more changes for code directory

Chapter05_Kalman_Filters/Kalman_Filters.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:293a09cc844ccb8d9ee5a2a79a6375ecb56770e0e5e90dd5d3698900e6006206"
+  "signature": "sha256:dea8b0a50eff26f334abc7863ef4ec47ce0257f7405dc287360ef650b1855279"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -23,7 +23,7 @@
       "#format the book\n",
       "%matplotlib inline\n",
       "import sys\n",
-      "sys.path.insert(0,'../') # allow us to import book_format\n",
+      "sys.path.insert(0,'../code') # allow us to import book_format\n",
       "import book_format\n",
       "book_format.load_style()"
      ],
@@ -250,7 +250,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7f4ac50ad828>"
+        "<IPython.core.display.HTML at 0x7f9a41e44828>"
        ]
       }
      ],
@@ -342,10 +342,10 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        " 0.4900\t-1.5190\t 0.0639\t 0.5312\t-0.4402\t\n",
-        "-0.8721\t 0.4444\t 0.0782\t 1.0500\t-1.4336\t\n",
-        " 0.3928\t 1.6109\t 0.3260\t 0.4645\t 0.2985\t\n",
-        " 1.2323\t 0.6590\t 0.9813\t-0.7694\t 0.2915\t\n"
+        "-1.8386\t 0.7546\t-0.5046\t-2.9576\t-0.2675\t\n",
+        " 1.4816\t-0.9532\t-0.8862\t-0.3574\t-0.4382\t\n",
+        " 0.1608\t 1.1827\t 0.4886\t 2.0902\t-0.2451\t\n",
+        "-0.4182\t 0.5224\t 0.1251\t 2.1121\t-0.6231\t\n"
        ]
       }
      ],
@@ -392,7 +392,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAr4AAAF2CAYAAACI1JsxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Wl0VHWe//FPpbKAREhSCagQ2SFBGMQFWUylWZXVQXBs\n+Q9it0or6qBHXKBlsWOziEu33aPtCIID2CCbMA0NmD5MYgTnKIvnIBJlD9hsIUFAYiqV+j+gq5pA\nlptacm9VvV+PkqpbdX98KeWdm1u3bIWFhR4BAAAAES7G7AUAAAAADYHwBQAAQFQgfAEAABAVCF8A\nAABEBcIXAAAAUYHwBQAAQFQgfAEAABAVag3f3Nxc3X///erWrZumTJniu93lcmnq1Km65ZZb1K9f\nP/31r38N+UIBAACAQMTWdmfTpk31yCOPaOvWrSorK/PdvmjRIu3bt0/5+fnas2ePfvWrX6lHjx66\n7rrrQr5gAAAAwB+1HvHt2bOnBg0apGbNmlW5fePGjRo3bpwSExPVs2dP9ejRQ5988klIFwoAAAAE\notYjvl4eT9VPNT506JDatm2ryZMnq3///mrfvr0OHjwYkgUCAAAAwWDozW02m63K9xcvXtQ111yj\n7777TidPnlSTJk30448/hmSBAAAAQDD4dcS3cePGunjxotauXStJeuWVV9SkSZOrHnf48GHFxHDh\nCAAAAITWuXPn1KVLl1q3MRS+Vx7xbdOmjfbv36+bbrpJkrR//34NGDDgqsfFxMQoMzPT6HqjlsPh\n0OrVq5WdnW32UiyNORnHrIxhTsYwJ+OYlTHMyThmVVV5hVsrP/1Ob63dqaJT5yVJHW9I0kvjnGp5\nbd2PrzV8Kysr5XK55Ha75Xa7VV5erpiYGA0ZMkSLFy9Wv379tGfPHu3atUtz5swJyh8IAAAAuFxN\nwfvMvbdo+B1t1TwtTQUFBXU+T63h+/HHH2vq1Km+79etW6cnn3xSjz32mA4cOKDs7Gw1a9ZMs2bN\nUosWLQL8IwEAAAD/VFfw2ut5Sm2t4Xvvvffq3nvvrfa+WbNmadasWfXaGWrGKSHGMCfjmJUxzMkY\n5mQcszKGORkXjbMKdvB6GTrHF6GXmZmp4uJis5dheczJOGZlDHMyhjkZx6yMYU7GRdOsQhW8XoQv\nAAAATBXq4PUyPXxLS0vlcrnMXoapSkpKJEkVFRUmr8Ta6jsnj8ej5ORkxcXFhXJZAADATw0VvF6m\nhq/3Qy/S0tLMXAYiVGVlpU6ePCmHw0H8AgBgIQ0dvF6mhu/58+eJXoRMTEyMmjdvrtOnT6t58+Zm\nLwcAgKhnVvB6mRq+Npvtqg/HAIIpJiaG1xgAACYzO3i9TD/HFwAAAJHJKsHrRfgCAAAgqKwWvF6E\nLwAAAILCqsHrZe7eI0yrVq20YsUKs5cRcr169dKbb74Z0HM8/fTTGjNmTJBWBAAAzFRe4daHW/bK\nOfkjPTf/UxWdOq+ONyTp7Sf7629zR+ue3u1Nj16JI77ww4YNG9S4ceNq7ysqKlLv3r21cuVK9erV\nq8bneOWVV+R2u0O1RAAA0ACsfoT3SoQv6i0lJaXObTweT633JyYmBms5AACggYVb8HpZc1VhoKys\nTJMnT1bnzp11yy236M9//vNV2/z973/Xww8/rM6dO6tz58569NFHdfLkySrbLFiwQD169FDnzp01\nY8YMjR49Ws8884zhdRQVFalVq1Z6++231a9fP7Vv314///nPdezYsSrbLV26VH379lXbtm115513\navny5VXu/+GHH/TUU0+pe/fu6tChg/r37681a9ZU2cbpdKpVq1Zq1aqV3njjjWrX0bt3b0nSfffd\n59v2888/9233wgsv+G6v6VSHTZs2acCAAWrXrp169uyp//zP/6xy/5gxY/TKK6/oqaeeUqdOndS7\nd29t2rTJ8MwAAIB/wuWUhppY/ohvy//3Xkie99jSRwN6/O9+9zv97W9/0/vvv6+kpCRNnTr1qm2e\nfPJJlZWVaeXKlfJ4PHr++ef15JNP6qOPPpIkffbZZ3r55Zf1m9/8Rk6nU++99562b9+u1q1b13s9\nCxYs0Jtvvqm0tDRNmTJFTz31lFavXu3bz4svvqiZM2eqf//+ys3N1eTJk9WmTRvdcccdkqTXXntN\nX3zxhRYuXKjmzZursLDQ98l6XmvXrlVFRYWGDh161bVxW7ZsqV27dunYsWMaNmyY5s+fr9tuu02S\n1KxZM99206ZN0+TJkzV9+nSdPn36qj/HgQMHNGHCBD3++OO6//77tX37dr3wwgtq0aJFlVD+8MMP\nlZOTo2effVavvvqqnn32WWVnZ6tRo0b1nh0AAKhduB7hvZLlw9eqlixZookTJ6pv376SpJdeekmj\nRo3y3V9YWKj/+7//08cff6xu3bpJkl5++WWNHj1a+/btU4cOHfTf//3fysrK0kMPPSRJmjlzptau\nXevXen75y1/K6XRKkqZPn66RI0fqu+++U8eOHfXBBx8oKytLDz/8sCTp0Ucf1SeffKKFCxf6wvfI\nkSPq0KGDbrnlFkmX3qh3peTkZEmS3W6/6r6YmBilpqbq4sWLkqSkpCSlpqZetV1iYqISExOVkJBQ\n7ekQS5cuVevWrfXiiy9Kktq2batt27Zp0aJFVcI3Oztbo0ePliQ9/vjjWrdunQ4fPqzOnTsbnBgA\nAKhLpASvl+XDN9Ajs6FQWlqq0tJSZWRk+G7r0qVLlW0OHjwoSbrpppt8t3m/PnDggDp06KADBw4o\nOzvbd39CQoLatGnj15ouX4s3/g4ePKiOHTvq4MGDVfbjXcvWrVt9348dO1aPP/64Bg8erDvuuEN9\n+vTR3Xff3eCfenbw4EFlZmZetdaNGzdWua1du3a+r5OSkiRd+nsBAACBi7Tg9bJ8+FpRsGKwuuep\n601h9XkuI/d5DR48WF988YU+/fRTffbZZ3ryySc1cuTIgC9bVl82m83QDGJjr37p+js7AABwSaQG\nr1d4r94kzZo1U0pKir755hvfbXv27KmyjffI7e7du323eb9u27atpEtHLb/++mvf/WVlZb4jxfV1\n+Vr27t1bZQ1t2rSpsh/vWrzr8EpJSdE999zjO2d2w4YN9V5HXFycJKmioqLObasL8jZt2lT5s9S0\nVgAAEDzh/qY1ozji66dx48Zp/vz56t69u5KTk/Xb3/62yv0ZGRnq2bOnZsyYoTlz5sjj8WjGjBnq\n3bu3OnbsKEl68MEHdf/992vhwoXKysrSggUL5HK5/FrPwoUL1a1bN6WmpionJ0e33367OnXq5NvP\nAw88oAULFqhfv37Kzc3Vtm3btHLlSt/jX3/9dXXp0kUZGRm6cOGCNm/erK5du/ruLysr0w8//CDp\nUtSeP3/ed4WK5s2b+7Zr3ry5EhMTtX79enXr1k0JCQlKSEiQzWZTZWWl7w1tZWVlKi8v16lTp+Tx\neJScnKy4uDiNHTtW8+fP1+zZs/Vv//Zv2rFjh9auXas5c+ZU+fNydBcAgMBF+hHeKxG+fpo0aZJO\nnjyphx9+WE2aNNFzzz2n7du3V9nmj3/8o1566SXfm7KcTmeVQO7Tp49efvllvfXWW5ozZ47GjRun\n7t27Kz4+vt7reeihhzRt2jQdPXpUt912W5XLjd15552aPXu23nnnHeXk5Khly5aaN29elQ+YSEhI\n0Lx583TkyBE1btxYvXr10syZM333r127Vs8++6ykS0dq3333Xb377ruy2WwqKirybRcTE6N58+bp\n1Vdf1c033yyXy+X7MItjx475LnfmfZ4ePXrIZrNpxYoV6tWrl9q3b68//elPmjdvnv7rv/5Lqamp\nmjRpku67774qf94rjxY39LnIAACEs2gLXi9bYWFhyA6dFRUVXfVGpcudOnVKaWlpodp9WOrZs6ce\neughTZw40dD2Rj8pLZpF4+vM4XBIkoqLi01eibUxJ2OYk3HMyhjmZFywZxWpwetwOFRQUKD09PRa\nt+OIr8lee+01DRo0SM2aNdOqVatUXFyskSNHmr0sAAAQQSI1eOuL8DXZV199pYULF6q8vFydO3fW\nBx98UO01dGvDr/kBAEB1CN6qCF+TLV68OKDHp6enVznHFgAAgOCtHuELAAAQIQje2hG+AAAAYY7g\nNcbU8PV4PPJ4PJyjipCprKzkmr8AgIhF8NZPQOH75Zdf6pVXXtHhw4fVtm1bzZo1SxkZGYYfn5iY\nqLNnzyopKSmQZQDVqqys1MmTJ32XggEAIFIQvP7xO3zLy8v19NNP6/nnn9eIESP0pz/9SZMmTdKm\nTZsMP8c111zj+/SuaBYbe+mvwcjH/Eaz+s7J4/HI4XD4PkYZAIBwR/AGxu/wPXDggC5evOi75uwv\nf/lL/f73v9e3337r+6hcIzjay4W8jWJOAIBoRfAGR9DO8fWeq3vkyJF6hS8AAACqV+5ya0nubs3+\n8FOCNwj8Dt927dqpcePG+vjjjzVs2DAtWLBAdrtdFy9erLId51fWzfureGZVO+ZkHLMyhjkZw5yM\nY1bGMKe6eYP31eUrdOh4qSQp40aHpo7tq9FZGbLbCd7LGT2t0e/wjY+P1+9//3v99re/1Zw5czRs\n2DC1atVKiYmJVbbLycnxfe10OpWdne3vLgEAACKaN3jnLtuqwyfOSpIyb0zVlLF9CN4r5OXlKT8/\nX5Jkt9vldDrrfIytsLAwKNd6KikpUXZ2tjZu3KgbbrhBklRUVKTMzMxgPH1E49xVY5iTcczKGOZk\nDHMyjlkZw5yuVtM5vNMedGp0VoZKS0tMXqG1ORwOFRQUKD09vdbtAjrH98CBA2rVqpUuXryonJwc\n9erVyxe9AAAAqF1db1prnpZm8gojS0Dhm5ubq/nz56uiokJOp1OvvvpqsNYFAAAQsbhKgzLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4abc066128>"
+        "<matplotlib.figure.Figure at 0x7f9a28e15f98>"
        ]
       }
      ],
@@ -435,9 +435,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAGWCAYAAAA5TTZIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAGWCAYAAAA5TTZIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffc01d0>"
+        "<matplotlib.figure.Figure at 0x7f9a28db9400>"
        ]
       }
      ],
@@ -469,9 +469,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAGWCAYAAAA5TTZIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAGWCAYAAAA5TTZIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4abc053be0>"
+        "<matplotlib.figure.Figure at 0x7f9a28bfb7f0>"
        ]
       }
      ],
@@ -489,9 +489,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAGWCAYAAAA5TTZIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAGWCAYAAAA5TTZIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aafdf2eb8>"
+        "<matplotlib.figure.Figure at 0x7f9a28da1e48>"
        ]
       }
      ],
@@ -534,7 +534,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAssAAAF2CAYAAACYtNXtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XlYlOXixvHvsG+uqKAk7oJJCi64oaiZSmWLZZlJnjJb\ntEXbFz2ZWlZaeixPZZtLZVZqZimlmVouuKWpkQhuLLnhggw4bPP7gw7n51FBEXgGuD/X5XUxvu+8\n7z081zD3wDvPY9mzZ48dERERERE5j5PpACIiIiIijkplWURERETkIlSWRUREREQuQmVZREREROQi\nVJZFRERERC5CZVlERERE5CJUlkVERERELqLYsnz48GGio6MJDQ1l4MCB7N27t9iD2u12Ro8eTWRk\nJMHBwaSmpp6zPSYmhn79+tGhQwfuvvtuEhISSv4IRERERETKSLFledy4cQQFBbFp0yaioqIYM2bM\nJR24ffv2zJgx47z/P378OM8++yyTJk1i8+bNdOrUieeee+7yk4uIiIiIlLEiy3JGRgbr169nxIgR\nuLm5MWzYMFJSUoiPjy/yoBaLhejoaFq3bn3etqSkJKpVq0bHjh2xWCz069ePxMTEK3sUIiIiIiJl\noMiyfPDgQdzc3PDy8mLIkCEkJycTGBjIvn37SnzC4OBgXFxciI2NJS8vj5iYGHr27Fni44mIiIiI\nlBWXojZmZWXh7e2N1WolMTGR9PR0vL29ycrKKvEJPT09eemll3jwwQfJyckhICCAOXPmlPh4IiIi\nIiJlpciy7OnpidVqxd/fn9jYWACsViteXl4lPmFcXBzjx49n4cKFNGnShHnz5vHAAw+wdOnS8/Y9\ndOgQFoulxOcSERERESmOzWajefPmF9xWZFlu1KgRNpuNI0eO4OfnR3Z2NocOHaJJkyYlDrNu3Tra\ntGlDs2bNABg0aBCTJ0/m+PHj1KlT55x9LRYLrVq1KvG55NL5+vqyaNEiIiMjTUepsjQG5lX0McjO\nzSMv346rsxPOTpYK+cuGij4GlYHGwDyNQfmLi4u76LYiy7KPjw8RERHMmjWLZ555hjlz5hAQEEDL\nli0L94mOjqZt27Y89dRT59w3OzubnJwcoKCt22w23N3dad68OZ988gn79++ncePGLFmyhFq1auHr\n63slj1FEpNKz2+0cPHqGHfuOsevAcQ4cOcOhY+kcPpHJmaxsbDl5hfs6WSzUruZB3Zqe1K/tTcuA\nWgRdVYs2TerQMqAWTk4Vr0iLiJhQZFkGmDBhAk8//TTh4eE0a9aMadOmnbM9JSWFq6666rz79e/f\nn9TUVCwWC1FRUVgsFuLi4ujZsyfR0dHce++9nDlzhqZNm/LOO+9UyN+AiIiUtVNWGz9vT+Ln35NY\n83sKx9Mv/pkRZycLzk4WcvPs5NvtHE/P4nh6FnGHTrBqe1LhfrV83OkU7M+1oYH0bdeIOjU8y+Oh\niIhUSJY9e/bYTYe4mKSkJF2GUU58fX2Ji4ujXr16pqNUWRoD8xxlDLJz8/hx60EWrUtg1fYkcvLy\nC7fVqe5J26Z1aNu0Ls3q1yCwXnUa+HpTw8sdDzfnwl885OTmc+LMWY6eyiTp+Bn2JJ/kz6QTbIk/\nyuGT1sLjOVksdAr2587IltzYqSmebsX+DqVMOcoYVGUaA/M0BuUvLi6Ohg0bXnCbyrIAFF4Gk5aW\nZjhJ1aUxMM/0GJw4c5Z5P8UxZ8UfHDmVCRSU2S5X1+fa0Ib0atOQFgE1r+gvcXa7nUPHzvDLrhR+\n2HKQX3alFJbx6l5uDOrRkgejriGgjk+pPKbLZXoMRGPgCDQG5a+osmz2VwgiIsLRU5n865vf+GL1\nHs7+fd1x0FW1GNwziJs7N8OvVslnIPpfFouFRvWq06h3dYb2bkV6ZjZLN+7j85//ZPu+Y3wUs4s5\nK3Zzc5dmPH5LGM3q1yy1c4uIVEQqyyIihqRnZvPv73bwYcwusmy5APQObciIqGvo3rpBuXyWo7qX\nG3f3Dubu3sHsOnCc977/nSUb9rHw1wS+WZ/I0N6teGJgO13XLCJVlsqyiEg5y8+38+XaeCbNj+Vk\nhg2Afu0b8cygDgQ3rG0sV0jjOrwzqjfPDOrAjCXbWbAmnjkr/+DrX/fy6E2hPHjDNbi5OBvLJyJi\ngsqyiEg5ik8+yXMf/0rsnsMAdA725/nB4XRo4Wc42X8F1qvO1BE9GBEVwivzN/HT9iRe+3Iz36xP\nYMqIHrRrrg8diUjVobIsIlIO8vLzeXvJdqYv/o2cvHzqVPdk/NDO3NK1mcNOnRl0VW3mPt2ftbtS\neP7jX/kz+SQ3jV/CfX1b8/yd4Xi66yVERCo/J9MBREQqu0NH07lt4ndM+XorOXn5DO0dzJqpg7i1\nW3OHLcr/X4+QAFZOvo1RA9riZLHw0Q+7iRq7mN0H9Ul9Ean8VJZFRMrQ4nUJXPf8IjbHH8Gvphfz\nn4vi9eHdqentbjraZfF0d+GFweEsm3gLLRrUZG/qKQa8tISPf9iF3e6wM5CKiFwxlWURkTKQk5vP\nP+eu55F//0zG2RyiOjRm5Wu30eOa81c8rUhCGtdh+aRbubt3MLacPMbN3cAD/1qJ9WyO6WgiImVC\nZVlEpJQdO53J4Mnf89EPu3F1duLVe7vxweg+1K7mYTpaqfB0d+GN4d2Z9Xgfqnu5sWzzAW56aQkH\nj6abjiYiUupUlkVEStHug2lEjf2GjX8exq+mF1+Pu5Fhfa6uENcmX64bwpvw3YSbad6gJn8mn+T6\ncd/wy64U07FEREqVyrKISClZ83syAycs5a8TVjq29GP5pFsdakq4stCsfk2WvnwzfcICOZVhY+gb\ny/lybbzpWCIipUZlWUSkFCxYs4d7psaQcTaHm7s0Y8ELN5TqMtWOrLqXG5880ZdRA9qSm2dnzPtr\nmLHkN33wT0QqBZVlEZErNGPJbzwxay25eXZGDWjLOyN74e5atVa6c3Ky8MLgcCYN64rFAq9/uYUX\nZ68nLz/fdDQRkSuiGeVFRErIbrfz+ldbeHvJdiwWmDSsG/+47mrTsYy6t29r6tbw5LF3VzNn5R+c\nycpm2oORuDjrdzMiUjGpLIuIlIDdbuelTzfyUcwunJ0szHi4J7d0bW46lkO4sVNTfKt7MmzqDyxa\nl0BObj5vj+yFq4sKs4hUPPrJJSJymex2O899/CsfxezC1dmJ9x+7VkX5f3RpVZ/Pn4uimqcrS2P3\n8fDbP5Gdm2c6lojIZVNZFhG5DHa7nZfmbeDTVX/i4erMJ0/2JapjE9OxHFKHFn588fwN1PByY/mW\nAzw04ydycnUNs4hULCrLIiKX4bUvt/DRD7txc3Hioyeuo1fbhqYjObTQZnX58sUbqOntzg9bDzLm\n/dXk52uWDBGpOFSWRUQu0b+++Y13vt2Os5OF9x69lp5tVJQvRUjjOnz6bH+8PVxZvD6RF2av07Ry\nIlJhqCyLiFyCD5bv5I2vtmCxwIyHe9KvQ2PTkSqUsGb1mP1kXzxcnZn3UxyvzN+kwiwiFYLKsohI\nMZZsSGT8pxsBmHp/D32Yr4S6Xt2A9x/vg4uzhXe//513vt1hOpKISLFUlkVEirD+j1RGv7cagHFD\nOjG4Z5DZQBVcn7BA3h7ZC4sFXvtyM4vWJZiOJCJSJJVlEZGL2JN8guHTVpCdm899fVvz4PXXmI5U\nKdzUuRkvD+0CwBPvr2H9H6mGE4mIXJzKsojIBRw+aWXoGzGkZ2YT1aEx46M7Y7FYTMeqNIb3D2F4\n/xBy8vK5f9oK9qacNB1JROSCVJZFRP6H9WwO90z5gdQ0K+1b1OPtUb1wdtKPy9L20t2diOrQmNOZ\n2Qx9I4ajpzJNRxIROY9++ouI/D/5+XZGv7eG3QfTaOxXndlP9sPTzcV0rErJ2cmJt0f2IqxZXZKP\nZ3DfWz9yNjvXdCwRkXMUW5YPHz5MdHQ0oaGhDBw4kL179xZ7ULvdzujRo4mMjCQ4OJjU1HOvR0tK\nSmL48OGEhYURERHB4sWLS/4IRERK0eT561i2eT/VPF2Z/WRfalfzMB2pUvN0d2H2k/24qo4PvyUe\n45EZMZpSTkQcSrFledy4cQQFBbFp0yaioqIYM2bMJR24ffv2zJgx47z/z8vL46GHHqJVq1asX7+e\nlStX0q5du8tPLiJSyr75dQ8T5/2KxQIzH+lNi4BapiNVCXVqePLRmL54uDnz6cpdzFyyxXQkEZFC\nRZbljIwM1q9fz4gRI3Bzc2PYsGGkpKQQHx9f5EEtFgvR0dG0bt36vG1btmwhPT2dMWPG4OnpiYeH\nB40aNbqyRyEicoV2H0zjvinfAfDi4HCuDQ00nKhqCWnsy1sPRALw7KxV/LIrxXAiEZECRZblgwcP\n4ubmhpeXF0OGDCE5OZnAwED27dtX4hP++eefNG3alKeeeorOnTszdOhQEhMTS3w8EZErdTLjLMOn\n/UimLYe7erfmoRvamI5UJd3cpRlP3dGZvHw7D739EwePppuOJCJCkZ9aycrKwtvbG6vVSmJiIunp\n6Xh7e5OVlVXiE2ZkZLB161YmTJjAlClT+PDDD3niiSdYsmTJBff39fUt8bnk0rm6ugL6fpukMTAj\nP9/OiBlfk3Qsgw5B9fngqQG46KPPxrx6/7XsPnic5bEJPDhjFWun34Onu6vpWFWKfhaZpzFwLEWW\nZU9PT6xWK/7+/sTGxgJgtVrx8vIq8Qk9PT2pUaMGAwcOBGDo0KFMnz6dM2fOUK1atfP2nzhxYuHX\nPXr0IDIyssTnFhH5X29+tZFlsYnU8vFgwT9vx9PdlZycHNOxqixnZyc+feFWwh/+kJ37j/HEuyt5\nd3SU6VgiUsmsWbOGtWvXFt7u1avXRfctsiw3atQIm83GkSNH8PPzIzs7m0OHDtGkSZMShwLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffc61d0>"
+        "<matplotlib.figure.Figure at 0x7f9a28d9ee10>"
        ]
       }
      ],
@@ -571,9 +571,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAF2CAYAAABtSl5dAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsvXmYHGd57n1X78vsPYs00kiyJGuxFWzZwmaxLVvYgGPi\nxM7yBQz+yAnBCfLhEAc4JAccg4PNSQIkYfkCAQcIBi+RjVlsvGFky5u8yLv2dTTSbD1Ld0/v3fX9\nUfVWVVfX1t1VvUw/v+viwjPqma6ZqeV57/d+7ofbv38/D4IgCIIgCIJoc1yNPgCCIAiCIAiCaAao\nMCYIgiAIgiAIUGFMEARBEARBEACoMCYIgiAIgiAIAFQYEwRBEARBEAQAKowJgiAIgiAIAgAVxgRB\nEARBEAQBwEJh/OlPfxoXXXQRzj//fFx99dV4/PHHAQC5XA5/93d/h/POOw+XXXYZHnroIccPliAI\ngiAIgiCcgjMb8LFv3z6sXr0aPp8PTz/9NG644Qbs3r0bd955Jx599FHccccdeOutt3DDDTfgoYce\nwpIlS+p17ARBEARBEARhG6aK8YYNG+Dz+cDzPHK5HMLhMDiOw69//Wt85CMfQUdHBy644AJs3rwZ\njz76aD2OmSAIgiAIgiBsx2PlRbfccgt27NiBQCCA73znOwgGgzh27BjOOOMMfPrTn8a2bduwZs0a\nHD161OnjJQiCIAiCIAhHsNR8d8stt2DPnj341Kc+hc985jPIZDJIpVIIhUI4ePAgJicnEQ6HkUwm\nnT5egiAIgiAIgnAES4oxAHg8Hlx33XX48Y9/jGeffRbBYBCpVAoPPPAAAOAf/uEfEA6Hy77u+PHj\ncLko/IIgCIIgCIJwlng8jrPOOqvqr7dcGDN4ngfP81i1ahUOHz6Ms88+GwBw+PBhvOc97yl7vcvl\nwsaNG6s+QGLxEYlEcN9992Hr1q2NPhSiiaDzgtCCzgtCCzovCC0ikQh27dpV0/cwlHKnp6dx7733\nIpFIIJ/P46677sLMzAw2b96MK6+8Ev/1X/+FeDyO559/Hq+88gquuOKKmg6GIAiCIAiCIBqFoWLs\ncrnwy1/+El/96leRy+Wwdu1afPvb30ZPTw8++tGP4siRI9i6dSu6u7tx2223YWhoqF7HTRAEQRAE\nQRC2YlgY9/X14Yc//KH2F3o8uO2223Dbbbc5cmDE4obsNYQWdF4QWtB5QWhB5wXhBNQVRzQEuqER\nWtB5QWhB5wWhBZ0XhBNQYUwQBEEQBEEQoMKYIAiCIAiCIABQYUwQBEEQBEEQAKgwJgiCIAiCIAgA\nVBgTBEEQBEEQBAAqjAmCIAiCIAgCABXGBEEQBEEQBAGACmOCIAiCIAiCAECFMUEQBEEQBEEAoMKY\nIAiCIAiCIABQYUwQBEEQBEEQAKgwJgiCIAiCIAgAVBgTBEEQBEEQBAAqjAmCIAiCIAgCABXGBEEQ\nBEEQBAGACmOCIAiCIAiCAECFMUEQBEEQBEEAoMKYIAiCIAiCIABQYUwQBEEQBEEQANq8ME6mc3jt\n6BR4nm/0oRAEQRAEQRANpq0L41vufA5Xfv5neOnQZKMPhSAIgiAIgmgwbV0Yj00nAACHxuYafCQE\nQRAEQRBEo2nrwjiTKwAAovFUg4+EIAiCIAiCaDRtXRins0JhPD2fbvCREARBEARBEI2mrQvjTC4P\ngBRjgiAIgmgVeJ7H5+/4LR58/lCjD4VYhLR1YZwWrRQzMVKMCYIgCKIV2Ds6g3++5znc8sMnG30o\nxCKkrQvjDLNSUGFMEARBEC3B/EJW/P9Mg4+EWIy0d2FMzXcEQRAE0VIkUkJhnEznGnwkxGKkzQtj\nwWM8E0vTkA+CIAiCaAEWxIJ4gQpjwgHavDAWFON0rkAXGEEQBEG0AAnxeZ3M5FAskqhF2EvbFsaF\nYhHZfFH6OBonnzFBENUxPZ9COptv9GEQRFuQSMlCVoquO8Jm2rYwzuaKJR9HqQGPIIgqmFvI4MJP\n/RR//vVHG30oBNEWKHd4kxna7SXspW0L43SudJU5HaMGPIIgKudUNIF0toBDp2i0PEHUA6VivJAm\nxZiwl7YtjJm/mEFZxgRBVAO7l9CWLkHUB1KMCSdp28KYjYNmUGQbQRDVwO4lqQwVxgRRDxIlhTFd\nd4S9tG1hnFFbKeZJMSYIonJY0106W6DYR4KoA3ExxxigLGPCftq4MCbFmCCI2mGFcZHnS5JuCIJw\nhoUUKcaEcxgWxvl8Hp/97Gdx0UUXYcuWLbj++utx6NAhAEAsFsOnPvUpXHjhhbj44ovxzW9+sy4H\nbBcZtZWCPMYEQVSB0pZFPmOCcB6yUhBOYlgYF4tFrFy5Ejt27MCLL76Ibdu2Yfv27QCAb3zjG0in\n03jqqadwzz334O6778bOnTvrctB2kBIV43DAC4AKY4IgqkOZcEM+Y4JwHmXzHQ3nIuzGsDD2+XzY\nvn07hoaGAADXXnstjh8/jpmZGRw5cgSXXXYZfD4fli5dis2bN+Pw4cN1OWg7yIjKzrJIGABZKQiC\nqA6lYkxDPgjCeRIpSqUgnKMij/GePXswNDSE3t5eXHzxxXjiiSeQSqUwOjqKN954A+9617ucOk7b\nYR7j4UgHAEExpsYZgiAqRVkMk5WCIJwnkVY039EuDWEzHqsvjMfjuO222/C5z30OHMfhQx/6EHbu\n3IktW7agUCjgU5/6FDZs2KD5tZFIxLYDtguv/zQAYCjShZDfi2QmB3+oE50hf4OPbPHj9Qr2lWY8\nL4jG0arnBefxSf/tC4Rb7vibnVY9LwhnyBeKJbs0POehc4OQYPeLWrBUGGezWWzfvh1XXXUVrrzy\nSgDApz/9aWzYsAHf/e53MT09jY997GNYuXKl9O9Kbr31Vum/L7nkEmzdurXmA68VdmEFvB70dwdx\nYjKHqfkUFcYEQVSE0ldM27oE4SwJRVQbQB5jAti5cyeefPJJAIDb7cYll1xS0/czLYwLhQJuuukm\nrFq1Cp/85Celzz/11FO4++674fV6sXTpUmzduhXPPvusZmH8iU98ouTjaDRa00HbQXRWHN9azKOv\nw48Tk8Ch46fQ7SsYfyFRM2x13wznAdE8tOp5MRtLSP89MTWDaLSzgUez+GjV84JwhrFoouTjmfkE\nnRttzqZNm7Bp0yYAwv1i165dNX0/U4/xzTffDJfLhVtuuaXk86tXr8bPfvYz5PN5TE1NYdeuXTjz\nzDNrOph6wjzGAZ8bfV0BAEA0TskUBEFURkbhK07naGFNEE6izDAGSDEm7MdQMR4bG8OOHTsQDAZx\n/vnnS5//3ve+h3/8x3/El770Jbzzne+E3+/H+9//fnzoQx9y/IDtgj3A/F43Ip1CYTxDkW0EQVSI\nshimuDaCcJaEqhCma46wG8PCeNmyZdi3b5/uv//whz+0/YDqRUZRGPd3BQEA0zGKbCMIojIolYIg\n6gcrjD1uF/KFIinGhO207Uho9jAL+DyIMCsFKcYEQVRIyeQ7Uq8IwlEWxOa7oV5hBgHFtRF207aF\nseQx9rrR1ykoxjTkgyCISiHFmCDqB1OM5cKYFGPCXtq+MPb73OjvJsWYIIjqKJ18R813BOEkrPlu\nSZ9QGC+kaTFK2Ev7FsZZ5jH2IMIUYyqMCYKokHSOFGOCqBeyYixMrU2RYkzYTNsWxuxh5ve6ZY8x\nWSkIgqiQEsWY/I4E4SisMGaKMXmMCbtp28KYKcYBnxzXFo2lwfN8Iw+LIIgWgzzGBFE/mJWivysE\nt4tDrlBENk8WJsI+2rYwVuYYhwJeBP0eZHIFin4hCKIiKJWCIOpHXEyl6Aj50BH0ASDVmLCXti2M\n5RxjIcpZUo1p+h1BEBWQUXiM06QYE4SjMPGqM+hDOOAFACRJ0CJspG0LYynH2OsGAHnIxzz5jAmC\nsE6JYkyFMUE4SiIlF8YhVhiTYkzYSNsWxlKOsU8ojPu6SDEmCKIyCsUicoWi9DEVxgThLKz5riPk\nQ0eAWSlIMSbso+0LY7+oGMsNeKQYEwRhDXVuMXmMCcJZlFYKSTGmLGPCRqgwFj3GzEpBWcYEQVhF\n7SkmxZggnIVZKToUHuMFUowJG6HCWLRSSFnGVBgTBGERphh73FzJxwRBOIOkGIf8lEpBOELbFsZM\n6WFWij5x+t00WSkIgrAIU4h7O4SFNVkpCMI5eJ5HIi3EtbWbleKNY1HsenOs0YfRFrRlYVws8sjm\nhYYZKZWiW3iwzVDzHUEQFmEKcU/YD0AolGlIEEE4QyZXQL7Aw+dxwed1y3FtbWCl+It/eRQf/r+/\nRiyZbfShLHrasjDO5OXGO44TtkAjneQxJgiiMtho+Y6gF163C4UiX5JSQRCEfTAbBSuI2ymVYnx2\nAblCEZNzyUYfyqKnPQtjVSIFIHuMyUpBEIRVpDx0n0eKfiSfMUE4gxTVFhQK43bJMc7kCtIu92wi\n0+CjWfy0ZWGs9hcDclzbTDxNW6EEQVhCykP3uhH0Cwk35DMmCGeQEilEpVhKpVjkk++UP99sgna1\nnaYtC2P1cA9AWHkG/R5kcoWWvsiy+QLe93/uw//+/lONPhSCWPQwdTjg8yDoEwtjimwjCEcos1K0\nSSpFPCX7imfjpBg7TXsWxtnSDGMGU42nW9hnfHwihjeORfHIy8cbfSgEseiRrRRuuTBe5A9pgmgU\ncoaxaKXwC/+/2K859nMDpBjXg/YsjDU8xoByyEfr+oznFoSVZTvE1xBEoylRjP2kGBOEk7CoNqYY\nt4uVIqFUjMlj7DhtWRhreYwBoI8N+WjhyLY5cTWZzFBsFEE4jVIxDoiKsXoaHkEQ9rCgar4Lt4mV\nIqEo/OdIMXac9iyMNTzGgGylaGXFeF5UjIs8L/2cBEE4A4trC3jJY0wQTiM335Uqxos9rqLine truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAF2CAYAAABtSl5dAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aa0095940>"
+        "<matplotlib.figure.Figure at 0x7f9a21695d30>"
        ]
       }
      ],
@@ -670,7 +670,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAtEAAAF2CAYAAACoOMTMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4a9afc1e48>"
+        "<matplotlib.figure.Figure at 0x7f9a215e8c50>"
        ]
       }
      ],
@@ -718,7 +718,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAtEAAAF2CAYAAACoOMTMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xlc1VX++PHX57JfVkEEBUUQFxSVRREXQC1zt3JNG2uy\ntH62aU3aTGlOWjZNVs40NV8cSystwz2XXCeRVNz3BNwQUAERWS/r/fz+IJkoFy7bh+X9fDx8ePl8\nPuec9+eAl/c9ns85SlxcnIoQQgghhBCi0nRaByCEEEIIIURDI0m0EEIIIYQQJpIkWgghhBBCCBNJ\nEi2EEEIIIYSJJIkWQgghhBDCRJJECyGEEEIIYSJJooUQQgghhDDRfZPo69evM3nyZAICAhg9ejQJ\nCQn3rfTAgQOMHDmS4OBgevfuzezZs8nLyys/Hxsby+DBgwkMDOT5558nNze3enchhBBCCCFEHbpv\nEj1nzhw6duzIwYMHGTp0KDNnzrxvpe3ateM///kPR44cYefOndy4cYPIyEgADAYDL7/8Mi+99BL7\n9+9HURQWLVpU/TsRQgghhBCijtwzic7NzWXfvn1MnToVS0tLnnzySVJSUoiPj79npa6urri5uQFQ\nUlKCqqrY2toCZaPQDg4ODB8+HGtra6ZMmcKWLVtq6HaEEEIIIYSoffdMohMTE7G0tESv1zNp0iSS\nk5Np06YNFy9evG/FV69eJTg4mF69euHg4MC0adMAuHTpEj4+Phw5coSnn34aLy8vsrKyyMzMrJk7\nEkIIIYQQopbdM4k2GAzY2tqSl5fHhQsXyM7OxtbWFoPBcN+KW7VqxZEjR9ixYweXL1/mm2++ASA/\nPx+9Xs+NGze4cOEClpaW5ceFEEIIIYRoCMzvddLGxoa8vDzc3d2JjY0FIC8vD71eX+kGWrduzbRp\n01i6dCkTJ05Er9eTn5/P4MGDGTx4MFlZWQB3rDMxMRGdThYQEUIIIYQQtScnJ4fOnTubVOaeSbSX\nlxeFhYWkpqbi5uZGUVERV65cwdvb26RGjEYjqqoC0LZt2/JRaYDz58/j6OhIs2bNfldOp9Ph5+dn\nUlui+lxcXFi7di0RERFah9IkSf9rS/pfO9L32pL+15b0v3ZcXFyIiYkxudw9h3nt7Ozo168fkZGR\nFBYWsmzZMjw8POjQoUP5NZMnT+aDDz6oUG7z5s3ExcVhNBq5evUqn3/+OeHh4QCEhoaSk5PDpk2b\nyM/P5/PPP2fYsGEmBy6EEEIIIYRW7jtX4u233yY+Pp6QkBB++OEHPvroowrnU1JSyMjIqHDs1q1b\nvPTSSwQHBzNhwgR69OjB9OnTgbIpIosXL+af//wnffr0AeDVV1+tqfsRQgghhBCi1ilxcXGq1kHc\nTVJSkkzn0ICLiws///wzLVq00DqUJkn6X1vS/9qRvteW9L+2pP+1c3s6R+vWrU0qJ0/tiTuSDy/a\nkv7XlvS/dqTvtSX9ry3p/4ZFkmghhBBCCCFMdM/VOYQQQgghGpNbt25RXFysdRi/c3vTuZKSEo0j\naXxUVaVZs2ZYWFjUaL2SRAshhBCiSbi9sZurq6vGkYi6ZDQaSUtLw8XFpUYTaZnOIYQQQogmITc3\nF0dHR63DEHVMp9PRokWL8tH+Gqu3RmsTQgghhKinFEVBURStwxAa0Ol0Nf69lyRaCCGEEEIIE0kS\nLYQQQgghhIkkiRZCCCGEEMJEkkQLIYQQQghhIkmihRBCCCFEgxMfH8+zzz5L79698fT05MMPP6zT\n9iWJFkIIIYQQDU5eXh4eHh68/vrrtGjRos5XXpEkWgghhBCiHtu3bx9BQUFMmTIFPz8/li1bxqBB\ng+jWrRt79+4tvy47O5tZs2bRvXt3/Pz8mDhxIgkJCeXnz58/z1NPPUVgYCA+Pj5ERESwcuXKCm0V\nFxczd+5cgoODadeuHf369SMyMrL8fFJSEp6enqSkpJQfW7RoEaGhoRXqWbVqFZ6enpw+fZoRI0bQ\nrl07QkJCOHPmDABFRUUsWLCA4OBg2rdvz6hRozh8+LBJ/RIYGMjcuXN5+OGHsbS0NKlsTZAdC4UQ\nQgghfuHx+JJaqTdlxdRqlU9PT+e5557Dy8uLOXPmEBUVxc6dO4mMjCQsLAxVVZk8eTIWFhYsX74c\nR0dHlixZwmOPPcbevXvR6/XcvHmTwMBAZsyYgYuLC9HR0cyePRsPDw8iIiIA+OKLL1i9ejWRkZF4\ne3tz+fJlkpKS7hvf3UaB33jjDV588UX8/Pw4depU+Y6BM2fOJC4ujn/961+0atWKtWvXMnHiRKKj\no2nZsmW1+qquSBIthBBCCFHPubi4EBISQm5uLuvWrSM0NBSDwcCuXbsA2Lt3L0ePHuXo0aPl25rP\nnz+f1atXs3PnTkaNGkVISAghISHldU6aNImvvvqKXbt2lSfRSUlJuLm50a9fPwA8PDwqFZ+qqnc8\n/sILLzBo0CAA2rRpA8DFixfZsGEDmzdvpnv37gDMmDGDdevWsW7dOqZPn25q92hCkmghhBBCiF9U\nd8S4tlhbW5f/ffu1lZUVBQUFAJw+fRpVVenbt2+FcgUFBVy5cgUAg8HAxx9/zI4dO0hNTaW4uJiC\nggK6dOlSfv2YMWNYs2YNYWFh9OnTh169ejFixIgqT5fo1avX746dPn0agHHjxlU4XlhYSGJiYpXa\n0YIk0UIIIYQQDdSvR4AdHBzYunXr765xcnICykamY2JimDNnDj4+PpiZmTFt2jSMRmP5tQEBARw8\neJCYmBj279/Pm2++ycqVK1m9ejVw52kbvy7/Ww4ODnc9t379emxtbSscs7e3v+v19Y0k0UIIIYQQ\nDZy/vz/Z2dkUFxfj6+t7x2sOHjzIlClTyqdXGAwGkpOT8ff3r3CdnZ0dQ4YMYciQIQQHBzN9+nRu\n3bqFk5NTeVKcm5tbfn1ycrJJK2PcHvlOTU1lwIABJt1nfSKrcwghhBBCNHBhYWEEBQXx7LPPEh0d\nTWJiItHR0bz22mtcunQJAB8fHzZu3EhcXBxnz57lpZdeorS0tEI9S5YsYe3atZw/f56EhAQ2bNiA\nh4dH+Wi2g4MD3t7erFmzBoAzZ86wfft2k2Jt164dI0eOZPbs2WzdupXExERiY2N56623iI2NrXQ9\nxcXFnD59mtOnT1NUVERqaiqnT5+usHJIbZKRaCGEEEKIeu7XI713eq0oCl9//TULFy5kxowZ3Lp1\nC1dXV8LDw2nWrBkA8+bNY9asWYwcORIHBwemTp1KTk5OhXbs7e2JjIzk0qVLmJmZERAQwPLlyytc\n8/777zNr1iy+/fZbgoKCGD16NLt3775nzL+1ePFiFi1axLx580hLS8PZ2ZnQ0NBKP8gIcP36dYYM\nGVLh/r/++mvGjx9fJxuvKHFxcXd+nLIeSEpKws/PT+swmhwXFxcAMjIyNI6kaZL+15b0v3ak77XV\nFPo/PT29fOUK0fTc7fvv4uJCTEwMrVu3Nqk+mc4hhBBCCCGEiSSJFkIIIYQQwkSSRAshhBBCCGEi\nSaKFEEIIIYQwkSTRQgghhBBCmEiSaCGEEEIIIUwkSbQQQgghhBAmkiRaCCGEEEIIE0kSLYQQQggh\nhIkkiRZCCCGEEMJEkkQLIYQQQogGZ+XKlYwcOZLOnTvTpUsXxo8fz+HDh+usfUmihRBCCCFEgxMb\nG8v48eNZs2YNGzZswNXVlUmTJnHp0qU6aV+SaCGEEEKIemzfvn0EBQUxZcoU/Pz8WLZsGYMGDaJb\nt27s3bu3/Lrs7GxmzZpF9+7d8fPzY+LEiSQkJJSfP3/+PE899RSBgYH4+PgQERHBypUrK7RVXFzM\n3LlzCQ4Opl27dvTr14/IyMjy80lJSXh6epKSklJ+bNGiRYSGhlaoZ9WqVXh6enL69GlGjBhBu3bt\nCAkJ4cyZMwAUFRWxYMECgoODad++PaNGjTJ5FHnx4sVMnjwZPz8/fH19effdd8nPz+fHH380qZ6q\nMq+TVoQQQgghGoBVZybXSr0TunxVrfLp6ek899xzeHl5MWfOHKKioti5cyeRkZGEhYWhqiqTJ0/G\nwsKC5cuX4+joyJIlS3jsscfYu3cver2emzdvEhgYyIwZM3BxcSE6OprZs2fj4eFBREQEAF988QWr\nV68mMjISb29vLl++TFJS0n3jUxTljsffeOMNXnzxRfz8/Dh16hQWFhYAzJw5k7i4OP71r3/RqlUr\n1q5dy8SJE4mOjqZly5ZV6qOsrCwAHB0dq1TeVJJECyGEEELUcy4uLoSEhJCbm8u6desIDQ3FYDCw\na9cuAPbu3cvRo0c5evQorq6uAMyfP5/Vq1ezc+dORo0aRUhICCEhIeV1Tpo0ia+++opdu3aVJ9FJ\nSUm4ubnRr18/ADw8PCoVn6qqdzz+wgsvMGjQIADatGkDwMWLF9mwYQObN2+me/fuAMyYMYN169ax\nbt06pk+fbmr3ALBgwQJ8fHwYPnx4lcqbSpJoIYQQQohfVHfEuLZYW1uX/337tZWVFQUFBQCcPn0a\nVVXp27dvhXIFBQVcuXIFAIPBwMcff8yOHTtITU2luLiYgoICunTpUn79mDFjWLNmDWFhYfTp04de\nvXoxYsQILC0tqxR3r169fnfs9OnTAIwbN67C8cLCQhITE6vUzgcffMCBAwdYu3YtVlZWVarDVJJE\nCyGEEEI0UL8eAXZwcGDr1q2/u8bJyQkoG5mOiYlhzpw5+Pj4YGZmxrRp0zAajeXXBgQEcPDgQWJi\nYti/fz9vvvkmK1euZPXq1cCdp238uvxvOTg43PXc+vXrsbW1rXDM3t7+rtffzSeffMKyZctYtWoV\nvr6+JpevKkmihRBCCCEaOH9/f7KzsykuLr5rInnw4EGmTJlSPr3CYDCQnJyMv79/hevs7OLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaff81358>"
+        "<matplotlib.figure.Figure at 0x7f9a21634f28>"
        ]
       }
      ],
@@ -768,7 +768,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAtEAAAF2CAYAAACoOMTMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aa0052630>"
+        "<matplotlib.figure.Figure at 0x7f9a28dd1908>"
        ]
       }
      ],
@@ -891,26 +891,26 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "time: 0 \tposition = 0.655 \tvariance = 2.500\n",
-        "time: 1 \tposition = 0.170 \tvariance = 1.667\n",
-        "time: 2 \tposition = 0.110 \tvariance = 1.250\n",
-        "time: 3 \tposition = 0.047 \tvariance = 1.000\n",
-        "time: 4 \tposition = 0.053 \tvariance = 0.833\n",
-        "time: 5 \tposition = 0.174 \tvariance = 0.714\n",
-        "time: 6 \tposition = 0.159 \tvariance = 0.625\n",
-        "time: 7 \tposition = 0.167 \tvariance = 0.556\n",
-        "time: 8 \tposition = 0.039 \tvariance = 0.500\n",
-        "time: 9 \tposition = 0.070 \tvariance = 0.455\n",
-        "time: 10 \tposition = 0.074 \tvariance = 0.417\n",
-        "time: 11 \tposition = 0.036 \tvariance = 0.385\n",
-        "time: 12 \tposition = 0.133 \tvariance = 0.357\n",
-        "time: 13 \tposition = 0.344 \tvariance = 0.333\n",
-        "time: 14 \tposition = 0.252 \tvariance = 0.312\n",
-        "time: 15 \tposition = 0.273 \tvariance = 0.294\n",
