rx5euSRR9w6btiwYVq7dq2ioqK0YcMGbd68WRs3btSOHTsUFxenb7/9VhMmTPDqfaL8cHcldAahAwCAwvDbv5icPn1ahw4d0unTp4vtnG3bttWWLVv08MMPq3r16rbXg4OD9dJLL6lr166SpClTprh9zoEDB2rJkiUaP368br31VtWoUcPlMSkpKfr0008lSW+88YaaN29u2xYdHW3ruvXqq6/qzJkzbrcF5ZOjSkb+CoijQeiMAQEAABIBpEj++usv3XfffYqKilLVqlVVt25dVa1aVVFRUbrvvvv0559/Fun84eHhTrs0xcfHS5K2b99epOu4snbtWuXk5CggIEA9e/YssL1du3aqU6eOTp06pcWLF5doW+B79kHCnVmw8o8PYSFCAAD8G7/9vTRx4kS1bt1an376qQ4fPmwbkGuM0eHDhzVt2jS1bt1ab7zxRom1ISMjQ5IUFhZWYteQpH/++UeSdPHFFys4ONjhPnXq1JEk/frrryXaFvieo0pG/nEe7s6CRQABAMD/8NvfC/PmzdPjjz+urKws9ezZU8uWLdOBAweUlZWlgwcP6ocfflCvXr2Uk5OjkSNHav78+cXeBmOMZs2aJUlq3759sZ/fXtWqVSVJx48f17lz5xzuc+DAAUnStm3bSrQt8D37Fc3dGQOSvwsWg9ABAPBvBBAvvPLKK7JYLJo0aZK+/vpr3XDDDYqMjFRgYKBq166tTp066euvv9akSZNkjNErr7xS7G2YMmWKNmzYoODgYA0fPrzYz2+vdevWslgsysnJ0bx58wpsX7dunS2AWKsljmRmZiotLS3PA+WPoyDhbAxI/i5YDEIHAMC/8dvfC3/88YciIyP1r3/9y+l+Q4YMUVRUlDZu3Fis109MTNSwYcMknZ8Fq1GjRsV6/vxq165tG/sxfPhwrV271rZt+/btGjBggO15enp6oeeZMGGCqlatanvUq1evxNqMkuOsKxULEQIAAFcIIF4ICQmxjXlwJSoqSiEhIcV27d27dyshIUEZGRnq16+fRowYUWzndua9995T48aNdfDgQbVr104NGzZU48aN1bRpU+3cuVN33HGHJKly5cqFnmPUqFFKTU21PZKTk0ul7She7nTBcjYLFoPQAQDwb/z290K7du20detWp5/2S9LZs2e1bds2XX311cVy3cOHDys+Pl6HDh1S9+7dNXXq1DzrMpSkmjVrau3atRozZoyaNm2qw4cP6+jRo0pISNDatWt1ySWXSDpfLSlMSEiIwsPD8zxQ/rjTBcsaMOz/ftoHFyogAAD4LwKIF5577jllZmbq/vvvL3RQdlZWlh588EFlZmZq7NixRb7miRMnFB8fr507d6pDhw6aNWuWgoKCinxeT1StWlXjxo3T33//rfT0dP3zzz+aN2+errzySq1fv16S1KpVq1JtE0qfs2l4rSHDWgGxr3CwECEAAJCkwheZgCTpp59+cvj6mDFj9MILL+iHH37QoEGD1LRpU9WsWVPHjh3Tli1b9NFHHyklJUXPPvuszp49W6Q2nD59Wt26ddOmTZvUpk0bLViwoMSn3vXEiRMntHLlSklSQkKCbxuDEudsGl53KiD2lRMCCAAA/ocA4kLHjh0L7eZkjNGRI0c0YcIEh9sk6dlnn5XFYsnTJ94TmZmZ6tGjh9auXau4uDgtXrxYVapU8epcJcVaEbrxxhvVtGlTXzcHJcyTaXgLq4DQBQsAAP9FAHHh+uuvL7VxFvnl5OSob9++Wr58uRo1aqSlS5eqRo0aLo+bOHGiJk6cqHbt2mnGjBnF0pa//vpLO3fuVEJCgm119tOnT2v8+PF65513VLFiRb377rvFci2Ube5UQOiCBQAACkMAccHatcgXZs6cqblz50o6f6PWp08fh/tFRkbaFiWUpJMnT2rv3r2Kjo4usG9ycrJatGhhe27tHvb555/briWdX2zRfoHDnTt3qmfPngoLC1PDhg0VHBysrVu3KiMjQ9WqVdPs2bPVuHHjIrxblBf2g9BdzYLlqgsWFRAAAPwPAaQMy8zMtH2dlJSkpKQkh/s1aNDA7XPm5OQoJSXF4bXsr5eVlZVne/PmzfXggw/q559/VnJysrKzs9WgQQMlJCRoxIgRTme/woXFWQXE+qerLlhUQAAA8F8EkDJswIABeRb5c9fYsWMLnXkrOjra9qm1Jxo2bKj333/f4+Nw4XE2C5azCghjQAAAgMQ0vEVy5MgRPf/887rmmmsUERGhkJAQRURE6JprrtHzzz+vw4cP+7qJQLHzZBYs+wqHfRcsKiAAAPgvKiBe+uabbzR48GClpaXlqSicOHFCv/76q9auXas333xTU6ZMKXTsBlAeFecsWAQQAAD8DwHEC6tWrdKdd96p3NxctWzZUkOGDFHTpk1Vq1YtHT16VFu2bNG7776rxMRE9evXT1FRUXkGdAPlmTsrodMFCwAAFIaPH73wwgsvyBijp556SuvXr9fAgQN19dVXKyYmRu3atdN9992n9evX69///rdycnL0/PPP+7rJQLFxZwwIXbAAAEBh+O3vhbVr1+qiiy7Siy++6HS/cePGKSIiQmvXri2llgElz51ZsFytA0IFBAAA/0UA8YLFYlHDhg1dfnobGBiohg0b+mwhQ6AkeFIBKWwdECogAAD4L377e+HKK6/Url27bDdRhcnOztauXbvyLPwHlHfezoJFBQQAAEgEEK+MGjVKJ06c0KhRo5zuN3r0aJ04cUJPP/10KbUMKHmerAPCQoQAACA/ZsFyYd++fQVea9q0qV566SU988wz+uGHH/Twww+radOmqlmzpo4dO6YtW7Zo8uTJ2rRpkyZMmKDGjRv7oOVAybDvSuXJLFiOjiOAAADgfwggLkRHRxc6hsMYo40bN+rBBx8s9PhRo0bp6aeftt2QAeVdcVRA6IIFAID/IoC4UL9+fQaRA3Y8mQXLPmDQBQsAAEgEEJf27Nnj6yYAZUpxrANCBQQAAP/Fx48APFIcs2BRAQEAwH/x2x+AR9ypgOTfN/9xVEAAAPBfdMHygqOZsVypX79+CbQEKH3uVECs7AMGCxECAACJAOIVZzNjOWKxWJgFCxcM+yCRvwKS/9+FqwoIAQQAAP9DAPGCs5mxzpw5o+PHj0uSgoKCFBUVVZpNA0qcJxUQumABAID8CCBecDUzVlpamqZMmaJx48apX79+evHFF0unYUAp8HYMCF2wAACARAApEeHh4XriiScUFxen7t27q0mTJrrnnnt83SygWBRHBcSKCggAAP6Hjx9L0M0336wGDRrorbfe8nVTgGLjSQXE0SB0puEFAMC/UQEpYdWqVdPWrVt93Qyg2BS1AmI/eJ0KCAAA/oePH0vQ0aNHtWXLFoWGhvq6KUCxcVYBcXcWLCogAAD4L377l4Djx49r0aJF6tq1q86dO6fOnTv7uklAsbEfTO5JBcTRcQQQAAD8D12wvOButxFjjGrXrq3//Oc/JdwioPSwEjoAACgKAogXrDddhalUqZJiYmLUtWtXjRgxQhEREaXUMqDkOQog7qyEThcsAAAgEUC8Yj+NKOBvrKHBGiLsX/O0CxYVEAAA/A8fPwLwiDVUZGdn216zhgsGoQMAAFf47Q/AI95WQBgDAgAAJLpgFUlmZqZmzJih77//Xtu3b9epU6dUpUoVXXrpperSpYv69u3LFLy44DgKIJ7OgkUFBAAA/0UA8dKaNWt09913a+/evQUGpScmJuqrr77S888/r88//1zt27f3USuB4mcNEu5UQAobhM40vAAA+C8CiBc2b96s+Ph4paenq3bt2ho8eLCaNm2qWrVq2RYf/Oijj7R371516dJFa9eu1WWXXebrZgPFwtkYELpgAQAAVwggXhgzZozS09N1991366OPPlJQUJDDfQYPHqzPPvtMzz77rGbPnu2DlgLFrzhmwaILFgAA/ovf/l746aefFB4erg8++MBh+JCkoKAg/fe//1V4eLhWrlxZug0ESlBxzIJFBQQAAP9FAPHCuXPn1LhxY5cDzENDQ9W4cWNlZWWVUsuAklfUCgjT8AIA4N/47e+Fpk2bav/+/W7tm5ycrLi4uBJuEVB6PJkFy9EgdBYiBADAvxFAvDB8+HAdOnRIb731ltP93n77bR0+fFjDhw8vnYYBpaA41gGhAgIAgP9iELoX+vXrpwMHDuipp57Sjz/+qCFDhqhp06aqWbOmjh07pi1btmjy5Mn67rvv9Morr6hv376+bjJQbKzVDk9nwbLvgsU0vAAA+C8CiAuuuojMmzdP8+bNK3T7U089pX//+995btaA8qyoFRC6YAEA4N8IIC7kX2TQV+cAyorimAWLLlgAAPgvfvu7YO0uUtSHN4wxWrVqlUaOHKl27dqpWrVqCg4OVlRUlHr37q0VK1Z4fM7Dhw/r008/1dChQ9W2bVuFhITIYrFo8ODBLo89d+6c3nrrLbVr105Vq1ZVUFCQIiMj1bNnTy1fvtybt4hyyNtB6PbrgFABAQDAf1EBKcOWL1+uzp07Szp/YxcbG6tKlSopKSlJs2fP1uzZszVmzBiNGzfO7XPOmDFDjz32mMdtOXv2rDp37qxffvlFkhQdHa3Y2Fjt2rVLc+fO1dy5c/Xyyy/rySef9PjcKF/yV0Dsqx4MQgcAAK7w278MM8YoNjZWkydP1vHjx7Vt2zYlJiYqJSVFo0aNkiSNHz9e3377rdvnDA8PV3x8vEaPHq158+bpkUceceu4N954Q7/88osuvvhi/frrr9q9e7d+//13HT16VGPHjpUkPf3009qxY4fH7xPlS/4KiKOQ4eg5CxECAACJCkiZ1rZtW23ZskUVKuT9MQUHB+ull17Sxo0btWjRIk2ZMkUJCQlunXPgwIEaOHCg7XliYqJbx3333XeSpGeeeUZXXXWV7fWgoCA999xzmjt3rjZu3KilS5cqNjbWrXOifMofQNytgNh3waICAgCA/+K3fxkWHh5eIHzYi4+PlyRt3769xNuSnp4uSYqJiXG4vVGjRpLEbF9+IH8XLEchw8rRQoRMwwsAgH/jt385lpGRIUkKCwsr8WtdccUVkqQ1a9YU2JaZmanff/9dktSmTZsSbwt8yxoy6IIFAAC8QQApp4wxmjVrliSpffv2JX69f//736pcubJeffVVvfHGGzpw4IDS09O1ceNG9e7dW3v27NHdd9+tdu3alXhb4FveDkKnCxYAAJAIIOXWlClTtGHDBgUHB2v48OElfr1mzZpp9erVio+P14gRI1S3bl1VrFhRLVq00K+//qpJkyZp2rRpTs+RmZmptLS0PA+UPwxCBwAARUEAKYcSExM1bNgwSednwbKOvyhp+/bt05EjR2SMUVRUlK688kpVrlxZKSkp+uSTT/Tnn386PX7ChAmqWrWq7VGvXr1SaTeKV1ErIEzDCwCAf+O3fzmze/duJSQkKCMjQ/369dOIESNK5brTp0/XrbfeqgMHDmjlypU6cOCANmzYoJSUFI0ZM0aJiYm6/vrrtXv37kLPMWrUKKWmptoeycnJpdJ2FC9PKiCOBqGzECEAAP6NAFKOHD58WPHx8Tp06JC6d++uqVOnFph1qCRkZWXpiSeekDFGEydOVIcOHWzbgoODNW7cOHXp0kWnTp3Sf/7zn0LPExISovDw8DwPlD/OpuHN//eRhQgBAEB+/PYvJ06cOKH4+Hjt3LlTHTp00KxZsxQUFFQq105KStKRI0ckSTfeeKPDfawrtq9fv75U2gTf8XYMiH0XLKbhBQDAf/Hbvxw4ffq0unXrpk2bNqlNmzZasGBBqUy9a3Xq1CmX+xhjJP1vamBcuKxBwtMxIHTBAgAAEgGkzMvMzFSPHj20du1axcXFafHixapSpUqptqFRo0a2m8wffvjB4T7Lli2TJF166aWl1i74RnHMgkUXLAAA/Be//cuwnJwc9e3bV8uXL1ejRo20dOlS1ahRw+VxEydOVHR0tPr27Vss7YiIiNBNN90kSRo+fLh++ukn27Zz587pmWee0dKlSyVJ99xzT7FcE2WXJ7Ng2Vc4HHXBogICAID/qeDrBqBwM2fO1Ny5cyWdv7Hr06ePw/0iIyNtixJK0smTJ7V3715FR0cX2Dc5OVktWrSwPT979qwk6fPPP7ddS5LmzZuXZ4HD999/X9dff7327dunDh06qE6dOrr44ou1c+dOWxet+++/X7169fL27aKccFYBcWcQuvW4/NsBAIB/IICUYZmZmbavk5KSlJSU5HC/Bg0auH3OnJwcpaSkOLyW/fWysrIKXOOPP/7QxIkTNX/+fNvA9OrVq+vaa6/V4MGDCR9+oqhdsKyVE4kKCAAA/ogAUoYNGDBAAwYM8Pi4sWPHauzYsQ63RUdH2waMe6patWpOzw3/kD9IuFsByT94Pf92AADgH/jtD8AjzgJI/ueuKiAEEAAA/A+//QF4JH8lw1kAcTQInS5YAAD4NwIIAI9QAQEAAEXBb38AHnEVQCpUqFBgX/uvrVPwOjoWAABc+PjtD8AjrgKIfbcqZwPU8+8LAAD8AwEEgEecTcMr5a2AFFYNcfYaAAC4sPHbH4BHPOmCVVg1xPrcUVUEAABc2AggADziSQCx/9rZGiEAAMB/cAcAwCOupuF1twLC+A8AAPwTAQSAR7ytgBBAAACARAAB4CFPZsGiCxYAAMiPOwAAHimuQehUQAAA8E8EEAAeKa5peAkgAAD4JwIIAI/kX9Hc3QpI/i5YBBAAAPwTAQSARxyt52HP3QoIY0AAAPBP3AEA8IirweTuDkKnAgIAgH8igADwiCcVEAahAwCA/AggADxCFywAAFAU3AEA8AgVEAAAUBQEEAAe8bYCkj9wEEAAAPBPBBAAHimuAEIXLAAA/BN3AAA84iqA2AeNwr529BwAAPgHAggAj+SfTjf/c1ZCBwAAzhBAAHjE20HoFoslT1ghgAAA4J8IIAA84u0YEMn5rFgAAMA/cAcAwCPFFUCogAAA4J8IIAA84skgdAIIAADIjwACwCOeBJCQkJBCt9EFCwAA/8QdAACPuAogubm5tq9DQ0PzbKMCAgAACCAAPOJJAHFWASGAAADgnwggADySf90PT7pg2e9LFywAAPwTdwAAPOKqAhIUFFToNiogAACAAALAI54EkPwIIAAAgAACwCOezIKVH7NgAQAA7gAAeMRVALnkkksKPZYKCAAAIIAA8IirAHLXXXcpPj5eH3/8cYFjCSAAAKCC610A4H9cBZCqVatqyZIlDo8lgAAAACogADziahpeZxgDAgAAuAMA4BFXFRB3j6UCAgCAfyKAlGHGGK1atUojR45Uu3btVK1aNQUHBysqKkq9e/fWihUrPD7n4cOH9emnn2ro0KFq27atQkJCZLFYNHjwYKfHRUdHy2KxuHw8//zz3r5dlBNFCSB0wQIAAIwBKcOWL1+uzp07Szp/kxcbG6tKlSopKSlJs2fP1uzZszVmzBiNGzfO7XPOmDFDjz32mMdtadOmjerWretw29mzZ7VhwwZJ0tVXX+3xuVG+FFcAoQsWAAD+iQBShhljFBsbq8cff1x9+/ZV9erVJUnnzp3T2LFjNWHCBI0fP15XXXWVEhIS3DpneHi44uPj1bZtW7Vt21bLli3TpEmTXB43a9asQrd9+OGHuv/++xUZGakbb7zRvTeHcosKCAAAKAoCSBnWtm1bbdmyRRUq5P0xBQcH66WXXtLGjRu1aNEiTZkyxe0AMnDgQA0cOND2PDExscjt/OyzzyRJ/fr146bSDxBAAABAUdAHogwLDw8vED7sxcfHS5K2b99eWk0qYO/evfr5558lSffcc4/P2oHSQxcsAABQFNwBlGMZGRmSpLCwMJ+1Yfr06TLG6PLLL1fz5s191g6UnuKahpcKCAAA/okAUk4ZY2zjMtq3b++zdnz++eeSqH74E7pgAQCAomAMSDk1ZcoUbdiwQcHBwRo+fLhP2rB+/Xpt2bJFAQEB6tevn8v9MzMzlZmZaXuelpZWks1DCWEdEAAAUBRUQMqhxMREDRs2TJI0fvx4NWrUyCftsFY/brjhBtWpU8fl/hMmTFDVqlVtj3r16pV0E1ECGAMCAACKgjuAcmb37t1KSEhQRkaG+vXrpxEjRvikHdnZ2fryyy8lSffee69bx4waNUqpqam2R3Jyckk2ESWkuAJIUFBQsbUJAACUH3TBKkcOHz6s+Ph4HTp0SN27d9fUqVMLDAguLUuWLNHRo0dVqVIl9ezZ061jQkJCFBISUsItQ0kjgAAAgKKgAlJOnDhxQvHx8dq5c6c6dOigWbNm+fQGztr9qmfPnqpcubLP2oHSV1wBxNkU0wAA4MJFACkHTp8+rW7dumnTpk1q06aNFixY4NOpd0+dOqV58+ZJYvYrf1Rc0/ASQAAA8E8EkDIuMzNTPXr00Nq1axUXF6fFixerSpUqPm3TN998o7NnzyoyMlI33nijT9uC0pd/9iq6YAEAAE8QQMqwnJwc9e3bV8uXL1ejRo20dOlS1ahRw+VxEydOVHR0tPr27Vsi7bJ2v+rXrx9TqfqhogQQ+32pgAAA4J+4AyjDZs6cqblz50o6f+PWp08fh/tFRkbaFiWUpJMnT2rv3r2Kjo4usG9ycrJatGhhe3727FlJ50OF9VqSNG/ePIcLHB44cEArVqyQRPcrf5U/OFABAQAAniCAlGH2i/YlJSUpKSnJ4X4NGjRw+5w5OTlKSUlxeC3762VlZTk8fvr06crNzdXll1+u5s2bu31dXDjyV0A8mYmNMSAAAIAuWGXYgAEDZIxx+dizZ0+e48aOHStjjFauXFngnNHR0W6ds2PHjg7b9OSTT8oYoz///LP43zDKhfwBxJNueAQQAABAAAHgkeIKIHTBAgDAPxFAAHiECggAACgKAggAjxQlgNhXPQggAAD4JwIIAI8EBATkGXjuSQAJDg62fU0XLAAA/BMBBIDH7EOHJwEkJCTE9jUVEAAA/BMBBIDHCCAAAMBbBBAAHvM2gNAFCwAAEEAAeIwKCAAA8BYBBIDHqIAAAABvEUAAeMy+euFtBSQsLKxY2wQAAMoHAggAjxVHBYQAAgCAfyKAAPBYcYwBIYAAAOCfCCAAPFYcFZDQ0NBibRMAACgfCCAAPOZtALHflwoIAAD+iQACwGP2QcKT6XTtZ76qXLlysbYJAACUD0zED8Bj3s6C1aFDB9WsWVOxsbF5xoMAAAD/QQAB4DFvu2BVrlxZe/bsYQ0QAAD8GAEEgMe8DSASYz8AAPB3jAEB4LGiBBAAAODfCCAAPEYAAQAA3iKAAPAYAQQAAHiLAALAY97OggUAAEAAAeAxKiAAAMBbBBAAHiOAAAAAbxFAAHiMAAIAALxFAAHgMfvQERwc7MOWAACA8oYAAsBj9gGEVc0BAIAnCCAAPGY/CxYVEAAA4AkCCACPUQEBAADeIoAA8FhAwP/+66ACAgAAPEEAAeAxi8Vi+5oKCAAA8AQBBIDH7CsgBBAAAOAJAggAj9kHEPtqCAAAgCsEEAAesw8gAAAAnuAuAoDHcnJyfN0EAABQThFAAHgsMzPT100AAADlFAEEgMcuvvhiXzcBAACUUwQQAB57+umnVbt2bY0bN87XTQEAAOUMAaQMM8Zo1apVGjlypNq1a6dq1aopODhYUVFR6t27t1asWOHxOQ8fPqxPP/1UQ4cOVdu2bRUSEiKLxaLBgwe7fY6lS5eqd+/eioqKUkhIiGrXrq2OHTvq1Vdf9bg9KJ8aNmyoQ4cOacyYMb5uCgAAKGcq+LoBKNzy5cvVuXNnSednHYqNjVWlSpWUlJSk2bNna/bs2RozZoxHn0LPmDFDjz32mFftMcZoyJAhev/99yVJdevWVfPmzXXs2DGtXr1amzZt0siRI706NwAAAPwDFZAyzBij2NhYTZ48WcePH9e2bduUmJiolJQUjRo1SpI0fvx4ffvtt26fMzw8XPHx8Ro9erTmzZunRx55xO1jR48erffff1+XXXaZ1q1bp+TkZK1bt067d+9WSkqKPvnkE4/fIwAAAPyLxRhjfN0IOJaWlqaKFSuqQgXHhapu3bpp0aJFuvXWWzVv3jyvrjF27Fg9//zzGjRokD788MNC99u0aZOuvPJK1ahRQ5s2bVLNmjW9up69tLQ0Va1aVampqQoPDy/y+QAAAEoa9y9FRwWkDAsPDy80fEhSfHy8JGn79u0l3pZ33nlHOTk5GjZsWLGEDwAAAPgnxoCUYxkZGZKksLCwEr/WggULJEkJCQlKTEzURx99pO3bt6tixYq66qqrNHjwYIIJAAAAXCKAlFPGGM2aNUuS1L59+xK91uHDh3Xw4EFZLBatWLFCI0aMyLMS9vz58/Xyyy/rm2++sQ2aBwAAAByhC1Y5NWXKFG3YsEHBwcEaPnx4iV7r0KFDkiSLxaInnnhCbdu2VWJiojIzM7V582bFx8crLS1NvXv3VnJycqHnyczMVFpaWp4HAAAA/AsBpBxKTEzUsGHDJJ2fBatRo0Yler0zZ85IknJzc1W5cmV99913atGihYKDg9WsWTPNmzdPUVFRSktL08SJEws9z4QJE1S1alXbo169eiXabgAAAJQ9BJByZvfu3UpISFBGRob69eunESNGlPg1Q0NDbV/fe++9ql69ep7tYWFheuihhyRJixcvLvQ8o0aNUmpqqu3hrFoCAACACxNjQMqRw4cPKz4+XocOHVL37t01depUWSyWEr+ufeBo0qSJw32aNm0qSdqzZ0+h5wkJCVFISEixtg0AAADlCxWQcuLEiROKj4/Xzp071aFDB82aNUtBQUGlcu3o6GhbcCgsQFhftx+cDgAAAORHACkHTp8+rW7dumnTpk1q06aNFixYUCpT71oFBgaqTZs2kqRdu3Y53Mf6ep06dUqtXQAAACh/CCBlXGZmpnr06KG1a9cqLi5OixcvVpUqVUq9HXfccYck6csvv1RWVlaB7dOmTZMk3XDDDaXaLgAAAJQvBJAyLCcnR3379tXy5cvVqFEjLV26VDVq1HB53MSJExUdHa2+ffsWW1sGDx6sevXqac+ePRo2bJjOnTtna+Po0aNtUwI/9thjxXZNAAAAXHgYhF6GzZw5U3PnzpUkBQQEqE+fPg73i4yMtC1KKEknT57U3r17FR0dXWDf5ORktWjRwvb87NmzkqTPP//cdi1JmjdvXp4FDsPCwjR79mzdeOONeu+99zRjxgzFxsZqz549OnbsmAIDA/XBBx+oWbNmRXjHAAAAuNARQMqwzMxM29dJSUlKSkpyuF+DBg3cPmdOTo5SUlIcXsv+eo66WbVu3Vp//vmnxo8fr8WLF2vjxo2qVq2aevXqpaeeekpt27Z1ux0AAADwTxZjjPF1I+Cf0tLSVLVqVaWmpio8PNzXzQEAAHCJ+5eiYwwIAAAAgFJDFyz4jLX4lpaW5uOWAAAAuMd630InIu8RQOAzp06dkiTVq1fPxy0BAADwzKlTp1S1alVfN6NcYgwIfCY3N1cHDx5UlSpVZLFYSuQaaWlpqlevnpKTk+mnWYbwcymb+LmUTfxcyiZ+LmVTafxcjDE6deqUoqKiFBDAaAZvUAGBzwQEBKhu3bqlcq3w8HB+QZRB/FzKJn4uZRM/l7KJn0vZVNI/FyofRUNsAwAAAFBqCCAAAAAASg0BBBe0kJAQPffccwoJCfF1U2CHn0vZxM+lbOLnUjbxcymb+LmUDwxCBwAAAFBqqIAAAAAAKDUEEAAAAAClhgACAAAAoNQQQAAAAACUGgIILlgLFy5U586dVaNGDVWqVEktW7bUpEmTlJub6+um+R1jjFatWqWRI0eqXbt2qlatmoKDgxUVFaXevXtrxYoVvm4i/r8xY8bIYrHIYrFo/Pjxvm6OX8vJydGUKVPUoUMHRUREKDQ0VA0aNNBtt92mefPm+bp5funo0aMaMWKE4uLiVLFiRYWGhqpRo0Z64IEHtGPHDl8374K1e/duTZkyRffff7+aN2+uChUquP1/1C+//KIePXro4osvVlhYmJo1a6Zx48YpIyOjFFqOQhngAjRhwgQjyUgyMTEx5oorrjABAQFGkrn11ltNTk6Or5voV5YtW2b7eQQEBJhLL73UtGjRwlSuXNn2+pgxY3zdTL/3999/m+DgYNvPZNy4cb5ukt86ceKEadeunZFkLBaLady4sWnVqpWJjIw0kkzv3r193US/s3XrVlOzZk0jyQQFBZnGjRubyy67zISGhhpJpmLFimblypW+buYFadiwYbb/l+wfrv6P+vzzz01gYKCRZOrUqWNatGhhgoKCjCTTpk0bc+bMmVJ6B8iPCgguOL/88ouefvppBQQE6IsvvtDOnTv1xx9/KDExUbVq1dL8+fP1xhtv+LqZfsUYo9jYWE2ePFnHjx/Xtm3blJiYqJSUFI0aNUqSNH78eH377bc+bqn/MsbowQcfVFBQkG644QZfN8ev5ebm6tZbb9Wvv/6qXr16ad++fdq6davWr1+vgwcPKjk5WY8++qivm+l3/vWvf+no0aNq3769du3apa1bt+qvv/7S/v37deutt+rs2bO67777ZFjdoNhFREQoISFBL7zwghYtWqTevXu7PGbPnj0aNGiQcnJy9Morryg5OVmJiYlKSkpS48aN9dtvv+nJJ58shdbDIR8HIKDYdevWzUgyDzzwQIFt06dPN5LMRRddZM6dO+eD1vmn1NRUk5WVVej2rl272qpT8I0pU6YYSebll182/fv3pwLiQ++9956RZDp16kS1tow4c+aMrYr+559/Fth+4sQJY7FYjCTz999/+6CF/sWd/6OGDBliJJkuXboU2LZ69WpbJevw4cMl2VQUggoILihpaWlatmyZJGnQoEEFtvfp00fh4eFKSUlh3EEpCg8PV4UKFQrdHh8fL0navn17aTUJdo4dO6annnpKzZo102OPPebr5vi9t956S5I0btw4BQTwa7osOHfunG38YExMTIHt1atXV40aNSRJ2dnZpdo2FGSM0Zw5cyQ5vhe45ppr1KRJE2VlZTGeykf4nw0XlA0bNujcuXMKDQ1Vy5YtC2wPCgpSmzZtJElr164t7eahENbBgGFhYT5uiX967LHHdOLECU2ePFlBQUG+bo5fS0pK0tatW1WjRg1dc801mjdvnu6++27deOON6tu3rz788ENlZmb6upl+p1q1aqpXr54kac2aNQW2b9u2TSkpKapWrZouueSS0m4e8tm3b58OHTokSWrfvr3Dfayvcy/gGwQQXFCSkpIkSfXr1y/0E3frp1fWfeFbxhjNmjVLUuG/KFByfvjhB02fPl133323OnTo4Ovm+L3ff/9dktSkSRPdc889uu222zR9+nQtX75cX331le6//35deeWV2rt3r49b6n+sMy4NHDhQ33zzjVJSUpSamqrvv/9et912mywWi1555RWFhob6uKWw/n4PCQlRVFSUw324F/AtAgguKP/884+k8+Xwwli3WfeFb02ZMkUbNmxQcHCwhg8f7uvm+JWMjAw99NBDqlq1ql577TVfNweS7VPb3377TdOnT9fgwYO1Z88eZWRkaNmyZYqJidHWrVvVu3dvphQvZffee6+++eYbRURE6Pbbb1dERISqVaumm2++WcHBwVq4cKHuv/9+XzcT+t/v92rVqslisTjch3sB3yKA4IJi7coTHBxc6D4hISGSpPT09FJpEwqXmJioYcOGSTr/6WKjRo183CL/Mn78eO3YsUMvvviiatWq5evmQNKZM2ckSVlZWbruuus0ZcoUNWjQQCEhIbrxxhs1e/ZsWSwW/f777/ruu+983Fr/YozRrl27lJKSosDAQMXGxqpZs2YKDg7Wpk2b9MEHH+jEiRO+bibEvUB5QADBBcVa+j537lyh+1j7TzPewLd2796thIQEZWRkqF+/fhoxYoSvm+RXtmzZoldffVUtW7bUww8/7Ovm4P+z775jDef2mjdvrk6dOkmSFi9eXGrtgvTQQw9p5MiRqlevnnbs2KGkpCRt3rxZycnJ6tatm+bMmaNOnTopJyfH1031e9wLlH0EEFxQ3CmputNNCyXr8OHDio+P16FDh9S9e3dNnTq10DI5SsaQIUOUnZ2t9957j5mWyhD7/5eaNGnicJ+mTZtKOr/OAUrHH3/8oSlTpigoKEgzZsxQdHS0bVvNmjU1ffp0RURE6M8//9TMmTN911BI+t+/o5MnTxa6Lgv3Ar7Fbx1cUKyzj+zbt6/QqRB37dqVZ1+UrhMnTig+Pl47d+5Uhw4dNGvWLGZe8oENGzbIYrHo1ltvVe3atfM8vvrqK0nSyy+/rNq1a9tmjkPJa9y4se1raxeR/Kyv80l76Vm9erWMMbr00ktts2HZCw8PV9u2bSVJ69evL+3mIR/r7/fMzEwdPHjQ4T7cC/gWAQQXlBYtWigoKEgZGRlKTEwssD0rK0u//fabJOmqq64q7eb5vdOnT6tbt27atGmT2rRpowULFlD+9qGcnBwdOXKkwMPaf/r06dM6cuSIjh075uOW+o8WLVrYuo9Yb5Dys75ep06dUmuXvzt16pTLfayftFv//cB36tevr9q1a0s6Hx4dsb7OvYBvEEBwQQkPD1fnzp0lSR999FGB7bNmzVJaWpouuugidezYsZRb598yMzPVo0cPrV27VnFxcVq8eLGqVKni62b5LWvXBEeP/v37Szq/EJ4xhq4+pahSpUrq1q2bJGnatGkFth8+fFjff/+9JOmGG24o1bb5M+un5Nu3b1dycnKB7WlpabYPty699NJSbRsKslgs6tmzpyTH9wJr1qzR1q1bFRQUpFtvvbW0mwcRQHABGj16tCwWiz788EN9+eWXttf/+OMPPf7445KkJ5980unsGCheOTk56tu3r5YvX65GjRpp6dKltlWDAeT17LPPKjAwUDNmzMgTQk6ePKkBAwYoPT1dMTEx6tOnjw9b6V+6dOmiiIgIZWVlqW/fvnlC+dGjR3XXXXfp+PHjCg0N1e233+67hsJm5MiRCg4O1pIlS/Tqq6/aKlR79+7VwIEDJUmDBw+2VUpQuiymsNE5QDn24osvasyYMZLOLzZUuXJlbdq0Sbm5uerevbvmzZunwMBAH7fSf3z55Zfq16+fpPOfJNasWdPhfpGRkbZFCeE7AwYM0LRp0zRu3DjbvyOUrvfff19DhgyRMUb169dXzZo19ffff+vs2bOKiIjQ0qVLdeWVV/q6mX5l0aJF6tWrlzIyMhQYGKiYmBgFBQVpx44dOnfunCpUqKAPP/zQVkFE8Vm9erV69Ohhe3769GllZmaqYsWKebrxbtiwIc8YnU8//VT33XefcnNzVadOHdWsWVObNm1SVlaWWrVqpR9//FGVKlUq1feC8xwvFQ2Uc6NHj1bz5s315ptv6vfff9fhw4d1+eWX67777tPQoUMJH6XMOt2hdH7V2cJWnm3QoEFpNQko0x566CHFxcXp1Vdf1S+//KI///xTUVFR6t69u0aNGsX4Dx/o2rWr/vjjD73++utavny59u3bJ2OMIiMjdf3112v48OFq2bKlr5t5QcrKylJKSkqB18+ePauzZ8/anuefmOHee+9VbGysJkyYoDVr1ujvv/9WTEyM/u///k9PPfUUq9b7EBUQAAAAAKWGMSAAAAAASg0BBAAAAECpIYAAAAAAKDUEEAAAAAClhgACAAAAoNQQQAAAAACUGgIIAAAAgFJDAAEAAABQagggAAAAAEoNAQQAAABAqSGAAICX9uzZI4vFoujoaF83pVi0a9dOEREROn36dIlfa+XKlbJYLOrYsWOJXwslp7h+jgMHDlSFChW0devW4mkYgDKNAAIAhZg4caLGjh2rkydP+ropJW7WrFlau3atHn/8cVWuXNnXzYGfefrppyVJo0aN8nFLAJQGAggAFGLixIl6/vnnCw0gQUFBaty4sRo1alS6DStmubm5Gj16tMLDwzV06NBSuWbFihXVuHFj1a9fv1Suh7ItNjZWffr00dy5c/Xrr7/6ujkASlgFXzcAAMqrOnXqXBBdRr7//nslJSWpf//+Cg8PL5Vrtm3b9oL43qH49O/fXzNmzNC7776rdu3a+bo5AEoQFRAA8HMffPCBJOn//u//fNwS+LPOnTsrIiJC33zzjV90ewT8GQEEAPKZOnWqLBaL9u7dK0lq2LChLBaL7bFy5UpJzgehW/eVpDlz5uiaa65R5cqVVatWLfXv31+HDx+27fvJJ5+oVatWqlSpkmrWrKmHHnpIqamphbZv//79evTRR3XppZcqLCxM1apVU6dOnfT11197/F7PnDmj7777TqGhobrhhhsc7lMS78XV4OWzZ8/qtddeU7t27VStWjVVrFhRl1xyie655x79+OOPefaNjo6WxWLRnj17tGLFCnXt2lURERF5flaStG/fPj388MNq2LChQkJCFBERoa5du2rRokUO22CM0aeffqrrr79e1apVU3BwsGrXrq1WrVrpySef1P79+x0eM2PGDMXHx+uiiy5SSEiIYmJi9Oijj+b5PuV34sQJPffcc2rRooXCw8NVuXJlNW3aVA899JA2bNhQYP+UlBQ9+eSTaty4scLCwlS9enV17NhR06dPlzGmwP7Wv9MDBgxQZmamxo4dq9jYWIWGhqpevXp6/PHHdebMmULbZ/25V6pUSRdddJESEhK0fv36QveXpFWrVqlnz56qXbu2goKCVKNGDTVt2lSDBw922M2qQoUKuummm5Senq758+c7PTeAcs4AAPJYuHChad++vQkJCTGSTOvWrU379u1tj8TERGOMMbt37zaSTIMGDQqcQ5KRZN5++20jydStW9c0b97cds5mzZqZ9PR08+ijjxpJJiYmxsTFxZkKFSoYSaZDhw4mNze3wHlXrlxpqlataiSZsLAwc/nll5t69erZrvfEE0949F6XLl1qJJmrr7660H1K4r2sWLHCti2/vXv3mqZNm9que8kll5iWLVuaGjVqODymQYMGRpJ56aWXTEBAgKlevbpp06aNqVu3rlmxYoUxxphff/3VVKtWzUgylSpVMq1atTJ169a1XeOZZ54p0I4nnnjCtr1+/fqmTZs2pmHDhiY4ONhIMnPmzMmz/7lz50yfPn1sx0RFRZnmzZubihUrGkkmMjLSbNu2rcB1Nm7caKKioowkExAQYJo1a2auvPJKEx4ebiSZ/v3759k/KSnJ9jMPDg42LVu2NDExMbbr3nvvvQW+35988omRZPr162euv/56Y7FYTFxcnGncuLEJCAgwkkx8fLzDn//LL79sO3dkZKRp1aqVqVy5sgkJCTHjxo1z+DOZO3eu7bwXXXSRadmypWnSpImpVKmSkWSGDRvm8FpvvfWWkWQGDRrkcDuACwMBBAAKYb2x3b17t8Pt7gSQSpUqmS+++ML2enJysomNjTWSzG233WaqVq1qli1bZtv+559/2m60Fy5cmOecBw4cMDVq1DAWi8W89NJLJiMjw7Zt9erVpk6dOkaSWbBggdvv8fnnnzeSzNChQwvdpyTeS2EBJDs727Rq1coW/P7+++882zds2GAmT56c5zXrzykwMNA8//zzJisryxhjTG5ursnIyDBnzpwx9evXN5LMHXfcYdLS0mzHTp061QQGBhZo49GjR01AQICpWrWqWbVqVZ7rpaenmy+//NL88ccfeV7/97//bSSZFi1amA0bNtheP3v2rBkyZIjtPdlLTU21te3mm282ycnJebb/9NNP5vPPP7c9z83NNa1bt7Z97w4fPmzbtmjRItsNfv7vkTWABAUFmWbNmuUJQr/88ost7CxatCjPcYmJiSYwMNBYLBbzzjvv2ILNqVOnzJ133mmCgoIc/hwvu+wyWzuys7PztH/FihVm/vz5xpE1a9YYSaZx48YOtwO4MBBAAKAQxRFAHH3S+9///te2/c033yyw3Xoj++ijj+Z5/fHHHzeSzGOPPeawPQsWLDCSzA033ODqrdkMHDjQSDIvvvhiofuUxHspLIDMnDnTSDI1a9Y0x48fd+s9WH9Ot9xyi8PtU6ZMMZJMrVq1THp6eoHt1nBw3XXX2V775ZdfjCTTs2dPt9pw9OhRExISYsLDwwuECGOMycnJMW3atDGSzE8//WR7/ZVXXjGSTNOmTfMEysJYK1YhISHm0KFDBbZbz9egQYM8VRBrALFYLOa3334rcJz171b+n9Pdd99tJJk+ffoUOCY9Pd3UrFnT4c8xJCTEVK9e3eX7yc/6byo0NNTjYwGUH4wBAYASNGjQoAKvXXnllbavBw4cWGB7ixYtJEm7du3K8/rs2bMlSYMHD3Z4rZtvvlnBwcFas2aNsrOz3Wrf8ePHJUk1atRwuW9xvpfCzJs3z3aui/5fe3cbEkXXxgH8v6uoaYuxaZqlkvhuqeiagZoVpVEJIogJboXRlhWYkpYYlBlFWJEGpiiSmiAZBJF+MAIlixTEl9QtdVMzFQ1f0A1dreb5IDPPbjvr7pZpdV8/iO77nJk558wsNGfOy7V+vUHnsI4cOcKbXltbCwA4ceIELCwstPKTk5MBAK9fv+bWQTg6OgIAGhsb8fHjR71l19TUQKVSITIyEps3b9bKFwqFOHToEABorGFh25ucnAxzc3O95bBtiY2Nhb29vVb+qVOnYG5ujoGBAbx//14r39/fHxKJRCs9KCgIgPZzYstLSkrSOsfCwoL3mQOL929qagrPnz/X0yJN7O9wbm5uRQJiEkJWB23DSwghvxFfjBBbW1vub75tb9l89RcwpVKJ/v5+AIBMJluyzLm5OYyPj8POzk5v/ebm5gDAoJff5WrLUuRyOQD81DasXl5evOnd3d0AAG9vb958Nzc3mJmZYX5+HgqFAr6+vti0aRNiY2NRVVUFV1dX7N69G7t27UJYWBh27NgBU1PNfz7fvn0LAHjz5g1CQ0N5yxkdHQUADA0NcWnGtldfW0QiERwdHdHb24vu7m54enpq5OuKWbNhwwYAms9pamoKY2NjAHTfW13pKSkpOHPmDCIiIhAYGIi9e/ciNDQU4eHhEIlEOtu3Zs0a7r9nZ2cpKCYh/yjqgBBCyG9kaWmplcbuKMWXp57PqO1mpL6T1KtXr/SWOzs7a1D92C/Ohmx7ulxtWcr09DQAYN26dQYdr87Kyoo3nX2pZl+yfyQQCGBra4uhoSHMzMxw6WVlZfD29kZxcTFqa2u50QBbW1ukp6cjNTUVQuHiRAL2+QwODmJwcHDJeqo/G2Pbq68tAGBnZ4fe3l6NtrB03SO2HerPSb0zwnYk+cric/r0aYhEIty+fRvNzc1obm7GzZs3YWFhAalUipycHFhbW2udNzExAWDxmRgyKkcI+TvRFCxCCPkLqH8Jnp+fB7O4hk/nH76tgfmwL7Lsi99qY7+OL2ccCPbesV/zf8QwDD5//qxRPrA4xejKlSv49OkT5HI5CgsLERUVhfHxcaSlpeHOnTtaZWRmZup9Ng8ePPjp9uprC/D/kZalRhqMKQsAd39+tFQ9pFIpWltbMTIygsrKShw/fhympqYoKipCQkIC7zns71AsFsPExOQXak8I+ZNRB4QQQnRgv97/CaytreHg4AAA6OzsXLbrsms42KlAq83HxwcAeONE/Cx3d3cAQFdXF29+T08P5ufnYWJionOKkqenJ2QyGZ4+fYr8/HwAQFFREZfPTonq6Ogwqm7GtldfW2ZmZrgRGPbYn7Vu3Tqug6orar0hvxt7e3vExcWhuLgYjY2NEAqFePbsGUZGRrSOZdsVEBDwCzUnhPzpqANCCCE6sPPRDZ3O9LvFxMQAAO7evbts12TXK+gLKrdSoqOjAQAlJSXLNioTGRkJYLHDwK55UZeXlwcACAkJ0TlFSR27XmN4eJhLO3jwIMzMzFBTU4Oenh6D68a29969e5ifn9d7PNuWqqoq3sCGhYWFUKlUcHZ2hoeHh8H10GXfvn0AgIKCAq08lUqFkpISo67n7e3NTb1Sv3+spqYmAEBYWJixVSWE/EWoA0IIITq4uLgAgFbk7dVy4cIFiMVilJaWIjU1VWvazsTEBEpKSnDt2jWDr+nm5oYtW7ZgYGCAN7L3SouOjoZEIsHY2BgOHDigtZNTW1sb7t+/b9Q14+Pj4eTkhNHRURw7dkxjbcPDhw9RWFgIALh48SKX/uLFC6SlpWmNNCiVSuTk5ADQ/Erv4OCAc+fOYWFhAZGRkRoR2IHFaV5NTU1ISkrS2GlKJpPB2dkZnZ2diImJ0VigDixGE6+oqOD+f8+ePQgKCoJKpUJ8fLzGFKja2lpkZWVxbVmOEbyUlBQIhUI8evQIBQUF3BqRL1++IDExkbeTOD09jcOHD6Ourg7fv3/n0r99+4a8vDxMTk7CysqKt4PErm+KiIj45boTQv5gK7nnLyGE/E3Kysq4GBdbt25lwsPDmfDwcC7InCFxQPgsdR7DLB0lvKGhgbGxseGCym3bto0JDg5mXFxcGIFAwABg4uLijGonG8361q1bvPm/oy36IqF7eHhw5bq7uzOBgYHM+vXrl4yEriteC8MsRkJnI8hbWVkxEolEI4L8pUuXNI5/8uQJl2dra8tIJBKNqObW1tZMc3OzxjkLCwtc3AwAjL29PbN9+3bGz8+PEYlEXLpcLtc4r7W1lbG3t+ciofv4+DD+/v5cffkiobNR3M3NzZmAgAAuICQARiqV6oyE/uO1DHke169f14juLpFIGJFIpDMS+uTkpEbwSj8/P0YikXC/W4FAwBQVFWmVMzg4yEVoJ4T822gEhBBCdJBKpcjNzYWvry8UCgXq6+tRX1+/rAukjRUSEoKuri5kZmbC29sbfX19aG9vh1AoxP79+5Gfn4/c3FyjrpmYmAhTU1ONL+2rycnJCc3Nzbhx4wYCAgIwPDwMuVwOsViMo0ePIjs72+hrBgcHo62tDSdPnoSNjQ3a29uhVCoRERGB6upqrWuGhYUhLy8PUVFRWLt2Lbq6utDf3w9XV1ekp6fj3bt3WusUTE1NUV5ejurqam5qVUtLC0ZGRuDu7o6zZ8+irq5Oa22Gn58fOjo6kJGRAS8vL/T19UGhUMDBwQFJSUlISUnRON7V1RUtLS04f/48nJyc0NnZibGxMezcuRPl5eUoLS1d1vVLGRkZePz4MYKDgzE5OQmFQoGwsDA0NDTwbjksEolQXl4OqVQKR0dH9Pf3o7OzE2KxGAkJCWhpaeGNZVNZWQmGYXTGuSGE/DsEDGPg3oiEEEL+WTKZDEVFRXj58qXOOBaE/C5fv36Fh4cHlEolFAoFxf8g5B9HIyCEEEKQlZUFS0tLXL16dbWrQv6DKioq8OHDB1y+fJk6H4T8B1AgQkIIIdi4cSPKysrQ0dEBpVJJL4FkRQkEAmRnZ0Mmk612VQghK4CmYBFCCCGEEEJWDE3BIoQQQgghhKwY6oAQQgghhBBCVgx1QAghhBBCCCErhjoghBBCCCGEkBVDHRBCCCGEEELIivkfdbzNmZAmh2EAAAAASUVORK5CYII=' width=800.0/>\n",
+       "            </div>\n",
+       "        "
       ],
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -2254,7 +345,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,
diff --git a/stride_examples/examples/marmottant/02_embedded_bubble.ipynb b/stride_examples/examples/marmottant/02_embedded_bubble.ipynb
index f544365c..dd18bfe5 100644
--- a/stride_examples/examples/marmottant/02_embedded_bubble.ipynb
+++ b/stride_examples/examples/marmottant/02_embedded_bubble.ipynb
@@ -36,7 +36,8 @@
    "outputs": [],
    "source": [
     "from stride import *\n",
-    "%matplotlib notebook\n",
+    "from stride_private import *\n",
+    "%matplotlib widget\n",
     "\n",
     "import numpy as np"
    ]
@@ -245,65 +246,86 @@
      "output_type": "stream",
      "text": [
       "(ShotID 0) Preparing to run state for shot\n",
+      "(ShotID 0) Selected boundary type complex_frequency_shift_PML_2\n",
       "(ShotID 0) Estimated bandwidth for the propagated wavelet 1.600-2.400 MHz\n",
-      "(ShotID 0) Spatial grid spacing (0.050 mm | 12.833 PPW) is below dispersion limit (0.128 mm | 5.000 PPW)\n",
+      "(ShotID 0) Using DRP scheme\n",
+      "(ShotID 0) Spatial grid spacing (0.050 mm | 12.833 PPW) is below dispersion limit (0.214 mm | 3.000 PPW)\n",
       "(ShotID 0) Time grid spacing (0.005 μs | 15%) is below OT2 limit (0.012 μs)\n",
       "(ShotID 0) Selected undersampling level 20\n",
       "(ShotID 0) Selected time stepping scheme OT2\n",
+      "(ShotID 0) Expected wavefield size 2.3193 GB\n",
       "Operator `acoustic_iso_state` instance configuration:\n",
-      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05}\n",
+      "\t * name=acoustic_iso_state\n",
+      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05, dt: 5e-09}\n",
       "\t * opt=advanced\n",
-      "\t * platform=None\n",
-      "Operator `acoustic_iso_state` generated in 18.22 s\n",
-      "  * lowering.Clusters: 11.51 s (63.2 %)\n",
-      "     * specializing.Clusters: 6.70 s (36.8 %)\n",
-      "        * fuse: 4.36 s (24.0 %)\n",
-      "  * lowering.Expressions: 4.26 s (23.4 %)\n",
-      "Flops reduction after symbolic optimization: [5668 --> 1306]\n",
-      "Operator `acoustic_iso_state` fetched `/tmp/devito-jitcache-uid1000/09185d1cbee216e49094c2430518fc1f3f7a43d1.c` in 0.67 s from jit-cache\n",
+      "\t * devicecreate=(p(t, x, y, z), p_saved(time_under0, x, y, z))\n",
+      "Operator `acoustic_iso_state` generated in 33.59 s\n",
+      "  * lowering.Clusters: 26.59 s (79.2 %)\n",
+      "     * specializing.Clusters: 16.18 s (48.2 %)\n",
+      "        * fuse: 11.99 s (35.8 %)\n",
+      "Flops reduction after symbolic optimization: [1860 --> 1249]\n",
+      "Operator `acoustic_iso_state` fetched `/tmp/devito-jitcache-uid1000/79e5ef08afb9d889d9de0bd310320f97556f9534.c` in 0.56 s from jit-cache\n",
+      "Operator `acoustic_iso_state_save` instance configuration:\n",
+      "\t * name=acoustic_iso_state_save\n",
+      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05, dt: 5e-09}\n",
+      "\t * opt=advanced\n",
+      "\t * devicecreate=(p(t, x, y, z), p_saved(time_under0, x, y, z))\n",
+      "Operator `acoustic_iso_state_save` generated in 29.80 s\n",
+      "  * lowering.Clusters: 22.83 s (76.7 %)\n",
+      "     * specializing.Clusters: 13.90 s (46.7 %)\n",
+      "        * fuse: 10.31 s (34.7 %)\n",
+      "Flops reduction after symbolic optimization: [1860 --> 1249]\n",
+      "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/cf34e4c/472372fba7795fec518f2b5350679d8e).\n",
+      "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/cf34e4cd438053ba83e1143c86979972b8352954.c -lm -o /tmp/devito-jitcache-uid1000/cf34e4cd438053ba83e1143c86979972b8352954.so\n",
+      "Operator `acoustic_iso_state_save` jit-compiled `/tmp/devito-jitcache-uid1000/cf34e4cd438053ba83e1143c86979972b8352954.c` in 3.79 s with `CustomCompiler`\n",
       "(ShotID 0) Using inhomogeneous density\n",
       "(ShotID 0) Running state equation for shot\n",
-      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=8,nthreads=6> took 0.329654 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=16,nthreads=6> took 0.340834 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=24,nthreads=6> took 0.343902 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=32,nthreads=6> took 0.343749 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=16,nthreads=6> took 0.349124 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=24,nthreads=6> took 0.355063 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=32,nthreads=6> took 0.358047 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=64,nthreads=6> took 0.369792 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=96,nthreads=6> took 0.370216 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=120,nthreads=6> took 0.384957 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=8,nthreads=6> took 0.348787 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=24,nthreads=6> took 0.355744 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=32,nthreads=6> took 0.352925 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=64,nthreads=6> took 0.358633 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=96,nthreads=6> took 0.363869 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=120,nthreads=6> took 0.382335 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=8,nthreads=6> took 0.355765 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=16,nthreads=6> took 0.354143 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=32,nthreads=6> took 0.349894 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=64,nthreads=6> took 0.369859 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=96,nthreads=6> took 0.370375 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=120,nthreads=6> took 0.371509 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=8,nthreads=6> took 0.356544 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=16,nthreads=6> took 0.359466 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=24,nthreads=6> took 0.348482 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=64,nthreads=6> took 0.356375 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=48,i2y0_blk0_size=24,nthreads=6> took 0.341489 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=48,nthreads=6> took 0.351965 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=48,i2y0_blk0_size=48,nthreads=6> took 0.347255 (s) in 5 timesteps\n",
-      "AutoTuner: run <i2x0_blk0_size=64,i2y0_blk0_size=32,nthreads=6> took 0.342511 (s) in 5 timesteps\n",
-      "AutoTuner: selected <nthreads=6,i2x0_blk0_size=8,i2y0_blk0_size=8>\n",
-      "Operator `acoustic_iso_state` ran in 82.11 s\n",
-      "Global performance: [OI=0.01, 18.00 GFlops/s, 0.07 GPts/s]\n",
+      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=8,nthreads=6> took 0.181665 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=16,nthreads=6> took 0.219824 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=24,nthreads=6> took 0.209254 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=32,nthreads=6> took 0.221023 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=16,nthreads=6> took 0.277745 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=24,nthreads=6> took 0.211388 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=32,nthreads=6> took 0.213780 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=64,nthreads=6> took 0.226255 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=96,nthreads=6> took 0.201738 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=8,i2y0_blk0_size=120,nthreads=6> took 0.208525 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=8,nthreads=6> took 0.184190 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=24,nthreads=6> took 0.190233 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=32,nthreads=6> took 0.188832 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=64,nthreads=6> took 0.196997 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=96,nthreads=6> took 0.223017 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=16,i2y0_blk0_size=120,nthreads=6> took 0.236120 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=8,nthreads=6> took 0.192039 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=16,nthreads=6> took 0.193979 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=32,nthreads=6> took 0.215875 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=64,nthreads=6> took 0.232399 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=96,nthreads=6> took 0.215103 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=120,nthreads=6> took 0.230530 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=8,nthreads=6> took 0.180182 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=16,nthreads=6> took 0.184600 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=24,nthreads=6> took 0.205180 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=32,i2y0_blk0_size=64,nthreads=6> took 0.215435 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=48,i2y0_blk0_size=24,nthreads=6> took 0.181535 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=24,i2y0_blk0_size=48,nthreads=6> took 0.234917 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=48,i2y0_blk0_size=48,nthreads=6> took 0.237129 (s) in 5 timesteps\n",
+      "AutoTuner: run <i2x0_blk0_size=64,i2y0_blk0_size=32,nthreads=6> took 0.186503 (s) in 5 timesteps\n",
+      "AutoTuner: selected <nthreads=6,i2x0_blk0_size=32,i2y0_blk0_size=8>\n",
+      "Operator `acoustic_iso_state_save` ran in 55.70 s\n",
+      "Global performance: [OI=0.01, 16.38 GFlops/s, 0.10 GPts/s]\n",
+      "Global performance <w/o setup>: [55.70 s, 0.10 GPts/s]\n",
       "Local performance:\n",
-      "  * section0<160> ran in 0.01 s [OI=0.13, 0.22 GFlops/s]\n",
-      "  * section1<160> ran in 0.01 s [OI=0.13, 0.22 GFlops/s]\n",
-      "  * section2<160> ran in 0.01 s [OI=0.13, 0.32 GFlops/s]\n",
-      "  * section3<<1349,20,160,160>,<1349,20,160,160>,<1349,20,160,160>,<1349,20,160,160>,<1349,20,160,160>,<1349,20,160,160>,<1349,160,20,160>,<1349,160,20,160>,<1349,160,20,160>,<1349,160,20,160>,<1349,160,20,160>,<1349,160,20,160>,<1349,160,160,20>,<1349,160,160,20>,<1349,160,160,20>,<1349,160,160,20>,<1349,160,160,20>,<1349,160,160,20>,<1349,15,15,17,17,129>,<1349,15,15,8,8,120>,<1349,29,169,129>,<1349,20,160,120>,<1349,29,169,129>,<1349,20,160,120>,<1349,169,29,129>,<1349,160,20,120>,<1349,169,29,129>,<1349,160,20,120>,<1349,169,169,29>,<1349,160,160,20>,<1349,169,169,29>,<1349,160,160,20>> ran in 81.85 s [OI=0.01, 18.06 GFlops/s, 0.13 GPts/s]\n",
-      "  * section5<<1349,1>,<1349,1>,<1349,1>,<1349,1>,<1349,1>,<1349,1>,<1349,1>,<1349,1>,<1349,1>> ran in 0.01 s [OI=34.60, 0.30 GFlops/s, 0.01 GPts/s]\n",
-      "  * section6<<1349,120>,<1349,120>,<1349,120>,<1349,120>,<1349,120>,<1349,120>,<1349,120>,<1349,120>,<1349,120>,<1349,120>> ran in 0.01 s [OI=45.00, 18.21 GFlops/s]\n",
-      "Performance[mode=advanced] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6, 'i2x0_blk0_size': 8, 'i2y0_blk0_size': 8}\n",
+      "  * section0 ran in 0.01 s\n",
+      "  * section1 ran in 0.01 s\n",
+      "  * section2 ran in 0.01 s\n",
+      "  * section3 ran in 24.33 s [OI=0.01, 19.42 GFlops/s, 0.18 GPts/s]\n",
+      "  * section4 ran in 7.82 s [OI=3.04, 21.77 GFlops/s, 0.30 GPts/s]\n",
+      "  * section5 ran in 23.28 s [OI=0.01, 11.58 GFlops/s, 0.15 GPts/s]\n",
+      "  * section6 ran in 0.01 s\n",
+      "  * section7 ran in 0.02 s [OI=1.45, 1.36 GFlops/s]\n",
+      "  * section8 ran in 0.25 s \n",
+      "Performance[mode=advanced] arguments: {'i2x0_blk0_size': 32, 'i2y0_blk0_size': 8, 'nthreads': 6, 'nthreads_nonaffine': 6, 'pthreads': 0}\n",
+      "(ShotID 0) Completing state equation run for shot\n",
       "(ShotID 0) Completed state equation run for shot\n"
      ]
     }
@@ -315,7 +337,7 @@
     "traces_0 = await pde(shot_wavelets, vp, rho=rho, problem=sub_problem, \n",
     "                     diff_source=True,\n",
     "                     boundary_type='complex_frequency_shift_PML_2',\n",
-    "                     save_wavefield=True, save_undersampling=20)\n",
+    "                     save_wavefield=True, save_undersampling=20, force_raw_wavefield=True)\n",
     "\n",
     "wavefield_0 = pde.wavefield.data[:, :, pde.wavefield.shape[-1]//2].copy()"
    ]
@@ -354,7 +376,7 @@
    "id": "1d3dced9",
    "metadata": {},
    "source": [
-    "Then, wen define the initial bubble conditions, the bubble's initial radius, by creating a `SparseField` object."
+    "Then, we define the initial bubble conditions, the bubble's initial radius, by creating a `SparseField` object."
    ]
   },
   {
@@ -373,7 +395,7 @@
    "id": "7f253313",
    "metadata": {},
    "source": [
-    "We also create a `ParticleField` object to define where in the simulation region the bubble will be located: in this case at its centre."
+    "We also create a `SparseCoordinates` object to define where in the simulation region the bubble will be located: in this case at its centre."
