linear_regression_project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 欢迎来到线性回归项目\n",
    "\n",
    "若项目中的题目有困难没完成也没关系，我们鼓励你带着问题提交项目，评审人会给予你诸多帮助。\n",
    "\n",
    "所有选做题都可以不做，不影响项目通过。如果你做了，那么项目评审会帮你批改，也会因为选做部分做错而判定为不通过。\n",
    "\n",
    "其中非代码题可以提交手写后扫描的 pdf 文件，或使用 Latex 在文档中直接回答。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 目录:\n",
    "[1 矩阵运算](#1-矩阵运算)  \n",
    "[2 Gaussian Jordan 消元法](#2-Gaussian-Jordan-消元法)  \n",
    "[3  线性回归](#3-线性回归)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 任意选一个你喜欢的整数，这能帮你得到稳定的结果\n",
    "seed = 9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1 矩阵运算\n",
    "\n",
    "## 1.1 创建一个 4*4 的单位矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 这个项目设计来帮你熟悉 python list 和线性代数\n",
    "# 你不能调用任何NumPy以及相关的科学计算库来完成作业\n",
    "\n",
    "\n",
    "# 本项目要求矩阵统一使用二维列表表示，如下：\n",
    "A = [[1,2,3], \n",
    "     [2,3,3], \n",
    "     [1,2,5]]\n",
    "\n",
    "B = [[1,2,3,5], \n",
    "     [2,3,3,5], \n",
    "     [1,2,5,1]]\n",
    "\n",
    "# 向量也用二维列表表示\n",
    "C = [[1],\n",
    "     [2],\n",
    "     [3]]\n",
    "\n",
    "#TODO 创建一个 4*4 单位矩阵\n",
    "I = [[1,0,0,0],\n",
    "    [0,1,0,0],\n",
    "    [0,0,1,0],\n",
    "    [0,0,0,1]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.2 返回矩阵的行数和列数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 返回矩阵的行数和列数\n",
    "def shape(M):\n",
    "    num_row = len(M)\n",
    "    try:\n",
    "        num_col = len(M[0])\n",
    "    except TypeError as e:\n",
    "        num_col = -1\n",
    "    return (num_row, num_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.004s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 shape 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3 每个元素四舍五入到特定小数数位"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 每个元素四舍五入到特定小数数位\n",
    "# 直接修改参数矩阵，无返回值\n",
    "def matxRound(M, decPts=4):\n",
    "    for i in range(len(M)):\n",
    "        for j in range(len(M[i])):\n",
    "            M[i][j] = round(M[i][j], decPts)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.060s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 matxRound 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_matxRound"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.4 计算矩阵的转置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 计算矩阵的转置\n",
    "def transpose(M):\n",
    "    return [list(row) for row in zip(*M)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.011s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 transpose 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_transpose"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.5 计算矩阵乘法 AB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 计算矩阵乘法 AB，如果无法相乘则raise ValueError\n",
    "def dot(lin_A, lin_B):\n",
    "    dot_product = 0\n",
    "    for i in range(len(lin_A)):\n",
    "        dot_product += lin_A[i] * lin_B[i]\n",
    "    return dot_product\n",
    "\n",
    "def matxMultiply(A, B):\n",
    "    r_a, c_a = shape(A)\n",
    "    r_b, c_b = shape(B)\n",
    "    if c_a != r_b:\n",
    "        raise ValueError('Dimension mismatch.')\n",
    "\n",
    "    B_t = transpose(B)\n",
    " \n",
    "    return [[sum(e1*e2 for e1, e2 in zip(row, col)) \n",
    "             for col in B_t] for row in A]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.079s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 matxMultiply 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_matxMultiply"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "# 2 Gaussian Jordan 消元法\n",
    "\n",
    "## 2.1 构造增广矩阵\n",
    "\n",
    "$ A = \\begin{bmatrix}\n",
    "    a_{11}    & a_{12} & ... & a_{1n}\\\\\n",
    "    a_{21}    & a_{22} & ... & a_{2n}\\\\\n",
    "    a_{31}    & a_{22} & ... & a_{3n}\\\\\n",
    "    ...    & ... & ... & ...\\\\\n",
    "    a_{n1}    & a_{n2} & ... & a_{nn}\\\\\n",
    "\\end{bmatrix} , b = \\begin{bmatrix}\n",
    "    b_{1}  \\\\\n",
    "    b_{2}  \\\\\n",
    "    b_{3}  \\\\\n",
    "    ...    \\\\\n",
    "    b_{n}  \\\\\n",
    "\\end{bmatrix}$\n",
    "\n",
    "返回 $ Ab = \\begin{bmatrix}\n",
    "    a_{11}    & a_{12} & ... & a_{1n} & b_{1}\\\\\n",
    "    a_{21}    & a_{22} & ... & a_{2n} & b_{2}\\\\\n",
    "    a_{31}    & a_{22} & ... & a_{3n} & b_{3}\\\\\n",
    "    ...    & ... & ... & ...& ...\\\\\n",
    "    a_{n1}    & a_{n2} & ... & a_{nn} & b_{n} \\end{bmatrix}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 构造增广矩阵，假设A，b行数相同\n",
    "def augmentMatrix(A, b):\n",
    "    return [AA + bb for AA, bb in zip(A, b)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.007s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 augmentMatrix 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_augmentMatrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2 初等行变换\n",
    "- 交换两行\n",
    "- 把某行乘以一个非零常数\n",
    "- 把某行加上另一行的若干倍："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO r1 <---> r2\n",
    "# 直接修改参数矩阵，无返回值\n",
    "def swapRows(M, r1, r2):\n",
    "    M[r1], M[r2] = M[r2], M[r1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.003s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 swapRows 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_swapRows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO r1 <--- r1 * scale\n",
    "# scale为0是非法输入，要求 raise ValueError\n",
    "# 直接修改参数矩阵，无返回值\n",
    "def scaleRow(M, r, scale):\n",
    "    if scale == 0:\n",
    "        raise ValueError('Scale can not be zero.')\n",
    "    for i in range(len(M[r])):\n",
    "        M[r][i] = M[r][i] * scale\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.003s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 scaleRow 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_scaleRow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO r1 <--- r1 + r2*scale\n",
    "# 直接修改参数矩阵，无返回值\n",
    "def addScaledRow(M, r1, r2, scale):\n",
    "    M[r1] = [e1 + e2*scale for e1, e2 in zip(M[r1], M[r2])]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.003s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 addScaledRow 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_addScaledRow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3  Gaussian Jordan 消元法求解 Ax = b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.1 算法\n",
    "\n",
    "步骤1 检查A，b是否行数相同\n",
    "\n",
    "步骤2 构造增广矩阵Ab\n",
    "\n",
    "步骤3 逐列转换Ab为化简行阶梯形矩阵 [中文维基链接](https://zh.wikipedia.org/wiki/%E9%98%B6%E6%A2%AF%E5%BD%A2%E7%9F%A9%E9%98%B5#.E5.8C.96.E7.AE.80.E5.90.8E.E7.9A.84-.7Bzh-hans:.E8.A1.8C.3B_zh-hant:.E5.88.97.3B.7D-.E9.98.B6.E6.A2.AF.E5.BD.A2.E7.9F.A9.E9.98.B5)\n",
    "    \n",
    "    对于Ab的每一列（最后一列除外）\n",
    "        当前列为列c\n",
    "        寻找列c中 对角线以及对角线以下所有元素（行 c~N）的绝对值的最大值\n",
    "        如果绝对值最大值为0\n",
    "            那么A为奇异矩阵，返回None (你可以在选做问题2.4中证明为什么这里A一定是奇异矩阵)\n",
    "        否则\n",
    "            使用第一个行变换，将绝对值最大值所在行交换到对角线元素所在行（行c） \n",
    "            使用第二个行变换，将列c的对角线元素缩放为1\n",
    "            多次使用第三个行变换，将列c的其他元素消为0\n",
    "            \n",
    "步骤4 返回Ab的最后一列\n",
    "\n",
    "**注：** 我们并没有按照常规方法先把矩阵转化为行阶梯形矩阵，再转换为化简行阶梯形矩阵，而是一步到位。如果你熟悉常规方法的话，可以思考一下两者的等价性。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.2 算法推演\n",
    "\n",
    "为了充分了解Gaussian Jordan消元法的计算流程，请根据Gaussian Jordan消元法，分别手动推演矩阵A为***可逆矩阵***，矩阵A为***奇异矩阵***两种情况。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 推演示例 \n",
    "\n",
    "\n",
    "$Ab = \\begin{bmatrix}\n",
    "    -7 & 5 & -1 & 1\\\\\n",
    "    1 & -3 & -8 & 1\\\\\n",
    "    -10 & -2 & 9 & 1\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & \\frac{1}{5} & -\\frac{9}{10} & -\\frac{1}{10}\\\\\n",
    "    0 & -\\frac{16}{5} & -\\frac{71}{10} & \\frac{11}{10}\\\\\n",
    "    0 & \\frac{32}{5} & -\\frac{73}{10} & \\frac{3}{10}\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & 0 & -\\frac{43}{64} & -\\frac{7}{64}\\\\\n",
    "    0 & 1 & -\\frac{73}{64} & \\frac{3}{64}\\\\\n",
    "    0 & 0 & -\\frac{43}{4} & \\frac{5}{4}\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & 0 & 0 & -\\frac{3}{16}\\\\\n",
    "    0 & 1 & 0 & -\\frac{59}{688}\\\\\n",
    "    0 & 0 & 1 & -\\frac{5}{43}\\end{bmatrix}$\n",
    "    \n",
    "\n",
    "#### 推演有以下要求:\n",
    "1. 展示每一列的消元结果, 比如3*3的矩阵, 需要写三步\n",
    "2. 用分数来表示\n",
    "3. 分数不能再约分\n",
    "4. 我们已经给出了latex的语法,你只要把零改成你要的数字(或分数)即可\n",
    "5. 可以用[这个页面](http://www.math.odu.edu/~bogacki/cgi-bin/lat.cgi?c=sys)检查你的答案(注意只是答案, 推演步骤两者算法不一致)\n",
    "\n",
    "_你可以用python的 [fractions](https://docs.python.org/2/library/fractions.html) 模块辅助你的约分_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 分数的输入方法\n",
    "(双击这个区域就能看到语法啦)  \n",
    "  \n",
    "示例一: $\\frac{n}{m}$  \n",
    "\n",
    "示例二: $-\\frac{a}{b}$  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 以下开始你的尝试吧!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " -9, -2,  7 ||  1 \n",
      " -9,-10,  4 ||  1 \n",
      "  0,  0,  2 ||  1 \n"
     ]
    }
   ],
   "source": [
    "# 不要修改这里！\n",
    "from helper import *\n",
    "A = generateMatrix(3,seed,singular=False)\n",
    "b = np.ones(shape=(3,1),dtype=int) # it doesn't matter\n",
    "Ab = augmentMatrix(A.tolist(),b.tolist()) # 请确保你的增广矩阵已经写好了\n",
    "printInMatrixFormat(Ab,padding=3,truncating=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "请按照算法的步骤3，逐步推演***可逆矩阵***的变换。\n",
    "\n",
    "在下面列出每一次循环体执行之后的增广矩阵(注意使用[分数语法](#分数的输入方法))\n",
    "\n",
    "$Ab = \\begin{bmatrix}\n",
    "    -9 & -2 & 7 & 1\\\\\n",
    "    -9 & -10 & 4 & 1\\\\\n",
    "    0 & 0 & 2 & 1\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & \\frac{2}{9} & -\\frac{7}{9} & -\\frac{1}{9}\\\\\n",
    "    0 & -\\frac{8}{9} & -\\frac{3}{9} & 0\\\\\n",
    "    0 & 0 & 2 & 1\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & 0 & -\\frac{31}{36} & -\\frac{1}{9}\\\\\n",
    "    0 & 1 & \\frac{3}{8} & 0\\\\\n",
    "    0 & 0 & 2 & 1\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & 0 & 0 & \\frac{23}{72}\\\\\n",
    "    0 & 1 & 0 & -\\frac{3}{16}\\\\\n",
    "    0 & 0 & 1 & \\frac{1}{2}\\end{bmatrix}$\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " -9,  1, -9 ||  1 \n",
      " -8, -4, -8 ||  1 \n",
      "  2, -2,  2 ||  1 \n"
     ]
    }
   ],
   "source": [
    "# 不要修改这里！\n",
    "A = generateMatrix(3,seed,singular=True)\n",
    "b = np.ones(shape=(3,1),dtype=int)\n",
    "Ab = augmentMatrix(A.tolist(),b.tolist()) # 请确保你的增广矩阵已经写好了\n",
    "printInMatrixFormat(Ab,padding=3,truncating=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "请按照算法的步骤3，逐步推演***奇异矩阵***的变换。\n",
    "\n",
    "在下面列出每一次循环体执行之后的增广矩阵(注意使用[分数语法](#分数的输入方法))\n",
    "\n",
    "$Ab = \\begin{bmatrix}\n",
    "    -9 & 1 & -9 & 1\\\\\n",
    "    -8 & -4 & -8 & 1\\\\\n",
    "    2 & -2 & 2 & 1\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & -\\frac{1}{9} & 1 & -\\frac{1}{9}\\\\\n",
    "    0 & -\\frac{44}{9} & 0 & \\frac{1}{9}\\\\\n",
    "    0 & -\\frac{16}{9} & 0 & \\frac{11}{9} \\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "$\\begin{bmatrix}\n",
    "    1 & 0 & 1 & -\\frac{5}{44}\\\\\n",
    "    0 & 1 & 0 & -\\frac{1}{44}\\\\\n",
    "    0 & 0 & 0 & \\frac{117}{99}\\end{bmatrix}$\n",
    "\n",
    "$ --> $\n",
    "Max (| C3 |) = 0, no solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.3 实现 Gaussian Jordan 消元法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 实现 Gaussain Jordan 方法求解 Ax = b\n",
    "\n",
    "from fractions import Fraction\n",
    "\n",
    "\"\"\" Gaussian Jordan 方法求解 Ax = b.\n",
    "    参数\n",
    "        A: 方阵 \n",
    "        b: 列向量\n",
    "        decPts: 四舍五入位数，默认为4\n",
    "        epsilon: 判读是否为0的阈值，默认 1.0e-16\n",
    "        \n",
    "    返回列向量 x 使得 Ax = b \n",
    "    返回None，如果 A，b 高度不同\n",
    "    返回None，如果 A 为奇异矩阵\n",
    "\"\"\"\n",
    "def gj_Solve(A, b, decPts=4, epsilon=1.0e-16):\n",
    "    if len(A) != len(b) or len(A) < 1:\n",
    "        raise ValueError('Row count mis match.')\n",
    "    Ab = augmentMatrix(A, b) \n",
    "    #print Ab\n",
    "    num_col = len(Ab[0])\n",
    "\n",
    "    max_num = 0\n",
    "    row_index = 0\n",
    "    for i in range(num_col - 1):\n",
    "        # find the row which has the max absolute value of current column\n",
    "        for j in range(i, len(Ab)):\n",
    "            if abs(Ab[j][i]) > max_num:\n",
    "                max_num = abs(Ab[j][i])\n",
    "                row_index = j\n",
    "\n",
    "        if max_num <= epsilon:\n",
    "            return None\n",
    "\n",
    "        # swap the row with max number with current row\n",
    "        swapRows(Ab, i, row_index)\n",
    "        \n",
    "        # scale to 1\n",
    "        factor_fraction_str = '1/{}'.format(Ab[i][i])\n",
    "        factor = float(1.0 / Ab[i][i])\n",
    "        scaleRow(Ab, i, factor)\n",
    "        \n",
    "        # eliminate each value of other rows in current column to zero\n",
    "        for m in range(len(Ab)):\n",
    "            if m == i or abs(Ab[m][i]) <= epsilon:\n",
    "                continue\n",
    "            f = float(Ab[m][i]) / Ab[i][i] * -1\n",
    "            addScaledRow(Ab, m, i, f)\n",
    "        max_num = 0\n",
    "        row_index = i\n",
    "    last_column = transpose(Ab)[num_col - 1]\n",
    "\n",
    "    # format result\n",
    "    result = [[0] for i in last_column]\n",
    "    for i in range(len(last_column)):\n",
    "        result[i][0] = round(float(last_column[i]), decPts)\n",
    "    \n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 3.782s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "# 运行以下代码测试你的 gj_Solve 函数\n",
    "%run -i -e test.py LinearRegressionTestCase.test_gj_Solve"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## (选做) 2.4 算法正确判断了奇异矩阵：\n",
    "\n",
    "在算法的步骤3 中，如果发现某一列对角线和对角线以下所有元素都为0，那么则断定这个矩阵为奇异矩阵。\n",
    "\n",
    "我们用正式的语言描述这个命题，并证明为真。\n",
    "\n",
    "证明下面的命题：\n",
    "\n",
    "**如果方阵 A 可以被分为4个部分: ** \n",
    "\n",
    "$ A = \\begin{bmatrix}\n",
    "    I    & X \\\\\n",
    "    Z    & Y \\\\\n",
    "\\end{bmatrix} , \\text{其中 I 为单位矩阵，Z 为全0矩阵，Y 的第一列全0}$，\n",
    "\n",
    "**那么A为奇异矩阵。**\n",
    "\n",
    "提示：从多种角度都可以完成证明\n",
    "- 考虑矩阵 Y 和 矩阵 A 的秩\n",
    "- 考虑矩阵 Y 和 矩阵 A 的行列式\n",
    "- 考虑矩阵 A 的某一列是其他列的线性组合"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO 证明："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3 线性回归"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1 随机生成样本点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 不要修改这里！\n",
    "%matplotlib notebook\n",
    "from helper import *\n",
    "\n",
    "X,Y = generatePoints2D(seed)\n",
    "vs_scatter_2d(X, Y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2 拟合一条直线\n",
    "\n",