-        "time: 16 \tposition = 0.210 \tvariance = 0.278\n",
-        "time: 17 \tposition = 0.210 \tvariance = 0.263\n",
-        "time: 18 \tposition = 0.168 \tvariance = 0.250\n",
-        "time: 19 \tposition = 0.206 \tvariance = 0.238\n"
+        "time: 0 \tposition = 0.827 \tvariance = 2.500\n",
+        "time: 1 \tposition = 0.427 \tvariance = 1.667\n",
+        "time: 2 \tposition = 0.192 \tvariance = 1.250\n",
+        "time: 3 \tposition = 0.548 \tvariance = 1.000\n",
+        "time: 4 \tposition = 0.416 \tvariance = 0.833\n",
+        "time: 5 \tposition = 0.409 \tvariance = 0.714\n",
+        "time: 6 \tposition = 0.297 \tvariance = 0.625\n",
+        "time: 7 \tposition = 0.490 \tvariance = 0.556\n",
+        "time: 8 \tposition = 0.407 \tvariance = 0.500\n",
+        "time: 9 \tposition = 0.291 \tvariance = 0.455\n",
+        "time: 10 \tposition = 0.120 \tvariance = 0.417\n",
+        "time: 11 \tposition = -0.043 \tvariance = 0.385\n",
+        "time: 12 \tposition = -0.082 \tvariance = 0.357\n",
+        "time: 13 \tposition = -0.130 \tvariance = 0.333\n",
+        "time: 14 \tposition = -0.208 \tvariance = 0.312\n",
+        "time: 15 \tposition = -0.144 \tvariance = 0.294\n",
+        "time: 16 \tposition = -0.075 \tvariance = 0.278\n",
+        "time: 17 \tposition = -0.073 \tvariance = 0.263\n",
+        "time: 18 \tposition = -0.030 \tvariance = 0.250\n",
+        "time: 19 \tposition = -0.045 \tvariance = 0.238\n"
        ]
       }
      ],
@@ -1030,24 +1030,24 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "PREDICT:     1.0000   502.0000\tUPDATE:    -5.0106     9.8047\n",
-        "PREDICT:    -4.0106    11.8047\tUPDATE:    -1.9323     5.4138\n",
-        "PREDICT:    -0.9323     7.4138\tUPDATE:     2.3085     4.2574\n",
-        "PREDICT:     3.3085     6.2574\tUPDATE:     4.5496     3.8490\n",
-        "PREDICT:     5.5496     5.8490\tUPDATE:     4.5375     3.6904\n",
-        "PREDICT:     5.5375     5.6904\tUPDATE:     6.3341     3.6267\n",
-        "PREDICT:     7.3341     5.6267\tUPDATE:     6.4186     3.6007\n",
-        "PREDICT:     7.4186     5.6007\tUPDATE:     8.5696     3.5900\n",
-        "PREDICT:     9.5696     5.5900\tUPDATE:    10.7097     3.5856\n",
-        "PREDICT:    11.7097     5.5856\tUPDATE:     9.8509     3.5838\n"
+        "PREDICT:     1.0000   502.0000\tUPDATE:    -1.9271     9.8047\n",
+        "PREDICT:    -0.9271    11.8047\tUPDATE:     1.4652     5.4138\n",
+        "PREDICT:     2.4652     7.4138\tUPDATE:     0.8840     4.2574\n",
+        "PREDICT:     1.8840     6.2574\tUPDATE:     2.2629     3.8490\n",
+        "PREDICT:     3.2629     5.8490\tUPDATE:     5.3172     3.6904\n",
+        "PREDICT:     6.3172     5.6904\tUPDATE:     4.8154     3.6267\n",
+        "PREDICT:     5.8154     5.6267\tUPDATE:     6.7095     3.6007\n",
+        "PREDICT:     7.7095     5.6007\tUPDATE:     7.0910     3.5900\n",
+        "PREDICT:     8.0910     5.5900\tUPDATE:     9.0888     3.5856\n",
+        "PREDICT:    10.0888     5.5856\tUPDATE:    11.0984     3.5838\n"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAscAAAF2CAYAAACCiDVjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAAF2CAYAAABnFvAPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffae828>"
+        "<matplotlib.figure.Figure at 0x7f9a2169e208>"
        ]
       }
      ],
@@ -1183,9 +1183,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAsoAAAF2CAYAAAB3dr7TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAsoAAAF2CAYAAAB3dr7TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffee278>"
+        "<matplotlib.figure.Figure at 0x7f9a28d8c780>"
        ]
       },
       {
@@ -1193,7 +1193,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAskAAAGDCAYAAADZHo16AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aafe0b9e8>"
+        "<matplotlib.figure.Figure at 0x7f9a2161a278>"
        ]
       },
       {
@@ -1405,9 +1405,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAsMAAAF2CAYAAACLY5UZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAsMAAAF2CAYAAACLY5UZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4a9afed940>"
