{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 布洛赫球\n",
    "\n",
    "[![下载Notebook](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r2.5.0/resource/_static/logo_notebook.svg)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/r2.5.0/mindquantum/zh_cn/beginner/mindspore_bloch_sphere.ipynb) \n",
    "[![下载样例代码](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r2.5.0/resource/_static/logo_download_code.svg)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/r2.5.0/mindquantum/zh_cn/beginner/mindspore_bloch_sphere.py) \n",
    "[![查看源文件](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r2.5.0/resource/_static/logo_source.svg)](https://gitee.com/mindspore/docs/blob/r2.5.0/docs/mindquantum/docs/source_zh_cn/beginner/bloch_sphere.ipynb)\n",
    "\n",
    "## 单比特量子态\n",
    "\n",
    "与经典比特不一样的是，量子比特可以同时处于计算基矢 $\\left|0\\right>$ 态和 $\\left|1\\right>$态上，通常表示为：\n",
    "\n",
    "$$\\left|\\psi\\right> = a\\left|0\\right> + b\\left|1\\right>$$\n",
    "\n",
    "这里，$a$和$b$是复数。由于量子态的归一性条件 $\\left<\\psi\\middle|\\psi\\right> = 1$，因此，我们有：\n",
    "\n",
    "$$\\left|a\\right|^2 + \\left|b\\right|^2 = 1$$\n",
    "\n",
    "对于二维希尔伯特空间，我们可以将计算基矢做如下的映射，\n",
    "\n",
    "$$\n",
    "\\left|0\\right> =\n",
    "    \\begin{pmatrix}\n",
    "    1 \\\\\n",
    "    0\n",
    "    \\end{pmatrix},\n",
    "\\left|1\\right> =\n",
    "    \\begin{pmatrix}\n",
    "    0 \\\\\n",
    "    1\n",
    "    \\end{pmatrix}\n",
    "$$\n",
    "\n",
    "因此，任意单比特量子态可表述为：\n",
    "\n",
    "$$\\left|\\psi\\right> =\n",
    "    \\begin{pmatrix}\n",
    "    a \\\\\n",
    "    b\n",
    "    \\end{pmatrix}\n",
    "$$\n",
    "\n",
    "在一般情况，我们并不关心全局相位，因此，我们可以假设 $a=\\cos\\left(\\theta/2\\right), b=e^{i\\phi}\\sin\\left(\\theta/2\\right)$：\n",
    "\n",
    "$$\\left|\\psi\\right> = \\cos\\left(\\theta/2\\right) \\left|0\\right> + e^{i\\phi}\\sin\\left(\\theta/2\\right)\\left|1\\right>$$\n",
    "\n",
    "这里，我们不妨在单位球中来表示该任意量子态，如下图，将 $\\theta$ 和 $\\phi$ 分别取为仰角和方位角。\n",
    "\n",
    "![bloch-sphere](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r2.5.0/docs/mindquantum/docs/source_zh_cn/images/bloch_sphere.png)\n",
    "\n",
    "下面，我们将展示怎么在MindSpore Quantum中展示一个单比特量子态，并且以动画的形式展示单比特量子态的演化。\n",
    "\n",
    "## 导入相关模块"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mindquantum.core.circuit import Circuit\n",
    "from mindquantum.core.gates import RX, RZ\n",
    "from mindquantum.io.display import BlochScene"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了在Jupyter Notebook中动态展示量子态，我们需要运行如下指令："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib ipympl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 搭建量子线路\n",
    "\n",
    "由上面bloch球可知，我们可以通过旋转门 [RX](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.10/core/gates/mindquantum.core.gates.RX.html) 来控制仰角 $\\theta$，通过 [RZ](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.10/core/gates/mindquantum.core.gates.RZ.html) 来控制方位角 $\\phi$。因此，我们可以搭建如下量子线路："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" width=\"256.8\" height=\"80\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<rect x=\"0\" y=\"0\" width=\"256.8\" height=\"80\" fill=\"#ffffff\" />\n",
       "<text x=\"20.0\" y=\"40.0\" font-size=\"16px\" dominant-baseline=\"middle\" text-anchor=\"start\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#252b3a\" >\n",
       "q0:\n",
       " </text>\n",
       "<line x1=\"48.8\" x2=\"236.8\" y1=\"40.0\" y2=\"40.0\" stroke=\"#adb0b8\" stroke-width=\"1\" />\n",
       "\n",
       "<rect x=\"72.8\" y=\"20.0\" width=\"80.0\" height=\"40\" rx=\"4\" ry=\"4\" stroke=\"#ffffff\" stroke-width=\"0\" fill=\"#fac209\" fill-opacity=\"1\" />\n",
       "<text x=\"112.8\" y=\"36.0\" font-size=\"20px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >\n",
       "RX\n",
       " </text>\n",
       "<text x=\"112.8\" y=\"52.0\" font-size=\"14.0px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >\n",
       "theta\n",
       " </text>\n",
       "\n",
       "\n",
       "<rect x=\"172.8\" y=\"20.0\" width=\"40.0\" height=\"40\" rx=\"4\" ry=\"4\" stroke=\"#ffffff\" stroke-width=\"0\" fill=\"#fac209\" fill-opacity=\"1\" />\n",
       "<text x=\"192.8\" y=\"36.0\" font-size=\"20px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >\n",
       "RZ\n",
       " </text>\n",
       "<text x=\"192.8\" y=\"52.0\" font-size=\"14.0px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >\n",
       "phi\n",
       " </text>\n",
       "\n",
       "</svg>"
      ],
      "text/plain": [
       "<mindquantum.io.display.circuit_svg_drawer.SVGCircuit at 0x7f64772355b0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circ = Circuit()               # 搭建制备任意单比特量子态的线路\n",
    "circ += RX('theta').on(0)      # 通过RX门控制仰角\n",
    "circ += RZ('phi').on(0)        # 通过RZ门控制方位角\n",
    "circ.svg()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里我们不妨取 $\\theta=\\pi/4, \\phi=\\pi/4$，并计算出该位置的量子态。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.85355339-0.35355339j 0.14644661-0.35355339j]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "state1 = circ.get_qs(pr={'theta': np.pi/4, 'phi': np.pi/4})\n",
    "print(state1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 展示量子态\n",
    "\n",
    "在MindSpore Quantum中，[BlochScene](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.10/io/mindquantum.io.BlochScene.html) 是用来展示布洛赫球的模块，我们可以在 [BlochScene](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.10/io/mindquantum.io.BlochScene.html) 中添加任意多的单比特量子态，并且还可以动画展示单比特量子态的演化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\n        case 0:\n            cursor = 'pointer';\n            break;\n        case 1:\n            cursor = 'default';\n            break;\n        case 2:\n            cursor = 'crosshair';\n            break;\n        case 3:\n            cursor = 'move';\n            break;\n    }\n    fig.rubberband_canvas.style.cursor = cursor;\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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 * http://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home 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, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    var manager = IPython.notebook.keyboard_manager;\n    if (!manager) {\n        manager = IPython.keyboard_manager;\n    }\n\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
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\" width=\"548\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scene = BlochScene()                       # 创建布洛赫绘图场景\n",
    "fig, ax = scene.create_scene()             # 初始化场景\n",
    "state_obj1 = scene.add_state(ax, state1)   # 往场景中添加一个量子态"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "此外，我们还可以以深色模式来展示布洛赫球，如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n    if (typeof WebSocket !== 'undefined') {\n        return WebSocket;\n    } else if (typeof MozWebSocket !== 'undefined') {\n        return MozWebSocket;\n    } else {\n        alert(\n            'Your browser does not have WebSocket support. ' +\n                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n    this.id = figure_id;\n\n    this.ws = websocket;\n\n    this.supports_binary = this.ws.binaryType !== undefined;\n\n    if (!this.supports_binary) {\n        var warnings = document.getElementById('mpl-warnings');\n        if (warnings) {\n            warnings.style.display = 'block';\n            warnings.textContent =\n                'This browser does not support binary websocket messages. ' +\n                'Performance may be slow.';\n        }\n    }\n\n    this.imageObj = new Image();\n\n    this.context = undefined;\n    this.message = undefined;\n    this.canvas = undefined;\n    this.rubberband_canvas = undefined;\n    this.rubberband_context = undefined;\n    this.format_dropdown = undefined;\n\n    this.image_mode = 'full';\n\n    this.root = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (fig.ratio !== 1) {\n            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\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\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\n        case 0:\n            cursor = 'pointer';\n            break;\n        case 1:\n            cursor = 'default';\n            break;\n        case 2:\n            cursor = 'crosshair';\n            break;\n        case 3:\n            cursor = 'move';\n            break;\n    }\n    fig.rubberband_canvas.style.cursor = cursor;\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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 * http://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home 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, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    var manager = IPython.notebook.keyboard_manager;\n    if (!manager) {\n        manager = IPython.keyboard_manager;\n    }\n\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
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BM8mwGLDs/eHZ+dCAp4qNuxdIvmPCD+Sdn8S67GNXCq3fr8lfxKrs+vNY5u26BtL71aAA3s2IjIyvNMSurVufD0XRVtOCnLUtAmKjiGjthBSiUwK0JGS0dDh6MN2/EFHHp0OpOxF2e/Xsdjod+Q8oIcRYLHhYRvC03EfgQBlIIJVQfA0y4YrV2xzcpVLO/iTdHBytfqTkJOr9dijO38S+jlZKhRyKeQKisiQgHxiJVKLCAtuMeihN+gRERWGF1/8DhKTYqBUK2Eym9HQpENlTR2OncjAp5t3QO2lBflTkLeJ2QKYIAFJBL3eBF1rK4xmtOeiuCkobBEfVqvFYBEUve0jiw1XPuXc12AkwGJjMO4az9kpAjaxoWttQnVrtVN93C43kT+JVqNBaHAgIsNCERocDB+NFxQUsUHGAosEEguJEkovIYVEKrH6ZUglIhwUdGxi+y6TwSKTwywFTBIzzCRKyAlTYoGJwoTFF8kaCyQi8sYMqdkMicUMk6EVukYdqmtqUV5Zg4qKGlRX17vkiMeT9somNurysgEPdfT1JF48l9uPAIuN229PeUU9EAhQBiBYFYw7UWyQg2pwkD8SE6IRExMBjVoJSw8vPXEwIZXCTM6rUjlkCrX4bpHKYSLlQBfQ30UIMIkKGcxeQUKIyPS1IJuJ1GK2fidhAUAmAQxkyTCa4OfvLcJ9jWaDECRmiVl8JxFiplwWlFjNaERNbQPyC0uRl1cMXUvLIH6uJfCOjBYOoiw2BvE28tRviQCLjVvCxzcPJgJ3mthQK5WIigpBdHQ44mOtFUo7NpIBDboWyFUaKNRqyFUqNLUYcfTUWWHZWPPoA6iuq0OTTieOQCzCWiEleSE+nXupVFApFIDRBLk6HF4KJTRogEGvR6vegIb6RuhbWkFHO3SXhDxaJRIRfaPT69HSakBdbQNkcjnMZhMCA3wQHBIAOVlKhKYh2WFGs74FV6/nwQQLgoP9UVBcjILiEjQNmkycLDYG0/8neK7uIcBiwz1cuVcPJHAniA2VUonRo4YieWg8GSeEOLBQ1IaI4pCj1QRU1NQjt6AEIaEhmDd/BsyQoLlFj8rqOhSVVaKwuBRhocEICfSFSk6dmEV9j1adDpUVVRiWlIixo0eJo5WSkhL4+PrCKAkSIiLE1yR+Ts1sNiP9+GmcO39JWDYiI8Igk0isJejbjmmkIqRGCr2uFTm5RaipboCXlxr+vj4IDQ2Ev78PpHR0Q0c5EsBLq0VgYCDUKhVq6+tx/tJVZJy5CCNMMItMruToSinnjULAiL8PeL2bjmIjC/ia6PPAfyo8JSbgcgIsNlyOlDv0VAL+Sn+EqEJuu2MUehGHRYRi6rTx0PpoYSZxIZUBMhmadK1o0umh1moRFh4GvwB/XLmeh5OZF6BWqxEc6Ieq8io0NNTD39sLCdFhCA7wEQKDZIC+1YDikkoUFZehtq4R/v5++NlL/ymsFc0tOjQ1NiIgIAhVDTLxMz+tXogOsk7Qd7PZgl//5k9obmqBj68X6uuboFYrER0ZhoSEaKiV8k4WF72+FcUlVSgqqoCuqQUalRrhYcGICA2Gv6+vzUaC1hajcHItq6gWmUvDwoIxZsxwlBSXoaCoHNW1te2PoTigESKkwxcJEZIoZnPbz43iCMc9jcWGe7hyr4OJAIuNwbRbPNdbImATGy2GZlTpq26pr36/mbKTtiWzshUHU6pVGD5iKILDAqH11lqtGG1fJWWVuFFUgSFJcRiTmoymhiaUFpeiqLAIxYUlQiRYjBQbIkFYeCCSEqLh7+cjlkWOnKVl1SgsKhMOm+YOn8S9NGrMmD4JJAqio6whr/SKDg5PFsceX335MfR6PWbNnCz61rXosXXbHkyaMAqJCXF4f92mTplQKRMrHZ+kJCfAW6uBnJxO2xr1S9aO69k3hK+Hr48WiQlRiIwIgZSOYyBBXW0Trl7Nh0atQdqYkYgIDYVcJkdTow7Xr+Xi2rX8Dv21iYkeMrnSbyn8l0SJqH1DDqxkLRFWE/q79eeOixIWG/3+74UH9DgCLDY8bkt4Qu4i4PFig3JRUNly8dWhhLnyZnIrypApVyqRnJyIiKhQWCTkQSERhcFaW1pBfhrREWG4ePEKTqRnQCWXQ6VSoLauoQtW8n8YkZIIX28v8Tv6lF9QWCZe8M26nh0yVUoF5s2bhsOHT6GhsUlYGB775tMwGoxYv+6tbh1Pg4MDsPqh5dix8yCuZeV1u8UkPEJDAjByxBDhwGprZCEpKa3E+YtZwtJClhHyQYmPjWwXJ8WllbhyNRetBiOiIsIQHxeNuvoGnDl3GQG+fkhKjEduzg00N+uF/4gtiRqFAUtFJldrKHB7MHBPRfis5dhgpCqvZBkRgsQmRNqOcchaIjxMbJaSDmIj97q7Hm/ulwl4NAEWGx69PTw5VxLwU/ojVBWCAbVstCW3uikqbgoLEhJf/7KVMBeJryQWDE2IQnhwAGA2QtIWPlpTVY/UkcOgUqlQXl6FrOw8XM/KQ31DU7f4yIIwPCUBYSGB4vcGoxH5+SXIzS8WL/O+2sRxqZgwYQzeW/cZmpp0dokN6nPFsvnwUqvx0catfQ0hHE+HDIlFYnxke54Nk9mC0tJKXMvOR1NTC9QqBYYNjUdMdJg48qHfkxUkO7uwU+hsUlIcFs6bLgrsFRWX4/KVLMGHxFXHZk2aZk2UJmrckCihfCXi70KStOcn6VOUiMrAViFC/ynDQtFcUYb6nCzhT0JWEorGGexF+PrcSL6ACbQRYLHBj8IdQ8AmNvSGZlS6+RhFpNqWK0Qpc4ncWtKc/k7igTw3RYbMthTc7ZkzKQrDYm5Pv92xnkdUeBBShsaBrArU6P6ysiqcOHURQcH+SIiLxvXreait72rBsG0wHVEkJ8UhLi5CHEPQ8QiJjOtZNyCVSaEQtUdkwt9CJpMK/woKOfXx0SI4KEAkA5MrFJgzaxIKi0qxZds+8QJPHjYEk6YtEC/v0+l7xSd/epnT0UdkRCi8tBo6n0BQUAAmTRqDLV/tRW5eIVQqJXy8vWA0mmEymUS4Kwkfuq/dqgEJoqNDERsdjgB/6zEPtWZdK9JPnBMWGDpeGZGSIEJ7qVHI7NnzV9HYdNM6Q9wSE2ORMmyIiM45e+4KDh4+4fCzby3CR5YRCgsmAdImTEhEtosUEiUdivBJpVCEhcBUVYOW/ILOniEdi/C1CRCjrQhfh4yunlqEz2GAfMMdS4DFxh279Xfewl0tNkgsdDrysB2ByBU3BYWwVlAWTlsVUhIUlIGbSphbi4TdLGVu7JLwiaIxpk0eQyksRCPDfGBAIHz9fHH23GUcPnq6fSO9vbUIDPAT1gOVWikiNurqGnDleg6io8KQNnpYuzOmUqVCYEAA1r7zqbACrLzvLoRHhHZ6KHbvPYLLV7IxauQwzJk9pdPvSkrKsfHz7VDI5Xj2qUfQZPSxRovIGij1Bta+8zGam1uw9K7ZSEyM63TvhUvXsW//MSQlxmHJXbM7/a6yqhrrN2wRP3t8zb1ivoZWo7C4tLbqYTIZIafQFsrwIZGgpcWA6zkFwsKi9VIjeVgcFHIZjCaTOFbJu1Ha5UEnRiRu6uobkZI8BBERITh79jKqa+pc9o/CVhmYRAkJQ21EFEyVNdDnFwhribNF+GwWEfrebGhCs6nZZXPmjpiAOwmw2HAnXe7bowj4KfwQqg6FI5YNYXVo96OwHXlYfwbKOUGCwyYo2o5BpG1OjlQYDO2lzK3Fwsi3wp6qn0q5HJMnjYKfr7b9xRoQGAiNRoP6hkaRx4KiSShMdM++o8jJLcC4sSMxfdp4cT1ZB1paWsTPq6urEBcTIX5O1ozmZmuEirHVICwA9Kk5MjxEWC1sFgaTyYzGxia06FuFX4RSoRD33rNsPnQ6cvrc134MQZ/oR46eDJNFgivn04V1xuavQPeS9UNUb6VP/zKZSO4lfC9USvj5+YjU6OJLZhUJ+TeKxFwnThgtxlUq5dbvKhX2HUgHlUuZM2uiKLxGjfr09/fHtet5wmIxcUIqfL014nd0tFJb14Sa6nohusT1Emm7k+qIlCRMmTwWWq0X8vKLcPz4GZRXutZ5mNbuFR6BlooKNORmd/o30bkIn6ytSjAV5bPWuhG+JSJ5GrWbXiAKqRJNxiaU6EuhNw3mhGce9b8InowbCbDYcCNc7tqzCNwUGzpU6iu7nRw5ZqoCAyGlIw8SFPSibBMTJCJsfxaWCjqXNxjbK4/aqo+K76abRwH2ULC9ANVqFWZMHQcvLyXMbX1QpMmWbQeF4+OQxFh4a7VobG5GU1Mzmpt0yMotQG1tHehehUIOna5FiI2gAD+MHj0UWsprASAvvwRXruWJF7qzjaJRlEolauvq27sgB9E133gKJoMRH334do+ZSW030LysIuBmH87MJzwsCKNSh0KlsFacpXlknL0Mna4V48cOh1IlF74clDRMqdLgk0+3ieue+fbDaGlpFczoyIW+kwVlzOjhCAjww6Yvd6KgsKtFxJk5innJZPAKC+9WbNjbp60IH1lKZFI5ApWU/EyB4pYSVOvv7NT79jLk6waWAIuNgeXPo/cjgb7EBlkxVCGh8E1IhEnfYhUWUor0IKuESVglrELC2CYynH9pB/j7idBRMuGHhQWhrrZRWAtGDE9ot0IolEp4eWlx8PApFBeXdXFo7A1d0pAYJA+NEy9bSth17vw1VFa57pig49j2RKN0vJ6ORwoKS7DvwPFb3n0Kf42KCsWokUmQtZ01NTXrcTT9DDReakxMGy58Q8iSkpF5RYiL4cOHiJwddERF4oKsK2+/txEtulYsWTwLra0GlJRWQKNR4sq1XDT04Ghr7+RdITa+PhYlqPNSeqOqtYrFhr0bwdcNKAEWGwOKnwfvTwK+Cl+EqcOgN3Rv2ZCqVPCOjYcmPALNJYXtIsNVcyT/BnKATBoShyWLZ4sMm+UVVcLRs6qyCvHxEUIcUFMoVTh/4Tqyc8ih0P5kU3RskTZqmBAw1CjB1cXL2Z2cLp1ZDx2FPPzQMhw7nimOZm5FbMyYNh7Dhibg7Xet/iKuaHQEM2H8SAQH+oruSABdvpKDwpIKTBw3HH6+3uIY6Oz5aygqrug0JDGzOaVSpA35mFCorig8Z7EgK+cG9u47alekTndrIbGhCQuHvptjFGfXzmLDWXJ830ARYLExUOR53H4n0C42jC2obOn8wqHJSJVKITYU/v7QlZa4bH5kwZg+dRyqa+uxa/dhEVESHh4qrBUkPuhTua12CZ3v03HH+YuO52OgyI4JacOh1WrEMcWFS1kib4YrWnxsFJYvm4/1H29BZWVns72jlo2oyDDcf+9ibPh4C8q/1tetzpWsFdOnjGkXbRWVtUJsDRsah8jwYCFtzl243icX8hGJjY1E2tgRCA4MgL61FVnZ+SLKhqwejrSbYqMcDblWv5FbbTaxQVFVNXd4BeNbZcn39w8BFhv9w5lH8QACPgofhKvDoe9HsWGL5CgtKUf6ybPi+MDWyCly4bwpwuGRmr7ViIOHTzv1CTo8NAhjRw8Tzpy6llaczrwk0ou7qi2cPx2hIcFY99EXXbp0VGyQleSpJ1fh5OlzOJ150VVTbO+HHFEpI2lcbET70crZC1nw99O2H1GREOsuUqW7yfh4azFzxgSEBgfD21uD3XuOtjub2jN5d4iNQGUgNEqtCOFmsWHPLvA1A02AxcZA7wCP328E7BUbSv8ANJcWu2ReT31rFfLyCsULquORQcqwBAxPSYShVS/GKSuvwckM5168cbHhSB0xRKTvrqyqRebZq04Jlp4WTOLgySdW4vz5K0g/cbZbsbFy1TdgMBqw6dMP+3QQpQ7mz5mK6upaZJ677BLO3XXirVVjyqTRIuqFWnVNgwh3TYizRuZcuJIjytfb24jDXYtmIjLSmqcjI/OCXc627hUblahprbF3CXwdExgwAiw2Bgw9D9zfBGxio9XYgopejlFcKTbWPLwC17JycfLU+fblJiXGYlRqkggBpSDRS5coH4T9L72O3IYlxYJ8+ps5AAAgAElEQVS+qN0oKMX5i9ku84OwjUNhsQ/cvwQff7IVZRVdw0LJshETP0qUhS/MPW+X2Oivvacon0kTU9t9OShnaEFBSbuF49yFLNywM/LE398Xy++eC5lMLo6qamvrsWPXIVRW9f6yF2IjNMzqs5HnmmOUm5YNFhv99SzxOLdGgMXGrfHjuwcRAW+FDyLU4ehRbCiU8I6LhyvFBqUGb2zSCUqzZkxEcVGpSBVOuSgo/PJUxkXU1nefVrw3tGTFSB2Z2P7SvJ5VgKtZN4uOuXpbqNprXW19t0KGxMb9Kx+FwWDC5k3r7RYbwrfERBys1h13NmtSs+T2HCBlZdWg0FmyNp06fVlUj+2ukViheVINmNDgICxcMANbt+0VOUHozxTNcuxYBs6cu9KjyKMwaU0Iiw137i/37fkEWGx4/h7xDF1EwCY2DEY9ylvKu/RKOTaE2AgIQHOJc5aG7qZKkRDz5kxDSEgASktLRf4Myv2QnVOEq9dyhZOoI41egOPGJre9LIGLDvgfODKOvdc66rNB/dIanv7WKhw/dQ6ZZ5w7PrJ3frbrKA/JzGlj21O+1zfqRPIvyjuSfuJ8u48LVb+lNOvR0RGIi4lEY1OzcIy1zduWOpz8Y6ZOTkNwcCA2fbFrQMRGhb4Cta21jqLg65lAvxNgsdHvyHnAgSJgj9jQxsaJpF6uEBtkfRg9OhlTJ6WhobER9fV1InsoZbz00ngjKDgAb761QfhXULZMenlVVdaguqZWVGntWCPExoycH8eNTRFCgyJO6BN1SalrM1523B8SSkvvnosdOw6iqod03s6IDRrjvnsWoVWvx9btB/rtkaA9GZ4Sj8T4KDEmMaT8HMT60NFM+Pr64MH7l4h9qqysQX5hMXJybqCsvGfG5MtBdWHouEmpVgkfnY7NHZaNIFUQ1AovsNjot0eHB7pFAiw2bhEg3z54CHjLvRGhiUDPlg0FtLHxLhMbo1OTMXvWZFy8eBUajUKEY9JLbff+E+I7hcDaqqwunDsN0TERoPom1Ohlt2X7fvHiotDZsNBgNDQ0IjjYD4H+PjBZyPx/CRWV7nUOpGiaWTMntYui7nbbWbExdfJYjBg+FGvf+cQtDxGJACoC56P1go+PN0rLKoSD6PCUIRiTmozGRmsGUwo3Jt4NjTpR3C0iPBQlZRXQ61sdmtfc2ZOROjIZpzLOIz39TLulwyY2WsrL0Zif61CfPV3MYsMlGLmTfiTAYqMfYfNQA0vAfrERhOYSa30OZxqZ68kPgSwVSQkxSIiPtFZRbWgWmS2Nps6lzTuOQfcG+vshwN8X+QXFwoQ/Pi0V49JGoqG+Ho2NDaIAWUhoqEhc1dysE1EdO3YfFt2MGpksjml0er14Wer1+h6tJPasjQqleWs0+OTz7T1e7qzYSEyIwdIlc/H2uxvFOntrZJGgGimi+FpbvZa4mCiRol1DX14qUSvGFvVD5ezjYq3WC1uzFZajPB/0O3LQDQ8P7FSrhkrQZ567Zg+abq8ZnzZSHK3k5heJnCqtBoOo9KsOCYU7xEa5vgJ1fIzi9H7xjf1HgMVG/7HmkQaYgLvFBr0QJ4wbiXHjRmHDxq9gMhowZ+YE4ZRYVlGDjMzLDqUc74hrdGqSKLNODo03CipgNplBNVOo0in5HBw6ckpc/s3HHhAl4Tu2jzduFccAM6dPQErKEFFF1WAwiBfhtWu5OHv+CshPYeK4UaIv+iLHTRIq49JSce7cFdQ1NoKKw5nNFvFypiiaAiGGdAgODsLdy1fCYjLjZPoeUfW1vq4exaUVIlX40CHxkEolIiOn+JJIcCrzAih/xaOP3IMbN4rQ2mq0FmNTyJCReRFFxWUYkTIEkyeOhaKtEBtZIHJzC0Rpe41ajW8/+ZBYZotOL4rO6Vpa8OWWvWJdSUlxUMoVon4MFZRraGwWP/96Iwde2iNbkTOyPp27mCUie5xt8XFRWLxwFkpLy/HFlj1WsREcipYK11k2glVBUCm8wGLD2V3i+/qbAIuN/ibO4w0YAa1ci0hNZI/HKFTB1TsuAapAxy0bVKCMEl/FREfgdOYFkYdh/pxJQmiYTBbs2nusV4tGb1BShsUhKTFGCI3MM9fES7y3Rs6X9JIXZebVKuEHQk6o1uOYIFGsTUFVVBUKFBaV4ur1XAQHBWDurCnCAkPOq/Sd0qlTtMWnn2/HvNlT4efvY03h3dY2fblLJCmbPHEMRo6d0anE/JUr2di19wj8/Xzx6OoVInMnCSST2QSzyYI33/lY9LKYIjr8qeS7WeTpMBiMOHPushAbEeEhwkGT5k71SshSQxVvS8sqRU4RtVoJvd7QXsHV2QeLOEyaMEIILmqU1vzIsTOocyJKyDYHKmNP6ekpVFgmV0AVHIKWijI05uc5O81O97WLjZZy1BncU/PGJRPlTphAGwEWG/wo3DEEbGLDaGpFma5rGm+b2FAHBaGp2P5jFHpRL186DzKpDDt2HxKfaBctmNqWMluCnXvSu/1UbQ/4mOgwjEkdKi49e/46Copck37cnrHJ5yE0NAgVFdWdklfRi54sFcLKAYsIA506c7EQDCeO7aHXNSxmi9NWHHvm5upr6MhrwrjhCA70F12TiNl36JRLasosXb4QOWU1uHTytAvFRjBUCo2IqmKx4eqngftzBwEWG+6gyn16JAESGxGaSJh6Exux8VAHBzskNnx9tMIRdN/+Y2hu1mPB/MlQihL0UuzZd1xUXXWmBQf7Y9L4keLYwd15NJyZn+0eZ3026P60MSMwcsRQfLC+axr0W5mTM/fKpVLMnT0RKpVC3E5VctNP3kzG5kyfZGWaPXcqhoxORcaBozi8+StnuulyT7CKxYZLQHIn/UaAxUa/oeaBBpqAl9wLkZqonsWGjI5R7BcbqSOGISs7Tzgs2hqlDaeiatQOH810KmEX3UtF1aigGH3ipiqlmeeu9js+qkx7/sJVcdTSW7sVsZGSPEQcP/37jfVOW39cCYbEwfw5NwVHbn6JKOR2K00qV2Dq/FmYlByHY1/txN79x26lO3GvTWyUtZSh3mCNquHGBDyZAIsNT94dnptLCdjEhtnUitLujlHsFBt0vDBn9mQRtmmLcKCJJiVEIyU5Xsz55OlLPWal7GtR9Ml6+pSx8NKoRKXY4ycu9PuRBGUMfeyRe/Dllj3Iv9H7kdKtiA3KyrnqoaX45NOvhC+GJzQ6Jlq0YAoUcpnwNaGidqVl3WcYtWe+UoUC6qBgjIoNw+JxKXhj7QZk596w59YerwlWh0AlV4PFxi1h5Jv7kQCLjX6EzUMNLAG7xUZIMJqKun/BksPlkkWzERkZgj3700GOkNT8fLWYNX0cLBYLsnIKcOWac6nD6UU3ZXIqggL80NSsw9Fj56DvJorC3SQpamXBnKl4oy3pWG/j3YrYIMvNs99ejb3703HpSpa7l2V3/zSvhXMnWx1lLRYh+HpKatZXpzaxQaGvgZZW3Ci49ey0LDb6os6/9zQCLDY8bUd4Pm4j4CXzQqRXFDpaNigSwctLI/JVGMxmEY2i7kFskEXjoQfvhrdWi6927BcRE9ToE/DiBdNE+GSrwYRde9KdLoZmizyhpF+Hj51pr6viNig9dDx31mRR3bS7kvJfv+VWxAb19fiae5GbV4BDR0739zJ7HS80OACTJoxsu0aCQ0cznIpQEWIjMNga+nrDGo0yIS0VsXFR+GzTDqfWbBMbpS2laDA0ONUH38QE+pMAi43+pM1jDSiBm2LDgIA4H6xYthCTJqaJT68USXH81BlsO3kRpbqWHi0blPuBzP3VHVJ3U4irRq0UCad27HY+8iQsNBATx40QjDLOXEFx6cAdK6x6cKlIFkbhq301EhvzFt0jkont37PF7kJstn4p9FWn03XyfelrzP76fdqYZERFhLQLjn0HT6KpucWh4W1iQ1dehqYCq8UrbexIrHrwbhw4dALbdjierj1EHQKlXA0WGw5tBV88gARYbAwgfB66fwloZBpEeUVj+pQ0rH56hXgpymSy9km0mkyotCjw6a6DOLZjd/vPfX21iIuJxvmLXZ00Y6LCMGaUNTT1cPpZ1NY69ymT8nTMnD5W5GZwhVPirZKl7J7NuhaU9pHTg6w5UABDUybCYgGyrp4ERO4sSo81+Bsdm82dOV4IUrEqiQS79h0XFXvtbVKlEuqAIHQUG3Tv9KnjRcj09h0Hsf/QcXu7E9fZxEZJSyka2bLhEDu+eGAIsNgYGO486gAQILExf+wsPPPUo1CF3ExOZZuK2QJUWGSoaDXhw9fWIi+vAOQoed+KBTCajPhow9ZOFVrpRTR7xjhxjHIrESN0PDNtyij4+fqgprYBx46fv+VEVf2F1yI3oWJCLob6TKM3Ma7XH0HIqQRIjDdFXF9zCQ8PQdrYEdix45BHrntoUiySk2LblyHq2+w9DqO557TzHdfck9igaxbMnY4F86dh/YbNIpOrvS1UHQqFXAUWG/YS4+sGmgCLjYHeAR6/3wiQ2HjlpV8hJjIM6jBrLoWO7abYMKLowiVs3bYb9yxfIOqcbNq8C01Nuk7X0yderVYjBMLR9HNO+2mMTEkU9VNaDUYcOpIJnZN5OVwFkjKNkvC5ePl6n126QmzERIfj3hWL8P4Hn6O23jnLUJ8TvYUL5DIpZs+cII7KKDqFbDaOiEsSG6qAQLSIY5SuUSgzp01AxplLaGruvT5MxyWw2LiFDeVbB4QAi40Bwc6DDgQBPy9f7PrwE5SXlUMZ3LNlo8pghp+F6oZcR0N9I77YsruLAEgZGoekITFiGfsPnXbakZOiTqZMHiVeYCczLqGs3PkQS1cxnT93KkKCAvHRxq19dukKsUG1XKimiz1htn1OyE0XUPn4cWOTRQgyZU+l/wqKynH2fN9F22RKFZQBAT2KDduUKTmcj7c3ikr6zhLbLjZ0JWg0Nrpp1dwtE3AdARYbrmPJPXk4gciQcHy59gOUlpT0KTYCYMKu3fuw/9AJYdno2LzUKsyfS3VPLMgvKMX5i86FbFJ45czpadBq1LhRWIZzF/q2JPQH4ocfXIqKymrssSP5lCvEBiXSeu6ZR3Dw0Mlu/WL6Y832jDFj6hhRP6WyshaU3ZXamfPXUdhHCnl7xcbqVcuRGB+Df7z6Pur6sPCw2LBnx/gaTyLAYsOTdoPn4lYCjlg2fC0G/PRnv+/ko2Gb3II5k6FWK2AyW7BtZ9/RGj0tatTIIYiLiUCzTo+DRzJuuQ6HK+CR/8gzT63G4SOncO5C31lLXSE2aN6PP3ofsrNu4Ei6Z4W/dmRqixYinw2KSKHcKuQwSpYtqirbUxNiwz9AFGLr7hjFdp+31gvffe4xUaX2tTc/gtFo7LFPFhuueNq5j/4kwGKjP2nzWANKQCVT488/eRnREaG9+mxUGkyoLyjA3/+xtst8O4anHjiciYbGJqfWFBIcgMltORzST5xHZbVnVO4MDg7A6oeW49PPtvVZXZYW7iqxQSHF9Q1NfaZGdwq2C2+aOW0s/Hy9kZVbiPiYSMjldBwnwfbdR3sUi+1io7wUTYUFvc4mKiIUzzz1CC5cuo6PeznGsomNYl0xmozOPYMuxMJdMYE+CbDY6BMRX3C7ECCxsTBtNp558lGowrr32aiEHJWtJpBlY8OGTaJcvK1RQbQZ09Pg6+2FauEUetYpNBS9MnvmeKhVSo8Ic+24CCqNPn5cKg4cPGFXrRJXiQ2nQA7ATeGhQaI6rEi6djQTc2fTcZoZpWVVOJV5udsZyVQqKP3IZ6NvsUEdjBmVggfvX4J/vvo+Ssu7z7USpgmDXKYEi40BeAh4SKcIsNhwChvfNBgJkNiI8YrB9MlpWP1M1zwblCeiok1skM+GBWZ8/MlmnDhlFRW22ieUPnz/gdPdHrHYw8VWrI3SkVP0idFkXwilPX339zWuEhuUyyQyPAxXruX09xIcHo/8bPx8tKISb1VNLSZPTBUOo2fOX0NhUXmX/qxiw9/qINqHZcN2M0UD9ea3QWJDJsRGEZqN9kexOLxYvoEJuIgAiw0XgeRuPJ+ASqpCjDYWMJngG+uFFcsWYfIkawZRcvasqq6FOTBEWDZIbNjyUm38bCsyMs5h0fwp4rpzF7Nwo6D3Sqg90fD31WL6tDTRNZUvpzLmntTCQoPE0VCznVkyXSU2hlMtlnnT8err6zzCd6W3PYkID8b4sSnQtxqwd/9JJCREgaKTqO0/dAqNTZ0zjLaLjbIyNBX1fozScVy5TIY5s6bgaPppkWCtYwvXhEHKYsOT/unwXPogwGKDH5E7hkBHsUHmZ2q22igkIuoaGrHmu89i5JSJ8IeJclS1t7Nnz6O6qkLkWfhq+xGnc2pQ2fgAfx8UlVQg82zfDpj9vTlPPP6AsC4cS8+0a2hXiQ1bro33PvgMdfWeHcpJVox5cyaKvBtkzSgqquhUJXb7zqOdqvTK1Cooff3R4qDY8PXxxg/+85vIzi3AuvVfsNiw64nkizyVAIsNT90ZnpfLCXxdbJAz3uTJafhyy+72T9M+CUOw4J6lWDhxVCexQZPJysrCZ5u2O50LIzYmHKNHJomx9h8+7VDKa5fD6KZDlVKBp7+9Gjt3HcLV67ntV9AnbDLFUIiqEGASCfR6a7pupbcMhalXO2UQDc0cAugloNBeupeEHB1RmS1mWMyWTi9i2yBUH+XRR+4RhclsBe76Y83OjpGUGI2UYfFCGB06egZqtRIL55Lly9zFn8dZsUFzGzUyGWtWr8DGT7fhVAf/oXbLRnMRmk18jOLsPvJ9/UeAxUb/seaRBpiAUqpErDZOHKPUS2vx3f94DI0NncMMSWyoQ0IxfUQSFi+a1WXG27fvxa69hx1eCb3IZ88aD6VcjgtXcpCX53yZcQpPVSoVUCmVwomTTOxeXmpER4ZDoVBAqZBDrpALUZN59pKY69w5U0D5QWRyOeRyuTg62rv3qCibPmnCGIwckQSFQg6VSgWjwYgLl67h0JFTCAsJwkMrl3Zar16vx+trN4if3b9yIV4reLWT2BhXNh2FuWWYOH4UpkxO63Tv9aw8bN95ED7eWjy25l6YTeZ2EaLWqLFrzxFcuZqNeXOmIijIX6zBZDKJMNBz56+KaJXwsGAkJsTCYDDAYDDC0GpAfWMjCgqtR1vBwYEwtLaKYw76HSXicnVTKRSYN3ciaC+OHj+H6pp6REWGIG10shjqZMZllJVXiT/bxIaurBTNRYUOT2XlfXchNTUZf/vHu8JHhFq4JhxSmQLFLDYc5sk3DAwBFhsDw51HHQACNrEhk0iw7OEZCAjwEwmU6htumu1tYqO5tBjzZ0/DkiXzusx0164D2L7LsUqdo1OHIjY6TIR3HjpyRhzDkDleo1EJCwD9nBp9klVrVNCoVFCplVCrVNh3IB2NTc2YM2syyLeBxIKtnTx1FuknzsJ2DEE/pxeswWhETW19ewnzpXfNhkwmFzVexAvcaMLpjAsiPXh8bBTCQoNFoqqE+FgcOXYa5RVVwsJA9V/i46JFRVeas7BQmM3IybX6HoTHBOFc1PFOYiPm0nDo6w0ga0VQoL+wipBFhNbb2NiM4tJykPhKHpYIqVQKiVQKuVSCkSOScejISWTn3hBVUQP9fSEj64j4kiPzzCUUFJZgWFI8pkxJE0XrxJdSgRs3ivDFlj3iWIzyhHRsJJ7eXfeZ8EOZMmkMgoMChWWmRa8XCdvy84tRXlkl1koJ1ijvCf2c1ttbs+0pVeelKr3UbMdkRqMZu/cdh9FkgkythtLXD86KDRKV3/vON3Dy1Ln2gm02sVHUXAidqXMa/QH4p8VDMoE+CbDY6BMRX3C7ELCJjXkzJyFlchxeX/sRbhR0tjBYxUYImktLYDGbsXrlMkyYOK4Lgr37jmDrtj3doqGXqtbbC970pdHA398HYWEBwimUIhjGjR8FL40GGrVKvGgrq6qxfsMW0ddT31olPu3Ty46+6KV48PAJIUZIFPj5