    "### 3.2.1 猜测一条直线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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lx2Qi/RKclE3KfNCAAEEEEAAAQQQQAABBMouQABY9gq6mT8BoBtHRrEXsA8A6884cED66Eel+8vbJMScBFy4MN7rwOZQ4/r10owZ9sid7ijSK8luV8ZoCCCAAAIIIIAAAggggAACdQECQPaCESAAZB/kJZA8AKzP2BylW1zeJiEmgNu+XVqzZuB0n+mAXP+Zw4zmlOCSJdKcOdIwT/+kFumV5Lw2Is9FAAEEEEAAAQQQQAABBEIWIAAMubrx1+YpVog/Aa6srED6ANDQBdIkpLkD8sSJ0tix2eyNorySnM1qeQoCCCCAAAIIIIAAAgggUC0BAsBq1bvdagkA2Qd5CbgJAOuzD6RJSF7FKMIryXmtnecigAACCCCAAAIIIIAAAiELEACGXN34ayMAjG/FlW4F3AaAZm5xm4Tceqs0cqTb1QQwWhFeSQ6AkSUggAACCCCAAAIIIIAAAoUSIAAsVDlymwwBYG70lX+w+wCwThqzSchLv/cO7dsnHTkijR4t9fRk99pt0auf5yvJRbdhfggggAACCCCAAAIIIIBAmQQIAMtULX9zJQD0Z8vInQX8BYD150Y0CXlw2NX6yInVOqBzT97R3X268cbcuf4ab7AxEEAAAQQQQAABBBBAAAEEEMhKgAAwK+liP4cAsNj1CXl2/gNAo1dvEnLHHdJrrw3xfF7jdLPu0D26QSfUdervU6dKGzZIM2aEXALWhgACCCCAAAIIIIAAAgggELoAAWDoFY63PgLAeE5c5V4gmwCwNu/Hv7RHunGRLj7+WMuVPKaLtUjrtEfTTv191Chp82apt1cyr8TyurD7TcCICCCAAAIIIIAAAggggAACfgUIAP36lmV0AsCyVCq8eWYWAJoOt7NnSy8fPa7rdJ9WaZnG64Uhoq9q+Mm/3aZb9YoGmoSceaZ0ySXStm1Sf//pW3hdOLwNyYoQQAABBBBAAAEEEEAAgRAFCABDrKr9mggA7c24w41AJgGg6Ww7fbq0Z8/pSZEz/lsAACAASURBVE/QAd2pj+pa3d9yJc9okpboLj2sd8RaKa8Lx2LiIgQQQAABBBBAAAEEEEAAgRwECABzQC/gIwkAC1iUikwpkwDw0UelefNai16urVqrxbpQz7S84AFdrY/o8/q5zoksSePrwpEXcwECCCCAAAIIIIAAAggggAACGQkQAGYEXfDHEAAWvEABTy+TAPCqq6RNm9ornqljukWfPtkIZITiNwlpNaIJAXfsoHFIwHuWpSGAAAIIIIAAAggggAACpRMgACxdybxMmADQCyuDxhDwHgCaxh1nnz34233t5jVFe7ROi3Sp4jcJaTXWtGnS7t3SMM//ZNGUJMYO4xIEEEAAAQQQQAABBBBAAAERALIJjIDnmAJkBNoKeA8A9+6VzPf54v6Gyb5JSKuxzWvHc+fGfWr868z3DE0zkjVrpC1baEoSX44rEUAAAQQQQAABBBBAAIHqChAAVrf2jSsnAGQf5CXgPQDctUuaNct+eWmbhJjXjjdutH9upztMJ+OFCwc3M2l3PU1J3NozGgIIIIAAAggggAACCCBQZgECwDJXz93cCQDdWTKSnYD3AND2BGDz9JM2Cenulg4dksaOtQMxV7d6tXfnTmn+fOno0fjj0ZQkvhVXIoAAAggggAACCCCAAAIhCxAAhlzd+GsjAIxvxZVuBbwHgDbfAGy3tKRNQkz4OHlyPLBOr/Z2dQ18T7C/P95YjVfRlMTejDsQQAABBBBAAAEEEEAAgdAECABDq2iy9RAAJnPjrvQC3gNAM8WoLsBxl2HbJMSc2ps5M3p0m1d7o0cbekVWTUmSzI17EEAAAQQQQAABBBBAAAEE/AsQAPo3LsMTCADLUKUw55hJAGgacsyb5wbQpknIk3tHRp4A3LrV/tXeJCvx1ZQkyVy4BwEEEEAAAQQQQAABBBBAIFsBAsBsvYv6NALAolYm/HllEgCa12unT4/XPCMueZwmIed+9S6NuvIdbYf8/velSy+VXnkl7lOTX+ejKUny2XAnAggggAACCCCAAAIIIIBAlgIEgFlqF/dZBIDFrU3oM8skADSv2JoA7Nln3XNGNQnR1VdLn/+8dM45gx5uwr9LLpF++Uv3c2o1YpqmJNnMkKcggAACCCCAAAIIIIAAAgj4EiAA9CVbrnEJAMtVr5Bm6z0AzOIV26gmIRo3TrrjDumGG6SuLpk5vfvd2Zz8a9wsNk1JQtpkrAUBBBBAAAEEEEAAAQQQqLoAAWDVd8DA+gkA2Qd5CXgNAM3Jv9mzpaNHs1leVJMQXXyx9v7ZOs28blpmc2pcedymJNlo8RQEEEAAAQQQQAABBBBAAIGsBAgAs5Iu9nMIAItdn5Bn5y0A9PHdvziFGH3WcX3/pvt0wbpl6n7phSG3vKrhWqVluk236hWNjDOks2s4AeiMkoEQQAABBBBAAAEEEEAAgVIJEACWqlzeJksA6I2WgSMEvAWALjv/xq3imWdKb3mL9N3vSr/ef0B36qO6Vve3vP0ZTdJirdVWXRF3+FTXDR8uHTwojR2bahhuRgABBBBAAAEEEEAAAQQQKKEAAWAJi+ZhygSAHlAZMpaAtwDQNP3YtCnWHJxcdMYZrRt6RDUJuV8LtFSr9XMNbhLiZFINg4TeBfill6R9+6QjR6TRo6WeHsJO13uI8RBAAAEEEEAAAQQQQKC8AgSA5a2dy5kTALrUZCwbAS8BoAmDzj5b6u+3mUqya7u6JHO67le/an+/aRKyQrdruVZqhF4bcuHzGqebdYfu0Q06oa5kE4m4y5yInDvXy9BeBo0T6JnXvLdtk9askbZsGVxv0/V4/nxpyZKBdQ/jf8t5qRODIoAAAggggAACCCCAQDkECADLUSffs+S/GvsWZvx2Al4CQPOtu6lTi4ce1STkMV2sRVqnPZrmdPLTpkm7dxc/BLMJ9P7pn6SFC6U9e6KpzF7YsEGaMSP6Wq5AAAEEEEAAAQQQQAABBEIUIAAMsar2ayIAtDfjDjcCXgLAXbukWbPcTND1KMN0XNfpvpONQMbLf5OQUaOkHTuKH36Zjs1xA73zzpN+/nPp2LH41TEOmzdLvb3x7+FKBBBAAAEEEEAAAQQQQCAUAQLAUCqZbh0EgOn8uDu5gJcAsKgnABuZJsh/k5CRI6WHHip+6LV168DrukePJt9Ice4sSxgaZy1cgwACCCCAAAIIIIAAAgjYCBAA2miFey0BYLi1LfrKvASAWX4DMC2wzyYh69cPnKor8s+c/Js923/4Vzcoy+vQRa4Zc0MAAQQQQAABBBBAAIHyCRAAlq9mPmZMAOhDlTHjCHgJAM2Ds+4CHGex7a7x1STEnIScPDnNzPzea775N316vO/4uZxJ2RqiuFw7YyGAAAIIIIAAAggggEA1BQgAq1n35lUTALIP8hLwFgCakGfevLyWley5LpuEmM7EBw9KY8cmm0sWd+VVIxMOb9yYxQp5BgIIIIAAAggggAACCCBQDAECwGLUIe9ZEADmXYHqPt9bAJjX6bK0pTRNQq7XvVqp5amahJQh5MrrlGZ3t3ToULHD0bT7iPsRQAABBBBAAAEEEEAAgUYBAkD2gxEgAGQf5CXgLQA0C8r6+3IuEdM2CSn6a655f6ex6K9Hu9xLjIUAAggggAACCCCAAAIIEACyBwgA2QN5CngNAM3Csuow6wsxSZOQMjS6yLtT886d0syZvqrGuAgggAACCCCAAAIIIIBAsQQIAItVj7xmwwnAvOR5rvcA0BCbk4CmG+6ePeUEj9MkZLlW6l5dr7NGdWnHDmnGjGKvddcuadas/ObICcD87HkyAggggAACCCCAAAIIZC9AAJi9eRGfSABYxKpUY06ZBICG0nwTcPt2ac0aafNmqb+/GMAjRkivvhpvLlFNQh7vukS6e50u/uOp8QbM8ao8TwCWoUFKjqXh0QgggAACCCCAAAIIIBCgAAFggEVNsCQCwARo3OJEILMAsHG25vtz+/dLf/In0iOPOFlHokHOOEP65S/tbo1qEiKTbi1bJt16qzRypN3gGV6d5zcAy9AgJcNS8CgEEEAAAQQQQAABBBCogAABYAWKHGOJBIAxkLjEi4CXANCES/v2SUeOSKNHSz09rTu+mkYZ8+Z5WVfkoGeeKb3ySuRlbS8wTUJWa6mu0QOtr5k0SVq7VrriiuQP8XxnXl2Ai94gxTM7wyOAAAIIIIAAAggggEAFBQgAK1j0FksmACzfPpggybQwMP96a+1fv15bxnpJH0qwJDOWue9tkiZK6pJ0QNIPJX1b0l9J+kWCcTvd4iwANK/4bts28Irvli2DX/Ht7pbmz5eWLJHmzpWG1Xa8uWf69Oy/DWgO5r3lLdJ3vpNe87bLHtaK/YulZ59tPdiCBdLq1dI556R/mOMR8ghgy9AgxTEzwyGAAAIIIIAAAggggAACIgBkExgBAsDy7YMTHaZsGwCeIem/S7o+Yi/Ml7TFMVXbADDuKT4zH5smH1OnShs2nG6SYe6dPVs6etTxyjoMZ07//epX0vHj6Z9pws1D+49p7F/cLq1cKb322tBBx40b+Nv110tdJtctxi/rAHbUKJWiQUoxqsMsEEAAAQQQQAABBBBAICQBAsCQqpl8LQSAye3yurMxAOyT9LSk+rueNgHg62qh3jtrCzFn0jbUxjNJ0nmS/rWkqyQt9x0ATpzYY32Kb+vWgdN9NgGeCYJMI5De3oFVmzHe8x7p2LG8ypnuuac62po2x4sWSY891nrASy6R1q2TTApakF9WAWxzzQuyfKaBAAIIIIAAAggggAACCGQiQACYCXPhH0IAWPgSDZngn0t6ovYv85ru+ZKeq11lEwB+StKttfs+JunODhQjJMXsVxsb9NQJwL//+z4tW9Yjk2FF/eqn+Mx1SU/vNZ8G27FDmjMn6snF/PvOndJM8wK3+ZljhffeKy1fLr3wwtAJmyYh5m8rVhSmSUiSENecojRvNf/kJ9E1Ma/9rl9/+tRn9B1cgQACCCCAAAIIIIAAAgiEJUAAGFY9k66GADCpXHHuSxIATqp9388Ee1+W9Ec5LOdUADhyZJ+OHTP/Md7vrLOk3/zNeAFQuxGbvwf3/vdLX/1qvOcX6apTJwAbJ3XggLR0qfRAOZqE2LzGfeGFAxnnZZdJ27cPfPfRnOjs7z8NYHLO+ncfTbBb/+5jkerGXBBAAAEEEEAAAQQQQACBrAQIALOSLvZzCACLXZ84s0sSAH5W0s2SzOvEFzScIIzzPFfXnAoAJfMmc/wA0NUEGjvC5tGUIu06TNB18GDrLscnx374YWlxOZqEmG8Ctgv0mp2aG7scPizt3y+Zfx8zRpo4sYNJWnTuRwABBBBAAAEEEEAAAQRKJkAAWLKCeZouAaAn2AyHTRIAPiPJnAI0rxLXXyA1HSL+lSRzKvBnknx/FS/3APCqq6SNGwcqlXVTChf7o3H+bcczHze8vVxNQswr2aZnyY9+FK3U3Ngl+g6uQAABBBBAAAEEEEAAAQSqJUAAWK16t1stAWD594FtAPibkn5eW/Zf1L4DaL4HuFDS+Nr/3DQBeVzSSkn/0xNR7gHgyS66hwZWt2+f9L3vSTfeWJ6GII0nGCNr5LlJiE3n5k5zTfJNQJp8RFafCxBAAAEEEEAAAQQQQKDCAgSAFS5+w9IJAMu/D2wDQNPuYltt2XdIen/tNeB2Ep+XtDQBU9Q7vefWTiAqr1eAzZpMN+BHHhn8DbkEa838luZvGMaagOMmIebU5LZtA9/h27JlsGHza7pxvsOXpitwc2OXWB5chAACCCCAAAIIIIAAAghUQIAAsAJFjrFEAsAYSAW/xDYAnC/pa7U1/VLSGbXTfp+oBXJnSnqnpM9Jen3tusWS7rZ0MN8XjPnL5xuAMSdXyMtM6LZkScKpRTQJOX7+JHWtWytdcUXbB9g07ojzmq6LV7AThaIJCbkNAQQQQAABBBBAAAEEECiLAAFgWSrld54EgH59sxjdNgC8VtJfNUzs+5IulfRK02R/W9I/SRol6ReSzrP8LiABYET1u7okcygvyS/tiTcTuP3zqod17qcW69yjz7acws/evkDn/PVqDTv3nEF/9/GarqsmLFavRSeB5x4EEEAAAQQQQAABBBBAoGQCBIAlK5in6RIAeoLNcFjbANC88vu3DfP7fyT9Q5v5rpL0sdrf3i3pGxbrKsUrwHHXM3KkdPfd0lvfKn3iE9JDD8W9s/11Y8dK5tt5SX9JT7w1nt47U8e0QrdruVZqhMynHwf/Xuwapxc+sVLnfep6qatLvl7TNQ1NNm1KKnH6vliNUdI/hhEQQAABBBBAAAEEEEAAgdIIEACWplReJ0oA6JU3k8FtA8B3SPpmbWa/kjRGkvn3Vr/LJW2t/eE2Sf/J4YpybwJiu5Z64Ga+ezdvnu3dfq63PfHW7vTeFO3ROi3SpXqs5USfn3qJxn1lnaZ/YKpMP5Gkv1ahpQlBzz7bzXcY641dTLjKDwEEEEAAAQQQQAABBBBAwDS93Kc3vOENdQrz/9iHS/UECADLX3PbAHCKpHqEYz6+98YOBL8r6Ye1v6+TdKNDrtIFgGbtJnCbM0eaPl2pgrC0p//qdbA58RZ1em+Yjut63auVWq7xemFIqfu7huuzx5frdq3QKxqZeCs0h5Z790rmO4Gufma8yZPTj+aqs3H6mTACAggggAACCCCAAAIIIJBcgAAwuV1IdxIAlr+atgHgCElHJZl//z+SJnYgaAwL10j6E4dcpQwA64FbVJjWycl8v+/YseTf/2scO+6JN5smGxN0QKu1VNfogZbLeEaTtFhrtVXtm4R0Wn9zaLlrlzRrlrudtXOnNHNmsvFcdzZONgvuQgABBBBAAAEEEEAAAQTcCRAAurMs80gEgGWu3sDcbQNAc892SbMl9Uv6tVog2EriXZK+XvvDJyV9xiFXKQPAxsAtaTOML3xB+uM/dicZ58RbkiYbvXpYa7VYF6h1k5D7tUBLtVo/1+AmIVEraw4ti3IC0HVn4ygH/o4AAggggAACCCCAAAIIZCFAAJiFcvGfQQBY/BpFzTBJAPinkv5bbeBrpDZHvaS/lPSh2nWXSfrHqMlY/L2UAaBZX2PgZhMame/frV8vvfZa9ifekjbZiGoS8rzGnWwgcq+u1wl1xS5/o6HLbwAOHy4dPCjZfgMwaZi7ebPU2xt72VyIAAIIIIAAAggggAACCGQuQACYOXkhH0gAWMiyWE0qSQA4WtIzkiZI+okk8wLmgaanzpX0LUndkp6S9GZJJ6xm1vni0gaADz4oTZokjR4t9fRIY8ZI27dLa9ZIJhDqN+cqaz8TSM2fLy1ZMvDtwGHDBgLELL955yJgi2oS8o+6RIu0TnsV72N+za/pJg0om7eYzTcR6/emfZ17xw5pxgyH/2Q0DMV3CP24MioCCCCAAAIIIIAAAlUSIACsUrXbr5UAsHz74FJJFzZM+zckrar9Z9PC9Z6mJX25zRL/vaQHJZk9YJqBfFbSLklnSnqnpI9IJzs9vCbJhIGt28Mm9yttANi4ZPM6az3gmztXOnxY2r9/4N9NMDhx4tDTaC4CucaAMerEm6vAMapJyKsafrKBSJwmIc2vLSd5RbnV1rPtimzzbcR2W/23f1t64gnp18zL9A5+fIfQASJDIIAAAggggAACCCCAwCkBAkA2gxEgACzfPjCB3gctpt2pxjdJWi3pdW3GOyLpWkkPWTwv7qVBBICNizWn+jZsiHcaLMsTb66bbKRtEtLqNV0XQZx5xXr37oFTlnF/roLHri7pyisHTnqaINhmDo1ztXml3Ga/xfXgOgQQQAABBBBAAAEEEAhPgAAwvJomWZHFf1VOMjz3eBBwGQCa6Zl3Nk0QaL5kZjoCmxdYTdeHb0r6gqSfeliDGTK4ANAsynT4jfNdOFfBU5wTb65OADbvg6RNQtq9ppvHq7iugtikQXDjfXyH0NP/pmFYBBBAAAEEEEAAAQQqLkAAWPENUFs+ASD7IC+BIAPAeggY9V24LE+8uXzluHmzJGkS0im0zDIE8+kSNwiue+YRfub1Dz7PRQABBBBAAAEEEEAAgWwFCACz9S7q0wgAi1qZ8OcVbABoShfnddQsQx9XJ91Md10TnDX/4jYJ6Zo2NfI13e9/X3r/+6Uf/zj6H4J6Z+UkTTh8nYysz9qEgFFBsLk2yzA4WpQrEEAAAQQQQAABBBBAIDQBAsDQKppsPQSAydy4K71A0AGg4Ynzem5WJ95cvXK8bp20dKl09OjQDRCnScjB65br3P++Qhpp+ssM/dl8A+/886VNm6SLLkq2GV1/G7HVLOIEwa5qE2e/JZPiLgQQQAABBBBAAAEEECizAAFgmavnbu4EgO4sGclOIJcA0HTtPeMM6eWX7Sab5Op237prHssm9Ep64s3lKbNvfWug83GrENCsLapJiCZNku6+W+o1n508/csqDK0/0fcJwPpzooI5V6cz4+63JHuZexBAAAEEEEAAAQQQQKC8AgSA5a2dy5kTALrUZCwbgdgBoHmV0rzi+Z3v2Azf+loTknz849LChdKePenH6zSCCRsPHZLMa7NRPxPQbd8urVkz0ESk37Riqf1M11wTuJkOs3PmpOswO3t2++Cu0xybX2eNE1pGNQnRggXS6tXSOecoy9eh6+v0+Q3ARstOwZzLOdjst6j9yN8RQAABBBBAAAEEEEAgHAECwHBqmWYlBIBp9Lg3jUCsALB+4u3FF6V589I8buDe+mmsToFb+qecHsGcMps82W5EEwrt3y8dPiyNGSNNnBgvRIzzFJen7OKEln9y/TFdtv12DVu1UnrttaFTHDdOJ+5YqTf/t+v11N6uOEtoeU2cV21b3ejq9F2niXcK5lyfQkyy3xKjcyMCCCCAAAIIIIAAAgiUQoAAsBRl8j5JAkDvxDygjcCpALCrq0/Hj5v/OPBrdeLN5Susw5p2fWPg9txz0gc+4K5mO3dKM2e6G8/FSHFO79WfE/eV48jQ0hy3XLRIeuyxlkv4R12iRVqnvZqaeIlRr9o2D2wc3ve+eM1GEk+qdmO7YM71dwiLuN/S2nE/AggggAACCCCAAAIIpBMgAEznF8rdBIChVLJ86zgVAO7d2yepp+2JNxP+bdsm3X679MgjyRbariOrCa727ZOOHJFGjx7491mzkj2j1V1FPZEV5/Re2leOh3gcPy7de6+0fLn0wgtD/vyqhmullut2rdArat0kpFNlbL6Bl+QkZJpd0S6Y4wRgGlXuRQABBBBAAAEEEEAAgTgCBIBxlMK/hgAw/BoXdYWnAsC+vj719Jw+Adg4YZvTau0WasI/8129es+JeqBovre3Zcvg7+2Z1zUbv7+XBs+cZDx40N3ru2nm0uneyNN7rh984MBAK+EHHmg58jOapBt1t76lwU1CoqYR9xt4ab43GDWHdn9vFwS7/AZgWfZbUkPuQwABBBBAAAEEEEAAgWQCBIDJ3EK7iwAwtIqWZz2RAaCLU1rNr7C6CBTjEtucSIs7ZkjXff8zD2v8LYs16cSzLZd1vxZoqVbr5zon9rKjTly6eJU89mRqF0YFc66+Q8h+s60M1yOAAAIIIIAAAgggUA0BAsBq1DlqlQSAUUL83ZdAxwAw7Smtyy+XbrllcNdcF4GiDYbtN+lsxi77tfX69h89phW6Xcu1UiM0tEnI8xp38m/36nqdUHSTkKhv4JmauGgmY+MfFcy5mhP7zaYqXIsAAggggAACCCCAQHUECACrU+tOKyUAZB/kJdA2AHRxSqu5K2zaQNEWKWlXWtvnlPH6VvWdoj36H/qPukSPt1xS3CYhUScAXZ22s3GPCuZ87Heb+XEtAggggAACCCCAAAIIhC1AABh2feOujgAwrhTXuRZoGwC6PhHlImCxWXy7hiM2Y5Th2uYGKuYzjmPHRs+8XX2H6biu170nG4GMl32TkKhXbV1+by96lQNXxA2C0wTUVdlvcc25DgEEEEAAAQQQQAABBAYLEACyI4wAASD7IC+BtgGgq1Na9VcvXQWKcaCaG47EuadM10Q1UJk/XzLdg+fOlYa1+d8uUfWdoANaraW6RnZNQqJetXXdcTeqbrbBXJJX1EPfb1HG/B0BBBBAAAEEEEAAAQSiBQgAo42qcAUBYBWqXMw1tgwAXZ7SqneFvf56adMm/wjNDUf8PzHbJ9g0UJk6VdqwQZoxY/Acberbq4e1Vot1geI1CYl61XbXLmnWrOzMPvMZ6eMft3uejXHo+81OjqsRQAABBBBAAAEEEECgnQABIHvDCBAAsg/yEjgVAH772316y1t6NGaM9OUvS9dd525KJvT5vd+T+vvTj2lOtJl/HT9+eizz2mn91NucOe1PvaV/er4juDqdZnsK70zFaxKybdL1+pcfdbU9dWj0bJ+dVtz2BGD9eeaU5fbt0po10ubNg/duVfZbWnvuRwABBBBAAAEEEEAAgdMCBIDsBgJA9kCeAqcCQKlP3d09MoGJOSHm8vfgg9LVV7sb0QSKo0dLhw/rZGA5cWK87965m0H2I7n8Pl3SU3hRTUK+d+YluuiJdRo2bWpbIJvTh66U434DsN3zzJz376/WfnNlzzgIIIAAAggggAACCCAwIEAAyE4gAGQP5CkwKACUzH90//vKV6QPfMDduDt3SjNnuhuv6CO5aKDSGIKlOYUX1STkePdwdd28XFqxQho5siVt1PcHfdQj6tVkH89kTAQQQAABBBBAAAEEEECgLkAAyF4gAGQP5CngPQA0r0s+9pjb776ZAGvy5DzZsn22qwYq9RDMxSm8qCYhuuACae1aqbd3CJar9dhUIao5ic1YXIsAAggggAACCCCAAAII2AoQANqKhXk93wAMs65lWJX3ANAEL/fcI40fP/i7fUlxTKB48GD4r/w2+rg6MdcYgrkaM6pJiBYskFavls4559SSXJxotN0/9WY0Y8fa3sn1CCCAAAIIIIAAAggggEB6AQLA9IYhjEAAGEIVy7kG7wGgOe1lQpe3vc3NtwWrdpLLxWm9+tZsDMFcnsKLahKiceOklSsl0wq6q+vkdNJ80zDpP2pVOzma1In7EEAAAQQQQAABBBBAwL0AAaB70zKOSABYxqqFMWevAaD57tydd0pXXikdPeoGrGrfckvzvb5W4vUQ7MUXpYsukp55xk1dzChRTUJ0ySXSunXS1IEmIUm6GqeZbdW+HZnGinsRQAABBBBAAAEEEEDArQABoFvPso5GAFjWypV/3t4CQNNN2GQ9ixa5C//SdnMtY7mSduxtt9Y1a6RHHpG2bJH6+92LmCYh+//8Xr3+88ulF14Y+gDzDvfy001CzEnAhQulPXvcz6V5RE4A+jfmCQgggAACCCCAAAIIINBagACQnWEECADZB3kJeAkATfj3ta9JS5e6C3bMmDt2SDNm5EWVz3NdnwD0vYpT32g8dmBgAzzwQOtHNjQJMd8E3L5dMuHk5s1+gskqfjvSd60ZHwEEEEAAAQQQQAABBOILEADGtwr5SgLAkKtb7LU5DwDNKb316yXzium8eW4Wf+aZ0kMPSVdc4Wa8Mo3i8huAWax7yDcaH35YWrxYevbZ1o9vahJi1rt/v3T4sDRmjPSJTwzUPu2vat+OTOvF/QgggAACCCCAAAIIIOBWgADQrWdZRyMALGvlyj9vpwHgl7888DrnsGGSqy6zdWLz2bgNG6p3AtCs37Wlz23b8huNx45Jt90mrVolvfba0Me3aBJSv8hVs5KqfTvSZ40ZGwEEEEAAAQQQQAABBOwFCADtzUK8gwAwxKqWY03OAsDGVyx9nVozrwGbV0R7e8uB62qWrkIwV/NpN07kNxqfemrgo5CPP956iKYmIeYi83rw9OnpXiWPnJdvGMZHAAEEEEAAAQQQQACBygsQAFZ+C5wEIABkH+Ql4CwAbHzF0ud366r4LUAXIZjvDRa7LsePS/feO9AIJEaTEDNv0yhk9uxkzWRiz8s3JLh6cQAAIABJREFUEOMjgAACCCCAAAIIIIBApQUIACtd/lOLJwBkH+Ql4CwAbHzF0nXn2macKp7oShOC+d5c5huNX/yi9OY3S6NHSz090tixEU89EL9JiBlp61Zp/ny7ENCEf1/4guW8fGMxPgIIIIAAAggggAACCFRSgACwkmUfsmgCQPZBXgJOAsDmQM7nCcA6VBW/6ZYkBMtjY3V3D4R1S5ZIc+cOfBOy7S9Ok5DPf16aMOHkSUDzjck9e6JXZQLII0ckc+Cw/rOaV/QjuAIBBBBAAAEEEEAAAQQQiC1AABibKugLCQCDLm+hF5c6AGz1iqWvbwA2Sla1q6tNCFaEnRereUtUk5Dx46WVK6XrrtOJYV3avl1as2bge5D9/YMDPrMfzf6L+sWaV9Qg/B0BBBBAAAEEEEAAAQQQiClAABgTKvDLCAADL3CBl5cqAOzUlMN351pzmuvQoRivmhYYP+nUzDcB24VgphmLOX33trcNnMArwi928xbLJiEm6Nu/Xzp8WPrBD6Q//VPp5Zfjrzj2vOIPyZUIIIAAAggggAACCCCAQEsBAkA2hhEgAGQf5CWQOAA0r/2uXy/NmNF66ll0rjWvGk+enBddMZ7bGIKNGSNNnDgQimbxGraNQOxmHOad3XvukW6+mSYhNsBciwACCCCAAAIIIIAAAoUWIAAsdHkymxwBYGbUPKhJoG0A2OobavXTZeZk2Zw5nb/tlkXn2p07pZkzqWkrgSxew7aVt2re8rOfSUuXSg8+2PoxF1wgrV2rE5f3avr0eN8FbDdfq3nZLprrEUAAAQQQQAABBBBAAAFJBIBsAyNAAMg+yEtgUAA4fHjPqeYNJuAzr1bWX7FsPF0Wd7K+O9dyArBzJXy/hh13HzReZ9u85ejmhzXizxbrdX3Ptnzcz96+QG/+9uf1C01IMp1T99jOK9XDuPnkdxr37Rto1BK7czRuCCCAAAIIIIAAAgiUWIAAsMTFczh1AkCHmAxlJXAqAHzkkT5ddFHPyddHXf58da41pxEPHqzmNwDj1ieL17DjzqV+XZzmLeb06LZtA40+tmyRRvQf0626Tcu0SiP02pBHHtJ4LddK3afrdEJdtlM6eX2ceSUamJtOCTTXtbmBS+zO0ZgigAACCCCAAAIIIFBCAQLAEhbNw5QJAD2gMmQsgVMBYF9fn3p6zH90//PRuZbAJrpOWbyGHT2LwVdENW/ptFem6imt0yJdosdbPvY7ulSLtE5Pa4rttBQ1L+sBuWGQgM3/DqBDM5sHAQQQQAABBBBAIEQBAsAQq2q/JgJAezPucCOQSQBoplrvXPuf/7O0Y0f6yfPKZjxD369hx5vF4Kvavbod57ToMB3XDbpHd+hmjdcLQx7/K43QSi3Xp3WLXtFIq+nxSrkVV+yL49S1eTA6NMfm5UIEEEAAAQQQQACBkggQAJakUJ6nSQDoGZjh2wpkFgDWZ2CCwClTpB/+MHlVaNpgZ5ckgLF7gt3VrZq32AaV5+hnWq2lWqDWTUJ+pAu0WGv1LfXGnhxNZWJTxb7Qtq6NA8fuHB17NlyIAAIIIIAAAggggEB+AgSA+dkX6ckEgEWqRrXmknkAaHgJBbLfZDavYPqeXfNJuzSvKl+hf9BaLdYkPddy2vdrgT6ieE1COAHotvJp6lqfCWG/25owGgIIIIAAAggggEB+AgSA+dkX6ckEgEWqRrXmkksAaIiTnErjtcB0m7P+GrZprrF5s9TYhCHdyPHvbtW8JW2zkpF6WSt0e6omITSViV/DuFemrWv9ObzuH1ec6xBAAAEEEEAAAQSKLEAAWOTqZDc3AsDsrHnSYIHcAkAzDZtTaeYk0Pr10owZlNCFwEsvSfv3S4cPS2PGDLySvWCB9MorLkZvP0ar5i3mf7ZpU/rnpmkSQlOZ9P7NI7iqK7VxXxtGRAABBBBAAAEEEMhegAAwe/MiPpEAsIhVqcaccg0ADXGnU2nmVNb8+dKSJdKcOdIw/knxuittAtmkE2k+zWWCyLPPdncaMWmTEE6ZJa1o6/tc1pUOzW5rw2gIIIAAAggggAAC+QgQAObjXrSnEmsUrSLVmU/uAWAjdfOptIkTpbFjq1OMIqzU52vCrb7nZr67N3Wq+5XbNAnhO3Pu/V3Xle8zuq8RIyKAAAIIIIAAAghkK0AAmK13UZ9GAFjUyoQ/r0IFgOFzl2uFzYHsL34h/f7vS0eP2q+jXUfXXbukWbPsx4t7R1STkK90X6Mp31ytN18+Ie6QXBdDwHVd6dAcA51LEEAAAQQQQAABBAotQABY6PJkNjkCwMyoeVCTAAEgW8JKwHXzFtcnxVotJqpJiMaPl1aulK67TurqsvLg4tYCruvKCUB2GgIIIIAAAggggEDZBQgAy15BN/MnAHTjyCj2AgSA9maVv8PmW4FRzVtcfyvud35Hevrp1iWKahKiSy+V1q2TpkypfI3TArisKx2a01aD+xFAAAEEEEAAAQSKIEAAWIQq5D8HAsD8a1DVGRAAVrXyKdftsnmLy26xf/M30vbt0po10ubNg5uLmCDpyvce16feeI9+576bNeyFF4YqjBghLV8u3XKLNHJkSqVq3+6yrhs3VtuS1SOAAAIIIIAAAgiUX4AAsPw1dLECAkAXioyRRIAAMIka9wwSSNu8xXTgnTcvPWqrDsP790uHD0tjxkiDmsr87GfS0qXSgw+2fvAFF0hr10q9veknVtERfNW1opwsGwEEEEAAAQQQQKDkAgSAJS+go+kTADqCZBhrAQJAazJucC1gThNOny7t2ZN85MSdfP/hH6TFi6Xnnmv98GuukVavlibQJMS2OrnW1XayXI8AAggggAACCCCAgGcBAkDPwCUZngCwJIUKcJoEgAEWtYxLMt8VnD3bbYfh2A4vvyzdfru0apX02mtDb6tIkxBzknPfPunIEWn0aKmnRxo7NrZiywtzrWu6qXM3AggggAACCCCAAAJOBQgAnXKWdjACwNKWrvQTJwAsfQnDWYDrDsPWMk89JS1aJD3+eOtbA2wSYk7pbds28M3ELVsGfzOxu1uaP19askSaO1calvD/UuVeV+uNwA0IIIAAAggggAACCLgXIAB0b1rGERP+16oyLpU5F0yAALBgBan6dFx2GE5kefy4dM890s03S4E3CbGxnjpV2rBBmjEjkapsnhXVOTrZDLgLAQQQQAABBBBAAIF8BQgA8/UvytMJAItSierNgwCwejX3tmJXr5C67DCceLGBNwnJ41ReIeqaeENwIwIIIIAAAggggAAC6QQIANP5hXI3AWAolSzfOggAy1ezQs3Y9yukaTsMp8YKsElIEb7Ll3tdU28MBkAAAQQQQAABBBBAwE6AANDOK9SrCQBDrWzx10UAWPwaFXaGNq91pn2FNFeEgJqE0Jk3153EwxFAAAEEEEAAAQQqLEAAWOHiNyydAJB9kJcAAWBe8iV/bh6vkOZOFkCTkEcflebNSy9pxjGNQfghgAACCCCAAAIIIIBAPAECwHhOoV9FABh6hYu7PgLA4tamsDMrwiukueGUvEnIVVdJmzal1zPjbNyYfpysR3D1ncqs583zEEAAAQQQQAABBMovQABY/hq6WAEBoAtFxkgiQACYRK1k97gMPXiFtFb8EjQJaa772LHS+edL/f3pN3B3t3TokGTGLPrP93cqi75+5ocAAggggAACCCBQDAECwGLUIe9ZEADmXYHqPp8AMNDa+wo9eIW0acMUrElIVN1dhH91gb17pcmTi/0PUGW+U1nsMjA7BBBAAAEEEEAAAUkEgGwDI0AAyD7IS4AAMC95j8/1GXpU/RXSlmUrSJMQm7q72H47d0ozZ7oYyc8YlfxOpR9KRkUAAQQQQAABBBBwIEAA6AAxgCEIAAMoYkmXQABY0sK1m7bP0MO8Unr22dV7hTT2FsmxSUiSusdeV5sLi3wCsNLfqUxbWO5HAAEEEEAAAQQQ8CJAAOiFtXSDEgCWrmSaIMmcfTH/emvtX79eW8Z6SR9KsaSzJD0l6bdqY/xE0vkpxut0KwGgJ9g8hvUdepjAZ+pUdysrcoCUeJU5NAlJU/ek6xw+XDp4sJjfAOQ7lUmryn0IIIAAAggggAACPgUIAH3qlmdsAsDy1Ko+0xMdppw2APycpI82jE8AWL79kfmMswg9du2SZs1yt7Siv0KaaqUZNQlxUfck6yxyF2C+U5mkotyDAAIIIIAAAggg4FuAANC3cDnGJwAsR50aZ9kYAPZJelrSFbUL0gSA/1bSE5Jerf1rjCQCwPLtj8xnnEXowQnABGX13CTEVd1tV2aeO3eu7V3ZXM93KrNx5ikIIIAAAggggAACdgIEgHZeoV5NAFi+yv55LagzYd2B2iu6z6UMALsl7ZR0kaT/JOl6SecRAJZvc+Qx4yxCD5ffACzyK6TO6+exSYirutusedo0afduaVgB/y+Xyz3a3S0dOlTM15xt6sW1CCCAAAIIIIAAAsUQIAAsRh3ynkUB/2tU3iSle775Rl/aAHCppDsl/S9Jb5b0LwSApdsHuUw4y9DDVeBU5FdIvRXRcZMQl3WPu+ZRo6QdO6QZM9rfYea1b5905Ig0erTU05NdiMYp1biV5DoEEEAAAQQQQACBrAUIALMWL+bzCACLWRebWaUNAM1Jvz2SRkmaJ+lRST8mALQpQXWvzTL0cPXKaZFfIfW6kxw2CXFd96h1m/Bv82apt3foleZbhNu2SWvWSFu2DO4UbU7SzZ8vLVky8Nqwz5ODfKcyqor8HQEEEEAAAQQQQCAvAQLAvOSL9VwCwGLVI8ls0gaA/1PS70v6K0kLaxMgAExSiQrek2Xo4aLpRJFfIc1s+zhoEuK67p3Wbmq2fn3rk3+mC/HChdIe8/+FEfEzXaQ3bOh8gjBqjE5/dx2KBtmpOg0w9yKAAAIIIIAAAggkFiAATEwX1I0EgOUvZ5oA8AOSHpT0vKQ3Sfo5AWD5N0SWK8g69DCBz+zZ0tGj9quM8wqp/aglviNFkxDXde/qkswBxfrPfKexfnJvzpzWJ/e2bh24xmYvdDpJmLaSLl+LrtR3KtPCcz8CCCCAAAIIIIBApAABYCRRJS4gACx/mZMGgONrHYTPkbRI0v9ooHBxArAngvbcWjMT9fX1qcd8rItf6QTyCD2KFvyUrmiNE07YJMR13Z97Tjp8eOBfY8ZIEyd2/nZfUYNgvlNZ6n8amDwCCCCAAAIIIBCsAAFgsKW1WhgBoBVXIS9OGgDeU+v2+11Jl0g64TgAbByvIxwBYCH3VexJ5RF62Lz62ekV0tiLDP3CBE1C8qi7KUORXwXnO5Wh/4PC+hBAAAEEEEAAgXIKEACWs26uZ00A6Fo0+/GSBICzJW2T1C/pIkm7m6bt4gQgAWD2eyGXJ+YVepggaPv2geYPpkFEv9nNtV+7V0jz7BKbS3FsHlpvErJ8ufTii0PvHDFCMn+75RZp5EjlVfe8nhuHssjhZJz5cw0CCCCAAAIIIIBAmAIEgGHW1XZVBIC2YsW73jYAPEPSP0v6XUl3SvpYiyW5CACj3unlFeDi7aVEMypC6GGCvf37W79CWpQusYlw87gpZpOQE5f3avr0eA042i0jSVOWvE4exi1FUV9Pjjt/rkMAAQQQQAABBBAIT4AAMLyaJlkRAWAStWLdYxsAfkrSrZL6JE2RdMRTABilZAJCMwe+ARgl1fT3Ip5iK2roYfOqsO8usZZlzv/yGE1Cdn9otS5+7wSrRhz1hSVpyuLy24Pd3dKhQ52/NZi0CHynMqkc9yGAAAIIIIAAAgj4ECAA9KFavjEJAMtXs+YZ2waAv5T0Okl/KenhNsv/oqTfkPT/S/pw7RrTIfgRh1wEgBaYZTjFVrTQo2jzsSh3cS6N0SRk74dWata663Tk5a7Y807ajdd192Ez3uTJsadtdaEJn6+9Vnr66ejb+E5ltBFXIIAAAggggAACCCQXIABMbhfSnQSA5a+mbQAY+9t8TTTbJc11yEUAGBOzTKfYbObqM/Qo6onEmCUfdFkhTnxGNAk58m8u1YLD6/SNZ8yh4s6/NHXftUuaNSvqCfH/vnOnNHNm/OvjXNkY1ptvU5pPK7b6tftOZZxncA0CCCCAAAIIIIAAAjYCBIA2WuFeSwBY/toSAJa/hm1XUMZTbEmac7gsYRG+SZh2PYU88RnRJOTEiBH63/9+uT559Bb9zddHxmrKYutU9BOANgH4m94k3X+/NGOGrQLXI4AAAggggAACCCBgJ0AAaOcV6tUEgOWvrG0AGGfFLpqARD2HE4ARQiGcYuvUnCNqgyT9e5G7xMZZk02IlMt3C2M0CTn6ubX637/bq8OHpTFjpIkT3Xxrz+U3AE0tzAm99743TlWiryljWB+9Kq5AAAEEEEAAAQQQCEGAADCEKqZfAwFgesO8RyAAzLsCHp4fwik2Dyyxhix6l9hOiyhViBSjSYhWr5YmTIhVt7gXuaqveV6SRiSt5hlCWB/Xn+sQQAABBBBAAAEEyidAAFi+mvmYMQGgD1W/Y14q6cKGR5hmHatq//kxSfc0Pf7LCabDCcAEaC5uqX/vbds26aab0o9oTsPNdfnlxvRT8jqCyxNiPrvEBhMixWgSopUrpeuuk7riNwnptElcnfCsP8N8k3D3bmlYwv9rSFjv9R9pBkcAAQQQQAABBBBwIEAA6AAxgCES/leeAFZe3iWYQO+DFtNPUmMCQAvgtJd2+t5b2rHNaamNG9OOUp77i/6NuHaSpQ+RIpqE6NJLpXXrpCnRTUKidpsLq+ZnpAnKXQWSaeYQZcbfEUAAAQQQQAABBKotQABY7frXV58kHEIuXwECwHz9nT7d5ntvSR6c9Sm2JHN0eU8ZusS2Wm9ZQqSOHYkjmoRoxAhp+XLpllukkSNTlT3NK7etHpwmKHf1SnLcORSiK3Sq6nEzAggggAACCCCAQNYCBIBZixfzeQSAxaxLFWZV+SYgSb73lmRjmFNxkycnubN895T1BOD73y999avpvc04f/u36cdpHMG6I3GMJiG6+27p8stTTXTLFmn+/FRDnLo5aVCe1Svn1jVww8IoCCCAAAIIIIAAAoEIEAAGUsiUyyAATAnI7YkFKh0Auj7B1KkKO3dKM2cmrlOpbnQZyAwfLh086KZ7bSdEM+fx4yVzgC7tz3xm7/nn3c3Z5oTqkI7EnpuEFCHszWIOqWqQdkNxPwIIIIAAAggggEAQAgSAQZQx9SIIAFMTMkBCgcoGgD6+YdapBlU6AWgcsn4lM+H+P3VbFiFSkjkmOaFquupu3iz19tae6LFJSJ6ve9dP5N12m2Re33b1aw7rndTA1eQYBwEEEEAAAQQQQKC0AgSApS2d04kTADrlZDALgcoGgK6+9xbHOqtTbHHmktU1rnyzasrwyCPS29/uTufb35bmzUs3XpoTqiYE3LFDmjGjYQ4emoTkFZzanMizrUJjWO+8BraT4XoEEEAAAQQQQACBYAQIAIMpZaqFEACm4uPmFAKVDQBdnVCLYx+3sUCcscpyjYsTltOmSbt3S8My+N+QX/+69J73uNP9xjekP/zD5ON58zPvOH/pS9LNN0svvjh0gpZNQvJ43TvJiby4lWgM673VIO5kuA4BBBBAAAEEEEAgKAECwKDKmXgxGfzX28Rz48awBSoZALoMLeJsj6xOscWZS5bXlOn0lKsTi3VfEyi+613JtV3Np+3ec9gkxFWYHicoT7On4lSjcQ7eaxBnQlyDAAIIIIAAAgggEIwAAWAwpUy1EALAVHzcnEKgkgGg69cWO/lneYotxT7wdmuS01pDvmHnbXanB3a9J0wjkCuvlJYskebOtT/FmFmo5qBJSFZBmYsTeVFbqTEwzawGUZPi7wgggAACCCCAAAJBCBAABlHG1IsgAExNyAAJBSoZALpuXNDOvuV32BIWqsy32XyvzQSm69c3fbsug8W77ALcPN0hnXkj1uPyhGp3t3ToUERH4pRNQlwEc3GCcldBYzv+xjlkXoMM9jiPQAABBBBAAAEEEMhXgAAwX/+iPJ0AsCiVqN48KhkAuj7t1Wrb5HGKrcjb14RE27dLa9YMdKjt7z89W/PdtfnzB07LzZljf1rO1bpdnfhKux9c78/YHaijmoRcdpl0993SlClDlpjm1dy4Qbnv+jQ2TcmtBq42M+MggAACCCCAAAIIFE6AALBwJcllQgSAubDzUEmVDABdnu5ptYvyOsVWlh1t/Pfvlw4flsaMkSZOjDihltHCfJ8wixt0uT6hunOnNHNmTMQUTUJ8vu7t85/ZVmF9rjWIWSouQwABBBBAAAEEECiXAAFguerla7YEgL5kGTdKoJIBoEFxfZqoKKfYogrO39sLuHiVNco3zquuhTh9ZpqEfOQj0le+0npJF1wwcBrw8ssH/d3X696uTeqTbhfWu35e7FOYURuIvyOAAAIIIIAAAgiUVoAAsLSlczpxAkCnnAxmIVDZANDVaa+77hpo8lCUU2wWtS/Fpebk17590pEj0ujRUk9PutOCUeOZ10DNa8g+f1FdoV2edjPB9MGDKcy++c2Bd7Ofe641yTXXSKtXSxMmnPq7j9e9XZ/Ie/vbpRUr2r9yXqga+NyMjI0AAggggAACCCCQmQABYGbUhX4QAWChyxP05CobALo47RXnNFfQuyfF4joFcaY227YNfC9wy5bB3ws0TS3q3wuM213XZrynn5ZM0w6fP3P6dOPGzk9wdUI1zrMi15qiSYir173zOJFXqBpEFokLEEAAAQQQQAABBIouQABY9AplMz8CwGycecpQgcoGgIYii8YFbLrTAnGCOPNG6Re/KO3ZEy0Xp7uuzSupZrzly6UPfjD62WmuiNOZ19UJ1ajThlbrSNEkxOo5LS7O40ReIWuQFpL7EUAAAQQQQAABBHITIADMjb5QDyYALFQ5KjWZSgeAptI+GxdUaidFLNYmiLNx69RtOUltR46Ujh2zmUGya6O+CVfYE6pxmoTcfLP0yU9KBtPhL+sTeYWtgUNThkIAAQQQQAABBBDIToAAMDvrIj+JALDI1Ql7bpUPAE15bcIpOvza/wORJIizeUqr7rppTnfaPDvptXE686ZZQ9yOw0nnr6gmIRdeKK1dO6RJSOLnScrjRF6ha5AGk3sRQAABBBBAAAEEMhcgAMycvJAPJAAsZFkqMSkCwFqZfTQuqMQOilhkmgDFxq/xe4wuTm7ZPDvJtVEnAOtjJglPO52KTDLXjvckaBKSdA4u6prku52Fr0FSUO5DAAEEEEAAAQQQyFSAADBT7sI+jACwsKUJfmIEgC1K7KpxQfC7J2KBLgIbG8P69+5cnRSzebbNtbadeQt/QtU0CbntNulzn5Nee20oxfjx0sqV0nXXSV1dNlRDrk0TKKc5FWlTg8mTpb/+a2nGjFRL5WYEEEAAAQQQQACBwAQIAAMraMLlEAAmhOO21AIEgKkJGaCdQNZBXL3jratvxfmqrGl0Yk6V2fxKcUL1Bz+QFi2Svvvd1ku77DLp7rulKVNslj7k2rxO5DXW4Gtfk8znEFv9knSqTgXCzQgggAACCCCAAAKlECAALEWZvE+SANA7MQ9oI0AAyNbwJpB1EGeClx//WDr/fKm/39uyUg985pnS178u9fYmG6rQJ1QzahJicyLP9Xc7zbOvvVZ6+uno+sXpVB09ClcggAACCCCAAAIIhCBAABhCFdOvgQAwvSEjJBMgAEzmxl0RAiakOvvs7IM4E6y9+93uyuOrK3Ca11Hdrc7jSBk0CcnjVGRepw89VoqhEUAAAQQQQAABBDISIADMCLrgjyEALHiBAp4eAWDAxc1zaabJhTn9lPXvvvsGPjXn6rd+/cDn6/bscTXi6XGSNKRwPwvPI0Y1CTFH6e68U5owIdVEsjgVmdf3B1PBcDMCCCCAAAIIIIBAYQQIAAtTilwnQgCYK3+lH04AWOny+1v8rl3SrFn+xm83susTgCbIfNObpO3bpTVrpM2b3Z5qrDcuyV4qwyfGaRKyapX0R3+UukmIr1W5aGhTicDXVwEYFwEEEEAAAQQQCECAADCAIjpYAgGgA0SGSCRAAJiIjZuiBPI4AWi66z73nLtvALbq1ls/afbBD0pPPBGlEP33euOS6CuzvcKsc98+6cgRafRoqadHGjs25RwyahLSPEsXa3HV0KYSgW/KbcLtCCCAAAIIIIBAqAIEgKFW1m5dBIB2XlztToAA0J0lIzUI5PENQNddgNuFcy7XZhqXHDrkIFxzsPvMKbdt2wZOOm7ZMviko7POthk1CXG9FlcNbYoa+DrYPgyBAAIIIIAAAgggECFAAMgWMQIEgOyDvAQIAPOSr8BzXYUmcan+7u+kP/gDyfdpLdenG814kyfHXaWf62y66jrpbOuxSYjrtbgMfE31zOvks2f7qSOjIoAAAggggAACCBRXgACwuLXJcmYEgFlq86xGAQJA9oM3AVdBXNwJmkYdU6ZIvr/X5vr7hsuWDTQayeuXa2dbx01CfKzFdeBrOks/9JDU25tXxXkuAggggAACCCCAQB4CBIB5qBfvmQSAxatJVWZEAFiVSuewThdBnM20d+6UZs4cuMNnx1bXgdCwYQPfE7zoIpvVurnWp1PsGTpqEuJrLa4DX+MyapS0Y4c0Y0ZsJS5EAAEEEEAAAQQQKLkAAWDJC+ho+gSAjiAZxlqAANCajBtsBEwoc9llksl4fP82bZLe977TT/FxGsyM7vqVUDPmb/2W9MwzkgkDs/q5CGiddrZN0STE51pcB771+jq1y2rT8BwEEEAAAQQQQACBxAIEgInpgroxw//KF5Qbi0kvQACY3pARIgRMEPfOdw5uKuEDzbz++9RTg0M0m+/BmUBm/fp4p7J8fN8w6w6xrl7RdjrvhE1CfK7FR+Bb3/9O7Xz8Q8WYCCCAAAIIIIAAAs4ECACdUZZ6IALAUpev1JMnACx1+coz+XXrpBtv9D/fVoHediM9AAAgAElEQVSKOR1mGi+Y7rabNw8OIocPl+bPl5YskebMiX8Cz1Xg1Cjy3vcOzC+rn6sQ00tnW8smIb7X4mr85tp6sctqA/EcBBBAAAEEEEAAASsBAkArrmAvJgAMtrSFXxgBYOFLFMYEXbyiGUciKlAxp7n275cOH5bGjJEmTpTGjo0z8uBrzHouvFB69ln7e9vd0d0tHTqUbD62s3B5qs3rvGM0CTn8X+7U+N+doP5+W4Wh17dbi4/A1zzdq11CDrM39u2TjhyRRo+Wenqy2ZMJp8ttCCCAAAIIIIBAaQQIAEtTKq8TJQD0ysvgHQQIANkemQmkadIQd5K+AxUT/G3bNnCa8GtfG+g47PJnvjc3ebLLEVuP5fq7dvV5ewmPIpqE9I8dr//40ir9pf5IJ9SVGq9VDXwG2FnVvBNM477esmXwKVnzz1T9lOzcufFPyaYuBAMggAACCCCAAAKBCRAABlbQhMshAEwIx22pBQgAUxMygI2ACRdMmODz5ytQsfmeYNL1NXYyTjpGnPtcd7Y1gegjj0hew6OIJiE7dJlu1N16WlPiELS9pl0N7rpLuummVEO3vDmrmrebuc2+njpV2rAh3ncy3UsxIgIIIIAAAgggUG4BAsBy18/V7AkAXUkyjq0AAaCtGNenEnB98qzVZHwEKkk6CieB8hVeNs8lizo0P9NJeBTRJORXGqE7dLP+qz6pVzQySQnUqgY+T69mVfNWGEn29ahRA9+q7O1NxMtNCCCAAAIIIIBAZQUIACtb+kELJwBkH+QlQACYl3xFn+v65FkrRteBis/wp3H+piHJwYPZfG/N5TcAbbays/AooknI/6cLtVhr9W1dbjM9taqBz9d/s6x5M0SafW3quGMHJwGtNhcXI4AAAggggEDlBQgAK78FTgIQALIP8hIgAMxLvqLP9X3yzHWg4jP8ad4CUQ1MXG8ZX51to+bpNDyKaBLyV7pWH9Wd+oUmRE3r5N9b1cBXA5B2z4s10ZQXudjX06ZJu3fzTcCUpQjydi/fAg1SikUhgAACCFRNgACwahVvvV4CQPZBXgIEgHnJV/S5vk+euQ7RfIY/zVvAPMs0Wcjql+XamtfkNDx6+WX95Ibb9K8e/JxG6LUhfIc0XssUr0lIqxr4DEqzrnkdx1Xt85p/Vv+M8Jz4AjSSiW/FlQgggAAC1RUgAKxu7RtXTgDIPshLgAAwL/kKP7dMgYrPuTZuAaeBWMy95eIUWMxHtbzMZXhk1nLlb/9Ay55ZpIv13ZbPi2oS0qoGPgPrPGpeh3G1r10H7mn2E/fmJ0AjmfzseTICCCCAQLkECADLVS9fsyUA9CXLuFECBIBRQvzduYCr00fNE3MdqPgMfxrn7vSVWMtqpfkOnOWjhlzeHB6lfW3QrGXOZce14OUvnWwEMk4vDnlmuyYh7Wrg65X1PGvucl93d0uHDmXz3cq0+437/QjQSMaPK6MigAACCIQpQAAYZl1tV0UAaCvG9a4ECABdSTJObAEfJ898BCq+wp/m8C/vjqpJ/gt87GJ3uNCER6bpiQnu1qyRtmyR+vtP32D+Pn++tGTJwKvRw2L8X8q77pI+/OH/y967gNtVVeffb0LCNYkSwGoTFZVbCGiNNUGrSbhEa6tisGovEsBaQg+PlSDWhLZKop9aScD2b+Ak2k+S6leJ1KSWi1aFJGolUavEf1AoKkguUAkt5qJYknzPOHtvss8+e+91m2utOdf6refJ05o915xj/Mbc4eTNmPOVTjjwiK7XAv2RPtc1gnaTkH7GJHmY1jgzQklZBNf72rXpTsq0eK0EAln+ASGPP7NLQMCSEIAABCAAgUQEEAAT4ars4Bh/rals7iRWLgEEwHL513b1LH9x7ISWl6CSh/jTHrt1LK5a5YeTapIjfC437UknSQ88ED3j1KnS6tX9WXUTMl+rL+kGDeiF+mnXRcwk5KmPLtMl7+tuEuJaLDv5ZOlznyu35q739aZN0vTp0TVkRLUIuPiHHNdd29UiTDYQgAAEIFBFAgiAVaxq8pwQAJMz4w03BBAA3XBklhQEXHSe5SmiuRZ/DJG5FLe62mbNitfVlgJtqleeeEKaOFE6cCDV67m/1E/o7ScoH6V9+ht9UFept0nI7r+5Vs+/5hJp9Ohhebg8LmtT23HZZzwjd1R9F3C9r+kALLeeZa3u6ioHl3eBlsWCdSEAAQhAAAJxCSAAxiVV7XEIgNWur8/ZIQD6XJ0axJam86woEc2l+GPHWb/1LenUU/29L821MJTH9u12bDBuJ9IZ+oFWqLdJyMFXv1qjBgel008fFnrVDDNc7mv7Ltox7gkT8qg2c/pMoGrfC59ZExsEIAABCFSHAAJgdWqZJRMEwCz0eDcLAQTALPR41wkBE3A2bGjcA2f34bXfA2cCw+tfL73pTdJppzWEhkmTihMc6vSXXNdHQ51sji6TdB4bTNKJNEoH9GfqbRKisWOl971Puvpq6aijhlZPMn+/nH3qdKrTvs5rH9Z5XpciMkYydd5J5A4BCECgfgQQAOtX824ZIwCyD8oigABYFnnW7UrA/mK5fbu0e3fjeKyJg/aMGydNnlyc8NcKroriT6+tF0IHYHtdzBjEnjRi1m+ov0mI7HLCG2+UzjtvaA+eeaa0dWv6L61vd53VaV+nrxpvFvVnBcfI2WsQgAAEIFAXAgiAdal0/zwRANkHZRFAACyLPOt2JWBiy/r17lxhs2KuovjTi4nLrp6s3KPeN9FvzRopa8xRJiF6+9ulZcv0H9uepZkzpb17oyIb+bmPbqd12tfJK8YbUQRcdwtjJBNFnM8hAAEIQKAqBBAAq1LJbHkgAGbjx9vpCSAApmfHm44JJLkPMI4rrKvwsjgW+yj+9OOSppvOFeck87SODW7bJtleyPJEmYTo2GOla6/VVyZforlvHp1IBMzLoTpLvq13Q9jXJvBajffsKa8L2AXrqs3huluYDsCq7RDygQAEIACBXgQQANkbRgABkH1QFgEEwLLIs+4wAmkcgYsUV3yPz9V2cnU01FU8/eYx0cCOis+Y4WY1Mwn59zPna/wPvtV9wle/Wvf+xaDees3psY4D5+lQ7SZjycd97VsXsCvWVZona+dtOwuMZKq0M8gFAhCAAASiCCAARhGqx+cIgPWos49ZIgD6WJWaxRRCJ5KVJEmHYgjiT7dt5uJoaFHb144N2t2QWTsA2+O99/8e0JRvfLJhBPLEEyNTGTtWB//yffr6q6/W//nUUV1Na+bOlQYGpFmzGvdY+v4k2deWy7nnSn/1V5Ldweg6vySxFNkF7HsNy4jPVbdw6zh/GTmwJgQgAAEIQKBoAgiARRP3c70A/orgJziiykwAATAzQibIQsCF4FSkwUKUY3Fo4k+32mURZPvtBfPVeOCBLLtl+LvWAWiO0BMnDneOTrvCsE6kRx6RFiyQPve57tM1TUJ+Mf28p01rxo8v1qE6bZ7d3mvt6w99SPra1+LN7FqA87EbMR6Jeo5y1S3skzt2PStJ1hCAAAQgUCQBBMAiafu7FgKgv7WpemQIgFWvsOf5hfyXyHbH4pDFn25bJI0YY/fymZB04MChGU1Ua4miL32pdNxx7sW6XDuRvvSlRjvfT3/a/ZvUNAnRs57l+TctOrw0NXd1DD+L6BzaPZvRlQhjRGj/eBMGVaKEAAQgAIGqE0AArHqF4+WHABiPE6PcE0AAdM+UGRMQyFW8SRAHQ0cSSHIcs3Xk2Rrjtm9v3M3XTRTNo965i8j79kkf/KC0dKn01FMjQTVNQnTJJdLo0UFupTIFOISkILfMUNBl7ptwqRE5BCAAAQjUmQACYJ2rfyh3BED2QVkEEADLIs+6cnmRfMsVdsIEwLok4PrIsyux7s47pbPPbmRamID0gx9I8+dL3+ptEqLBQen0012WIPe5CuPXIxNXe4KjpLlvla4LlNk5Wk7GrAoBCEAAAhBITwABMD27Kr2JAFilaoaVCwJgWPWqVLR2h5tTA4d7pSlTKoXIq2RcHHl2ITYZFBN6P/Yx6dJLG0YUhXUi2fnmT/Y3CRkyEDGXjCOP9Kp+vYIpW4DLoys0CPAVCjJNt/C0aRUCQCoQgAAEIACBmAQQAGOCqvgwBMCKF9jj9BAAPS5O1UPbvFmaMcNdluYKO326u/mYKR8CWcS6zoie/3zpC1+QTEwotBMppkmIzjsvH4gOZy1TgKML2GEhS57KdbdwyemwPAQgAAEIQCAXAgiAuWANblIEwOBKVpmAEQArU8rwEqEDMLyauYo4jVjXa21rtPviF6U5cxqdgPPmSVu3RkfaurcwUydS4CYhZQtw/BkQvU9DHOGiWzjEvIkZAhCAAAQgEEUAATCKUD0+RwCsR519zBIB0Meq1CQml+KDuc3u2tU4GsoTBgET6y68UDIRKOtz9NHS17/e6AQsvBMpYJOQsgU4uoCz7nzehwAEIAABCEAgJAIIgCFVK79YEQDzY8vM/QkgALJDSiVQ5vHDUhNn8SECZuZx7rluYFhH35YtjTsBW0+cTiQbs22btGePNG6cNHlySiE5QJOQsgW4sgVINzuPWSAAAQhAAAIQgEA8AgiA8ThVfRQCYNUr7G9+CID+1qYWkZVtQFALyB4n6UoAbqUY1wnWugTXr5eWL5fWrZP27z8EyRyl586VBgak2bOHC4qRKAMzCSlbgKMLOHJHMQACEIAABCAAgQoRQACsUDEzpIIAmAEer2YigACYCR8vZyXgwhW2W+dX1rh4P38CLsWfVrQmKK5Z0z/2JPcEmkv16tWNo8WJnkBMQlzWIO0xfFcicJzaJ6ohgyEAAQhAAAIQgIBjAgiAjoEGOh0CYHiFe5Yk8xu1Xy9v/jqumcYqSRfHSOlISa+VZDaRNs/JksZL2i3pPklflrRC0s4Yc6UdggCYlhzvOSOQxRX2mGOkjRtTCDTOomeitARcd59ZHNa99/jjvY/wpjEfsT22dm3DZCTxE8ck5LrrpBNOSDy1qxfKFuDoAnZVSeaBAAQgAAEIQMB3AgiAvleomPgQAIvh7HKVg30miyMAvljSN5qCX7+4TAx8p6SInpbUqSEApkbHiy4JFC7MuAyeuVIRcH3/XCsIExanTBkZkmuhOfbdgVEmIRMnSh/7mHTJJdLo0alY2kux4+lYoWwBji7g1CXnRQhAAAIQgAAEAiOAABhYwXIKFwEwJ7A5TtsuAD4s6YeSXtNcL44A+CpJX2+O/6akWyV9R9IuSdYKckFT+DtMkt1O9QZJd+SQDwJgDlCZMh2BJEcz7djvqlV0/qUj7cdbeXQAWmabNknTrae67XElMt1zj7RhQ8q7A3MwCXFxl6ErNp0GLEl2mWtxNsnajIUABCAAAQhAAAJFEUAALIq03+sgAPpdn27RLZb07eavRyWdKOmnCQTAV0p6tySb594e6Z8vaa0k2x8/bh4R7td5mIYiAmAaaryTGwETI1oCix27bDdnsDvGWuYMs2YlNGfILWImTkvA5f1z7TF06wB01eV24onSgw9GZ2wdiEuWSM97XoezsJmErFwpLVwoPfHEyInGjpXe9z7pr/5KOtJuiej9JBHMo+4y9EGAows4el8xAgIQgAAEIACBsAkgAIZdP1fRIwC6IlnePEkFwLiR3iLpzc3Bdg399+K+GHMcAmBMUAwrnoAJRNu3S7t3S+PHS5Mm9b7brfjoWNEFAVf3z7Vi6WVE4XqdpLmPcBZ+ZKe0YIF0883dpzrpJOnGG6Xz7IrYkU8eYlkecybllETUpAs4KV3GQwACEIAABCBQNgEEwLIr4Mf6CIB+1CFLFHkJgJdL+kQzsLdIMkHQ5YMA6JImc0EAAokIuOrMay3azQk2r07DRIm2DR7WjZfCJCTPbj0fBDi6gNPuLN6DAAQgAAEIQMB3AgiAvleomPgQAIvhnOcqeQmAV0pa1gzcOgG/4DgJBEDHQJkOAhCIT8DF/XPtq5mgOHv28PXzumswfpYjRw5zFk5gEnJw1Gideaa0dWv61a1zrt99fT4JcHQBp68zb0IAAhCAAAQg4B8BBED/alJGRAiAZVB3u2ZeAuC/SHpjM9Spfe4LTJsNAmBacrwHAQg4IZClo609gF7CVl5uw1mTNxFw48Y2I5sYJiGb3rFCZ13SxeI4YTDdhNJuUyDAJQTLcAhAAAIQgAAEINCHAAIg28MIIACGvw/yEABfIum7kswJ2Po9zkiByQS+fs+zm0YmevjhhzV5ctTwFBHwCgQgAIEIAnb/3PnnS7/8ZTpUI8S0tml87ABshTdCtIwwCXlq1Fh9+OBCfVhX60n1NwnpR7LbUel05HkLAhCAAAQgAAEIQCAuAQTAuKSqPQ4BMPz6uhYAj5D0DUm/3URjjsBfTIEptmswAmAKurwCAQg4I2CdgBdcID30ULIphx2n7fKqb3cAdobYtRtvZ3+TkP/USfpz3aivqbtJSBRBMyV5/HFMdaI48TkEIAABCEAAAhBwSQAB0CXNcOdCAAy3dq3IXQuAn5T0zubkqyRdnBIRAmBKcLwGAQgUT8Dun/vkJ6X3vlcy4S7qiesEW7YLcL88+nbj3XGHNDAgPfhg1yn+UW/XlbpOj+mEKFQjPrfOyCnZTxMnXpcXIAABCEAAAhCAQF0JIADWtfLD80YADH8fuBQAF0n6cBOJHQGeJWlvSkRRZ3o5ApwSLK9BAAL5ETAh8Pbbpb//e+mrX5XsZGzrGTNGmju3oYvNmiWNivFfUNduwy4zj+zGM5OQJUt0YOkyjd7/1Iild2mi/lIf06d1iQ5qdOzQNm2Spk+PPZyBEIAABCAAAQhAAAIZCSAAZgRYkddj/PWlIplWNw1XAuB8SYNNTPdJerWkn+eIDROQHOEyNQQgkJ2ACyMK127D2bMaPkOcbrwfr/uBHp07X6/Ut7ouv1Gv1nyt0I8Ur60vzprdFrJ6bNsm7dkjjRsn2dWxEya4JsJ8EIAABCAAAQhAoHoEEACrV9M0GSEApqHm1zsuBMA/kvQZaaiFw27BepWkbTmniQCYM2CmhwAE/CDgym04j2zidOOZ8HbcsQf0pwdW6qNaqGfqiRGh/Fpjhz6LMgmxLspdu+ILdyagrl8vLV8urVsn7d9/aGnrYGx1ZM6eHa8jMw+GzAkBCEAAAhCAAAR8J4AA6HuFiokPAbAYznmuklUAfKOkf5Y0RtLOZuffj/MMuDk3AmABkFkCAhDwg4C5DZtYtTftpQo5pRGnG89EuGc+s3E34rO1U9drgf5QN3eNyExCLtOg7tS5XT9P4gJswum8edJW86KPeKZOlVavlqZNixrJ5xCAAAQgAAEIQKB+BBAA61fzbhkjAIa/D7IIgPY3tNskmfPvruadfzH+quUEGgKgE4xMAgEIhEIgiaBVRE5xu/G63WP4u7pDN2hAL1B3k5DVulDv0bIRJiFdnYe7JJtGMI1yZS6CKWtAAAIQgAAEIAABHwkgAPpYleJjQgAsnrnrFdMKgK+U9G+SjpFknpfnSDLjj6IeBMCiSLMOBCDgDQHrptuwoXGkde3a4UdaTZB7aqTXRm6xx+3G6+VkfJT26f1aMiT0jVW0SYjd1/c//xN9VDfLkWkTATdupBMwt03DxBCAAAQgAAEIBEkAATDIsjkPGgHQOdLCJ0wjAP6WpLskPbPp8vtaSd8sOHIEwIKBsxwEIOAXgU6TkZ07pXO7n5zNJfA43XgW48SJw4XKzmDO0A+0QtEmIfePnqL//u/+9/+5ME054wxpy5ZooTEXqEwKAQhAAAIQgAAEPCSAAOhhUUoICQGwBOgZlzSDjpPa5jhe0rXN/20i3qc65r+p43+/SNK/S3pW8/cXSPpqREz/Jcl+uXwQAF3SZC4IQCB4AnYfn91lV8QTVySLG9MoHdClijYJeev3rtZpv3VkzxS7HTdOwyOOuJlmXt6BAAQgAAEIQAACIRJAAAyxau5jRgB0zzTvGU3QuyjBIp01vljSpxO8b0MXS7om4TtRwxEAowjxOQRqTsC6z7Ztk/bskcaNkyZPju8eGyK6ON12LvJKckx282Zpxoz4q0aZhPxq8kk68qbBnq2OvY4bx4+gMfK1r5XWrKn2fknKhPEQgAAEIAABCNSXAAJgfWvfnjkCYHj7AAEwvJoRMQQgEJOAHQFdv75xR966dcOPnh52WMNJd2BAmj27mkc8XQlgvXAnNcqI2wHYuV6USYguvFBatkw64YSnX3UtgNZhv8T8WjEMAhCAAAQgAIGaE0AArPkGaKaPAMg+KIsAHYBlkWddCHhKIIlLrh2VXb26emYPro7AdiuxHftdtSoZsyyiXJRJyNDlgtdeK11yyZCam1ZsjLOdq7pf4uTOGAhAAAIQgAAEIIAAyB4wAgiA7IOyCCAAlkWedSHgIYGvfKXR3bd3b/zgknazxZ+5vJEuTDDaozdn4VbX5KxZ6boms3YlmknISl2qV+ju7mBnzpQGB7V595REx42TVqmK+yUpA8ZDAAIQgAAEIFBPAgiA9ax7Z9YIgOyDsgggAJZFnnUh4BkB6/wzDSiJ+NdKIcl9dp6l3TOcLDyOPrrRGfnc50rjx0uTJmW/B89FV6KZhPxowUqd8v8ulJ54YmTuY8fq53+6UM8dvFpPqrdJSNYaVnG/ZGXC+xCAAAQgAAEIVJ8AAmD1axwnQwTAOJQYkwcBBMA8qDInBAIj4KLjLa6jbUhofOqIdFqjR3ZKCxZIN9/ctRz/qZN0mQZ1p87NrVxF7Jd+BjZ1M7fJrZBMDAEIQAACEIBAbAIIgLFRVXogAmCly+t1cgiAXpeH4CBQDAEX3WUWqc1jxiBVEleS3ImY5n6/JBXO0pXYtevujjsabi4PPtg1jNW6UO/RMj2mQyYhSeKNGtvaL1Hjknzez8Bm9GjpVa9qzPbNb9bP3CYJR8ZCAAIQgAAEIOCeAAKge6YhzogAGGLVqhEzAmA16kgWEMhEIOv9cq3F7X6744+vnnOwiUobNjRckdeuHS4cubjfL0nxnHcl7tsnLVnScAN+6qkRoezSRL1X1+rTusT5lcW279asSZJ9/7FJxNp+M2FW4q4mzAQBCEAAAhCAwCECCIDsBiOAAMg+KIsAAmBZ5FkXAp4QyOIwmyaF0MUV47V9u7R7t7v7/ZJyTCJ0xe5K/MEPpEsvle7ubhKyQTOHjgX/SFOShttz/GGHSY8/nvx+xG4dpps2JTew6ZcIZiXOysxEEIAABCAAAQg0CSAAshUQANkDZRJAACyTPmtDwAMC994rmShX5IO4kp12Ll2JBw5IK1dKC7ubhPxaY/VRLdSH5c4kxPbflBiaYtTR3lGjhndmZicsYVbigiJzQAACEIAABCDQIoAAyF5AAGQPlEkAAbBM+qwNAQ8IbN4szZhRfCCIK9HM496l6LwrcWd/k5D7dbL+XDc6MQmxzr3p0/uzSNLxGE012YgizEqSRcRoCEAAAhCAAARCJYAAGGrl3MbNEWC3PJktPgEEwPisGAmBShIoowOwBRJxZeSW6tfpZkdm585t+HaY2Yp1veX63HGHnnzngI7YkZ9JSFQHYJo7D10zycOsxHWMzAcBCEAAAhCAgP8EEAD9r1EREeb9I3wRObBGmAQQAMOsG1FDwBmBou8A7AwcceUQkSSdboXdpbhvnw4uXqKDy5Zp9H63JiFmoLJrV+87ALO4Hjv7gkhybVbiMjbmggAEIAABCEAgHAIIgOHUKs9IEQDzpMvc/QggALI/IACBIYHjllvKAVFXcaXzeO/990tvf7u0d2/8OhR6l2IOJiH9am+dkGeeKW3dGp9HXiPTmpXkFQ/zQgACEIAABCAQJgEEwDDr5jpqBEDXRJkvLgEEwLikGAeBChOwLrxzziknwTqJK/2O96alX+hdik2TkP+9aqHG7n1iRMhJTUL6dX+WuSe71SLqqHLa+vEeBCAAAQhAAAL1IYAAWJ9a98sUAZB9UBYBBMCyyLMuBDwiUHa3VR3ElSTHe5NujaLvUjy4Y6e+NGWBXveLm7uGGsckJCrmMrtSuyUVx6wkad0YDwEIQAACEIBAvQggANar3r2yRQBkH5RFAAGwLPKsCwHPCJR531rVxZUijCyKvkvR9ssHX3mHrntyQC9QMpOQqK7Fsu+l7PbVtCPyb36zZ19awoEABCAAAQhAICgCCIBBlSu3YBEAc0PLxBEEEADZIhCAwNMEihCquuGucgdgUcJqGXcp2n754zft03v2LdFVWqox2j+ivLs0Ue/Vtfq0LpE0SnHuLSzTmbrXHwdHHy2tWyfNmRPeHxid901OntzbeCW87IgYAhCAAAQgEA4BBMBwapVnpAiAedJl7n4EEADZHxCAwDACeR5V7YY6ygk25PIUebS6rLsUW/tl9NYtWqH5eoXu7lqyDZqpZScN6pqbp2jatP5V3bxZmjHDv8pHdS76FHG/+yZtr8ydKw0MSLNnS6P4KdSn0hELBCAAAQhUmAACYIWLmyA1fvRKAIuhTgkgADrFyWQQqAYBEw82bJCWL5fWrpX2tzV2mWBn4sGjj0obN2bPt4zOtexRx5uhaCOLsjopW/vlhk8c0PFfWKkPH1yoZ2qkScjBsWM1auFC6eqrpSOP7AnRxw7AVrBRdxfG2xn5jkoi4k+dKq1erUhRNt+ImR0CEIAABCBQDwIIgPWoc1SWCIBRhPg8LwIIgHmRZV4IVISAHR/cvl3avVsaP16aNKlxfNCVuFX03XVFlqVoIwsf7lK0/fLo93dq4gcX6LivdjcJ0cknSzfeKJ17btdy+HgHYHugPu/ZNMf44xzLLvJ7w1oQgAAEIACBqhJAAKxqZZPlhQCYjBej3RFAAHTHkpkgUCsCLo63htBNlbaoZYhYZXUA9mR0xx2Nc6YPdjcJ0YUXSsuWSSecMGKKosXTJHX2tWs1y32TIR1vTlIrxkIAAhCAAAR8IoAA6FM1yosFAbA89nVfGQGw7juA/CGQgQCCQ294RR9j9fYuxStV/isAACAASURBVH37pCVLpKVLh58lb6GbOFG69lrpkkuGXUbnqsM0w/bu+WpZ9y32ywVBPo9KMycEIAABCEDALQEEQLc8Q50NATDUyoUfNwJg+DUkAwiUSoAjh93xF21k4WtX2tN0tmyR5s+X7u5uEqKZM6XBQWnKlKFXXAhaeX4xfOu2dCWY+ny8Oc96MjcEIAABCECgCAIIgEVQ9n8NBED/a1TVCBEAq1pZ8oJAgQSSmA7Ysd9Vq6pvOlB0B2AQws2BA9LKlZIZgTwx0iREY8c2PmuahGTpMLUuPXvaDWxcfiV8uG+xPR9XR6a9F5JdFpG5IAABCEAAAgUTQAAsGLinyyEAelqYGoSFAFiDIpMiBIogEMc52K6DmzVr2EnPIkIrZY0i7wAM7i7FnTulBQukm6NNQrJ0mM6YccjAxlyr3/hGd1vBpw5Al3vNx+PN7qrGTBCAAAQgAIFyCSAAlsvfl9URAH2pRP3iQACsX83JGAK5E+jlHJz7wp4t4Korq19aQZs3xDQJ+Y+HT9C8edLWrdEF7tVh6lIk8+2+Rdfdpj6Jm9EVZwQEIAABCEAgHAIIgOHUKs9IEQDzpMvc/QggALI/IAABCOREYMUK6bLLcppckol/a9dKc+bkt0buM8c0CTl48SXasHGUli9v5Nx+tNcEublzG4bD/TpMXQmyvh2TdX3fpG/Hm3PfgywAAQhAAAIQKIgAAmBBoD1fBgHQ8wJVODwEwAoXl9QgAIHyCNiRaOtGs26qPJ7K3aWYwCQkbYdpVY0y6ADM4xvGnBCAAAQgAAH3BBAA3TMNcUYEwBCrVo2YEQCrUUeygAAEPCPgSmxqTytup5tnKOKHk9AkJP7EjZEunIV9vG+xyseb49bYGGzbJu3ZI40bJ02eLE2YEPdtxkEAAhCAAASKIYAAWAxn31dBAPS9QtWNDwGwurUlMwhAoEQCro6bvva10pIl0vjx0qRJNRE1EpiEJC1xFmdhn+9bdLXffDve3K++JuiuX6+hY+Hr1g0/Fm5mJq1j4bNn18N4KOl3gfEQgAAEIFA8AQTA4pn7uCICoI9VqUdMCID1qDNZQgACBRJw2ZFVa1fWmCYhOuGERNXN4izs632LrjpObR4TzHx/Nm6U/vRPpQceiI506lRp9Wpp2rTosYyAAAQgAAEI5EkAATBPuuHMjQAYTq2qFikCYNUqSj4QgEDpBLiTzWEJYpqE6JJLErV5WSdgVmdhh1lmnqqqx5vbwbQ6/t7/fukb30iGrBKGOclSZjQEIAABCHhIAAHQw6KUEBICYAnQWXKIAAIgGwECEICAYwK4sjoGatMlMAmJu7oJShs2NI6QpnUWjrtWEeOqerzZ2CURbHux9vkIdxH7gzUgAAEIQKB8AgiA5dfAhwgQAH2oQj1jQACsZ93JGgIQyJEAHYA5wY0wCTk4Zqx+feVCHbH4aunIIxMFkdZZONEiBQyu4vHmNDn1Qu2jiUsB24IlIAABCEDAEwIIgJ4UouQwEABLLkCNl0cArHHxSR0CEMiHgMs7AM35d9eumph/xCzHwR079V9vX6DfuOvmrm/sGHey/uuaG/WSK8/VqBr+hJWkW+7006XFi6XnPc9P99wsXY29tlMo9xzG/DowDAIQgAAEAiKAABhQsXIMtYY/nuZIk6mTEEAATEKLsRCAAARiEqijK2tMNJmGtYtbv6s7dIMG9AI92HXOLz7jQp34z8v04nOTmYRkCtCTl6OON//O70g2xu7Ss8bK1uOTe66Lew27lSMkp2NPthNhQAACEICAIwIIgI5ABj4NAmDgBQw4fATAgItH6BCAgL8E6ubKWkQluh0FPUr79H4t0VVaqjHaPyKMXZqoR668VlOXJjMJKSKfotZoP9788MPSX/+19KMfRa9etnuuq+9QZ6a1dtaOLjsjIAABCEAgRwIIgDnCDWhqBMCAilWxUBEAK1ZQ0oEABPwg4KJ7ifvKDtUy6ijomdqiFZqvV+jurhtg97SZGv+ZQWnKFD82SAlRpLlLr0z3XFddtN1Q2z2dNd4KJew+loQABCAAASOAAMg+MAIIgOyDsgggAJZFnnUhAIHKE4gSrfoBwLH0EJ24YuooHdClWqmPaqGeqSdG4D04dqxGLVwoXZ3cJCT0zRraXnR5j2a32m3aJE2fHnpViR8CEIAABEIjgAAYWsXyiRcBMB+uzBpNAAEwmhEjIAABCKQmEFrXVdxETaDZtk3asyd/84ikR0GfrZ26Xgv0h+puEqKTT5ZuvFE699y46QY9Lq6A2i/JortRXTtpd+ZGB2DQW5rgIQABCARLAAEw2NI5DRwB0ClOJktAAAEwASyGQgAC5REoUnBynWUSV1YTWlatkqZNcx1F9vlMSFq/Xlq+XFq3TtrfduVenuYRaY+CRpmE6MILpWXLpBOqbRKSVEDttVOKdM/dvFmaMSP7nu02A87a+XBlVghAAAIQiCaAABjNqA4jEADrUGU/c0QA9LMuRAUBCKjhUlqG4JQH/ChX1rlzpYEBadYsaZSHPxUkETFdmkdkPQoaZRKiiROla6+VLqmuSUhaAbXze1Cke26eHYBF5pHHnyXMCQEIQAAC4RJAAAy3di4j9/BHfZfpMZfHBBAAPS4OoUGgzgTKEpyKYN7uyjp+vDRpkjRhQhErp1ujzGPMroSgKJMQzZwpDVbHJKTVMfvoo9J550kHDqSrfftbRbrnZhV++2VbZCdjdurMAAEIQAACVSKAAFilaqbPBQEwPTvezEYAATAbP96GAARyIFCm4JRDOkFPWbZ5hMujoGYS8uP3rdQLBhdKT4w0CdHYsVLAJiH9OmZdbcIi785z1bnYnnvRdxm64s48EIAABCBQDQIIgNWoY9YsEACzEuT9tAQQANOS4z0IQCAXAmULTrkkFeikPphHuOoAbJVgSMB65k7piiukNWu6VyZAk5AkHbNZtmOR7rmu7i5s5YuzdpbK8y4EIAABCLgggADogmL4cyAAhl/DUDNAAAy1csQNgQoS8EFwqiDW1Cm5EmCyHLl0eRR0hPnDHXc0Ll588MHujAIxCUnTMZt2UxTZAejiz4N28W/tWmnOnLSZ8x4EIAABCEAgOwEEwOwMqzADAmAVqhhmDgiAYdaNqCFQSQI+CE6VBJsyKVdHMLOaLuQax7590pIl0tKlw22NW8w8NwnJ0jGbdFuU4Z7rIj+fnbWT1oDxEIAABCAQNgEEwLDr5yp6BEBXJJknKQEEwKTEGA8BCORGIFehJ7eoqzmxy867rOYRhQjDW7ZI8+dLd9/dvaAemoS47JCLs4uzCrlx1ug2Jm2Ho5Vs8WJ/nbXT8uA9CEAAAhAIlwACYLi1cxk5AqBLmsyVhAACYBJajIUABHIj4JPglFuSAU2cy917U9IBcCF0xTJ/MKvclSsbRiAFmYS03Hr37JHGjZMmT47vCO1KGI1blSxHueOu0WtckjsOTzpJ+od/0JCxMw8EIAABCEDAJwIIgD5Vo7xYEADLY1/3lREA674DyB8CnhDwSXDyBEmpYbh037VEsppHfPaz0tvfnh7JZz4j/cmfxHx/ZwyTkMFB6ZxzYk44fFg/t17rlpw7t3E14ezZ0qg+PyG66piNk0QsATXORBnGGLcNG6TlyyW7z2///kOT2fHkFrdZs/pzyxACr0IAAhCAAAQyEUAAzISvMi8jAFamlMElggAYXMkIGALVJOCb4FRNyvGz8kmQLawDsBNPDiYhSTrZpk6VVq+Wpk0bWTeXHbNRu8JH91zLf/t2afduafx4adKk+J2TUfnyOQQgAAEIQCAvAgiAeZENa14EwLDqVaVoEQCrVE1ygUDABHwSnALG6Cx0lwJTVvMIV0ddo46wdj2OO8adSUiau+xMfOvmXuv6+9Jr4/Ra39lGYyIIQAACEIBAjQggANao2H1SRQBkH5RFAAGwLPKsCwEIDCPgk+BEaRoEXB0xzWoekWccsY/jTtyiUZelNwnJ4mbbrQPPdcdstz2Pey5/EkAAAhCAAATcEkAAdMsz1NkQAEOtXPhxIwCGX0MygEBlCOQp9FQGUoGJFNV51y8ll8Jwpxtx4uO4Nx3QtO/ENwlpdRTaMVW7v/CBB9IXr/MOvrw6ALlLL32NeBMCEIAABCAQRQABMIpQPT5HAKxHnX3MEgHQx6oQEwRqSsAHwamm6LumXdrde23RuBa6bL4pU6RMx3HP6G8Ssm/yyfrYCwb1oX8/Z5hRRda91X6E2aUwaqLfl78sPec53KWXtUa8DwEIQAACEOhHAAGQ/WEEEADZB2URQAAsizzrQgACIwj4IDhRluEEXB9dTcrX9VFXcyM2wWvmTGnv3qTRSMOO40aYhKzSPF2lpXpMJyRfqMsbkyc3TEFa7sB0zDrByiQQgAAEIACBwgggABaG2uuFEAC9Lk+lg0MArHR5SQ4C4REoW3AKj1j+EWfqlpuTLT7XHYBbt0pvfatk/zftM+w47r590uLFOrB0mUYf2D9iyl2aOCQC3qSLnf17b8sd+IknpHPOSZvFofeizFGyr8AMEIAABCAAAQgYAQRA9oERQABkH5RFAAGwLPKsCwEI9CRQpuBEWboTSHJfnkvzCNdHXc1R9w1vyF7ldtHM2Pz5q7bo7355qc7Spq6Tb9BMXaZB/UhTsi+uRifiF74gXXmlQzHTSWRMAgEIQAACEIBALwIIgOwNBED2QJkEEADLpM/aEIBATwJlCU6UpDcBO6K9YYO0fLlkQtr+toa3PM0jXB51tRxuuSV7lVvOxu3H1kfpgC7VSn1UC/VMPTFikV9r7NBnH9bVelJHZg7CRMAVK6T58x0cZ84cDRNAAAIQgAAEIBBFAAEwilA9PqcDsB519jFLBEAfq0JMEIDAEIGyBCfwRxOwzrzt2yVzuB0/Pl/zCFfmMLfeKp1//nDhMjrT7iNajsLf/e7IY7jP1k59XFfobVrT9eX7dfJQN+Bdyn5+17otly2TLrggmQho4qGJuHMyHtGOy6/liLxnjzRunGT3GU6YEPdtxkEAAhCAAASqQQABsBp1zJoFAmBWgryflgACYFpyvAcBCBRKoEjBqdDEWCySgCtzmM99TjLBzNVj9xO+//29Owp/V3foBg3oBXqw65KuTEJMIDUxbd68eMeBXR7R7sfS6rZ+faNjdN264cKrCahz50oDA4dMTVzVhXkgAAEIQAACvhJAAPS1MsXGhQBYLG9WO0QAAZDdAAEIQAAC3hNwYQ7z1FPSjBnuUr3zzkYHXftR6M7Zj9I+fUCL9R4t0xjlYxLSfhy5jCPa3YgmOcLfMjWZNu3QTHQMutunzAQBCEAAAv4QQAD0pxZlRoIAWCb9eq+NAFjv+pM9BCAAgWAIZDWHce0o/MUvSm98Yzx8Z2qLVqq/Sch8rdB9Oi3ehG2jWseR24/Ultkxm7ZOZmoydiwdg4k3AC9AAAIQgEAwBBAAgylVroEiAOaKN5fJnyVpevPXyyXZr+OaK62SdHHCVX9X0qXN+U6Q9HNJmyWtlPSlhHMlGY4AmIQWYyEAAQhAoFQCSTrLOo+6unYU/vKXpXPPjY/DTEJM5DMjkGfoFyNeNJOQj2jR0K+kJiEmbk5xYzAcP6EuI7N0ao4eLR04EL18t47B6LcYAQEIQAACECifAAJg+TXwIQIEQB+qkCyGg32GJxEArfaDTfGv15QmAl5m9+EnCzHWaATAWJgYBAEIQAACvhDIYg7j0lH4mmskE6OSPnmYhGzaJE23f5Ys8XFxV2Pc8Is2MYkbF+MgAAEIQAAC/QggALI/jAACYHj7oF2Me1jSDyW9pplGEgHw/5F0dfO970n6mKQfS3qRpL+U9NLmZzbur3PAhACYA1SmhAAEIACBYggkPerqylHY5rE76yZOTO8q7NIkxIcOQFds4+4cEwE3bmzUgQcCEIAABCAQAgEEwBCqlH+MCID5M3a9wmJJ327+elTSiZJ+mlAAPKkpHI6R9B1JMyX9si3QoyVtkPTbkp6Shi4GMnHQ5YMA6JImc0EAAhCoKYFQTBtcdKnZ0eItW6RRo6SsHYUuTELGjJF27Wo4AZf5ZGWRJvb2WqR5n3cgAAEIQAACRRJAACyStr9rIQD6W5u4kaURAJdLGmgu8ApJd3dZ7CxJ32r+/ickvStuQDHHIQDGBMUwCEAAAhAYTsDEtPXrwzNtyHJPXWfXmauutywmIW96k7R2bbm70+X9ikkzsRrMnp30LcZDAAIQgAAEiieAAFg8cx9XrJMAaN1u1s1WtSepAGg1t6PDkyT9SFK/q7vt81MlbZP0PMd3ASIAVm0nkg8EIACBAggkMePw0bQhrVOtCW1z5hwC7KKjsDVbWpOQm26SLrqogKL3WcK1w3KSbKzzcM2aJG8wFgIQgAAEIFAOAQTAcrj7tmqdBMCdkj4l6ZOSfuZbITLEk1QAfGHbcd4VTZOPXsvb5+YQbI+91zpqnCHcp19FAHRBkTkgAAEI1IiAK/GsbGRJRMxOR+H22LN0FHZjkNQk5O67pRkzyqHZ6gL94Acl68Qr4znsMOnxx8s/Al1G7qwJAQhAAAJhEUAADKteeUVbJwHwQLODzf7v7ZJulPSlvMAWOG9SAfD3Jd3ajG+BpI/3idU+v675ub1n3Fw9CICuSDIPBCAAgRoQyCJ2+WjakMVRuL3caUTRqO3yOt2uGzSgE/VQ16GrNE9Xaak23nuCpvQ7R9Bjoaz3NiYRUKNyzfq5DyYoWXPgfQhAAAIQqD4BBMDq1zhOhnUUAC3nlpOu/WQ7KOnTkn4eB5iHY5IKgJc1xU9L5S2SbumT0x9I+nzzc3vPOgLjPibw9Xue3TQy0cMPP6zJk6OGx12WcRCAAAQgUDUCLo67+mzakNRRuLO+eQhiR2uv3q8leo+WaYz2j9hSuzRRRy9fqqP+/OKGK0nE4+rexjwEz6jY+32+aZM0fXqWGXgXAhCAAAQgkD8BBMD8GYewQvRPbCFkES/GVgegjW7P28TA/5X0z00x8OvxpvNmVFIB8L2SPtaM/nURXZD2eavr7ypJyxJk3RJZI19BAIxExAAIQAACtSbgyvCiyqYN/ToKs2yeKJMQzZwprVghnXZaz2WSCJT97m3M0gWahUG/d+kAzIss80IAAhCAgEsCCIAuaYY7V50EwO9LenGzVO3iVItB6/d+KOkGSf8oaXcApU0qAP6NpCXNvM6VdGefHM+R9LXm5/behxLwQABMAIuhEIAABCDQm4CZLdzSr189Jry6mDa0Ogp37pRe8xpp/8gGvpjEGsOiTEI0dqy0aFHj15FHDps7TceeHdnO0/QkUfJ9Bo8ZI+3axR2ArngyDwQgAAEI5EcAATA/tiHNXCcB0OpylqQBSXa01X5C7SYE2jj7/X2SPts89vo9j4uaVAAsqgMw6kwvR4A93lSEBgEIVJdA1vvXiiZj8U6cmF3EsrjraNrgSjw1flEmITr5ZGlwUDrH/v1QytKx13lvo6suUJf7ty6CsktmzAUBCEAAAuUQQAAsh7tvq9ZNAGzxP1bSO5oOtyc3f7NfV+C3m12BN0t60rMiJhUAi7oDMAoTJiBRhPgcAhCAgCMCru5fcxROomnsiKUdC3X11O3IpmvhzIS573/4dp103YD0UHeTEM2bp4PXLtWZ55ygrVvTV6793kaXQmb6iIa/WeUj5a4YMQ8EIAABCPhBAAHQjzqUHUVdBcB27nMk/bmk10saE9EV+D9NwxAzw/jPsovXXD+pAGh5/mvzXVyAPSkiYUAAAhDIi4Cr+9fyii9q3s2bpRkzokbF/7xupg0uDFRadIcdzd27V1qyRFq2rGt75v9OmKhLf7FUN+nijquX49fKRprINm2auy7QZKv3Hu2zqYyrHKswT2gdz1VgTg4QgICfBBAA/axL0VEhAB4i/pxmR+A7JU1q/narK7DTNMQ+trvzbpT0L1IXe7ziKplUAHyhpB83wzMh0zoCez32+aXND+29nzpMiw5AhzCZCgIQgEA3Aq7uXyuTLh2A2elnOYrbWt0Er1WrGmLcsGfLFunSSyVTVrs8GzRT87VC96m3SUi/DK3z75pr3HaBttYz82ITSJM+nceTk77P+HwJhNzxnC8ZZocABOpMAAGwztU/lDsC4Mh9MFrS+ZLmS7LuQGPU73jwI5I+2fy1vYRtlVQAtHy2SfpNST+SNKVPzGaIYj+xW17P7eCQNVUEwKwEeR8CEIBAHwJZRB+fBA6XdwDW2bQhjRhs28tMfhcvlmbNkkww6/qYy8jKldLChZIVrOP5tcbqI1o09OvJoSuY4z+jR0sW+7lmW+bosbn++q+lX/9amjtX2me3Psd8uhmUxHyVYQUQCL3juQBELAEBCNSUAAJgTQvfkTYCYP99YF1vdjzYzq8c1xzaqyvQPPZubXYFfqXA7ZVUALTQzOXY8rLnFZLu7hKvGaZ8q/n7Nv5yxzkhADoGynQQgAAEWgRcHPv06Yijq/vf6m7akEQcMT+PT32qIQDGfsx2+IorpDVrur5yv07WZRrUXWqYhMR9rr9eWmCXljh67F7CRx+Vli+X1q2LbzDTswvSUVxMk41AGpEbQTcbc96GAATCIYAAGE6t8owUATAe3cMlvbV5XPaVzVf6dQX+pOke/GlJu+ItkXpUGgHwFEl2Lbfdefgd+wd+Sb9si+AoSRsl/bakpySdnsOdhwiAqUvOixCAAAT6E3Bl/OCLyUHV8ilz/5o4vGFDQ/xau3a4+GUdktYRNzAQ0fEXkcB919+uI64c0InqbhKySvN0lZbqMZ0QC8WJJ0oPPxxfqOs3qTlBn3KK9EM74xDjsfEXXJCdSYylGJKBQFU6njMg4FUIQAACfQkgALJBjAACYPJ9cGZTCHy7pHEdr3feFfgrSZ+V9HdNwS35aiPfeJWkk9p++3hJ1zb/9zclfarjlZt6LPoRSQubn31P0t827wZ8kaT3SXpp8zMbd7WLwDvmQADMASpTQgACEDACVeuYq1pHoy+71E7rbt8u7d4tjR8vTZokTZiQPTq7t/HlU/fq/Vqi92iZxnS5KnmXJg6JgHFNQuwIsgmXWR8T9OzEctyHDrG4pMobx58P5bFnZQhAIBwCCIDh1CrPSBEA09E9T9J7m3cEWidg5z2BNmuLrX1uv/5J0l9LPf45PH4cJuhdFH94T5HX7jq0uwvf0Weuf2iagBxIsF7coQiAcUkxDgIQgEACAi7vzDOx5PHH3YhCCVLoOjSUDh9cRxvXAE6c2BDaztQWrdSlOkvdTULWa9bQseAokxBXAmCafejTnZhp4q/6O3QIV73C5AcBCLgggADogmL4cyAAxq/hsZIuaZqDtDrwogxCOoXAPZLeJWl1/GVHjHQlALYm/r2myPdySdZN+JikbzePMN+RIc6oVxEAowjxOQQgAIEUBKrsmuvrHV+4jo7cqO1dqKO1X5dqpT6qhXqG0pmEmBnIqafGP7qb4qvT9xWf7sR0nVvo81Wt4zn0ehA/BCDgJwEEQD/rUnRUCIDRxM0Mwwwz3iLpiI5j0+2GIPb/f615p96fNF1zbfZO0xD7338haXn00pUegQBY6fKSHAQgUBaBzZulGTPcrb5pkzR9urv5ss6UxMiiCNOGJPFMnSqtXi1Nm5aVgv/vd+vKerZ26uO6Qm9TOpOQW26RLrpI2ru3nPx9uROznOz9XLWqHc9+0iYqCEAgZAIIgCFXz13sCIDdWR4jyUQ8E/5e3BzSfqS39Zb9nv1TtnX0fULS/c0P7Hjt7ze7/ey4cKdhyJOSzmjeueeummHNhAAYVr2IFgIQCIRAlTsAWyUowsgiTrl97UiME3veY6xGJ50k/cRs0Tqe1+l23aDkJiEmRj/xRMOoJIkImPTev15s6uYiHcJx9jr8eZf3d5X5IQCBehBAAKxHnaOyRAAcTshEORP9WgYfnaYeNrr1e/c2u/hM/Ov3b9F2tNbEQfu/7fcFXte8RzCqRlX9HAGwqpUlLwhAoFQCLjtizBV21y4/7gDsBTUvI4uoIoZyJ2FUHnl+bh17Jpp1e45WcpMQE3umTJGSdF3a+PvvT2b80YuJT3di5lW30I6zV73jOa86My8EIFA/AgiA9at5t4wRAKXDm8d7L5P0yiakXt1+5hv3xaagd1eCLXSYpH+V9LttIqA5774swRxVG4oAWLWKkg8EIOANAe7EyrcUuI7G42vi7LHHSgf6WInFNQn58ZjThonRcbtATzhBsqPgrp6WCOlqvqh5iuzCSyKs+nKcnQ7AqB3E5xCAAAQaBBAA2QlGoM4C4Aubhh5m7HFcD+Gvxee/JH1K0qB9d1JunVMl/bBNALSjw89MOVcVXkMArEIVyQECEPCSAK6Y+ZYlZL5FCkpWhThidByTkH85fZHe8t1F0pFHjihuvy7QEDvEyujCC/U4e906nvP9k43ZIQCBKhNAAKxydePnVjcB0O7me0PzmK/dzWf59+r2M4qbm91+dlv1r+Nj7Tny55ImNte0fw8f42DOUKdAAAy1csQNAQh4T4AOtXxLFEfUihNBUXfKlSEotfJPIpZGmYTo5JOlwUHpnHPi4B0aE1qHWBldeKEfZw/t+xh78zIQAhCAgEMCCIAOYQY8VZ0EwL+R9GeSJjXr1Uv4+5Wkm5vC33cd1/b7ks5sCoB2H6AdDa7rgwBY18qTNwQgUAiB0P9SXwikFIu47Dgq4k65MgSldqxpxOgokxDNmyctXSrZ+d6Ix2W98r4Ts4wuvDT16URuR6y3bJFGlfS3iiQic7/tgstz1LeJzyEAgZAJIACGXD13sZf0n2p3CSSYyTruWiYc9lrLmbfF4KHmEV876rsrwbxJhtq9f+YqbGsiAEoPG7yHH35YkyebHsgDAQhAAAIuCZQhKLiM38e5Quoo86X+acToKJMQTZzYEAEvvjhSeXLVIXbeeZIxzeNJw6gVxzHHSBs3StOmJY+sCuJZFUTM5JXjDQhAAALJCCAAJuNV1dF1FABbtWzlNfMvUgAAIABJREFU/rVmt5+ZdPS5ptrJFrAOQBMA7UEARAB0sqmYBAIQgEA/Akk6wKyTZ9WqdEJCXaoQyp1yZQlKvfZBWjHyK0vv0Stumi9t2tR96lmzGseCTzut5xZ0JXKdeKL0k59E6o2JvwplCliuxNGijrP3guvbfk+8CQJ4oej7QwNAQogQCIoAAmBQ5cot2DoKgJazGXCslrRc0n250WXifgQ4Asz+gAAEIFAQgbiOqaallHWMryAUmZcJoQOwTEEpFzF6/35p5Upp4ULJVIjOZ+xYadGixq8uJiHG44UvlB58MHP5lccxUVcCZdLYXB6PLuI4e1T10orMa9dKc+ZEze7353mJc2XeH+o3caKDQHgEEADDq1keEddNALxX0g2SVknamwdQ5oxNAAEwNioGQgACEHBHoJ9jqrtVqjuTS9EkrzvlyhKU4lQ9kxi9c6d0xRXSGvNm6/L0MQmx47tfszMfGZ+4nW5JBJmyuvBCELOTlqtOHc95i3NJWE6dKq1eTfd40v3KeAgUSQABsEja/q5VJwHQLOPu9LcUtYsMAbB2JSdhCEAAAtUgUJZgE5ee7/G18kgtRt9+uzQwID1k1zd3eTpMQlyKtv063dIIMkXF1g1TKMfZ4+771rhMInPSxUoan7c4V+duypJKyrIQyJ0AAmDuiINYoE4CYBAFqVGQCIA1KjapQgACEKgSAZ877MoUlAqt8d690pIl0rJlkh0R7nzaTELu/eEoWYeSq8c656ZMaczW6vT7znca4fz4x9GrtHdLldmFV+ba0ZTcjEgtMrtZPpdZ8hbnuE8xl7IxKQRKJ4AAWHoJvAgAAdCLMtQyCATAWpadpCEAAQiET8DXO/aMbB1EnWE76J57pPn9TUK2DAzqJW/rbRKSdEfefbe0b5+0fLm0bl13/TFqTnPutbvnnvEMacaMqNHxPzevlOnT4413KRbndZw9Xib1GZW3OOfzn231qTKZQiAfAgiA+XANbVYEwNAqVp14EQCrU0sygQAEIFA7Ann/RTwt0Koe6+zLI8Ik5OCYsVry1CJ9RIv0pI5Mi/bp9046SXrggczTyETAm26S7Mi2q6e9OzHOnKEcF4+TS9XHFCHO+dzdXPX6kh8E8iaAAJg34TDmRwAMo05VjBIBsIpVJScIQAACNSKQ91G8NCh97wBMYo6ROP8dO6QFC3qahNyvk3WZBnWX7FpoPx47Snz//em6CDszSNOFh+Djxz6IE0URtUIQjlMJxkAgTAIIgGHWzXXUCICuiTJfXAIIgHFJMQ4CEIAABLwlkOQy/jPOkFatytcp08djnWnMMTIVPMIkZJXm6Sot1WM6IdMyrl6eNUvasCH7bHEdittXKqKrLHtmxc6Qq0idIZW8xTmXf3b0M8vJgIBXIQCBDAQQADPAq9CrCIAVKmZgqSAABlYwwoUABCAAge4EfHMdzVsoSLIPkgik7eYYSdboOjbCJGSXJg6JgDfpYknl/jjsSgC0DrHZs5OT8+E4e9miW+EidcIyFSHO+d49nBAZwyEAgQ4CCIBsCSNQ7k881KDOBBAA61x9cocABCBQUQI+uI4WcVQwTvm8OCIdYRKyXrOGjgXfJ3cmIXHYtI8ZPVo69VTphz9M+uah8dZdumWLNCrlT/Zl1MoX0a00kTpBuYsQ52p5f2iCGjAUAqETQAAMvYJu4k/5Y4KbxZml1gQQAGtdfpKHAAQgAIG8CPhwrNOHrrKn+TZNQva/d6EO2/uLEdif1OH6qBY6MwlJU9dbbpEuukiyxsWkj5mJbNyY/Wh5EiEs63H2JGs57QztgFuG8Jm0vja+CHGuCJExTe68AwEIuCGAAOiGY+izIACGXsFw40cADLd2RA4BCEAAAp4TcCHAmdvttm3Snj3SuHHS5MnShAnRifsgQHaNcscOPfLHC/TsDWu6flymScimTdITT0hz5yYTAU38W7tWmjMnui5xRhRxnN0X0c3Fd2TatDhUs48pQpxzecw4jSFNdkrMAAEI9COAAMj+MAIIgOyDsgggAJZFnnUhAAEIQKAWBNIKLR/4gGSC1Lp1w91p7WJ/E6gGBhp3zfU6burLEeReRX7g72/XUVcNaNL/PtR1SLtJiImgDzyQ/3YxgcccgZN0xmXtwovKKo/j7L6Ibt6K1D2KUpQ459P9oVH7k88hAIFkBBAAk/Gq6mgEwKpW1v+8EAD9rxERQgACEIBA4ASSCEovepFkwshPfhKddL9jmSGICAf37NXDf7ZEk25epsMO7h+R8O7DJ2r7FUv1xNyLddYr8v1xubNbqoguvOgKux/hk+jmu0jdjX4R36sQubjfqcwIgWoSQACsZl2TZpXvTzRJo2F8nQggANap2uQKAQhAAAKlEYgjKE2fLlnn37598cPsdvzUZaeSdRw+/ni8Y8fxo+4Yec89euqd8zXmO5u6TrH35bP0sm/naxJiws6a7qeSlUcXXmpWGV/0SVwqQkzLiGvE60Xw80mkdc2P+SBQdwIIgHXfAY38EQDZB2URQAAsizzrQgACEIBAbQl0E5TsiOvMmcnunmsB7DSgKOKuMufFa5qEaOFCDSluHU/eJiEm7NiR6l6PhZTmLkbnnDJO6IvoFpxI3eRelDjnyzHtjNuN1yEAgQ4CCIBsCQRA9kCZBBAAy6TP2hCAAAQgAAE1jvyeeaa0dWt6HHYX3ZYtjTsBi3ArTR9pxJs7dkgLFvRsx7tPp+gyDWq9znYWQju79kmtLuvXS8uXp7+L0VmQDibySXQLUqRu1qAocS7t/aEuDWkcbDumgAAE2gggALIdEADZA2USQAAskz5rQwACEIAABCS5PlYYsrjy9Ia4/faG08lD3U1CbtJFukpLtUvHZ95DJvDZUu1Pknsb+93FmDk4hxP4tC+CFqklFSXOJdmHeRvSONyKTAWB2hJAAKxt6YclzhFg9kFZBBAAyyLPuhCAAAQgAIEmAdfHMl12enWaYxRatL17pcWLpeuuG26F3AxilyYOiYA36eJMN+p0HqEuStwplKX86gz1SYxMW4eixLk494eagD1rVm9X8LQ58h4EIOCWAAKgW56hzoYAGGrlwo8bATD8GpIBBCAAAQgETMClWNdu2OFaVCwV8T33SPPnS5u6m4Ss16yhY8H36bTUYbaOAX/ve+7uYkwdTE4v+iS6udz3ZYrURYtzVTKkyWmbMy0EvCaAAOh1eQoLDgGwMNQs1EEAAZAtAQEIQAACECiRQF6ijOtjxSUiaizdNAn59ZULdfiv8jEJufNO6V3vcncXY+nMOgLwTXSrlEithnfN9u3S7t3S+PHSpEk5u2f7tsGIBwIQiCSAABiJqBYDEABrUWYvk0QA9LIsBAUBCEAAAnUhkNddaK6NRXypx00f3qGj/mqB3qY1XUPKYhJiRyg3bMieaZSjcPYV0s/gk+hWOZE6fVl4EwIQqAkBBMCaFDoiTQRA9kFZBBAAyyLPuhCAAAQgAAFJeXUAGtyi3EqLLORrXyv9279Jr9PtukEDOlHuTELMQdmE06yPiWxruuuTWafO/L5PoltVRerMRWICCECgsgQQACtb2kSJIQAmwsVghwQQAB3CZCoIQAACEIBAUgJ5H8uskqGFsTr2WOnAgQblo7VXH9BiXanrNEb7R6B3ZRKStKbtdzEmfTfv8b6JblUUqfOuIfNDAALhEkAADLd2LiNHAHRJk7mSEEAATEKLsRCAAAQgAIEcCOR9LLMot9Ic0Aybsle35It1j1Zovs5SfiYhSXOzWKdMSfpWMeN9E92qJFIXU0FWgQAEQiWAABhq5dzGjQDoliezxSeAABifFSMhAAEIQAACuRAo4lhm0W6leYDqd1/iaO3XfK3QR7RIz1A+JiFJcjLD4unTk7xR7Ni0ottnPiOdcoq0Z480bpw0ebIbo4vQRGrrRt22rcGh/XHJpNgdwWoQgEARBBAAi6Ds/xoIgP7XqKoRIgBWtbLkBQEIQAACwRAo+lhm2W6l7eJJEsEkzn2Jz9EOXa98TEKSbCifOwBbeSQR3V7wAsl+mUmKGTK3HjvuPHeuNDAgzZ4t2T2KaR/fRWqLb/16aflyad264Rzacx49WrrgAjdM0rLkPQhAwE8CCIB+1qXoqDL8p7LoUFmvYgQQACtWUNKBAAQgAIEwCfh2LNM1xX7iSVwRKcl9iXmYhMRlMmaMtGuXm864uGumHRclupmo98AD0oMPRq8wdaq0erU0bVr02KgRZYvUnfElEUvb33XJJIoZn0MAAv4TQAD0v0ZFRIgAWARl1uhGAAGQfQEBCEAAAhDwhEDaY5lr10pz5niSRJcwkognUYJJkvsSo0xCHtNxukpLtUoXSXL347jPLsD9dkmn6HbffdLb3y7t3Rt/bx1zjOT7foyfTWNkmu9l+xpVZJKUIeMhAIEGAQRAdoIRcPcTBzwhkIwAAmAyXoyGAAQgAAEI5EogiVh2xhnSqlVuOq7ySiqNeNJPMElzX2LRJiEWo3XOhfxUvSM1bm2ycOgUATdu9Pu7GpcJ4yAAgfQEEADTs6vSmwiAVapmWLkgAIZVL6KFAAQgAIEaEIg6ltm6c23WrGx3ruWNMot4YiJgN8Ek7X2JRZmEmCi7ZYvfdYmqe1rG7fPCYSTlKjCJ2jt8DgEI9CeAAMgOMQIIgOyDsgggAJZFnnUhAAEIQAACMQj4dhdajJCHhuQpImURFs0k5OO6Qm/V57umcp9O0WUa1HqdHTfVp8f1Ei0TT1TyC2m6LLuFHHonpCsO7WxCZ1Ly1mR5CARPAAEw+BI6SQAB0AlGJklBAAEwBTRegQAEIAABCECgPwFX4kkvwSTN0eL2iH9Pt2m5LteJeqhrIjfpoqH7AXfp+FilrtI9b0nuWewHJ9S7EFs5ueLQzih0JrG+DAyCAAR6EkAAZHMYAQRA9kFZBBAAyyLPuhCAAAQgAIEKE3AlnvQTTJLcl9gNtSuTkBDuYoy71ZI4LUfNae7Ojz8ehhtyZy4uObTPHTKTqHrzOQQgEE0AATCaUR1GIADWocp+5ogA6GddiAoCEIAABCAQLAGX4kmUYNK6L/FDH5K+9rV0yKJMQrYeP0tvfXxQ9x447ekFxoyRXv966fzzpSlTpPHjpcmTwxS72qnde69kTsyuHpvP+IT2uObQyThEJqHVkHgh4CMBBEAfq1J8TAiAxTNnxQYBBEB2AgQgAAEIQAACTgm4Fk/iikjr1kl//MfSL3+ZPJ0ok5CDhx+ux965SD9920Ld+5MjtXatdNtt0v79h9YysbJl0GIuwKMC/Al/82Zpxozk/Hq9sWmTNH26u/mKmsk1h/a4Q2VSFHvWgUCVCSAAVrm68XML8MeD+Mkx0msCCIBel4fgIAABCEAAAuERcC2eJBFM7Fjw294mPfBAOm5RJiE/PfwUvePX0SYh1kW3erU0bVq6OMp6qyzxtqx8e63rmkP7OnEFbd+YEA8EIJCdAAJgdoZVmAEBsApVDDMHBMAw60bUEIAABCAAAW8JuBZPtm6VTj89fromGJ51Vvzx3Ua6MAkJ0RjE5fFtOya9a1eYx6JdcmjfXyEzyfaN4m0IQMAIIACyD4wAAiD7oCwCCIBlkWddCEAAAhCAQEUJuBZP7L60z3wmfjedKwGyZRJy1ejrNPpA21nfZt0e03FDTsGrdFHPH+dNBNy4MX7sPmyJIgxcfMgzKgZXHNrXwQU4ijqfQ6DaBBAAq13fuNkhAMYlxTjXBBAAXRNlPghAAAIQgAAE5Fo8SdJN51KAtHv93vC8e/S+n87XWdrUtbLrNUuXaVD36ZBJSPtAcwnesiWcOwHvuks655zsm9jmsbsQQ31ccWjPP3QmodaSuCHgCwEEQF8qUW4cCIDl8q/z6giAda4+uUMAAhCAAARyIpCHeJKkm86VADlrlrRhgxRlEvKkDtdHtEgf1UI9qSNHUA1J+DFn5TPPlOzoddonNNGzW54uOIQsBKetPe9BAAK9CSAAsjuMAAIg+6AsAgiAZZFnXQhAAAIQgECFCbgWT1qo4gpLrgTIlgDYWj/KJOQ+nTLUDbheZw+rbmhHP81MZeZMae/e5Js0iVCbfPZi38jCoT1SX5lYt+y2bdKePdK4cdLkyWHe2VjsrmA1CKQngACYnl2V3kQArFI1w8oFATCsehEtBCAAAQhAIBgCrsSTzoTjdNO5ECDt7sH775f2j7z+T0lNQuwo8eOPhyWufOUr0ty5yUTAJEe1Q9nIaTh0in9r10pz5hz63TKFN/turF8vLV8urVs3fH/bPrWaDww0jm+P4m+poWxT4gyEAAJgIIXKOUz+aM0ZMNP3JIAAyOaAAAQgAAEIQCA3AlnFk26Bxe2myyJAmpB1000ausuw19MyCblS12mMok1CzJzERMWQHmM4b16848DWnblqVViGJ3FrkYRD+5ztTHwQ3pLkMXWqtHp1NesZt+6Mg4BrAgiAromGOR8CYJh1q0LUCIBVqCI5QAACEIAABDwmYKLDn/yJ9KMfuQkySTddGgGy1cX2jGdIM2ZEx/xi3aMVijYJWb3pNE2fHj2fbyNMuLJ7EK1jzDrZ2jsix4w51DFmx6Wr3DHWj0N7zWx/XnBBo4uuxcQH4S3Ld6G9e9G3/Uk8EAiJAAJgSNXKL1YEwPzYMnN/AgiA7BAIQAACEIAABHInYIYS1g3l6knSTZdEfGnv2LI1rAsqzhPHJOQXA4t0wrKF0pEjTULirOHDGDu6un27tHu3NH68NGlSWMeaXTFs59ASPU0g7MbEB+Etazfsxo3+dgKWeZza1X5invoQQACsT637ZYoAyD4oiwACYFnkWRcCEIAABCBQIwKbN8frpouLZNMmJeqmax2/vOYa6etfl+x/tz8m4rz61dIHPiCdfXajk82EhYkTu98B2CvOKJMQnXKKNDjYWISn8gR8EN5c3IcZ13ynqIL6cJy6qFxZp1oEEACrVc+02SAApiXHe1kJIABmJcj7EIAABCAAAQhEEkjSTRc5maQkHYA2X5IuwPa7z+wOwFtuiRPR8DFRJiG66CJp6VLp+OOTT84bQRDwRXhz5Ygdx3yniMKk/S4XERtrQCCKAAJgFKF6fI4AWI86+5glAqCPVSEmCEAAAhCAQMUIpOmm64XA7p3btSv+0dMsRzBtrXPOSVeMKJMQHXdcQwQ0MbDKl+elwxf8W74Ib2lF7M4CxDXfybNwWb7L3GOYZ2WYOy4BBMC4pKo9DgGw2vX1OTsEQJ+rQ2wQgAAEIACBChEoQ4jIegTTzC9Mn7M7DNM+F7zoHt1y/HyNsnPL3R5zilixQjr11LRL8J6HBMrY750YXArvScx38ihH1u+yz/cY5sGLOf0kgADoZ12KjgoBsGjirNcigADIXoAABCAAAQhAoBACRXdEuTqC+YlPSK97nfTLXybHZI7CQ8LDS/Y3RL5FixqXC3Y+hx/e+Gxh2CYhyQlV8w1fhLeyj967qq6r7/KWLTTbuqoJ86QjgACYjlvV3kIArFpFw8kHATCcWhEpBCAAAQhAIGgCRf8l3pXgOHq0dOBAcvQm/q1dKw07erhjh3TFFdLnP999whqahFTRxdUX4a1s853k35rub7j6Lvtyj6ErLswTHgEEwPBqlkfECIB5UGXOOAQQAONQYgwEIAABCEAAAk4IFHmMz9URzDSJm2vqqlXStGk93r7tNunyy6WHHuo+IMIkJHTRrOourr4Ib74IkWm+Q+3vuPou+3CPYVYWvB82AQTAsOvnKnoEQFckw53ncEkXSnqLpJdImijpfyVtl/RNSSsl3Z1DegiAOUBlSghAAAIQgAAEehMo4iJ/l0cw49bSDEPmzpUGBiS71i/S12PvXmnxYum666T9+0cu02ESUhXRLImL6wtfKP3t30qveU1805e49cpznC/Cm8vvQVLzHVd8XeZQ9j2GrpgwT7gEEADDrZ3LyBEAXdIMb67nSrpN0pkRoV8v6T2SDjpMEQHQIUymggAEIAABCEAgHoEkIlBkN12XJV0LMFFZHXWU9KUvSTNnRo3s8vk990jz50t9TEK2/sUKve39p8YyI5k6VVq9uk/3YYoQXb2SRvy1te0Y9gUXNMTV2bNjiKuuAk45j0vRKqvwFnr3nOvvss03ZUrKwvIaBDISQADMCLAiryMAVqSQKdIYI+k/2sS/LZKuk3SfpPGSXtUU/Y5pzv2Xkq5NsU6vVxAAHcJkKghAAAIQgAAE4hOwjjZz2V2+vHFXXnsTXOJuuo5lXR/BjJOVCZWpTQYs+T4mIU/qcH1Ei/RRLdSTOjIynK73D0a+le+ALMe/2yPzWeBsj9MX4S30+/Ncf5dNZ58+Pd+9zuwQ6EUAAZC9YQQQAOu7D94s6ZZm+t+S9GpJnWdAXibJPhsr6b8lPUvSU46QIQA6Ask0EIAABCAAAQikJ2AdU9u3S7t3S+PHS5MmZTvy6bprKG5mmU0GIkxC7tMpukyDWq+zI0N62oG41z2EkTO4G+DCAKY9Gh8Fzk5avghvLthnErczbiPX32U6ADMWhNczEUAAzISvMi8jAFamlIkTsW6/Bc233ijpX3vM8AVJc5uf2VHh/5t4pe4vIAA6Ask0EIAABCAAAQj4Q8DlEcwkWTkzGbjtNh28/HKN6mEScpMu0lVaql06vm94ZQo37YG5EsM6RcCNG/086mxx+iS8Zem+LFtIdvldznqcOsmfBYyFQDcCCIDsCyOAAFjfffAJSZc30z9D0tYeKOzY71XNz35b0ncdIUMAdASSaSAAAQhAAAIQ8IuAqyOYSbJyaTKw4fa92vT7i3WlrtOYEQdEpMd03JAIuEoX9f3rROauxCQAeozNqxa+CJy9EPkkvKW5f9GXTktX+8eZQO/gO8EU9SSAAFjPundmjQBY333wF5L+rpl+nA5AMwB5pqRfOEKGAOgIJNNAAAIQgAAEIOAXgTy6zuJk6OqIYUv0eLHu0QrN11na1HX59Zql+Vqh+3Vq18/LFj1cdnB1S9AHgbPfvvBJeMvbfCfO9yPNGFffZd/3Sho2vBMWAQTAsOqVV7QIgHmR9X/eEyQ9IGmCpG9KmtXlDsCXSrpb0uGS/knSHztMCwHQIUymggAEIAABCEDAHwIujmCmycaFyUCnaDZa+4dEPjMCeUaXfwfuZxLisisxDQ/Xd7h1xlC2wBmHiU/CW57mO3FYpBnj4rvse7doGi68Ex4BBMDwapZHxAiAeVANZ0672++zko6S9D1JH5d0v6Rxkn6n6QJsjsDfl/Q6SY8kSM0Evn7PsyV92wY8/PDDmjw5aniClRkKAQhAAAIQgAAESiaQ5Qhm2tBddAD2Es2eox36uK7QW/X5ruH1MglxEVNaHq5dXDvjKFvgjMvFR+HNtflOXBZpxmX5Lpd9j2GafHmnmgQQAKtZ16RZIQAmJVa98adLulLSO7pc4vKopL+VtFLS3oSp25HhWA8CYCxMDIIABCAAAQhAIDACaY5gpk0xqcmACTDbtkl79kjjxkn2b7ETJkhRotnv6TYt1+U6UQ91DbXTJMRFV2JaJnl3AFpcZQqcabiEJLylyS+vd9J8l325xzAvJswbFgEEwLDqlVe0CIB5kQ1j3rGSPiDpzyQ9q0fI1qW3WNJtCVNCAEwIjOEQgAAEIAABCFSPQJIjmFmyj3Mc1TrB1q+Xli+X1q2T9u8/tKJ1s82dK/3e70nvsH8W7vMcrb36gOKZhNx77yhNmZIls/Tv5n0HoEVWpsCZngxvpiGQ5Ltsx35XrfLXKTpN/rwTNgEEwLDr5yp6BEBXJMOb5xhJt0ua2bz7b5mkT0v6iaQjJc2Q9H5Jr5JkYt6CNtOQONlGnenlCHAcioyBAAQgAAEIQCB4Av2OYI4eLR04kD3FKJOBJOJF3GjMJGSlLtUMbe76yvpRs/Xb3x7UuJd1NwmJu06Wca5cXHvFEFoHYBaWvCv5eJyaukAgDgEEwDiUqj8GAbD6Ne6V4dLmHX/2+cWSVnUZOEbSv0k6W5L9aGqmIFscIcMExBFIpoEABCAAAQhAIBwCnUcwf/M3pd/5HWnr1vQ5RJkMpDm+GDeaKJMQHX64tGiRtHChdKT9G3OxjysX125RJz12XWzmrJY3AY5T502Y+V0SQAB0STPcuRAAw61dlsit7o9Jmtg0/ej3z7JmBvKN5mJmEmKdgC4eBEAXFJkDAhCAAAQgAIHgCeRpMpBl7iRgo0xCdMop0uCgdLb9u3JxjwsX117Rxjl2XVymrAQBCECgNwEEQHaHEUAArOc+sOO3O5up3yzpD/tgsH+q/WXz8y813YBdUEMAdEGROSAAAQhAAAIQqASBNF16USYDeYpfvaBHmYToooukpUul448vrG55iaBRx64LS5CFIAABCEQQQABkiyAA1ncP2E9cP2+m/8+S/qAPivGSftH8/FZJb3CEDQHQEUimgQAEIAABCECgGgSS3NMXx2Qgz+Ov/YifcPRe/eAPFus3PnvdcKeR1kvHHdcQAU0MHFVMP0IagbVfjlHHrovekb1cnYuOg/UgAAE/CSAA+lmXoqMq5r+4RWfFelEERkv6b0kTJO2Q9HxJT/V46fWS/rX52f+R9BdRk8f8HAEwJiiGQQACEIAABCBQHwIuTQbyNsDoVpVhXYn33CNdeqm0ubtJiGbPbhwLPrUYk5AkAmu/HWc5btxYvsNrHFfngQENYS5IZ63PF5VMIRAYAQTAwAqWU7gIgDmBDWDa/0/SHzXjvEbS4i4xH9u8/+/05mevbZqCuEgPAdAFReaAAAQgAAEIQKCyBLKYDNi7Eyd2b8DLC1jXrsT9+6UVKxpGIBZU59MyCbHPjzgir9CenrddYP3CF5I7MEcdu849geYCScTMqVOl1avLFyyLYsM6EIDASAIIgOwKI4AAWN99cJqk70o6uonAuvzMCfgnkuzev7MkXSHpec3PvybpPIe4EAAdwmQqCEAAAhCAAAQg0E7g3nslE35cPTfdJN16q7R27XBR0Zxw585Se83vAAAgAElEQVSVrNNs1qw+nWY7dkhXXCF9/vPdQzKTEBMKrV2toMf0SDsa/N73Sj/9afSicY5dR8+SfUSa48y+CJfZs2cGCEAgDQEEwDTUqvcOAmD1apokIxP0/klS1C3MdzbvCbRjw64eBEBXJJkHAhCAAAQgAAEIdBCwU7czZrjDsmmTNH16o4lv+3Zp925p/Hhp0iRpgl0qE/e57Tbp8sulhx7q/kYJJiEuj13HxZB2XBZDE1+OLqfNnfcgAIH0BBAA07Or0psIgFWqZrpcjpP0p013X/t34mc27wN8RNK3JdlR4S9KOphu+p5vIQA6Bsp0EIAABCAAAQhAoEXAdQegzTdliiO+e/dKixdL1/ljEtLKLLPA6QhRt2lcuDr7Zl6SIy6mhgAE2gggALIdjAACIPugLAIIgGWRZ10IQAACEIAABCpPwOUdgHbMd9euhJ1+cQh7ZhISJ+Qyx7hydbZ5CjxpXSYy1oYABJoEEADZCgiA7IEyCSAAlkmftSEAAQhAAAIQqDwBVy7ANs+aNTnh8swkJKcsnUwbRD2dZMokEICAawIIgK6JhjkfHYBh1q0KUSMAVqGK5AABCEAAAhCAgLcEguoY89AkxKfCuuzoPOww6fHHc+jo9AkYsUAAAsMIIACyIYwAAiD7oCwCCIBlkWddCEAAAhCAAARqQSDIO+M8NAnxYbN4faejD4CIAQIQ6EsAAZANggDIHiiTAAJgmfRZGwIQgAAEIACBWhAI0jXWTEKuuUa6/nrJjgh3PscdJy1dKplj8Kh69DPk5epciy8BSUIAAkIAZBMgALIHyiSAAFgmfdaGAAQgAAEIQKA2BL7yFWnuXMl0tbjPMcdIa9dKc+bEfSOHcd//vjR/vmTqV7fHnCwGB6VTT81hcb+mpAPQr3oQDQRCI4AAGFrF8om3Hv9klg87Zs1GAAEwGz/ehgAEIAABCEAAArEJWCfgvHnS1q3Rr5xxhrRqlTRtWvTY3EdgEjKE2OUdgLm5Oue+GVgAAhBISwABMC25ar2HAFiteoaUDQJgSNUiVghAAAIQgAAEgidgdwJu2CAtX97o7ms/XWuikHUJDgxIs2Z5eLIWkxDhAhz8V5AEIFAaAQTA0tB7tTACoFflqFUwCIC1KjfJQgACEIAABCDgEwHrKNu+Xdq9Wxo/Xpo0KRBX2BqbhATl6uzTZicWCECAOwDZA0MEEADZCGURQAAsizzrQgACEIAABCAAgZAJxDEJWbascea5QiYhQbo6h7zPiB0CFSJAB2CFipkhFQTADPB4NRMBBMBM+HgZAhCAAAQgAAEI1JxADU1CgnR1rvk2JX0I+EAAAdCHKpQfAwJg+TWoawQIgHWtPHlDAAIQgAAEIFApAnaceNs2ac8eadw4afLkAo8T20WG5gS8aFHjPHPnc/jhjc/s1xFHVIJ7sK7OlaBPEhAIkwACYJh1cx01AqBroswXlwACYFxSjIMABCAAAQhAAAKeEbDjqOvXNwxF1q0bbihy2GGHDEVmzy7oFK6ZhLz73dItt3Qndcop0ooVkgVUgSdYV2eH7EsVnh3mwVQQKIIAAmARlP1fAwHQ/xpVNUIEwKpWlrwgAAEIQAACEKg0gSTi09Sp0urV0rRpBSEpwSSkLCEqaFfnlNvBO+E5ZR68BoGiCSAAFk3cz/UQAP2sSx2iQgCsQ5XJEQIQgAAEIACBShEI4vhpASYhZQhR/YTGYF2dE3w7vBaeE+TBUAiUQQABsAzq/q2JAOhfTeoSEQJgXSpNnhCAAAQgAAEIVIJAcAYUOZmE5CFE9RL3kgqNZXUj5r3BgxCe84bA/BDIQAABMAO8Cr2KAFihYgaWCgJgYAUjXAhAAAIQgAAE6kvAhKgzz5S2bk3P4IwzpC1b8rsTsKv4dUwMk5Crr5YWLoxlEuJSiIoS9+y6wh//WHrwwWjmJ54ovehFjXsZzRel9ZRyH2N0uIlGBCc8J8qOwRAohgACYDGcfV8FAdD3ClU3PgTA6taWzCAAAQhAAAIQqBiBu+6Szjkne1I2j0sfjn4i2ujR0hve0PAGmX3KDo26IptJiEshKkkXYXbqjRkKv4/RQeAhCM8O0mQKCOROAAEwd8RBLIAAGESZKhkkAmAly0pSEIAABCAAAQhUkcBb3tLbYDdJvjbPmjVJ3ug9NomIZh1yZhD8sp23SpdfLv3sZ90nvugiaelS6fjjh33uUoj66lcbLsl2VWHRzzHHSGvXSnPmFL1yuvV8FZ7TZcNbECiPAAJgeex9WhkB0Kdq1CsWBMB61ZtsIQABCEAAAhAIlIAdrZ04cfjR0rSp2JHUxx+XJkxIO0PjvTRHcUeNkj7xCWngor3SNddI11/fPanjjpOWLZPmzXv6vLIrIWrFCunKK8sR/1rETQTcuLFAZ+YMpfZReM6QDq9CoDQCCIClofdqYQRAr8pRq2AQAGtVbpKFAAQgAAEIQCBUAvfe2zg+6uqx+aZMST9blqO4tury5dLAgKQEJiGuhCgTPk1QLfvJ+z5GF/n5KDy7yIs5IFAGAQTAMqj7tyYCoH81qUtECIB1qTR5QgACEIAABCAQNIHNm6UZM9ylsGmTNH16uvlcHMW1uwEtp5e9TI0OwMFBadEiaffukUEdfrh+9Z6rNfFvF+qXB45IF7Snb7m+j9F1mr4Jz67zYz4IFEkAAbBI2v6uhQDob22qHhkCYNUrTH4QgAAEIAABCFSCgE9CjKujuC94QcNh144FDz07djTcQuyiwC7PfTpF87VCGzS7EjW1JFzex5gHFJ+E5zzyY04IFEkAAbBI2v6uhQDob22qHhkCYNUrTH4QgAAEIAABCFSCgMujmGPGSLt2pb8D0NVRXCtM1w64W/ubhHxaF+u9ula7NNwkJMRCu7qP0WXutte2bZP27JEeeUQ6/3x3s2c9eu4uEmaCQPEEEACLZ+7jigiAPlalHjEhANajzmQJAQhAAAIQgEAFCLgS3rJ0nbkUIq0kb3pTwxF3xGP2vH1MQh7TcXqPlmm15kkK+69TPohidqx7/frG3Yzr1rkxm+msaVbhuQJfYVKoOQEEwJpvgGb6Yf8XixqGTAABMOTqETsEIAABCEAAArUi4OrobZZ751wfRY7sgIswCblLs3WZBnW/Tg12L2S5j9FF0mboYmbLW7e6mK33HFmE53wjY3YIFEMAAbAYzr6vggDoe4WqGx8CYHVrS2YQgAAEIAABCFSMgAvzjazOs67vhLMSRXbANU1C9l2xSEc/NdIk5Ekdrg/ran1UC/VrhWcSEpl/jvv4K1+R5s6VrOEy7+fOO6Wzz857FeaHgL8EEAD9rU2RkSEAFkmbtdoJIACyHyAAAQhAAAIQgEBABKxba+bMdILNMcdIGzdK06alT9h1B6BFErcD7puf36Edb3233qLqmISUeSw2y15Ks4MQANNQ450qEUAArFI10+eCAJieHW9mI4AAmI0fb0MAAhCAAAQgAIHCCaTp2jLxz+7amzMnW7h2B+Cxx0oHDmSbp/3tuB1wrQ7IE7fequW6XM/Xz7oG0c8kZMIEyXLw5SnrWKyLbtKkDMvKNWmcjIdAXgQQAPMiG9a8CIBh1atK0SIAVqma5AIBCEAAAhCAQG0IJLm3zY79rlqVrfOvHawZd/zLv7hBnbQDrtW1dnDvXl2ja7RA12uM9o8IpptJiImgy5ZJl13mJnYXs2S5jzHL+q7uk0wSQ+R9j0kmYywEAiSAABhg0XIIGQEwB6hMGYsAAmAsTAyCAAQgAAEIQAAC/hGwLq4NGxrOrdbdZ1fltR4T1uxut4EBadYsaZTDv3G4FI/SdIW1d0C+RN/XCs3XDG3uWqCWScj2Y04dYnTeedKZZ+ZveBFnt2S9jzHOGr3GuHKUThpD3G7PpPMyHgIhEEAADKFK+cfo8D/H+QfLCpUigABYqXKSDAQgAAEIQAACdSVgx1q3b5d275bGj5cmTZLsuGsejwmPL3yh9OCD2WdP2wHX3gE5WvuHnIA/okWaoJEmIb8edbgeu/Rq/ebfLZSOOEJF333XjZKL+xjT0re9MnHicME47VxJ34t732PSeRkPgRAIIACGUKX8Y0QAzJ8xK3QngADIzoAABCAAAQhAAAIQSEzgu9+VXv5yycTAtE/WDrjODshn7d+hv1NvkxCdcoq0YoU0e7bS3KOYNs/O91zdx5g2njyMXOLGQgdgXFKMqyIBBMAqVjV5TgiAyZnxhhsCCIBuODILBCAAAQhAAAIQqB2BG26QLr88XdquO+DaOyCf891bNekjl2v0w91NQnTxxdK11+o/fna85s2Ldxz46KOlffvS5dr+lnVlWtdjFifmrFFs3izNmJF1luTvJ73vMfkKvAEBvwkgAPpdn6KiQwAsijTrdBJAAGRPQAACEIAABCAAAQikJmAi4LvelcwVuJAOuL17pWuuka6/vvtZ1+OOG3IEOXjhPG3YOKrvPYoXXSSdf76bI7M+GGGU1QGY5r7H1BuTFyHgIQEEQA+LUkJICIAlQGfJIQIIgGwECEAAAhCAAAQgAIFMBOw48B/8Qbw7AV07EncGbp2A27ZJe/ZI48ZJz3v8+xr3nvmStb11e2bPlgYHpVNPVa97FF0LZmUfgy3rDsC09z1m2py8DAGPCCAAelSMEkNBACwRfs2XRgCs+QYgfQhAAAIQgAAEIOCCQOs+vo9/XLr11uIciS12W3v9+oYb8rp1w9e2jrs3v2m/PjhpUCd/epFGmUtK53P44dLVV0sLGyYhnY/rI7M+GGEU7QKc9b5HF3uUOSBQNgEEwLIr4Mf6CIB+1KGOUSAA1rHq5AwBCEAAAhCAAARyJFCkI3G7G3BUSrNP2aEvPPfdOvZrt3QfeuqpjW5A6wpse6rWAWipWTfeOedEEXPzuev7Ht1ExSwQKJ4AAmDxzH1cEQHQx6rUIyYEwHrUmSwhAAEIQAACEIBA5QikcfI1Merr77tVL/3U5dLP+puE6Pjjh5i5PDLrixGGdU2eeWY8A5QsG6eQ+x77BNh5JHzyZMmMWHggUAYBBMAyqPu3JgKgfzWpS0QIgHWpNHlCAAIQgAAEIACBJoEqiCLW+TdzpmReH0kfE6W+8eW9+q110SYhQzbBo0bJ1ZFZn4wwsjCMwzzv+x57xRB1JHzuXGlgoNHoOYq/iccpJWMcEUAAdAQy8Gn4YyfwAgYcPgJgwMUjdAhAAAIQgAAEIBCXQJVEERfda0/fSXfP96X50SYhd+041cmRWd+MMNJ2UZrBst1luHZtsfc9Ru33JEfCp06VVq+Wpk2LmpXPIeCGAAKgG46hz4IAGHoFw40fATDc2hE5BCAAAQhAAAIQiEWgaqKIq/vrnhbj9u9v3P23aJHUwyTk4KKrNW3NQn3/hyNNQmIVQZKvRhhJ9kdnV1+R9z1GcU4rZpqIOWdO1Ox8DoHsBBAAszOswgwIgFWoYpg5IACGWTeihgAEIAABCEAAArEIVFEUye047o4d0rvfLd3S3STkV88/VXMfHdSXfjXcJCROIVwbYbg+xt1ycTYnZd+6+uLwzXKc2XVt4sTLmHoSQACsZ907s0YAZB+URQABsCzyrAsBCEAAAhCAAARyJlBFUcSlIcdhh0mPP97FFOLWW6XLe5uE/OOYi7XgqWu1Sw2TkKjHlRFGUce4ferqi2Jrnzs9Es7fzOMgZ0xKAgiAKcFV7DX+mKlYQQNKBwEwoGIRKgQgAAEIQAACEIhLoKqiyL33SnZ3m6vH5psypcts5i5iF91df/3wS+6aQ//7sON0xf5lWq15knr/de7kk6VPfaphWJLlSXJMt2532zk/Ep6lULwLgT4EEADZHkYAAZB9UBYBBMCyyLMuBCAAAQhAAAIQyJFAVUWRzZulGTPcgVu1SkNGvz2f/5+9OwG7q6rvvv8NiQTMYEtwTFKtVCCGtJqWxFZJYjBap2JQfDtIBK0MEYXWCghtQXspCjJoDSGt1iba52kpQwDt07coJHFMULGpQWvVx5KkvlUSq0mY9A7vtXLOTU7u+wx777P22cP5nuvqVcy999prfdY+hPyy1vp/vXuRkG88eQmv33UD39x/XMcmwkrDfirP1nEbd7wZpJYVmmP62FZ5BAwAyzMXRfbEALBI/eF+tgHgcM+/o1dAAQUUUECBmgrkdk5ewV6xVwAeeSTcdluPIhA9ioTsf8Lh/OW0S7hw98U8SvciIWlX59VxG3fMV2ggW8Jjdti2hlrAAHCop//xwRsA+h4UJWAAWJS8z1VAAQUUUEABBXISqHMoEnNso/yJi0D0KBLyLY7jHG5gI92LhCQ9E7Cu27hjvvaxA+GOW8Jjdtq2hlbAAHBop/6QgRsA+h4UJWAAWJS8z1VAAQUUUEABBXISqHsoEmt1Yyv/CSfA1q0wIcmfzHoUCfk4Z/BOuhcJSRI61nUbd8zXPvaW8M2bYcGCmD20LQUOChgA+jYEgSS/zSilQB4CBoB5qNqmAgoooIACCihQoEDdQ5FYwdjYKQrtLum+eO/xWx7bu4+/fdblnL7rWiYxMm62H2AG76B7kZBeoWOsoDO0c+ONBb6QOT667mF3jnQ2XYCAAWAB6CV8pAFgCSdlSLpkADgkE+0wFVBAAQUUUGB4BOoeisTYGtvubUgTlI2GkL/G11nD2SxkS9sX7G6WHNgW/G3aFwnpFDrG3OocipDs3g3Tp9fvOxDTadIk2LWrnk71m/lqjsgAsJrzFrvXBoCxRW0vqYABYFIpr1NAAQUUUEABBSoiMAyhSD/FMTpNY5qgrHV13mGMHAj5ruBdTGfPuOYf4XDexyW8n/FFQjqFjnUPcWN+lVwpGVPTtvIUMADMU7c6bRsAVmeu6tZTA8C6zajjUUABBRRQQAEFgNe8plHdtt9PmlVx/T4r7f133gmnnAIPPZT2zs7XJykC0SlgfQY7uY4LOI2b2j6gXZGQTqFj3bdxx5sxiLUlPM0W8Cz9D+/Njh2wdy9MnQqzZrnaMItjle8xAKzy7MXruwFgPEtbSidgAJjOy6sVUEABBRRQQIHSCoStsRs2wKpVcOutsH9//13NOxTpt4cXXghXXdVvKwfvT1IEotfqvFfyKVbxVp7J/W07NrZISLvQsdcz0o44SbCZts2yXB/e+3CeYhhj1k+v8xizttv6nVy/HkZajosM4e/y5bByZePsyUQFaLJ2xPtKIWAAWIppKLwTBoCFT8HQdsAAcGin3oEroIACCiigQJ0EwpbYFStg27Z4o8orFInVwzDmF71o8CsAk6zOeyL7uJzL+SN6FwnZvHnCuMqzw7CNO+Z78PrXw3e/m63FJBWZs7Sc5js5dy6sWwfz52d5kvdURcAAsCozlW8/DQDz9bX1zgIGgL4dCiiggAIKKKBAxQXCVtiwkmjfvngDySsUidXDPAqBJC0CkWZ1XpIiIb/06Rs45hXji4SU4Wy7sm9b7ffdD+95WC27bFmsN7PRTpZ+5dWXuCOztX4EDAD70avPvQaA9ZnLqo3EALBqM2Z/FVBAAQUUUECBFoE8imFUIYiIde5b68uU9LzDtKvzehUJeezww5lwySVw8cUwefLjXYo1xrTbuHttWz35ZHjb2+CVryx222q/7/4xx8CNN8ZfdddPv8oevPsv3/4EDAD786vL3QaAdZnJ6o3DALB6c2aPFVBAAQUUUECBAwJ5rIIL237Xro0fisSeslir41r7lSYoy/L8XkVCOO44uOGGxoFwkeY37TbuNNtWp0+HK6+Es85KHwT2u7Iwxruf1ibJO1zWfiXpu9fkL2AAmL9xFZ5gAFiFWapnHw0A6zmvjkoBBRRQQAEFhkAg1gqxUIzg1FMbxQgWL04f5gyaOu0KvCT9SxsG9WPfq0gIZ5zRqGxy9NEMcjVZlm2rwfaZz4RbbukdGvdaWZimIEY//llD3yTvUVn7laTvXpO/gAFg/sZVeIIBYBVmqZ59NACs57w6KgUUUEABBRQYAoEsq9DasbzmNY1z0KrySXMGX5IxHXkkfP7zvQOs1rb6Xek1hb385dHv5owfX8uE1tKwow+ZMQOuvvpAZZc7PzMh9RmPabdx9xM0hi4fcQTcfnvns/TSrCwcWxCj3WrBN78Zbropyex2vybptu+kT4r1nYzdr6T997p8BQwA8/WtSusGgFWZqfr10wCwfnPqiBRQQAEFFFBgCARiroILKwB374awpbMKnyRVeNOM48Mfbpxpl/bTT2j2+Flvh30dzj4bwqDafcJ24Btu4Gv7jktc5TntNu5+w8zRbj/xifC5z40PUrOsLAxtXX45bN4M69dDa0Ya3td2mWna+QvXx3z3h/k7mcV+GO8xABzGWR8/ZgNA34MgcDTwJuAU4BjgF4FdwHZgE3AL8KXIVAaAkUFtTgEFFFBAAQUUGIRA7FVwob05cwbR8/6fUaaxZwm3xq3OC2lWOPvvXe+CPXvGAx1+OFxyCY9ddDEbvzyZVasaKzZbQ7BQwXh0C23abdyxtq2Gjo/dSt1PSNr/m5KshVjvfpney2Qj96pBCxgADlq8nM8zACznvAyyV6cBq4EZXR56G/CayJ0yAIwManMKKKCAAgoooMAgBGKvggsrrRYsGETP+39GzJVWITjbtau/1Y9ptrd2XZ23cydccEHnva0tRUJ27IB774UHHjhwVCDPfz7MCv9ln+ETa9vq6KPvugte/OJ8itRkGF7PW2K9+8P8neyJ7AUHBAwAfRGCgAHgcL8HK4CPA4cBP2wGgZ8HdgNPa64GfDXwEyAEhTE/BoAxNW1LAQUUUEABBRQYkMCwrzaKFVrFOmstbKPduJE4q/M+9Sl461vh/vvbvk13PfMMfm/7Vfxwf9hA1PiEraxpimiM3hczTB1tM2wlD6sKf/ITWLp0QF+IPh7jCsA+8Lw1lYABYCqu2l5sAFjbqe05sLDR4l5gMvA5YDToa3fj4cCjPVtMd4EBYDovr1ZAAQUUUEABBUohEDO4ibEKbtAosbathnbCMXsxP2FuwmK+sJt32jSYOTPDCsO9e+Hd74Zrr2174N0DzOAdXM06wlqCQ/84ObaIRrexxQ6SR58VtjnPn984E7DMn5jv/rB/J8s8z2XpmwFgWWai2H4YABbrX+TTPwOcDDwAhDAw/P9BfgwAB6ntsxRQQAEFFFBAgYgCZVsFF3FoPZuKUbhi7Hl1PR9axAVf/zo/+d2zeNK/39P26XezhHO4gW9z3CE/T1oFOPa21SKI+nlmrBWgo30Y5u9kP/MwLPcaAA7LTHcfpwHgcL4HxwPfbA79cuDdBTAYABaA7iMVUEABBRRQQIEYAmVeBRdjfL3a6KfAxONVeOf3ekqxPw9jXHLSCCseXM37uITpjC8S8giHH/jZ+7mYRw9sLGp8uo0xBKgbNsAVV0AoZDKsn9grQIf9Ozms71HScRsAJpWq93UGgPWe306j+zPgPc0fzgXua/5zqP4bDvQIZwCGKsB5fgwA89S1bQUUUEABBRRQIEeBoVkF18UwShXeHOeon6bHzu8z2Ml1XMBp3NS22W9x3IHVgBs5uKe53SrHNEVL+ul/2e/NYwWo38myz3qx/TMALNa/LE83ACzLTAy2H58GXtEs7hFCv98HLgR+taUb/xdYC1wN7M2hewaAOaDapAIKKKCAAgooMCiBYVgF18syTaDVtQpvrwcN+OedVpO9kk+xirfyTNoXCfk4Z/BOrmLXgTUFjYIco+ccZglMBzzsgTwuzxWgficHMoWVfIgBYCWnLXqnDQCjk1aiwRDuPQv4VyBU/X1rl15/A3gZ8F8pRxYCvm6fUGX4wIEi27dvZ9asXpenfLqXK6CAAgoooIACCuQukCXUSXpGXO6dj/SAqFV4I/Wp32a6nSc3hb1cxrv5I65lEiPjHtVaJOS00yZw443QTzDV71jKdH/e7354Fz/4QXjXu9rWb+lIkXe/yjQHw9oXA8BhnflDx20AOJzvwU+A6cAjzSrA/wNcDNwC/BSY19wi/PImzxeBk4D9KbgeS3qtAWBSKa9TQAEFFFBAAQXKJ1DXVXBZpKNU4c3y4Ij3JK0o+2t8nb/iLBY0/k5/3OcuXsxbD7uBL+8+lhe+ELZti9jJCjaV9wrQNN/DVr68+1XBqapllw0AazmtqQdlAJiarBY3/ByY2BxJ+Gu7FwFfHjOyw4BPAaMh4GnQ4dCP9iQGgLV4VRyEAgoooIACCijQW6COq+B6j7qeV9x3H8wNp4Qn+BzGCOfSvUjIfadcwgtuO7RISIKmK3fJhAkQ/m9/y5KJSZNg+XJYuRIWL278PI9PlpW4EyfC+98P73hHfv3KY6y2mU3AADCbW93uyulfQXVjqt14wpl+U5qj+nvg9zqMMPzWH7YAh09YHfjaFBK99vS6BTgFppcqoIACCiiggAJVEajDKriqWOfRzy1bYOHCdC2HIiEf4nxex81tb2xXJCTdE8p/dTjRaPVqePazYe9emDYNZs6E6WHfVY6ffrZX53keYY5DtukMAgaAGdBqeIsBYA0nNcGQfgCEAC583gis63LPDmBmOKoP+KUEbSe9xCIgSaW8TgEFFFBAAQUUUECBAQmkWQE4tkuv4g4+wnmJi4QMaEgDfUxYPbluHcyfn/9jrfybv3FdnmAAWJeZ7G8cBoD9+VX17i3Aic3Onwzc1WUgXwJe0Dwv8IiIAzYAjIhpUwoooIACCiiggAIKxBBIegZgp2elKRIC+f5xdNEi+OpXYd++GDLJ2xhUUY1O1ZqT97RxZWu15rT3en01BAwAqzFPefcy33/j5t17288q8HHgjObNLwXu7NLQaFgYftucmvWBbe4zAIyIaVMKKKCAAgoooIACCsQS6FYFOOkzQpGQv59+Fsf/tHORkHO4gf/g2KRNpr4uBFthC+7pp0NY2TjIzyC218aYp2AS2gnVmv3UV8AAsL5zm2ZkBoBptOpz7ZnA3zSHcy5wQ5ehPQDMAL4NHBeRwAAwIqZNKaCAAgoooIACCjhdCI8AACAASURBVCgQSyDWyrK//dgI97y5e5GQ93IpH+AiHmVyrO4faCdUt926tVHg4q674OSw72nAn9Y+xH50vys1W/sTCoLs3p3/eYWxDWwvuYABYHKrOl9pAFjn2e08thDohXMAn9Bc/RdWAbb7LAY2NH/wMeAPI3IZAEbEtCkFFFBAAQUUUEABBWIJxDpb7vOfhxkz4KkjvYuEnM0aNhH++NH/Z+zqu1gr5bL0LK/ttf2c1dhuHKG9OXMO/iQEjDt2NAqaTJ0KochJ3gVNsvh6TzIBA8BkTnW/ygCw7jPceXzXA2H1X/iEKsChGnDrZxqwCXhe8xcXAO3X72czNADM5uZdCiiggAIKKKCAAgrkLhCrumxr+DaIIiFjz9+LuVIuC3qv7bVZg7Ys1Zq79X/zZjjxRNiwAVatgvXrYWTk4B1hleDy5bByJSxZ0lhZ6ac6AgaA1ZmrPHvq1zZP3XK3/WTgK83Kvj9vbgO+BfgpMA+4CDi+OYTVwMrIwzEAjAxqcwoooIACCiiggAIKxBS4885G6JO2iMZhh8GppzbCorCasHX7bSgScjmXcwHXMYmWhKnZ8QeYwTu4mnWsIG2RkLDldu3aQyvwxl4pl9a33fbaYNJv0BZ7XDfdBJddBtu29R7hICsd9+6NVyQRMABMolT/awwA6z/H3UYYFnnfDvxKl4vCWYHnAD+LTGUAGBnU5hRQQAEFFFBAAQUUiC0QVgKuWJEsGGr37Oc+Fx55BL773UN/+jzuZQ1ns6DDJqO7eDGjRUJC4PSXfwnXXw+33jp+ZdpLXgKnnAKh6u/s2YduVY29Ui6Lb+v22jSe3YK2mCsbQ0g5eTI8+GDy0Q2q0nHyHnllNwEDQN+PIGAA6HswpbkV+HXAc5qVfn8IfAFYE6rC50RkAJgTrM0qoIACCiiggAIKKBBTIKxY27ixsTX0lltg//50rR9xROP6hx8+9L7DGOFcuhcJueoJl/LKTRfx/Bc0ioSMbpkNK+huuw0++9nuW1W/+U0IQVqRn7C9dsECyLKislvQFutswxAAtm73TWo1iErHSfuS53VZt2nn2ae0bRsAphWr5/UGgPWc1yqMygCwCrNkHxVQQAEFFFBAAQUUaAqE1WsnnZRupdgoXggBw7lxDz00nvMZdC8SwnHHwZo1sHgxaVfQXXUVvPrV2QKuWBMfVgCGcYcVimm3U4c+dAraYlVr7meceVY67qdf/d4bY5t2v32Ieb8BYEzN6rZlAFjduat6zw0Aqz6D9l8BBRRQQAEFFFBgaARiVAY+5hgIQWCnc+Z6FQnZ+bIz+c3PXcX2B2dUxn3SJHjgAXjhC7Nvow6DbRe0xZiTGJB5VTqO0bcsbaQNmdetO/TcySzPzPseA8C8havRvgFgNeapjr00AKzjrDomBRRQQAEFFFBAgVoKxFptdtddjZWAYTvx2PP8Qlj2u6/ey/uecDmzbr6OCW32pf6Iow8UCfkEp1fiRKuwTffcc2Hp0v5fi3ZBWz/VmrNu/R07kl6Vjvsf+eBaiL1Ne3A97/4kA8CyzESx/TAALNZ/mJ9uADjMs+/YFVBAAQUUUEABBSolEOu8udawKJyttnMn7NkD06bBzJktBTzuvRfOPhvuuaetU2uRkDJDhtAuhJ2hym6/n05BW9bQKmxLTnueY7sxtKt03O9Yi7i/nzC17OchGgAW8UaV75kGgOWbk2HpkQHgsMy041RAAQUUUEABBRSotEDsirO7dx9aqbcjTlgBuHo1P7/oEiY9uGfcZY9wOO/lUj7ARTxKo0hImT5h2+7nPw8zZsQ5g7Bb0JZm22ro12WXQQgUY31aKx3HanOQ7cTYTl3m8xANAAf5NpX3WQaA5Z2buvfMALDuM+z4FFBAAQUUUEABBWohEMKdmJV004ZFZ79qJ8s+fT6v4+a2nt/iOM5mDZtYXBrv0RVh4czDQdm1Vmtut716+XJYufJALZUDCysXLozHNVrpOF6Lg20p1hb3sp6HaAA42PeprE8zACzrzNS/XwaA9Z9jR6iAAgoooIACCihQA4EtW4oLi1pXH/YqEvI3nMk7uYrdFFskJIR/IYBbtgyKsuu6vRooOtQt29cijy3uZRqjAWCZZqO4vhgAFmc/7E82ABz2N8DxK6CAAgoooIACClRCoMiwaOyzp7CXy7mcC7iOSYyM8yu6SEjYBrp27cGqsLEDwLSrJzu9YDG3dYfiLbt2JdzWXcI3PqZFWc9DNAAs4YtXQJcMAAtA95EHBAwAfREUUEABBRRQQAEFFKiAQMyAJG1Y1ClAex73soazWUDxRUJC6HPqqQe314Yp3bDhYKXjGIU2Qptp7Xq9WnVf9dZr/KM/LzLgTtrHfq8zAOxXsB73GwDWYx6rOAoDwCrOmn1WQAEFFFBAAQUUGEqBosKibuHMYYxwLqt5H5cwneKKhISQ8sQTG69FmmIcaV+kTlWA07Yzen3dz71L6hJ7lWYZz0M0AEz6NtT7OgPAes9vmUdnAFjm2bFvCiiggAIKKKCAAgq0CBQVFiVZffgMdvIhiikS0roq7847IRTa2Lcvn1cndoGJule+TToLrgBMKuV1VRcwAKz6DFa3/waA1Z07e66AAgoooIACCigwZAJFhkVJVx8WUSRkdFVeWPm3aFF+4V84W3DrVpgQ+U/w/fR7tNLx/PnV/jIkCZmTjjDGNu3Qnx07YO9emDoVZs3q/3xFVwAmncF6Xxf5Xx/1xnJ0UQUMAKNy2pgCCiiggAIKKKCAAvkKFBUWpVl9OOgiIaFvixfDvHmwbVs+/nkHbVlWLrZWOs5n1INtNWnI3KtXWbdph4B99NzI9ethpKW+TThjMqwsXbkSlizJFgIbAPaaueH4uQHgcMxzGUdpAFjGWbFPCiiggAIKKKCAAgp0ESgiLMqy+nAQRUJGV+WF4Gbp0nxem0EFbWnOLhxb6bjdyPNYxZaPcKPVNCFzt35k2aadxn7uXFi37mCV6aQmBoBJpep9nQFgvee3zKMzACzz7Ng3BRRQQAEFFFBAAQU6CKQJLJKERUmgs6w+zLNISOuqvFirx8Y6xLJL4huuCUHrxo0Hqxe3rkILW1tHV6GFFY/ttiLnvYot6TiyXJclZG43X2m3aQ8qUDcAzPJW1O8eA8D6zWlVRmQAWJWZsp8KKKCAAgoooIACCowR6DcsygKaJSwJz4ldJKR1VV7M8+NCX5MEbVns0t4TxrVzJ+zZA9OmwcyZ3c+hSxMKZ13FlnYMaa/PEjKPPiPLNu1BPs8AMO3bUM/rDQDrOa9VGJUBYBVmyT4qoIACCiiggAIKKNBDIG1Y1A9omqBp7HNiFAkZuyovdgXZLVvgxBP7ERr8vVmC2UFtbU6rMaixDHrFoQFg2jehntcbANZzXqswKgPAKsySfVRAAQUUUEABBRRQoGQC3VYf9upqryIhPzn8aM7/2dWsfex0oPHH5W6r8kJgt3Bhr6cm//nmzbBgQfLri75ykKvYBjXWNCFz1m3agz5z0ABwUG9PuZ9jAFju+alz7wwA6zy7jk0BBRRQQAEFFFBAgQEIjF19+KMfNaql9qrIG4qErDvybOY9dE/bXu5b+GK++yc38IS5x3bd/hp7BWBob86cAcBFeMSgV7FF6HLiJvLe4h7r3MikVYcNABNPfa0vNACs9fSWenAGgKWeHjungAIKKKCAAgoooEA1BRKHNy8aYcINq+GSSxqH3Y39HH44XHopXHQRTJ7cFiPmGYBhpeGuXd3P2ivTjAx6FVtRY4+9xT3mOzNxIuze3fudMQAs6u0p13MNAMs1H8PUGwPAYZptx6qAAgoooIACCiigQAECicKbUO3i/PPh5pvb9/C442DNGgjlb9t8Br2aqwBGxx0RvYhVowaAESewwk0ZAFZ48iredQPAik+g3VdAAQUUUEABBRRQoFYCd9wB550H99/fflhnnglXXQUzZhzy82FZCdc66CJWsdXlXSvi3EgDwLq8Pf2NwwCwPz/vzi5gAJjdzjsVUEABBRRQQAEFFFAgD4G9e+Hyy+G662BkZPwTjj4arr4aTj8dJjT+OF3ns/A6EQ9yFVsIG3fsgDA1U6fCrFm9t7zm8WrEanOQdqN9NgCMNXvVbscAsNrzV+XeGwBWefbsuwIKKKCAAgoooIACFRfoGizdey+cfTbc075ICC9+MdxwAxx77AGFv/s7eMMbsoN88pPwB3+Q/f5B35n3KrYQqm7YAKtWwfr1h2ax4dy75csbxV6WLHk8hx00QebnxVw9mfTcSAPAzNNVqxsNAGs1nZUajAFgpabLziqggAIKKKCAAgooUH2BVMHS/hFY3btIyGMXXsS835jcs/JwN70TToCtW6sTZuW5iu1rX4MVK3pXcg6ec+fCunUwf3613s1BnxtpAFit9yOv3hoA5iVru70EDAB7CflzBRRQQAEFFFBAAQUUiCaQOVjqUSRk3+zjeMX2NWyifZGQpAMIZwmGFW1V+OS1iu3OOxur+/btS64wZQrceissW5b8nqKvHPS5kQaARc94OZ5vAFiOeRjGXhgADuOsO2YFFFBAAQUUUEABBQoQiBIs9SgS8jecyTu5it0cWiQk6XDDqrAbb0x6dfHXxV7FFgLaRYvShX+jCiEE3LSpOisBB31upAFg8d+XMvTAALAMszCcfTAAHM55d9QKKKCAAgoooIACCgxUIGqw1KNIyI84mndwNZ/gdCDdH7fD2Xa7d1enwEXMVWyLF8O8ecm2/XZ6eZ79bLj9dpg9uxqGUd/LHt8oA8CB/iuntA9L92+k0g7DjlVQwACwgpNmlxVQQAEFFFBAAQUUqJJAbiutehQJ+SxLOZfV/AeNIiFJP+FsvTlzkl5d7HUxbUPBj6VL44ynSkVCoqxMTcBmAJgAaQguMQAcgkku6RANAEs6MXZLAQUUUEABBRRQQIG6CMRcpTbufL6REb5/8WqO+uAlTGfPOLJHOJz3cikf4CIeZXIi0s2bYcGCRJeW4qJYq9hibScei1KFIiFpzqYMxWLWrk2/1dkAsBRfl8I7YQBY+BQMbQcMAId26h24AgoooIACCiiggAKDEYgVLHU6ny+s2Fs2dycf4nxex81tB/UtjuNskhUJqdIKwNHB9ruKLWZBkXYTUIUiIWE15caNsGpVo6DJyMjBkUya1CiMsnIlhK3SEzKkOAaAg/n3TdmfkuHVKfuQ7F9FBAwAKzJRdlMBBRRQQAEFFFBAgSoKxAyWOp3P1/qMV3EHH+E8nsn9bbl6FQkJQc+uXdU4v27sAPtZxRZCz7BSL89PlYqEhHcqFJ7eswemTYOZM/t/JwwA83y7qtO2AWB15qpuPTUArNuMOh4FFFBAAQUUUEABBUokEDtY6rQ6r3WV4RT2cjmXcwHXMYmWZVxNl25FQqpWBXjsVGddxbZlCyxcmP+LE7bPbt2abQVd/r3L9wkGgPn6VqV1A8CqzFT9+mkAWL85dUQKKKCAAgoooIACCpRGIHaw1Ol8vnbnDD6Pe1nD2SzgnrYe7YqEhHbGnTNYGs10HUmzii12UNutp3UyTjMjBoBptOp7rQFgfee27CMzACz7DNk/BRRQQAEFFFBAAQUqLBA7WOq0ArBTNdzDGDlQCfh99C4ScuwJk4d2dVrMrdq9Xteqr7LsNb5OPzcAzCpXr/sMAOs1n1UajQFglWbLviqggAIKKKCAAgooUDGBmMFSr/P5ulXDfQbdi4R8e8JxsGYNx75lccWE43U3VrGWXj3qdJZjr/uq/nMDwKrPYJz+GwDGcbSV9AIGgOnNvEMBBRRQQAEFFFBAAQVSCMQKlpKsHOtVDbdXkRDOPBOuugpmzEgxwnpc2m4bdV4jq2Kl5X4tDAD7FazH/QaA9ZjHKo7CALCKs2afFVBAAQUUUEABBRSokECsYCnp2XG9quGOFgn5I65lIvvHSx59NFx9NZx++lBVq+i0jTqPV63TWY55PKssbRoAlmUmiu2HAWCx/sP8dAPAYZ59x66AAgoooIACCiigwAAEYgRLaavHJqmGe+Gye/n1vz6bCfe0LxLC0qWwejUce+wAlMrxiG7bqGP20BWAzAZ2xDS1rWoIGABWY57q2EsDwDrOqmNSQAEFFFBAAQUUUKBkAv0ES1OmwKZNMH9+tkF1rYY7MtII+S65BPbsGf+Aww+HSy+Fiy6CyZOzdaBid/XaRt3vcHqd5dhv+2W93xWAZZ2ZwfbLAHCw3j7toIABoG+DAgoooIACCiiggAIKDETg/e+Hd70r/aOuuAIuvjj9fanu2LkTzj8fbr65/W3HNYqEsHg4ioT02kadynbMxUnOcuyn/bLeawBY1pkZbL8MAAfr7dMMAH0HFFBAAQUUUEABBRRQYIACRa4ATDXMO+6A886D++9vf9sQFQnpto06lemYi5Oe5djPM8p4rwFgGWdl8H0yABy8uU9sCLgC0DdBAQUUUEABBRRQQAEFchUIQdJznwvf+lb2x6Q9AzD7k4C9e+Hyy+Haa2G/RUKCZdhGvWMHvPrV8L3vZdcd6Dxm72YudxoA5sJauUYNACs3ZbXpsAFgbabSgSiggAIKKKCAAgooUC6BEPxt2NDI0sIZfv1+Br5y7N574eyzwSIhj09dZVZy9vuy5XC/AWAOqBVs0gCwgpNWky4bANZkIh2GAgoooIACCiiggAJlEsjjDLlCzo4LRUKuv75RCMQiIQdesSxFQkIhl1tvhWXLyvSWDrYvBoCD9S7r0wwAyzoz9e+XAWD959gRKqCAAgoooIACCigwUIEsAVGSDk6cCLt3w/TpSa6OfE3Y/xqKhNxyS/uGLRLSETxs+127NnsV58gzWVhzBoCF0ZfqwQaApZqOoeqMAeBQTbeDVUABBRRQQAEFFFAgX4F+togm6dl998GcOUmuzOkai4Q8DtutSMikSbB8Oaxc2SicPGGAqcfoeYXhKMepU2HWrIJC4zGvoAFgTt/JijU7wK9CxWTsbt4CBoB5C9u+AgoooIACCiiggAJDIhACoXnzYNu2/Aa8eTMsWJBf+4latkjIOKYQuu3c2dglPW0azJw52NBt9LzJVatg/XoIO7dHP2Hl6GgYuWTJYMPIVigDwETfrtpfZABY+yku7QANAEs7NXZMAQUUUEABBRRQQIFqCYQiHUuX5tvnwlcAtg7PIiH5TnbC1tOcNzl3LqxbV8x2ZAPAhBNa88sMAGs+wSUengFgiSfHrimggAIKKKCAAgookIdAXlskQ5GOm27Ko8eNNsO20l27BruyrOdoehUJmTy5UUDkwgsh/LOfqAJZzpssqiCJAWDUqa9sYwaAlZ26ynfcALDyU+gAFFBAAQUUUEABBRToLZD3FskQKh511KFbL3v3Kt0VhVQBTtpFi4Qklerrutbw+v774YwzYN++9E2GEHDTpsGuBDQATD9PdbzDALCOs1qNMRkAVmOe7KUCCiiggAIKKKCAApkFBrFFMmzNDdsr8/yELcbhDLdun7xWNyYeVygS8ta3wvbt7W8580y46iqYMSNxk8N+Ybfwuh+bUJ1469bBnQloANjPbNXnXgPA+sxl1UZiAFi1GbO/CiiggAIKKKCAAgqkEBjUFsktW2DhwhQdS3lpt7Am79WNKbsKoUjIZZfBddfB/v3jbz/6aLj6ajj99MGlT6kHUY4b0oTXWXqcJFTO0m67ewwAY0lWux0DwGrPX5V7bwBY5dmz7woooIACCiiggAIKdBEI4cmiRYPZIpnnCsBu2zXTBEQDLwBhkZC+vp9Zwuu0DxzktnIDwLSzU8/rDQDrOa9VGJUBYBVmyT4qoIACCiiggAIKKJBSIKyKmzcPtm1LeWPL5Wm2SOZ1BmC3gg1ZAqKBF4CwSEimF7Cf8DrNAydOhN27B1NYxgAwzczU91oDwPrObdlHZgBY9hmyfwoooIACCiiggAIKZBAIWxuXLs1w45hb0myRjF0FOASQa9e2L9TQT0BURAEIehUJOf54WLOmsWRzyD8xwus0hGH16pw5ae7Idq0BYDa3ut1lAFi3Ga3OeAwAqzNX9lQBBRRQQAEFFFBAgcQCscK4NFskY4WOixfD5ZdD+P8T2vxpOUZAlGZ1Y2L0JBf2KhLypjfBlVcOdZGQWO9RkukI12zeDAsWJL06+3UGgNnt6nSnAWCdZrNaYzEArNZ82VsFFFBAAQUUUEABBXoKxNyOm2aLZIxg7rnPhW98o3ttjFgBUZrVjT3R01xgkZCuWrHC66RT0m0FYMyq0gaASWek3tcZANZ7fss8OgPAMs+OfVNAAQUUUEABBRRQIINA7IIcabZIDmJrbqyAKM3qxgzT0PuWmhQJiRmSxQyve08ATJoEu3YdegZgXlWlDQCTzEj9rzEArP8cl3WEBoBlnRn7pYACCiiggAIKKKBARoEtW2Dhwow3t7kt7RbJPItzxAyI0qxujKc5pqWKFgnJKySLHV73mrexIXCeVaUNAHvNxnD83ABwOOa5jKM0ACzjrNgnBRRQQAEFFFBAAQX6EIgdoqRZATja7TRBSrdiH2MZyjC2Pqam860VKhKSZm7nzoV169oXcmmHETu87jVXrdvA8wyuQz8MAHvNxnD83ABwOOa5jKM0ACzjrNgnBRRQQAEFFFBAAQX6EIi5Sq7dFsmkXQurxDZuhFWr4NZbISx2G/2Edpcvh5UrOxf7GERAlHZ1Y9KxZ76u5EVC8g7JYge83eahtRDMILauGwBm/lbU6kYDwFpNZ5TBXAm8s6WlFwMborR8aCMGgDmg2qQCCiiggAIKKKCAAkULlO2cvBBK7twJe/bAtGkwc+ah564l9YodEGVZ3Zi0r5mvS1Ik5Jpr4A1v6F4tJXMH2t84iJAsZnjdbfhTpsCmTY2ViTGK1ySpKm0AGPmFrGhzBoAVnbicuv1rwFeASQaAOQnbrAIKKKCAAgoooIACNReofKXcDvMTMyDqZ3XjQF6fUCTkrLPgK+GPh20+S5fC6tVw7LG5d2dQIVkYSKzwuhNKCP/CitRlyxpXDOq7YgCY+2taiQcYAFZimgbSycOALwMnAj8EntJ8qisAB8LvQxRQQAEFFFBAAQUUqIfAIAObQYvFCogKrwKcBK4kRUIGFZLFDOTa8c6ZA5/85KFnEg7qfTIATPLC1/8aA8D6z3HSEV4AXAt8C7gVeJcBYFI6r1NAAQUUUEABBRRQQIFWgUFs2SxCfJBhVBHja/vMgouEDCokC2OPEV53mreXvhQuvhiWLGnsno65orRXVWkDwNJ8mwrtiAFgofylefhs4D5gKhBW/C0BLjMALM382BEFFFBAAQUUUEABBSonkHfRhiJAYgRESc5sK2JsPZ9ZQJGQQYZko+PvJ7zuaQiMVic+4ojGP8f6dDtT0gAwlnK12zEArPb8xer9HcCrgLXAGcDlBoCxaG1HAQUUUEABBRRQQIHhFQhhyooVsG1bb4MQjK1de+gWyd53Df6KfgKi1gIQg+95hCcOuEhIUYVXQnh9yinw0EMRzNo0Ed6DK66At789XvvdqkobAMZzrnJLBoBVnr04fX898A/AbuB44EcGgHFgbUUBBRRQQAEFFFBAAQUa2yo3boRVqxoFEMLRcqOfUAxj+XJYuRIWLx5oYdm+pqaOqxtTgQyoSMiWLbBwYaqedb24W0g29sZQqTe8k3l9jjwybsDoCsC8Zqo+7RoA1mcus4zkF4BvAk8D3gJ8tNmIKwCzaHqPAgoooIACCiiggAIKdBUIWzp37oQ9e2DaNJg5E6ZPryZaHVc3ppqJARQJKWoF4KhDrPMHU7lmuLhXVWlXAGZAreEtBoA1nNQUQ/qrZvD3ReBF4czTiAHgrB79CKHjPeGa7du3M2tWr8tTjMpLFVBAAQUUUEABBRRQQIEBCNRxdWNqthyLhMQ8A7BXSNZu3LGKvqQ2TXlDr6rSBoApQWt6uQFgTSc2wbBC4LcJCAvw5wP/1nJPjBWAo2Fiz64YAPYk8gIFFFBAAQUUUEABBRQouUCdVjdmor79djjvvLDCo/3tb3oTXHklzJiRqvlYq/B6hWTtOhWj6EuqwWa8eM0aOOuszjcbAGaErdltBoA1m9CEwzkc+DowB7gKuHDMfQaACSG9TAEFFFBAAQUUUEABBRRQoCnQR5GQEKCGxYShialTIWwSC9vDY63CC+0sWZJ+pvop+pL+adnuCEVFwvmay5a1v98AMJtr3e4yAKzbjCYbz2jAdz/wXGBfDgFgrz29bgFONldepYACCiiggAIKKKCAAgrkItApdOv7YQmLhDz2nGPZsKFRIGb9+kMLxEyc2CgQc+658La3QTgPMOsnVJjeujV7kZksRV/S9DVGQZBuFaYNANPMRn2vNQCs79x2Glmo9PuvQFgFeApwe5sLY6wA7CUbAsIDa8PdAtyLyp8roIACCiiggAIKKKCAAnEEwrbWXqFbqMocVstN6Ccx6FEkZP/hk1n1pEv5kx9dyKNM7jq4Y45pFI95+OH0Bt2CsTStpSn6kqbdcO2HPwwXXwwPPpj2zkOv7xR0GgD251qXu/v5OtfFYNjGsQYIpwN8D7i0w+BfB7y2+bO/AEb/ruWONqsFs/oZAGaV8z4FFFBAAQUUUEABBRRQIINAmhBr7lxYtw7mhxPj+/n0KBLyTY7nbNbwORZ1fcoRRzR+nCYE7LU1Nu2wRou+XHEF/Mu/pL278/VhdeOmTXDOOf232W6rswFg/651aMEAsA6zmG4Mfwu8Md0tj1/9y8D3M9479jYDwEiQNqOAAgoooIACCiiggAIK9BLIso01aoDWo0jIx3gTF3Ilu+lcJCRslX360+F7YTlLj09YDbd2bYQAs81z8qhO/OY3w0039RpV75+3K3ZiANjbbRiuMAAchlk+dIwGgMM3545YAQUUUEABBRRQQAEFhlign0IWsbbQBv7H9uxl7S9fxum7rmMi+8fNyI84mj/mGj7JG4D2cUUI9sKW2euvbxS+CDuNRz+TJjXODQxbmBcv8TGWfgAAIABJREFU7nMLc4/3JWZ14o9+FI466tCxZH1dw9mJu3c3CqiMfgwAs2rW6z4DwHrNZ6zReAZgLEnbUUABBRRQQAEFFFBAAQUKFAjbVufNg23bsnei3yIao08erej7fL7GGs7mRL7StlOfZSnnspr/4Ni2Px/d5hpW4oWzAffsgWnTYObMQ4Ov7CPufWfM6sRPeQqELdexPmFL8Zw5BoCxPOvSjgFgXWYy7jgMAON62poCCiiggAIKKKCAAgooUIhAzKAqFAbp59O6au4wRljJ9byXS5nOnnHNPszkAz+7kvFFQtptc+2nX1nujRms3nMPLFyYpRft79m8GRYsMACMJ1qPlgwA6zGPsUdhABhb1PYUUEABBRRQQAEFFFBAgQIEYm5VvfHG7APodG7eTHbwIc7ntdzStvF2RULabXPN3rPsd8baWh1W7LkCMPs8eGcyAQPAZE7DdpUB4LDNuONVQAEFFFBAAQUUUECB2gnELFbRT+gW+rFhA5xySmfiV3M7H+E8fontbS8aWyRk7DbXoiYvRnGVmPMUzkHctcszAIt6H8r8XAPAMs9OcX0zACzO3icroIACCiiggAIKKKCAAlEE8l5Z1q2TYYtsCP1WrYL165MVuJjCXt7NZVxA7yIhmzdPOGSbaxSwjI2ElYArViQ7Z7FTdeI8V2paBCTjxNbsNgPAmk1ohYYzCxp/tbN9+3ZmzQr/048CCiiggAIKKKCAAgoooEAsgS1b8j1brlM/0wRi7dpIUiTkWf+0mmNe3r5ISCy/NO2EwHPjxkbgmaU6cZ5nNRoAppnJ+l5rAFjfuS37yAwAyz5D9k8BBRRQQAEFFFBAAQUqLVDECsAsW2LbIY8WCXkflzCNveMueWzyZCZceilceCFMnjzu52Fb7Y4dsHcvTJ0KYc3J9OmDmc4s1YljFhWZMCbpMQAczLyX/SkGgGWfofr2zwCwvnPryBRQQAEFFFBAAQUUUKAEAnmfLTd2iP0UxejE1atIyMixxzPxr9fAokV023YczjBcvhxWroRQzXhsSJZ0uvIMFvvxmzIFNm2C+fPHj8QAMOns1vs6A8B6z2+ZR2cAWObZsW8KKKCAAgoooIACCihQC4E8z5ZrBYqxgq0beK8iId/6rTfx5l1X8sV/n9Fz3kLF3XXr2odl7W4eRLA4+twsKyhD+Be2HS9b1n7oBoA9X4mhuMAAcCimuZSDNAAs5bTYKQUUUEABBRRQQAEFFKiTQJ5ny7U6xXpON/s0RUKge9zRKzQb7Uea8wzTBoudxprmmZ2KirS2bQBYp2909rEYAGa3887+BAwA+/PzbgUUUEABBRRQQAEFFFCgp0CMlXkhZNq6tfu22Ze8BD772Z7diXJBkiIh53AD3+E5XZ935JGNlYAvfWn78wHzWI2XFKDfoiIGgEmlh+c6A8DhmeuyjdQAsGwzYn8UUEABBRRQQAEFFFCglgJ5nS03irV+feN8vUF+ehUJeZjJvJdLuZILeZTxRUJa+3rYYXDqqYeeD5i3WRqrLEVFDADTCA/HtQaAwzHPZRylAWAZZ8U+KaCAAgoooIACCiigQC0F8lrNFoKyF70IHnqoGLZeRUK+yfGczRo+x6JEHQzbeNeuhTe+EbZtS3RL24uSrJrM3nq6O90CnM6rrlcbANZ1Zss/LgPA8s+RPVRAAQUUUEABBRRQQIEaCcQ+Wy7G9uJYvL2KhHyMN3EhV7Kb3kVCjjgCHn64/56FcxFDxeGiPwaARc9AOZ5vAFiOeRjGXhgADuOsO2YFFFBAAQUUUEABBRQoVCDm2XJ5Ff4IZ/NlWVEYs0hIjEkKFZhvvDFbS2Hb744dsHcvTJ0Ks2a1P6cwSesGgEmU6n+NAWD957isIzQALOvM2C8FFFBAAQUUUEABBRQYCoF+z5YLAddNN8WlCufx7d/fX5uxioT01wuYOBF2704e3IVwdsMGWLUKwrmKIyMHexDaCucsrlzZWFU4IUWaYwDY70zW4/4Ur0w9BuwoSiNgAFiaqbAjCiiggAIKKKCAAgoooEA6gRAeHnXUoSFVuhbaX/3Up8J//3f/LcUsEtJPb+67D+bM6d1Cmu3Z4ZzCUL14/vze7YYrDACTOdX9KgPAus9wecdnAFjeubFnCiiggAIKKKCAAgoooEBXgRBshSAq9ifGCsDWPsUuEpJ2vJs3w4IF3e/Kq0DL6FMNANPOWj2vNwCs57xWYVQGgFWYJfuogAIKKKCAAgoooIACCrQR2LIFFi6MS/MrvwLf+U7cNkdbi1kkJE0Pe60ADCv/Fi2CffvStNq4dsoU2LSp90pAA8D0tnW8wwCwjrNajTEZAFZjnuylAgoooIACCiiggAIKKDBOIPYKwFD444Yb4I1vzA970EVCJk2CXbs6nwEYo4ryCSfA1q3dzwQ0AMzvnapSywaAVZqtevXVALBe8+loFFBAAQUUUEABBRRQYIgEYp8BeOutcOyx+WwrHjstgyoS0qsKcKwqyqGdUBik08cAcIi+mF2GagDoe1CUgAFgUfI+VwEFFFBAAQUUUEABBRSIIBCrCvBLXgLhHLzYoWK3IQ6iSEivYC6WX6+g0QAwwstegyYMAGswiRUdggFgRSfObiuggAIKKKCAAgoooIACQSCPFWyxQrGkM5RXkZBeW3Njhp0TJ8Lu3Z23GhsAJn0b6n2dAWC957fMozMALPPs2DcFFFBAAQUUUEABBRRQoIdAHmfYxQoV005ezCIhSYpzxD5DsVuxEQPAtG9DPa83AKznvFZhVAaAVZgl+6iAAgoooIACCiiggAIKdBGIXcU2RqiYdcJiFAkJ4V84z3DZsu69uOsuOPnkrD0df9/mzbBgQfv2DADjOVe5JQPAKs9etftuAFjt+bP3CiiggAIKKKCAAgoooMABgXB+3/LlsG9fcpBuQVk/oeLhh8NJJ8GGDTAykrw/rVf2KhLyGU7mXFbzHZ5zyAPCtt+1a2H+/PbPDeFm6NeqVbB+ffb+tWvdFYDZ5nqY7jIAHKbZLtdYDQDLNR/2RgEFFFBAAQUUUEABBRTILBBCuxUrYNu23k30CspihIrhjL0QTL7hDfDww737NPaKaU8cYdtbr2f26ktg795xDTzMZN7LpVwz8UJeeepkVq6ExYthQoeUJY1P2t5OmgS7dnkGYFq3YbveAHDYZrw84zUALM9c2BMFFFBAAQUUUEABBRRQoG+BsMJt48bGCrewDbZ1BV4IqcIqwV5BWWsn0oRmnULFvlcn7tgBb397Y0BtPiPHHs/Ev14DixZ19MvShzSTYRXgNFrDe60B4PDOfdEjNwAsegZ8vgIKKKCAAgoooIACCiiQk0BYgbdzJ+zZA9OmwcyZnVeodetCjFAxRpDI7bfDeefB9u3tu/umN8GVV8KMGYf8vJ/tzEmnJhROWbKk89WeAZhUst7XGQDWe37LPDoDwDLPjn1TQAEFFFBAAQUUUEABBUom0E+oGCNIPLAV+LLL4LrrYP/+8TpHHw3XXNPYdzxhAoMoaBJWPm7d2nnrceikAWDJXuSCumMAWBC8j8UA0JdAAQUUUEABBRRQQAEFFFBg4AJhV++998IDD8ATnwhPfjJMndr4v1mzEqxUDMv6zj4bvvKV9n0P5X1Xr+buHc9h6dL8hhcKqWza1LnoyOiTDQDzm4MqtWwAWKXZqldfDQDrNZ+ORgEFFFBAAQUUUEABBRQorUBrBd5wnF+7BXyh8xMnHjyrMGyr7VTU48ABh9dfD5e0LxLC5Mn8/TGX8sb7LuRRJkd36VZFeezDDACj81eyQQPASk5bLTptAFiLaXQQCiiggAIKKKCAAgoooEC5BdKcAdg6krlzYd26HivsehQJuY85nMMNfI7ORULS6iWpotzapgFgWuF6Xm8AWM95rcKoDACrMEv2UQEFFFBAAQUUUEABBRSosEC/FXgTr7TrUSTkY7yJC7mS3RxaJCQt7RFHwG23wUtfmvxOA8DkVnW+0gCwzrNb7rEZAJZ7fuydAgoooIACCiiggAIKKFBpgVgVeJOetReKhPznGZcx6+brmMj4IiE/4mj+mGv4JG8AsscxifvTnD0DwEq/xtE6n/2Ni9YFGxpSAQPAIZ14h62AAgoooIACCiiggAIK5C0QuwJvkmq7o4Hjsfu+xhrO5kTaFwn5DCdzLqv5Ds/JzJCkP6ONGwBmZq7VjQaAtZrOSg3GALBS02VnFVBAAQUUUEABBRRQQIHqCNx9N9Er8IY2Q2GQdp+xgeNhjLCS63kflzCNveNueZjJvJdLuZLsRUK69af1gQaA1Xlv8+ypAWCeurbdTcAA0PdDAQUUUEABBRRQQAEFFFAgF4HTToObborbdGjzxhvbt9kpcJzJDj7M2zmVW9ve2E+RkG79MQCMO/d1aM0AsA6zWM0xGABWc97stQIKKKCAAgoooIACCihQaoGf/hSOOgpGRuJ2c+JE2L0bpk8f326vwPHV3M5HOI9fYnvbTn2UNx8oEvJjjkrc6W79MQBMzDg0FxoADs1Ul26gBoClmxI7pIACCiiggAIKKKCAAgpUX+C++2Du3HzGsW0bPPe5h7adNHCcwl7ew59zPh9qWyTkhzz5QJGQv+MPEhcJCWOdM6f7WN0CnM+7ULVWDQCrNmP16a8BYH3m0pEooIACCiiggAIKKKCAAqUR2LIFFi7MpzvXXw/nnnto2yEUDEU5kn6ez9f4K87iN/hq21vSFAnZvBkWLDAATGo/zNcZAA7z7Bc7dgPAYv19ugIKKKCAAgoooIACCihQS4E8VwC+7GXwz/98kC1U/g3bf7/3vXSUsYqEuAIwnfswX20AOMyzX+zYDQCL9ffpCiiggAIKKKCAAgoooEAtBZJuyc0y+MMOgx//uHEO4J13wvLlsG9flpYa9/RTJGTSJNi1q/2ZhK09cgtw9vmp050GgHWazWqNxQCwWvNlbxVQQAEFFFBAAQUUUECBygj0KsrRz0DCqruHHoJFi/oL/1r7kKVIiFWA+5nF4bvXAHD45rwsIzYALMtM2A8FFFBAAQUUUEABBRRQoGYCd98NS5fmM6gvfxne/GYIZ//F/KQtEhLGuGRJ7x64ArC30TBcYQA4DLNczjEaAJZzXuyVAgoooIACCiiggAIKKFB5gcceg3nz4od0AebjH4czz8yPKEmRkGufs5pP/ftzmJAg1TEAzG+uqtRyglelSsOxrxUSMACs0GTZVQUUUEABBRRQQAEFFFCgagKhQEfMbbph/OHcvVe+Em67LV+NUCTkrazivVzKNPaOe9j+wydz2J/9KbzznTB5ctfOGADmO1dVad0AsCozVb9+GgDWb04dkQIKKKCAAgoooIACCihQKoEYhTpaB/Sa18Add8DIyGCG2atICHPmwA03NJLODh8DwMHMVdmfYgBY9hmqb/8MAOs7t45MAQUUUEABBRRQQAEFFCiNQFgJ+NrXwve/33+X8t7+26mHoUjImiecx9N/tr39JeFQwiuvhKOOGvdzA8D+570OLRgA1mEWqzkGA8Bqzpu9VkABBRRQQAEFFFBAAQUqJ7B/PxxzTH8h4AknwEc/Ci94QfzhX3stfOELcOuth64uDFuOly+HlSth8a/vZcJlfw4f+hCEAY39PPnJcM018Ad/QOvhgAaA8eerii0aAFZx1urRZwPAesyjo1BAAQUUUEABBRRQQAEFKiHQz5mAU6bApk1wxBEwd2784Z52Gtx4I/z0p7BzJ+zZA9OmwcyZMH36weeFnz/wL1/jqX92FlO+9dX2HTn5ZFi9Gp7znAM/NwCMP19VbNEAsIqzVo8+GwDWYx4dhQIKKKCAAgoooIACCihQGYEsZwKG8C+szFu2rBHQhV22sc8AnDgRdu8+NOwbRQ0VjTdsgFWrYP36xrN7FQk5UBjkTxtFQnb86EfMnj17tLnwDzsqM2F2NJqAAWA0ShtKKWAAmBLMyxVQQAEFFFBAAQUUUEABBfoXCCsBV6yAbdt6txW2/a5dC/PnH7w2rNa76abe96a94r77OFDTo/XTq69JioTseM97mB063fgYAKadmJpcbwBYk4ms4DAMACs4aXZZAQUUUEABBRRQQAEFFKiDQFhVt3FjY1Vd13P3Fh9ynN6Bod99NyxdGl9h82ZYsOBgu2lWK/4Ot/ERzmN2m8V9Ybnf4+v/DADjT1xFWjQArMhE1bCbBoA1nFSHpIACCiiggAIKKKCAAgpUTaDXuXtjxxPCw3nzkq0gTGPRugIwy3mFU9nDu7mM8/kQEzlYJMQAMM0s1PdaA8D6zm3ZR2YAWPYZsn8KKKCAAgoooIACCiiggAJtBUJAd9JJ8OCDcYBCtd9duxpnAPYbMD6fr/GJI85i7sONIiEGgHHmqOqtGABWfQar238DwOrOnT1XQAEFFFBAAQUUUEABBYZeIGzRffnL4xQEGa0CHFBjbDEORUK+dd4qnvO3l7Jj7163AA/92woGgL4ERQkYABYl73MVUEABBRRQQAEFFFBAAQWiCKxZA+ec039TIfRbsqTRTqwiIwdCxWt2sOMtb2H2P//zaCctAtL/dFWyBQPASk5bLTptAFiLaXQQCiiggAIKKKCAAgoooMDwCvS7XTfIhUrDW7c2io2E8wiPOirOqsKJE2H37tDmDmbPfrwMiAHgkL6uBoBDOvElGLYBYAkmwS4ooIACCiiggAIKKKCAAgr0J5ClYMfoE6dMgU2bYP78xq+EQiBz5/bXn9a7Q3vTphkAxhOtbksGgNWdu6r33ACw6jNo/xVQQAEFFFBAAQUUUEABBQ4IhPMAly+HffuSg4Tw79ZbYdmyg/ds2QILFyZvo9eVmzfDM55hANjLaRh+bgA4DLNczjEaAJZzXuyVAgoooIACCiiggAIKKKBABoGwEnDFCti2rffNYdvv2rUHV/6N3uEKwN52XpFNwAAwm5t39S9gANi/oS0ooIACCiiggAIKKKCAAgqUSCCcCbhxI6xa1VjdNzJysHOTJjVWCa5cCYsXN878G/uJeQZgeN6uXZ4BWKLXo9CuGAAWyj/UDzcAHOrpd/AKKKCAAgoooIACCiigQL0FQpi3cyfs2RPO4YOZM2H69N5jjloF+EbYscMtwL3V63+FAWD957isIzQALOvM2C8FFFBAAQUUUEABBRRQQIHCBO6+G5Yu7f/xoZ0lSwwA+5esRwsGgPWYxyqOwgCwirNmnxVQQAEFFFBAAQUUUEABBXIVCNuI581LdpZgp46EMwa3bm1sM3YFYK7TVZnGDQArM1W166gBYO2m1AEpoIACCiiggAIKKKCAAgrEEAgFRRYtSldVePS5obrwpk0HC4wYAMaYkeq3YQBY/TnMOoL5wG8DJwEnAE8Bfgb8F/BF4GPA57I2nuA+A8AESF6igAIKKKCAAgoooIACCigwnAJ33tkoGrJvX/Lxh/AvFB9ZtuzgPQaAyf3qfKUBYJ1nt/PYNgKLEgz9E8AfAo8muDbtJQaAacW8XgEFFFBAAQUUUEABBRRQYKgEwkrAFSuSbQcO237Xrj248m8UygBwqF6ZjoM1ABzO9+A7wDHN1X7/2Fzpdz8wEfhN4B3AzCbN/wZ+PwcmA8AcUG1SAQUUUEABBRRQQAEFFFCgXgLhTMCNG2HVqsbqvpGRg+ObNKmxSnDlSli8uHHm39iPAWC93oesozEAzCpX7fs+BawDbgZa/tXx+KCOBr4AHNv8lbBaMPZ2YAPAar9D9l4BBRRQQAEFFFBAAQUUUKBPgZ/+NBTpgL17YepUmDULpk/v3Gi4fudO2LMHpk2DmTO7Xx9aMgDsc5JqcrsBYE0mModhvAq4o9nuh4HzIz/DADAyqM0poIACCiiggAIKKKCAAgqUXyCs6NuwobGib/36Q1f0TZx4cEXfkiXtV/SlHaEBYFqxel5vAFjPeY0xqqnAnmZDnwZCIBjzYwAYU9O2FFBAAQUUUEABBRRQQAEFSi+Q5ky/uXNh3brxZ/qlHaQBYFqxel5vAFjPeY0xqqOAXc2GwkrA34nRaEsbBoCRQW1OAQUUUEABBRRQQAEFFFCgvAKxqvqmHaEBYFqxel5vAFjPeY0xquXALc2GrgIujNGoAWBkRZtTQAEFFFBAAQUUUEABBRQovUBY+bdoEezbl76rU6bApk3ZVwIaAKY3r+MdBoB1nNX+x3QY8CVgQbOpE4GvpGw2rPDr9nkacE+4YPv27cwKJ536UUABBRRQQAEFFFBAAQUUUCCjQNqCGhkfk/q2cObfvHmwbVvqWx+/4YQTYOvWbGcCGgBmd6/TnQaAdZrNeGN5B/DBZnO3AqdmaPqxpPcYACaV8joFFFBAAQUUUEABBRRQQIFWgUEX1Miif/fdsHRpljsPvSe0EwqDpP0YAKYVq+f1BoD1nNd+RrUY+AwwCfgh8KvAf2do0AAwA5q3KKCAAgoooIACCiiggAIKJBMooqBGsp4detVpp8FNN2W5c3w7N96Yvh0DwPRmdbzDALCOs5p9THOBzwG/CDwCvAzYmLG5Xnt63QKcEdbbFFBAAQUUUEABBRRQQIFhFyiqoEZa97At+aijYGQk7Z3jr584EXbvhunTD/1Zr63PBoD929ehBQPAOsxinDH8MvB54BlA+FfTaUDY/pvXxyrAecnargIKKKCAAgoooIACCihQY4EiC2qkZb3vPpgbltpE+oT25syBNFufd+7cwezZs0d7EP5hR6Tu2EyFBAwAKzRZOXY1hH5h5d+zgbB19wxgXY7PC00bAOYMbPMKKKCAAgoooIACCiigQN0Eii6okdZzyxZYuDDtXZ2v37wZJk2CFSuSFRUJ4eNVV+3gFa8wAIw3C9VsyQCwmvMWs9dHN7f5PrfZ6HnAqpgP6NCWAeAAkH2EAgoooIACCiiggAIKKFAngaILaqS1jL0C8KMfhfPPh337kvfkyCN38NBDBoDJxep5pQFgPec16aieBNwFzG/ecDHwgaQ393mdAWCfgN6ugAIKKKCAAgoooIACCgybQNEFNdJ6xz4DcPJkePDBtL0IO34NANOq1e16A8C6zWjy8TwR+Bfghc1b3gv8afLb+77SALBvQhtQQAEFFFBAAQUUUEABBYZHIHaY1q6gRh6asULLUPwjGKT/GACmN6vfHQaA9ZvTJCM6HLgDeGnz4g8BFyS5MeI1BoARMW1KAQUUUEABBRRQQAEFFKi7QOzttKMFNfJ2i7VtOXs/DQCz29XnTgPA+sxlmpHcDJzavCFsAQ7hXyj+0enzKPDtNA9IcK0BYAIkL1FAAQUUUEABBRRQQAEFFGgI5FFQY8GC/HVjFC7JvvovjM8AMP9ZLv8TDADLP0d59LBb2Nfuef8JPCtyRwwAI4PanAIKKKCAAgoooIACCihQZ4GqrgAMc/K1r8GiRemKd4zO5ZQp8NBDsH9/1tk1AMwqV6f7DADrNJvJx2IAmNzKKxVQQAEFFFBAAQUUUEABBUogEPMMwEmTYNcuCCvrBvW5805YvjxdCBjCv+uug7e8pZ9eGgD2o1eXew0A6zKT1RuHKwCrN2f2WAEFFFBAAQUUUEABBRQoVCBWQY3Qzo03Dn4oYSXgihWwbVvvZ59wAqxdCz//OSxc2Pv6zlcYAPajV5d7DQDrMpPVG4cBYPXmzB4roIACCiiggAIKKKCAAoUKxCqoEdpZsqSYoYQzATduhFWr4NZbYWTkYD/CysSwSnDlSli8GCZMgP63PhsAFjPT5XqqAWC55mOYemMAOEyz7VgVUEABBRRQQAEFFFBAgQgCMQpqhJV1W7c2wrWiP2Fb886dsGcPTJsGM2eO35bc/9ZnA8Ci57kMzy/B614GBvtQgIABYAHoPlIBBRRQQAEFFFBAAQUUqLpAvwU1Nm2C+fOrpdDf1mcDwGrNdj69NQDMx9VWewsYAPY28goFFFBAAQUUUEABBRRQQIE2AlkLaoQtt8uWVY+0v63PBoDVm/H4PTYAjG9qi8kEDACTOXmVAgoooIACCiiggAIKKKBAG4EsBTWqtvJvdNj9bX02APQLBAaAvgVFCRgAFiXvcxVQQAEFFFBAAQUUUECBmgikLahR5WFn3/psAFjleY/VdwPAWJK2k1bAADCtmNcroIACCiiggAIKKKCAAgp0FEhSUKPqfFm2Ph955A4eemj26NDDP4RE0M+QCRgADtmEl2i4BoAlmgy7ooACCiiggAIKKKCAAgooUA2BtFufr7xyB694hQFgNWY3v14aAOZna8vdBQwAfUMUUEABBRRQQAEFFFBAAQUUyCCQZuvzzp07mD3bADADc61uMQCs1XRWajAGgJWaLjurgAIKKKCAAgoooIACCihQRoFeW5937DAALOO8DbpPBoCDFvd5owIGgL4LCiiggAIKKKCAAgoooIACCuQsYACYM3BFmjcArMhE1bCbBoA1nFSHpIACCiiggAIKKKCAAgooUC4BA8ByzUdRvTEALEre5xoA+g4ooIACCiiggAIKKKCAAgookLOAAWDOwBVp3gCwIhNVw24aANZwUh2SAgoooIACCiiggAIKKKBAuQQMAMs1H0X1xgCwKHmfawDoO6CAAgoooIACCiiggAIKKKBAzgIGgDkDV6R5A8CKTFQNu2kAWMNJdUgKKKCAAgoooIACCiiggALlEjAALNd8FNUbA8Ci5H2uAaDvgAIKKKCAAgoooIACCiiggAI5CxgA5gxckeYNACsyUTXspgFgDSfVISmggAIKKKCAAgoooIACCpRLwACwXPNRVG8MAIuS97kGgL4DCiiggAIKKKCAAgoooIACCuQsYACYM3BFmjcArMhE1bCbBoA1nFSHpIACCiiggAIKKKCAAgooUC4BA8ByzUdRvTEALEre5xoA+g4ooIACCiiggAIKKKCAAgookLOAAWDOwBVp3gCwIhNVw24aANZwUh2SAgoooIACCiiggAIKKKBAuQQMAMs1H0X1xgCwKHmfawDoO6CAAgoooIACCiiggAIKKKBAzgIGgDkUpfOoAAAYBklEQVQDV6R5A8CKTFQNu2kAWMNJdUgKKKCAAgoooIACCiiggALlEjAALNd8FNUbA8Ci5H2uAaDvgAIKKKCAAgoooIACCiiggAI5CxgA5gxckeYNACsyUTXspgFgDSfVISmggAIKKKCAAgoooIACCpRLwACwXPNRVG8MAIuS97kGgL4DCiiggAIKKKCAAgoooIACCuQsYACYM3BFmjcArMhE1bCbBoA1nFSHpIACCiiggAIKKKCAAgooUC4BA8ByzUdRvTEALEre5xoA+g4ooIACCiiggAIKKKCAAgookLOAAWDOwBVp3gCwIhNVw24aANZwUh2SAgoooIACCiiggAIKKKBAuQQMAMs1H0X1xgCwKHmfawDoO6CAAgoooIACCiiggAIKKKBAzgIGgDkDV6R5A8CKTFQNu/lM4PthXFu2bOHpT396DYfokBRQQAEFFFBAAQUUUEABBRQoVuAHP/gBCxYsGO3Es4D/LLZHPr0IAQPAItR9ZhD4DeAeKRRQQAEFFFBAAQUUUEABBRRQYGACJwJfGdjTfFBpBAwASzMVQ9cRA8Chm3IHrIACCiiggAIKKKCAAgooULCAAWDBE1DU4w0Ai5L3uZOBeU2GHwEjkhQm8LSW1ZjhN4P/r7Ce+GAFyiXgd6Nc82FvyiHg96Ic82AvyiXg96Jc82FvyiPgd6M8czEReHKzO/8GPFKertmTQQkYAA5K2ucoUF6BxwuyALOBHeXtqj1TYKACfjcGyu3DKiLg96IiE2U3Byrg92Kg3D6sQgJ+Nyo0WXa1/gIGgPWfY0eoQC8Bf2PuJeTPh1XA78awzrzj7ibg98L3Q4HxAn4vfCsUaC/gd8M3Q4ESCRgAlmgy7IoCBQn4G3NB8D629AJ+N0o/RXawAAG/FwWg+8jSC/i9KP0U2cGCBPxuFATvYxVoJ2AA6HuhgAL+xuw7oIB/a+07oEBSAX/PSCrldcMk4PdimGbbsaYR8LuRRstrFchZwAAwZ2CbV6ACAv7GXIFJsouFCPjdKITdh5ZcwO9FySfI7hUi4PeiEHYfWgEBvxsVmCS7ODwCBoDDM9eOVIFOAv7G7LuhQHsBvxu+GQqMF/B74VuhgN8L3wEFkgr4e0ZSKa9TYAACBoADQPYRCpRcwN+YSz5Bdq8wAb8bhdH74BIL+L0o8eTYtcIE/F4URu+DSy7gd6PkE2T3hkvAAHC45tvRKtBOwN+YfS8UaC/gd8M3Q4HxAn4vfCsU8HvhO6BAUgF/z0gq5XUKDEDAAHAAyD5CAQUUUEABBRRQQAEFFFBAAQUUUECBogQMAIuS97kKKKCAAgoooIACCiiggAIKKKCAAgoMQMAAcADIPkIBBRRQQAEFFFBAAQUUUEABBRRQQIGiBAwAi5L3uQoooIACCiiggAIKKKCAAgoooIACCgxAwABwAMg+QgEFFFBAAQUUUEABBRRQQAEFFFBAgaIEDACLkve5CiiggAIKKKCAAgoooIACCiiggAIKDEDAAHAAyD5CAQUUUEABBRRQQAEFFFBAAQUUUECBogQMAIuS97kKKKCAAgoooIACCiiggAIKKKCAAgoMQMAAcADIPkIBBRRQQAEFFFBAAQUUUEABBRRQQIGiBAwAi5L3uQoooIACCiiggAIKKKCAAgoooIACCgxAwABwAMg+QgEFFFBAAQUUUEABBRRQQAEFFFBAgaIEDACLkve5ClRf4OXAP7UM493A5dUfliNQIJHALwGvBJYAzwNmAROBB4CvAn8P/CPw80SteZEC1RAI7/3bm+9++OdHgO8ANwLXAw9WYxj2UoEoAvOB3wZOAk4AngL8DPgv4IvAx4DPRXmSjShQfYErgXe2DOPFwIbqD8sRKFAtAQPAas2XvVWgLAJTgG3AMw0AyzIl9mOAAu8B/hTo9XvoV4DXAvcPsG8+SoG8BELg/XfAkzo84N+BVwDfy6sDtqtAiQQ2AosS9OcTwB8Cjya41ksUqKvArwHhv4kmGQDWdYodV1UEev3hpSrjsJ8KKDBYgWuAPwJ+2Pwb7/B0VwAOdg58WnECHwXeDOwDbgU+C/wH8DAwp7lC6sRm98Kvh1Uie4vrrk9WoG+B8Ie3sKLpic13+QrgbuBI4HeBtzSf8C0gvPu+732T20DJBcLK12Oaq/3Cau+w0i/8ZU9YCf6bwDuAmc0x/G/g90s+HrunQF4ChwFfbv7e0PrnBlcA5iVuuwp0ETAA9PVQQIG0AiHM2NLc2vg24K+aDRgAppX0+qoKfADYBawG9rQZRPgD4P8CXt/82Z8Df1HVwdpvBZphX9juHra0h1VPXxqjErZ1he1d4XMZEFbJ+lGgzgKfAtYBNwMjbQZ6NPAF4Njmz8L3xu3AdX4jHFsngQuAa4HwF0ThL03f1bzQANB3RoECBAwAC0D3kQpUWCAEGyH8CyFg+EPepuYfDMOQDAArPLF2PbrAjObKkMOBrUBYQeVHgSoKhBV94d/74bMGOKfNIMIKj280V8D+GHhq8yy0Ko7XPisQS+BVwB3Nxj4MnB+rYdtRoCICs4H7gKlACPzCXySFPz+EjwFgRSbRbtZLwACwXvPpaBTIW+BPgKuAbwO/2tzmEraBhY8BYN76tl81gXuA32huFQ7/8etHgSoKvBe4pNnxFwCbOwziYiBsDQ6flwJ3VnGw9lmBiALh3/ujq8Q/DYRA0I8CwyQQAvDw3q8FzmgWCzQAHKY3wLGWTsAAsHRTYocUKK3As5qFP8IZUC9pnnsW/ibPALC0U2bHChYIK//mNf8AOL3gvvh4BbIKhJXeocppOPPyF7pUtg7nnoVzAsMnbAEe/UNe1ud6nwJVFziqeVxEGEcIQn6n6gOy/wqkEAjHoPwDsBs4HviRAWAKPS9VICcBA8CcYG1WgRoK/B/gt5tVIN/QHJ8BYA0n2iFFEXgKsLNZ8S6sBFwQpVUbUWDwAuEPbeE8s38Fntfl8b/Y/INeuCQURRg9A3PwPfaJCpRDYDlwS7MrYffEheXolr1QIHeB8JdF3wSe1iwSFYqnhc/lbgHO3d4HKNBVwADQF0QBBZIIhOp1fwf8T/Nv8f7bADAJm9cMsUD4w17YMh8+oUDCB4fYwqFXV+AI4KFm95NsYQzVf6c0Kz6GFYF+FBhWgXAuZiiWM/qXP+Esza8MK4bjHjqBUCAwVIcPq8JfBDzWFDAAHLpXwQGXTcAAsGwzYn8UKJ9A2MIS/hYvrGg6F7ihpYuuACzffNmj4gUWAp9vrv7bARwHPFh8t+yBAqkFngz8sHlX2Mr1uz1aCH85FH6vCAVBwvZ3PwoMq8A7Wv7iJ1Q+PXVYIRz30AmEwC8cHRGqY4eigf/WImAAOHSvgwMum4ABYNlmxP4oUD6BvwHObB78/lvAfgPA8k2SPSqNQKh+GlZ5zGr+jXc4L/Ou0vTOjiiQTiBUcLy/ecsngBU9bg/Xhnu+C/xKukd5tQK1EVgMfKb5l0AhQA9F00Z3TtRmkA5EgTYChwNfb1aEb7ft3QDQ10aBggUMAAueAB+vQCSBScDPIrQVgr6/bRPwhb/FC9VMw2/qrR9XAEZAt4ncBPL6XnTq8LRmUZxfb17wLuD9uY3OhhXIX8AVgPkb+4R6CcwFPgeEMzEfAV4GbKzXEB2NAh0FRgO+8JdBz20Wj2q92ADQl0eBggUMAAueAB+vQCSBPIKOyUCoYnoscC3wx236agAYaQJtJheBPL4XnToazkr7J+DFzQuuAcIWMD8KVFnAMwCrPHv2fdACv9w8/uEZze2PpwFh+68fBYZBIFT6DcWiwirAU4Db2wzaAHAY3gTHWGoBA8BST4+dUyCVQPiNt9/PD4CfNBv5PeB/AT9vnv0XDncf+wl/u/dnzV+8Gbip+c+bgf/bb2e8X4EIArG/F+26FILGUOnx1c0fhmp34fBrPwrUQcAqwHWYRceQt0AI/cLKv2c3j384A1iX90NtX4ESCawBzgK+B1zaoV+vA17b/NlfAPc1//mONqsFSzQ0u6JAfQQMAOszl45EgdgC4T9eP56x0bFbiTM2420KlF4gVHoMFbJHiyOEQgmhanbrWZmlH4QdVKCLQDjM/aTmH85+ofmXQu0uD1V/Q8XH8HkPcJmqCgyJwNHNbb7hL0XD5zxg1ZCM3WEqMCoQjhB6Y0aOsHr2+xnv9TYFFEghYACYAstLFRgyAQPAIZtwh5tJ4K+BP2ze+almpccY53Fm6ow3KZCDwPuAcJ5l+LygWRCq3WMuBq5o/iCce/YvOfTFJhUom8CTmoWeQrXT8Anfgw+UrZP2R4EBCBgADgDZRyjQr4ABYL+C3q/AcAt4BuBwz/+wjz6c8/dHTYTPAq9sHvo+7C6Ov14CC1pCv7DF65w2wwsrYb/RrPz4P8BTIhWmqpeko6mbwBObQfcLmwN7L/CndRuk41EgooBnAEbEtCkFsggYAGZR8x4FFBgVMAD0XRhWgdb/iA3bHl/q+TXD+ioMxbhHtwGHM2EXAV8aM+p3Alc2f+3dQPh++FGgzgKh0EE4tyz8uz98PgRcUOcBOzYFIggYAEZAtAkF+hEwAOxHz3sVUMAA0HdgGAXeBny4OfCdwP/TUjynk8e/uyJqGF+V2oz5+cAXgCOBUBAqbAu+u/m/w/mX4eD38Pk28BvAntqM3IEo0F4gFD47tfmju5rh32NdsB5tfj/0VGCYBQwAh3n2HXspBAwASzENdkKBygoYAFZ26ux4HwIbgMUp7/eA65RgXl46gVDl+pPA9A49C+Ff2Ab/ndL13A4pEF+gW9jX7mn/CTwrfjdsUYFKCRgAVmq67GwdBQwA6zirjkmBwQkYAA7O2ieVR8AAsDxzYU8GK/BM4Pxm0DcLCKuaQuD3j8BHgAcH2x2fpkBhAgaAhdH74AoLGABWePLsej0EDADrMY+OQgEFFFBAAQUUUEABBRRQQAEFFFBAgbYCBoC+GAoooIACCiiggAIKKKCAAgoooIACCtRYwACwxpPr0BRQQAEFFFBAAQUUUEABBRRQQAEFFDAA9B1QQAEFFFBAAQUUUEABBRRQQAEFFFCgxgIGgDWeXIemgAIKKKCAAgoooIACCiiggAIKKKCAAaDvgAIKKKCAAgoooIACCiiggAIKKKCAAjUWMACs8eQ6NAUUUEABBRRQQAEFFFBAAQUUUEABBQwAfQcUUEABBRRQQAEFFFBAAQUUUEABBRSosYABYI0n16EpoIACCiiggAIKKKCAAgoooIACCihgAOg7oIACCiiggAIKKKCAAgoooIACCiigQI0FDABrPLkOTQEFFFBAAQUUUEABBRRQQAEFFFBAAQNA3wEFFFBAAQUUUEABBRRQQAEFFFBAAQVqLGAAWOPJdWgKKKCAAgoooIACCiiggAIKKKCAAgoYAPoOKKCAAgoooIACCiiggAIKKKCAAgooUGMBA8AaT65DU0ABBRRQQAEFFFBAAQUUUEABBRRQwADQd0ABBRRQQAEFFFBAAQUUUEABBRRQQIEaCxgA1nhyHZoCCiiggAIKKKCAAgoooIACCiiggAIGgL4DCiiggAIKKKCAAgoooIACCiiggAIK1FjAALDGk+vQFFBAAQUUUEABBRRQQAEFFFBAAQUUMAD0HVBAAQUUUEABBRRQQAEFFFBAAQUUUKDGAgaANZ5ch6aAAgoooIACCiiggAIKKKCAAgoooIABoO+AAgoooIACCiiggAIKKKCAAgoooIACNRYwAKzx5Do0BRRQQAEFFFBAAQUUUEABBRRQQAEFDAB9BxRQQAEFFFBAAQUUUEABBRRQQAEFFKixgAFgjSfXoSmggAIKKKCAAgoooIACCiiggAIKKGAA6DuggAIKKKCAAgoooIACCiiggAIKKKBAjQUMAGs8uQ5NAQUUUEABBRRQQAEFFFBAAQUUUEABA0DfAQUUUEABBRRQQAEFFFBAAQUUUEABBWosYABY48l1aAoooIACCiigQEKBlwOfBlr/2/CHwPOAHyRsY/SyxcBngYkt9/0P8Hzg+ynb8nIFFFBAAQUUUECBCAIGgBEQbUIBBRRQQAEFFKiBwPuAd40Zx0bgZGAk4fieAnwdePqY618D3JawDS9TQAEFFFBAAQUUiCxgABgZ1OYUUEABBRRQQIGKCoQVe3cBi8b0PwSDlyYY02HA/wu8ZMy11wJ/nOB+L1FAAQUUUEABBRTIScAAMCdYm1VAAQUUUEABBSoo8AzgXiCs5Bv9PAa8AvjnHuO5DLh8zDWbgZOAn1XQwi4roIACCiiggAK1ETAArM1UOhAFFFBAAQUUUCCKwLJm2BdW9I1+Hmie4bejwxOWAncCrff8uHnPf0bplY0ooIACCiiggAIKZBYwAMxM540KKKCAAgoooEBtBd4N/PmY0X0BWAL8fMyvP6157t9Tx/z6KcDttRVyYAoooIACCiigQIUEDAArNFl2VQEFFFBAAQUUGJBAWMkXVvSFlX2tnw8AF7f8QrjuM8CLx1x3DfCOAfXVxyiggAIKKKCAAgr0EDAA9BVRQAEFFFBAAQUUaCcQVvSFir5hhd/oJ5wH+Grg081feA/wZ2Nu/nKzkIjn/vleKaCAAgoooIACJREwACzJRNgNBRRQQAEFFFCghAJhZV9YCRgqBI9+djXP9ju+zVmBu5s/u7+EY7FLCiiggAIKKKDA0AoYAA7t1DtwBRRQQAEFFFAgkcCfAn8x5sp7gGe2qRYczv27I1GrXqSAAgoooIACCigwMAEDwIFR+yAFFFBAAQUUUKCSAuGcv/8DvLRH7z8IvLOSI7TTCiiggAIKKKBAzQUMAGs+wQ5PAQUUUEABBRSIIPBk4F5gZoe2vtQ8929sheAIj7YJBRRQQAEFFFBAgX4FDAD7FfR+BRRQQAEFFFBgOAROAjYCY//7MZz79zxg+3AwOEoFFFBAAQUUUKB6AgaA1Zsze6yAAgoooIACChQhcC5wfZsHbwUWAI8U0SmfqYACCiiggAIKKNBbwACwt5FXKKCAAgoooIACwy7wfCBs853cAWIVcN6wIzl+BRRQQAEFFFCgrAIGgGWdGfulgAIKKKCAAgqUQ2A68FXgV3p05zTgpnJ02V4ooIACCiiggAIKtAoYAPo+KKCAAgoooIACCnQT+Afg9WMu+CywGJjU8us/BeYD35VTAQUUUEABBRRQoFwCBoDlmg97o4ACCiiggAIKlEngrcBHxnRoW/PMv7cDV4z52deA3/I8wDJNoX1RQAEFFFBAAQXGV3HTRAEFFFBAAQUUUECBIBBW831xzLl/+4ATgW82qwF/Gnj5GC7PA/T9UUABBRRQQAEFSibgCsCSTYjdUUABBRRQQAEFSiDwpOa5f8eM6csbgXUtv3Y0cC8wa8x1ngdYgkm0CwoooIACCiigwKiAAaDvggIKKKCAAgoooMBYgVDM47VjfvFvgDe3oXohsMHzAH2JFFBAAQUUUECB8goYAJZ3buyZAgoooIACCihQhMDbgA+PefA3muf+PdShQxe3OQ8wVA4O4eAjRQzCZyqggAIKKKCAAgocFDAA9G1QQAEFFFBAAQUU+P/bu2ObhsEoCMBXpWYFdgiiYYksQJWeVViAip4VaMgENFTswAbIEkjIkpETRRcn+trI+u/5s4voiudfgXWSXZLVH5Jh79/w+8c/TMN/SvsAvUcECBAgQIAAgYUKKAAX+mCMRYAAAQIECBAoC1wlGb7iez3KvU/yPGMW+wBnILmEAAECBAgQIHAKAQXgKdRlEiBAgAABAgSWJ/CSZDMa6ynJdo9R75K8jvYBfv18Ufhzj3NcSoAAAQIECBAgcEQBBeARMR1FgAABAgQIEDhTgYckj6PZ35PcJpna+zd1q/YBnulLYGwCBAgQIEDgcgUUgJf7bN0ZAQIECBAgQGCOwE2StwP2/k2dbR/gHHXXECBAgAABAgSKAgrAIrYoAgQIECBAgAABAgQIECBAgAABAm0BBWBbXB4BAgQIECBAgAABAgQIECBAgACBooACsIgtigABAgQIECBAgAABAgQIECBAgEBbQAHYFpdHgAABAgQIECBAgAABAgQIECBAoCigACxiiyJAgAABAgQIECBAgAABAgQIECDQFlAAtsXlESBAgAABAgQIECBAgAABAgQIECgKKACL2KIIECBAgAABAgQIECBAgAABAgQItAUUgG1xeQQIECBAgAABAgQIECBAgAABAgSKAgrAIrYoAgQIECBAgAABAgQIECBAgAABAm2BbxTHXTOkbfwvAAAAAElFTkSuQmCC\" 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     "output_type": "display_data"
    }
   ],
   "source": [
    "#TODO 请选择最适合的直线 y = mx + b\n",
    "m1 = -1.5\n",
    "b1 = 10\n",
    "\n",
    "# 不要修改这里！\n",
    "vs_scatter_2d(X, Y, m1, b1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2.2 计算平均平方误差 (MSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "我们要编程计算所选直线的平均平方误差(MSE), 即数据集中每个点到直线的Y方向距离的平方的平均数，表达式如下：\n",
    "$$\n",
    "MSE = \\frac{1}{n}\\sum_{i=1}^{n}{(y_i - mx_i - b)^2}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.21432772711\n"
     ]
    }
   ],
   "source": [
    "# TODO 实现以下函数并输出所选直线的MSE\n",
    "def calculateMSE2D(X,Y,m,b):\n",
    "    return sum([(y - m*x - b)**2 for x, y in zip(X, Y)])/len(X)\n",
    "\n",
    "# TODO 检查这里的结果, 如果你上面猜测的直线准确, 这里的输出会在1.5以内\n",
    "print(calculateMSE2D(X,Y,m1,b1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2.3 调整参数 $m, b$ 来获得最小的平方平均误差\n",
    "\n",
    "你可以调整3.2.1中的参数 $m1,b1$ 让蓝点均匀覆盖在红线周围，然后微调 $m1, b1$ 让MSE最小。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3 (选做) 找到参数 $m, b$ 使得平方平均误差最小\n",
    "\n",
    "**这一部分需要简单的微积分知识(  $ (x^2)' = 2x $ )。因为这是一个线性代数项目，所以设为选做。**\n",
    "\n",
    "刚刚我们手动调节参数，尝试找到最小的平方平均误差。下面我们要精确得求解 $m, b$ 使得平方平均误差最小。\n",
    "\n",
    "定义目标函数 $E$ 为\n",
    "$$\n",
    "E = \\frac{1}{2}\\sum_{i=1}^{n}{(y_i - mx_i - b)^2}\n",
    "$$\n",
    "\n",
    "因为 $E = \\frac{n}{2}MSE$, 所以 $E$ 取到最小值时，$MSE$ 也取到最小值。要找到 $E$ 的最小值，即要找到 $m, b$ 使得 $E$ 相对于 $m$, $E$ 相对于 $b$ 的偏导数等于0. \n",
    "\n",
    "因此我们要解下面的方程组。\n",
    "\n",
    "$$\n",
    "\\begin{cases}\n",
    "\\displaystyle\n",
    "\\frac{\\partial E}{\\partial m} =0 \\\\\n",
    "\\\\\n",
    "\\displaystyle\n",
    "\\frac{\\partial E}{\\partial b} =0 \\\\\n",
    "\\end{cases}\n",
    "$$\n",
    "\n",
    "### 3.3.1 计算目标函数相对于参数的导数\n",
    "首先我们计算两个式子左边的值\n",
    "\n",
    "证明/计算：\n",
    "$$\n",
    "\\frac{\\partial E}{\\partial m} = \\sum_{i=1}^{n}{-x_i(y_i - mx_i - b)}\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\frac{\\partial E}{\\partial b} = \\sum_{i=1}^{n}{-(y_i - mx_i - b)}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO 证明:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3.2 实例推演\n",
    "\n",
    "现在我们有了一个二元二次方程组\n",
    "\n",
    "$$\n",
    "\\begin{cases}\n",
    "\\displaystyle\n",
    "\\sum_{i=1}^{n}{-x_i(y_i - mx_i - b)} =0 \\\\\n",
    "\\\\\n",
    "\\displaystyle\n",
    "\\sum_{i=1}^{n}{-(y_i - mx_i - b)} =0 \\\\\n",
    "\\end{cases}\n",
    "$$\n",
    "\n",
    "为了加强理解，我们用一个实际例子演练。\n",
    "\n",
    "我们要用三个点 $(1,1), (2,2), (3,2)$ 来拟合一条直线 y = m*x + b, 请写出\n",
    "\n",
    "- 目标函数 $E$, \n",
    "- 二元二次方程组，\n",
    "- 并求解最优参数 $m, b$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO 写出目标函数，方程组和最优参数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3.3 将方程组写成矩阵形式\n",
    "\n",
    "我们的二元二次方程组可以用更简洁的矩阵形式表达，将方程组写成矩阵形式更有利于我们使用 Gaussian Jordan 消元法求解。\n",
    "\n",
    "请证明 \n",
    "$$\n",
    "\\begin{bmatrix}\n",
    "    \\frac{\\partial E}{\\partial m} \\\\\n",
    "    \\frac{\\partial E}{\\partial b} \n",
    "\\end{bmatrix} = X^TXh - X^TY\n",
    "$$\n",
    "\n",
    "其中向量 $Y$, 矩阵 $X$ 和 向量 $h$ 分别为 :\n",
    "$$\n",
    "Y =  \\begin{bmatrix}\n",
    "    y_1 \\\\\n",
    "    y_2 \\\\\n",
    "    ... \\\\\n",
    "    y_n\n",
    "\\end{bmatrix}\n",
    ",\n",
    "X =  \\begin{bmatrix}\n",
    "    x_1 & 1 \\\\\n",
    "    x_2 & 1\\\\\n",
    "    ... & ...\\\\\n",
    "    x_n & 1 \\\\\n",
    "\\end{bmatrix},\n",
    "h =  \\begin{bmatrix}\n",
    "    m \\\\\n",
    "    b \\\\\n",
    "\\end{bmatrix}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO 证明:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "至此我们知道，通过求解方程 $X^TXh = X^TY$ 来找到最优参数。这个方程十分重要，他有一个名字叫做 **Normal Equation**，也有直观的几何意义。你可以在 [子空间投影](http://open.163.com/movie/2010/11/J/U/M6V0BQC4M_M6V2AJLJU.html) 和 [投影矩阵与最小二乘](http://open.163.com/movie/2010/11/P/U/M6V0BQC4M_M6V2AOJPU.html) 看到更多关于这个方程的内容。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4 求解 $X^TXh = X^TY$ \n",
    "\n",
    "在3.3 中，我们知道线性回归问题等价于求解 $X^TXh = X^TY$ (如果你选择不做3.3，就勇敢的相信吧，哈哈)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 实现线性回归\n",
    "'''\n",
    "参数：X, Y 存储着一一对应的横坐标与纵坐标的两个一维数组\n",
    "返回：线性回归的系数(如上面所说的 m, b)\n",
    "'''\n",
    "def linearRegression2D(X,Y):\n",
    "    # convert 1 dimension vector to two dimensions\n",
    "    x2 = [[v] for v in X]\n",
    "    x1 = [[1] for v in X]\n",
    "    x21 = augmentMatrix(x2, x1)\n",
    "    y2 = [[w] for w in Y]\n",
    "    XT = transpose(x21)\n",
    "    XT_X = matxMultiply(XT, x21)\n",
    "    XT_Y = matxMultiply(XT, y2)\n",
    "    result = gj_Solve(XT_X, XT_Y)\n",
    "    result = transpose(result)[0]\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(-1.3482, 10.0003)\n"
     ]
    }
   ],
   "source": [
    "# 请不要修改下面的代码\n",
    "m2,b2 = linearRegression2D(X,Y)\n",
    "assert isinstance(m2,float),\"m is not a float\"\n",
    "assert isinstance(b2,float),\"b is not a float\"\n",
    "print(m2,b2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "你求得的回归结果是什么？\n",
    "请使用运行以下代码将它画出来。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.993422579118\n"
     ]
    }
   ],
   "source": [
    "## 请不要修改下面的代码\n",
    "vs_scatter_2d(X, Y, m2, b2)\n",
    "print(calculateMSE2D(X,Y,m2,b2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bonus !!!\n",
    "如果你的高斯约当消元法通过了单元测试, 那么它将能够解决多维的回归问题  \n",
    "你将会在更高维度考验你的线性回归实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 生成三维的数据点\n",
    "X_3d, Y_3d = generatePoints3D(seed)\n",
    "vs_scatter_3d(X_3d, Y_3d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "你的线性回归是否能够对付三维的情况?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [],
   "source": [
    "def linearRegression(X,Y):\n",
    "    x1 = [[1] for v in X]\n",
    "    # 构造 X 的增广矩阵\n",
    "    mat_X = augmentMatrix(X, x1)\n",
    "    mat_Y = [[y] for y in Y]\n",
    "    XT = transpose(mat_X)\n",
    "    A = matxMultiply(XT, mat_X)  \n",
    "    b = matxMultiply(XT, mat_Y) \n",
    "    result = gj_Solve(A, b, decPts=4, epsilon=1.0e-16) \n",
    "    \n",
    "    return [x for [x] in result]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "coeff = linearRegression(X_3d, Y_3d)\n",
    "vs_scatter_3d(X_3d, Y_3d, coeff)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "celltoolbar": "Raw Cell Format",
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}