    ]
   },
   {
@@ -383,7 +405,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "x_0 = ParticleField(name='x_0', num=1, grid=problem.grid)\n",
+    "x_0 = SparseCoordinates(name='x_0', num=1, grid=problem.grid)\n",
     "x_0.data[0, :] = np.array(space.size) / 2"
    ]
   },
@@ -440,42 +462,59 @@
      "text": [
       "(ShotID 0) Preparing to run state for shot\n",
       "(ShotID 0) Estimated bandwidth for the propagated wavelet 1.600-2.400 MHz\n",
-      "(ShotID 0) Spatial grid spacing (0.050 mm | 12.833 PPW) is below dispersion limit (0.128 mm | 5.000 PPW)\n",
+      "(ShotID 0) Using DRP scheme\n",
+      "(ShotID 0) Spatial grid spacing (0.050 mm | 12.833 PPW) is below dispersion limit (0.214 mm | 3.000 PPW)\n",
       "(ShotID 0) Time grid spacing (0.005 μs | 15%) is below OT2 limit (0.012 μs)\n",
       "(ShotID 0) Selected undersampling level 20\n",
       "(ShotID 0) Selected time stepping scheme OT2\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
+      "(ShotID 0) Expected wavefield size 2.3193 GB\n",
       "Operator `acoustic_iso_state` instance configuration:\n",
-      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05}\n",
+      "\t * name=acoustic_iso_state\n",
+      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05, dt: 5e-09}\n",
+      "\t * opt=advanced\n",
+      "\t * devicecreate=(p(t, x, y, z), p_saved(time_under0, x, y, z))\n",
+      "Operator `acoustic_iso_state` generated in 52.26 s\n",
+      "  * lowering.Clusters: 40.12 s (76.8 %)\n",
+      "     * specializing.Clusters: 24.53 s (47.0 %)\n",
+      "        * fuse: 18.73 s (35.9 %)\n",
+      "Flops reduction after symbolic optimization: [1883 --> 1249]\n",
+      "Operator `acoustic_iso_state` fetched `/tmp/devito-jitcache-uid1000/af348409237fad0eb9c1d6b6c12ff7feeac0a66e.c` in 0.66 s from jit-cache\n",
+      "Operator `acoustic_iso_state_save` instance configuration:\n",
+      "\t * name=acoustic_iso_state_save\n",
+      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05, dt: 5e-09}\n",
       "\t * opt=advanced\n",
-      "\t * platform=None\n",
-      "Operator `acoustic_iso_state` generated in 21.48 s\n",
-      "  * lowering.Clusters: 14.37 s (67.0 %)\n",
-      "     * specializing.Clusters: 8.90 s (41.5 %)\n",
-      "        * fuse: 5.41 s (25.2 %)\n",
-      "Flops reduction after symbolic optimization: [6318 --> 1738]\n",
-      "Operator `acoustic_iso_state` fetched `/tmp/devito-jitcache-uid1000/80b6432b7ba3e43442da5ca9c007b17f53a87a36.c` in 0.65 s from jit-cache\n",
+      "\t * devicecreate=(p(t, x, y, z), p_saved(time_under0, x, y, z))\n",
+      "Operator `acoustic_iso_state_save` generated in 49.92 s\n",
+      "  * lowering.Clusters: 39.03 s (78.2 %)\n",
+      "     * specializing.Clusters: 24.29 s (48.7 %)\n",
+      "        * fuse: 18.75 s (37.6 %)\n",
+      "     * schedule: 10.29 s (20.7 %)\n",
+      "Flops reduction after symbolic optimization: [1883 --> 1249]\n",
+      "recompiling for non-existent cache dir (/tmp/devito-codepy-uid1000/4194f14/25c540ef1691e4eefd5181fd845f6fea).\n",
+      "gcc -march=native -O3 -g -fPIC -Wall -std=c99 -Wno-unused-result -Wno-unused-variable -Wno-unused-but-set-variable -ffast-math -shared -fopenmp /tmp/devito-jitcache-uid1000/4194f14e4dc8631801b87cd22b43c5c9dde3a90d.c -lm -o /tmp/devito-jitcache-uid1000/4194f14e4dc8631801b87cd22b43c5c9dde3a90d.so\n",
+      "Operator `acoustic_iso_state_save` jit-compiled `/tmp/devito-jitcache-uid1000/4194f14e4dc8631801b87cd22b43c5c9dde3a90d.c` in 5.81 s with `CustomCompiler`\n",
       "(ShotID 0) Using inhomogeneous density\n",
       "(ShotID 0) Running state equation for shot\n",
-      "AutoTuner: cannot perform autotuning unless there is one time loop; skipping\n",
-      "Operator `acoustic_iso_state` ran in 93.44 s\n",
-      "Global performance: [OI=0.01, 17.58 GFlops/s, 0.01 GPts/s]\n",
+      "AutoTuner: cannot perform autotuning with 2 time loops; skipping\n",
+      "Operator `acoustic_iso_state_save` ran in 66.48 s\n",
+      "Global performance: [OI=0.01, 15.25 GFlops/s, 0.10 GPts/s]\n",
+      "Global performance <w/o setup>: [66.47 s, 0.10 GPts/s]\n",
       "Local performance:\n",
-      "  * section0<<1,7,7,7>,<1,7,7,7>> ran in 0.01 s [OI=0.10, 0.40 GFlops/s]\n",
-      "  * section1<160> ran in 0.01 s [OI=0.13, 0.22 GFlops/s]\n",
-      "  * section2<160> ran in 0.01 s [OI=0.13, 0.32 GFlops/s]\n",
-      "  * section3<160> ran in 0.01 s [OI=0.13, 0.22 GFlops/s]\n",
-      "  * section4<1> ran in 0.01 s [OI=0.15, 0.02 GFlops/s]\n",
-      "  * section5<<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,15,15,17,17,129>,<1499,15,15,8,8,120>,<1499,29,169,129>,<1499,20,160,120>,<1499,29,169,129>,<1499,20,160,120>,<1499,169,29,129>,<1499,160,20,120>,<1499,169,29,129>,<1499,160,20,120>,<1499,169,169,29>,<1499,160,160,20>,<1499,169,169,29>,<1499,160,160,20>> ran in 92.96 s [OI=0.01, 17.67 GFlops/s, 0.12 GPts/s]\n",
-      "  * section6<1499,1,7,7,7> ran in 0.01 s [OI=0.10, 0.26 GFlops/s]\n",
-      "  * section7<1499,100,1> ran in 0.18 s [OI=1.69, 0.34 GFlops/s, 0.01 GPts/s]\n",
-      "  * section8<<1499,1>,<1499,1,7,7,7>> ran in 0.01 s [OI=0.13, 0.60 GFlops/s, 0.09 GPts/s]\n",
-      "  * section9<<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>> ran in 0.01 s [OI=34.60, 0.52 GFlops/s, 0.01 GPts/s]\n",
-      "  * section10<<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>> ran in 0.02 s [OI=45.00, 17.84 GFlops/s]\n",
-      "Performance[mode=advanced] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6, 'i2x0_blk0_size': 8, 'i2y0_blk0_size': 8, 'x0_blk0_size': 8, 'y0_blk0_size': 8}\n",
+      "  * section0 ran in 0.01 s\n",
+      "  * section1 ran in 0.01 s\n",
+      "  * section2 ran in 0.01 s\n",
+      "  * section3 ran in 0.01 s\n",
+      "  * section4 ran in 28.86 s [OI=0.01, 18.20 GFlops/s, 0.16 GPts/s]\n",
+      "  * section5 ran in 9.24 s [OI=3.04, 20.47 GFlops/s, 0.29 GPts/s]\n",
+      "  * section6 ran in 27.52 s [OI=0.01, 10.88 GFlops/s, 0.14 GPts/s]\n",
+      "  * section7 ran in 0.05 s [OI=0.50, 0.08 GFlops/s]\n",
+      "  * section8 ran in 0.47 s [OI=1.19, 0.09 GFlops/s, 0.01 GPts/s]\n",
+      "  * section9 ran in 0.03 s [OI=0.67, 0.57 GFlops/s, 0.04 GPts/s]\n",
+      "  * section10 ran in 0.01 s\n",
+      "  * section11 ran in 0.02 s [OI=1.45, 1.15 GFlops/s]\n",
+      "  * section12 ran in 0.30 s \n",
+      "Performance[mode=advanced] arguments: {'i2x0_blk0_size': 16, 'i2y0_blk0_size': 16, 'nthreads': 6, 'nthreads_nonaffine': 6, 'pthreads': 0}\n",
+      "(ShotID 0) Completing state equation run for shot\n",
       "(ShotID 0) Completed state equation run for shot\n"
      ]
     }
@@ -487,7 +526,7 @@
     "                     p_0=p_0, kappa=kappa, kappa_s=kappa_s,\n",
     "                     chi=chi, r_buckle=r_buckle, r_break=r_break,\n",
     "                     problem=sub_problem, diff_source=True,\n",
-    "                     save_wavefield=True, save_undersampling=20,\n",
+    "                     save_wavefield=True, save_undersampling=20, force_raw_wavefield=True,\n",
     "                     boundary_type='complex_frequency_shift_PML_2',\n",
     "                     num_inner=100)\n",
     "\n",
@@ -512,976 +551,74 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "919bab61b1c84ca38fa95df9d5815dcf",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
        "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\n",
-       "        'matplotlib',\n",
-       "        mpl.mpl_figure_comm\n",
-       "    );\n",
-       "}\n"
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
       ],
       "text/plain": [
-       "<IPython.core.display.Javascript object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "traces_1.plot_one(60, plot=False)\n",
+    "plt.xlabel('time (microseconds)')\n",
+    "plt.ylabel('pressure (Pa)')\n",
+    "plt.subplots_adjust(left=0.2)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fa34a5dd",
+   "metadata": {},
+   "source": [
+    "However, if we subtract the result of the baseline simulation, we will be able to see the non-linear signal generated by the embedded micro-bubble. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "42eb1535",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3b2d35b4e9b64da1abed2de1cfa402bc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
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\" width=\"640\">"
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
       ],
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -1489,9 +626,8 @@
     }
    ],
    "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "traces_1.plot_one(60, plot=False)\n",
+    "traces = traces_1 - traces_0\n",
+    "traces.plot_one(60, plot=False)\n",
     "plt.xlabel('time (microseconds)')\n",
     "plt.ylabel('pressure (Pa)')\n",
     "plt.subplots_adjust(left=0.2)\n",
@@ -1500,4114 +636,296 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fa34a5dd",
+   "id": "d4270928",
    "metadata": {},
    "source": [
-    "However, if we subtract the result of the baseline simulation, we will be able to see the non-linear signal generated by the embedded micro-bubble. "
+    "We can also look at the magnitude spectrum of this signal and compare it with the signal used to excite the source. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "id": "42eb1535",
+   "execution_count": 18,
+   "id": "a5cc35c8",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "15a1e6fa7b51471fac31ef09df821df9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
        "\n",
-       "mpl.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",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "15a1e6fa7b51471fac31ef09df821df9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
        "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from stride.utils import fft\n",
+    "\n",
+    "freq, wavelet_fft = fft.magnitude_spectrum(shot.wavelets.data[0], time.step)\n",
+    "freq, traces_fft = fft.magnitude_spectrum(traces.data[0], time.step)\n",
+    "\n",
+    "plt.figure()\n",
+    "\n",
+    "plt.plot(freq*1e-6, traces_fft, c='r')\n",
+    "plt.plot(freq*1e-6, wavelet_fft, c='k')\n",
+    "\n",
+    "plt.xlim([-0.5, 12])\n",
+    "plt.ylim([-80, 5])\n",
+    "\n",
+    "plt.legend(['recorded', 'emitted'])\n",
+    "\n",
+    "plt.xlabel('frequency (MHz)')\n",
+    "plt.ylabel('magnitude (dB)')\n",
+    "plt.subplots_adjust(left=0.2)\n",
+    "plt.show()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d4f36d7",
+   "metadata": {},
+   "source": [
+    "We can clearly see the excitation of high-order harmonics due to the non-linear behaviour of the bubble.\n",
+    "\n",
+    "Plotting the wavefield using two scales for the incident and scattered field will allow us to visualise this more easily."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "8c9cf787",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f60835ab86204470a475e4dc38dc7198",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
+      "text/html": [
        "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\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": [
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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "traces = traces_1 - traces_0\n",
-    "traces.plot_one(60, plot=False)\n",
-    "plt.xlabel('time (microseconds)')\n",
-    "plt.ylabel('pressure (Pa)')\n",
-    "plt.subplots_adjust(left=0.2)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d4270928",
-   "metadata": {},
-   "source": [
-    "We can also look at the magnitude spectrum of this signal and compare it with the signal used to excite the source. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "a5cc35c8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\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": [
-       "<img 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4t2KCLYHnZ4SAoFCQAQwUEj7px4RQBFA/8ysCChVBNDLQTx+HJNy5sTrFy4gY+rU2H3o0M0k6QmWvG4dTpQsCYbqnAUwZ84ck1RdJgSEQOggIAIYOmPhSUtEAEUAPZk3jnhHBNC7Yb7apg0eHjUKOwG8P2gQOnbqZL/AGzeA++/Hu7t3YwhgkrCvXbtWp4D2EdSTQsDvCIgA+h1iv1YgAigC6NcJFs6FiwB6MXonT2JKxoxoeO0aMqRNiz0HDtg//XNV27UrDg8ciHsTJ8al69exdOlSPPXUU140Sq8KASHgSwREAH2JZuDLEgEUAQz8rAuTGkUAPR+oGxMn4pE33wQzLg8aNMikV3LbNm+mAyBaJ06MMdevo0KFCia3pUwICIHQQEAE8NZxKF++fLyp13w9aswx/Pbbb4P5hT0xEUARQE/mjSPeEQH0fJh/L1UKBdeuRYpkyXD4+HGkTp3as8Ly58c/W7fi/iRJcPXaNWzatAmPPfaYZ2XpLSEgBHyKgAjgrXCeOHHCCNe7fu/uvfdeQ9D45zJvSVv0Gr0tSwRQBNCnPwiRVJgIoIejeewYBmbKhK43bqB6hQqY482pXf/+QPfuqJ4hA74/dgwDBgy4mXjdw9bpNSEgBHyEgAhg/ECKAPpoogWpGOUCDhLwoVCtCKCHo/DxxyjTrBlWAxg3bhyaN2/uYUEAdu4EHngAYxMlQqsbN1C2bFmsXLnS8/L0phAQAj5DIJwJ4I0bNzBkyBAwVSgzRT344IPo0aMHXnzxRaxYscK4nCxcuBCdO3fGtm3bTDpRapL+/PPPaN++PQ4cOIDnnnsOEyZMuKltGv0KmP/3jz/+eAvWy5cvN+VGt169eqF37964fPkyunfvji+//NJc6TJz1eDBg8Fyop8e9uzZE8eOHUPlypVRpkwZ9OvXT1fAPpvRtxYkAugnYMOhWBFAz0bpRLlyyLhqFa4D2Lt3L3LlyuVZQa63ihfH7g0bcB9gMoLwxy9dunTelam3hYAQ8BqB2AggidX58+e9LtuTAlKkSGFbKaBbt2747rvvMGLECOTNm9d8WPJjddGiRWAfSNRKlCiBoUOHGoL38ssvI3v27LjzzjuNX/PZs2fx/PPPo2PHjjd9nKMTQF4HP/7442jatCmaNGliupM+fXrzUUwSt307PaSBVKlSmb969ephz549puxs2bJh5syZhhBu3rzZtG/9+vWGhPIWpHbt2oackjyyrfIB9GS2JPyOCGDCGEXsEyKAHgztv//i66xZUffGDeR/8EFsjvqR86Ck/39lxAigXTs8fNdd2H7xIr755hvzlS4TAkIguAjERgDPnTtnCE0wjKQsZcqUCVbNNmbIkMEElZFUuaxx48aGvJK0kQBGVx4gMevSpQt27tyJ++7j5ygMYSRpIxmjxQwCsXsFzDJJ8vbv32/In8uefvppFCtWzJC+unXr4uTJk1iwYMHNf3/11VdN3SKACQ65Rw+IAHoEW2S8JALowTiOGYP6rVvjCwDvvvuuucLw2g4eBHLkQLsbNzACwBtvvGGuXWRCQAgEF4FwJYAbN240xComWeQ1bKFChczvFgngkSNHkDFjRgPyZ599htatW4Pk0WU8gZs7dy5++eUXrwggP2p5whizPZcuXTKnfdOmTTPt4okjTw9dNnLkSHMKKALon3UgAugfXMOiVBFA94fpWtmyyPzTTzgOGP+XcuXKuV9IbG8UK4bFGzeiMmC+kPmlrNRwvoFWpQgBTxEI1ytgXqfyepe+frzWjW684uWJHAkgT9xc7iaxRdzSd2/WrFkmVSXN0xNAEjxeAW/dutW4uUQ3nqZmyZLFyMuQDIoAejpb3X9PBNB9zCLmDRFAN4fywAGsy5EDvFBJmyYNjh47ZiQRfGItW+LiuHG4J2lSnL961fzg0r9GJgSEQPAQCNcgkDNnzpiTvU8++QT169e/DUBXEIi3BJCBJc2aNUOHDh1u1vHVV1+Z/41tcNmOHTvw0EMPGT9EBrrFZrwC5knf/Pnzb/5znTp1zJWwTgD9swZEAP2Da1iUKgLo5jCNHIkeb7+N9wBzncGvWp8Zr3wbN0b1e+7B98ePY+DAgSY6TyYEhEDwEAhXAkjEGGDBCOBhw4aZaFr+3q9Zs8b4L+bOndsnJ4CVKlVC8uTJMXbsWBM8Qr9D1lG6dGnjX8iPWAaY8O+1117D6tWrTXt43ctgN/ooUvf02Wefxbp161CqVCkTJFKrVi0sXrzYRC0rCMR/818E0H/YhnzJIoBuDlGpUiiydi3oDcPrkoYNG7pZQDyP//47ULAgxt51F1pdvGiulmNKLPiuMpUkBISAHQTCmQCSOI0aNcqQs127dpmr3sKFC6Nr1664HpV5yNsTQJI2nvYx4pf+fKyT1qJFCxPMdvz4cePDx6vkK1eu4L333sOUKVOMxMw999xjAlT69OlzU/x+4sSJ5nm+xwCRJ598UjIwdiaqh8+IAHoIXCS8JgLoxij+8w8O5c4NV/za4cOHkTlzZjcKSODRK1eA1Kmx+9IlycH4DlWVJAS8QiCcCaBXHY+Ql5UJJP6BFAGMkInuSTdEAN1AbehQTOzYEW8CeOKJJ7BhwwY3Xrb5aIkSwPr1eDhrVmw/dEhyMDZh02NCwF8IiAD6C9nAlCsCKAIYmJkWhrWIALoxaKVK4YW1a/EdcPNKw4237T3aqhUwdizaFS6MEb/8IjkYe6jpKSHgNwREAP0GbUAKFgEUAQzIRAvHSkQAbY7a2bO4nDYtMly/Dsa18fSPp4A+t4kTgTffxOICBVB50ybJwfgcYBUoBNxDQATQPbxC7WkRQBHAUJuTIdMeEUCbQ7FoEX6oUgVPAUZagf5/iRMntvmyG49t2gQ8/jgupkqFe65fN4r9koNxAz89KgR8jIAIoI8BDXBxIoAigAGecuFTnQigzbHq0gXvDBqEYQAaNGiAyZMn23zRzceuXjWBILh4EdXKl8e8FSskB+MmhHpcCPgSARFAX6IZ+LJEAEUAAz/rwqRGEUCbA1WqFAquXYvfAXz99ddgfkq/GfN2rluHMQ0bovXkyZKD8RvQKlgIJIyAi0Aw5y317mThhcCFCxdMLuM8efLgrrvuuqXx2v8ARQGH13z2aWu1AGzAefYsLqRLh9TXruEagH/++Qc5c+a08aKHj7RuDYwZg51vvIEHJk5E0qRJjYCrNh8P8dRrQsALBK5duwZmsciUKZPRrZOFFwLUE2S+Y2YsiZmCTvufCGB4zWYft1YLwAagixdjXeXKJv0bNwH6//k1R++kScDrr+MGcw5v24ajR48ahfzixYvbaKweEQJCwNcIHDp0yKQi4/pnRgu/rn9fN96h5VGQmj7UJH8UwM6aNettSGj/EwF06PKwuq0FYGP4u3bF6IED8RZg0hXNmzfPxktePLJ5M1CgAJAqFaqWLo2FixZhzJgxaNmypReF6lUhIAQ8RYBkgh9+nuaj9bRevec9AiR/WbJkiZW0a/8TAfR+hoVxCVoANgavVCk0XLsWUwD07NnTpC3yqzEQJE0a4MIF9GjeHO999BFef/11MEWSTAgIgeAhwOtgpjOThQcCyZIlu+3aN3rLtf+JAIbHTPZTK7UAEgD23DkgXTo8evUq/gAwd+5cVKtWzU+jEa3YUqWAtWsx6+238fyIEShQoAB+Z65gmRAQAkJACPgEAe1/IoA+mUjhWogWQAIjt2QJzlaqhDQAmOL84MGDsfqS+Hz827QBRo3C/saNkfPTT81XLMeK/kcyISAEhIAQ8B4B7X8igN7PojAuQQsggcHr1g2rBgxAOQDZs2fH/v37AzPa1Bls1Ag3ypRB1r/+wr///os1a9agJCViZEJACAgBIeA1Atr/RAC9nkThXIAWQAKjV7o0hq9Zg/YAatasiVmzZgVmuLduBfLnN4Egz5Uti/kLFmDUqFFoTYkYmRAQAkJACHiNgPY/EUCvJ1E4F6AFEM/oRfn/1b16FV8DeO+999CtW7fADPe1a1YgyPnz6NWiBfqOG4eGDRtiEiViZEJACAgBIeA1Atr/RAC9nkT+KKB///5GboR5YO+4445Y5QcoSNyqVSv88MMPRiS4bt26GDp0qHnermkBxIPUkiVApUp4MGlS/HX1KhYuXIjKlSvbhdb758qUAVavxpx27VBz+HDkz58fmykRIxMCQkAICAGvEdD+JwLo9STyRwG9evUy4pX0OZswYcJtBJByBAULFkTGjBkxbNgwUO2cJ0S1a9c2V4V2TQsgHqS6d8ep/v1xd9QjFGTOkCGDXWi9f65tW+DDD3HwzTeRfcIEJE6c2ASCpEyZ0vuyVYIQEAJCwOEIaP8TAQzpJcArv7fffvs2ArhgwQIjR7Jv3z5ky5bN9GHq1Klo1KiRUT5Pw+tDG6YFEA9IZcrgh9Wr8RQA5gHdvXu3DUR9+MjnnwMNGgAMBPn7byNEu3r1apSiRIxMCAgBISAEvEJA+58IoFcTyN8vx0UAKUg8e/bsW7ThTp48ifTp05sr4QoVKthqmhZAHDDR/+/uu/H+lSvoBOCll17C9OnTbWHqs4f++AN49FEgZUpUL18e38+bh5EjR6INJWJkQkAICAEh4BUC2v9EAL2aQP5+OS4C2LRpU+zZsweLFy++pQl33nmnCRSoU6dOrE27dOkS+OcyLoCcOXPi9OnTtk8N/d3nkCh/6VLgmWfwUvLk+PbCBQwePBjvvvtuYJvGjCDU/btyBb3btkWfkSPRoEEDTKZEjEwICAEhIAS8QkAEUATQqwnkzsu9e/dOMI3Yxo0bUbRo0ZvFxkcA9+7di0WLFt3SBAaATJkyBa+++mqsTYurDSKAMeDq0YNhv8iTMiX2nDuHZcuWoWLFiu4Mt2+e5QngH3/g+969