+1g/sesN0Le2oq6uQTh00idsenGTkOjrJdnTflLI5bChCfjks212b7mrfDbsHrCbC4m3TG5dOx31UA4TpYosPErxnV7WFy5eEy/+8WmpiAgPgUqlhFqtFscf6SfO4OKl60hJHoKF86eLEUhQ6XQtKCoqxY7dVksWCRUSLFQjp7GpCaS8Jo4fAbPFgj37Toh9IWE0d+YEqFQK5OYV4+KVnFsWGzQ2PSsda+aw2LiVJ4bvHQgCLDYGgjqPOSAEFFIF4rTxmDV1HHJr83D8ZNc8GR3FhkalwNzZExETHY2hw4Z1mTNFqGSeuQA/P2/4+HgLiwC9iBYtmCE+tdtaaUkpdLpmlJRWIv9GqTCJ00uruVmHZp0OjQ3N4pP1YGyuFhtkqSCrzEA0smwE+PtCo1FD66URglDX0iIyqZLFhNKJe3trIJXerGh79twFkXeloakFSpUaDXUNMBgNiAgLFHYRquBbp9ND6eMrSsw7c4zSkUXa6BHIzS+EulULqUwOtmwMxJPCYzpDgMWGM9T4nkFJwCY2pGYzCpuLul1Du9goK8W0SaMQ4OcNiVQGX98AjBs3uss99fV1uHGjEPX1jdizPx21tXXCp4COP+joQ66QYsLY4cLacEAUbOscwuhJIMlC4KhVxJViY/GCGfDSeuHzL3Z6EpZOcyFG4rilzXIFWJCakiCsKt4+vkJ0entrUVFegcbGBiE4LmWXIHnUcDQVl6AqOwtlFVUoL68SlilHGgmeF37wLRQWlmDXphNCbBQ2F6DF5LnPlCPr42tvbwIsNm7v/eXVtRGgGhb/74XnkHW8CGczLnQSG/QCCQoOAEWnGPyCUE55NiQmjB+bLHwVQsPCYDJZhPNlSspQSCSds4+mn8jAxo1bu31R287w8wtKcP5itsfuBx3DPP2th7Fn31Fcy8qze56uFBuzpk9ETEwk1n3UOczT7skMwIXke0JF+Si77P7DGcInhY5SAv39RLIvik5p0JvhExqKCI0CEWqrVeTS5Sy8t+5zkUWWcmmQf0xxSRmqq+t6FXyjUpOx5uEV+HLdAeQVlLDYGIA95yGdI8BiwzlufNcgI3DvioVYdf8yvPWnz5GfUyDEBp3Rz5w+AdFR4eIMn1p6TjEOX8hGYqAX4qPDhE8FFVujT67U6Mz/4VX3Cv+Iju3U6bPY8PFmEVlha+HhQcKqQb4C+w+eQove4LHUKE35mtX34PMvdvRZxbTjIlwpNiakpSItbSTeeMsa6TJY2sRxI0A1c7JyCnDlWn77tONiwzFqRBLMcgWOn89GVW4eDBVlCA22HrEUl5QjJDgQ337iIfj5+Yj7WvStyM8vwjvvfSpEB1kzKOKoY3vyGw8iQhOJDz7ajNz6XLZsDJYH5Q6fJ4uNO/wBuBOWTz4SP33xOeTlFMG7xQ+7dxzCrswDQmxMGJcqIhzIEZD+5y8Lj4QqJBRzxyRBYjEhO7cIl6/ezDlBvMaMHoE1q+8X4aMd25kzF7F+w+ci/ThZS+bMHAetViOcQq9m3XwJeSLzxIQYLF0yF2+9+4nwO7G3uVJsUDG2+ZRF9N/rhEAbLM2WUVTX0oo9+090mvbC+VOg0GjQAhn2frETzSXdH99RxdfIiFBERYaJo6St2/aJfn7+0ndEtFRObiGyc/KRnX1DOB4//81nkHnuCjbs/QJ6PkYZLI/KHT1PFht39Pbf/ot/5OEVWLFsvigFXlxUgaIzlTiZfgYnc7vPkOmTkIiIoUkYExcCWMzYsftYt+mzU0cm47E1DwqTecd2/vxlfLD+M4SHBWHsqGEiQmHfwVMen4KbQk0nTxiN195c79BD4UqxER8XheVL5+PtdzcKf5fB0ugIauG8yeJZOJx+FrW1De1T99aqMXPuVECpRsaBo8g9e7OwX1/ro8iaMWOGIzEhGonxse15R37/ymsYFjIU1bX1yK7LZbHRF0j+vUcQYLHhEdvAk3AFAUp0NW3qeMydPRmffr4D585fwbQp43DPioV4572NuH41H/HeCZCaLShs7j65kk98IibMmYpgBZCbW4BLVzpbNTrOc3hKEr752ErIFYpO07946Spyc7Kh9VLjyrU8ZOU4nsjJFTwc6WPurMkIDw/B+o+tIbj2NleKDXpZ07GBTtd3jgt759df16WNSUZUREiXoxQaf+SoFMQOTYC5pgpffPCZCJV1ptFRV0J8NE5nXkSkJhLf+94TqJPVYMf+gzh+4oxIcMaNCXgqARYbnrozPC+7CWi1Xlh291wsWjgTXhq1yDRJacWvXussFOQSeZvYgHCs666FJKdgxpI5kDc3YN/+E30WJEsemognvrlKOI92bNXVVcg4fQa79qV7vFWD5k0+K5RIjJJ8OdJcKTYcGdfTro0MD8G4sclobNSJVPQdm9rbG3MXzoRK34isjHM4ccp+60ZP64zyisSiu+ZgxrKxkCohoqEoM+uXW/aIzKrcmICnEWCx4Wk7wvNxmAA5f953zyLs2nMYO3cdFtkvyYHzh997Al9tP4DLV7JEnzKJDAneiZCaexYb01fchbDEeEgaG7Bt+0G75pKUGIcnn1jd7mRqu6moqAT/fPUdcZRyuzZXig2ybFD469m2tOSDiRnNnaoCi6iUr1V+lWs0GDoiGcmhPlA012PDxp3CEfRWGlk2ZEol/vPnq1FcbvU3Sh05DC/+5A8wmVyfnv1W5sr3MgEiwGKDn4NBSYDqeFDiLMoMKbJBqlSo6/CpnCwdFF3xs1/+H7JzbnQSGzKLBAVN1p99va1+9hvQqzXIOnsBWdftd+qMj4/BU08+InIwdGw5OflY+/b6W365uHOTyDdgyeJZyDxzEcWlFQ4N5UqxQQN/59lHcfDQSZy/6HkVcfsCM3lCKkKC/XH5ah6yc28enck1XlBovbFoQjIUzXWoqq7H1u2H+uqu19+T2IBMhtixIXjm2Yfxk5+/gty8QpH5lBxNly+bjzff2sDC45Yo882uJMBiw5U0ueIzT9MAACAASURBVK9+I0C1IihM8ns/+LVI192xhYQE4pXfv4S9+47h3Q8+a/+VzbLRk9gICvTDoofugV6jxZ7Nu2Bo0Tu0nrjYKDz3zONdjlTy8gvwxtoPRfpxT2x+vt54/NH78cXm3V3St/c1X1eLjW99c6XI2El1QAZbi4+NQOqIIaipbcCR9JvZaUlsyLVa+JpbMSs1Tizrsy/2otGBqJ+vs4jyioJFKkVB8w389n+eR01NHX77+3+Jy8aOGY4fPf+UqKnz5lsfDzaMPN/blACLjdt0Y2/nZZGT3O9/+2P8/V/v4fCRU12W+tKPn0N0VBheePF3nV7w9Ak+0XsIehIbdy+eCb+EBNRLFTjw1V6YHUybHRjgi0Xzp2Ns2tgugqOgoAivr13Xpw/IQOybrYjb++s+R23dwPpsPPrwPcgvKBIVZwdbo/ol8+dMFPkxdu5Oh6EtN4tNbOhKS3DPzNGiKu/17AIcO+68oLKJjRtN+Rg1dhgmjBslwpZtTqKUMv9bTzyE7z//3ygtc8xaNdi483wHBwEWG4Njn3iWHQjMmjlJmNsff/K/RKGyjs3X1xv//avnQS/OU6fPd/pdb2KDztofemARJMGhOJ1TiuJrWQ6LjbSxyYgKD0FDkx7z5s4Saas7Nsrl8fqbH3hcWOfIlCRRgv7V1z90uBy7qy0bK+9fIj6l7953dFA+83Nnjhe5VU5mXEJZebVYg9xLC7mXF0hseBt1WLJoOiwWCzZt3o+GRudCfG1iI78pDwZzV58gqvHy2j9/g1f+/OagtBINys3nSfdKgMUGPyCDjkBCfAx+/9sf4a//eAdHj2V0mb9MJoOpm6RQvYkNyotBDn4Nah8cPpcLXWW5Q2KDqofOmz1ROAgeOpoJjcYLzzz9KHx9rJkhba20tByvvf5+l6OfgdyEKRPHYPjwJLz93qcOT8PVYiMpKQ6teoPDxzkOT9xNN4waOQRxMRHtFV+/LjZIcCycOxkREcGoq2/CF1v2OzWTaK8omKVS2MSGXC7HnNmTce7cFeEgTWHZv/jpd/HD//otWzacIsw3uZoAiw1XE+X++oXAg/cvwbH0DFFTwtZGj0pBRWU1SkrKu52DFFIk+nR/jLJk4XSEhPjjRrMFFwor0VJZCbPR/iiS5KQ4DE2KEYmWjqZbzeMhwUF47plH4efn12k+5eUVQnDU1Tf2C6u+BqGwzQB/P1xsi9rp6/qOv3e12HBkbE+81pZNtL6hGQePWIWwsGxorJYNXVkJgoMDcPeiaeJ3mzbvA13raGsXG415MFgM4tjuX3/7tag8TKnOqUVEhPb4b8HR8fh6JnCrBFhs3CpBvn9ACVCVzXtXLMC27Qfw25dfEIm8/vnaBw6LjW+sWSZM28eyylBjljokNshiQmf1KpUCGWeudoroCA4KwLNPP46AgM6Co7KyCq++/oGoEjuYm6vFBr2Ifby1IrJiMDYqzEbZRKnt2ntchD2Tc6hcfVNs0O9WPbAYKpUcDY0t+PzLPQ4v9etigzp49JF7cfdds/HV9v344MPBU8zO4cXzDYOSAIuNQbltPGkbAbJmPP/9J0FmZKlUgl++/Fdc76FqqbBs+A6BzCxBYVNBe3XNAH8fLL97lkhpvunIRSiCQxwSG5Q5kjJIkv/Inv0nu2SIJKHx3NOPISgosNPGVVfX4LV/v4+qmtoB3dDkoQkoq6h2Svi4WmxMnZKGYUkJnaKIBhSOE4PPmj4Ovj5eyDhzBcWlld2KDXImXrZkpuj98y/3Oey7Ee0VDbNUgvzGPASG+GHxoplYOH+6sHCknziDv/ztbSdmzrcwAfcRYLHhPrbccz8RoKqtf/ifF4VlgoqjrVv/BbZ8ZS1k1bFRcbQhvkldxMas6eMRHxeOVoMRW45fhTo0FC1VlTDbmYnRVkb+atYNXM/qPn+Hv58vnn36MYSEBHWaU21NHV59431UVlqdCfu7EZP/eHYNDh0+KUJOHW2uFhtUVXfcIKz82pHbyOFDkBAXgbwbJbhwKbtNbGigKy0Vxyi29vDKxSIypay8Bjt2O+YQG62NgVkCNGpq8dc//1w4HZN1Lyw0SCT3+s73fyVybnBjAp5CgMWGp+wEz8NpAhTiN2XyWPzo//0e48aORG5egTDDz5wxEZMmjEbmmUs4e+4yqqvr2sVGUVMhzLD+z/ix1UshkQCZZ64ip8EATWgYWqrtExtk8p89I01YM/buP9FrGXmKlHnmqccQHhbSaa2UjOzf/34PZRVVTjNw9kaqNvrENx7E5q/2Is+JowtXi43RqcmYOWMC/vnaOmeXNOD3RUaEYNyY5PZ8G9ZjFBIb5LNR2j6/qIhQzJ87UYSrfrppb5dS8l9fCEWYDBuaIKoVhyrCse6TzchrzMXosSm4cPEqWlsNIqFXbEwkTpw6x2JjwJ8EnkCnD3tJKdOdqwrEHJmAhxAICQ4UznDkr9GxTZo4BsvunoehSXEifXlBQQlOfHUJZzMuwyY21ColHnpgobjtk892QRoS4ZDYGJGSgMT4KJSWVeFU5uU+iVA47LNPPYqIiLBO1zY2NOHVN95DqYMZPPscsI8L6JPwQw8uFQXYnLGuuFps0IuUjgMGW5n5jpipAN/cWRNgMluwY9cxSL003YoNumf5kpkICPDFmXNXce6CNa2+rVFRulaDAb4+Wjz15MOgZHWUivxGQRGKL1Yj88IV5DTkwGjhAmy3+u+A73c/AbZsuJ8xjzDABLReGoxKTQb5d5RdqMOVi9nwj9dgyeLZKCougUxqRlNzC7ZuOwRZaJvYqKmCubX3+hV0BLFg7iThGHoq4zJKy+2zTFAehqe/9SiioyM6C46mJrz+xgedImzcjW5IQizuXjJHZJrUtbQ4PJyrxQYlGJsyOQ1fbt49qGvKLFowBUq5HIePZqLRhB7FxpCEKEyfOhYSiRRHjp1FVFQEoqPDERMVjrq6Brz6xoeg52zZ0nnIzbmBrJx8kfo+2isGZimQ25gDk8XUad/CQoPx8KplYk+bmhyPdHH4IeAbmIAdBFhs2AGJL/FMAt7eXnj5lz/Ea69/iGvXey4F33H2Sb5Dhc+GxbcVo9vKguv1OgQEBKC2vhkb95+CT0QUhseGoaqiEuRTQVk1jd3k7QgLCcTE8SPES3HPPnIMtf+MXKNW4+lvr0FsbFQnuM3NOpH4q6Dw5tm+O+nHx0Zh/LhUfLpph1PDuFpsODUJD7zJVifl/KUsFFU1WMVGSTEM1VUICQ5AaEgQQkODUFpWiXFjhsFiMSMqKgpqtQaFRaUoLCxF3o1CXL6S3e3qYrSxMEks3YoNP18fvPqPl/H2u5+K4oTcmIAnEGCx4Qm7wHNwisDKB+4WpeW/+/1f2Z0kyyY2bMcojz+yDIAF5y/mCMtEvVyNsKQhWDJzPLzbiqqRox2FqK77aLOYJ1V5JfN2ZFgggoP9kZtfgouXu38p9LYwKtr27SdWIyEhttNlLboWvPHWh8jL9/zwT3eIDfokT43Sfg/GJpNKMXJEEmKjQ4XFLPNaAVoMJqTFhWP+hBHiSI8alYWnXDFGowEJ8WTlkuD9D7fatW6b2MhpzO5W5P74hadBPkJUiJAbE/AEAiw2PGEXeA4OE9Bo1PjHX3+F/QeOi9Tk9raOYkOhlGPVg1Z/jY8/3SXM09qYWKhDw9BaUwOFFAj090NgoD80aiVOZlwQ1z7x+APw8lLjRv4NEQHj5x8AXUsrGuob0dDQiDPnLou+6Bo6Y/96SvWOc6WKtU9+82EkDYnvLDj0rXjrrfXIzrW/8qy9DDpeR34B5KDo7Ivd1WIjMMAPj6xaLiwtJf3sv2IvPxKJ3loNvLVaaL29xD6fPGVNjX/fioWIigyDrkWHstIyKJRKnL1WiOKKagTAhECZRWT4pC9dW2E+tVKJVSsXiWfpqx1HUFnVdyh0X2KD/JVe+MG38PyP/weUJp8bExhoAiw2BnoHeHynCKxYNh+rVi7Fd3/wa1FLw95mExvFTYWIiQ3HrBlpoFCU99ZtEV1oo2OgDg1Ha20NTK3dV2mlJF7DkmKQNCRGhMs2NrXC11sLSjDm7avF+g2bRQG4ZUvmIiEhBoZWgzg7b9K14MzZS8jJLQCFwlLUQrOuBUajEfcsvwuJidaKoLbW2tqKt97ZgOtZ9h0R2cug43X0ctQ1t2D7budKnrtabPj6avGNRx/Api93oqCw/16SlIzLZDbDaDTB398PlFWVHD01Xl4gn5/K6hpRY8Q2PxtDi5n8fXR4/8NN4t7hKUMgk8qg0+kwPDlORCntOnIOMqXSGo1SfjPjbcd9uP+e+fDWqlFSUold+473uZV9iQ3KO/P6v36DbTsO4JNPt/XZH1/ABNxNgMWGuwlz/24h8LOXviM+Hb7+5kcO9d9RbCxePA3BQX6oqW3E5q8O2C026MKpk0chKMAPl6/mIju3qNs5UDZMf39f+Gi18PbWQKPR4MrVHFH3g15KC+ZNb7+PEor5+voK35GOjY5wTp86g4KiEpzKOC+sJPQiVKpVQsSQv0hrqx66Zj0MDlappXEeXX0P8m84X2XV1WLDS6MW1UodDcWVy2VQyOUCHVkM6M9R0eEgq4FSqQCJCaVShSPpp8U18+ZMRVhYENQqFchKRvV0duw8iGtZeRgzOgWzZkwCHWc16XRobtIJ6wBZtuiIhAQk5bVoamwG+diQSOmu3bVgKmheh05fgd5kQXNJCVoquhcb4WHBWDR/srAyffLZ7m59hDqO0S42GrLbQ7i/PodRI4cJ/4+a2nqH/o3wxUzAHQRYbLiDKvfZLwToCKK3I4ruJjHEJwlyixRk2Vi+fJYIK0w/eR7XrluTcbVbNupqYNJ3b9mg6JMFcycLz4K9+0+iuc0c7uii6cWl0aig1qhB5cmpLZg3C6mpKV0ER15ePta+87GwmCxfOg/xcdGdrjl85BQyz14S/iTz5k4RLy2jwSi+V1XVYFdbFdXFC2bAbLbAaDLCZDQjNXUYMjIuIP3kWcTFRiHQ31e8POnLYraIcNjyymqQCIiMCBP+AWTuJ28K6r+grAgVE3Ix1GeasBBdrz+CtNKpUEAlwnhpvsGB/sJaIJECMokMkEpQW1cvfk/9UgZTqUwGqUwqIjjGjUvFtp0HkJWVj2lTxoEcHumlLb5kMhxJz0BxSTnSRg/HpEljhLCQtPlBUPbY7TsPipTn33z8AcHIbDZB32KAXq8XIb7k7Dtx/Ch4aTTiZ2Rdokic0tJK4ftD49DaexIR9u7zzGljxNwzruSjur65V7FBfd63fA58fLQ4efqSELG9NXvEhr3z5OuYQH8QYLHRH5R5DJcSIItBZWWNU33axEZJUxFWrlwAhUKOL7ceQG2dtSiaVWyEobWutkexERsTjtEjk0SUyuFjZ52aR083yWVSrH74PowdM7LTJeT78cG6jTh34Yp4GdKndaVS2faJXQFKDFZf3yQKqsXHR4uXtlwhFxkqG5ub230K7lm+AArx0pZDJpcJf5TDR0+JxGdzZ01G8rBEyORSSKUyMf7Jk2eFEKFEUXRvx0YOju989EkXsfH/Rr0IrUKLTz/bjuLScsyYNh5pYzuvh5JQ7TtwHMFB/njwviXCt8VkNgkhRC/c3XuPiEiMhXOnwcvbSxxRmIwkkEw4e/6KEEDh4SGICA9pF1UkrOobGkUxPnIyJSFHjrx070C0tNHDEBUZimsF5cgvqYKuF8sGzW/ShFSkDIuDyQys+2hrj1OmtVEGUZPUgpz6ni0b1MHjj96H7JwbOHLUatHhxgQGigCLjYEiz+M6RYByCPzlTz/DH//vTWRkWh02HWlDfIZAbpGhQVaLFctmipfbuo+2tTtIaqNioA7rXWzYwhqvXMtDVo7rI0bI4rHqoeUYP25Mp6XRkcqHH32OzDMXHVlyj9fSS/2bjz2ALzbv7rake8eoEJqTQqkQL3HKtmprTYamLmIj9tJwyExytOj0wjpAlgdKI08WEZvFhLj35JRK/ix0PEFCYTC3pMRopAyLR1F1Ay5lFYrQ15aK7isS0zrJyvPgffPFknurBttRbGTXZ/Xq3EvHjSTkfve/rw5mlDz324AAi43bYBPvpCWsXrUcC+ZPx3Pf/blIz+xos4kNTSgwZeooWCzA++tvfopsFxv1tTB1czxCL86F8ydDKpFg/6FTaGxyPBGWPXMmJ9SHHliGiZPGdhEcH3+yGSdPu8aiQpEV5KDq7Kd/V/ts2MNmsFwTHhaECWnDUas34eTZa32KDVrX6pV3QaGQobikErt7cBSlgoJR2mhh2ehLbFDiukcfuQfffvYn0Onc86wOlv3geQ4sARYbA8ufR3eAAHnY/+tvvxYm4Xc/+MyBO29eahMbqVNiERLmh9q6Jny5dX/7BX2JjeioUIwdNQz1jc04eDjDqTnYexN9gn3gviWYOnVCp1soAdQnG7fg+Mkz9nbltuvcITZmz5gkHBuzc7svaue2xbi4YwqPnTNzPFqlChxIP2eX2BiSEI3pU8eIjKLvrrPmdfl66yg2suqv9zprSh7297/8Ev/317dw/MTAPy8uRszdDSICLDYG0Wbd6VMlZ8Hv/+c38fyPfut0Su9En0QoLHLMunsUZAog8+xVnL94syaFV1Q0NGHhaO3BsjExbbiIYrieVYCrWe7NgWHb7/tWLMaMGZO7bP9nn3+FI8dOOf1YJCbEYHhyIrZut0biONPcITaeeOwBXL6SJXxFBnOTS6W4a9E0mJQqHDp2HvUFN9BSWdHrkuieNavv7jXnhiNigwb78ys/w/kLV/HWO58MZpw890FOgMXGIN/AO2n6ixfOFOWz//SXtU4v2yY25q9Ig1lixFfbD6Oy+maejptiow6mr9UKoRfBwgVTRPjjwSOZqG9ocnoejt64fOl8zJl9M1TWdv8XX+7AwcN952XobrxJE8YgdeRQvPXuRken0369O8TG42vuRXZ2QXuYqtOT84AbF86bDLm3D06euYLya1l9ig2a8sxpaUiIj8TFyzk43U1xP0fFxphRKSL8lUKuuTGBgSLAYmOgyPO4A0KAxIZGqsLspakwS8xY/8kOER5qa0JsUDRKQ30XsRES7A9yDm1pacXu/Sf6ff5LFs/Bgvmzuoy79as92Lv/iMPzoeOKyKhQrN9gTWjmTHOH2Fjz8ArxYjx0xHmrjTNrccc9M6aOgU9ICM5dzkHB+Ut2iQ2KdqLjF8pCS5ltv94cFRvuWBf3yQQcJcBiw1FifP2AEKAU0BRqSXkQbqUl+CQixMcPE+YkoUmvEwmU/j973wEWx3W1/e5s32XpHSRASAgJVSRUUO/dtmTZju24xi1xqvPFn5PY+Zzkt5M4vTndcRLH3ZYtWb1avUsINdSoopeF7WVm/+fc2QVWgNiFRQJprp59dhFz79x77rDzzjnveU/7pktOEcMonYANXzn5sooanDp9/Vh5b+Z4vb4L5s/A4oVzOhyyactObA1SBXTxghlM0GrN2o43tEDn3xdg4wv3LEdNTR127u6ZxybQud+I44ggGjcoBRevVODC0ZMBgQ1Kf37wC2IohSoRNzT5i3IFCzZIsGzVXQtxsuAcSIdEapIFboYFJLBxM6wunTNoC1AKH0k/v/rT14Pu274DgY30pESMmJiKmvp6bNy6v1Ow4TKZ4Lbb/H43c1ouwg06HD9ZhMqbWLdjzux8LF/qr3lBE922Yw82btoZsH2YVLndwUSwetr6AmyMGpnFtEFKSkKfVtzTdfa0X072EAzOGoLyyjoU7DkIR0N9QEPds3IBtFoVqqobsHXHQb8+cnBI9majdEcQ9XX80x9+jN17DjMpfalJFrgZFpDAxs2wunTOoCxAKox//uOP8bc33sOOnQeC6nvtwQQ2powdhajBGphsFnz0yfaAwIZGo8L82ZOYcubW7YduugbEzOmTcecdizrYYtfn+7Fuvb+3piuDEUHU5XL1qgZJX4CNXm1wP+uckZ6C7LEjUFffgkPbPg8YbAzNSEU+y0qR4V/euj2+pfnAhlsm4LKpjdx8vaUTsTomOhI/+OFv+pmFpOncLhaQwMbtstMDeJ0L5k3HY4/cjae/8mKvwyjpYRlYOmcaYHCipOIqdu3xV1bUJaVAm5iIaz0bvpTXvlAN7enWTJsyAatWLevQfe/eQ1izdnNPhw2qX1+AjYS4GObFIiXQgd6SE2MxdvI4NJus2LN+e8Bgg2TZH/zCEhZKWbt+N1Or9TUF5EjSpyAYsEHkalITffSJ5/04SgPdvtL8B44FJLAxcPbqtp3pD77/NSY89erPeq+CSGDj7qXzYFO0YM/B47hc7O+q7wpsjB87HClJcbh0uRznL96YlNdANnxy3jjcs3o502Vo3w4eOIYP12y4rrpkzshhuFpRDWNL240skHO2P6YvwMady+exarpUsXSgNyr0lzc9D1abEzs+3Rww2KB1+wS+CgovoKCwjSPUE7AxbGg6/t8Pn8Pz3/0pSsukrJSBfl0NxPlLYGMg7tptNGdyI3/7m1/CwcMnQcXGetsIbNyzfD4sXDPWb92Nunqj35AENjQJiXBbTHDb2jgblMJIlUP3HypEYxAl7Xs730D6T8wdg/vuvQOctxiZr8+Rwyfx/kefseJp1zZay1NP3I9NWz7HxV7ohfQF2KA0X4F390r/IxC73YhjIsL1yJ8zFS6XgM0frQ8KbGQPT8ekCTkdys63gQ0el02XA1oGEYHvumMBqzlTVzfwPUYBLVo6qF9ZQAIb/Wo7pMn0tQXSw9Jxz7L5sMhb8OHarTBb/EmguqRkaBKS/MCGTwmS6nps3nqw05t3X8+7u/HHj83BA/ev7AA4jh8/hXffX9uhgmlEeBge/uIqfLJ2S7/jbCxbModV1P1sY+Bk1+7sc7N+T9V8Zy+aASp5+9k7nwYFNmiP7lw+i9Xveff9TXB7S9kroECSPhluWeBg42atXzqvZAGfBSSwIV0L/doCKSmJqK1tYETGULRhUUNx18LZDGy89d5nrV/gvrE7AxuDUhMwdtQwNDQ148ChwlBMo0/GGDMqGw8+cDerCtu+FRScYQXc3FRO1NviY2Nw373L8N77n7EKqq1fCEoZwAHkJBFcHnjaJEg6nXNfeDaWLZ4FuZyq8fqTd/vEaH08KKWxLlg+FzJOjk3vr4O5piaoMz7y4HLG29i+8wiuVolF3HxgwyVz44rpSsDjUfp4bGw0Ck6dC7iPdKBkgVBZQAIbobKkNE6fWOAPv30Zh48U4N9vrQnJ+KOTRmLxzHwY+Ub896MNHcZsAxtmuG1W9vsxo4ZhcGoCLl0px/kL/Yev0ZlBckZk4eGHVoPqyLRvp0+fx3/e/qi14NqgQUlYcedcvPPRp7C4bODUHDiVDDK5h93cZHIZIAAeQQaP2wOPyyOCD3p3e4EI/SznO1R9jTuaAZnbH/AEs3kkNqZUKrBtp39acjBj9KdjFy6fB4VSgR2fbEJjeXDpvCtXzIXBoEVtnRGbtorCbT0FG1TEcFr+BHz1Gy/3J/NIc7lNLCCBjdtkowfiMpOS4vGbX7yIn7z2Z5wsOBuSJeQNycXsvFy0oBn/eb+j5oA2MQn0clssrWCD1BwplHLk2FnUDIB4d3ZWJh595F4olUpmMw8E5nIvunQR761dB49cQHxSNEaNycK+Q0fBk/tCAcjkdCwAwcOABhTeIvMMdADgxXffZzpYgID64eVI04xn/3/JeBjRRwcBNg4ePiRbNuAHmbN4FhNP27d+G6quBCeqNXTIIORPGQNAhn+/LSq9KmQKJOmSEaxnY3r+RHzt2YdZRopUAXbAX1YDbgES2BhwW3b7TNiXrvf4Uy/A4XCGZOGzRk7FpNE5MHMm/OvdTzuMeS3YUCuVrKQ8tS3bDsLp7iauEJJZ9nwQAgycWoYhw9Nw3xeWs8+895/b40ZpRTm27doN3sMzD4bH6QHPPBaA4KSwCYMbrY3Gkylk4BQyBkjonbweMgInnAwe8GjOqEWSNhsUf6kwn0bEuUTIXHLRK8I8Idd4RgIIz/TcAv2v54z502EI0+Pglp2ouBAYodO3CrVKhftWL2A/frBmG2w2RyvYcMrcKA4ijJI2OBmv/eQFvPh/v5KURPvfZXLLz0gCG7f8Fg/cBX7nuSfZE+GPXvl9yBaxasZiZKakotHVhHc+Xt812LBa4bZakBAfjbzckTCZbfh8r78mR8gm1cOB6IbPwh9qGeRqmRgGoegJAQQ5kJQSh7nzpokAATLIPXJwghzVV+uw8bMdcNjcvSO7coBMJaAlpxqpYaMYCKl2nEdkSQJkXjcJ825c4xnpLjwza2oe9Do91t8CBFHa2ulz8xEebsCRbbtRev5C0Lv98APLmX/q8z3HUFpeDaVMiURdEoIFG/S39ObfX8Nvf/8m9h88HvQ8pA6SBXpjAQls9MZ6Ut8+tQBJlFM9h8827AjZeR5dthpxhkhUW2rw0Wcda4JoE7xhFJsINij9kNQcb2Y9FFq8TOUFFF5QQSCD+BV0T/eBCwY0OLTyK8hTkRATizuWLIJGrfGzYXNzM+rq6rFufS9tK+fRNLISg3RjydOPcksBos4mA4KcgQ+OPCAEdliYxuchuX54ZkreOGjVOmzbso8RVIkr0soXcXlDPCG7Ivp+oKmzpyIqMhzHd+7FlTPngz7hlLxRyBqWhrPnruDoiXM9Bht04h/+4Bv4bMNOHDl6Kuh5SB0kC/TGAhLY6I31pL4DzgJPr3wA4Wodyo1XsXZzx9TKa8EGfdHHxkSi4PRFlFcEl0nQI+NQMkgroJC1ETc5j5/XgjkOZD5gIcDjbLspi8SLtpaYEIuVdy2FRqP2+3+b1YY3//0+qy7a49YV2OCvTxDtNDzDQIkMY0ZlQavR4tChglaeCPOGtHpJBlZ4ZvKMyYiJicTJ3ftx6VTw3KMhGSmYPnUc04TZuGVfK9hwwIUSc3GPt07qKFngRlpAAhs30trSuQK2gFqtgtPpYryCvOMbmwAAIABJREFUULaHFq9EUmQsCkrOYs+hjmGRVrBhtzKS6ML5U6BSKLBn/wk0t/Su4myHdXAQwx/eTBARZIjeCfFm3Oa1ICt4nIKXVwHwxK+gp/wAW3xcNFbdtRRandavR21NPT7+dAPjAnTWyAfBcTLISPjC21hQhpMxT4YgF1A3tNTPsxF3KQ0cTy4WIpN6/FRMaTtJN4L+ddUmTx4LXZgGu/cfET0iPq6Ily/Cxu1BeIbZK3CTBWjZ7g8jBdG42GgU7j2IopOnu+9wzRGGMB1W3iFW+v3vuxsh9yiQoEtET8EG/W2FigMV9GKkDretBSSwcdtuff9e+JceuxcZ6amMzBbKdv/8OzAoNgH7Co/ixNmOegNUXp5lo9htUPJuzJudx+p0bN56oIMwVjDzauVXqAhceF/twAQLh/gyQngPAxVi6ICIm4JfZgcnk0HOcZAr5ExTg0qIs5/lcihVCigVijatDY8HSrUSJC5FJMXRo0dDpSZE09ZsFguKiorg5on8KqIKlv7aHmF0sVinx4lN5s1+YGNx2CKoZP7n6N5WHvC8By63Gxq1iq3FbneIwMTjYe8Wi5URWxUqOQSZh33mPQLc9E/gIch48AIRXgUILh5ul/czZdcQOPGIabw+/ZAbFZ7JnToRiQkxOHvgMM4e61n4wqe3sWHzPrQ0Wr1gw4kSc3DZLU88Tn9Xg/D9H/yy+y2RjpAsEEILSGAjhMaUhgqdBV798f+gvKIKf/rLf0M3KICv3PNFhMm12H/6GI6f6ejSbg82YvRqRg5tMVmxe1/ghDqZUgQTotfCS9xsByaY14JxLWSQE3AQ5OJLxkEtU0OjUoGyEAg4kAeB5wUGIKjkeCAA4HoG02g0GD58OJSqawCH1YaiCxfgdgUXUnF4nNh8DdhYFLaQreOmNBlpf3hE7grZWOZh3hcX72bARMkpWHYMZeDwTh4OhxtWix1upxsupwCnzSW+rG4GWlr1RXqRhDR+Si6SEuNw4fAxnDp8okdm8dVJOVdUgoLjF3sMNlavWoL5c/PxzFdf6tE8pE6SBXpqAQls9NRyUr8+swAJUv3rH6/hX2+twZate0J6nu8++WXwZjf2neres5GRFI3hQ9NwtbIWJ051kkVA/AryVLR6K0RhLLkCUOmUUKmVUGoV0OlVpFYNpUwBrUoDNadkmSEQZJAR8aIXzeVyg+d5VoiNHBHkASClUIEX4HA44HA6mf4F/c7F86ygnU6rw4L5s6DT6/zObGxuxrp1W2E2W1i0wSMI/mEQCoFQJIJSZn3xiG44GyzkIpOBoi5epwnLjGHpszRnihqxMI04fwJXo0ZmMe9G4ZkiCuJAoRC9OHRK+r1eq4FCSR4dBZNnJ5VOWhcNplYSSGMoo6NVZQRCPPBQzToCI5wHIBEz9rOH7QWdj+0JffbI4HTwcFid8JC3iQdsJjtMzTbYLU7YzA727naQAEnXmzhuSi5SEmNRdPh4j8HGjPzxyEhPhs3uwqef7EKCNsEbRgnOszF39lQ8+aX78MVHn2MgVmqSBW6UBSSwcaMsLZ0nYAtkDhkM8mx876Vf4PKVsoD7BXLgi08/C2eLE9sO7cP54o5Sz+09G2OzBiOJ3N/ni3Gl7KoIJNQyaPQqaCPU0IapoTdoodWroFATAYNCFmJIA7wMstYXCWK1u9teM1H60id+CtVeob5OFw+XywmHwwW70wWnwwk3z4N3i2DB7RYYwKDwTk8b1d1YvWoZwiPC/YagLJUPP96AlhZzYEP3kCB6vcEn5o5iYZ89+3uXaszJRCAiVxBgEUNLVLqdOAvkOSIwqFIp4Xa5GXghnghLHyas4fOOeAEJA0gMgIhgRPyZA+eRweUWwHk4OKxu2M0OmJutaDGaYTU5YGm2Iyd3DKjU/PlDx1F45ARio6OYbPiFi8UBpx5TGGbhvCkMlL3zzmYGNuxwoTTIMMqkvLGssOGXnn4BZrOokCs1yQI3wgIS2LgRVpbOEZQFyM372COr8ciXnhefWEPYXnrmq3A0O7DlwB5cKO34VKiNT4A2NRkKuRuTxmdCHaZEk7kFco0CnNzD+AKUzinIBHjoRdwGAhI8Bxk9XNNn9sAog8CTl4GH0+WCyWRhpDwqnU7AgjwS9P8uJ39dsmQIl+431LQpuaipq8eM6VMQGRnh9ztTixkffrwexuaW7k/fB2Cj+5P27REEJFRqkftCKqwqFYWwCFhqoNIrWXhLruIAhYd5rMiJ4gMePs+Ih7wjSjmg5MBrtFBZAb3JgUS9AXFRMQjThOGnr7yOivLqgBZDnp57714AwpcffbgDMarYHoGN0aOGg1LKSbK8rl1NnIAmIR0kWaAXFpDARi+MJ3XtOwvodVpYrP4VWUNxNp9nY8uBvbhQWgxduAbR8RGIT41BXGIUEB0GRXQ0OBkPGW9vBRUELljYw+utoPogvJ2H0+GGze6AxWyFxWKHw+uJoJBFf210M73vnqU4crQQNbX1WL1qKaKio/ymazab8eFHG9BkbL7+Mm5BsBHMvhEgUWuU0EZpYYgLQ3h8BNQGJWQaTlRppX8EWmwctE1WyJ3OVu8IeUV48lI5BViabaivbkJtTSOM9S3MK0LE4PbhmXtWzWceny2bD0Fp18LmcaLMElytHqo5o9fr0NxsCnmmVzB2k469/SwggY3bb89vmxX/7c+vYUhGGopLylFcUoqKmkqkhMfD4nCgzlUPtYGDxyOw2L1AL5kAt0YNp0oNmUsA5yREARgbLDA322A2WWC3O+GwOztUix1IRqUb5N0rFzEVybLyKhCwu3vlEsTExvgtw2Kx4OM1G1Hf0NT18voAbEwYl8MKsR08UtAvzSpXy6EK0yAmOQZu4nqoOIwfP4pl+1CmEIW4mltMqKttwqVzl5CWNggGjRrmiirAbYfOoIVM4YFKQ7VrZCwUI4Zo2j4TD8RisTGyatXVBjTUGDFzynjoVBoUHL0IY4kdNnfwYKNfGlSa1G1hAQls3BbbPLAW+cLzz2Df/mPYs/dIzyYuA8Jj9Jg1bzKyRqSxjBAHb4fbw0Pp0sImOGCT28HL3QxsyAUFe4q0NztQ02iFiZdD6QEyk+NgMtlwsjB4iemeTfzG9KKQwJ3L52P33iOo9JYt12k1TIcjLt4fcJDw10cfb0BdQ1sZer9Z9gHYmDY1l4Uwdu05fGMMcp2zcCoOCp0KaoMW6UMHISI2AobIMISHGRixtbqmHmfPFSF9cCqsTVbUV9WjqdYIp8UueiYAZI8ZibjocFwpPIvL5y62nk3BcQiL0CEsQovouChEROqhCVO31qGhA1vDM16eCOOIWAVUXmxCQ3MziutKIFCqr1PwZs+Inymtt7NGXo1nnrwfaz7dgivF5TfdvtIEbh8LSGDj9tnrAbFSeqL99xu/wN/+8R527DrQ7Zwpq0Gu4RARa0Da0GQMGz4YhmgdI//xMqpJKjCPBeNYCB6o7Fq4HR40mZoRHmFAWFgYogwR0Bt0kEOOyzW1OF9RicGpiXBbzCz7wtxih8loRmOjkT1tUpqk2zVwmfwkErVsyRzs/PwAamrbQIRGo8KqO5cgITHez+52ux0fr9mAmtqGjvvRB2BjRn4uOLkCn99gsCGTc1DolYiMj0JMUgwi4yNARNqyikqW5TJ8xFAWLqMQRHNDCxqrG1BfWQ+X2QGeMlK6aNljRyIuKhyXT53BlfOXur2mFZwMYXodIqLDWXXe8Eg9VBoFk6UnLxzVnVFzWqj1KthkFjQ3mVFWWoWqq/WwWRwsc4a4HR4GQrxaI0wQToBWocbf/vgqfv3bf+LQ4ZPdzkU6QLJAqCwggY1QWVIaJyQWSElJxK9e+x5e/vFvce68f4VMkrKWa+TsRcTNlPR4DBmaiuSUOHBKjgELBjAIWPACzEYrnBY3ykqrUVtZj+YmCx5buRqCxY1j5wpxsbycub1J9EqtUSEmNhqCVgNVbDTS0xMgczlhMIQjPi6W5Uq63C5s374HY8aMZGu1mq0wm+jmY0ZzYzMsZi8Q6ecphZSNQYJpZWWVsNrsfvtGv1t552IkJSX4/T+l0a5ZswlVNbX++9wXYGPaRHaOPfuOhuSa6nQQAhZaBcJjwhEZFwmjzYS0zFQMyciAUkkpuRwTEWtpMeHyhVI0VNXD4/DAZbbDbXMFNa+ccTmIjjTg4olClFzsmAEVyGCUy5SSHItxY7JZMT3BxiEqKRw2tZkBEErfpXezzYaaxkbU1jaioc4oejsIfFB2Lk8IRIZXX/42PvxgIw4dLPB6QbzeEK9HhB0nNckCIbaABDZCbFBpuN5ZYOKE0fif557AV771A5jsllZwQd4LlVaF9CFJyMpKY+mn9KRHSpIynrJAAKfNjZqr9bhysQJ1dUaW8XFte3zVaghWAcfOncbFso7kOnVUFNSxccgml7lGgUvFFTBbrIiMioBCxcFktWLkyGGIiAqHXqtjVWnFx0gPDhw+BoM+DFExkbCYrDC3WNBsNMHY1AK7xcFSLEkDo783tUqJO1csQkpqkt9UKQV3zdpNqKxsVyOmD8DGrOmTwAtu7N0fuJDadW3KyaDQKiHXKRCXFIvEwYkwRIchIjwCWlJTlclw6PBxpuURoTWgsaYR9VUNsBotIrAg91Yv2ugJoxFp0OPc0ZOouBIcobP9aSm0tGj+FAY2ju2/CIfMCYS5kJGRiqTEWKjVSpaSyzRQODFjqsVixYXiUlytqWNgnED51559GNu378fpwgsiAPECkVZQIvgUbNvCMyw0Q0q27t7ZohdmlLoOcAtIYGOAb+CAn76M6oNw4Lwei/kL8zFvUT5efuW3LHbNqeQYNDgew4anQR+mBUf3ah7geBmsLQ5UVdSi4modc/F3Bi6utc9jd90Nj92DwstFOHOpo0vbBzbG5WRCDQEnC4pgsnTMiiH9BoVSAY1OjYgoA5tbo9GI1MHJSElOZIx/8hKI4lIeFBVdRm1dA9IHp8BitsNsMjP3N2V7OG1O8CSv7QUi7jA7XOE2cA4F5A4lOKcCnLMLoaoeXAA6rRoxMdGoqqrpEvyolArcsXwhBg1O8TuDy+nCp2s3o/xqlfj/fQA2oiPDWfaw0RhA6m0n6ydgoQnXIjY5FlHxUYiIDYdarcax46eQP3kCC7EZW0xobjKhubaZeS2a65vhthEhOPRgcGzeWITrtTh96DiqSnvHk1iyIJ8VYjtzvBQNZiOqbW3Aj1J0E+NjkJqaiCHpKUzwzNcIIlRW1uLSlTI89eSD+HjdZhScOcfAB6fgwFRv6V1OqdvkCWnzhvh97iI84+ON3IzaMz34E5C63AQLSGDjJhj9tj0l6V55QQUBDPrMSqVzAKcUK37GxEUhKjYcVdW1yEhJwaCkBGiVagYuCGS4XDyuFFfgwsVSGJtNQZvyi8vvgsLN4VJlCY4WnunQn8CGLj4BuWOGgXM5ceDQqaC9EQyIkDaDXovIqHCER4ah2dTCtBqys4cyIKJUEhChW4AMNTW1OFlwBpkZ6XA53bhivYwaeQXTGHEJLrh4FwSBsmNE8CF3EPigd3rJIXMHB0QGpSRiWv4ErFm79boFuUgAa8XyBUhPH+RnJ5rX2rVbUFp+tU/ARjCb2j4zhLRQLE478iaOZXyc9pkhjY3NKCq8CLfVCRepflpcLNR2I9r4ybkI06pQcOAIassre3XKGVPHMY7RxdOVqGqs8wMb1w4cHRWO4cPSkZ6ezAi37YFHVVUd9h082bEAH6niKrjWv0cGQAj0EyhRUqymCxBCHhLKDme1Z3wkVSk806vNvsU6S2DjFtvQ/rKcNn6FCCqY94Ji4ayMOFXypCcpEWCwSqAOL4FNqUbeuBwkxRJPQmw2mx1Xq+px9uwlGANVtuzCEPcuWgadTI3y+krsO9axToU6MhJRgwYhJzsdgs2GA4cLQ2pSBkQ0CpEASEAkIgxuwQ2jyYTccaMRHh6GI5VHUG4q8/pECI6QjQRWbIyKpREAcfMuOHkX3AJJaQOcU8VACHs5RW+Iwq5gYmPXSndnpKVi8qSx+PDjjd0CKZrvsqXzMWRImp8deLcb69ZvQ3F5CZpGVvoVYos6mwx0U2L+ekYlBVniiFRcbReuIdaMNzNEqVMhPSuNcS0IyPkyQ0gRc++Bwyzd2dls7zQzJKSbGeBgefkToFEpcWLPQdRX+a8pwCFaD5s2ZSxiwiNRXdqCotJi1LTzbFxvrKhIA4ZkpGLokEFej5sIdcnbcehIIcydeO86G488H+zvWEmy/G0eEfpbJk160QsivqTwTLC7e2sfL4GNW3t/b8jqyCvR6rEgb4WGA0e1L5hrVgQUvhd9CRFz3xcD5h0igY2yUKZMGoOMtOTWOdMX4JFjp1ltEqr5EYo2J3cK0uKTUVR2BSfOdaz6SmAjfsgQZGWmwGZsxvGColCcttsxqH6IXCFj6pT2oUZA42ES2+Qy5+SiO5zUSqmJgRmCIGIjr4fb42YEVp7eCZDwTuYRIREyzhuKIRBCYGRwbCqmjs7FmjXbu50XHUCAY8miORg6bIg/4OB5rN+8DUc1+0IKNhbMy0dTixkFRUX+mSERBtQ3GFnoKW/CGEbgbJ8Z0lDZCKfZdt3MkIAWHOKDJk2fBLWCw5Fd+2Csre/V6FQjJSosHI4W4ODJgoDBhu+k5K3KnzoeiQnRrP4Mu64AFJ6+iNNnLjHF2542qlvD/t7p714Kz/TUjLdsPwls3LJb2zcLIyBBrmsibPo8FqyoFnO1tgMWcllb/r/Xa8EIZp2Ahvi4aMyaniuSLb23041b96Ku7jpiUj1cXn7OBGQNSsPlyhIc6SyMEhmJ1OHDkD44ES119Sg827PsgR5Oj3Wzx7fArXZCULshqFysTodSroRSroJSroCCU0IhV7AKplQrQ7xhUJUyKupBQXX6SBraREHgmeeEeUR4KsXuYqCE3mU818oJYaEZ5hWhl8pby6VtFVSzZfHC2cganum3NCr49sG5D9BiJncVUG4pQNCejXaZITGJ0UjJSITDIyAlIYHJw1NmiJWARYsJFVeuorK8GoLNDbfVFXRmSG/2pad9p86aDIVMhoPb9sDU2IVeSYCDjxqZiSGpqVC41Nh+4HDQYINqwvzwB9/A2++tQ21NHaZOGQtKhaZmMluwZ+9x1Dd2oxob4Fz9DiPHBwMg3u8KKTzTEysO6D4S2BjQ29eHkyfiJuNX+MCF6LFg/Arv04svFEI3OSI4Umogle2mkAil3AVCFhuZPQQTxmezm6bNbsfgQYNw/OQ57Pz8YJ8sbmrOBGQPSkODtRFb9nTU8VBFRGLImJFISYxBXUU1LlwObSG44BdFJdMF8BoCHm7waid4NQ9e5WJAhErVKzgVVHICIEoovUBEwYAIgQ+xzDrziVC9Dqp8yiqxgj3FikCEwEd7IOJmPBAGPOw+fogCcpcKS2fOw4jsLH/AIQjYUnQE5S0V3YONdpkhJGSVkpECQ4x/ZkhtXS2aTWZG5G2qN6Lhaj0sIcoMCd7+vetBXqHJMyaD83iwZ9MO2E3B84zaz4AKuk0ckwOtR4+Nu/ej1h5cWEajVuPll76O/76zllXVpTY4NQETJ+Sw0B61g4cLceFSz7NmemKxUIRnqHIviZlZy0Nf5qAna5L6+FtAAhvSFcEY6K2eCi9pkwpN0Y3MF/7weS3orkW1HJhioffdp5QYrCmHD0vD5LzRrFtxSQUOHjmNH/7gm/jk0604fLRvpKpzh47G2KHDYObNWLft8w5TJrAxPHc04mMjUVlcjuIyb9ZFsIu7Icd74FES8HB7wYhL/KwmIOJm2QjMI0IAhKqe0junYF6R1hRJ7ydfcMYLRUR+iJcbIvJExNAMeUruyroLuakT2lYoeNBoBo5VHseeyk/9PBtE2tRE6FjKaVSCmBmi0+lQePocMoekseqnRPRtaWqB0ZsZMml0DipKq1F46vwNsWJfnoRCFROmToDHw2P3+h1wWy29Ol1keBhmTpkInUyPDbv2BQ02IsIN+O7zz+Cf//4QRReKW+dCmSwL505FdLRYlG/3vuMoKe0dmbVXC23XubPwDPF35Ho5FFo5ZERoVXCA2wNHkwu1u3sXqgrVvKVxJLBxW18D7YWxfACjPa+i7TPgEeDlV1DevZdnEaI8e8rMWL1yPrvVlZVXY9eeo9DrdHjpe8/iP29/gjNn22SdQ7lhowYPR97IHFgFKz7durNTsDF68gRERuhQXHQFldUD9YvLA0HNM+8HARAKyZA3RAQiPDhOzsIwFJrxhWQIjMjlFLbwajW0/8L3MkTIR8LzAiYmT8To+JGQQc6yPpotCqbtcKB2CxorrIjRxaHO2IgJeWNZSXWWGSLwIsfCaELRmUuwGa0sHELZIe0zQ8aPHcG4GeVUS2SANwpRjJk4Fi6HA/u37u412FCrFFg0ezq00GPT7n1Bh1ESE2Lxza89hj/++a1O7btg7hSm2UH8oPc+2sIqFPeHxsAFZbB5Q7j0gESaH5T9Qs46xmHiZHBb3Gg+2zvvUX9Y7604B8mzcSvuqndN7A/Ux63whkRa+RXXEje91Sd9WSGMuBkiUmZnJp6eP55pAVDo5IOPt7FDDAY9li+Zw2TKO5XGDsFeZcalY+bECbAJVnyyZUenYGPC9MnQ6VQoOl2E+oY+iF+HYB29GWLc2Gxoo1TYc/wQeKWr1SviVrnhUfGQc3IWklH5QjIUomFeEbnIDSEWBcchJ2kMBsemwylzw8ILLEqjU3BwuB3QyDQ4fPQUYiMjAbuHiWQ11TT51QzpzRoGSt+YqHBkj82B1WLBkZ37ew02OBmwfMFs5tnYtv8QKlquBmWKpMQ43HP3Urz19idobOp4bVPo7QurFzHC9rmiYhw51jE9PKgT9uRgDlCoKS1ezGKjFzUKkXhcYqiEgAZ5VnkrD7edZ+899bD2ZIpSn+AtIIGN4G3W/3pcI4zl41lQGMTPa6EU09NaM0EYv4JqJ/AsR/5GtntWzmeE0AOHT+HipRvHi0gOT8Kiafmw8has27azgzgkhVEmz50GlYLDqeOnYTJZb6RZbsi58iaMRlRkOLZs33fN+URviDPMCneYE26Ng4VpZHI5lCoNFCo1NBot1BotKKuBk8kxLHookiNSYOUFcB4OYXIONTVVSIsZBAXPwWl3sHoiVqsdzU0tuHKljN0oSE3VYXeDd/Msm6Z9I9DpcDj7zVN1bzYlMT4amSOHo8XYjBN7D8Ft7f31tGzuDBiU4dh1+BhKGkPPrRg9cijGj8tGVXU9tu7oG+5Ue5sy4qia8wIMjqU4M1DhFtrABQ/wNh5uKw/eTu/uG/6d1ZvrQOoLSGBjoF4FHBA+LIzFKqkugkzwtPErvF4LRtxsR9j0eS36w5JX3TkPYXotdu89jpIyMTasUMgRFqaHqcUM/pobUKjmHKuOxfI5M5lnY8vufbA5nH5DE9iYtmAmOJkHxw+dhM3u//tQzeNmjjMlbywTFtu+Zy/cOqf40jrg1roAlQCFUgOlWg2lSs0ABnkxfInHLO2Wsl3IZe10wu1yYnzcOIyOyIdc4HCidhsunixDsj4VUdHhCAvXIyxMB51OA6VCif0HjyJv4nhW1t5qt7H0VZvVDnOLFSXFFbBb7Vg4bzrOnL6Iogslrem+N9NevTn3oJR4DM7KRENtI04fOhoSsHHnwjnQynTYf6IAF2r86wf1Zq6+vsMyB2Pq5DGsIvC2nSGuvMsejLy6O15hP7qmfN6KNu+FIAILAhg2kXQutYFtAQlsDOD9S1qcAAUpcCopxk7I3y3+cVooLVB0LfJukvXrf4ucPHEUhmelM+GmHZ+LpeRJyvuZpx7AL37zD9TX9y5FsKsVx6pjsGDaVAgKNz4/fATGZrPfoerwSMxYMhsegceRfcfhdHesr9L/rBnAjOQC3BoXAxWRqTo0e5phFSwMVChUGiiVaijUKsjlitYsIpa84h2ap7RZpwsupx1up51xEGROORQ2FRQOFVZOf5hlu6zd/g6UzZTC7OsppuHKlRxzzSuUclY7JiEhBnqDHrowNXQ6PXRaLU4VnmW1ZWJiIxjAsdudzCtCQKSqqhYtRjNITIxUVgdK1d0h6clIykhDTWUtzh87GRKwccfCOdDJdDhy5izOlAdHop0xbSJmTp+EV372epcXzao75jKAWHjmEk4UBDf+tYO2kc8VorAfeS3c3nCIW6xKS6J05K1gIRGb6LmQarAE8Dc9wA6RwMYA27DW6cqA8OEGsZYBIQ2Ph31m6pz07tW+YEQq3ishzOKdPHNNUrzzZlZ3DDfocefyWSzltfD0JZw4dR6kHPnk4/fhtV/+tdN4cii2isDG3KlTIFPxOFRQgOp2JdZpfH10NKYumMnAxoHdRyEQS3agNZkHvJa8FW1eCyKIylUqqJQaKAhgKFVQqFRiHQzv+igdlhoTCXM64KKXgwrI2QEnB4VNCYVNDYVVxV4+lVDaw/mLloPneezctpGpnQbaCFRQATQCzRSaiYw0YOLksbDYbKAMCb1eD61Gg6rqGpSWViI3dxTsDgdsFhtTvTS3mFl104YGIwMibnv/KnY3Yng6opOTUFZyFcWnzsBt630YZcX8WQiTh6Hg4kUcvxycwu3C+dMxflwOfvaLv3S6Rb6HALomPlqzFVabI9CtZPhSrhJLELSGcknh3MuzaO+9EEMi4sMRbw/8egl8MtKR/c0CEtjobzvSw/mwLBPvkwMjVqnEpwjG2aAU1nbgwwdK6NuB1THwvSiV1VvbIBCNjB5OtbXbhPEjkDNCFIki3kZDkwmPP7IaP3ntz0zAqS8agY1FM2fALbOjqOQKzl/0j3lHxMchb840duM8sDvELuS+WBBlh2hc4HXktbCzUAivcTJgIXor1OK7StnmsaB5eL0WlHVAoIJCIgQsyHMBl8A8FnLyWtjU7P16heAIbCSlDGNjVlVcDApsXGsSShW9644F2Lv/KCqr6pgnRK1RshAhFVDLzEzipSkxAAAgAElEQVRjoRmdXoswnQ4arZbxP7Zt341pUyeC9wiMH2I1W2GiqruNLaitb2ThRDd5RG5QPRTfusaPyYIuJgYXi4pRWXQxJGBjyZwZiFSF43LVVewuOBTUVXXPqsWIi4vF6395y68fx8kwber4VgVf8miQZ6N9S01JwvRpk9BsbMbGLbvElHlfjSMioqvkolS5j8RJ3ys+rwWBCq/nQvJaBLVlt8zBEti4Zbayi4VQ8TMCHT4A4gMkpKNBNxwGRryAhFRAyVPi84YQ+GgFI6J3JNTeEJJfzkgXK4tS1dbs7Cz8/Fd/Z2Xd+6LFqGMwe1IeFFqgvqUR+w7563lEJyUhd8ZkOJ1OHN5/rC+m0IsxRQInhUJ4xrMQSZycUiFyLLxeC1bkzSsm6sUVPhkNuFxOuAlUuMRQiOByQ2FXi+CCPBY2NThHcIXdCGzMmruIkT337t7WK7BBXA7KSNq99wiqauq6tBWJZckJiGiJW6Jg5dOHZA5GdEwEdDot9Fo91FoVA1gHDh1HXFwUYqKjYCEgYrKgpcUKk9GE+vomuB0UlukbIDIlbxTkYQacPlWEhpLSkICNBdOnIlYfjRpTEzbs65i+fb0L7MnHvwCz2Yx33v+s9bDoqAjMnDae1eWhRlyZQ0dP+w1DGUqv/uwFpKYnwQ03/vTGv3H67Hkx/bRdlgg9rDBvRTsy5414cOnFH5XU9QZZQAIbN8jQ/fE0JNRFIISlyDJAIqaZEfmvVdDLLyQjFlIgHojH6QvNECARP/e0EXdj0sRRLMpPAOjCxTIUFBYF58IN8OQENsZkZiE+NQIOjx2btvmriMYPSsGYqXmw2Ww4duhkgKP2/WFUdt48uA4g7oM3M0SpFr0XtF+siUrlIluCFEKJY+FygHc64HQ6wLuczEtBJFmNW4emMjPkNmWHQm3BrobAxrIVKxnY2LRxba/ARrDn7ux4VuxOqYBGr0aYQQ+L3YbUlAQkpiZAr9NAr9VBpVazrpcuFqOxsQlDMtNYwT+LiTgiFhibTDA2NcPpIJ5Kx4yZQOZJ8yCipaDW4hgVO6uqhNsWvLrlwvkzcOFCMUrKKthpx48Ygey0TFyuLMfuguC8b//7P0/jZMFZbN66B2E6LcaPz0b64CQWziQvF1WCvVJ8lV1TvlAIfS8sXjqbFeTb8NkOzJmWjzCdHt9+7kdobjCJPAvmuXCz7wKpSRbozAIS2JCuiw4WYNLBPvDhDcf4qraScBP7vc8j4uWIsJRarxeEcULIC0J58AESVEkqee7sSYiMEJ+uiElQVVWPo8fPdCBx9mbLolUxSItLQlZOKiOJrtu4x2+45IzBGJmXC7PFgpNHTvXmVL3v66sZEm2AITUc5YbirjNDXC7GsyCvhdMLMKjWicixELkWcjtxNGSYN3sqywI5eCQ0Kq39DWxcz/AMiBAXxKBFeGQErDYLAyRDh6WzDBl9mJ5lRVFrbDTi+PFCjBg5DG43LwKRZjMTJSMwQkDE7eoaiFAGzoRx2XAp1Dh6tBD2muoegY1XfvgdqNVqbN+xF1u3fY5Rw7IwImMYimsqsOt4cGEU4kqFG8KQM3IIEuJjWk1VXHEVBecvwCm42UMHpaN62N+zB8kJiXjt/30fx4+ewU9+/Htkpqbhn6//Eju3HsD/PP/j3l/n0gi3hQUksHFbbHOIFkkyHe28IOJnkRBGNVNCQVAl9cJxY7IQFxvdOml64jx15hIuXylnX/q9aQQ2YvVRGJ83FG7OhQ2b9/p5eQcNzcDw3LGMM1J4vM2VTK75rKEZKDx9vm/SctvVDNGF65CZnQFDtAERERHQqlVsjh+fXwNBcMM/M4RInHZvZogYDmEETgIWrLx8x0ZVVZuNZhw+FhowFUqwQfofpAOy7+BxWAIse96b66F9X4VSBCKUfh0ZGQ4ePBxuJ0aNGg5DmJ7JrJPsO0FhCvnt+vwgBg1OgkalYhkzlLLd3GRCi9EEp5NHuF6LkSOGwCxwTHq9J2Bj2JA0PPPMwyIAFzyorKrBicMFSIyIh9HRgjU7tga0fCLbpg1Oxrgxw6HRqlhxP0Hhgdluw8lzRWhsaO5UNEuwe/C3372GWEMU7r77KZjNotz6Fx9Yhf976Tk8/ZX/xY6d1+q1BDQl6aDbzAIS2LjNNryvlhsKgqpGrsKwzAycPX0J4WF6FlqJijS0TplIm0QaLCmrQnlFdY+AB4ENg0KPSfnZTLBq5+dHYbHZW8+RNiwDw8aPhdFowumTIthISojHihULmDbFhx+vR3l572tGiDVDtIhNikV0QjSrGWIwGFBZVQ2TyYSckSNgMpvFmiGUbVHZgKu6S7ArWwAX1+qtIGBBXAsZLz6NB9IWzZuOxiYjjrQDU4H06+qYUIKNpIQ4zJo5Ces27LjhYKPr9bWl7hrC9YiMDodao0JtfQOyszMRFxcDvU7PvE6s0i4v4MSJAsYlMei1cMpUaKxpQmNxORqra+ByOBlYIb2S7tqM/Dzcecei1lAZVdm9ePYyTHVmmD02fLBpQ5dDUKpxRloKskdmQB+pYfwsj8IDQQ60NFlwquACGmqMIsi4RjSLwiKh5md1t1bp97e2BSSwcWvv781f3fUIqj5viDdlNzEpDg88sAJvf7AOtVX1LD1XrVAiKz0N6alJ0BA/gcQfRHoCuxkVF1/FlZJyNLcEVuAqWhUNgyIMo8dlQBOhwOGjp1Fbb2y1U/qwTAwdPxpNxmacOXkW8XHRuP++lYxLQm3f/qM4ciy48AOJGKnCNIhJikFUXCRqW5qQnByPrGGZfjVDWppNKLlUwWS9easTvM3lx4Whuia0/utlhgSy4YsXzEBdfSOOnQiNFDWBjaXLV7IMns295GwMSknCtPxcrFm7lamI9vfmS91VqeQIjzQgIsrAwjI1DfVITYmHWqGANiYG8dExMECAzOnC2XMXceFyMYZmpLPQTGODEfV1jSzLQ9QQadN2WXnHYkydksvSg33t0pnLMNa0QKbj8MmOLX5p4pQ6nJmVgsEZydAYyIMBVrOG1F15B49BSan4+98+hLnZInItvHLfgpR+2t8vtQE/PwlsDPgtHLgLuJagmpgah+dfeAp/+ttbKKuobJcpQ/ohMoRHhoEUGdNSkqCQycEJMsh4GWSCDBaTDbW1jaipa2Qyy2Zz59ksPrAxcfJwyDQCq2x5+tyVViNmDB+KoWNz0Gg0gbfakJgQj/G5YmVajyDgZMEZ7NrdtYQzhZYUWhXkOiUSB8UjOS0JhnAqoR4OSi8UPB6cOHkaNosdkdow1Fff+JohWUPTYbZaUVlZG5KLh8BGVvY4NtaF8yd7RRDNSE/F5Lyx+OCjjX0TrgrJigMbZHTOEERGR6Ciycz4NJEyDyLDdWg0NsPpcmLWzKkwhIWxgofkEXG5XKipq8Wuzw8hM30Q44OMGZGNpKQEKOVyyGUc855cOV+CpmojEtPikDYmDZ9u3AgoBGjClFDp1eAIkIKD3CNnpQnKSqpxuuASZk2ehImjxuDbz70qiWYFtoXSUSG0gAQ2QmhMaajeWSAmJgqv/+6HeOW113HmwkUxO6YLgqohUo+09EQMGpwIjU7FioBxROcQSLpdrAhparLgakUdrlbUorGxGW6ehw9sDBuRgsh4HSwWB3buERVMqfnABtX/GJ01hHS5/Rb11n8/Yl4BajIiG+qViIyLRExyDHuPiDRAq9Xi0JETyB4+lJEOif/RUt+CxppGVpDM2WJjT5m3SiOwMWrMJHgg4Mypo70CG8My0zBu3EgGNgZ6mzwxByqVEmdKa9HSaIS9tgpub8hOzsmgVCuh0WoQGx+D6OhIRMZEMNBRdOEyliyeg6jICKbKypx5HsAtuGF1kJpqFWRuDnKtBy6Vg3ktCFjQO1XPNdabUXalGhfPlqKpurlVNOvF7z7LMm5++Zt/DHTTSvMfgBaQwMYA3LRbdcpEwvv7X36Cn//qbzh6rBNlxC4IqiqdEnHxUUhMjkF6RhJUGhU8HN36BAgyD2QCGPhw2lzgm2VovmqB1WpGWmYCe6T8bFNbRkpefh4iU5NhiIjA8PTBraYmVUynzAOL247DBScBNYfqulrMnDYFWr2G6qDCarGipcUMY70RF89fgcvsBG91wW3rH2W6fYuJjYmCw+GAqQvvT7DXVyg5G3QNEDlzoJeX96W9ki2PFZXDabXBXlMFt72NH9SVnRUcB41eg7iEaMxeNBU2lw1WwQ4XxDCanFdCz2uhlnOsam+0IQrJsUlIS0rDV7/8A1y6UNLp0H/786vYtHk3PlqzqcstJsB/cO869vvHnngOe/d1nVr7gxe/hYcevBvHTxTivge+HOxlIx1/m1lAAhu32Yb35+US0//ll76Od95bhzNnLwY11fYEVbVOhfjkaKQNSUZSaixUagXo/wR42Bc1bxNg5a1wc07IeKChthk2swMJMfEYnJGBskYTwmIiMXhQItwyAS6Ohws8ZOwfPWzKYDZZsHf/ISTFxcNpcaKhoh5mo1kEFkIAzL+gVhfag5ctmYWrV2tx8tS5kAwcSrARkgn1g0HCDTqMHZ3F0mNPXqkCb7d3CjYIWFAdEhLUik2IhC5cA4VODk0YAWaZGBIRyHPBsZChTq2FwqWC0qpCRIQedz+4EnKOQ21tPSMwf/1bLzFe0bWNwi8zZ0xiVXfLuiE4b9/8HgYPTsFvf/93/OH1Nzu1Jnnt1nz4d1b35u57n8KZs0X9wOrSFPqzBSSw0Z93R5pb7y3gJaiGxxiY52PEkCzEhkdB0LjBK5wQZAI8Mg/zgJA3xK1SwBGlg1slg1bGQcGpoVKooFSooFNooeHUKD5XgoP7jsFtcwM3WP669wYBli+dg/LyKhQU9q7Ilm8uoQQbiQkxUKvUKA1Bxk8obNXTMRITokHVUymr6VJNExSCALmlBZFaFbQaNVRaFQzROii1CpYh4iG9GvKPCZwYFhE4pokSY4hCTFg0YsJjEGuIgUFrwJlj51BbVocRE4dj7MzR2LLlc/zold/AZPIvKtjTub/20xex8s7F2PX5fjz5zPOdDvP2f/6AvInj8O57n+Kll3/e01NJ/W4jC0hg4zba7IGwVHpSojh3X2UixGriEK2MhMnRjKnzRyE2MRJhUREwROnRbGmBkXfAFm2AK0wAR0Wo3DwrXicjUEFMPo+HqHdwWt2QQ4HI8EiYjRYUniqC0+lirxtdfyPYfV2xdC5Kyypw6vSFYLt2enwowcaUiWNgMIRh6879IZnbjRiEQiZ0zarUKug0ahjCdDAY9NBq1UyVU9DqIYcLcocJMs4lggtvhgiBC+IYEXA1mexouNqI+kojmmpNmD9zBh558B7I5SJvqKGhEZxcgcuFl2CqN4PXevCbN/8Jp6v7MN3onCxotRocPtq9tsr9992JH738HZYePTl/eQcT3rFiIX752g9gNLZg4ZL7WeaW1CQLdGcBCWx0ZyHp9zfUAi88/wwDGr/+7Rt9cl4f2DA7WjAkJwmjRmbC6RKwYME8Rsg7faUEBVcroTHoMDghEiabCRanFQ7eAYfbDoF3t3pBMrOGQK1Rg/fwKC0rgcloFsmp9HIKcNl5OGwuWMw22O12OF1uLyDx1uIQei7x3hvjrFg2FyUlFSg80//Axoz8XHZD/XxPcDLcvbFHV319sucqpZJVoKXqszqdGmq1BkqFnKncqtUq0HF+jbxkcg+gADwKAW6tBgqBB2eywGm2MY0LY0MzzEY708uwNtsZiVNw+F8PX37yISxaNJsNTYqv//vdV1Df2IQVc2YjOToJlaZa/OvTjwNa+re+8TgTJvvRK7/v9visYUOwfu2/2XHzFt2HsrKrrX2I8Lx54ztIiI/Fyz/+Ff77dmDn7/ak0gG3vAUksHHLb/HAWuCXn3oAyckJeOnlX/fJxNuDjYhEHWbNyGXiSv95Zz10Wg3y505HVEYa1FodGq9WYyZLTxQFm4gk6uDtsDgsOH/5Msbl5uD85SIkDUoiIQMUFp4SwzLEDpGJ5FR692XIgNJ0eZn4M717ZCxDxmZ1MFVQuVwBh9PFwJbd4WTF4Egxte0VmmJhC+bmo+JqNc4VtaX89sbY5NmYkj+HlaY/fPDzXmWjzJk1GQ67E/sPnejNlDr0ZcBBoWBS5L6XSqViXgMCDnQT1WjUTM+COBCUphxwozAciWXJeDhlbjh5J6sdooQcFy9ehd2jgt1ogbn0KpxNFqZtIdhJNOv6Z5gyKRfjx43CwcPHUXj6XKuI3X3LlzIF0ZKGq3hno0jm7K796fc/YpV0//vO2u4OZTyMowc3IDzcgG9/54dY+1mbSun/fudZPPH4/Th3/hLuuvtxtudSkywQiAUksBGIlaRjbpgF7rtnGWZMz8NXv/Fyn5yTipBFqaJgcbTArXJi1Z1z2Xnefm8Tu/EPGz0C42blo66xGYd3H8LQoenIyx2L7OyhTMaaAAdF10klkkhx/37rQ1Dp7WeffQinzp7Hmg0boTOooQlTM7KfLkzNRJVIClurV0OpljNgAgIihHLaaYWA94IQ9v19/ZudIHhEL4nLLRaw4zgmqsW7eLh5N/t/Ai6CwIOnypwens2Z+tENgrn3BYFxWSldUvDQ74jbGvzNg8BGalo2s2NF6fkegQ2OaUgAc2ZPEdVbzxQxgMfJZGxtdPMnYMBxcgYOFEql+K7gxOgWALVa9D4wsCCnqsYysbKxrzJdD64ospHLxbN5ON08XE4H7LwTNrcddsEJt4xn+hi80wOPm2wJaBVqTBybw7wVu7Yfh8IQC1ejGZbyMvC23lczfuCO5YgLj8X5q1ewZseWbleVkBCL3/3qB/jpz/+MEyfPdns8HfDG336JGdMns+v7x6/8hvXJHJKGtWveZCGj+7/4FRwNkdx9QBOSDhrwFpDAxoDfwltrAQsXzMAjX1yJLz76bfFmHOLWBjZMMLqMeOTBFezmuHXHISYGlpkzHLlzpqPe2IJDu/zFuxLiYpCVlYkF82eyG8zPf/Vn2O0ONsPp+XlYedcSvPHmuzhztl14gmLzVF1XJYPM+04/KzVyBjyUKiWUag5KtQIanRoqNd1I5VBwom4CqagqZAqoOAUL0YiiC33fCJRQE5/wCRiJN3Sqz+FyiwqXKgVVjCU/DqDWJzLQY24qZziJwADdoFsbOXQI5AgeBiJ8PIS+X4n/GUSQ5QHJfhM4M1NKqsMJgfcw7gN5k0hK3PfiIXiLEop1gWgPWSo1T+nU3hcvg+DwgFQ4ebsHSVExGDdqOBOG23+wAJr4BLjNBDZKwfeg6uu1Nnpo5Z2I1kfh5OXz2Lh/V7cmnDt7Kp780n14/KkXmM5GIO2rX3kU3/jaEyg4dRar73uKdXnzH7/GtPw8rF23Bd9+/keBDCMdI1mg7StgaPa00H+jSwaWLNBDC0ycMBrfee5JPPXl7zMxrFC3a8HG3XfNh16nRkVlHXbsOoyMEcMwcd5MNDVbsL+PC0y1Bx/twYiMPB9yr54YvXs/y0nWnZ7uKQ3Slw7pkUEBBVRyFdQqetJXMg4BC+bwAhRyOQsPsX70pA8ZAzMUmqEbb6hu+jJVLBtbcNaFdMtojuS5IMVN5mEgJU2Owk/kiREBg8Phgt3h8IIInoEh+j2VvOe9x5AaJ33urtE+sJfaCxA5WSuwgA9cUBKSvQ1cENBo33KyhyAjPRnFJZU4c/4KtPEJcIUQbNw5bx7SkwZh1/HDOHDmeHdLwvhxIzFmdDb+9Z/A+RX5UyfiX2/8hoGv8RMXYc7sfPzhd6/AbLFi0ZL7UVvX0O15pQMkC7S3gOTZkK6HfmUBItwRIc/krS4Z6snFqGOYiqjFIXo2RucMxfixw1kI4a131yMtKxOTFs5Gs9mCvdtuTjVLBi58XhC68dHTNL0rKCbgYeCDgRFv3Qt6Z7c7Cpd4X3RjpAJb9DNzPbRrnWWjkN4DxRvIkyGjF/1jIQh6p5CE+Jm11re2Y6ZOmwc378GRgzsYiBE9Id6bsO/N9/8eMYzjO4a8HSz27wHL6CDOSiDAoLfXBtmNeStUgJw8T/SZ5t0OVHjIa+FsByzsAvv99Vr+lLGIjjTg5KkiBmJDDTbuWbIIKTFJWL93NwqKAwuLBGsrqnJ87NBGxnN56NGv4yevfJeFC3/+yz/hr3//b7DDScdLFoAENqSL4LayQCvYcJphdDaBxJfuWjGH8Rne/WAzEjMGI3/JPLRYHdiz5fP+ZRu64RMIaReOYSCEwIjPG3KNR4T4IlS9kxRUWXVPN7BgznRUlFaj8FT/ykYhj8zqVUtw6NBJFLfLgAjVJrTazee1oCqoBBy8XAsfyBC9Fh5vhog3fhTgJMh7tGj+VOYx2rX3OKvRw8CGySRyNuy2AEfq+rDH77kb4WoDPty6FReqL193PBILG5SahPNFl9k1Hkz79KM3MHJkFsorKjEolTw15Vh2x0MsxCQ1yQLBWkACG8FaTDq+zy3w0IN3sS/pNZ92T34LdjLR6mjEqGJg8YIN6n/PynlMg2Dz1gPwaLSYdcdi2Fwu7NiwM9jhb9rxMoXIDfGBDxYKoJ8VYtXP9l6Q2bMno7KmGhculTIQ4vF6QDwkfko/kzckiOBqqHQ26Gn6jmVzsXvPEVRW97JIHBNzE+0hV7fzWrTjWhAhV3AAvEPwggvRFr1pVHV1+pSxcLhc2Lr9EBtKm5AAV0towAZ5nB6/dxUMagP+s/YzlBsrrjvd2bOm4OknvoAvPf1dWK3BAR2fHLnvBF966n+we0/XRQh7Yzep761vAQls3Pp7POBW+I2vPYqIcENAmgDBLq4zsLFk0TTExUSitLwaBRfKsWD1Crg8HmxZK6b8pacPwte+8hj7/J+3PsLJUx1Ls6cNTsHTTz7EdBdIeXHd+m3BTq1vju+EoHrnynmoqKxGwZmzrdyQ1tAMSUaQN6TVEyJ6Q1h4hm7EnTwcE9hYuOQOxp/YvmV9j7JRaPGREQYsXjgT23bsR31DU1D2EOXqCVQQyBCJnCy19NqQiJfEycicxLUI7mG/2zkNzUhF9vB01NQ04MgJUQ4+lGBDo1HhwTtWMLDx1/c/Qr39+hwZ0teIiY7Ei//3q27nfu0BK5YtwK9+8X/sv7fv2Itnnn0h6DGkDpIFfBaQwIZ0LfQ7C6xetRgL58/AU1/5fsjn5gMbVqcZTU7xhjZmVBbGjRnGOAQfbtqP5Q+sgiCTYeu6bSwdltpjj9yHUTnDUVtbh5//8i9+KaLxsTF49tlHEabX4+jRArzz/qchn3coB0yIj4HNbofJZhXJkNdky3RFUCWeCPEr2ntCmGfELUNKShYjc1SUFfUYbMTHRYMyJ9Zv2gWTydL1kllBPi+Jk+au4cSaNe2ABfNakKeGwiE2EVh4nL3zWgSyB3kTcpAQF4Uz54tRXCKKYYUSbBAgu3vRQhjU4fjrex+g3lHf5bSUSgX+/uefMA/hJ17gHMgafMdQ1tXrv3+VFe1buuKhbmuqBDO2dOztZwEJbNx+e97vVzx50jg8943H8cQz3wtZvQffoqNU0YhVx6A92KBsjdUr57FDPt58EIvvWwEPp8CuTbtg86a2JibE4dvfepqlbVI9iCPHCtjxEeFh+OqzjyM6KhJnz17Am/9+/4aQG/tyE69LUOU8kJH3w4+gKsPY3MkMhJw8chC8SyRRMlDCB+49GJSSiGn5E9iNkdJRW5+IiMip5sCpvO9KGQhMtKWe0mdKPxVTT30pqKH2WnRncwpxLJo/hYmG7dl/As0tImBqBRtlpeAdgaWednUuqh2zfNZshGki8Nd3378u2KAslBe+8wyee/5VXL1a3d30/X5P1/knH72BEdlD8cc/vYnf/O7vQfWXDpYscK0FJLAhXRP9zgIpKYn41WvfY2GUYKu/dreYzsAG9XnogeWQwYOjZ0swLC8XCrUa+3fsbb1h0DH3rl6OyZNy0djYhJ/9/I9QKlV49suPICkpAVeulDKWvk+Dort53Mzfjx2TDbPJisvFZcFNgzwKnfBCKKNj6R13weV2Ydv2z/zIqp0RVFs9I50oaNKNWpALorelffppOxIny7Shl80j8i1sHpYxcrNbRLgeM/LHs7TizdsOtmbjaBMT4WpugSUEYCMzIxVz8iZDxqvw1rq1aHB0nYI6IXcU5syagl/8Onig8Ogj9+L7L3ydkUPJq+HTk7nZNpbOP3AtIIGNgbt3t+zMKcVy1szJOH7iNFpaQlPJ0mcsH9iwOS1odDa22nDe7ElISY6Dhedg04ZBa9DjyO6DqG9oKzIVGW7AC//7VSiVSny6djNGj8rGkCFpqKqqwR//9C8WmhgI7Qurl6Gmth47d4sExt424mx88bEn4BKc+OiTtyBTeFrDM50RVH0aIkwkzEtQpTiIjHRECMx0ln7aTjSLPBfdSX33dk096Z+RnoKc7AzU1jfh8NE2Xk8owca40cMxccQo1FS2YNvh/dcFGz1ZA/VZvnQ+fvaT7zMPzWNPPIf9BzqWrO/p2FK/29cCEti4fff+tlw5SZWTsNe1YCM2JhJLF02DQ6ZAI1QIj47AyQPHmKpo+7ZsyTzMnTOt9b/Iy/H71/8ZclDUl5tz7+qlqK9vwo5dB0JyGgIbDz36FNwuN9757xv+nI0uFFQZqGgnXkaaHJnpaYgOj8Thg6cYx0Lwci2YaNbNd1x0a6u8CSOREBeN80UluFTcliXCwIaxBebyEggOUXG2p23poulIjkhA8aVa7Dt9DI2ONsDcfsyYmChWyp5q4ATSZs+aiv976TlGzKaqu9T+8Po/8dvf/yOQ7tIxkgW6tYAENro1kXTAzbBAakoi8268/e7akMqWdwU2KN5+z6r5UBkMqHZxiIiJxLkThSgpqfRbPnE0XvzeNxl3w2K14nd/eAP19Z1/4d8MuwVyzntWLoHR2ByyMu7XBRvXmVB7BVXBLWD29MmICovAhx9uDmQZ/eoYqseyYN5kptjanq9Bk9QmJsFlbA4J2KBwn+QoWd8AACAASURBVNqtxqkTxThVer5LsPHg/Xdg1ozJePrZFwP6+3num0/hy08/zNJji0vK8NbbH+PDj9b3KxtLkxnYFpDAxsDev1t29qNzsvDi977aI3Lb9YzSFdigPvPmTELS4FS0KHVQajUoPXcBZ88Xtw5HN5RHH76XCR1Ro/ooP33tjzA2twyofVh11yKYzRZs2bY3JPPuKdi49uTLl8xhKqXrNuwIybxu5CCxsZGYMnEUUz/duvOw36lDCTYeeXA5lC419u85gysNZZ2CDbLhH3/3Qxw7fhr/+Of7N9IM0rkkC3RpAQlsSBdHv7QAlft+468/xT/++QG279wfsjlGqiIRp47rEEahE6SnJWP67ClwhEVB4GSoLS7FsZPnW899/713YuLEsexGTTUjoqOjcPjwCbz3YWBlvkO2iF4ORFkKTocLZ85d7OVIYncCGxOnzGWS48cP7+px6us9q5agqakZ20K43yFZYACD+OqhlFXU4NRpf7uKYMMIc3lpr8IoaqUS992zECq3Bls3H0O1tRZN7XhHvmlSHZTvv/AVfO+lX+DylSBJwAGsVTpEskBPLCCBjZ5YTepzQyzwk//3HZSXV+L1v4SuFoMPbNhd1g7kOvJcPPDwStj1ERA4Dqbqauw9IKa4rlg2H7Nn5bOUzD//5d+IjY3GF0mPQxDwy1//BdU1oS1AdkMMHKKTENgYP2kWk0U/eWx3j8HGww/ehcuXy7Hv4LEQzezGDTN7xgSE6bU4dvIcqqr9M0RawUZZCQRnW0pvsLOLjY7A0sXToXbrsGHDQdQ7GjoFG1979mGkp6Xi28+/GuwppOMlC/SZBSSw0WemlQburQUeeWgVKH3v698KXTnr64ENmu9ddy+BMjEJAieH29iErTsPYc7MqVi+fAFLaXzjn++g6OIVtrRvf/NpJCcn4PSZIvzzX+/1drk3rL8hTA8CVsYQVdVlYZRHnmJpv+9eSxANYlVDM9PQ0mxGbf3AqihKOi1zZ01kqa5bth2Ey+2f06tLTIbT2ARzL8HGkIwUTJ86Dpxdja1bjnQJNoivUVvbiK3bQxMmC2ILpUMlC3RpAQlsSBdHv7XA8KwMZA/PxLr1O8SqoCFoEapIxKvj0Jlng4YflJmBqYvngOfkkNvMqKk34b57VrAzv/3OJzh+8nTrLHJGZuHxR7/AfqaMlJKS8hDMsO+HWDR/OnQ6HdasDU3tmVBxNvp+5X1zhvTBSRg1MhMNTS04cOhUh5OECmzk5Y7EiOwMlJ2vx8ULlUzQy6eC2zcrk0aVLBA6C0hgI3S2lEYaABbwgQ2Hy8qeDK9tSn0Y7nx4NTwKJeJ0aowePZplnpCuxu69HXUpvv7VL4HqohQXl+EPf3rzpluAtBE0ahVUKhWr00LvdfUNsFrtSEyMA6l0DhuaDuLElJZeRV19I06dLgI9nS9ZNAucnIOcgJacAyeX4e131jFF1GVL5iA5OR4clZsnngbH4fPdB3H2/GWMzM7ClOkLWBl6tbyZ/b6yspaBGfKgPPH4faK8u+BhYwmCBx9+vBFmixX5U3KRkpLAZNBpviRTTkJuJDgWExWB4cMz4XI64XS74XK6YLHaUeqtCBsZEc6ExIiUSV6nm9WIGEoE0WtTXn3zaQUbpSUQXD0Po6xYMgNRUeEoPFyC2uqWTsFG/tRcFBYWwWS+jtz7zTKUdN7b2gIS2Litt7//Lz4lOQHDhw/Bjp2h0YToDmwo9HpMmD8T2TnZyBsxHHK5HDt27sP6jds7NdawoRl45qmH2O8olEIhlVA1ulFrtWpotVp2M20yNkOn02D8mBxotCpo1PQ7NRRyBd79UExTvP++5YiNifabwsbNn+PS5VKQcmhe7hjIFRwDDfWNTaioqMKBQyfZjX7WjEnsPORFoqJqJDV+8PAJBhCyhqbj/7f3HuBVXWe+9//0qt57QYCEhBBF9I6xDdjYuNckTk++m/Gd3Okz30zmZmZuMrmTLzeZ+HpS7Nhx7zbGhd6bAEmIIkCo915PL9/zrqMjitqp0hF5lx8ebGvvtdb+7Q37v9d63/+r1+tEGiX9omPIw6G7pw/RURHY/tBTooR5WclBsurCkMGI6poGMc6CBbmg1GIqvy4RYkaC0rJLMFusoKyjuLgY6HVaZGSkoKWlHecrKnG1qlaURicHTKVCAYVSDrlcLtKM33znU3F93/3mk1AoFeLfab4kOj76eDe6evqQP282EuNjYTJZhNmawWhCe3unmC/NiZoQQH42Ctq8a9NScX0HDp8RYuj2pk1KhqWnB4N+ig3KRCH2h3dXwGpyosPcgV5L78hwbufdX/zqZZw4WernlfHpTCCwBFhsBJYn9xZgAps2rMQ3nnsU3/re32NoyOB37xGKCMSr4zHeygaJjdSCfCxetgAywyAqr9aiqnriMt6+TIr8GPR6LcLCdAjT68WLnF6w5H/hFgUarXqk66tXq/Hl3qPi+Ae33yVeouKX0QST2Ywjx1wuj/SCplUJi9kiXr4Wq028bG/+8l+7eilSUxPwxluByaIJxDZKZmYq7t+6ES+98i6GhsYuhU4iga7NbQmfnBgPpUoBtVIlfleplai4cFVYay9eWIDs7DRhbKXRqMUKz+nT5Th1plwweuC+TaLuzdCgQaywdPX0jrygaQXIaDBicNAwaZ2btNQELCiYjb7+QRw5XjbmoxAIsREWpsWO+zeIYne73j8BtUI7Smx86xuPY9HCAvy3538kxBc3JhBKBFhshNLd4LmMIhAVGY4Xf/0v+NWvX8XR4/7bJt8QG8Yxi1jJtTro0tJx1z2rhdjoGxjCkWO+fSVq1GpERIaBlvsjwvTQ6bUjrp23r0CQmdK+/cdRW9+E1JQEUW/FMGjAkMkkXny0vUBf54FoK5YvRGZGCt5827VC4G8jsbHtgcdht9nxxa73fMpGyc+bjQ3rluGF/3ojICsOt18TbS/R6gMJFRJ2GenJ0Gm10Ok0QvSROCMxR8d87ztPiRUtp8MhVmgGBgaxZ98xISjiYqOF4OntGxCiZtmSfMTFRk0oSklsmLu7MUQBolarT7hnZaVg1YoiUZn4sw9OjhIb5Pr5wi9/hPc//NKnCq8+TYpPYgJeEGCx4QUsPnR6CPzbj/8Cra0d+OWvX/F7AuGKcCSoE2C2Tiw2Fi1dgDgVlWYDdn0xcVQ/ZXfExEQiKioSZpMZlyqrxArE1559eGS+tCrT3z+Aj6hsvc2O9LRk8VImEUFf0O5S9n5f4DR0QGIjK6dIFFmtqyrzSWwUL5mPBQV5+N0fpt+EKjIyHHRPw8P0oBWFsPAwHDlaIsTFtnvXiXo41MhBtr3VZQd+8MgZWG0OKORysVJyc9MmpcDc3eWX2LjnrpVIiI9Cb98Qju2tEGKj3dyBvuFtFDJqe3D7Znz/z/5RPE/cmECoEWCxEWp3hOczisAjD92LrfeuF9bLVqvNL0Keio3oxHgUz04WYx09Xore/iER7BgVHQmz2SxEAqVqbly/HCqVShxHAYxkorRn/zHxhTwrO124i/b1DcyIarC+giWx8djTz8FuteH9d/7ok9jIy52F5KR47AtQbI6v1zLZeRQ/Eh5Bq1VhSE6MRXiYRmxn7T14WsSJbFy/AiajWcTDdHX1orGpBa0mh99i44lH74FSIUdp+RW0VPVAdZvYmJeXg9TUJOzec2SyS+CfM4FpIcBiY1qw86DeEEhKisfmTavEErG/cRsjYsNmQqdptBGXTKOFPi0dCr0eGxbNdmVeSGRQa7Ui8JKW4917/5QtkZ2Vho4u14tlpmQAkEgqXjx/JNDSm3sx1rGBiNnwdw7Tcf6yJQWIi43Elao6XKtqEBk9CQmxiI2NQmx0tFjtauvowrGLNZAZh/DgqiI01zehtqEJ9fXN6PPQ50QuleLxR+8R2zcf7TwApUUzSmxMx/XzmEzAGwIsNryhxcfOeAJhijAkqhNhHkNsxERHYlbuHKQWFqCsshrzUqKh1bhWLcw2oKO9S2Q0dHT2zOiVinm5s7Bp4yq88OJrkwZAenLDAyE2KHbCbLLMmO0ktVqJTeuLJ8xCIXa0wqVJSobKYsLq3DSkJycKEUKtra0T/9+vXhb/Ttk4t2+/uNknxkfj7rtWwGg04d0P9yFWFeMSG6Z29Fn78I3nHsOhw6dExhE3JhCqBFhshOqd4XndQoAyCmiJmoJEaVvC1zaW2Lhn8xoULZgHCkY1OyW43mfCqfLLiFU5kZIYJ4a6WFmNmtsqwPo6h+k+LycnA1vuXoff/O5NkX7qbwuE2Hju2Ydx+UoVTp522cOHesvJTkXunEyRZnviVMWE09Ulp8DU1YXBuho4RYCqFplpKSJQ9WRJmagU+0//8AP0Dwzh2rVaVF6txvXqupEtw43rlyI1OQ49vYPY+dkhxKpioVJohNiYVZCKv/6L7+B//uuvhD8JNyYQqgRYbITqneF53UJAp9Piv379L3jrnZ349LMDPtNJiEjAusLlSE2Lx2ufvC++Ju/asFKYXFVV16OhtROyhCTI9Xoka+WYl5s1PJYEn35xZ+yHe5Jm6g1gf8UGff1//7tP4/CRElQE0KfEm2vw9tgNaxaLTJbyimtoaGrzSmzcfjDFApGXzKzsDOTOyUJMTJRIW/63n/5fmC0WPPvkNmGYVlp2BRWXqm6IDXM7/vYfvy1SeP/5X37p7SXw8UxgSgmw2JhS3DyYPwT+/M+eA8Vv/NXf/tTrbpYWLxDBnIWz82HrcqLi4iW8u3sn2ju6b+lLptFAl5YhxIbWasTKZYUjPy87fxWNze1ejx1qJ5BRGmUv/PH1j0QAq7+NxMaTz3wTNpsV7771itcBomRU9o2vPYZPP9uPmtrAe5r4e323nx8VGYZVyxeILZ+9B05P6l4qVjY6O4Wpl9M+eYAzFfkjL5DSsosiRujpx7cIM6+Ki9U4X3EFUYposbKRkheL7z3/JH704/+Dy5XXA32Z3B8TCCgBFhsBxcmdBZMAlUb/m7/8Lv767/4dtXWTv5QoBqOnt1+4Xf6P//4NRESEoeT4RTRUtKGnrwcdYwaIusQGBYhaOztw9+YVwvmSmoM8Dr6c+cWtaBUnJSlBZEoEahtlTl6xSBO+drnEa7ERHxuNxx+7D2+/s2tGFGErzM9BeloiGpvaUVZxddJHXpeSAlOH52Lj5g5Tk+OxcX2xcE+dPXu2yIK6fKYGZ89V4ulvb4NRYsS//eSFSefABzCB6SbAYmO67wCP7zEBqlHywi//GWfOVeB3L43vx0AplDseuBsrVyzGr154FSdPlYq/rG20X64IQ5I6EVabWex5395kahIb6VCEhcHY3oY1K4sQEa4fOYz252mfntsNArSysenuB4Rd+cF9O70WG2Qwdv+2TRO6h4YKb7lMirs2LBMrDidPV6Cze/JnwR+xsXnTciQlxGBg0ISTp8+jeHEhMmLS8cEHe9GLXuhiVKidAatBoXL/eB7TR4DFxvSx55F9IECFu8jRseLi6C9KclF89OEtuGvjSvT09GHX5wex78Bxsf/tbnq5HkmaJI/Fxvx5s5CRniRsv8nnoK9vEEdOjG1L7cPlTMsp9KJcMD8X1TWNot6Kv83fmA0an/wrLD66a/o7f2/OT09NRGFBjqiBQrVQPGn+iI0d2zcgTK8VLrY1dc1iuARNPML0EUC4DX/1D9/Cl3uO4IMPvxBup9yYQKgSYLERqneG5+U1gbs3r8ETj27DBx/txhe7D4uVjNubx2IjPAzGtjakpsSjaP4cYVseEaYTWwWHjpzB4FBgrMO9vsgAnEBi43vffhp79hxF5bVqv3sMhNjwexJT1MHaVQsRHqbDpcoaVNc2eTTqDbFRA6cXNUuio8Jx35Y1Iibknfd3w2Z3FY7buGQ1dtx/L378n/8Hi1bm4YH7N4Ps7l/8zRsor6j0aE58EBOYagIsNqaaOI/nNwGqa/HQjnvxny+8Kv4iJvfJS5erIJFIhF/BROZa3ooNnVaNDWuXwOF0oqOzFwlxZBk9iKMzfHXjv333GRw6cnrMFSJvb5C/YmPVisUiAPL4yXPeDj2lx5OJ24pl80Vg6L4DJR57rehSUmHq6HClvnohNjasWYK0tATxvH2y65C4Vios99ff+T7a23vw4ruvY9A6gKioCHzv209hQWGe2DY8OlyUb0rh8GBMYBICLDb4EZlxBJIS4/Dzn/09fvO7tzB7dqYoQ/7Dv/xXtLSOdgS9/eJ0ch2SNcnjb6Oo1NClZ0AxvLJB529YtwQ6jRoXLlejIC9bdHno6DkMzOAaFFQh9Ny5izhbesHv+++v2Hh0xxaRFUM276HcFhflIikxFvUNrTh/scrjqQqx0d6OwXrKRvG8GutXnroPgBMl5y7jcqVrBYoq4y7NXYTXXt+Ja13VQmy428YNK0TlWjL/4sYEQo0Ai41QuyM8H48I/MUPv4Wc7HTxVffrF1/D4SOnPTrPLTZsdgvajKP9EWRusRERDuNwkS139gGZeiUnxUGlUsBktmLvgVMejRmKB33lmR2oqqoLyGqCv2Ljua88jMuVoW3oRRk8m9YvEY6gh46WemVNPyI2aGXD4doKmayR8ddD26mkPPD2u7thtlqRGB+LH/w/X8Wx3WUoL7+KFmMLBm2Do7qi9PCkxHicC4CQnGye/HMm4CkBFhuekuLjQopA4fxc/P3ffB9l5y/jf/30/3o8NxIbSZpk2CcSG5T6GnlDbNDXLH3VDgwaca6sEutWLxTjHTleir7+IY/HDqUD16xags6unoD4M5DYWLHmHpFifOrYHq+yUcjQirYADh4+jQuXJk8jnS6GubMzkDMrDV3dfThxemLH0Nvn6IvYWL60EHNy0mC3O/H625+JLmNjorB+7TIc/bIMMqliXLFBPOfPz8UP/vs/w+7FSsp0seVx/zQIsNj407jPd9xVLltahB8+/3VUXqnGP/3PX3h8fVq5FsmalHHFhlSlgj4t8xaxQZkSmzctE0XZqLrnymVF0GqUsFjt2L3vhMdj36kHktiYv3A1nA4nLpQf80psRIaH4dlnduCjT3ajodFVrj3UGgXUkteFUi7H2bLLaGnt8mqKvogNt2toRUUVSiuu3DJevDoeCrlqXLFBMU3//r/+Bv/6kxdwngNGvbpXfHDwCLDYCB5b7jmIBGiZeVFRPkrOVni1R+0WGw67Ba1jbKPcEBsRMLa2jFzB6hULRFlxMnHq7e3H+jVLxM+OnSxHT6/vtVqCiGjCrlVKBRQKxbjFv7yZF4mNZ776LZH989brL3slNmge6enJQmiYTGZvhp2yY7MzU4RtPaWWHjx8Dk6Rk+R5c4uNgdoawDn5NkpsdAS23rsaDocTb7+/G1KJFE8/9QB27z6MxuY2uMVGs7EZQ7bRK2vkR/P6Kz/H719+B3v3H/d8onwkEwgiARYbQYTLXU8NgfBwvSg9T6ZSkzWtTItkbQomFhu0jRJ5i9hwL6M3tXSgtPwKCgtmIz01QQgNEhwzrVFQbXxcNN5+z7VE70/zN2bDn7GDfS5t82xctwQqlRLlF66hoXHiOihjzcdbsbFiWSFmz0pDTU2T8HTZsX2zKBT4i/98GT09/UjQJEAuU2I8sREXF43//MWP8NP//V84V3ox2Ii4fybgEQEWGx5h4oNCkQAZeNFH5tatG/DH1z/E/gOTb2lMKjaUSujTaRvlVrERGRmG1VQPw2bHnv2noFDKsXFdsbAy98ZzIVQ4kjlazqwMvPr6h35PyR+xQe6hapVKVDoNxZaRloj5+Tkwmiw4cOgMHB6sTNxyHRIJRG2U9nZ4srIhl0rx9JNbRSrw7n0nodfp8M2vP46PPt4jKsRSI7EhkynRMs7KRkJCLJ5+Yjte/O2bwn+DGxMIBQIsNkLhLvAcfCLw5OP3476tG0UmAxUX+7Mf/hjWSVwob4gNK1qNo2MEpMNiQxkZBUOry7HR3TatXwqNWomSc5fQ1t6NhYVzkZIcB3rZfr77mPBfmClt8cJ8LFpUgN/+/m2/p+yP2Lj37rXQqNX48JPdfs8j0B1Q5sn6dYtH0p5rhx08vRrHS7FBK2hLiwvEM/X2e1/i+R88h66uHvz+5XdHtm/cYqPZ2ASDzXCbtpEIocKNCYQaARYboXZHeD4eE5DJpPi7v/6++EJXKOR48+2d2Llr/4Tna2QapGhT4bB7Lzby82YhKyNJVH6lCrC0xL71nlXiL/e29h6UnJs5S9bzcmdh08ZVeOHF12D3MB1zPLD+iI3HHtkqXqb7PFiV8vjBCNCBJCRJUFKxugOHSkYcPL3q/haxUQ1MIgSeenwLqP5KXUMrrl6rx5OP3Y+XXn1PxAm5W6ImAVKxjXKr2KDKxk8+dh9+9vPforll5lcn9oozHxzyBFhshPwt4glORID20p//wdewcME8WK02PP8/fizqoozXJhUbCiX0GZkYa2UjOioCK5fNF86Re/adFkvqaakJWFAwW7iX7jtYAsMMMVTKzEzFffeuFy8yg8E/EygSGw8+8gzsNjt2fvSmVwGiZC5WVnoRJef8NxcL5J8U2h5bt2YRdFoNKq/Voep6g2/dS6TQJScPb6NMLDYiI/TYvm2dGOeDj/djcMgofD1uD0gdERuGJhjsBhHo+/ijW7FtywZRdPCF/3pd/FngxgRCiQCLjVC6GzwXnwhQ9P19WzYgJycDr73xsajIOd6X3Q2xYUOr8Ua2iXtgqVtsREXB0HLrNgr9xX/XhqXC1OvUmYvo6OwRp91710rI5VJ0dvXhZIl3Hgw+XXAATqIMB1qR8TazYqyhSWykZ80H5QbXV1d4LDbIepviET7/8hCqrtcF4KoC14U7VkOsahw+I2J1fGpeiA2qJpucFAuT2QanUyoKrPUPjDbtStQkQipToNnQhJSseHz/O08jNjYa77y3C59+doC3UXy6UXxSsAmw2Ag2Ye5/SgnExEThlz//RxHH8eHHu3Hx0rVbxlfL1EjVpsFhH19skF25Kjp6lNigjubnz0JGWhLqG9tw/oKr7zC9DmtXF4mvUHc8x5Re9DQPRmLj0Se+Kr6mP3r/dY/FBtWxWbFiEUrOnL9lm2CaL0dsY1A9HFo1I4t6n2I13BdBYiMpGaaOdgzUXB/30jQaFR7avhG0NQiJAhnpqaLOCdm4395IbERGRKCy/RpikiPw7NM78IdX3uOtk+l+cHj8CQmw2OAH5I4iMCs7XXwty2Uy4d9QU9uIT3buHbHlnlxsKKBLzxxXbIwU47LZhcGX+4s3d24mcrJShQPD7r0nYPX1S3iK7gbxoZTKknMVqK3zrHrpeFPzJ2Zjii7Xq2HoPtL9HDKacPjIOf9iWjwUG2tWLkRWZrKwwV+0cAFefuV9XLmtIq9KqURhYS42LFyFyMgo/N3PfzIqQNSrC+WDmcAUEmCxMYWweajgE6AibT/7yd9i5659uHTpGrZt24j+vgGxj01fqnOzZsHYZIPDbhepg7c3qcItNmJgaBn7Jbxh7WKxl19ecQ0NTS7fBUpZvPfuVaJwVv+AEYePnQ3+xfo5AtlaU+Eusnz3p/kqNiLC9bA7nBgcDB3Ld4Vcjo3rl4B+JwO3xib/Ai0lUim0iROvbNC239OPbxHbHykpKThXdllsobgbbTdR1lVB/hwRCF17vhUVl6pwvPI0jHZObfXn2eVzp44Ai42pY80jTRGBRx7agh0PbMZf/d2/o6mpFRTTQXU7yFvi+e8+h94aA0pKynGq8gxq6xpv+XL1RGzkZKcid04munsHcPwmQ6/Y2EgsX1IgrpIqdba1e2drPUV4RoYJVDE2X8WGSHvVqMV2V6g09wpV/6ABR46W+h3T4onYKF6cj7y5mZDJZJBIlXj19Y+QlZkKEs6Hj5aI7TkKpL1WVYvS0otQW/WQyuRoNDTAZPcvuDdUuPM87nwCLDbu/Hv8J3eF9PX303/9K1isNvzDP/1c2GhTo4yRgjlzsX7+SiTFx0GfosTFi1fxxzc/FmmsFHvRZzBCn5EFVfT4KxtqtRKb1heLl8DBI2dF1oC7rVpRhKgIvRjr893HQ9p745Ed96Cvb9Dv0u6+io0nH78PrS0dOHA4NKrn6nVqrF29WBi1lZy9hLaObr//7LjERhJMHR1jxmxQfMjTT2wTcS49PUOIjI4S1YxpFa6zqxu/+NUfRgWnJmqSWGz4fWe4g6kmwGJjqonzeFNCIDMjFX/+/Nfxk5+9iJabPAdUMjXStGmA3Q5ptEOIgobGFvEXPMV6dHT3o6rXgOZ+I+ovXsDAwNhL/MWL5iEhPhrXaxtxubJ25JpoSXzL5pViSdztxzElF+zDIFvuWQelUoGPd+714ewbp5DYeJpqo1hsePtNz2qjUDbMd7/9JI4dP4vyECkWtnRJPuJjo9De2YPTZwLjmSKRyaBNSBwlNmKiIpGVlYbMjERR1E8mkyM9PR0trR24dq0Glddqbnlub75BVLWY+uWVDb8eWz55igmw2Jhi4Dzc1BFwb5/cPKJKqkKaLl2IDaot4W5qlRI5szKROSsTSfPyoIqLw2BjA9557zOxgrGwaB7aO7rQ0dElTJ4S42OwZFEezGYr9h8quWUrJjkxFouKckXXgfpCDgY1WqYnRk3N3tf7uHk+JDby5i8XflWVF056lI0SGRGOZ59+MGSqvZJwJAFJMSQUbzM0FJjtCZfYoJWNdqj6u7H13vVIT0sGFRIkt9vr16+LLb6ePgM+//LIyCrcRPfbLTYaDA0w8zZKMP5ocJ9BIMBiIwhQucvQIRAZGY5nn3oQL7/6HgYHDRhPbLhnLJHJhalXWHIS5P296OzuFdsrTz2xXawCUOvr60dHVw+sZiNIpFRW1aOqqv6Wi87PzRbZBZSdsu/gaZhMltCBEuCZkNhYs3EbnHY7jh76wiOxkZwUL0yoyPV1cOhWy+0AT2/S7ii4dw0ZeGnUqKpuQOVV3z0/tBo1qDZJXGwM4mIjERMbi8YBIw59theSxUpy3wAAIABJREFUzlY88vBWNNQ3i9W0tJQ4JCXFiuqur7/1ucfxIcmaZEAmA4uNSW8tHxBCBFhshNDN4KkEnkBUZLjITiHfjf/4xe89Fhvq2FgMNd/IRqHVjeiocMTF04skCvowHa5eqULe3CwolErEx8eju6cPvd19aGhuE0vhd9+1AjKpRKTBfrl38iJxgb/6iXuMDA8TVu9lFZd9N60SsTBSPPu1b8NmteHN11/ySGxM9bVONN7snHTMzUkXgvDg0bOTsqCtsogwPSIiwxEVGQFylq28eh0Nja0oLJiLdWuXwWQ0i5iL9q4etBntqKm4gIGaG8XmSGxt3rhUbLdR3E99w+g6PePNmcVGKD09PBdPCbDY8JQUHzdjCSxZPB9/+cNv4eVX3sP+vSeRrssYtY1y+8qGOi4WQ00T+0/QS+eu9UuFY2lX7wD0Gh2iYiLR09WLPQeOg7JTViwthNPhgEKpQm/voHCELCu/LLZdlAoFLJMUjgsm9NSUROx44G788fWPxjSP8nTsmSw29DoN1qxaJEThubIraG7tEJdNKxThEWEI1+sQHqZHWLgOx0+cE1to92/bCIoJomaxWNHd3YuzpRdQXdMAtVol0mYHhtN5aRtFk5AIszD1uiE27tuyFtFRYXA4gdfe3OUpanHciNgYqofZYfbqXD6YCUwXARYb00Wex51SApTmSamWP/3pbzFUb4XE4UCTYbSYcG+jeCI26ALycjMxKzMVXd19OHH6VqtylVKBpUvmIyJcK65Vo9MjTK/HS6+8J/77iUe2gbZ5hoYMIqNlcGgI5eWX0d7ZjfAwHbQ6LQwGg6hd4rNd9gSUIyPChPvkR5/sFl/lvjZfxAYVYKutbcLpM+W+DuvTee5aIyQmkhLjkZ2ZJOzn6aVvMFpx8PApUPDq977zlIhnoWYymzHQP4TPvzyIvv5BJCbEip+Ru+dkdWWE2IhPgLmTslGqhU8GPS9Li/NF33v2n0JLa6dX18JiwytcfHCIEGCxESI3gqcRXAL0cviLH34TZ05fQH1pxwRiQyZSXz0VG5QGu3FdsUiXPHqiDL19o2tZbFhXDJ1GJYIPDxw6LVwiqWWmp4C2eXR6Lci6m4IGj504JzISlhcvQHHxghEo9AVNW0Hku0AvyhXLFoplf6PJBJPJLF6I9GVNjX5OKycWs3XCOAByEf3ed57Gvv3HcKlyfCvtye6Mt2KD0owpE+XI0TM4f+HKZN1P+HMSZUqVEuSuSemiGpUKVdV1YgVifv5c4SKrVaug0aqh1WhwtuwCSs5UCPZr1yxBd1eXyEiSKzXo6urF4aOnxXgZackYMhpFNpLZ7Hu8zYjY6OiAsaFOBMXKZYDZbMLAgAEf7jzg9fW7xUb9UB0sDt/n5vXAfAIT8IMAiw0/4PGpM4+AQqpAhi4TUkpNHWocdQH0cnCJjTgMNY3++VhXXFQ4B6nJ8Whr60JJ6Wg3Ttpm2bCGam0o0NM7gJOnKya1wKYXJwWmkukVuZVqtBoRmEqCgmItNm9eDXKWpGV7lUoFq8WKF3/3ppgelRmnwly0fUPbNFSzZP/Bk6irbxIxGrlzskUmBMWSzJmdiYaGZuz64pBY/i+YN1t4g9jtdvG1T06r16rqhGhJiI8RQbKuKulO8XtPbx+MRouI2XDYHdi/52PxM3qB0wu/s7NbZPNkpCdDIpVAJpUhPFyPVSsX46NP9ohASTKwio2OFKZWMrlcWM1X1zaIn1Fsw7KlRVAq5FDIFVAo5ejtGxgxAqMiZHTeze3Ntz4Rgb2LF+YjOTkRJpNJrEAYjEY0N7cJs7WwMB1Wr1gg/FUqLlaJku7BaBK5DJq4BFi7OrF9+XzEx0Wio6ND8Hn7/d0+BQ6z2AjGneI+g02AxUawCXP/IUWAxMZz9z0BnUqN37z32qgvfyE20jOhjo/3WGzQvj+VI6eX6tGT5ejtHRh1zWQYtWrFQijkMvQNGHDk2LmAcaEXplKpFKsc1OgFrdVqxJc+ffHTi/pqVa0IYM3JzkDu3GxRlpxe3BTo2NbRhU8+3SfEzdNPbBcxKGRG5W4vvPiaEEcPP3gPkpMTbpn3/v3HcelKNe574HHEx0dDKxsQ1V+pNTa1ClFA/X3v20+Put433vwYXT192LxplVhpoK0im90mfi8/f1mstiTExaBoQZ4waLPZrLBabBgYNODiZVcRvNSUBCGmKAXZYrGIl7fD6ZiU7Ypl80F1bjq7enGyJHjl7UlsaOMSsa5oLgoSwnHtWpUotkZW9+UVVyed51gHpGhT4JRKwSsbPuHjk6aJAIuNaQLPw04PAYVEgbsWrsfWTatxoPwYvthz+JaJ0EtWrGx4ITaog8KC2UhPTRgzdsM9QGJiDJYU5Yn/rK5txqXKGwGD00Nj/FFJOMnkUhG/4A5ipe0ZuUImRBV9mZOqMBqNsFjtKFi4SqyM1FWViu0iWt0g0eCue6LX68QqicPpRPHiAuFp8vKr70/LZWdlpiA/N0vM7/CxUhiMgfHUGOtiSGzEZWbjwfXFaL1YJoRfR0cvPt9zzOdrd4uNuqFaWB2uLTluTCDUCbDYCPU7xPMLKAESGxn6TCyen4dV2xbg0137cfTEjaJpvooN2tJYv3aJyGo4deYiOjp7xpz3gvlzkJYSL352+swlEQw6nc2dxkkrDL42itl46ivfgt3qmYMoZeFQfAqttEx1iwzXYeWKIhFjc+HSddTWtwRtCiTK5GolFFExSNYrUZQULsba+dkR9PSOLh3v6URStSlwSKVgseEpMT4uFAiw2AiFu8BzmDICbrEhdThRsCob69ctwx9efR+VV12rDL6KDTp3Xm4WsjNT0D8wJL6Yx2sb1i6BTqsW/hQHj5wR2wLT1fJzc7Bh/XK8+Ns3fa7j4m2A6HRdKwmrNSuLRAxMa1sXzowRXxOoudGK0KYNK6DSanDs/DWsXTALir5ONDZ1YP8hVxCqr43Fhq/k+LzpJMBiYzrp89hTTkAukSNTnwUSG42GRhQvLkRp+cUbqaUSKcIyvd9GoQuhL/aN65aIGIWy81fQ2OzybLi9UfGtzZtchl+U6XD0RDmMpunxS6CYhx0P3IPX3vhYBHv60rwRGxQXsm7NUhw9ftYvbw9f5rmwcC5SkuNgMJlFRVfrcIE+X/qa6By6//dsXovMjBTsOXAC6XlzoLOZIOvtxBtvfy62kvxpI2JjsBZWJ2+j+MOSz506Aiw2po41jxQCBG4XG+4ppSTFQ6fT4ur1ep/FBvXlLj9PIuLAkfHdKEmYrFxWCL1egyGDEcdOnJ8Wgy+KpXjuKw9j5659qK2b2MRsvNvnjdjIyUrHli3r8dIr72Lopmq5wX40SFQVzZ8tAoKPn6zwaxtjormSt8rWLRuQGB+Lz788BJVGjaz5uVCbDdj5x/cCsoqVqk2FQypBHYuNYD823H8ACbDYCCBM7ir0CdwQGxBVM93t8Ue2IX/ebPzhtQ/Q4VS4AkTJrtzLr1DKDFm7aiF0Oo2IB6C4gPEaxXmsXlUElUIBu92JPftP+ryV4St5iiv47refwsmT51B6fnTarif9eiM2VixfiNy5s4Sb61S1iHAdViwrFCm1lVdrUVXtWUqzL/MrmDcHK1csxKe7DsBgNGDFikVw6sNQc/4SSvffGozsS/90jlts1A7WwOa0+doNn8cEppQAi40pxc2DTTcBmUSGLH02pI5bxQYtfX/1mYeQkZGCdw+dQ6vR6pPYoOuLjYnA8uL5ogjbsXGMvtwcwvRarF+zRNQTofTNfQdLPErdDCTHJx69D3X1jThxqsynbklsPPrkV2G12PHR+69NWBtlx/a7YbGYha/HVDRaaVi1skgYe1HQLgXvBqPROOQrQo1Wi6xmCzZtXApypG0ZsqLs6CkM1tUGZGgWGwHByJ1MMQEWG1MMnIebXgJusSFzStAwdGulVhIc9OJNXVCE3SUVqDx9xuuVDffVLSycg5TkeGFvffR4+YROnrGxEVhRXCiKchlNFhw4dCZogoNWXjQaFdQaNTRq+qVCd28fOjt7EBcbjYKCOWKlhXw75Ao5hgaH8OXeo+KyyPJdpVAKnwgKpJVKJXj73U/R1d2PzVt2IC01ccRng8qml5ZdwvGT54QZGG0tkOkXiSvaNmrv6Mauz13umSuWFQljLtp6Ip8Mk9mEpqY2kZJK98Rhd/rEg4I0ly8rQLSwhDeK2JhgxGlQjZktd68V9XBqaxtFuvDdm5ZDLpfCIZHh6PnrGGxpwWB9oMRGGhxSgFc2pvfvEh7dOwIsNrzjxUfPcAITiQ26NKlUhq3PPIarbT1ovHQZ8MAgaiwk5Ba6fs1i4T1xqbIG1bUTx0MkJ8Zh8cJcITjIaKrk7KVJXUbHGpe2RZKS4hAeHoawMLJA1wmzrr37jomX95Z71wljr5vbydNlKDlzHinJCcLZk9xIySDLYrNjoG8AJ0tc9UsWLywQv5NfBpl80VyrrtcJ+/VHHv+K+NmlsuOA1CleuF1d3aKwGbl15s3NEb4dsTHR4qvfYDIJ63Vq2+/bhIhwPVRKFVRqpag78v6HX6C5pR0rly/CoqJ5IoCWBIPBYMT163W4WFklAnJjYyLR2z8wZo0St/cJOaXSChPVnwl0I0v0tWuK0dTUii/2HBHW8WtWLgRt3ZAXyaET52FTa2Fqbw+42KgZrIbdaQ/0JXF/TCAoBFhsBAUrdxqqBOglmK2fhbFWNtxzDsuaBXVcPMztrcjJTh9Ji/X2mtJTE1FYkCNMruhlRymxE7WkxBgsLMqFFBK0d/bg7DlXddjbG61OUBG1mJgoREdHICoqUtiL7957VBhuUd0RuVwOo8Ekqo+SsRa92OnfExPjoFYpYTSaXHVVjBbExUXj7s1r8Nbbn464kHpzrd7EbHjSL4kIuh66drJdJxdRrU4DvVYjitORvTrVVElOjMfDD90ruiSB1Nc/gI6Obuw9cByZGckoyMsWK0olws9kbN8TT+Yz1jEiNmd1MQoK5qL8fCWOHnOtRuXPm4Ws9CRxyrnyK2jt7IU6JjagYiNNlw67xAkWG77ePT5vOgiw2JgO6jzmtBHwRmwkqWViJeDChSviZT3Wi3+yCylenI+EuCgMDBpx7HgpbGOIh5v7oHiP4kX5YqvCbLXhwMESUUskKSEOA0MG1Dc0Iy01CQ9u3yxOGxwyoLenH+0dXTg2bE5GQoT+v6eVYsm2+6knH8AHH32Jpua2yS5p1M89FRvk6UFbKLX1vmW93D4wBXzStVIp+IjwMERGhokVlUuVV7GoKE+4pkdGRsJstQsR0tbeierq+pHYCq8v9KYTSBA99MDdqLh0FRcvuazT42IjsXRJgRiXaq1QzRWpQgF1dCxMHYFb2WCx4c+d43OniwCLjekiz+NOCwFvxIahtRnzcmdh/dplYkn/iy8Pe/3lT4GDlJ1CdUrq6ltQMUF2ihtIfGw0lhXni20KlVqFxMREsWJRXlGJI8fOiO0DWo3o6u4Vy/b+NvpK/863nhRf575UYfVUbFAAbnVNvbiGYLXY2EiXWJNKRCyJyWRFbHwMEmJjhBh56dX3xJYLbX+Q4zqJNyrs5mmjrSZaFSL3U3qW3HVYoiLDsGxJgYgxudkwzC02jO1tGGqo83SYCY9zi43qwes+xbIEZBLcCRPwkgCLDS+B8eEzm4AUUmSHebKNEgdDa4uonErL9bTCYbc78Na7n3r9gqcvXnoRUSs5dwlt7bdalIs4i8RYUS+krqFZVGclA6rU1AQxPgVjHj56Fn39E2/D+HNnnnhkGzq6urHvwAmvu/FEbFDcxteefVgEhVLl2mC0yAi9yAKiF35LayfOlV25JTD35oyRezevwaxZGSI+pLenDzV1jULMUUn5sRoJi+LF81G8ZL4oAnfg0KmRw2h1hZxJRbxNZ6+4x+5VMKlSCXVUDFhsBOOOc58ziQCLjZl0t3iufhPwRWzQoBRkSfEbvnpRuK3MqXopxW8MGUwieJO2FvLyckQQJW19nDhZisorLm8OquOxZtVikUpKcR/HT5YFTXCQtXZcTDTeem+X14xJbDzz1W/BZrPhrddfHjP1lbw1qLrrb19622ux5smEqPLuiuWFIpPG0wBbCt5NS0sS6c7ZmWn46OPdogotxbX03xR0Svf+7rtWIykxDqfPVIhgWooFcT0XWlETh0ShzebA3gOnbvFKIbGhiooWMRsBX9kYuA4HJq9w6wk/PoYJBJsAi41gE+b+Q4oArSLMCs+BzCFB41DDmCmprgDROBjaWuG0j472p60VCso8eYoqnHr2lz1tVSxfOh+03D44aMTRk2WYP28Oli0tEuXfSWC0tHSMmo+aCrytXiS+1ikG41xZZcCDHV3CJkzcJ8rs8LaR2Ji/cDWcDiculB8bU2yQmElIiMUbb+30tvtJjyehQSsaarVSbIlQyXhP41XcndNz4RYQtMoTHROJK1ercfbsBWzffhdkEim+3HMEza3tI/PR6dTYuHbpiBgUpmy2W5+XG2KDtlFuTbWe9MLGOWBkG4XFhq8I+bxpIMBiYxqg85DTR8BTsaGKi4NxHLGxoDAXq1cuEd4UlAHiaU0ReimuXb1IVBwlgyla5qf0SHcJ9/GokNBYsjBPpHlSq6lrwcXL4zuTTjVdEhvLV28WfhinT+wde2VjTjZIcFHKaiAbrTosLy4ApRpTEO7J0+f9DgCl+JqF8/NcniNqJa5ercWxk+dE2q270YoG3UsKBqU1jj17T8LirrUikUCmUkGmVkOh1UGm1aH/aiUM5EjrZ6PnN1WXBrvUiep+XtnwEyefPoUEWGxMIWweavoJeCY2sqGKix9XbNBVUDrm5rtWi+0VKipWcfHKhBdHKwfbtm6AWq1Aa2urCPj0RjRQzMDqVQsRrteIcYYMZhw5fs7rL/iJJrl29VI0t7QJ7wxvmicxG9705+mx5GWxlISGQoG+gSGcLrngt9CgsefOzhJprddrGjA0aEBWVhre++Dzke2R6KgIFC/OEx4qdqcT+w+chhUkMNTDvxRwWO1wWCxwWMywm80YrKvx9LImPO5msXG9v2pCs7iADMidMIEAEWCxESCQ3M3MIZATPhsKBzmINo655x2WNbnYoKulFQda4aAVhw8+2jNuZgDVSXnsoa2w2W3Y9flBqFRyLC7KE8AuVFajtrbZY3jz82chI83l4+CEBIeOnAmYWdXjj2wVWRZ79h3zeD504GRiIzkpXqTyNjS2etXvRAdTZsmyJfnihU9bJ6dKLvrtDkpxMxvWLhcxHNeu1Yh0ZzJCc2edkLCkNObcuZlwSmXoGTTifGUdHDK5MH+zC3Ex/Mtqhd1ogM1ogN1oFDEdgWgsNgJBkfuYDgIsNqaDOo85rQQy9JlIViWiy9QJi8MCi90Cq5N+t4qS3UJsxMaJDIKxYjZunzz5PdjsdiQmxIpAz2tVt64MrFm1BHNmZ+Htd3eJIFBq7uqw9O/kx0C+DJ42ym5ZLuzNKSjRjvIL10T2hb+NVjYyMpLwx9c/9qqrycTG9m2bhNj48JM9XvU73sEJcdFYuGCuEHvdvQM4fcb7GI3b+6bYmK8+swMWixUHDp8StuM3N8oI2vHwVhitFjhlVAfFhtMnS2E1meCwWsUvl7gwCoHhDFL5egpwTtGlim0UXtkIyOPEnUwRARYbUwSahwkdAvSlSsXY6CuR9typSZwQ/0Xpi/K0BCA6AkPtLbBaTbA57B5F/ZOoKFowTzhcHjpSckssB9UgIcvtm1tebiZmZaaK/0WCoaHRc0MtilFYsnCeCDil1tdvwInT5X5tq8zJycQ9d6/F719+R3zRe9omEhu08vDNrz/uV1XZm+eRmZmM/Nwsca8ozfRM2WW/rpnquTQ3t4tA31lZ6WhsanFtxYi4C6XYFpGrNVhQlIdInQYShx2Dff04fvQsbCYjbAbX6gWtaExFu1lsVPW7zMS4MYGZQIDFxky4SzzHoBBQSVVQypRQydSgf1fJlJBCBnV6KuQxUbB1dAN2KuEtgc1ph81hgc1hg9Vpg81uBUmQ21tmeoqolUErHKVll3H6zMQCID83G1mZySLIsPz8FTQ2d3h8rfTCnTs3AzlZLsFCwaanSi74nK2i12nx3FcfwedfHvIqbmMisUF1WMij5NXXPhBF6XxtdK0F87KRMWwFXt/QiguXyNTKlYLqbYuNjcLqFYuRlpY8cr2UOSJTugI7SWhQ3IVC4sSCeVmI1GshtdsQExaGF194VQgN+Di2t3O9+XgWG/7Q43OnkwCLjemkz2OHHAGFRIHo7LnQJyTD0d0nYjtkErnrZT78i5QBvfzIPZK2XSgWwwr63SpECS3vLyoqQO7cbFEVleI6yHL8o0/2jhnQ547DoNRLeoHW1Xu+pULzutlxlP5bbC2UVMBm9z5OYH7+HOGq6Y0wILFx1707YLfZcGDvzluyUchbg17sb779qc/3WimXY2HRXMTFRglRdtmDwnbjDSbSZJcuFPemp38Ip0ovorG9C1KlWogHEdA5HHeRGBOBBbmZUEudcFpMCNeHw2Z3Cq+Q6WosNqaLPI/rLwEWG/4S5PPvOALhGdnQxifC0NEGh90mCqMppUoopEqxEkKCRC5VjIgPsRVz0zaMDbTyYYMdNpjtFmRmp4AcKykOYNcXh8YMJC3Mz0F6WqJgWVXTiMor3pUjJ4GzYtkCRIRpRR9kGna+4powqQp2I7ExO2+JWGW4Xnn2FrFRVJgnnFcny9YZb460TUTF6bRqlYiLKTt/VdiB+9Io7mJO3mwsX1mMssvXcb2mETaz6dagTpMRDqMRyxfORUZKnBimu7tPuII+9vB9+PjTvUKMTVdjsTFd5Hlcfwmw2PCXIJ9/xxEYERudbXCME+hHKxsKidwlPoQQUQhBMlYcCNlZr1q9CLowLSx2Mw4eO4Vr12tGbcPMzknD3BxX+fem1g6cP3/NY9Mw901ITooDCRcSH9QMJgtOnCwfFS8y3k2j2JIF83Nx8XKVqBLrSSOx8eQz34TNZsW7b70yps+GJ/3cfgxtD9E2ETGlAm5kaOaVZbtEgoiYaBQWFUCl0+JESQWcViukTgdMQ0Nw2qywm8wi5kLEXZjNiI2OxJZ7Vom6KdQGBk04dqIU7R3drpieYedQX64nEOfIIEXycIAox2wEgij3MVUEWGxMFWkeZ8YQ8ERsjHcxcpAAcQkPuUwJpUQBmcT14l9YmIvCglyxAlB67iIuXL4K23D8h4gDcViRmByDwoLZwviLtkPOlV2GyeRd8CEFZebOzRhJkaVYDooFOV9xdVLxQvVDvvHcYzh+4hzKzl/26J6NF7NBAaftnd3o7e33qB/3QTSHBYVzEB8b5RJeLR0iY8cTV1AqfEZBnZGxMShYMA/Z6SliW+RSxSWcLSkXqxgucWGE/aa4C7lUiqIFczEvL1uMSasgFrMdBQV5qLhQibfe9d7G3auL9vBgt9iwSRy4PhBYgzQPp8CHMQGfCLDY8Akbn3QnEyCxoYlLhLFr/JUNb66fXhBiC0aqgFatRV7ObHR39olaK/Fx0WikcuQXroitGMqG0UeokTcvEzIFlZk3o/RCJdooWNXLRqZXK5cVQSZzfaaT6Dh/8dqkMSEiVVUuw4cf7/ZoxLHEBgmGr3/tUZwuOY+zpRc86ocOSk1JANWRUSrkYvvlwuXrE2bpSOQyV8aISg2pSiUYyuDAEzvuhd1iRvm5CpSdKYexv1+Ii7FSmWk1aOmSfISH6cQ8FUoV0tPSRK2Xg4dPiXo1tIUTCo3FRijcBZ6DLwRYbPhCjc+5owkEWmyMBYuW5FcsWYh7Nq6DWq6Cw+pEc1M7Dh8+g57uXmg1auTnZUOn0QhDqPrmFlytqYPFZnVlxDisHqXj0tiZmSmYnzdrZHujf9CAqqp6NI/jzVEwbw7Wr12K3//hXY+2X8YSG4UFc7FmdTFe+eMHI94iEz00Oq0a8/NzRizZyRG0rPzqqK0cWnEgK3ASFpQ1IpHKoJRIkJOZjJz0FHzwwWcwDw4hOSYCDdW1sJjGT+Gl7a177lopTNaoUen40rIruPee9ThbehFnz12Y1Ep+qv8gyCFDki4FvLIx1eR5PH8JsNjwlyCff8cRuCE22uGwWYN+fcuWFIoXc0x0FKwWO179w4eIjYyCXq2HRqlESmI87Ha7cMq8fLEGgyKWQgK70z6chmtxpeZSNgzG/gKnGI783FlITIyBYjieg/q4cKkKtfUtt1wjCR1KgT18pMSjwM6xxMaTj9+H/r4BERA7UaN6KZT6OzsnXdROIb+La9fqUV3bNJLWKuqMDK9cyBRKcU8cZgviY8JRMHcW5malirTUKxcq8fmuPRgcdBmnjddioiJw7z2rIZPeOEKr0+OlP7wPqsobyu2G2LDj+kDo1McJZWY8t9AgwGIjNO4DzyKECLjERgKMXR1TIjbclx4RpseiRQU4fOQ0tt+3CcVLCiGVStHR1oWuji7InFJI7DI01rXj6pUGYc99ezouuYpS/IfVYYPdaYWV0nKdNwQTCY05ORnIzkoRWzauJhGZGdeu14/ERdDKRHNLOzq7eia9MyQ2Hnv6OditNrz/zh+RlBiLh3fci48+2YOGxluFjLszYbudEo85szOgUSvF/6bS8BSbYbTaXTVG1Crhe+Gwu+qMOC1WxEWFo6WxGVajAc8+ugXhKiVKSsrFVs1YRmTkHZKSnICUlERYLRaYTEbkzs0aCQCllZFjJ8pQdT0wFVknheXnARQTlKRLhk3CYsNPlHz6FBNgsTHFwHm40CcQnp4FTTzFbEyt2LidzBOPbkNB/hzI5XIMDAzi+vUaKJWuYFNyQZU6lejpGkBv5wBamjox2G+6IT5uc0WlNFwSHiIg1WEFZE7k5+cgJSl2RHRQAGZTS7uI6egf8CwTRUgVcmTNKYJTIkHttVKEh2mRP2+OiHUYK3sjMT4Gc+dkImy4qJzBbEVVfSvaugeFwKBG4sJutojO2+ZfAAAR50lEQVTskYSYCMzOSEb+rHRE6TX4zW9eQ219M0hIuO3f9Xot4mJjxGpKV08v8vNm48Htm0H/n6q1dnZ2YmjohqmY1WrH3gOnRPXdmdRYbMyku8VzvZkAiw1+HpjAbQTcYsPU1QH7FGyjTHQDlAoF5uXlgPwqsrPT8fuX3kbxknnQatXiNJlMhvj4eBw9dhbHTpaiIHcuNq9bhb7uQQz1G2EYMKO7qxf1DS1CiMikcjiHXVFpG8YpcSAtIx6JSTGQq6RwDruiOpxAT+8AnHbg5JnyCZ8REhtbtz8Gu92GL3d9MGbqK22RUCAmbZmEhenhlMthcUpQ19yFlo5u2ExmYahFIkOnUqK3s0tkjXzl0W2YnZUitkZq6xrR2tqBI8fOwGyxYMPaZViwIA9RkRGgsvDU9u47hr0HjotA06WL5yM8XAuH48bWUktbJy5evD5uvEqo/2Fwiw2rxIbqgepQny7PjwmMEGCxwQ8DEwhhsXHz1CjDg+p2UFrsd775GExUUXS4mqjVZseFC+SNYUBR4TxERUeCKqNGRoSjrqYZb7y5E3qVFn/5/HdgMdpgGDSJL/6hwSEcPHQKVosVlKoaGxMByMmhzAG7xA6n1CkMyq5W1Yky7maTBXaqFeNwwm6zu7ZyJFI8+7Vvw2a1ob3pMmrrG0V9GIvFJoIvZ2WlITkjGXK1WhQxs0sk6GjpxLWr1VDJJJidlYHYCB3iwnWICdNCq5Tjf//8t+jq7sWP/uHPQEXSbm6//PUrYotnWfECJCTEoqe7T6xm9PT0gRxCaXsmOTlOxIC4Vl4k6O4ewOFjZ71yRg3FPxhyiRxJ2mSw2AjFu8NzmogAiw1+PpjAbQTC0jKhTUhCKKxsjHdzKOaB6oQUzp+DqEj9yFYIiQaT2QqnU4KaumY0NbWhr39AiALajiksmAO9Xge9Vgu9Ro8wjR47P9kPqUOK+7fchbSUJBEj0dfXh8GBIZiMJtG3Q+KAE3bI1XKoNCqodUr09g3ivQ+/gFQiw9e++V0RB6GVDcDhtGPQYMK1ukaER0UCcirBDiikQKROh0i9Dk31TXj37Y+RmRSHrz6+TQgo2sYhAdTe0YVXX/tQZIIsLy4Sqxi0jURbO/0DgzDdVNAuIlyPrIwUzJmTCY1acVMcCkBbJXUNLTh79hLM1uAH+k7FHyS32LBIbKjhlY2pQM5jBIgAi40AgeRu7hwCI2KjuxN2q3eGWtNBQSaVYO6cLMydnYGwYbtymodCoUB4eDgUCiV27z0mTLqSEuOQmpootlZoNaCvd/CWuAqyYqeCdDq1Tvwqys8TAaUNdU1QqykTxCH8LygdlwQIZcHUNjZj7qIVcMokMBhbIUrXSWhxxA6pndw6BxEfHY3oMD3CVHLIHXYYBofwk5+9KPwrMtOThXDp7ZvY/EuhkCMiTCdWM2KiI5CQEA1yPL2lSSS4crUOV67WiD7vtEb3J1GbBBYbd9qdvfOvh8XGnX+P+Qq9JCDERnwiTD1dM0Js3Hx5CXFRyM5KFaseSqVi5EcOh0MEQyrkShQW5kGlUkGpVIqVgPMVLodMjVqNp564X/hN0C/rcBro7FlZaK5vF0ZkibGx0Ku1QmxYnRJQ5RgrpeGqIiGxOSExtLlEhsQOqcOKCxUX0dPVjuKieejtHRABqM1NrejrGxDG366EGKdY2VCqlELQUPyFSqmEWqUQRdzS05NFui5l2ozV7HYnGpvaUHHxGrp7vHMr9fLRmPbDWWxM+y3gCfhIgMWGj+D4tDuXwEwWG+67QqsdqSmJSE9NQEJCzEhA6c13jQSDRWxdmES8A6XAZmakguzO5Qo5JFKJECPXq+vE78kpSWSvCQfZr0tlkNolUDgBuV0CuUMKOYkNixUSkxlOCvakVRCbK77DIbWLbRg7/S51iCJ1ImLVy0bxIRSfcukSBXl2oKurd1ILdi+HCOnD3WLDDCtqB2tCeq48OSZwMwEWG/w8MIHbCNwJYuP2mxqu1wpDr4T4WERG6BEWroNc5kqjHa85JVI4pHI4ZHI4pXJRhoyKmEnsNhiHBmE1mtHZ2o7Ki5VIiYsXAasNtU1IionH3FnZ4nfKiFErlYiOjBQrE3ar3SVA7LQNYxdbMSREXP9up5xesa1jNlvR2taJoUEDjCaLiOPo6xsMedOtYP9hUkqUSNAmgsVGsElz/4EmwGIj0ES5vxlP4E4UG2PdFJ1Wg/BwHfR6DZS0mqFUQqHWQKHRQKJQweaww2YywUqVUU0m6NRKbFy9BOmJsVBKqQaJE6dLyvEfv/g9li9bBIvFinOlFaOGcsWBqESFXI1cA61CA5mExAv9M7zA4YQIEKXgUovDAqvdAovTCoud3FFD29VzKh94FhtTSZvHCiQBFhuBpMl93REEwlIzXNkoMzBmw7sbIIFc1BjRCKdOqVwBh9UiCphRpVQqwe6ukEq/0/+nNNLcubNELEV7exeuVdWC4kFe+u1/CC+MP/vz/9ejKZApmVqqFgJEJVNDJXWJEQrkGNsV1SU8qCaMECMO67SXe/foQgN80A2xYUHtYG2Ae+fumEDwCLDYCB5b7nmGEhgRG73d4gV7JzWqLeKyAle7rMCtVpdbp8UyLDRMsBkMsJmM4tdwBOekCLwVG2N1SOscSpkKKikJENWwCFFCAulIeIdEiBFXsAcJDuuw8CAhQiLEMWxKNumEZ+gBSqkSCRraRmGxMUNv4Z/stFls/Mneer7w8QiQ2CC7cnNfz4wXG1K5HDKlS1zIlSoR6CmExfDqBa1kuFYvXL8oaNSXFgixMd64CqlCrHy4BIgKSqkK5DdB7fZVELvDJrZfbEJ8DG/DiGTcO6O5xEYCTLCijlc27oyb+idyFSw2/kRuNF+m5wT0KeliG2Umig3a5pCpNMKtk6qlSiQy2K1mUWeEhMUNcWEU4iJQVW2DKTbGunMyiWyUAKEX8VgChAJT3VsvtBJisVtFcbqx6rZ4/pRMz5G06hPPYmN64POofhFgseEXPj75TiTgFhuW/l7YzKYQv8ThuAvaGqEy7ArFyLYIbQGJuAvaEhneGrEH6XqmWmyMdVPc2zDq4VUQ95bMWNswtMJjo6q47hiQ4ZWQUN+GYbER4n8ceXrjEmCxwQ8HE7iNQKiLDVfcBQV2UtyFGk6bDXazWRiQueIvzDe2RryIu/DnQXj+B98QVuO//f0b/nQTlHPFNoxMDRIh7oBUGVxpv+5tGIoFof9yb8NY7WaxDWO1W2ELoW0Yt9gwOi2oH6oLCi/ulAkEgwCLjWBQ5T5nNAF9Shq0CckIlZUNqUw+EtTpirugEuyUMeLKGrl1a2TI57iLGX3TvJy82IYRwahqYc9OYoRSdG8WIK7MGDI2o3RcyoKhlRAzrHaKC5keG3sSTHGaeLDY8PKG8+HTToDFxrTfAp5AqBGYbrHhirtQD8ddqCGRykYHdY5sjRhERgk3/wlIIb0pFdeVEUPBqG4/ECFERgSIaxtGZMHcFJAa7G0YEhuxmniYeGXD/xvOPUwpARYbU4qbB5sJBKZebAzHXShdWyNSsgR3p6PSyoXN4oq7MLqCOoMVdzET7s10zJECT12rIDcyYqQ3b8MMe4OMbMNQEOpwSi6Zk9lgD9i0b4gNM+qH6gPWL3fEBIJNgMVGsAlz/zOOgD6ZtlGSYBnoC1qAqEyucMVc3Bx3MRxvMV1xFzPuRk3jhCn11r3yoR5OyZVPtg1DpmTOG9kwvkyfjNBiNXEwOVls+MKPz5k+Aiw2po89jxyiBEbExmC/y9gqAM0Vd6FybY+o1K64C3LrHA7sdFotsJLXhcgaMcBpD9zXcACmz114QIC2YVy27K5VEBIhCimZkrltyG7fhnEJD9qGoYBUq8M2qSmZW2wYnSY0DDV4MCs+hAmEBgEWG6FxH3gWIUQgEGJjJO5i2K1z3LgLsTUyxHEXIXT/Az0VtxW725adAlLH24axOWwiCNUVkOqqEWO/yRVVLVMjVh0HFhuBvkvcX7AJsNgINmHuf8YR0CWlQpeYDIuXKxtk/02rFiNxF1aryBhxkKGWiLswjaSkctzFjHssAjphynxxpeHesGUfbxvmRnE6K6imTLgyAgOOQV7ZCOgd4c6CTYDFRrAJc/8zjoCnYmMk7oIEBqWk2u0ia8RtB07bJK6tkSEhNOD0zQp8xgHkCftEgITEjSBUKk6nHLUNQwGierke9cYGNBmafBqHT2IC00GAxcZ0UOcxQ5rAeGKDtkKEDbjSlZZKTYiL2+Mu3HVGOO4ipO/zTJiccEUdKUznSsW1OMzoMHXMhOnzHJnACAEWG/wwMIHbCAixQdkohiGxGiG2RlRqSGTykQJmYnvEZoXdaHStXlCdEev0GD3xDWQCTIAJhDoBFhuhfod4flNOQJeUgujcAjjJKXJwcMQC3J09YjUOiawRjruY8lvDAzIBJjBDCbDYmKE3jqcdPAJyjRa6lDRIJFLYjYaRlQsy1eK4i+Bx556ZABO4cwmw2Lhz7y1fmR8EqHqq0+EUqxvcmAATYAJMwD8CLDb848dnMwEmwASYABNgApMQYLHBjwgTYAJMgAkwASYQVAIsNoKKlztnAkyACTABJsAEWGzwM8AEmAATYAJMgAkElQCLjaDi5c6ZABNgAkyACTABFhv8DDABJsAEmAATYAJBJcBiI6h4uXMmwASYABNgAkyAxQY/A0yACTABJsAEmEBQCbDYCCpe7pwJMAEmwASYABNgscHPABNgAkyACTABJhBUAiw2goqXO2cCTIAJMAEmwARYbPAzwASYABNgAkyACQSVAIuNoOLlzpkAE2ACTIAJMAEWG/wMMAEmwASYABNgAkElwGIjqHi5cybABJgAE2ACTIDFBj8DTIAJMAEmwASYQFAJsNgIKl7unAkwASbABJgAE2Cxwc8AE2ACTIAJMAEmEFQCLDaCipc7ZwJMgAkwASbABFhs8DPABJgAE2ACTIAJBJUAi42g4uXOmQATYAJMgAkwARYb/AwwASbABJgAE2ACQSXAYiOoeLlzJsAEmAATYAJMgMUGPwNMgAkwASbABJhAUAmw2AgqXu6cCTABJsAEmAATYLHBzwATYAJMgAkwASYQVAIsNoKKlztnAkyACTABJsAEWGzwM8AEmAATYAJMgAkElQCLjaDi5c6ZABNgAkyACTABFhv8DDABJsAEmAATYAJBJcBiI6h4uXMmwASYABNgAkyAxQY/A0yACTABJsAEmEBQCbDYCCpe7pwJMAEmwASYABNgscHPABNgAkyACTABJhBUAiw2goqXO2cCTIAJMAEmwARYbPAzwASYABNgAkyACQSVAIuNoOLlzpkAE2ACTIAJMAEWG/wMMAEmwASYABNgAkElwGIjqHi5cybABJgAE2ACTIDFBj8DTIAJMAEmwASYQFAJsNgIKl7unAkwASbABJgAE2Cxwc8AE2ACTIAJMAEmEFQCLDaCipc7ZwJMgAkwASbABFhs8DPABJgAE2ACTIAJBJUAi42g4uXOmQATYAJMgAkwARYb/AwwASbABJgAE2ACQSXAYiOoeLlzJsAEmAATYAJMgMUGPwNMgAkwASbABJhAUAmw2AgqXu6cCTABJsAEmAATYLHBzwATYAJMgAkwASYQVAIsNoKKlztnAkyACTABJsAEWGzwM8AEmAATYAJMgAkElQCLjaDi5c6ZABNgAkyACTABFhv8DDABJsAEmAATYAJBJcBiI6h4uXMmwASYABNgAkyAxQY/A0yACTABJsAEmEBQCbDYCCpe7pwJMAEmwASYABNgscHPABNgAkyACTABJhBUAiw2goqXO2cCTIAJMAEmwARYbPAzwASYABNgAkyACQSVAIuNoOLlzpkAE2ACTIAJMAEWG/wMMAEmwASYABNgAkElwGIjqHi5cybABJgAE2ACTIDFBj8DTIAJMAEmwASYQFAJsNgIKl7unAkwASbABJgAE2Cxwc8AE2ACTIAJMAEmEFQCLDaCipc7ZwJMgAkwASbABFhs8DPABJgAE2ACTIAJBJUAi42g4uXOmQATYAJMgAkwARYb/AwwASbABJgAE2ACQSXAYiOoeLlzJsAEmAATYAJMgMUGPwNMgAkwASbABJhAUAmw2AgqXu6cCTABJsAEmAAT+P8B9pf1BrDYV3IAAAAASUVORK5CYII=\" width=\"539\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scene = BlochScene('dark')                       # 创建布洛赫绘图场景\n",
    "fig, ax = scene.create_scene()                   # 初始化场景\n",
    "state_obj1 = scene.add_state(ax, state1)         # 往场景中添加一个量子态"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 展示量子态演化\n",
    "\n",
    "当该量子态是一个含时演化的量子态时，我们还可以在布洛赫场景中创建动画。这里我们不妨假设仰角 $\\theta$ 和方位角 $\\phi$ 是含时的，我们求出所有时间内的量子态。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = np.linspace(0, 10, 500)\n",
    "all_theta = 4 * np.sin(2 * t)\n",
    "all_phi = 5 * np.cos(3 * t)\n",
    "states = []\n",
    "for theta, phi in zip(all_theta, all_phi):\n",
    "    states.append(circ.get_qs(pr={'theta': theta, 'phi': phi}))\n",
    "states = np.array(states)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面，我们创建一个深色的[布洛赫场景](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.10/io/mindquantum.io.BlochScene.html)，并用所演化出来的量子态的第一个量子态来初始化场景。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n    if (typeof WebSocket !== 'undefined') {\n        return WebSocket;\n    } else if (typeof MozWebSocket !== 'undefined') {\n        return MozWebSocket;\n    } else {\n        alert(\n            'Your browser does not have WebSocket support. ' +\n                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n    this.id = figure_id;\n\n    this.ws = websocket;\n\n    this.supports_binary = this.ws.binaryType !== undefined;\n\n    if (!this.supports_binary) {\n        var warnings = document.getElementById('mpl-warnings');\n        if (warnings) {\n            warnings.style.display = 'block';\n            warnings.textContent =\n                'This browser does not support binary websocket messages. ' +\n                'Performance may be slow.';\n        }\n    }\n\n    this.imageObj = new Image();\n\n    this.context = undefined;\n    this.message = undefined;\n    this.canvas = undefined;\n    this.rubberband_canvas = undefined;\n    this.rubberband_context = undefined;\n    this.format_dropdown = undefined;\n\n    this.image_mode = 'full';\n\n    this.root = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (fig.ratio !== 1) {\n            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\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\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    var cursor = msg['cursor'];\n    switch (cursor) {\n        case 0:\n            cursor = 'pointer';\n            break;\n        case 1:\n            cursor = 'default';\n            break;\n        case 2:\n            cursor = 'crosshair';\n            break;\n        case 3:\n            cursor = 'move';\n            break;\n    }\n    fig.rubberband_canvas.style.cursor = cursor;\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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 * http://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home 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, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    var manager = IPython.notebook.keyboard_manager;\n    if (!manager) {\n        manager = IPython.keyboard_manager;\n    }\n\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
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\" width=\"535\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scene = BlochScene('dark')                          # 创建布洛赫绘图场景\n",
    "fig, ax = scene.create_scene()                      # 初始化场景\n",
    "state_obj = scene.add_state(ax, states[0])          # 往场景中添加一个量子态"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了能够动态展示量子态的演化，我们从[布洛赫场景](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.10/io/mindquantum.io.BlochScene.html)中创建一个动画对象。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "anim = scene.animation(fig, ax, state_obj, states)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![bloch-sphere-anim](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r2.5.0/docs/mindquantum/docs/source_zh_cn/images/bloch_sphere.gif)\n",
    "\n",
    "由此，我们可以看到单比特的量子态在布洛赫球中已经动起来了。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<table border=\"1\">\n",
       "  <tr>\n",
       "    <th>Software</th>\n",
       "    <th>Version</th>\n",
       "  </tr>\n",
       "<tr><td>mindquantum</td><td>0.9.11</td></tr>\n",
       "<tr><td>scipy</td><td>1.10.1</td></tr>\n",
       "<tr><td>numpy</td><td>1.24.4</td></tr>\n",
       "<tr>\n",
       "    <th>System</th>\n",
       "    <th>Info</th>\n",
       "</tr>\n",
       "<tr><td>Python</td><td>3.8.17</td></tr><tr><td>OS</td><td>Linux x86_64</td></tr><tr><td>Memory</td><td>16.62 GB</td></tr><tr><td>CPU Max Thread</td><td>16</td></tr><tr><td>Date</td><td>Tue Jan  2 14:41:09 2024</td></tr>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<mindquantum.utils.show_info.InfoTable at 0x7fe9b428bfa0>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from mindquantum.utils.show_info import InfoTable\n",
    "\n",
    "InfoTable('mindquantum', 'scipy', 'numpy')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "MindSpore",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.17"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}