Ub13b+TLlw9bKREjEwJCQAgIAa8QEAEUAfRqArnz8rFjx8C/+Iy+ZnfddVeCBNDTK2CdANocsapVcWzhQmSMepzX6wzKCbi9+CIwYwYO9e6NbL17m0AQkvVUqVIFvCmqUAgIASEQSQiIAIoAhvR8TigIhFHCWbNmNX2YNm2aiQRWEIiXQ3rjBpA5MxYdPYoqAPLmzYsdO3Z4WaiHr0edRKJJE2SfN8+kolu1ahXKUCJGJgSEgBAQAh4jIAIoAujx5PHni9T4O3HiBObMmYMhQ4aYTZ/2wAMPmNMflwxM5syZzb/zWUYA16pVSzIw3g4M073lzIn+iRKh+40bRl/xyy+/9LZUz97/6iugXj2gbFnUSJcOc+fOxYgRI9CWEjEyISAEhIAQ8BgBEUARQI8njz9fJJmLzdl/+fLlKF++vKmaJLFly5a3CUEzEMSuaQHEgtTs2UCtWqiVJg1m//cfPvjgA7Rr184upL597pdfgCJFgAwZ0Pett0B9yNdeew2fUyJGJgSEgBAQAh4joP1PBNDjyRMJL2oBxDKKvXoBffsiR4oUOHD+PFauXImyZcsGZ7gpRxPl7zfvyy9RrV49PPzww/jzzz+D0x7VKgSEgBCIEAS0/4kARshU9qwbWgCx4FatGg7NmwfKa4dE0MW99wJ79+LwzJnI+vzzSJQokQkESZ06tWeDrreEgBAQAkLAZFZKmzato2XQEt24Qa93mRMR0AKIZdSzZcP3hw6hOqjD/Ci2bNkS3KlRtSqwcCEwfjxy9O2LAwcO4Mcff0S5cuWC2y7VLgSEgBAIYwS0/+kEMIynr/dN1wKIgeGhQ0C2bOgNoA9goqoZiR1Ua98eGD4caNcOtXbtMhlgguqXGFQwVLkQEAJCwDcIaP8TAfTNTArTUrQAYgzcvHlAtWp4MXVqzDhzJjSI1scfA82aAVWqoF+pUqAGZFAjk8N0rqvZQkAICIHoCGj/EwF09IrQAogx/H37Ar16IX/atNh6+jQWLFiAKlWoBhhEowQQr3tz58a8MWNQrVo1PPbYY9i0aVMQG6WqhYAQEALhjYD2PxHA8J7BXrZeCyAGgLVq4ers2UiRJAmuXLuG3bt3g9lZgmrMHpPRykmya/Nm3P/YY6DUz65VvZkAACAASURBVLlz55AkSZKgNu2WyulKfP06EEptCh101BIhIARCDAHtfyKAITYlA9scLYAYeOfMiR379+MhAClSpMCZM2dMJHDQjQTw2DFc27gRKcuUAVP6/f3337j//vuD3jRD+ugn2b07cOIE8NhjwOOPAwULWn8lS4oUBn+U1AIhIARiIKD9TwTQ0YtCCyDa8B85YlLAzQZQC0ChQoXwC4WYQ8GoQ/jTT8CXX6LAoEHYvHkzvv/+ezz33HPBbd369cBbbwEbN8bdDgqXL1gARMtxHdxGq3YhIASEACQDAxFAR68DEcBow0+plapVMShDBnQ5diy0Ai2aNgU++cScsr28fTu++eYbDB06FB06dAjO/CVZ7twZ+Owzq35qElJAu3p1YPNm4LffgN9/B374AaCY9csvA19/TWHF4LRXtQoBISAEdAJ42xyQDqCDl4UIYLTBHzAA6NYNjfLkweTdu9G3b1/06NEjNGYHZWAoB/PCC+iZLx/69euHxo0b4xOSwkAbfRKLFQN277ZqbtgQGDQIyJLl9pYsXw5UrgxcuQKQrA4dGujWqj4hIASEQKwIaP/TCaCjl4YWQLThf+EF4LvvUDxnTmzYt8+csr344ouhMT+iTieRLx++6tYN9erVQ5kyZbCKEcKBNBK5Z54BfvwRyJPHXEkbH7/4jM+89pr1xMiRQJs2gWyx6hICQkAIiADGMQd0AujgxSECGG3w8+TBjT17kJbBH+fPmwwgzAQSErZnj0W4kiXDr6tXo3CxYsiQIQOOHj0a2Oa1bAmMG2dd+a5dy1Qp9uofOBDo2hVIlAj49lugdm177+kpISAEhICfEND+pxNAP02t8ChWCyBqnI4fBzJkwAEAOcCg1SRGZoVyKyFhjLQl6Tp/Hud+/RWpChUyzSIBJBEMiJH4kQCSxM2ebfn72TVKxLRoYdLZmWCQlSuBJ56w+7aeEwJCQAj4HAHtfyKAPp9U4VSgFkDUaC1daq42l2bNimcOHULevHmxY8eO0BrKwoWBX38FZs1C7jZt8M8//5grYF4F+91WrLCufq9eBXiaxwAQd43v1qoFMNvK008DS5a4W4KeFwJCQAj4DAHtfyKAPptM4ViQFkDUqA0ebEjN6EKF8Navv6JGjRom525IWb16wFdfGQJWeflyLF682ASBMBjEr8ZgD57W8ZS0Th3L74+ngJ7Y3r3AffdZgtGMEi5QwJNS9I4QEAJCwGsEtP+JAHo9icK5AC2AqNF75RVg+nS0KlECY9etQ6dOnTCIka2hZO+9BzAquUEDtE2XDh9++KGRgaEcjN+MV7cVKwI8ASxSxLq6TZHCu+ooCfPNN8DrrwMTJ3pXlt4WAkJACHiIgPY/EUAPp05kvKYFEDWODzwA7NyJigULYvlvv2HSpEloSHmTUDIGT7z0kpFgGdeoEVq2bGmEoCkI7TebNQt4/nmAvpB//mkFonhr69ZZkcN33AHwRDA2+Rhv69D7QkAICIEEEND+JwLo6EWiBQDg1Cng7rvNPMiaKRMOHzmC9evXoxi17kLJtm4F8uc3wSArZs9GhYoVTSo4poTzi126ZEX57txp9BHBE0hfWalSVhQxTzT79vVVqSpHCAgBIWAbAe1/IoC2J0skPqgFAOt6s0IFnMqZE3fv22eG+dSpU0ibNm1oDfnly9b167VrOPzLL8hauLDJU8xo5bv8kWZt2DDgnXesE7q//gJSpfIdHq7TzHvuAYh58uS+K1slCQEhIARsIKD9TwTQxjSJ3Ee0AACMGmXEideVLYuSq1YhW7ZsOHCAgjAhaA89BOzYgRuLF+Pul17C6dOnTV7g/DwZ9KVRXzBvXuD0aWDCBOCNN3xZuhVNzPKpb0hpGKa6kwkBISAEAoiA9j8RwABOt9CrSgsAlj7dRx/hs+eewxvz5uGpp57CUsrChKLVrAnMmWNIa4kvvjBX1dOnT8dL9A30pbkEn6k3uHEjhRF9WbpV1ogRQLt2wCOPAFu2KE+w7xFWiUJACMSDgPY/EUBHLxAtAADly5vUZu8++yyGzJ+P1q1bYxRPBUPRqL9HyZqWLdHo3DlMnjzZ9zmL6WtIeRZKtfB6/Mkn/YPEf/8BOXMC/O/8+UDVqv6pR6UKASEgBGJBQPufCKCjF4YWAIDMmYEjR1C9bFl8v2oVRo8ejVatWoXmvJg8GWjUCChXDoOqVkWXLl1Qt25dfEltPl9ZlSrAokVWurYZM3xVauzl0MeQvoYShvYvzipdCAiB2xDQ/icC6Ohl4fgFEJUCjpMgLyNqd+7EsmXLUJHad6Forkjg5Mkx+/PPUevFF1G4cGH8/PPPvmnt4sVA5cqWRMsffwD33++bcuMqhTIwrOPaNWDTJuCxx/xbn0oXAkJACEQh4Pj9DyKAjl4Mjl8AP/0ElC2LizlzIuWBA7h+/ToOHjyIrFmzhua84LUsI2dPncL2b77Bwy+9hBQpUuDMmTMmIthre/ZZYMECoG1by0cvEPbCC8B331kRx0OGBKJG1SEEhIAQgOP3PxFAZ68Cxy+ATz4xEaibS5dGgdWrjfTLyZMnkcjTVGeBmE7PPWd85q4MHYoUnTvj6tWrJi9wTvrTeWNM+cbTOGb/oOwLxbEDYTNnWtfNOXJYwtC+ILKBaLfqEAJCIKwRcPz+JwIY1vPX68Y7fgEwCnXECEx/9lm8Mn8+ihcvjnXMVBHKNmCAJcz84ot4ZMsWbNu2zeQFfuaZZ7xrdZcuANPfsRxeBQfKLl60/DAZDMJUc2XLBqpm1SMEhICDEXD8/icC6ODZD+65/5lTL+rJpUmTxnlgRAU89K1RA73mzEGjRo3w2WefhTYOP/5oRS5nzYrnixfHrFmzMHLkSLRp08bzdjPrB08Qqf/H61imfwukMS/wpElA8+bAuHGBrFl1CQEh4FAEHL//iQA6dOZHddvxCyB3buCff1DnqacwddkyDB48GO+++25oT4rz5wFmKbl6FV2aN8egjz5CixYtMHbsWM/b/fXXQN26QPbsljhz0qSel+XJm0uWAJUqWf6Nhw4ByZJ5Uor/32GwCkXCM2UC/JF9xf89UA1CQAho/7s5BxLduEGnH5kTEXA0ATx71uTVpRXMnx+/b9mCOXPmoHr16qE/FYoXBzZswJRmzdBw/HhUqFABP/zwg+ftLlcOWLUK6N0b6NXL83I8fZOZQUg+jxwJTU1A/kRSq7B9e5OJxVjGjECuXNbJaZEiRpsR6dN7ioDeEwJCIMAIOHr/i8JaBDDAky6UqnP0Avjf/4AnnsC1TJmQ6r//cPHiRezYsQN5maIs1I1EZPhwbHj+eRSfOdNELTN62SNzScsw2weDMEjEgmFvvQWMHg289hrw+efBaEHsdf75p0X8Fi60/p0BQrF9M9OF4u23rewm6dKFTvvVEiEgBGJFwNH7nwigVoWjF8CUKUDDhthVvDjuX78ed9xxB86dO4ekgb7+9GQaUqD5xRdxOl8+pKNeH6gMc8r4c7ptLuJFvz/6/wXL1qwBSpcGUqUC/v0XSJEiWC2x6uVVO4NtSEp5QslraRI8/m+8Ct63z7gPmCvzTz+1dAxpHAMSRj7rRL/a4I6aahcCthFw9P4nAmh7nkTsg45eAFFRr/OffRbPzZ+P/PnzY/PmzeEx1ocPmyAQnkZly5wZhw4fNnmBixUr5l77eQ3OEz9G4DLy19tIYvdqv/Vpnqrdd59FqKZPB3yd39jdtjVuDEyYYL1VowYwdCgQ1+kw9RlJnnmFzhNV2r33WtfGzHUsEwJCIOQQcPT+JwIYcvPRNGjPnj3o16+f8ek6fPgwsmXLhtdeew3dunUzp1Quo/YbU5bxueTJk5uUYEOHDr3lmYR66OgFUKsWMHs2Rr7wAt6eMQO1a9fGDH+nPktoQNz5d2r27dqFio8/juW//45JkyahYcOG7pQAROkgGs2/7duDr8HnkqLh2FAfMFj266+WXx9JqTtR0SSC33wDMGcziSyvgmfN8l8+5WDho3qFQAQg4Oj9TwQwNGfwwoULMW3aNNSpUwcPPPAAtmzZgiZNmqB+/fqG4NGuXbuGggULImPGjBg2bBiOHz9uNn+SmFGjRtnumKMXwIMPGsHjNrVqYdSsWejYsSPef/9929gF/cEGDYyvXMsiRTDu55/RuXNnDBw40H6zSG5Ickh2mIGDmTiCbbxGffxxKxUdr4GD4UtHXCizQ01CRkZ7kmeZcjo8NaSmJPtCaSGWJRMCQiBkEHD0/icCGDLzMMGGDBkyBOPGjcOuXbvMswsWLEC1atWwb98+c0JImzp1qtGxO3LkiG1NP8cuAOre0cfs+nU8V7Ei5v/wA8aPH4+mTZsmOBYh88D48UY374P770eHnTvx8ssvmw8H28b8wUWLAnfeaUmbUIIl2EbyxXzAvEadOBGgPmCgLcq/EsmTW6einmZYuXABqF8fcJ0q9+8P8IQzlLPMBBpr1ScEgoiAY/e/aJgrCjiIE9Bu1d27dwdPBv/HyFUAPXv2xOzZs/H777/fLIIpzNKnT2+uhCkLEptdunQJ/HMZFwBTiDlOCHrLFotopE2Lh7Nkwfbt27F06VI89dRTdock+M9F9WH2HXeg1uXLKFKkyM35YatxHTtafm30taPPXagYiVL37sDTTwPUBwykMSsJffZ4fduzJ9Cnj3e180qYOH/wgVUOr4bdOaX1rna9LQSEQDwIiAACIoAhvkR27tyJwoULm6vexnRMB9PXNjW+gkwBFt3uvPNO4wvG6+PYrHfv3ugTy6bmOAJIwvPKK7hWvDiS//ILrly5gt27d+NeOu6Hi5Fc3HMPtpw6hcfA29J0Jo+xLeNJG/vKKFaeUDEXb6jYzp1WHmLmBN62Le7AC3+0l6nweErHU3Xq/aVM6Zta6JbhytTy7bfACy/4plyVIgSEgMcIiACKAHo8edx9MS7yFb2cjRs3oiiv5aKM2m5PPvmk+fuUUhNRRgK4d+9eLFq06JZmMEhkypQpePXVV2Ntnk4Ao2AhCe7dG3tffhn3Tp+OZMmS4cKFC0hCLbxwsmefxbkFC5Aqqs0nTpzA3XffnXAP1q4FSpWyJFcovszrzlCy556zImgDKU3DyGpG+TIymhJBvL71pblOXCk+vnEj8NBDvixdZQkBIeAmAiKAIoBuThnPHz927Bj4F5/xBOquqBRTJH+8yi1evLg51UvME5Eo8/QKOGbdjl0AJMjTpuGHZs3w1PjxRvyZItBhZ1HXpVnvuguHL15EzA+IOPvTti3w4YdAvXrAF1+EXrfpA1iggPHRBHMfM1OJv80l+/LEE1bwRrT15pOqqSXIa232J18+YP16i4DLhIAQCAoCjt3/oqGtK+CgTL34Kz1w4IAhf/Tr+uKLL247mXIFgezfv99kgaAxAICRwAoCsTGgJBebN+OT1q3RdPRoVKlSxQTWhJ2tWAFUqIDSyZJhzZUrZg4wGCReo4gxAxuYc3fOHCBUU981bw4w0IUn4iRLviZk0UGimHb+/Jbsy+rV1umoP4ynjIULW9i/8grAHMwKCvEH0ipTCCSIgAigTgATnCSBfsB17ZsrVy5znRv9WjJLliymOS4ZmMyZM4MRwrz6YwRwLUqaSAYmYQJE365Ll9C5WTMMHj8erVu3dgu3QM+JOOtjtoq0adHg6lUwedqAAQPQhT5s8RlPoChzQokVEhJGAYeiUQaGV7Jnzlip4Zgizl/mCjx59llg3jx/1WKVS4JJ/HkiOGIEwNNYmRAQAgFHQARQBDDgky6hCnnd+3oc8hc3ouUgpRB0y5YtbxOCZiCIXXPkAvj7b4tYJE+Ol559Ft/OmIHhw4fjbabuCkcrVgy9N24E41UZJPQJxZ3js5YtgXHjLIkVSq2EsjFitmtXIEcOS5LFX+nhSMhIjMeOBVq08D8ivH4n8WPawZ9+AooX93+dqkEICIFbEHDk/hdjDugK2MGLwpELgNeeNWsCBQuiEIDffvsNc+bMQfVQvQpNaH526IDPP/gADcDb4ArmgyBO46kTI1wpVLxwIVC5ckKlB/ffqaX38MNWtPJ771l5eH1tDPpInx64csUIg5sIZH8bP+QYqU/dxoIFAco7hVsAkr8xUvlCwM8IOHL/EwH086wKo+IduQAGDzZ6bDfq1EHa77/HmTNnsHXrVuSjY3442pYtWPPYYygNIFf27Ni7f3/cvaCuXqVKlugz/dCSJQv9Hn/1lRWswoAJErQoNwifNZzRxow6piwOhdYD5ZNHEs5sNKdOAaNHA61a+axLKkgICIGEEXDk/icCmPDEcMoTjlwAjRoBkyfjaOfOyETdNwDnz583+ZTD1Q6XLYusP/2ERAAuXroUdz5oV6QrM54wwCIcjJHAJUpY0ikcO15b+5KktWtn+eI1aQJ8/HFgEeGVM4kf/TEZhZ4xY2DrV21CwMEIOHL/EwF08IyP0XVHLoBixQyZWDdgAEp27YocOXKYlHrhbDfmzEGqmjVxHsD2X3/Fg7xWjGmXL1unZxSL5jVxHNliQhIH+smVLWs1jaS9UyffNZPRv5SdoTg4s6IE0hiRTdkZ5mN+800gmtZnIJuhuoSAExFw5P4nAujEqR57nx23AOh7lTatiSz9cvBgvNapkxHZXkE5lXC269fxWPLk2HL5Mha0aoUqvFKMaa6rTpJAXhOHm8/ZsGHAO+9YvWKgS1RWHK+G7eBBIHt260SRV7LByIfsEuVmR6g/qIAQr4ZULwsBuwg4bv+LBRgFgdidLRH4nOMWwIEDVkRp0qTo06ULevfrhzfeeAMTJkwI+9GtVaAAZm/ejNGZM6MViU1M3byGDa0MF61bA25IBYUUMJS44Qkg+/bNN96nsKO8TIMGQJEiViBGsIwR2ZMmWe2g5mG4kfNg4aZ6hYAXCDhu/xMB9GK2ROCrjlsAK1cCTz4J3H8/GpQqhc8//xz9+/dHV0qNhLl1eOstfDB6NNoB+CBmhC8lTqpWBRhVu2oVUKZMePaWJ7j0X+RV6R13ABTvrljR876Q/JEEdu4MUHImWEbNQ6aGO30a+OgjoFmzYLVE9QoBxyDguP1PBNAxc9tWRx23ACZPtgIJnnkGpc+dw5o1azB16lS8wqwMYW5jxowxgtY1Acwi2eOVL23pUqBGDYv8ValiCR37M6uGv3GklA3H67vvrMhgkltm13DXSCZ5/cto6GXLvCOS7tYd2/MubUBK0jDamf+VCQEh4DcEHLf/iQD6bS6FZcGOWwC9egF9+5pTpCyzZ+Pff//F//73P5NyL9xt4cKFqFq1KvID2MzObNsG7N4N1Kplsp6YE0CSpqhc02Hd34sXLekWBrPwBJAEzl3bsgV47DEjCG4CY9wQUHe3KlvPk9gyeIcBKf7SPLTVED0kBJyBgOP2PxFAZ0xsu7103AKoXx/44guc7dMHqUkGwb3/JNJRhiPMbceOHXjooYeQIkkSnL12DYlKl7akUxj9S+Frig4Hm+T4EuM9e4A8eawADgpF07fTHRs+HGjf3hLD5pV5KNgXXwCcowzUYf8iabxCAV+1QQhEQ8Bx+58IoOZ/dAQctwDo+7Z6NTYNGYLHO3ZE+vTpcfz48YiYFJcvXzZahtevX8chAFbWaAAvvghQTDkcRJ/dHYly5SyfRop7v/uue28z7y99CIcM+f/oYvdK8P3TzEZCUstgJeodxpES0vcVq0Qh4DwEHLf/iQA6b5LH12PHLQCmQTt0CN8NHowXOnXCE088gQ0bNkTMpLj33nuxd+9e/PTAAyjNnMd16xrRa5NzNhKNcjAMCqGW36ZN9gWieSVOH7vz55kLEHj88dBBh4SUZPbRR4HNm+33yd894Ckr9QqJl+vvzBnr2pouFEWLWn/MqOJLoW5/90vlOxYBx+1/IoCOneuxdtxRC4BBEClSGByG9O6Nd3v3xquvvoqvv/46YiZFxYoVsXz5ckwZNgz1c+a0ZFIiWVKEadR4XUpCR3ISmwB2bKPLwJHy5YFMmawgkFAKimGfOHbMUcwTSgbuBNP++88i2XQhsGMk4/zo8CQwx075ekYI+AgBR+1/cWAmHUAfTaZwLMZRC+DPPwHm+02bFs1feQXjP/4Y3bp1w3t0uI8Qa9KkCT799FP06tULvXv3jpBeJdANZu/49lvLn49i0Xase3egf3/rhPTLL+28Edhn2Bf6KD79NMD8zcEykmriu3On9SHBoBmelpJo8y9NGuCXX4Cff7Z0FHkKS59Tnjj36WNlbInkD5BgjYvq9QkCjtr/RAB9MmciqhBHLQDKn1SrZjauZzJkwNKlS/HZZ5+hEWVhIsQGDhxoNA3r16+PKRR9doLNmWMFufAkkCn97Fx3M9sGr/4/+8ySBQo127vXaFWCqeLcOdn0VT8okcNc0W+/bZ2u5splpcpLKEsJ/WmbN7cIOa1UKUtn8b77fNUylSMEfIaAo/Y/EUCfzZuIKchRC4DZL9q0Mdei9/36K3bv3o2VK1eirCvHbASM6vTp042mYalSpbB69eoI6JGNLvDEib6dJB8xBbBje51iy/T/u37dSolHLcBQtFdfta5dGRUcSDJPV4k33gCmTrVQqV7dylJiV5eQ5JGkjxln6CNIrUZm2nn55VBEWW1yMAKO2v9EAB080+PouqMWQNS12uV27ZB85EgTLXvgwAFkI3mIEPv5559RtGhRZMmSBYfo2+YUI9kYMwaoV8/I/MRrFMZ+5hkr2nbXrtBFiFeqTzxhnWhSz9FdmRtPe8Zr2/fft+pl2j2uG0+COihjw0wrjNJmWd9/b0nuyIRAiCDgqP1PBDBEZl0INcNRC4CCyLNn469evfBgnz5GMuXcuXNI5MnmFkJjGL0p1DSktA3t7NmzSJkyZYi21MfNYv7cEiWsIB+mVeOpU1w2YADQrRvAE7ZQDwBi2kKmL2RUMKVu/G0kmg8/bPnxzZjhfa5lXmEzBzX9LDkm7EuhQv7uhcoXArYQcNT+JwJoa07cfOj06dOYOXMmVq1ahT179uD8+fPImDEjChUqhMqVK5trtnA3Ry2AAgWMrMbCfv1QtUcPPProo9jCbBARZiSAJIKbNm3CY3Tad4Lx2pG5dJlCjRGoPHmKy+gvSL/BDz4A2jFzcgjb3LlWGj8KlR8+7H9haKbYo68fg08WL/bs5C8mnCSTzELDrC1ZswJr1wK5c4cw6GqaUxBw1P4nAmhvWvPqrGfPnvjyyy/NVVqxYsWQPXt2c2J04sQJQxp41ZY7d24TbRnOeWQdswBIEBixePYsxvTsidZ9+6JmzZqYNWuWvUkRRk/xCpjzk31jHx1jTPHH7C7xRc5yHpCE8JTwp58AZksJZaOfIn0USf4WLQIqVfJfa9essfDgiTh1/vjB5Cuj3yVF2PnB9cgjRowdd9/tq9JVjhDwCAHH7H/xoCMZmBjgZMqUCQ0aNDDRofmpaRWLXbhwwWywI0aMwEsvvYR33nnHowkY7JccswCOHrU03xIlQvu33sLwDz9E+/btMcyubEiwB8qN+vlBwmAQ9o19dIzRn4+RsyQwjAaOLbiD/zsjWilNQn27KF3IkMaIGnwUvG7VChg92j9NJTEuWRLgVfqbbwKffur7eog962CWE2Zw4QmjUt35HmeVaBsBx+x/IoC25wSOHj1qrnrtmrvP2y03EM85ZgG4fMRy5EDNwoUxZ84cjBkzBi1btgwEzAGto0uXLhg0aBBatWqF0f4iDAHtkRuVRaX6Mxp6lDCJafRrY2o8+qFRvy4czCVfRHFoysP4w2eVEb916gD0GeU1Ok9J/WHUCWTUPck31x4Dd2RCIEgIOGb/EwEM0gwL8WodswDo7E/R33Ll8OixY/jjjz+wcOFC48sZaUYhaApCV6lSBQuYScJJRr++Dh2sKF+eMMU0V4Rrs2bARx+FBzKUZcmQwUpb5w9NQJbPwA+meuvXD6BItj+NV9mu7CbLlgEVK/qzNpUtBOJEwDH7nwigZ6vg+PHjuOeee8zL+/btwyeffAJe/9aoUSMi9OMcswCiIj+vN2iAlNOn4+LFi/jrr7/wwAMPeDYxQvgtpoJjSri8efNix44dIdxSPzTNle3ljjuAEyesE63oVqECsGKFpUtHrbtwseefB+ivyuwaPXv6ttWUeunSxZKZ2b49MNfiPP0bN87KG8x8x/FFbfu2typNCNxEwDH7nwige7N+8+bNqF69uiF93EinTp1qTlQoG5I4cWLz32+//Ra1KC0SxuaYBdC4sdn0D3TogBzDhiFJkiSGyCdLliyMRy/2pu/duxf33nuv6Rv7yL46xujLRn0/XpUygpaZX1xGSRJG0zLHLklHHP69IYkVM5aQsBYpYqVc85WdPGlF5FKwmeLNr73mq5LjL4f1MUKd49SiBTB2bGDqVS1CIBoCjtn/RADdm/dVq1ZF0qRJ0alTJ3zxxRf4/vvvUalSJZNnlfbWW2+ZSMt169a5V3CIPe2YBcBrpuXLsbpHD5Tp188QJGYCiUS7du2aiVi/cuWKkS9itLqjjISC17sxfcy2brVIH08FGZUaTsT4yBEr1R0JLoMpfCUK7XKN4BUw8UmcOHBThbIwTz1l1aer4MDhrppuIuCY/U8E0L1ZnyFDBvzwww8oUKCAEdRNkyYNNmzYYLIs0LZt24YSJUrg1KlT7hUcYk87ZgHwVGjPHnzVsyfq9e2L8uXLg1elkWoPPvigueJetmyZuQ52lLlyA3PMd+78/6AJ1ykaxZV5DRxuRokWSrXw6pT5dn1hr79upXnr2NHK/hFo01VwoBFXfdEQcMz+JwLo3rznNe/hw4dBSRha6tSp8fvvv+O+qKTm//77r0khxtOWcDZHLIArV4C77jK5Xwd07oxugwYZiZ/PSAgi1OiusGjRIkyYMAFvhJOvmy/Gg1e89NulAPG2bZZANM11MhgssuNt35gJpHNnS1R5/nxvS7NOE3mSePAgsGSJpZ8YaNNVcKARV30igLfMAekAxrIkSABJ8lxyMCSA8rjXbgAAIABJREFUzKyQh6cKoI6sCGDY/JLwFIjBHnfdhaavvYZPPv3UCHj37t07bLrgbkObN2+O8ePHo0ePHuhLgWSnGckMrxWjy8HQf47SL998Y0nBhJtFD3A5ftz7wAnXlTg/jugLyP8Gw6JfBf/4o6URKBMCAUDAEQcgCeAoAhgHAaQf4J1RQqVz5841V2mu3KqXLl0yMiI6AfTTKqXP04YN///HzAQvvOCZbtjSpZYsyCOPoFKOHFiyZIk5/eMpYKQadQCpB1i/fn1MmTIlUrsZd78o8E1xdmbOoOwIpU6YCebqVSvwgGLQ4WY8sXvwQeDvv32Tp3fECCsVngujYOJBWZ6PPwYKFwY2bgysL2Iw+626g4qACCAgAhjLFHydvjE2LNyvEUNuATD11bPPWpt2bMagm+LFbYxMtEe4sXCDee45PLhjh/GNo/8f/QAj1Ri1XqdOHSNVtHLlykjtZtz9+uMP4NFHrUwTlIPhBwR96BhIwStPf4gpBwJlahxS67BhQ8t3zxvjOqNO5NChlnZiMI0ffHnzWgLRCeVyDmY7VXdEIRBy+18Q0BUBDALooVJlyC2AhQstHydu0MwZWqyY9cdTvO++iz/Pa1yg0m9q8GBcb90ayT/+GJcvXzYRwIwEjlRbv369CVLKmTMn/qHAr9OMp2UcX/b9+++t7BY87apRA5g9O3zR4BUpP1zo48h8xp5GMl+6ZOXi5ckos3NQkiXYxiAUCnUzhR/1CGNqOAa7fao/4hAIuf0vCAiLAAYB9FCpMuQWgOtUgps1TzpctmePdf3FgA5G77pzevfKK8D06TjYqxey9+ljdPEoBE2Zn0g1+qhmyZLFaFZSC/AOCiM7zRgpO368lUOXp4CUPHnvPaBbt/BFglfYDEyjz96qVQBT33liXEOMDg+lE9GLF62PPq51fwhee4KT3oloBEJu/wsC2iKAMUCvXbu27WH4jqdSfjBmGvntt99w5MgR3H333Xj66acxePBgE3nsMp7sMN8r5Wqo+1a3bl0MHTrUrc0+pBYAs1YwYpOnfzyxuf/+W5HlRk7B2FKlgJ9+sn+N98QTRjx3zaBBKN25s9HFoz5eJNuNGzeQIkUKQ3R37tx5M3o9kvt8W9940keh9qjIfezaZaWHoz9oOFv9+sAXX3gn3cLMH8wAwrJCyUd0+nSAH2wpUli/AdF+78J5yNT20EQgpPa/IEEkAhgD+Oj+f9xIZ86cibRp097UAKQANPX/SBT95QM4fPhwlCxZElmzZsWBAwfwDh3aQRmwNea/DD4pWLCgiVIeNmwYmLKuYcOGpk2jRo2yPZVCagG0aQOw7dWrA9Ryi2n03SIp5EnBvHmWr6Ad43XZiRP4auBA1OvSBU8++SRWhKMOnJ2+RnvmkUceMXqVjtQCJA6UGOHY89TYZTwJ5NVnONu0acCrr1oBEz//7FlPXBHRgcz+YaelvLqnr+batVbmE6bskwkBPyEQUvufn/qYULEigPEgxEwgJ06cwEcffXQzpRbJV8uWLY049JAhQxLC1yf/PmfOHJN2jtHHTPG1YMECVKtWzaSqc50K0vGfka08NWTb7FjILABmZqAmGTXc4tMko4YbndYLFbJSYiWUuYDlMv0XgIG9eqFrnz6GKE/y1oHeDrhBfoZR7IxUd6QWoAt7ZpqgzAiNLgT0LQt3c52U85SMJDehNRCzv0ePApkzWzqAhw5Z18ChZAz0KlnSOuGnbE/BgqHUOrUlghAImf0viJiKAMYDPk/YfvrpJzzkEpONenb79u0oVaqUOXnzt5GAtmjRwpwEsi20nj17Yvbs2Uac2mUnT55E+vTpzZVwBSa9t2EhswBGjgTefhvIlw/YsiXu691jx6wrPW58dvTcGP1JspgxI5o9/zw+/vjjiNcAdA075ww/XByrBUgg+LHAjwYa89zyxCvcjX6ADJCg0DVdGdxN9Td1KlCnDlCgABDt9yOkYKlb1/LZ5O8Y9RzDNWo7pEBVY2IiEDL7XxCHRgQwHvDpf8drXp6+RbdZs2aBV8UkXf4ynj6OHj0a58+fNxGdzEd8D6+0ADRt2tT4sS2mT1M0o24hT7coARKb8QSRfy7jAmCk6OnTp22fGvq8v5R+4ekMBZuZw5WSLfEZBZzpJM78pSSL8UVC0keT+oHFi6Ny2rQGr0jXAHRBR5/Rzp07O1cLkEC4xI75f3/4IZN4+3z6BqVA5jRm3yjjUqWKe03g1Sqz4NCtJEA3GO41EJZWIz+6+VvFKO7nnnO7CL0gBBJCQARQOoDxzpH27dsbQtW1a1dDwmjr1q0DhXYbNGiAD6JHqiYw25h5og+JSzy2cePGm76Gx44dM9fPe/fuNe/RD5EkMFGiRIYA8n9nuq/oxmhPCv++Sh+hWCyuNgSVANKfr1o166p2//6E5R+oFcaMLPTnSkgzzCUI/OqreOiXX7Bjxw63TkgT+gEJ5X+fNm2amQeO1QLk4PCak0SCAQU87eKpVyQYM5nMmGFFyjNi3q4Rj5w5gQMHQj8ghpIwlIahniPHzlPJG7vY6DnHISACKAIY76S/fv26iawdOXIkDtFfBjCBGW3btkWHDh1u+gXaWTkkdPyLz6hNd1csKZn2799vTuoYBMLgEE+vgEPyBLByZWszcudEYsAAS86DEZ0xTkFvwTcqcvh6ly5I8cEH5vRz165dN1P62Rm3cH3G8VqAroFj5gzqAVL2JFKsRw9L0qZJEyuDhl1zpZOjQDZvL5Int/tm4J9j+xj0xf8yGCRYOa1Jmr25gt692/qN4h+DdpjqjukZI1iHNPCTxbMaRQBFAG3PHE4Wmt0AC9sF23iQwR65cuW6mcHCFQRCYkhCSuOJDwMcwioIxLUh0ZGdV8B2fxR59UvxWjrCc4OIS+eOotILF+LQ0KHI9s47RheP0igMpIl0kxZgBI/wV18B9epZOoDUA7RrLl/bhD6c7Jbn7+d4wsksJRSHZvAL13sgjFfPVCKYONESoWcucUYnu/6YtSQuUkj/ZOosukgfT59jGn+vWra0PmIzZAhEj1RHLAiIAIoAhtzC2LBhA/hXpkwZowHIEyue+PEEcuvWrSY/sUsGJnPmzCYSmVfFjACmr2JYycC4tP3oYzlzpv2xoN8gIxl5orp6taUNGJvRt/Cvv7D2ww9Rqk0bQ6J5de4EkxZgBI/yr79aMjAkD4zqtWv0pZs/3/L9i5KWsvtqUJ4jEeMVPtcsT/2pX+hPo1/lJ59YOovxBfilT2+dTvKDlX8ulxSSPkp1MVDHZRScZ1Qzcy7TBYG+qAxsoaVObWU/efddwAEfpf4cOk/KFgEUAbxt3lSpUsUQLkb5xmdnzpzB2LFjkSpVKiPI7CvbvHmzuWJmhO+5c+fMCR/b1L17d2Tnl3CUUQiacjQxhaBJEO1a0BcAfzgZychNiad17pjLD6p/f6Br19vfpD8h/Z0SJcLXH32Eus2aoVy5cviR6bQcYo7XAozUcT5/HkiVyvJxJAG0c4rEZykPRaklEshwkVf58ksrgptt5y2Bnb56Mu78XXj66f8nb/ytbdQIeOkly4WAH5r827jRCk6Jz3hiSMLHP0Yyx5TlotQViR/HgUYNVJ7OygKKQND3v4D2NvbKFAUcAxfqpvXq1QupU6cGM3IULVrUaO3RN49Rv3/88YeRY5k/f77R4uMJHP3zwtGCugAYxBEV1WyucaP0+mzjOGYM0Lp13H6A9I1iRHHJkhhUowa6dOliAncmM3DEISYtwAgeaNfH08qVQNmyCXc0+npjDuBYfI0TLiQIT/C0v2hRiyy1bQuMGOH7RvDEjnJRdC158kmLnJG8xRZ4QvJH1xV+uPKPPn7847UuCSTfc2Wfia+l7BevmOnHyetkSnwlcOjg+447u8Sg7n8hAr0IYCwDcfnyZXz77bfGr27VqlUm8weNEbj58uVD5cqV0aRJk9v0AUNkTG03I6gLgNcg/MHkjyW/7N01l8RHXH6AvFZmOrB+/dB8/36MHz/enOwmFIntbjNC+XlpAYby6HjZtij/VpPvuGnThAvbtAl4/HH3r40TLtn/T9APj36LvCbdts0ewXKnVa6PSX6Q0teQV7yBstdfByhMT1krktxwIeaBwseP9QR1//Njv9wpWgTQBlqUSblw4YLR4YukAIKgLgD6IdH3hVe5FHV213illSmT5QfIr2c6aLuMX+n8MT93zmQTqNKli5HMmThxotFvdIpJCzCCR7p9e2D4cEtAnf9NyKgZyPSJJIEUSA83o94hZa8ocUWRaF8Zff0Y1MFbCOYab9HCVyXbK4cnsxTA//dfKyiE0d2ygCAQ1P0vID1MuBIRwIQxitgngroA+EPOvKYDBwKdO3uGMf1zvv3W+tHkj6fL6IxNeRkmk9+/Hw8/8giYvcWdLCmeNSi03pIWYGiNh09bw2AFnvxxni9cmHDRn35qXTeSBFJ7M9yMWoD0W+R16R9/WCdmvjBG444bZwVoMPVcMPQGXYL1rJspLsPFP9MX+AexjKDuf0Hsd/SqRQBDZCCC0YygLoCoCF3zVU+/GU+MX+wMwGHOV14TuYy+Qoy2a9wYNz7+GClSpDDyL07RAHTBIC1ATyZVmLzDU2/6/uXKZUXJJmQUoWcWHXe1AxMqN5D/XrOmJc9CTUBqA3prJJWMpqY/3ooVlv9fsMz1MUtfxPXrFRUcgHEI6v4XgP7ZqUIE0A5KEfpM0BYANRXTprVQPXLE5Or1yHgSwEwBFLTlFQ4joHk1zCsd+hXOnInDJUqYSGonaQC6sHRpAdJ3lQSYmWJkEYIAry5dEbHUnmNUcHxG4sdTQBLBnj3DE4R16yxJFfoC7toF5MjheT/4O8EIXUb/knxNn+55Wb548/Bh6yqYv2Pe3Ir4oi0OKSNo+18I4SsCGEKDEeimBG0BMHKRX9uMnqbEgqfGH3HqAVIKg4K4FMbdvt26HuImcfw41m3darKnMFKb0jlOsuhagH///Tfup3aZLHIQoA8s5z4zTPAkKz7j1S/9AEkC33wzfDEgaeNpnV3fx7h6SsL3yivWxyOjenPnDj4mU6YADRtaH7JsEyO9ZX5DIGj7n9965H7BIoDuYxYxbwRtAVDKgTlM3RWAjg35l1+2gkiYXokpslzZAxhhvGQJpk6dijp16jg2J65LC3Dp0qV4ilflsshBgGnF+OFD4WJmBonPGPzBSGCSQAZUhKu5/HsZ/c+rb090AS9ftm4J+EHIa/FevUIDDX7QMmUhCa47qTFDo/Vh14qg7X8hhJQIYAKDQQkYSsLs3LkTHTt2RPr06fHLL7+AWTiiCzOH0JjabkrQFkD9+tam5SJttlscy4N04KYjN384XdIy/G9UhOSgQYOMBmD9+vUxhV/YDjOXFuCnn36KN8P55Mdh42aru9S5pN6lnehRRsUz4nTzZiB/flvFh+RDJElFiliSKbzK5pW2u0Y/QvoT8gSVGn6BSjFnp51z5wI1alhSNBSzD+V8zXb6E8LPBG3/CyFMRADjGYxNmzbh6aefRtq0abFnzx4TSXrfffehR48eJqVYuBOKoC0A+u3Rf+/77wGmp/LGXPmEqZ+1b58V+XvliqXnlTcvnK6F5+o/M8n069fPG6T1bqgh4DpJr10bmDEj7tZR+NlFckgC77471HriXnt44s+Tf/aDp4BMqeaOubIIUUpn2DB33vT/s9euWWnm2C8KRTtItsr/4N5aQ9D2v0B3NJ76RADjAYfkr3Dhwnj//fdNZhCmZyMBXLNmDerWrWtIYThbUBYAtfmYGomRdwcPAlmzegchTwRYBnW06BfETZGpmKKSsDs9G4ZLC/C1117D559/7h3Weju0EGAEPa9zH3nE+qCKyxgQxTXB0ySuP0qphLORJDFggh95Q4cCHTrY7w2DLLJkAXgNHKop8QYPtqSxeNLJ1HPhPl72RyegTwZl/wtoDxOuTAQwHox48sfrXjrPRyeAPP176KGHTGRlOFtQFsDatVbKI5I2EkBfmEtTkIEfPP2LljLK6flwXVqAZcqUMVltZBGEAH3YGLyQNCnA/MCc/7EZI13Ll7f83kiaIsEoA9O4sXXiz4hguznQmTmleXPgsccAysCEIrmiuD0jnCloz8jn4sUjYcRCrg9B2f9CDAURwHgGhH5+CxcuRKFChW4hgIsXLzb+VPt45RjGFpQFMHo08NZb1tUvr4B9YR99dKuCPx3Fn3kG0aNg6cPJ01unmUsLMEeOHGE/X502dgn2l6foPE3nqR5dIeISR/7qKytIhCRw+fIEiw2LB0iOuJ75EUk/SMrc2DEqBaxeDbz/PtCxo503gvMMo4Hps0x/aQf6LgcC9KDsf4HomBt1iADGA1bTpk1x9OhRTJ8+3QR/0CcwSZIkqFWrFsqVK4cR/khM7sbgeftoUBYARVw/+8yK2GUQiC+M+UF5DUZLmdLIv/BEwKWDRw1ApvJzog6etAB9McFCuAxeEzKDxcyZVlR9bOZKu0gSyOCrSDFXxD+JL3ODJ04cf89cV+F8zuUvHKpYbNhgnfxRu5PBIJ5qpYZq/0KgXUHZ/0Kg39GbIAIYz4Bwgjz77LPYunUrzpw5g2zZsuHw4cNGV27+/PlISbIRxhaUBcA0R7x6iW/DchdT+gHyKohiqozumzXLlKBMGNTFvnEzE4q0AN2dWGHw/GuvAV9+CQwYAHTpEnuD6Rs7cqSVe5v+ZZFiFJTnVSmFsO3I27iyoTzzDMBbglC3J56wUsNJGNovIxWU/c8vPfG8UBFAG9gxhyx9Aa9fv26CQhgcEgkW8AVAn0lG7F29amlwUQjaV0a/Hvr3MFE8fQLBVMPT8OqrrzpWA9AFrbQAfTXJQrCc/v2B7t3jvyp0Rb0yPSLdLyLJqCfKm5iEciJHzxDEYCgS51C3SZOsKGD6efL0Mhh5ikMdIy/aF/D9z4u2+utVEUB/IRsG5QZ8AfBrll+1FG9lCjhfOmDTD4rXQMWK3UReEbAWFNICDIPF6GkTv/sOeOEFoGhRK2I0NmP6NAYTUCqGkjGRZAwAYYQzCR7XP6ODY7M1a4DSpS0XESoGhMPtDeV7eMJJ6Z7Zsy19QJnPEAj4/uezlvuuIBHAGFh+yK9km9amTRubT4bmYwFfAK4IvEqVAEpY+NlatmyJcePGwekaeNIC9PNEC2bxLh1M5gLmlWhsH1W5clk+b5EaUfr885bbB4WxGRAWm7VoYf1bgwbA5MnBHDH36u7UyQpYCZdra/d6F9SnA77/BbW3sVcuAhgDlzwx8i8yCOT8+fNIly6deZKZQVKkSIFMmTJhF78+w9gCvgBcmQuocUW/Fj8b/TcXLFgAp2fB0EmonydaMIun7BFFnuNyq6BmHiVS+F8GE2TPHszW+qdul8wNdQ5JdJn1JLoxYpiyU9QAXLIECCcXHmYqcakX8OSS2UuCYYw4p9Ykb26Io+uPc6tatf9vY3xtowvQoUNW5DZPNxmRTQH/IFnA978g9TO+akUA40Hnq6++wtixYzFhwgSj+0djNpAmTZqgWbNmqJdQ/s0QHPDoTQr4AnA5NVPJn35JfrZ8+fLhzz//hNPz4DKK/ZVXXoG0AP084YJVPKNgt2+3TtV5uh7duOEyQIqRryRC1AyMNOP1b+HCwG+/xR4w4bomJ/llho1w86VzBc5F828O6BBSZYFpJHmNHpcR/5desv4yZ7bGgkLbjFDn/02fb15lRzfuB/PmBS3COeD7X0AHzV5lIoDx4EQBaOYBpg5gdPv555/x4osvYje/zsLYAroAeFLBayoq8NOhOQCafDy1PX36NLZt23aTwIfxcHnc9A0bNqB48eKQFqDHEIb2i64rUAZDUAQ9urn8bkkCDxwI7X540zpq5VE7jySPv8suUWyemlEZYP368I2CfucdK2UdSdinn3qDknvv8jebmVYYPc2PB56w8oaMKfj4x1sxnuatWGFldnIZ3RBIymMznvhxLlLsmi4L9N/kh0sA9oOYzQno/uce8gF7WgQwHqh51btixQoUixZYwMe5oZYvX95cDYezBXQB8CuQRDptWuv6wJcBILEMwqVLl3BX1PXCyZMnb17hh/N4edr2I0eOgKLmiRIlMtlrnKiH6Cl2YfFet26WDExsBIG+cSSIPG2htlykGgkKo2VJ+HhS9sor1n/ppx2lC4pNm4AHHww/BBYuZCQXQF9Oph/182+nAYi/19Rs5SkejfXThzs25YajRy1Zr2+/BX74wXI3IBHnqSD/+LvPLDQkfvz9Z/t5Ys00huwPTwwp4xPjoMXfAxXQ/c/fnfGwfBHAeICrXr06/vnnH3MFXKRIEbOB/u9//zNXwDlz5sScOXM8hD00XgvoAmBic25QFSpYPxJ+tv3795sxSpYsGUgGOXZONWoBJk+e3ODAU+t7773XqVBEZr9dV5yPP25t3NFtzBigdWuLBPK5SDYKy/fqBfDKlERl7lyrt8SF4vMBJhg+g5oKBzxx44kcc5zz1Myfxn2NkeX0K2W91JCkbI6d39BTp6x22hGupnsCiSV1YSkPRhL51FP+7NktZQd0/wtYr9yrSAQwHrwYANKwYUOTDo5Egnb16lVUrlwZkyZNMoEg4WwBXQAuMdr27a3rDD8br+mLFi2K7Nmzg2TQ6UbSxxzWa9euRYkSJZwOR2T1n4EPPB2ibxuv1RgU4rKuXS2/OJLAUaMiq98xe8MABRI/upnQ+JvdsyfASNq48iSHCyJM48dgl3HjrFzG/jKe+DE4g7db1atbafayZPFXbcDp09bHCVMUcoyWLQPKlvVffdFKDuj+F5AeuV+JCKANzHbs2GH8yHiSQlHdB8PxGiGWfgZ0AVCcedo0gOmbKN7qZ2P0L6OA6b9JEW+nG0kfM6PMnDnTpDKURRAC9LdilCuvP5nntlSp/++cK6esU7JJtGoFjB1rXXnz1iF//sgY6H79LDLL4DkG0fnDeCJHdyd+MFN2Zv78wAQN8fq+Th3rBJC+gLyqD4BOY0D3P3+Mlw/KFAH0AYjhWkRAF0DFitZXHnORBiB6evLkyWjUqJE5reUJrtONpG/27NlGF7G5P08QnA50sPpPkWBeecYMBOGVGl0uwiX7hbf48dqS1+C8Bo6kiOe1ay1inz69JcXi60hmyrI8+aQlJs6octYXJX3m7ZDYep8n1489ZkULB+i0OqD7ny0QAv+QCGA8mL9BJ9h4bCK/MMPYAroAuLi3bLFycPLr0s82ZMgQvPvuu6hfvz6mMELQ4UbSN378ePTq1Qu9e/d2OBoR2H3XCRE/rviR5TKXRAxJIP1vZeGJAIktyR/zHjOyu0gR3/WDEbw8gZs+3dJQZMT0/ff7rny7JS1d+v97QwDma0D3P7sYBPg5EcB4AH+evgnR7MqVK9iyZYsRg65YsSK+C3On6oAuAEZ68cuVX+d0yvazdezYEUOHDkWHDh3Mf51uJH19+vQx+pUfxZUtwekghXP/XZGijLbcscPqCa+G6VzPIAJGXUaI60o4D5NXbaecDQM0Bg2y/Bp9ZQycYQANffBIwsqV81XJ7pfjytjCQDVeBXP++skCuv/5qQ/eFisC6CaC169fB1OM3XfffeaEKZwtYAuAsgB33GFpRVE3iv5KfjYG7/Dkj1kwwn2cfAEVSR9TwtWsWROzKA0iiywEqKvmirykzBKv7+hg77rGO3s2IH5VkQVqiPWGQTyUtWEmE2Y08YXxVoa3MzTeaL3+ui9K9bwMnnCyPRTspqsKg178ZAHb//zUfl8UKwLoAYrMBkIdwEN0mg1jC9gCoE6UK2KaEXoBiMirWrWq8f377LPPjC+g042kjyfaFIRex5ywsshDgA70FEF2pTtj6q5HH7VIIEmhLLwRcOV9pr4px9MXadQ6dLAC83i6GCofhrz+dcnB+DF1X8D2vxCedSKAHgzO/PnzjTwMZWLC2QK2ALZutaLx6MNCUdYAGHUbGf07b948Ew3sdGMEMCOBc+fOjT0UX5VFHgIUP6YfF0Whu3SxiCBTw5EE8qRHFt4I8EqfAss8eKBcCgPrvDHq9eXIYbnm8GqZsi+hYq5obsobkfhGlzbyURsDtv/5qL3+KEYEMB5U21OzLppRBoanfiQVJICjR4/2x5gErMyALQBG//LHivmUmVcyAEYRaOr/bdy40egBOt2oAUgtwDvvvBMXLlxwtDB2xM4F+rp27Pj/os8UP2YgG0kg023Jwh+BBg2siG4SfBJ9b4ykjyd/9M+mlmQAbmZsN5cuC/xwYVQwfZabNbP9qt0HA7b/2W1QEJ4TAYwH9AoxouYSJ06MjBkzmgAQRggnDXOZgYAtAJ5K8HSCAp8rV/p9mpOoMw3c5cuXjfhxLn5FOtyYAo7ZQGhOT40XsVOBQsEUDOapDjf0994DevSwSOCECRHbbUd1zJXz2Bep/WrXtrT3eA0cioFyzEDCBAKMZOctUuLEPh3qgO1/Pm21bwsTAfQtnmFVWsAWAE9K33rLSi/EfJF+ttOnT9/M/ct8zS7i4+dqQ774u+++20Sw//nnn3iYP6qyyEKADvTMtcqrQl4T9uljnZ6QBDLKUxb+CBw4YBF8pmWjOw1TtXlidF9ibl7Ky2zeHJqC2ZzP7Cs1AilKzbRxPrSA7X8+bLOvixIBjAdRl9RLuhiCmJw4FNb9wc85bZm7lU77v//+O3799VcUpLhplDFHcatWrUwbSHDq1q1r5E7uYLStTQvYAqCCPXXKGOJPlX4/219//WWytaROnRrso8xCgFlsmNFm+fLlJohJFoEI0NeWpyW83vvkE0sc2k9XaBGIXnh0KV8+yy9uxgyAp3iemOt0je4xFH8OVXMFqfgy8jmqrwHb/0IVWwAigPEMDq98Dx8+fFvO3yNHjpgcs9QF9Ke1bdsWJDNMaxadAF67ds2QQV5HDxs2DMePHzc+ibVr18YoN/J9BmwBMJx//HgrUXsARIhXr16NMmXK4P7778fff//tzyEKq7Lp0rBixQruJvGoAAAgAElEQVR8/fXXeJWp+WSRhwBlPCZNsk79vv8eYG5XksBq1SKvr07tEaVg+DvvzQd1oUKWJitvZxhwEarGgDWKUlNCjLqALskaH7Q3YPufD9rqryJEAGNBdhMnGphNqKA5YUvP6NUoI/mivAizKvgzmpKkj0EoM2bMwKOPPnoLAeS/VatWDfv27UM2HuMDmDp1qpE7ITlNkyaNrfkSsAXg8jUZMwZo2dJW27x5iPluSYZLliyJNWvWeFNURL1bp04dM0+GDx+Ot+lbI4s8BHjCzg29ShWAObAZ4UkSGO32IPI67bAeUa6FSQo8je4m8SMB5G0RXQWi7W8hieRLL1muQz72ZQ3Y/heSoFqNEgGMZXB48peIPhZGTP/GbU/wypUnbQmlivN03P/9919QxoTabRkyZECePHluIYA9e/Y0eV15NewyOvaTqJKwxgxecT3DK2X+uYwLgNGy9JmzSxo96lOZMlaSegaDcDH72UjOmfpMose3At2uXTuMGDECnTp1wiBmE5BFHgK8zitWzPINc2n/kQS6RKIjr8fO69H+/UDOnFY+YEbLuqsHyI8/XgHzt5i/yaFurjzIJKyMCmbUsg9MBFAEMNZpxMhREj9m+9iwYYO5anUZfewyZcqEJL5Oxh1VAeulbl3p0qXRvXt3c8oYkwA2bdrU/O+LmVc3mlHiY9KkSeBJT2zmSgcW89/8TgCZguqvv4AVK6yE4362fv36gSS5SZMm+Pjjj/1cW/gUz6wonTt3Nu4CnCeyCESAH3hMn+VyT+GmefGiFTQgiwwEeCiRIQNw4gTw889A4cL2+0UhfmoJMnPMvHlAuGiklihh5Sj2oRuRCKAIoP2F4+WTcZGv6MVSs45XltOmTcPKlSsNyYyLAJKkLoqh7UVyyvRncfl3Be0EkKcRp04BzEzwyCNeIpnw661bt8aYMWPQrVs3vEcpDJlBYPLkycZNoFKlSrfNHUEUQQhQIuR//7M6lCcPsGtXBHVOXTEIUFeV+qrupm+j7AtdcpiOk6dp4SJlNm0aQL9lHsaw3e6eesYybUQARQBvmxZz5swB04glS5YM/L/jsxo1atj+NTp27Bj4F59RqJfkbe7cubcI9dLvkGSwXr16ZhP39Ao4Zt0BWQD84rzzTqtq9v+ee2xj5umDL7/8Mr755huMHDkSbegwLTMI8IOhSpUqKFCgwC3uA4InwhCgn60rhyrdL1atirAOqjto1w4YMQJo29b6r12j8DP3NeaxHzzY7lvBf45yNUx1SH1LalrSH9BLC8j+52Ub/f26fABjIBw98pf/d1xGH0ESM18b5V2iS5ccPHgQlStXxrfffmskYXLkyGGighkEwkwXWfklB5hTQ17thVwQiEu3ilfmJIM+FvOMDX9KnPz4448m4OEVClDLDAL0GWVgE10Y6Gcqi1AEXBlA2D3O/6lTI7SjDu4WXTgY8U05J54E2jG6BzBAkL/Doar9F18/hgyxiCsDmhjY5KWJAOoE0Msp5P/XY7sCdsnAZM6cGUOGDMGJEyfM1R61CUNOBoYLlT4qWbJYEWcBsHz58hmx4/gCYgLQjJCrgqQvS5Ys5nSZWVLCPZNNyAEcKg1i3l+XXAbTWQ4bFiotUzt8hYDrd5XuNRSEtuPjuW4dULKkdY3KD0A77/iqvb4oh+LVmTJZJdGliKLnXpgIoAigF9MnMK/GRgBZM08KW7ZseZsQNANB7FpAFgD9FClJUaAAj6DsNs2r5xg5TW3ELVu2GAkdmYUAPxzoJ3r9+nXwZNl1eix8IgwB3kxwczx3DvjgA5jrQllkIcDAnlSpuKgtnzhGBSdkvCrmXKAmJLUhw9Ho00ptQCZhiJGq1d3uBGT/c7dRAX5eV8AJAL5s2TLwj1er3Dij20Q64IaxBWQBMHE5E5g/9RSwdKnf0bp69arx36RxzKJHcPu98jCogKSP4ua//PILClELTBaZCFSqBCxZIhHoyBxdq1eurC92hb6pDkF3AAbGdesWnsi8+KKVAYXXwe+841UfArL/edVC/78sAhgPxn369EHfvn1RtGhRc1ri0gZ0vULB4XC2gCwAnkAwnQ9/fL76yu9wkdxwrOi/yWtOf8n1+L0jfqqApO+3337D/PnzTbCTLEIR4CnJTz9Z685PklURilz4dKtePes31S6hc52e8UOcH+ThaAMHAl27WhHBX3/tVQ8Csv951UL/vywCGA/GJBLvv/8+6tev7/+RCEINAVkAnTtb0WbuRqt5iAezuDz++OMKdIgDP2pMMoiIp9ev04lcJgSEQHgi8P77QKdO9gSdD/8fe+cBLUWVdeHzy+hgRMWsYM6OOSOYdUyjmBNmJRlwUDEzo4IBzCIqJjCOAcVRzAFFVMw6yIgYUcw5p/Ff332e5+VS1V3dXdXd1X3OWi71ddWtW7vC3XXCPh+0SL+Q90f+XMJuUXUHDNq3W24psvTSIpMmVTS9qqx/Fc0w+52NABbAuH379k4Imp6yjWhVeQAo16cqccCAli+3jO2BBx6QzTffXFZaaSV5mUo3s2kQoHvNVVddJQMHDpTjjjvO0DEEDIG8IqD51Qjtv/pq4bMYNUpkhx1awsZ5fi9S8IIINlZhIUhV1r86v7eMABa4QLTMmm222eQkGqs3oFXlASDhGMX5YcNEDjoocxSvv/56p5e4ySabuNxNs2kROP744+X00093+ojoJJoZAoZAThHwvXq0hJtllvgT4WOP9o+8g3kX59kWW0zk7bdb5G+QwSnTqrL+lTm3au1mBLAA0kcccYTrrIFwLv9ocYHucg75bTm2qjwA9CWlPylfoCUIZ5cLK71u6XmLoPYNFeaIlDuHet7vggsuEO5rxLLRjjQzBAyBHCNAX1x6PdMmjXdtnGnnkMsvFznwwByfsIjstJPIyJEigwe35JeXaVVZ/8qcW7V2MwJYAOmNC5SZUxCCzlyerSoPgH6tjRvXokGVsZmHqzDAN910kxPH7tKlixPLNjMEDIEcI6DV3vQ8P/jg6BPxZYHQiMy7NNbAgS1VzBUWFlZl/avzW8sIYJ1foCynV5UHYNZZRb77TmTyZJEq5FIedNBBcsUVV7gewPQCNpsWAXpMb7jhhrLMMsvIq8Xyhgw8Q8AQqG8Ejj66xRPWu7fIRRdFz/Wll0RWWUVk9tlFPv88/1XhpeQ+Frh6VVn/6vvuESOAdX6Bspxe5g8AQrSIlWJffdXyAsrY6M9ML+XLLrtMDo77Is54DvU8/KRJk2TZZZeVOeaYQ7788st6nqrNzRAwBIohcO21IqhUFOr5jHewe/eqabEWm3LFv9NTnm4mGO+wMiuaM1//Kj7R7AcwAlgA465du06n/cfmhH/btm0rSy21lOy5555uQc2jZf4AvPlmSwPvtm1bvIBVaD207rrrylNPPSW33367bE/jc7NpENBrzh+//fZbmaVQ4rhhZwgYAvWNABW9dFmCBFEVG/WOVSUGIiJoBjaCLbpoSweURx4R2XDDss4o8/WvrFlVdycjgAXwpr8uRGLOOeeUNdZYQ3777Td5/vnn5YsvvpAttthCXnzxRaFVG9WmnTp1qu6VS+FomT8AJCavu65Ix44tVVtVsCWWWELefPNNGTdunKxXhZzDKpxSqofgHp511lnl+++/lzfeeEMWRxzWzBAwBPKJwM8/t0RZfvpJ5I03RKKe5xVWEJk4sbG6wuy4owiNGOhzTb/rMizz9a+MOVV7FyOABRA/9thjhZvkoosucp0lMNrBUUU5++yzy4ABA6RHjx4yYcIEGYvqfs4s8weAFkVU/q65ZkslcBUM2R48W5MnT25Y/cZKYTSSXCmCtr8hUEcI0NLxhRdaCBFaf77hFZxrrpa/UC2sodM6mn5ZU0FX9sQTRfbcU+S668oaIvP1r6xZVXcnI4AF8KaP7OOPP+4S5n0jj2r99deXTz75xIkNd+7c2XkF82aZPwBXXNGiO7X11i1agBkbxA8CiHFukHSz6RHg3n3iiSfk1ltvlR35kjYzBAyB/CKw774iI0aI/OMfIv37T3se9IOmUpgCPArxGsXuuUeEVpakX/33v2WdVebrX1mzqu5ORgAL4D3XXHPJ8OHDhcIC3+644w7Zd9995fPPP5fXXntN1l57bfffebPMHwDt28gL6uqrM4eH0C/eLfIzv/vuu8j8zcwnkYMDQProYz1kyBDp1atXDmZsUzQEDIFYBLTfeteuLfp4vp16qsjJJ4vQN5iCkUaxjz8WmW++lpxHCkHK+NjPfP3LAdZGAAtcJLolICaMttxaa63lCAWt4WijRfEHnRQuv/xyufrqqy0EHIUjuRnnniuCVAF9KzM2ij8oAunYsaO8XaWcw4xPKZPhIX1Dhw51HW5OOeWUTI5hgxoChkCVEKDj0WabtRTcvf76tAfdZhuR0aNFLrxQ5NBDqzShKh2G3PIpU0TQM+3SpeSDGgEUk4EpdNf8+uuvcsYZZ7gcwA8//NBtOv/888thhx0mtIlr06aNvPPOOy4/cJFFFin5Bqz1Dpk/AHvv3ZKfMWiQyFFHZX66yL/grV1zzTXl6SrlHGZ+UhkcANLXv39/J5ODXI6ZIWAI5BiBOFmU335r6Zv72Wci48eLrLVWjk8yYup4PG+/XQQP6JFHlnxuma9/Jc+o+juYBzAh5twsGPppjWKZPwCqUj98uMg++2QOGwLQCEFvvfXWclcVcg4zP6GMDgDp6969u2y33XZCOoOZIWAI5ByBhRcWmTpVhGJEVaR47TUR8tf//OcWHdaZZsr5SQbTR9LmpJPKDm9nvv7lAG0jgDm4SFlNMfMHYNVVRV58UeTuu0X++tesTqN13NNPP92F65HvueqqqzI/Xl4PAOlDI5G0BlIazAwBQyDnCFBox3sWwWdyrpdbrqXwDpHo9dcXefzxnJ9gxPQ5X86bc0XmpkTLfP0rcT612NwIYBHUb7nlFqF/KqHen9Ba8uy5556rxTVL7ZiZPwALLSTy/vsizz4rsvrqqc07bqAjjzxSzjvvPBeeJ3RvFo0ApG+dddaRDh06uPvazBAwBHKOAJ6wUOQZjx9rFrnY6OU1miFrM//8ZReCZL7+5QBvI4AFLtIFF1zg+slS8Tts2DDZf//95fXXX3f5Zb1793Y6gHm2TB8A8k94Af3yS4tie4cOmUO11157yfXXXy9nn322/L1McdDMJ1kHB5gyZYorlJlxxhnlxx9/tGrpOrgmNgVDoCIEqIrlo5e+v8iivPvuH8MhmbLllhUNX7c7s65wro8+KtK5c0nTzHT9K2kmtdvYCGAB7JdbbjmXLL/HHns4TTk6fyAzcvLJJ8tnn33mikPybJk+AMjizD13Czzff9/SDi5j23zzzeWBBx6Qa665RvamAMUsEgFIH1I52Keffipz63UyvAwBQ6AxEPjmG5FJk0ToFLLOOo1xTlFngfD1qFEtahN9+pR0npmufyXNpHYbGwEsgD19UidOnCiLLrqozDfffHL//ffLKqus4rT/kBth8cyzZfoAvPpqS24GRTPoNFXBuDYvvfSS3Hvvva5Vn1k8Au3bt3cfMXSxWYFWUWaGgCFgCOQNAdU55IP/mmtKmn2m619JM6ndxkYAC2CPt48cwNVXX90lzFNhSvXkfffdJ7vvvrtbQPNsmT4Ajz3Wos201FIiVKNVwRZccEH54IMPXL/mVSlAMYtFYMUVV5RXXnnF9bHeZJNNDClDwBAwBPKHwJ13imy3ncjKK7cUHJZgma5/JcyjlpsaASyAPoSPRHnCwJdcconLK+vUqZM888wzroUWsiN5tkwfgFtvFdl556pVoNGjeaaZZhK0G9977z1ZiAIUs1gENt10U3nooYfkuuuuc6LmZoaAIWAI5A6Bt94SWXzxlnxzwt4zzpj4FDJd/xLPorYbGgEsgD+kgn/+9Kc/ua2oBh47dqwstdRS0qNHD0c48myZPgBDh4rQZowcDZqUZ2yE4+dB9FTEFTbk/dpkDJdYwUzWCNv4hoAhkDkC//ufSLt2LeTvlVdEll8+8SEzXf8Sz6K2GxoBrC3+NT16pg/AP//Z0pz8kENELr008/MkV5NcNvo35z00nzlYItK3b18555xz5Oijj5azqtCmrxrnZMcwBAyBJkRg3XVFnnoKD43ILrskBiDT9S/xLGq7oRHAIvj/8MMPrrDgo48+ct5A32g7lmfL9AGg7+SQISInnDC9PlUGoI0ZM0Y22mgjWXbZZeW/yCCYFURg0KBBcswxx0i3bt1kxIgRhpYhYAgYAvlE4OCDRS6/XOTkk0VwPCS0TNe/hHOo9WZGAAtcgXvuuUf22Wcf+YRei4H93//9n8s3y7Nl+gDsuqvIzTeLnH++yOGHZw7TzTffLLvuuqt07txZHkUTyqwgAkjlcG8jnUNRk5khYAgYArlEgDUGCRh6A48cmfgUMl3/Es+ithsaASyAP7l+W265pdP9mx/F8QazTB+AjTYSGTNG5IYbRHbfPXPk0GQ87LDDZKeddnKV22aFEUDSCKmclVZaSV5++WWDyxAwBAyBfCLw4IMim20msvTSLdqHCS3T9S/hHGq9mRHAAldgjjnmcJIiSy65ZK2vUybHz/QBQFuO/ow8nFWQGYGkn3rqqdKzZ0+5+OKLM8GrkQYlrQHdRPQtP/zww0Y6NTsXQ8AQaCYEeH8tsEBLS7hvvxWZeeZEZ5/p+pdoBrXfyAhggWtwwAEHONmXAw88sPZXKoMZZPoAUJGLUDbepZVWymD20w5JVfall17qJHv+QfGJWUEEpk6dKgsvvLC0adPG9bieYYYZDDFDwBAwBPKHAG1H55tPhFStEvrOZ7r+5QRFI4AFLtR3330nu+yyi8w777zyl7/8xfVO9e3wKuS2ZXkfZfYA0P9XseLrjIczY+vatavcfvvtMmTIEOmF/IxZQQQgfX/+85/dNuS40hnEzBAwBAyBXCKw8cYijzwiMny4yD77JDqFzNa/REevj42MABa4DpdffrnT+5t55pndAknhhxr//cYbb9THVSxzFpk9AB98ILLggi0ueXpRtmlT5gyT77b22mvL008/7Ujg9ttvn3zHJt5yzjnnlC+//NJVTVM9bWYIGAKGQC4ROOwwkYsuEjn6aJGEslaZrX85AtAIYIGLtcACCwhevmOPPbaqIbLFFltM3n777Wlm1q9fPznjjDNa//bOO+9I7969XTcHCCrdHAYPHlySAHJmDwBhX1rzEAb++OOqPA50/nj//fcdCVxzzTWrcsy8H2TppZeWyZMny2OPPSYbbLBB3k/H5m8IGALNigBasz16iGy1lcjo0YlQ+Ordd6Vdhw7uI5h8/2Y0I4AFrvrcc8/tCEW1i0AggOQdHoy+0e8222yzCf9gyM/Q65bQ9Nlnny10wdh3331de7oLL7ww8X2cGQHUqiwKQSZMSDyfcjf8+eefXTjzt99+cyQQ4m5WHIH11ltPnnzySRk5cqQQQjczBAwBQyCXCIwbJ9Kpk8gii4hMmZLoFL566CFpt+mmRgATodWEGx155JGOZB1//PFVPXsIYJ8+fdw/UXb33XfLtttuK1OmTGnteXvjjTfKfvvt5wSrk37NZEYA6ZF80EEt1b+QwYwNHDp27Oha9tEGzgoakgGOkPm///1vVzxzCB1bzAwBQ8AQyCMCX34pMuecLTP//PM//rvAuXw1dKi069XLCGAer3c15kz4ly4JyGWsvPLK0xWB0EorC4MAQmRI1O/QoYMrRKFll/a3RfJk1KhR8uKLL7Ye/vPPPxc8loSENyYhNoFlRgD33LNF/+/EE0VOPTXBTCrbBC8W3ixIYBg6r2zkxt4bL/OVV14pAwYMqPpHTmMja2dnCBgCVUegY8cW79/YsS3ewCL2VZ8+0u78840AFgOqWX8vRKQoAoFsZWHnnnuurL766q6v7fjx4+W4445zhQ0UpWB4a956663pOjgQBr366qtljz32iJwWpJJ/1CCAEMxUcyBol0cIltw/hKC7dMkComnGRPgZkrz++uvL448/nvnxGuUA5LaeeeaZztPMPWdmCBgChkBuEdh6a5G77xa55BKR7t2LnsZXW20l7e65J931r+hR62sDywGs0vVAm+6fRfoUxhUw3HrrrbLzzju3ynVAAPF03XvvvdPMHg8hHsvdYzpvxM0hVQKIV3LVVUVmnVXks89EZpopc4TPP/98R2IggTfRENwsEQIUDeFZ3muvveTaa69NtI9tZAgYAoZAXSJwzDEigwaJ0Ic+QS78V0suKe3eeMMIYF1ezAabFFprUT2F/dMk9Nu2bdvpzvy9996TRRZZxCXsr7POOq41XTkh4Kp4AAcPbinF52vsrruqchUhMZAZcjazCstX5USqfJDhw4e7vFFawoUfE1Weih3OEDAEDIHKEBgxQmTffUVoQ/rww4XH+vhj+Wr++aXdb78ZAawMdds7awTuvPNO2W677ZzXjzw3LQJ59913ZUH09kTkX//6l6sErnkRyJZbitx3nwghxZgilrTxQgLnhhtucCSwb9++aQ/fsOONHj1attlmG1lttdXkueeea9jztBMzBAyBJkCAd9gaa4ggak8KkqfbO93ZH3WUfHX22dJOxAhgE9wauTnFJ554wnn6yD9s166dk6HBs4W2HV4/TGVg5p9/fhk0aJB89tlnzpOzww471FYG5ocfROaaS4R//+c/IiuuWBXcu3Tp4rTsqITebbfdqnLMRjgI9xYC2uSBoitpZggYAoZAbhH4/nsRpNLIQ3///ZZc9CibOlVkySXlqx9+MAL4G+JpZnWDAJ4YWpnRnYGQ7aKLLupy+o455hiZZZZZWufJgs12oRC0tvdKckKpVwGr/t9CC4m8+27hL7AkE0y4DTqNdGUxQeOEgP2+2ZtvvilLLLGESzug7aHf6aa0kWxrQ8AQMATqAAE6Gk2aJHL//SKbbRY9IXIEhwyRr9ZeW9qNH28ewDq4bDaFGiCQOgE89liRM89s6cVIT8YqGN8vdEKBLENoyKM0S4bAN998I7PPPrvb+Ouvv24VGk+2t21lCBgChkCdIbDTTiIjR8anINFha+mlXYvSr+68U9ptu60RwDq7hDadKiGQOgGkBduzz4pcc43I3ntX5SworEGsG4MEqlZiVQ6e84NAnvEq//DDD86Duvjii+f8jGz6hoAh0NQI9O8vcsopIgceKPK7bNo0eNCggEYFm2wiX912m0uzSlUFI2fgmwxMzi5YmtNNlQB++qkIRIyMAnIsfi9OSXO+UWO98MILrohhvvnmkw8//DDrwzXc+BQV0UkFvcm11lqr4c7PTsgQMASaCIGbbxbZdVeRddYRefLJaU988mSR5ZYjiV7k8cflq5VWMgJoOYBN9HAEp5oqAUR/jwKMlVYSefnlqoGqFdJWyVoe5AiOP//883LXXXfJ1kj3mBkChoAhkFcEJk4UoQc9xSC0h5thhj/OpFs3EfROf5coS3X9yyle5gHM6YVLY9qpPgAHH9zicj/ySJGMWuRFnTN9bHv06OFkcu644440YGmqMbbcckvXUYYOMsgImRkChoAhkFsEfv65hfz99JPIm2+KaE74K6+0OCeIUD3zjJOLSXX9yylgRgBzeuHSmHZqDwAPFfljJNiOHi2y1VZpTC/RGCeddJKcdtpp0rNnT7n44osT7WMb/YHA3nvvLdddd52TEzrqqKMMGkPAEDAE8o3AKquIvPRSSygYLUCIIJXBX3whsuOOIrfe6s4vtfUvx2gZAczxxat06qk9AK+9JrLMMi1t32j/Rhu4KtkBBxwgV111lSOBJ5xwQpWO2jiHQWPyvPPOk379+skZZ5zROCdmZ2IIGALNiYCGesOzZ10aP74lRGwE0GFgBLA5H5F0H4ChQ0V69UrWgidlvGljdv/991sIs0xcBwwYICeeeKJApK+gOs7MEDAEDIE8IzBhgggfs3PO2RKZ4h9Cwci/EB7+3VJzgOQYKyOAOb54lU49tQcAt/ptt4mcdppIlb1wK664orzyyiuOBG4WJ/xZKVANvP9ll10m3bt3txzKBr7GdmqGgCEwPQKprX85BtcIYI4vXqVTT+UB+OUXkXnmaam4euopkbXXrnRaJe2PjhPnMXHiRFmOEn+zkhC47bbbZMcdd5R1111XaENoZggYAoZAMyCQyvqXc6CMAOb8AlYy/VQeALSW1luvpQcwDbjbtKlkSiXtS/eKOeaYw+3DuWhXi5IGafKNx44dK507d5alllpKXiOX08wQMAQMgSZAIJX1L+c4GQHM+QWsZPqpPAA//iiC5+i990T22quS6ZS8L/2Sl19+eUcCUXM3Kx0BxRBP6hdUyZkZAoaAIdAECKSy/uUcJyOAOb+AlUw/7w/Agw8+6PL+IIHkAZqVjsCnn34q8xDCt1Z6pYNnexgChkBuEcj7+pcG8EYA00Axp2Pk/QEYPny47LfffrL55ps7MWOz0hH43//+5/on//rrr/Lee+/JQgstVPogtochYAgYAjlDIO/rXxpwGwFMA8WcjpH3B0AlTCCBaAGalYfA/PPPLx999JHQV3kVRFTNDAFDwBBocATyvv6lcXmMAKaBYk7HyPIB+O233+T/UGHP0Hr16iVDhw51Onannnpqhkdq7KFXWmklmTBhgjzwwAOy6aabNvbJ2tkZAoaAIWBC0O4eMALYxI9CVgRw8uTJ0qVLFzn88MPl2GOPzQzhv/3tb/Lvf/9bLrnkEqdlZ1YeAhtttJGMGTNGbrjhBtl9993LG8T2MgQMAUMgRwhktf7lCAIjgHm6WGnPNasHYMSIEbLvvvvKCius4DxLWdkaa6whzz33nCOB2267bVaHafhxd9llF7nlllvkggsukMMOO6zhz9dO0BAwBAyBrNa/PCFrHsA8Xa2U55rVA0BYlvDsn/70J/n2229dkUEWprlrzz//vKy66qpZHKIpxtRQ+kknnSSnnHJKU5yznaQhYAg0NwJZrX95QtUIYOG459kAACAASURBVJ6uVspzzeoBOPvss+Woo45ys8UDiCcwbfvpp5/kz3/+sxuWAoZ555037UM0zXj9+/d3xK9nz55y8cUXN81524kaAoZA8yKQ1fqXJ0SNAObpaqU816weAMgEpAK76aabhBBjUoMwIkmy8sorF9zlrbfeksUXX9x5F3/44YfMC06Szj+P21144YUuX3PnnXeWm2++OY+nYHM2BAwBQ6AkBLJa/0qaRI03NgJY4wtQy8Nn9QD069dPzjrrLHdq//jHP1rJYKFzpZPH8ccf76p627ZtKx9++GHB1m6PP/64bLDBBo4EvvHGG7WEMffHvvHGG2WPPfaQDTfcUB555JHcn4+dgCFgCBgCxRDIav0rdtx6+t0IYD1djSrPJasHgEKCiy66yJ0N3j+8gIXstttuk0MPPVSmTp3autnTTz8ta665Zuxu//rXv1zFKn1sH3300Soj11iH044q5RbtICZN0c98880nhP/NDAFDwBCodwSyWv/q/bz9+RkBzNPVSnmuWT0ABxxwQKswcyFS8cEHH7i8s9tvv92d2VJLLSXoB77++uty/fXXO69UnJ1zzjnSt29fRwKRLzErH4GXXnrJCUBD4PC8lmpUYlORje7jL7/8IjPMMEOpQ9j2hoAhYAhUFYGs1r+qnkSFBzMCWCGAed49qwdgt912a/X6UQn83XffyYwzzjgdVFtttZXcc889rlr4mGOOcYLOeAKvvPJK+ec//yknn3xyLLx///vf5dxzz3XFJoMGDcrzZaj53PG8LrzwwtKmTRuhuKZUAjdkyBB33bBvvvlGZp111pqfk03AEDAEDIFCCGS1/uUJdSOAebpaKc81qwdgu+22kzvvvLN1tlGVwD/++KPMMcccjnCMHTtWOnXq5LY//fTTXS7g3nvvLddcc03sGe+6666uYAES2KdPn5SRaa7h/IrqTz75RNq3b18SAFyr6667zu2DBxFPopkhYAgYAvWMQFbrXz2fczg3I4B5ulopzzWrB2CTTTaRhx9+uHW2UZXATzzxhKy//vpOvgXSoG3jECQmb3DdddcVtokzCOO4ceMcCaR61awyBOacc06hEGfixImy3HLLlTQYoXvC9hgFORTmmBkChoAhUM8IZLX+1fM5GwHM09XJeK5ZPQCQt6eeesp5kj799NPISmDVCtx+++1bcwA53RdffNGJOrMv3qg4W3TRReWdd95xJHC99dbLGKnGH37ppZcWWvhRUENhTVJDgxFBbrWXX35Z6C0cZ9XoEZ107radIWAINC8CWa1/eULUPIB5ulopzzWrB+Avf/mL/Oc//5G//vWvLscvqhJ4p512kpEjR8qZZ57p8v/U6Bwy22yzuf/97LPPZK655prurKk6RQSaggNIYIcOHVJGpvmGg0Q/+eST7pp07do1MQB33HGHQOLVGGOdddaJ3P+uu+5y1cLkeNLH2cwQMAQMgVohkNX6V6vzKee4RgDLQa1B9snqAVhiiSXkzTffFFqLnXrqqdP1BMYLtNBCCwlVwI899pjT8/ON395//33nRVx77bWnQ5v9FlxwQVesgAh0VIFJg1yiqp0GhIyeypdeeqkccsghiY9LviZ5m2oPPPCAbLrpppH7H3HEEa7fMDmiEEczQ8AQMARqhUBW61+tzqec4xoBLAe1BtknqwdggQUWcHl9EAoW+7ASGHIISYS4kXc288wzT4MogsSEIiks2HPPPadD+9lnn3UagZBAXzuwQS5LTU7jwAMPdJ650047TU444YTEc9h4442nEY8eNWpUrHfvoIMOkiuuuMIV/5AawH1hZggYAoZALRDIav2rxbmUe0wjgOUi1wD7ZfUAzD777E4OZNKkSbL66qu7//Yrga+99lrp1q1bbKGHEoW4LiKQjB122EHWWmstGT9+fANcidqfwrHHHuvC8XjpzjvvvEQTIgTfrl07J/NDHiCkv5B+I5qNCHhjhULFiQ5uGxkChoAhUAECWa1/FUyp6rsaAaw65PVzwCweAMK76Mnx7/fee8/lk0HS/GrdXr16uZZvaPlFdY6AiEBI9tprL4Eshqa6c5BAuoiYVY7A4MGD5eijj47FPOoIL7zwgqy22mrOo0cYf/To0TJs2DCBwEfZtttuK+QBYgMHDpTjjjuu8onbCIaAIWAIlIFAFutfGdOo6S5GAGsKf20PnsUDQE6ehnS/+OILOfLII11XEN+bR5Uv1b5IvlAMEhqFCPyd/D/yAEM7+OCD5fLLL3ck0c8/qy2a+T768OHDZb/99pMttthC7r333kQnA4mHzG+++eYy99xzO+8e3kO8iFG20UYbyZgxY9xPm222mdx///2JjsNG3CtUKtOxxMwQMAQMgUoRyGL9q3RO1d7fCGC1EU94PDwlp5xyitCmi84KXbp0cRWaalS/9u7dWx566CFHuMiVw4sz00wzJTyCSBYPALld88wzj5sDAsPnn3++8yxpJTDHpLKXSl48hBR8hKatydiOSuDQtMqYFnJ+BWriE7cNp0MA790222zjPHq0dkti++yzjxPrpmPLu+++63IIBwwY4IS8o4yQ/TPPPON+atu2rfCBQDV3MeMjAGkh5GWQmTEzBAwBQ6BSBLJY/yqdU7X3NwJYbcQTHO/WW28VvFyEyRBVJpzKwqeCx7/++qvTykNEmRAqpAt5jR133FEuvPDCBEdo2SSLB2DKlCnSsWNHV+ABAbz77rtl6623lhVXXNFJw1AlisdoscUWc5XCUUZOmbYT49zwLqkxZ0SLwYRKYQpOzCpH4Omnn3Ye10UWWUS4hmp8YFx00UVC72WumW/LLLOMvPbaa+4aQyC59yB/kMAoW3755eW///1v60+PPPKIUPBTzCCYVJNzv6M7aGYIGAKGQKUIZLH+VTqnau9vBLDaiBc5Hon1LLT0wqUyM8pYcMmnYqFWD9qNN97oQngskORkJbEsHgAWeBZ6SNrnn38ub7/9tjsfCCEaf4Rs+/fvXzTXDCKChzAsFoCQIDOCEPRbb72V5DRtmwQIaGU2njkIOJ1Z+DdhVyqtIfGav8dwiHRDyDC8tGeddZacccYZBYtI0GvEU8iYEEeIHfd5MVNhcfQhv/7662Kb2++GgCFgCBRFIIv1r+hB62wDI4B1dkEomEBIl3Aammlo3uHtI7yLFw1j4aQSljw6NcgWnjIIEtIcUUb/Xf5R4wFgUUaKJSlpLAaXSrRATCFweOoYWyuBKfwgx4xCDvLH4kzlRQgx0mtWDa8oMiX0AtaK0mJzst+LI8D1oXobg2RBthRr3ZvrRo4gRq9nJH5oG0f7OLx+J554oisAoRAkygjpE/bt27ev81xTOIIOZCGDXEI0SRmguIgPpDjD40z6wBprrNHaWrD4mdsWhoAh0IwIGAEUMQJYZ3c+nrw99tjDhVE17MZied999zlZFUgeQr14v/ibb+RTXX311W7/KKMQI8rjkiYBZEEnXxEvD/PFILQQWwgboW0evOeff94R2zjTQo/QS0TOHyLCYEOBiVk6CEDUZ5llFiesTT9fQvD0+IUMUnjBxwY5eFT+QsQge5C+/fff332sUPzB9eDeQwomyshP/fnnn10hCKFfdAAhhBruj9qH6nHIvhokL074m1xTPpTi9CPTQcpGMQQMgUZAwAigEcCq3cdx5MufAHlYkCbkT/yODHjtCIki0tu9e3dHAAmthtWaLLAjRowQ9NairBoeQFq/bbXVVo7cQfIwSALElBxGqjnxLuGxLCQETEixX79+rriFBR2DpJDzR5j78ccfl/XXX79q168ZDsRHB2kFFF3geSX3Dx1HPjQg9FwzvS8Jw+Nt1v/H68d9GdflA+KmBR949Sg24R7mftlyyy1j4VVNSN2g0MeKthc073Az3K12joZAZQgYATQCWNkdVMLe5EzxTyEjV+6JJ55whR9hizS8aEhn4HUpNwQcHjuLB0AlXCBnkDRMNeYgfITwIA8UgxQy9P0oavHFnvF6Lr744rEdREq4HLZpBAKQPUj7ueee6yq3uVaaUkA6AvIu8803nyvkgCwSNibkSlU2Xj8+XLh3H3zwwelGh/S1b9/e/Z0PkR49ejh5IPpAo/sYZRB+cj39ohRSIhCdjjLyFMmPJWTMdrQKNDMEDAFDIAqBLNa/vCFtIeA6u2LclCyy5MhpEQhhMzyAVELiZdEiEBLqaYeGEV6lErjWRSB4jpAHodJXQ9QqMaJQ0yMYiZtCRsUwxIJiEsgDRQkaHqcNHN5Ss3QRwBPHNSNnk/sQWRhy/TDuQULAeKgpQOLv5AziFSQkrN1Z+FChcCc0rQ7HSw0B1G4wha4luYUrrLCC8xySA8gc+AiAFEaZrzOoxDRdhGw0Q8AQaBQEjACaB7Au7+U+ffq4UCm5VSx2gwYNcn118byQSK8yMHhC+A2CRAUwnTFqLQNzySWXSM+ePd1ctEuHVgIr2MXCfmznS8F8/PHHTluQHDNyzQ499NCSzrMuL3IdTopiGw234z2DRGnhEdMl99LXXfQ9uSrvE6fVp2SOHFakfSgQ4qOG4+AZ574OTfMK8XxTXATZZBwKT6JMc035rZAgdbgveY6kVhA65r41MwQMgcZHwAigEcC6vMvxdNAmC2/a999/74ooWND8xRghaKpoQyHoJMK6etJZPAAUZ1DlGebuaSUwnjwIK569YqayIYTFkQJZb731nHcprAwuNo79ngwBJdhsHVXNS0gW0vfwww+7ASkEwSuNcY0I+xOip4gkNNUZ5Jpy72IQuVdffVXiBL01pMtHDmFp5GgQqSZ/MMpWXnnlVqHov/3tb84rmcTIYyQkzf01bty4JLvYNoaAIZBzBLJY//IGiYWA83bFUpxvFg8AhIAcRap4L7vsstbZIjIMCSilmwP5ZJANClvwzrRr186FD9GQo0LVLF0EVMqFamAwjurSQo4gMiuQQcLAhIkx7d5C+sKHH3443cS4jlxPNCJfeeUV97v2hD788MNdxxjfqEbGW8gHEBXI5IO+/vrrBYt/KFSZPHmyG4YPDjyNhQqN9Hi77bab3HTTTSXdm+kib6MZAoZAtRHIYv2r9jlUejwjgJUimOP9s3gA6M9LUj8FA3gt1bQSOCSGheAjLAeJJGeQvDM8oRQSEBLGk2iWLgJ41/7617+6vs2FNBoha4Rk6cesrQchZ5ByJF0oDglNdQP9oh6VeIn6KKCQhNAvOa6Ei/HuaScZvJBRtvDCCzsvoRrSQxyvkJFbSGU591Sc9zJdlG00Q8AQqAcEslj/6uG8SpmDEcBS0GqwbbN4APDmRLUEmzBhgiMWkMMlllgiEZKE/qgSRdaG8CJjhx0pEg1kG2WOAFW3kDWIOTmqIUHXAh4KNTSEDOnCY4iF1b1cd64/hU1ICKkHmVxYPgaiDI8heYLLLrusCy3TmQQpoUJGi0XIJVas1RxV0YyvHVAyB9UOYAgYApkhkMX6l9lkMxrYCGBGwOZh2CweACqXKV4hnEhf2EqM3LCuXbsKlaL0nUVqBCFrQsxm9YWA30mEln+EkX3DW4j3F/IGiVNDL5IQLx1G6IGNRiSmf1dRZ4SjH330UReq3WWXXSJPfuaZZ3ZC1nSbIReVMUOtzHBHlbfh78yZucdZ7969XZcTJJrwRpsZAoZAfhHIYv3LGxpGAPN2xVKcbxYPAJ0g8PaQtE81cyWG15DwILl/hH4pLvDbkVUytu2bLgLaqo1RkSIKvWRa0Ys394Ybbmg9OEVMiEdT9U24ln7DeBDVm0g+IWMRmubaDx8+3MkMheYfnzHJN4QQ0mlEw9RRZ0zVr18swrHj9APVC0lqAtXuZoaAIZBfBLJY//KGhhHAvF2xFOebxQNA9SUeHnL38PhUYnhz8MpQcKBGCC5JBXElx7V9y0OAa0XRBkSdfDrfCvUKpvMIxSQUbeDpRY4GLy/FJs8884wbBk8wHmGIFwQsNF82iPt6ySWXdHl9eA07d+4ceUKQPT4s6C6ipn2Qo3ZAkxAZGnIGyUtMKjTNeWmfZM7JzBAwBGqPQBbrX+3PqrQZGAEsDa+G2jqLB0BbhKXVjxUdRF82hAXYrD4RwFOHph95dXhufUPWiJy8sDhIt0HjEiFqvdb8nX0GDhzoNkFWCM9hnGcZkoVWJEauHl1JEEcn77R///6RgEEu8TpSMQzx40OjUKcRbZXHYKW0IiTvleIoa1FXn/etzao5Echi/csbkkYA83bFUpxvFg+AavUhAp2GqK4SSk5bCwJShMCGShEBWhki+o1WY5gjd9hhh7newieccILraR1leNUI9VLtiz3yyCNC7h+muaUQQohhaHTFQWNwxhlnFPoO44HGU9ilSxcZM2ZM5PG03zRea8LG5DFSzRxXpIS3EA1L7KijjnJFKklMexTHtclLMoZtYwgYAukikMX6l+4Msx/NCGD2GNftEbJ4AFSMl5ZitIOr1BDoRagXGzp0qBPsNatPBBAqR+MPCRfIjm8HHHCA6/17+umnO29YnBHiJ8cPvUfyASF0GN1faI8Y10aQFnVU/5IvSt4fOoaEk9mf/w+LUhhT8wrJT2Re5BtSkKJVweEcEVmHXGKQRDQHk8gRqeeQXsvI55gZAoZA7RHIYv2r/VmVNgMjgKXh1VBbZ/EAkHtFDtjYsWOlU6dOFeN19tlnO28LVqgLRMUHsgEqRkCLJGgZR2GHb4Q/0f1DIggyV6odffTRMnjw4FjPG8SNymHy895//30XzoV44RmM+hiByNF+jtxBRKzxVnPf0gkEL3ZobK9ddsj9o+ikEFnU/SGVzAnj2VCh6lLP37Y3BAyBdBHIYv1Ld4bZj2YEMHuM6/YIWTwAVG+SR0XHCBbkSk37z1LRyXyTdHao9Ji2f3kIbLzxxi5sS64e1b6+aVs3JIIQBS/VKAqhywxSLISSQyPsDHHzxZxJGaCLDB5HPHy+8YFCcQh5i9yvtJeDCN5///1OgDo0PJPoDGJ4DulnXSi/UPfHi6m6hYSQyZE0MwQMgdojkMX6V/uzKm0GRgBLw6uhts7iAdCEekJytOaq1JgjCzK5gOEiXunYtn+6CEB0IDxo/pGz5xu5eOjnFdLxKzQbrj26koSSr7jiiuk21VZzVOoiH4QhGbPffvs5EWkqjX3TloVamIHQOP2M43JXp0yZ4jyKSMqQkgCJJVSMF7CQQRLRrsTatGkj9PmOCxvjHSSHMq7TSdxx8GKql5NOLGaGgCFQHIEs1r/iR62vLYwA1tf1qOps0n4ACLuRc4W8BqE3WnOZNQ8C2lOXVnF0bfEN+RNC+KNHj5atttqqZFBURxCdSQTBQ1NPG6Lh9JzGqCimipyQLV4+X5tQvZUqK0O+6gMPPCDXXnutqyAOjSpl+hgTNia/cP7553f3eaGiEcZA3oZzViskM0NFMpXJpWJEdTWFMSaSXvJtZTs0MQJpr395hNIIYB6vWkpzTvsBIHG/bdu2bnam15fSRcrRMIUqdSnQwCtMRS7ewFINotazZ0+Xq4eXLrRbbrnFdQghrIv2n9pf/vIXV1W8yiqrOC8ZrefQKkRLkrw+9VSrziDevUMOOWS68VUyhkpjiKVWp5OX2Ldv38jT4YOI/D+EsdXwJC6yyCKR22sru3XXXdflIiYpMGGgnXfe2XVR6datmwt5mxkChkBxBNJe/4ofsf62MAJYf9ekajNK+wFAIoM8J4zFVSs4q3ZCdqCaIqB9oKOkXvAGT5061VXBUg1bqmk4F61A8u9Cu+aaa1z1cNj+DU1CvHsUYyy33HLOy4c3j7QCiBhkDqKF+DTalRQd0UouNHIb8RriBaTSmTxEpG0odCKfMMrUA0neKlXIPG9RGonsS1EJ26noOfNMGgpGc5Gwdxw2pWJt2xsCzYBA2utfHjEzApjHq5bSnNN+AFSLjYWMXCez5kKgkNgz8izcb6+++qqTZynVyB0kxByn66e6f9tvv73rGOIbXj4IH943ikQgbYR6fY8ZmoGMccoppzipmdDuvPNOV9lMmHb8+PEuxQFvIOQRYquVvv5+eOXwzlFgQuiXHD/yIDfYYIPpxkeqhvCyGvqHkM5iRhgacskHF8chzG5mCBgCxRFIe/0rfsT628IIYP1dk6rNKO0HgMUdL4tqsVXtROxAdYEAAs+Qp4MOOkiGDRvWOic/NxSx54UWWqjk+dJeEMFmJWDhAMVyBLW4gpw9NXQJKRLB8PrRZaRfv36uY0lo9Lcm/xAvIKLRGGLXkMG49nRKiAkp4/nkH4gkeYGhvfnmm05bkI8nSCUfUIXa2On+nM9SSy3l/hcvK8TUzBAwBIojkPb6V/yI9beFEcD6uyZVm1HaDwDSL4T3kILBK2LWXAhAoCBSYaEGPZ2R8cHwdPGBUKoREiWUS7iTMGpoxaqE2R59QDyBhHCxt956yxWJYMVkZqhsprc1lc6QUUyLL+JCrxwLUWw8i7Sl47/jikwghxSwQI45BvuE4ewozHyZGVIuyMNNmjuY9BpQZcz8qJSmktnMEGgEBNJe//KIiRHAPF61lOac9gOg2mp4JKiUNGsuBDQMi6du1KhRrSeP9p1W4OLZKkfLkd67hE7jxJSLETidDHPB6wfRYr5q2q+X3/AMhkZlc58+fZy+ITqHmHq8OR/IpfYi5jdy+ijq+PLLL50mJt5RQsLkDqJlGJoSXLqpQDCRUCK8i3wNMjZx5guls00WxVcIsXMc8jDJszQzBBoBgbTXvzxiYgQwj1ctpTmn/QDce++9TiSXissXXnghpVnaMHlBgCIKiikoXoDQqBF+pU8wFeJU4JZj5LYhJQNxI4wcWrFOIcWOqUUdVBKTbxjagAED5MQTT5wuvI3XDu8YBI/iFzVtRcc585xRwYx+Ybidbk+XFDQJtYoZIgrh8j2OUeeAVxLvpFpa+pv+sVQiB+8uRNDMEGgEBNJe//KIiRHAPF61lOac9gOAPMeOO+7oOjIgY2HWXAhQfIGcCjImiCqrUaFK6BYP2ccff1wWKBMnThREnimUoNo8NLxqF198sQvlqvByKQe6+uqrnbgzGoW+bp+Oofl8eAEJdauhSYhuIEUghJS1XZz+XbFQLxr/HjRo0HRTC72nEDkqjvEkFmqBCGH0q5ALtWCkqARPJV7MUsLEKuFDQQtE1cwQaAQE0l7/8oiJEcA8XrWU5pz2A6CVleQ+0VLLrLkQ4JqTt4b2Hm3V1AhjQoTIt4MklWPsRwVvnBeRDiGEbskFpPVbqaYeuLgqYyRf8BLiBaSLiBohbeaFV9IvKjnyyCOFwhT2u+CCC5znL6pARsfRfELa10FGsT333NOFm3faaSdB5zDK0DWEVNMB5Ntvv5WRI0c6Eh4ahTiEpMnBJESPdxEtxGLGfoyN5zaqo0qx/e13Q6BeEUh7/avX8yw0LyOAebxqKc057QcAEd0ePXpIlBRHSlO2YeoYAbx+FApQzepX21L8wEcB+W2IMpdj6Pip1ApesdCDReEJlbqQriOOOKLkQ+D1ozqXMDOiz6HhHYSYRRHMs846y1UPQ3xpDcfcyFckb1Hz5jTEHOdFY3/G8T2M6jmlkwlez7B45tNPP23NOyTsDs5xFcm+RifnBmklJxHpmELmHwP88SCaGQKNgEDa618eMTECmMerltKc034A4qpAU5quDVPnCOD1I/+TNmm0XlO744473EcBsilPPvlkWWeh9yo7U5WqVcU6GB1CKDyJ6+RR7KBIrqC9R7gToejQyM/DS3jhhRfKoYceOs3PFF6gCYgHDi/oRhtt5Mga86TimFCuesfJp6MjSWhIxSCdE+oQUvTyxhtvCPm1eFd9I80CTUOOTSUyuYBxOoYQbwjqbLPN5kijhqshpnRwiQsJk8vrk0QqujXMXQzTUn7/5ZdfyioOKuUYtq0h4COQ9vqXR3SNAObxqqU057QfgGJhrpSmbcPUKQKqSQfJQPhYTfPhwuKQUk6DUOtMM83kdsErRTjTN8gR5IuOIBSilGoqw0J3EASjQ9t6663l7rvvnibM62+D15FQL0VQePJWXnllR7aoAsaDV0zHkOITwrwhwUSsGvLYv39/+cc//jHNtK688kpH3iCV6CMOHDjQkVPGCA3SCUlkXuQCUs2LJiEW1blF99d56/8jZg0pTdPI2zznnHOcpiJ5nmaGQDUQSHv9q8ac0z6GEcC0Ec3ReGk/AMcff7wLkdESDNkMs+ZCAK8fGpB4k5AwUa9SnDxMqeggt8K4UWLSWgwBiSJnrlTD64enLq7IhNxAunjgBSSMGxpeOuSPyJmjNzDVsn43D/ZlDORdKPAITXsLhzqB2gM5Kq9Ww8bkGULKCB/TLYVQeGha5AJBhcgSRqeyGfI1++yzO6Ia5QWksMaXrUEEGzHsNE0FtePa8KV5LBvLEFAE0l7/8oisEcA8XrWU5pz2A6BeECom8UaYNRcCeP3mmGMOd9KEQ2lRhuHdgRRR1IBUTLkGUfnmm29cS7XQC6VyLAgj460r1bS1G2LKtFULDYFz9PwgT5CoKIN4UoSBxw+C5Vf8Il6N9w09xI8++ih2/HD+GlbHm0gBhy/ETFid8PqQIUMccQVfv1OJfxCeRzx9FMsgR4P5At3MSbUa/f20+ln/VqoWIO8Y5g4mcaZhbryZvqRNqdfQtjcESkEg7fWvlGPXy7ZGAOvlStRgHmk/ALQAK6R1VoNTtENWEQG8cyry7BMKqmbxNJHnRo5euaYVr5ApZGV8o8CEfLtyPVTk8WlYGQIIEfSN/sVo+8X18mVbFavW/fDE4ZHDCCt37NjRjRvVrYOiDPLyKKShYloNTJkXzyoEdNVVV239TeVZ0FzE80goOK7QhtAwRDGsYibkjUeV3Ew8caERTvdJO9eSMYoZ5BI5HiRvqGxW0hm1n/aJNvmoYqja72kikPb6l+bcqjWWEcBqIV2Hx0n7AVDZCjw+yGCYNR8CFGew+NPbFvFnTEOV3BPcG+UaMjLvvPOOyxUj5803JVBxRKbYMSF9WtwQgaj3QQAAIABJREFU1U2DPru0NyykyQcJg8Qge4ORE0lFNBbnHdV5IclCGJZQNMTON3L3yOGDwPXq1cv9xHzxsEIQ8V6SF0kBTpyHEX1OdDr9MRiHMDUFMORpUkkdmoa+CY+jxYjwtN9BJQpXrg9V09pyj/7g7BtlkGGkfTCIINiXolFY7Lra74ZAHAJpr395RNoIYB6vWkpzTvsB0JBUuZWYKZ2WDVNDBKgwhYxQdYo3ClORZnTwqFIt1yAStF8bM2aMy6fzDYkSpGKQYSHUWo5RZEKxCd46PGO+qZeqWKcNuojg9YOIMR8lM5BDvKOEhsMcRt9zyj54On3Dk0YBCILT5AhimrNIeJXnmP00/5JzCHv24lWEmEICqZhWU3mbOM+eEmu8+4Rn4/oeMx7En3ni9eM8mRshezyY3BNRBqmGXKtBZv3/L3YdOdfQW1tsH/vdEACBtNe/PKJqBDCPVy2lOaf9AJCoXqjhfUrTtmHqGAH10vk9bLWtGf12jznmmLJnjxwJsiT33HOPIyLlELRCByePjjy70AvnkzcIC0QrziA+aBESog5lW9q3b+/0/FQaRsfwtfaiws8qsI1HFc8qpl1XyH18+umnBRkVJUJRJJLwM8Q27C2slfsQQaqKfeNc8M5BsviN/EE8gerZ87eFxELKtQMQ0QBCxVrVG9cDWnMcdSw8nYSykxjVzHRu4aOCVoBxhmeV68bczQwBRSDt9S+PyBoBzONVS2nOaT8AiACTwxTXjSCladswdYwACz7hPj8Xj6pZRIfD8GOpp6H3V+jFYhzIDyQoynuX9DiaD4ckDEUfanTB0IIWnhmKUcoxLXaAJBEqVqOohergUD7HX6ggp773UDuH+F7BKO8rY7Af4e0ofFSiJ6oDCqLP9F6mgAOPLteWriCEs8Mwrbbq4zjkPuJlhBRyXSDQVIijDxka9wkV0GqlCHmjt4g3mKIfimfijPEhi+SOmsxMOXduY+6T9vqXR5SMAObxqqU057QfAHKQ+KKPEq1Naco2TJ0jQLswPFLox2277bZutlTNck8gRUJBQLmmUilhvprv/YrSCEx6PC2qCEPMtFrTsCzHCsOrScfXSmK6juC5UiNnjgIMBJ3JcYwyij8Ib6vMjXpV/dBtFPlmLApyIF+QNnLu/JCptumL0j/UeRGSpQBGSXAUxswLLcOwXRyh8E8++cS9FxCiDu1f//qX602slrRQiIIYJelx7ft0TPV+EpqmMtvMEACBtNe/PKJqBLDOrhpfqnE6W37yOwsFuVV8QZN4T8hl8ODBrWK5SU4r7QcALwbejEKVkknmZdvkFwHuXe5hvwJW26KVq9GnaEAo8fRQUUo4Us0vsIjqEpIUTdrAUeQREjTCrhRz8Jwxfrm2ySabyMMPPzxdwQXkGJJM7iIkL8oo/hg6dKgrrqKQRnP6fF1CLejwsWcs7eYRdmjhNyW3kEPOTQsy+A2vLd5bjoVnn/0hk2E1MttqnmIYSlZSSmoI5x8aXmEqlMmPhFxzr/D+KGYIWSP6jcW179MxyEGkuKSYpzA8JukAfLRQHBPlvSw2R/u9vhFIe/2r77ONnp0RwDq7auQAkSfkG8nzSD0gNqsiu3gE+LpGPJUvcjwrVPpFdQGIO8W0HwDCRYSNClVK1hncNp2UEYgiaYVy90o5vHbLoH2ZL06sHi7GiuoTnPQYcWLP2kYtrsI26fhaiYu4cs+ePVt3g7BBMnzh6HBMpFiQZMFTCBmD1EBQfEkcxYeOJIhDq2mfY64Dz6ZvhGcpcIFEE8al0EaNcCyEk3EpbqHymj7JtNz729/+Ns042iov9LLFkVLdWYkjJJMKbkLdvM8KVQLzjiHXlLxCLK59nx6DsDTvVUL3vFtVqqjYdUM3Ef1E8lbJXzVrLATSXv/yiI4RwDq/arzkCM/wlQwRxBCjZaEl3wnShbGIEBZiMVQx3mKnlvYDoJWSVGqim2bWfAhQAQtZoBMMHWEw9QyPHTvW9a4t19TrE5IM9POoVsV7Rb5euUZYlgKTq666yj1LahATcvY4Bh9h5RpeS8aGVCCwrIZnDw9f165dXf5slKkXkvAtlcjMJfTaabV1qPVH9S7yLdtss01r+zf/GBpepjUc26gh3q0i3kQXVOg6qh+y6jCG3lPN/4zah+NAVCH0f//7313xDAQ+Ll9Q58V7kOIVimogi4SoqR6OMl/eh9+jJITirifXnGvPfYcAtlljIZD2+pdHdIwA1vlVIwzD1zWLHDlCGKK6fIX74SIVsi1FCDftByCNRPw6vxw2vSIIRJEcqmZZ1KNCh6UA2r17d6dBR9WnfgyxvxYgFJIbSXKcOA8j3ncqU8lhI5etXIPknHvuudN5lGjJBmnzu3SEx8BTx8ceOJL3x/kTlkZrUE29aWEeHXjRSzhOw0+JXeg5VDy0MANvIP9NxS39jtUgWRSHEMJ9++23neC1moau4ySAyP8jDxBcCAeTQhIXLmZMCD7jk1cIbnjp0FDk/RdlvsA3vzPvQhXDOgadbBiXc0Leiqprs8ZCIO31L4/oGAGs86umba34slbjBQ8hRDLBN0IdmrMSdVokgPOPGg8ApBKZhKRewzi4/C9twiyEcsyaDwH16LAw46XBtIUbhQT0yy3X6HWLZzFsNUhYkzywQp6gJMeMk6tRyZVKO1UoEYPI0uNXjcIEUjnwuOFpizP1pkH88ESGOW3qSaQCl0pptR49ergOLJBAdPpCgxBxXFo5QvDUNM+Qj1DC15A0SGzYb3jChAlO9iaqpzDH5LyZA/MLTaWjyOcjn5HWdnHeQvZVbyYhYIp1kMYhpMv7JypsrB1Y9LhJ8wD96uS49npJ7qlC2+DtZH6ci1n1ETACKGIEsEr3HS9evtALGdWT6HqpEdbg5UBIzW9wDwHkS5vkcd8Qsh0xYsQ0VXX+73FzSIMAko+kpA+SyVzMmg+BY4891uVLQdYgDHiuqJrl3+RuIdhcrmlfWh1bx9EWbJBLSGa5FidYjfhyt27dBLKCJl+5hocNkhUSKHrgorOHR+v444+PHV7DsboBZAziqKZFG4TZCberka9HVXacQDtklJzE7bbbzhEwNe1+omFTHT8kwip+TX4iIVPfCO/yUcD7iyKg0DT8TOid4iHkbZgLeZKhcQ/hhYVwct54TPWdgwi1dnLx91PvsP4taR6g/64sVmRCVTof5Nz7hXoeh+ejGox4QInymFUXASOARgCrdscRsuCfQsbXrF+FR6iHr2E6B/jSDeWGgLP0ADJHchVZ7MlbtHZOVbu16upA2vdXw41UlhIexCg0QOuuXIvzoKlQcqUhWm1ZFxIriBMerNCzVup58HFGsVbYTSOuOCQcX3MR9e8hoaOlG0UX5FySJ6imxRu+NI8/NpEE5kTFLuQK4xmGUPnEnQ9UZF5CT6t6+aJC2EoO46RaVHuR4hIEpsm3iyuG0XlyD/FxjCyNfmjGyf8wLufPnAnr8qGaJA9QK7bBotiHBdET7u0ofcpC9whpBaQXWJFJqU9SOtsbATQCmM6dlMEovHgRjmVxCMNCWgTCS1C7EvAVyeJSqyIQFhyq8XgZ4lE0a04E1EuFLBGVq36FLsLApXhIQgQp/mCxDJPy8VqRpxXlgSrlKsQRTLxNhGmpwlXpkVLG1W3J24VEhvNUQeMbbrgh1nvPGIQ5eb40jSPUK9T2cBRjQXTU1JMXClzr7ypEzccnhJ2PNyIMfJDy4Yl3jetGhxE8uKGeoIamwQny7BuyN5CpqH7AvOOQ1uF88KDxgUwEJK7amvAt7z6Ki0gFwJgz+4e5hzoHldWiCwjEmHulWB4gOJP/pwVFaEBy7lHmp75AjiHpST9+Sb/hHc57m9Qds+oiYATQCGB177gSjkYiNCGnsG0UQ7CQEjpBm4pFkZw78pdYXGolA6NaYywQhPrMmhMB9ZZp4jy5anzI4K3BA1OJaThRZUl0LBUThkhBOMq1OKKnxRVxeWxJjwdhY46hbIkKqEe1uAvH7ty5c2t4N2z5xnuAylhMQ6K8K/CSkW8WF4LH2weR8juNEELmWH7lM79zHSFcVCVDEDHIFeQzav4qocO8wgiIr99Iz2CIE949iCEfDhBBNf3AZBvC/NxTmLbXw3MZ1eWDymZC23gB+SihkIVqbz+nOsQYmR26zhDNAL9C1eW+SDjjJC3C41lQbzgakBBbs+oiYATQCGB177gSjsbLiq9a8puiDCFoKuxCIeioPJi4w6b5AGgeFi9mPApmzYmA6tVpvhw6dQgcF/KiJEUKAeiDDjrISSARzlTDe4IAcbGFvdhx4kK9WiSBF5APrnKNqn39cKOaV007VSQJTWqYOkovL6rlm7Zzg8xA3OK6mED08MKpiDveSN5BYThWJX3U+4gHDFIIUYpqw+d7DSGa/vGjBLYpcOHveO44thqeX7APpWy093QcdqqxSCEH3mm0ECFeVAfH6QHiIQRnjs95YnF5zZBRX/KKsG5YnBd1v/idTLgn+P8sjHuiEq97FnOqlzHTXP/q5ZxKnYcVgZSKWANtn+YDoPk5hboZNBB0dioxCIQVs+pNqVRDj8Np31pawpE7pUbBAAUcpEtQqFCuabFHuIhTlEChBIUB5LuVaxpW5SMND51aKVXSKkkT5hHqWCrGruFe/k1YtViFtFbjars+JUFh2Ftz4wiF85t6+AhNE3YOw5/IqOCBxKsXeiw1p9BvgadC4r5YNiSTbfAKcn/hXVZT/cE4z5t+NOAFZF/6JUP+aIFHyDbKdA5gAPHE8PSxb2iaYwipJGQMEeZvFI4UMiWmbEMaz9SpU8u9rWL3O/300124G28uOJlNi0Ca619esTUCmNcrl8K803wAdOHXtlEpTM+GyCECWpChHwJpFWgABUn2kDzCc75nPK0cvbjx4wSoS7085MaSW4ZBFggt4hXTQgZCpBrCLTQ2mBLuhNSF5lfVQhLxlFIFTAgUL1mcoSwwbNgwpzFKyBvheXT5QskdlcpRMWsNvxeSyIE4UaThdy1hHoQ9yevzO5Sop4/jazoL4thUEZNeQuTDL4gjn5LzIrcPkhcauYJUjaM3iFeTNBlyMalUV3Ln7wOB4xpwrSByFK+QF4neIt7J0DRVh+tBb2I+IsiJRNKmkGlaAdvgFYXkpu2pUyFrPJ+Evs2MAIb3gBHAJn4q0iSAGvoLvTNNDG9Tnvq4ceNctw8VKU5LQw8wyTEjzBu2NFM5jTih46QXIiSvup9W6aJjRx5guUY4jrAj3jDtduEXyeAtiwvRJj2mVpZScYx0jYa1IYEQnziDECFjoh4/vGyQqrBtHQSRSm/Nh9T/JzQPgYwyzREMvXRaFe17XDWcj6cRcoVp8Qfzw6vlW1x/Zd1GRbZ1ftreLi5dQMP0GibG81hIxFzJKR8lYE0lOl5Q5GfI9YwzwusQUrU4D2PS6x61nYbH8Y6TP2tmBNAIoD0FrQikSQB5+eNFKLbQGPyNjUCY5xYXVi0HBS2iCCtKtWerXx1azvhKXsM81i222MLp/2nYs5yxdR9y9wiVUjQBQaBtIucTVu6We4y99trLhcpRDkBYupgQsx4HjxVadOrJw5tFXlooHaNCzCqorF1E0HzE0xZl2mM51LvTinH6IDNnDG8eXj0tJlOhZEhzlJC4ahzy/oHkhRZqR2qxWlweIF5H7iMNsXNtuEZhxbUeh9Z+yN8oodT5FOrqwr6EiP2+zKF3tNzrr/uBF6kGeJityCQazTTXv0qvV632Nw9grZCvg+Om+QDol7WGWurg9GwKNUBAJUVYYKnyVJHhSjX0OBXytkgxwLNBwYKatigjcR8h4XJNyWtYyY53h1zGUnXeouahxRbIhagcDKSLilqKHyo1xUK15fCKQtrC9nnhcbSbCsoCeLyowCUkDWGiSllNc33p/AFpUYLE3/HkRVlcP2BEr/Ho+cTdrwwmbIznChIb141DPWlxBJSxIXXaHxkvbKE8QEgwZBivMh8W5AmSqxgXYg7fe5rzSpiaCnh0DkODnJH3SSUwaQDkg5LbSfQkNOYLyYaE4pUFS8h5MakZrp1WUYe6kJXeY42yf5rrX14xMQKY1yuXwrzTfAA01EJXAxYcs+ZEQKtOWaDIpyI/jyraSjX0QJM+vJCRsKJYW52RV0VIslwLyauOQz4jZAcvIMUSlViYo4ccCZWtYVi73GNAqCBW5OrhnWJsjsEzybMZZ34nH8KRSh5CgWXVGqTog/A1It9cZ4TgKUCJMi2i0fxC3UbzDkNyqqFLvG6Escn7I8UEsheaElzC0pC80LQ3NbgQQsa6du3qCkLCPECIGQUZFKsgqo0MjhbH4MnGuxqa5vL57f1U1xEyjpczNLT/CC0T7of8U6QRd35hKzvG4mMBUkiepErxhMfQZ4W/Q0bJOa00vaDce7Je90tz/avXcyw2LyOAxRBq4N/TfAA0DEfbJ1pemTUnAnpPcfYkz1OFSPVspRp6jKeSG3hPOI4aQrrkkxUT+C12RfB8QQCUvKqXRaVJCBGzYFdiSg6oAqUlnObO+jlvlYyvVa8aooVY4sWDBBKmLGSqqUclNQQDcodHzvc2+fp1kCTCuxS2oEEY55XSPMGwxZsSsTDPkHmS70nuJTl2hM2pkvW7JOl5qMczKj+QbdSj5/cX1sKQMA9Q7y9CpxBijlesSwvC13gf/W4eWtwCLhDosLhDC0eQj8Gbx70QJaLN/NWjyLXhHrnrrrvcc4XFdVfhN9qEEvpV83UbK7m//H3xzqKziMeUZzJvlub6l7dz1/kaAczrlUth3mk+AOT/8GKNexGnMF0bIgcI4A1SfTU8SXhZyEerVEOPU1fPCeOT26QWtciXA5UffmSRpUsFRlgUbxdeFZL8KzGtQiU0jtdIxa2TVI4mOW5Y9atzD0O5UWNpyzjCpnzERXXvYD+t6iW/Ds9a2Hs4HFvz6sJzVFFr2sUh7q1G7qLvOSv0UXnSSSe5cK1fNewfXwtI8IbiFcU01A/R48NB+/AqeWZekFsMfUkKU0gtIMUgNPUw+n2cKeaB/EGWo3L7VLaIqmU+LnhvxrWD01Z6G2ywgdNo5L4cPny404DVcH3UtdTcRP0tLsQctS+5n2DFM4sHNs4gsJDmYh1skty3tdgmzfWvFvNP45hGANNAMadjpPkAFAvF5BQim3YZCECcyGsiT4+FE7JDHheewEoMb4pqsUEAlWiqbluxMGexY/vk1e9EgSeMhZecLnL4KjGVUdHwY9g7uZKx2Vf7BRNGZXFWiZmws0bUccjfpVCDkDdkN07UWAtECGdDLAnlUgEbZyoVE3qstDqY7i14RtWUiOn/Q9iYU5Rxf0FENeQdbqMFKHipIKAYeXWExvEyYninIZz8G0JINANSiR1xxBGODIdyOHocLYKByFNtq0Y+H1XPSvT9eemYECw8e4wd1w5OC2X83Go/v087voTnjUwP56EW9o2Ou1YIXnN96UBF8ROexDgjFYOPPD7+8YLmzdJc//J27jpfI4B5vXIpzDvNB0CrD+NCGSlM14bICQLqIaI9Fx4i8qfo4sCCV4lBwiBjGPeuhp10saWSlIrSSoyuFuRLacgsjhSWewz1lCuhCIs2yh1X99PWe5Bw8vUggn4/30Lja1GGbhNXyapeTN0ODxZewziDCHGNIHwQCzUtNAm9ZBr2ZDuKMCj+ibO49oC6vVbbhiFwvHR8lHB/kvsHwYRYEWr2W9qphzFOSiUuR1DD3lG5r4RmIVZULpOXB85xlboaYvY96MyX+xTyF6dPqDqOigN5uKRIFDPyKPFmYsV6a+NBRb+wkAZk1PEg4BS1UAWftvZhsfPzf09z/SvluPW0rRHAeroaVZ5Lmg9AGNqq8qnY4eoIAb89Fwss1bOVauhxeiwcmsjue7TSrNJVUkKHC7onxIWFy4UbLyiFA5oPpx5Bv0ih3LHZj566SowJ+0FQaDVHF5JiFnre4ry2Wlmr4xUrjtF2gHwY4DHCCvUo9gtSLrvsMiG6EGfF2gBCMugjrEUd4ThULxPm5H7CICQcXzEkfQHyxDZ4B0PTsHkol6PV0lEdcLQSnDlxf+GNjGsHp+kNVBvjOVTT8GvYMk9/V88k23H+SbrkUAkO4ebaYGHPav/cIZ+aIgERZC1Rb3Ox+0ylhNK654sdL+73NNe/cudQ6/2MANb6CtTw+Gk+AGlqpdUQEjt0CgjQFQEhXDw/vOQhCCpMXOnwJOYTpoLQQGwwLXTwPTflHoeqSsZWmZawqrmY/Eax46psiGrfqeBy0hBdsfHxDuElxYupuZdJu/MQiqXQQC0upK6kSLfDa0bxTJxF9QP2w5h4kfzuHowDYcGbSd5boQID1S/08/b8edAthflBbrhPooxrTASD8w+7zEBAydWM0zdVIhYSTN6tFK/w0eJXSHNduD7aGo+8VryUce3gtJsHhTlgoqZe7zhtSt2Pym+IPdXzhOvjjGsAmdU8V0h7KIfk76vXVP+GVA4tB5OYipXHhb2TjJHGNmmuf2nMpxZjGAGsBep1csw0HwASwamSDF9UdXKqNo0qIuB7RchFIqRHNSdVn5VaKKTMeOrliRPrLeWY6NsRuqZSEzKk0jBh5XEpY/rbhh6ruEKIcsdnPyWxhB8Jvyfx/rAfcit4b9UIU/JhF5oWJvB3rge5mYWIMeFWJXjaD1jlZCiWoDdvuaYVt+St0fc4NAS2ec/hBUMPL87weqH1xzg+BtqzlxxFCGJoWmQTlaeokj9+kYt6Q7VyGnKKVmBcOzjkYiCJYe/isCVfOC/1wlMMQiELupzgEHedkOLB40tOIuFywr94+LTiOBxfBcz172EOZBzOFMbMPffcLnSMl/KWW24p99JXvF+a61/Fk6nRAEYAawR8PRw2zQcg1Derh/OzOdQGAV/qBAKIV6GQUHAps0RrDo8NlYrccxieQPTSSvFCxB0z7C2rnSPiPDSlzJ1ttd+w5k0p4SwWRi3lOCpeTMUyhCOuQjYcExLEoq8V1nhxqQQOTQtN+LtWpxabn0rMaGgd7TvI71JLLeWKVco1PIQUeuCJg5T4hpcN4llMp7DQsVWnMY5gqkeagiefODKm5uERusXzi6nHUvPr/F7QYaEOxJnxo+avuYmhtA7H8LuAQHz5QFKPI4UboXGP4IVkLuTRko8IScPwtkeFdrVji46VVOcTGRuKtjDtthKHP/miyAtxj5VikFbmh1Mi9Cz746S5/pUyv3ra1ghgPV2NKs8lzQcgLhRS5VOyw9UBAio+TOiJhHJCeWlo6HFqtGkLxwvz9iqBIOwtq0QlrW4KGmbVgggNUT7zzDNuEU7DFH+qpCERkHCKTpKYelPZlnxCLbrx98VrxbwxXwC50PjaMUQrfrVHdNLwdNzYfAhAzvgwINTqm5+n9uWXXwri1aXa448/7ghIFFH1x8eLiVfPN+RREK8mNMrHCaZ9q/3wpxZNhcUwnA/eQa4jx/KFnDU0DZki/9A3P7wOgWPufCBFPYOQS8go3lPSEfhA0Z7VjBlXPa59s/W4SZ8PP3+0mHwQ86YYi/C9342m2DXU9n/F0irSXP+KzalefzcCWK9XpgrzSvMB0IWMFwkvZLPmRUAT15HPYMFjESkk5VEKUmGIln1VpiWuIrKU8cPesuQVIhicVqeOkLBo1XEaEjN6nqpdp/9P2BnCkcRUhJnQLt6XKIM04JmCXHKN0ekrZirHouFQ7R0eRWCKjeX/rh4uyB0kL44IMddyOmFoyJaPDC0U0WP4eXBR42tIneNSWEIYlmISwvI+KafYCG9XqNWnntaoIh4NfUfl9oVFN7TRo1gkKl9Q+1+T4oAHVXM5wZMClbjQOaFbtBvJ99XK7rBrTNR1VEcBvxXKS/S9t6WKyOv5xnVi0Xmluf6Vcs/W07ZGAOvpalR5Lmk+AFG5WVU+HTtcnSCgBIQCEHTuCMmkQc44Pc0vpAMBni4WChZY/l2sGCEJPBRnkPelVZe60CUNdRY7Bh4NxH8hfiyYWkkZ5UEqNlbc7wgW+5IfpYTfkTtBqBhZFEh7nOHxIT8yrgo13C/Uywtb1pV7ruqN5B4ghOnnuBGWpeK2UC5bseNSEEROJZWueOGSkk/dTtMTNKdUw/N+rrR6ncN2cHrvhYUpjE0onRA/oVruI9+0Cwi/k36hGq1UoJPn5xv3CfdLmCequYdxaRVaMc4zCEkkjA8p9buPhNiqRJH+HW8+91CU+d5ViDPXOWm3Ec3LxPsKpnGW5vpX7D6q19+NANbrlanCvNJ8AMgT4QXMVy8vD7PmRUBznxCiVU0xTf6vFJVQ2JcQl7YIw8tC0n8ldtBBB7mqSTyXzJ+uCyTcx+m0lXosiJ7mV0EuyBuDtOBBSksTDS1OX3NR8+6SzBVBX7Tn6FJBUUSc4a2iMIFwW5J5a79mlZbRbh9J9emKLeL8ToWt3y6OYh48xr78TBIM/G18SZpQdBlyBKHjfcd7L8r0g4IiCzT2CBPz3vWviW4TaqhqxTgedcS0fcPbqSFnCiv4oFDTQiPNsVOx7CgpG/V4IziNx0wN8sgc4zqIqEA1JIvrj1czimD6c0YKig4m5INCWgt1MkEuyM9XjBLUjsLbF4tHAolQdbF7p9z0gFLvpXrc3ghgPV6VKs0pLQLoJzInCQNU6fTsMDVCgHaAdLrA80CoDwsXqXKnxqKGR0tlZfwFOi5hvZRjhULNQ4YMccn8abVq84Wl8Z5RMBPlxSllzuG2hPr22Wef1j+X8kxC1GlLRncPcrTSMi1agACAqfZv1o4o5R4nbD2onWIYD4JKjiEePDyv5Vih8SFHSJpAMgm7RpkKVVNNzccEIVYIE15xvIpYnBi4kmQIOeQwNA3TUlFN7qaadgHBE3/llVe2Fp6Egs3k+hHaJtQfVhnj8Sb/ES8k3tvQ/P7OhIFJAwh7K4f7qOQRH1lIDJG6QZ5plKmnXH+j4ItcwGIyTJqzy37FvNhprX/l3Ff1so8RwHq5EjU1IkpxAAAgAElEQVSYR1oPgP81GteaqAanZ4esEQLa3gzvAl4kXtospMVe3kmmq4LjmuCtIUAWVbxolR4Drx8LKMnqdLiAoEBo41qNJZlzuI1Kk6hER6FQWDnjawiQfSEZeMYqxaWcefj7aD9g8sbIA9QevXhb6YRRifmtB/1KXMKueIEKEbQkxyUEyQcM4UqulRphXD4MChUzaBU54ctRo0Y5aSFSAEiJUFMPXaiLt9tuuzms8MryYRKa5g6GFeTqgaezCx54iBMFRnjUIPhq5O4xBvjxDvcrZrW9Ytz18VvkIe+EJxTPHp67qHsN2Rd+h/CRV6uhYt4LUR5kQtfkCIIb+/JxF5LUqGunxTH8VkjHkN/TWv+S3EP1uo0RwHq9MlWYV1oPQNqLcBVO3Q6RIQIaHqK6kJc2CygJ5WlYmKPHQkq1YCFvQinHVe+JtkFTz1VSKZUkx1KNNsaGLPtVokn2L7aNLvhsF9WJotj+WfyuenobbrihyxvUXDhIER8KlVhcFThj88FQaaWxSg+FYtJ41xBahswibxJlEBzyo7n/8X6SXxl6yvgQiGoHp9qqfh9j/xjaUo554O1TC/Mt/Q90v4WiFuJQNIFou2/FWnuqDiHkFQ8m3khIGrmAPI+hcc05DiSUZ1bz+fz5+Pto9TWEGxzw+KtHs9C9oh58tonTVtT901r/Krl3a72vEcBaX4EaHj+tB4CHnuqutMRyawiJHToFBPDOkfNF6I1E/GJf4qUckoWSBVPbSGkyfFSVZinj6rZ4/VhE8L5AWjQ8hxeQY6ZhhKYIGZKTRbiWMCJh7bQM4WDNwy0mtZHWMYuNo944woXk5uEFI8yXhjxQ2L1F54KmHUSGrhmEa8s1JHsIs4YFL5ovqV1d4sbXLkl4fiFj3F/sq6YVvWE7OP1QQEgdEhuaFnfQWpCQrFpU9xCVmsEjqZIqGoYnN5EPEd8gq+TsMS7jh4bXDykfbfGoxyQXEMxD07QQ7nlC4UjbEIKOK9xSLzaYkDLAfYynEmkcCHUxrPV3JHHwPEZZWutfufdVPexnBLAerkKN5pDWA0C1IA9qoaTeGp2iHbYGCLAI8KLnhU34sVKxX/8UtEpVFyZNxE/a77YYHFrdqPIkusiyQLJQpmFayEKeFTlLSjbTGJsx/MIYDbmmNXa542hIT4l6MZmRUo4TJQ3E/hoOJPcMslKuheLgOo72dS4mU6JdNnS/sKBBPba+2DieQ8L3/BsNP/QAQ4OYMQdy6jTXlm2UEPvEUc/Brz5WTc2oFoqEj/ng8UWs/eOHepnqeSMXEGmg0LRdoxLEYh1atAIasXA6/EBa+WjiA430jDgDJ18Pko8NPjqiTL3SVgRS7pNh++UagbQIoGpJhbktuQbHJl82AtrtQgco1oe0lANR3UpCvFaPsjhQSFGocX0p44etv6hyRNA3Lg+rlLF1W628RDuTxaoYgSjnGFSIsrDFLeDljFnJPh988IErgCA/zBeYpgChkEcnyTHxjpFqEIaTNRUBjxTEo1zT3rWhjp6SnmLeYfV+6vFVDFv/XwWf/ZClL28DoY/SMNQQtN9RAzkkKqHJm/O7k+h9jOwLz46ftkNleiiSrbmvcf160XpF05LQNyFwFb1GpokuHL75/bTJQeQjoFiP5rBlIqFzPv4gc3j9o/IMdT3j2EQduOdCrHVe5HTyjJA3bASw3CfD9ss1AmkRQK2GU92pXINik68YAcKZLEpqaYYhw5w8FWoOw2flngRdFSBoupCFwtDljuvvR4UuZEINKRVyD9M0FdyttMo2rTn5SgEQBzxCxXK0kh6bEC85bKGOnnreknYriTsehR54zghFEhpV8/UuIYFxBuGFbODNw8KwZ1Q7OG21hkcLD2CUaTcODauzjS+D4hfk6XOjWGhLurjnBi8lbebIoeSDLjT1HpKrh06havxRSMK64svxqJSSn+uqHWceffRR1xIwNC0aUgkcxiQXE+IWt49WfbMd86NNIPI5jBGa38vYCGDSJ822aygE0iKAmmyt/S0bCiQ7mZIR0ARu3bFYz89SDqBFGiTfIyWh3sYosdxSxtVttVWbLqoa6sLDsfvuu5cz5HT7+O2w+FG9MqkM/vsgGmYOSVGaxyh1LORu8DaRm4dHKq2UEZUXIeRLyF4NOZtBgwY5XcMoGZWk8w/zTnU/xJO5//BOQZYKGeSHLknkSUM4Qg9W2A5u5MiRTn6lUAELeYnkJ/q512EXEJ2TkjDVxlPvJV41pGpCU094VIEI2+p8Vc8QzyMFHuTchTmL6n2kwh59TYyqZELf9FqmKCa0sBiL3zUdI07gWYtpOEcIN2FkiCQFXKHpc87fjQAmfRJsu4ZCIC0CqMnWLJaEO8yaGwGVvvAXSjwoaZgm3usikFaiv85NPS+aU6jVqngGtYl9peehGmo6DkQWQpum4ZVnEQevpB0U0jx+1FjaD1irn5EggUBUalqxGooZh/mi5R4nLtQb53mMOo7KpsRVfIft4LQYqZD+JN4wKuwxFUEPu4DoXFQfT6vClZDGfdhoYUpUC0TIHsL/hE/9/ESVjtEuOhwbrydEH88kHjnyXjGqwfHkaWvAELOoHET6ZeOZx7vIh4TvZWR/QtuDBw92OYLMDWLOvYYnODQ+jPbee2/3ZyOA5T4Ztl+uEUiLALKA8XVWrHtArsGyySdGQKvCdQdCnngg0jANTVGFiJdE771Ke8rq3LR7BJWDeDPwBE6cONGFGPGGpGGam6Zj+Yn5aYxfr2MQ6oOI4NninFUSptL5EtbE+8dCz4KvplWulXpYlbCriLWOryRK2xIWOg+8Ypw/Y/kVu7pP2A5OyUyxfrbqVcXzRzFM2AVEx9c8PDT30OojD48q3LgCE+aLVz0qrxsRa2SXMF/GRfU/qYomrYHnk38oACLHkOdJtQZpIYf3L5Sw0flSTIJn0vcaQjwJiRNCD7UP2U/HpDKZXEMKZBA0R5UgNG2BZwQQVM2aEoG0CGAondGUYNpJtyKgi43+IVw4K4EqbM0WCgxXMjb7au9XvAtUMKsUB55BvA9pmCbv61hpkss05pfVGBoyhVQjQgwRJExXqRHixdNJyJecRzXVw0sSoi00B22th8fIz93Ufsi+Z6vQONqqLqqAQcOk2g4urj1cOD4FVhAsDaVq6DQULmeZx1sIeQMPnknubQpFokxFoqO61MTpvoa5vzouuZ4h8VWR67iqXs2vRGeQXsVqqj8YXmt+V2khCsP4kOMc43IYfb1A8wBW+gTa/rlEIC0CGJWvkUtAbNKpIOBX4zFg1Mu63AMRMmLxUO+RfsnHVSuWehy8FHhHMMJI5DVRqcqCSL5VGqYdJHQsiiJIxm90U08dGnBgW2lxhuKlHrown03bBvLR4LfGKxVnFUymIIh8ZzXuDbxpEDAK4CqxsB2ctmKLK2LQY2nYVTvjqOdMu4D4c9L+vuQVPvnkky4Pk1BolPmVyRSp+KQVjzgknuptng01wtAUYEB0kbABf0g/cwy1+Eh54EOITiXMNTQtvMELyHVV05SPsHiFcDipDhBdrgnhZT4A4nKDkUfSjw8jgJXcubZvbhFIiwCij8aDnGa3hNyCahN3eT8s8mqhUG0lEGmVLrl5VP2pFlpaUiosXrPMMoubIgsDZBBJjXfeeadVXLmS+bNvKAuC15Gcw0Y3rUTV84wSIC4Hg7iPACVRlYbYIWEUAPkha19uJY17I2wHp1p+WmUbhwvFJ6RFKJbq9YwqftA2ijpWIc+on1/oy/awL+QR4eeoHst4yvEQUoih+YlRcw97bofbaJeTkLx/9NFHLqcQQ+ZF/1u1FFVnUnMe4zRItcuKPuehDE4592Ee9zEh6DxetZTmnBYB1K9XXPW8yMwMAUKo6JdhGtZKA5VQcoh7DgJQLFcq6bFZ2LVLAeExFjksDb06nQPVoOSPqcW1w0o657xsh0AwxRBqfrFAJeeAPAsfn2FIGS8RIvUURtCNo1xTqSG/ICL8UKiUQPi5e4Rz8aDhJS1GLjX6oh5wPF7k70WR3r59+wr5p2qFPJc8B+Tr8TFHZxl0+9S00KQSfU91GsQJRytBI4eQfF/fVFTar3BX8Xkl6ZMmTXLaoFwXPuRCU4JtBNByAMt9L+R+v7QIYFwSdu4BshMoGwFCPhoe0vBU2YN5O6rEjH7Zq6RKVMir3ONplwq8GXgaMcgslY9pmPYvZizyo8IQWxrHqMcxVCxY5xbXNqzUuYd5obo/9whYF/OiFTueCt2jLTd58mS3uS9sDVGjuKIS89vB8d+IZjMmWn5aOBE1PjmJhLdVgSGqC4jup2LK/D+dOHg+C81bpV7CbhqahoHUEPl25Zh6POP6+2q7RPIKEeL2TT/6/LQPrRrWSADhaBUY19xLHQPKA8HmucMsBFzOFbR9co9AWgSQ5Gi+xijB5yvTzBAgpKkCtmlq0WmoB48EngnVBkNfjIrBNIzFlwWecDOV7SzAhIHTMl+sl0WWnKVmMPXe6rlGtSArBwfNqSTkS0GGGt0gqAb1+9+WM35Uv2kVEoZIQTYqNb8dHHmGfHiQT+e3NYs6Bv2JqU6nIIU5RXUB0f38Ig209/A0FrJQ7Fm31RZ7YU5kKRiQ24f3L65VoRZ0RPVB1hQKnlPwIT9RexPjZWZcP0QfpljwvJG/qWYEsJQrZ9tmjgDua2QA+HJl4SF5lwXOl6EgNEByLBWE9FwloRcCVoqXIi0CGDYGzxwgO0DdI0DBBEK1GH1YEetNwzQBXasT9eMjzTCzVnciMUOf1TDZvdLzwGOkXh06drBwN4NpP2A9V0LhtBSr1OK6wVAUQP4aXjvITLnGu5aKWd6tmtYQ6kWWO7bu57d+I+eQIgjNcy00tnqTIX58cGkBk98FRPf3Pc9xxRf+sbTdWyjWjLg2hV30+x4xYkRZpx62egsH4TwoyFJ5G/93zo1nkn/r79pZhI8M9BmxDh06uI9E+oX7KRfau54oBR9jRgDLuoS2U1YIsACxMNCMG3JHrgwPDA8wX7XkZZDfwkPCwsdNjDuciiuSf5NaWgRQq+14GfBSMDMEVCMNJPyXcqXIkJeHmC3PBZIWpXRjSHpszR3jo4tcJRYSSECapuSkmbrnhPJAaRW/aMI/700+njE07sjlxBPkFwuUcw0hCHSWwJRYaRu2tNpf+u3gVCg7iUwOhFQFkelugZNANSzDc+UYPDesH4RuCeEWsrguOGkU/VGBi/cPbUQqdkNjnmDt9zP2t9EiEXIakXuhcItr7rfZ024j2q9Y94fQohnItYNAGgEs56mwfTJBQGUo/H6HX3/9tUtm1YWUHBFK6/niI0yAofqPRhJVUkkTktMigFptx0PNS8vMEFClf5CgahCik4YR0uMjSBd5GtHjAaINFPd/GqYJ6ISS+KDCm4kMTJqm3gkWMp7nZjCf5HC+VJpqxXUl56+dZwgJQgB0bK1CDatYSz2WX9XO+5UPbyUwYdi51LH97TXnjnsakkLBDB//xYxKWOZFXh09iQuRUsSaEWpHgsWv1I86RlxkJ0qkudgcw9+jCmt0G99DznoYSsiwnYqp8/xQBEbOICSdvEaVrCHMHfVuUPF4cgsh8kYAS716tn1mCPDFSlsgFiEefpJV+TfhXUJq3OToXpEngitbjdY4hMUKicrytaghDPbjxtdcraSkMerE+YojvMNLMUzYzQwoG7iuESCExcsVI48H3bA0jI8WyBMGGcQDSKoEC1paHx8sfDxH/Jter1QdkmuVpqHFRjgbnK644oo0h67rsQilkjOH14rrl4YRGSFcCeHTnDkIER5BjHdjpUUafGhDWMnVI5xMtAMiRHXxzTffnMZpuI8k3vEQQYgPZI0ip2LGxxYkmHxV8lbx3HHfVmpIzKC7R0cNquzV6K5BmJrOK35VdynH450AeSPXDx1M37g/uE8w8vWi0pr4IEOKhvuI9ZHiD4TacZKoUZyIYyScP0SZ6BrSPvyubfRKmX+jbGsyMHV4JXmJkTPFy4YXF194uLFVLJYHENc4Sb2+QRYJFaMiH2U8COimmRkChoAhYAgYAoaAuNQqiGgzmhHAKl31JOSLZFXyFhDsJFxCVSO5ELis77jjDpfMSpgDAkj+DHpMvvGlxJcpXzZRFnoAyZnAZY6LPao9UVJo1CtDSLoST2LS4+VtO8Mn/ooZNoXvZsPH8Cn3fWf3TmHkNAKGh1hzPMvFOq/7GQGs0pXDpc8/hQwNJ8JZhBW4KX0yRTiD9jnkeJQbAs7qVNPKJcxqfrUe1/ApTACR0mjmPJxC96fdO8UJoN0/0RjZvWP3TrG1zwhgMYSq/Ds5HHgAWRD9VjqUuVPpi+ClFoFQ4o5HECMng99LKQJJ69TsRWMvmnLvJbt37N4p995hP7t/7OOq3PvH7h0RI4Dl3j0Z7YeXcLnllnN9J/H0EQKmGfn555/vQsC031EZGHID0WQijEsFJMSxFBmYtE7BHiRbxMu9l+zesXun3HvHCKDdO3bvVIKAEcDK0Mto72eeecbl//FvcgGpCoYMUtauhi4Z+kehEDSFINU2cgupqjruuONc1bLZtAgYPvF3hGFT+GkxfAyfct+ndu/YvVPs3jEPYDGE7HdDwBAwBAwBQ8AQMAQaDAEjgA12Qe10DAFDwBAwBAwBQ8AQKIaAEcBiCNnvhoAhYAgYAoaAIWAINBgCRgAb7ILa6RgChoAhYAgYAoaAIVAMASOAxRCy3w0BQ8AQMAQMAUPAEGgwBIwANtgFrfbpXHzxxU6K5v3333fVyvRlpDdwsxtV0SNHjnS9PZHyWX/99eXMM88U9BzNpkcAvNC4pLco95CZuL62/fr1c7qf33//vSyzzDKubzDdgprZfvnlF9ff9brrrpMPPvjAaaEig3XiiSdW3PM3j7g++uij7h387LPPuvcwfYCRBFOjvzwtQC+77DLXYICew0OGDHHv62awQvigssF9M3r0aHnjjTcEUfHNNttM6BdM/+dGNyOAjX6FMzw/xKe7desmkMBOnTrJpZde6trW0ai7Y8eOGR65/oem0Tkt+WhQzoKFrM/LL7/ssJl11lnr/wSqOEP0LXfddVfX+WbjjTc2AijiFurVVlvN4dGzZ0+Zb775XM9SugUtueSSVbw69XeoAQMGyLnnnivDhw93JAa5rP33319OO+009wHRbMYHAh2kVl99ddlpp52mI4B8eIIZfeL5iAAnSNGrr74qs88+e8PDVQgfGi7svPPOcvDBBzuNXZ67Pn36uHc291WjmxHARr/CGZ4fX5K8dIYOHdp6lOWXX959feLRMfsDgY8//tgt4mPGjJEuXboYNL8j8M0337h7iI8IFqZVV13VCKCIa/nIov7YY4/ZvRIgsO222woi+HhD1SA+s8wyi1xzzTVNjRc93X0PIN4/PFmQGrzJGPqA4Acx7N69e1PhFeITdfJ8kK699try9ttvN7wjwwhgU93+6Z3sTz/95F64N998s3Tt2rV1YL7AX3jhBUd0zP5AYPLkyUI/Z7yAK620kkHzOwK0L5x77rmdR2ejjTYyAvg7LiussIJsueWWQrtHnqWFF17YCb/jqWh2Izx3ySWXyH333ec8Wi+++KLrn07qwB577NHU8IQEh7AmHuPnnnvOeZTVtt9+e5lzzjmdF7WZLAkBfOCBB9z99MUXX7ioRCObEcBGvroZntvUqVPdooSXgvw2tYEDB7qXCuEFsxYE+ArnhUt4wTw6f9wVN954owtN8cXdtm1bI4DeAwMe2N///nfZZZddZPz48c6LQ5rFPvvs09SPFs8T+aJ4sNq0aeNaY3If0Ymo2S0kOOPGjXPpOeST+jlthxxyiPNw3XvvvU0FWTEC+MMPP8gGG2zg2rFee+21DY+NEcCGv8TZnKASQF4w6623XutBeBEThqH4wawFgd69e8tdd90lY8eOlUUWWcRgEZEpU6bImmuu6bw45N5g5gH849aYaaaZHD48X2qHH364I8tPPPFEU99DfDgcffTRrvCBHEAiDpDjc845R/AoN7PFEUDe1xTLqOFJ5hm85557mgquQgSQghA+tmiz+sgjjzS8948LbwSwqW7/9E7WQsDJsDzssMPk9ttvd0nXiy++eLKdmmArMCF1AA+OGp4cXtAzzDCDy1Pyf2sCSKY5xUUXXVQ233xzV1SlRq4teZJ4c5rZOnTo4HIk+bBSAxc8Ns3+4Wkh4MJPRhwBhPxRiEbI/KGHHpL27ds3xSNmBLApLnM2J0kRCJIUJPCrkbtEuLPZi0AIU0H+SMjma5L8P7M/EPj6669dCMo3KjkJvZCs3ux5knvuuafz0PgpA0ceeaQ89dRT03gFm/GeYnGG8FEdrcb75qqrrpJJkyY1IySt5xxXBMK9c8wxx7jt+HinIM2KQFpgU/L32muvycMPPyzzzjtv09xDRgCb5lKnf6IqA0NCNmFgdKaGDRsmEyZMEDwYzWwk7F9//fUyatSoabT/0JlCF9BsegQsBPwHJoR6ya1Fvw3PBDmAhO14xvbaa6+mvn3Q/CNRn3xIQsDPP/+8kNN2wAEHOFLTbEYlPUVmGIUehMKRD6K4CjkuMFGCzIcoedp8lDaLDEwhfMiLpIKcIpk777zTVUergR+pGI1sRgAb+epW4dzw/p111llOgBSvDdWcJnMiLpQZZXgpWMDMjAAWuwdYkChswDNB+gAFIVYFLIL3+KSTTnLe9Y8++sgVN1D9e/LJJzf8gh11z0DmIHyhkQ+J9p8KQUOYfSHoZvGyF8IHQfG41By8gXyUNrIZAWzkq2vnZggYAoaAIWAIGAKGQAQCRgDttjAEDAFDwBAwBAwBQ6DJEDAC2GQX3E7XEDAEDAFDwBAwBAwBI4B2DxgChoAhYAgYAoaAIdBkCBgBbLILbqdrCBgChoAhYAgYAoaAEUC7BwwBQ8AQMAQMAUPAEGgyBIwANtkFt9M1BAwBQ8AQMAQMAUPACKDdA4aAIWAIGAKGgCFgCDQZAkYAm+yC2+kaAnlCABHb7t27yy233OJEbOn6sOqqq+bpFKo2V1p80Ypx+PDh0qlTp6odNzwQAtYINT/77LOur7OZIWAI1CcCRgDr87rYrAwBQ0BE7r77btdbGjX/JZZYQuaZZx7505/+ZNhEIHDRRRe57hgPPvhg66/akeaJJ56Qddddt/XvP/74o+ug8dlnn7n+p9rxIOwlqzvQveaLL76Q22+/PRH2q6++uutcsvfeeyfa3jYyBAyB6iNgBLD6mNsRDQFDICECkJpBgwbJ22+/HbsHnq9G79mZBK5ll11WaG1FWzQ1CF2HDh1kq622cr1z1W688Ubp16+fvPPOO5kQwAsvvFCuvfZaeeqpp5JM3bYxBAyBGiBgBLAGoNshDQFDoDgCeJ0IZ6otuuii8tZbbzlvFX1MIX0jRoyQFVdcUcaMGSOvvPKKHHXUUfLoo4/KrLPOKltssYXrTY3XEPv222+lZ8+eMnLkSJl99tndtv/+979dSPm8885z20R5wOacc073u/Zwfu+995x367777nMhzg022EDOP/98WWyxxdwY6i3j72effbZAUHfffXc3xowzzui2wQNHmPSGG25w/Ww7duwoxx57rBxwwAGy9NJLS48ePdz81P7zn//Iyiuv7PoCL7nkktOBRzP7tdZay4XJ55hjjmkI4IknnigXXHCBfPDBBzLzzDO738AGj+Cpp55aMgHkGkT1T91www2dpxaDsIPH66+/7jy3ZoaAIVB/CBgBrL9rYjMyBAwBEfnyyy8dcbnsssvk6aefljZt2si8887rCCD5ZZC5Aw880DW7b9eunSNIBx98sOyzzz7y/fffOw/XL7/8Ig899JDDs1evXo7wXXnllbLAAgvI8ccf7wgLYyQlgN99950jjJ07d5Y+ffq4cPRpp53m5vPSSy85UgoBJBS75557yhFHHCGTJ0+W3XbbzR2D+WH8P2FZiOMqq6wib775pnzyySfu7wMHDpTrrrtOJkyY0HofQDg5BkQ3yhgbD9/EiROn+VkJLZ5BCCUh2SlTpjiS+fLLL8syyyxTMgH89ddf5eOPP249DsRys802c/iecsoprX+ff/755ayzzpJ9993X7mdDwBCoQwSMANbhRbEpGQKGQAsCEBv+weukBgGEHFIQonbyySe7cOO9997b+rd3333XhT9fffVVl+/Wvn175zGEZGHkvy2yyCJyyCGHJCaAkEdIDURL8+vw8OElJD8OzxoEEGKJ9wvSiu26667OW0joddKkSUK49v7773fEKbT333/fzXvcuHGy9tpry88//ywLL7ywC4XHkSnIKITOz/9jXCWAeORGjRrlyDAk7YUXXnBEeK655pqOALZt27Z13jo3PJbbbLPNdDmAP/zwgyPkEHPG94s+yAMkf7N///52OxsChkAdImAEsA4vik3JEDAEChNAPFjDhg1rhQlyAqEKcwEJ+44ePdoRQDx3ECHCrWqrrbaaELpM6gHs3bu387RBknzDMzhkyBDnlYQA4iG76667WjfBEwhBg4DddNNNzjuIl1JDwuH1hjgtuOCCcskllzhvIsQPT9sss8wSeWtQKQ3h9Y/pE0A8lpBdvIqQTjyrhKijCODQoUOnI6Z4U/H8hUUge+21lyOTTz75pAur+0YlMsc488wz7XY2BAyBOkTACGAdXhSbkiFgCBQmgH7eHltS5AA5iiIbECly5yB7xQggHqxbb71Vunbt2noJyCeE3EHsIHjk2xGiDQ0vGKHoqIpZPHQQJTyDhKEZvxABZJtu3boJ3kA8loRTfcIbHvuEE05wnjy8hr75OY277LKLCzPjESUM/PXXX0cSQAjnDjvsMM04UedE6Jscy/Hjx0fmJS6//PIuvO7nMtp9bQgYAvWDgBHA+rkWNhNDwBAIEIgLAYcEEAIEcaNYIkom5ptvvpG5557bVaYSjsUomMArRl6eegAhWoQsyWfDII7kyV111VWO2EHC8IYRkvaLLW8Kzx0AAAMTSURBVPxpFyOA7EthBEUkUSFgxsLbhqeyb9++7ngUtqy33nqx9wc6iYSyP/3009bQNBv7BBBJna233tqNd8YZZzhZlygPYBICCNZUGzPmpptuOt28CA2DT9zvdqMbAoZA7REwAlj7a2AzMAQMgRgEkhLAqVOnuhAv4dyjjz7aVf5SfEHOHaSNXDy8d4SDyX2D6EEaCcn6RSCQmhdffNERxf/973+OLD322GOuEAVip0Ug5OSRSweBREqFymKOy/8XI4Cc6v777+/y9QjFUgSCZ5JqYCWnbMP8Bg8e7MhiWNwRwgXxI8xNoQgV0mo+AaRYhu0gZoTKyyWAkOx11lnHVUITEldjTEg2hqdzu+22kw8//DA2bG03vSFgCNQWASOAtcX//9u5gxOFYigMo1OOG/uwM3fWYA324M4arGX4BMERR0WCZpjzdsPwknDi4ufm3ZidAIE7As8GwIaoWldg6yi0poWujVmtVl+bzeZUCasKeHkNTNW1vpm7rCYWJAtn+/3+FKjq0i0UXl4D07d4zVOY7Bi1MFgVrLBWuHomAFYhqwu5gFooq9rX3819fo7H4+lotaaTwuWjp3V29cp6vb4ZAK/ffzUAbrfbH+s8j3t5DUzfJGbeN4weAgTmFBAA59wXqyJA4A0CdbBeHye/YdqnpiiEtr6aO6pYPnpqMulIucrndUPGo3dH/r8GmMVi8XU4HG7eFzhyLmMRIPC6gAD4up03CRD44wIzBsCqlzVp9E1fDSy3Gk5+Y+/i7K5fWS6XH9uZmkK61/B83c7HFmJiAgTuCgiAfiAECPxbgRkDYEesfZdYZXK3252OmD0ECBAYLSAAjhY1HgECBAgQIEBgcgEBcPINsjwCBAgQIECAwGgBAXC0qPEIECBAgAABApMLCICTb5DlESBAgAABAgRGCwiAo0WNR4AAAQIECBCYXEAAnHyDLI8AAQIECBAgMFpAABwtajwCBAgQIECAwOQCAuDkG2R5BAgQIECAAIHRAgLgaFHjESBAgAABAgQmFxAAJ98gyyNAgAABAgQIjBb4BuWwKdJ22lVxAAAAAElFTkSuQmCC\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from stride.utils import fft\n",
-    "\n",
-    "freq, wavelet_fft = fft.magnitude_spectrum(shot.wavelets.data[0], time.step)\n",
-    "freq, traces_fft = fft.magnitude_spectrum(traces.data[0], time.step)\n",
-    "\n",
-    "plt.figure()\n",
-    "\n",
-    "plt.plot(freq*1e-6, traces_fft, c='r')\n",
-    "plt.plot(freq*1e-6, wavelet_fft, c='k')\n",
-    "\n",
-    "plt.xlim([-0.5, 12])\n",
-    "plt.ylim([-80, 5])\n",
-    "\n",
-    "plt.legend(['recorded', 'emitted'])\n",
-    "\n",
-    "plt.xlabel('frequency (MHz)')\n",
-    "plt.ylabel('magnitude (dB)')\n",
-    "plt.subplots_adjust(left=0.2)\n",
-    "plt.show()\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2d4f36d7",
-   "metadata": {},
-   "source": [
-    "We can clearly see the excitation of high-order harmonics due to the non-linear behaviour of the bubble.\n",
-    "\n",
-    "Plotting the wavefield using two scales for the incident and scattered field will allow us to visualise this more easily."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "8c9cf787",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\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": [
-       "<img 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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from utils import plot_wavefields\n",
-    "\n",
-    "plot_wavefields([wavefield_1-wavefield_0, wavefield_0],\n",
-    "                [dict(vmin=-1e3, vmax=1e3, cmap='PuOr_r'),\n",
-    "                 dict(vmin=-200e3, vmax=200e3, cmap='seismic', alpha=0.1)])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a0e1f345",
-   "metadata": {},
-   "source": [
-    "## Multiple bubbles\n",
-    "\n",
-    "So far, we have been looking at single bubbles. Let's add ten bubbles to our simulation to see what would be the effect.\n",
-    "\n",
-    "We can do this by defining the initial radius and the location of our bubbles using the parameter `num=10`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "id": "4f181b51",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "r_0 = SparseField(name='r_0', num=10, grid=problem.grid)\n",
-    "r_0.data[:] = 2.2000e-06\n",
-    "\n",
-    "x_0 = ParticleField(name='x_0', num=10, grid=problem.grid)\n",
-    "\n",
-    "np.random.seed(2021)\n",
-    "for index in range(x_0.num):\n",
-    "    x_0.data[index, :] = np.array(space.size) / 2\n",
-    "    x_0.data[index, :] += (np.random.rand(3)*2 - 1)*1e-3"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4a079cea",
-   "metadata": {},
-   "source": [
-    "We can then run our PDE as before, passing in the new `r_0` and `x_0`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "4b6d6e93",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(ShotID 0) Preparing to run state for shot\n",
-      "(ShotID 0) Estimated bandwidth for the propagated wavelet 1.600-2.400 MHz\n",
-      "(ShotID 0) Spatial grid spacing (0.050 mm | 12.833 PPW) is below dispersion limit (0.128 mm | 5.000 PPW)\n",
-      "(ShotID 0) Time grid spacing (0.005 μs | 15%) is below OT2 limit (0.012 μs)\n",
-      "(ShotID 0) Selected undersampling level 20\n",
-      "(ShotID 0) Selected time stepping scheme OT2\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
-      "Ensure that the provided interpolation coefficient and grid point values are computed on the final grid that will be used for other computations.\n",
-      "Operator `acoustic_iso_state` instance configuration:\n",
-      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05}\n",
-      "\t * opt=advanced\n",
-      "\t * platform=None\n",
-      "Operator `acoustic_iso_state` generated in 22.03 s\n",
-      "  * lowering.Clusters: 14.29 s (64.9 %)\n",
-      "     * specializing.Clusters: 8.68 s (39.5 %)\n",
-      "        * fuse: 5.32 s (24.2 %)\n",
-      "  * lowering.Expressions: 4.73 s (21.5 %)\n",
-      "Flops reduction after symbolic optimization: [6318 --> 1738]\n",
-      "Operator `acoustic_iso_state` fetched `/tmp/devito-jitcache-uid1000/80b6432b7ba3e43442da5ca9c007b17f53a87a36.c` in 0.65 s from jit-cache\n",
-      "(ShotID 0) Using inhomogeneous density\n",
-      "(ShotID 0) Running state equation for shot\n",
-      "AutoTuner: cannot perform autotuning unless there is one time loop; skipping\n",
-      "Operator `acoustic_iso_state` ran in 94.18 s\n",
-      "Global performance: [OI=0.01, 17.45 GFlops/s, 0.01 GPts/s]\n",
-      "Local performance:\n",
-      "  * section0<<10,7,7,7>,<10,7,7,7>> ran in 0.01 s [OI=0.10, 1.62 GFlops/s]\n",
-      "  * section1<160> ran in 0.01 s [OI=0.13, 0.32 GFlops/s]\n",
-      "  * section2<160> ran in 0.01 s [OI=0.13, 0.22 GFlops/s]\n",
-      "  * section3<160> ran in 0.01 s [OI=0.13, 0.32 GFlops/s]\n",
-      "  * section4<10> ran in 0.01 s [OI=0.15, 0.06 GFlops/s]\n",
-      "  * section5<<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,20,160,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,20,160>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,160,160,20>,<1499,15,15,17,17,129>,<1499,15,15,8,8,120>,<1499,29,169,129>,<1499,20,160,120>,<1499,29,169,129>,<1499,20,160,120>,<1499,169,29,129>,<1499,160,20,120>,<1499,169,29,129>,<1499,160,20,120>,<1499,169,169,29>,<1499,160,160,20>,<1499,169,169,29>,<1499,160,160,20>> ran in 93.48 s [OI=0.01, 17.57 GFlops/s, 0.12 GPts/s]\n",
-      "  * section6<1499,10,7,7,7> ran in 0.02 s [OI=0.10, 1.48 GFlops/s]\n",
-      "  * section7<1499,100,10> ran in 0.35 s [OI=1.69, 1.75 GFlops/s, 0.01 GPts/s]\n",
-      "  * section8<<1499,10>,<1499,10,7,7,7>> ran in 0.06 s [OI=0.13, 0.71 GFlops/s, 0.11 GPts/s]\n",
-      "  * section9<<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>,<1499,1>> ran in 0.01 s [OI=34.60, 0.46 GFlops/s, 0.01 GPts/s]\n",
-      "  * section10<<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>,<1499,120>> ran in 0.02 s [OI=45.00, 17.79 GFlops/s]\n",
-      "Performance[mode=advanced] arguments: {'nthreads': 6, 'nthreads_nonaffine': 6, 'i2x0_blk0_size': 8, 'i2y0_blk0_size': 8, 'x0_blk0_size': 8, 'y0_blk0_size': 8}\n",
-      "(ShotID 0) Completed state equation run for shot\n"
-     ]
-    }
-   ],
-   "source": [
-    "traces_2 = await pde(shot_wavelets, vp, rho=rho,\n",
-    "                         r_0=r_0, x_0=x_0,\n",
-    "                         sigma=sigma, mu=mu,\n",
-    "                         p_0=p_0, kappa=kappa, kappa_s=kappa_s,\n",
-    "                         chi=chi, r_buckle=r_buckle, r_break=r_break,\n",
-    "                         problem=sub_problem, diff_source=True,\n",
-    "                         save_wavefield=True, save_undersampling=20,\n",
-    "                         boundary_type='complex_frequency_shift_PML_2',\n",
-    "                         num_inner=100)\n",
-    "\n",
-    "wavefield_2 = pde.wavefield.data[:, :, pde.wavefield.shape[-1]//2].copy()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "75f7e786",
-   "metadata": {},
-   "source": [
-    "Subtracting the baseline simulation, we will now be able to see the signal coming from alll bubbles."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "7b48122d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\n",
-       "        'matplotlib',\n",
-       "        mpl.mpl_figure_comm\n",
-       "    );\n",
-       "}\n"
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
       ],
       "text/plain": [
-       "<IPython.core.display.Javascript object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "from utils import plot_wavefields\n",
+    "\n",
+    "plot_wavefields([wavefield_1-wavefield_0, wavefield_0],\n",
+    "                [dict(vmin=-1e3, vmax=1e3, cmap='PuOr_r'),\n",
+    "                 dict(vmin=-200e3, vmax=200e3, cmap='seismic', alpha=0.1)])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a0e1f345",
+   "metadata": {},
+   "source": [
+    "## Multiple bubbles\n",
+    "\n",
+    "So far, we have been looking at single bubbles. Let's add ten bubbles to our simulation to see what would be the effect.\n",
+    "\n",
+    "We can do this by defining the initial radius and the location of our bubbles using the parameter `num=10`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "4f181b51",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r_0 = SparseField(name='r_0', num=10, grid=problem.grid)\n",
+    "r_0.data[:] = 2.2000e-06\n",
+    "\n",
+    "x_0 = ParticleField(name='x_0', num=10, grid=problem.grid)\n",
+    "\n",
+    "np.random.seed(2021)\n",
+    "for index in range(x_0.num):\n",
+    "    x_0.data[index, :] = np.array(space.size) / 2\n",
+    "    x_0.data[index, :] += (np.random.rand(3)*2 - 1)*1e-3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4a079cea",
+   "metadata": {},
+   "source": [
+    "We can then run our PDE as before, passing in the new `r_0` and `x_0`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "4b6d6e93",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(ShotID 0) Preparing to run state for shot\n",
+      "(ShotID 0) Estimated bandwidth for the propagated wavelet 1.600-2.400 MHz\n",
+      "(ShotID 0) Using DRP scheme\n",
+      "(ShotID 0) Spatial grid spacing (0.050 mm | 12.833 PPW) is below dispersion limit (0.214 mm | 3.000 PPW)\n",
+      "(ShotID 0) Time grid spacing (0.005 μs | 15%) is below OT2 limit (0.012 μs)\n",
+      "(ShotID 0) Selected undersampling level 20\n",
+      "(ShotID 0) Selected time stepping scheme OT2\n",
+      "(ShotID 0) Expected wavefield size 2.3193 GB\n",
+      "Operator `acoustic_iso_state` instance configuration:\n",
+      "\t * name=acoustic_iso_state\n",
+      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05, dt: 5e-09}\n",
+      "\t * opt=advanced\n",
+      "\t * devicecreate=(p(t, x, y, z), p_saved(time_under0, x, y, z))\n",
+      "Operator `acoustic_iso_state` generated in 54.81 s\n",
+      "  * lowering.Clusters: 42.35 s (77.3 %)\n",
+      "     * specializing.Clusters: 27.17 s (49.6 %)\n",
+      "        * fuse: 20.48 s (37.4 %)\n",
+      "Flops reduction after symbolic optimization: [1883 --> 1249]\n",
+      "Operator `acoustic_iso_state` fetched `/tmp/devito-jitcache-uid1000/af348409237fad0eb9c1d6b6c12ff7feeac0a66e.c` in 1.21 s from jit-cache\n",
+      "Operator `acoustic_iso_state_save` instance configuration:\n",
+      "\t * name=acoustic_iso_state_save\n",
+      "\t * subs={h_x: 5e-05, h_y: 5e-05, h_z: 5e-05, dt: 5e-09}\n",
+      "\t * opt=advanced\n",
+      "\t * devicecreate=(p(t, x, y, z), p_saved(time_under0, x, y, z))\n",
+      "Operator `acoustic_iso_state_save` generated in 44.04 s\n",
+      "  * lowering.Clusters: 33.45 s (76.0 %)\n",
+      "     * specializing.Clusters: 18.23 s (41.5 %)\n",
+      "        * fuse: 14.00 s (31.8 %)\n",
+      "     * schedule: 11.10 s (25.3 %)\n",
+      "Flops reduction after symbolic optimization: [1883 --> 1249]\n",
+      "Operator `acoustic_iso_state_save` fetched `/tmp/devito-jitcache-uid1000/4194f14e4dc8631801b87cd22b43c5c9dde3a90d.c` in 0.86 s from jit-cache\n",
+      "(ShotID 0) Using inhomogeneous density\n",
+      "(ShotID 0) Running state equation for shot\n",
+      "AutoTuner: cannot perform autotuning with 2 time loops; skipping\n",
+      "Operator `acoustic_iso_state_save` ran in 69.15 s\n",
+      "Global performance: [OI=0.01, 14.67 GFlops/s, 0.09 GPts/s]\n",
+      "Global performance <w/o setup>: [69.15 s, 0.09 GPts/s]\n",
+      "Local performance:\n",
+      "  * section0 ran in 0.01 s\n",
+      "  * section1 ran in 0.01 s\n",
+      "  * section2 ran in 0.01 s\n",
+      "  * section3 ran in 0.01 s\n",
+      "  * section4 ran in 29.87 s [OI=0.01, 17.58 GFlops/s, 0.16 GPts/s]\n",
+      "  * section5 ran in 9.79 s [OI=3.04, 19.33 GFlops/s, 0.27 GPts/s]\n",
+      "  * section6 ran in 28.27 s [OI=0.01, 10.60 GFlops/s, 0.14 GPts/s]\n",
+      "  * section7 ran in 0.20 s [OI=0.50, 0.16 GFlops/s]\n",
+      "  * section8 ran in 0.66 s [OI=1.19, 0.59 GFlops/s, 0.01 GPts/s]\n",
+      "  * section9 ran in 0.05 s [OI=0.67, 2.83 GFlops/s, 0.18 GPts/s]\n",
+      "  * section10 ran in 0.01 s\n",
+      "  * section11 ran in 0.02 s [OI=1.45, 1.26 GFlops/s]\n",
+      "  * section12 ran in 0.31 s \n",
+      "Performance[mode=advanced] arguments: {'i2x0_blk0_size': 16, 'i2y0_blk0_size': 16, 'nthreads': 6, 'nthreads_nonaffine': 6, 'pthreads': 0}\n",
+      "(ShotID 0) Completing state equation run for shot\n",
+      "(ShotID 0) Completed state equation run for shot\n"
+     ]
+    }
+   ],
+   "source": [
+    "traces_2 = await pde(shot_wavelets, vp, rho=rho,\n",
+    "                         r_0=r_0, x_0=x_0,\n",
+    "                         sigma=sigma, mu=mu,\n",
+    "                         p_0=p_0, kappa=kappa, kappa_s=kappa_s,\n",
+    "                         chi=chi, r_buckle=r_buckle, r_break=r_break,\n",
+    "                         problem=sub_problem, diff_source=True,\n",
+    "                         save_wavefield=True, save_undersampling=20, force_raw_wavefield=True,\n",
+    "                         boundary_type='complex_frequency_shift_PML_2',\n",
+    "                         num_inner=100)\n",
+    "\n",
+    "wavefield_2 = pde.wavefield.data[:, :, pde.wavefield.shape[-1]//2].copy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "75f7e786",
+   "metadata": {},
+   "source": [
+    "Subtracting the baseline simulation, we will now be able to see the signal coming from alll bubbles."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "7b48122d",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e0fbde59d0cc4f87b3cfd7f2ff28805a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
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\" width=\"640\">"
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
       ],
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -5633,982 +951,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "id": "8539023c",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\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",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\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",
-       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
-       "        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",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\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 (fig.ws.readyState == 1 && 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",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.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",
-       "    this.rubberband_canvas.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            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",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // 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",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _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\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.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",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = 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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.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",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\n",
-       "        'matplotlib',\n",
-       "        mpl.mpl_figure_comm\n",
-       "    );\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "60a8892ee1fd42f3a4abd662d156aebb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "image/png": 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",
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\" width=\"640\">"
+       "\n",
+       "            <div style=\"display: inline-block;\">\n",
+       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
+       "                    Figure\n",
+       "                </div>\n",
+       "                <img 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' width=800.0/>\n",
+       "            </div>\n",
+       "        "
       ],
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -6646,7 +1012,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,