+        "<matplotlib.figure.Figure at 0x7f9a28dbdeb8>"
        ]
       },
       {
@@ -1415,7 +1415,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAArwAAAGDCAYAAADJfsOmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffee358>"
+        "<matplotlib.figure.Figure at 0x7f9a2169e048>"
        ]
       },
       {
@@ -1423,7 +1423,7 @@
        "stream": "stdout",
        "text": [
         "Variance converges to 0.09072976736236911\n",
-        "Last voltage is 15.592455113316198\n"
+        "Last voltage is 16.160958715064073\n"
        ]
       }
      ],
@@ -1486,9 +1486,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAsoAAAF2CAYAAAB3dr7TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAsoAAAF2CAYAAAB3dr7TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4a9af3a160>"
+        "<matplotlib.figure.Figure at 0x7f9a2163a518>"
        ]
       }
      ],
@@ -1555,9 +1555,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAs4AAAF2CAYAAAB+nR6pAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAs4AAAF2CAYAAAB+nR6pAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffeeb70>"
+        "<matplotlib.figure.Figure at 0x7f9a28d8c198>"
        ]
       },
       {
@@ -1565,7 +1565,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAGDCAYAAAAoFdb3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4a9adb7eb8>"
+        "<matplotlib.figure.Figure at 0x7f9a28bd72e8>"
        ]
       }
      ],
@@ -1641,9 +1641,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAtgAAAF2CAYAAABULe8GAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAtgAAAF2CAYAAABULe8GAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4a9add02e8>"
+        "<matplotlib.figure.Figure at 0x7f9a20599a90>"
        ]
       }
      ],
@@ -1705,9 +1705,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAs4AAAF2CAYAAAB+nR6pAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xl4lOX59vHvrNk3hn1RYgBZgpogwQWJgFjRCtVStVos\nLhR+aH1RsShWagVj1bq0tbhXLNJqFTBWgYqixCgiCFE2kSQE2QOBQJZJMtv7RzIjgQBJJsk8Cefn\nODxMZrmfK/AwOeee+7lu05YtW3yIiIiIiMhJmUNdgIiIiIhIa6DgLCIiIiJSDwrOIiIiIiL1oOAs\nIiIiIlIPCs4iIiIiIvWg4CwiIiIiUg8KziIiIiIi9RBUcN69ezcpKSm1/uvbty/Lli3D7XYzY8YM\nUlNTGT58OEuWLGmqmkVEREREWpw1mCd37dqVdevWBb7fvn0711xzDZdccgmvvfYaubm5ZGVlsWnT\nJiZNmkRKSgqdO3cOumgRERERkZbWpEs1FixYwOWXX054eDhLly5l/PjxREdHk5aWRkpKCsuWLWvK\nw4mIiIiItJgmC85er5fMzEzGjh0LQEFBAYmJiUybNo3FixeTlJTEtm3bmupwIiIiIiItqsmCc3Z2\nNiaTiQsvvBAAp9NJZGQkW7dupbCwkKioKMrLy5vqcCIiIiIiLSqoNc5HW7hwIWPGjAl8HxERgdPp\nJDMzE4DZs2cTFRV13PO2b9+O2azmHiIiIiLSfEpKSujfv39QYzRJcD58+DDLly9n0aJFgdt69uxJ\nXl4eAwYMACAvL4+RI0ce91yz2Uy/fv2aogxpIxwOBwsXLiQ9PT3UpYhB6JyQuui8kLrovJC6OBwO\nsrOzgx6nSaZ633//ffr06UNSUlLgttGjRzNv3jxKSkpYtWoVOTk5jBo1qikOJyIiIiLS4ppkxnnh\nwoVcc801tW6bMGEC+fn5pKenExcXR0ZGBp06dWqKw4mIiIiItLgmCc4LFiw4fmCrlYyMDDIyMpri\nEHKa0fIdOZbOCamLzgupi84LaS66Kk8MSS96ciydE1IXnRdSF50X0lwUnEVERERE6qHJ2tGJiIiI\nBMvlcnHo0CFMJlOjnn/o0CEA3G53U5YlBufz+UhISMBmszXrcRScRURExBBcLhdFRUV07NhRezxI\ng3i9XgoLC3E4HM0annVWioiIiCEcOnRIoVkaxWw207Fjx8AnDs12nGYdXURERKSeTCaTQrM0mtls\nbvQSn3ofo1lHFxERERFpIxScRURERETqQcFZRERERKQeFJxFREREmkBJSQm33XYb/fr1o3v37jzz\nzDO17p86dSrjxo077nkzZ86ke/fudO/evc77xTgUnEVERESawLx581i9ejULFy4kJyeHyZMn17p/\n9uzZvPrqq8c9b/r06axbt45Jkyad9OK2L774gu7du7Nr164mr13qR32cRURERJpAfn4+ffr0OeGW\n39HR0XXeHhUVRVRUFJGRkfh8vlMepz6PkeahGWcRERGRIEydOpXu3bvz5ptv8uWXXwaWXfiXakyf\nPj2opRj+mebrrrsOgAsuuCAw3tGzz3v27GHy5MkMGDCA5ORkJk6cyJ49e2qN9dZbb9G9e3c2bNjA\nT3/6U5KSkkhLS2Pjxo1B/AmcPjTjLCIiIq1Gt5tebraxd82f2KjnzZo1iwcffJCZM2eyZ88eXnnl\nFQAiIyMBeOihh5g2bRozZ87kwIEDDR5/8ODB5OTksHr1aiZOnMjixYvp2rUrAO3atQOgvLyccePG\nkZyczIIFC7BarTz++OPccsstLFmy5LglIA8++CC//e1v6devH+vXr2/2rarbCgVnERERkSDExMQQ\nExNDWFgYVquV9u3b17o/Ojqa6OhowsLCGrXMwmaz0b59e+Li4gBwOBzHHePdd9+luLiY5557LhCC\nH330UVJTU8nJySElJaXW4++8805GjRoFwBlnnNHgmk5XCs4iIiLSajR2VritW79+PSUlJQwYMKDW\n7SaTiR9++OG44DxkyJCWLK/NUHAWERERaQN69erFa6+9dtztx85OA8TGxrZESW2OgrOIiIhIEzlZ\nO7lT3R8VFUVFRcUJ7/cvwXC73cfdN3DgQN555x1iYmIC656l6amrhoiIiEgTOXYNs9frpbCwkMLC\nQioqKqiqqmL//v0UFhbicrlqPfa8885j48aNZGVlUVhYSFlZWa37e/bsicViITMzk5KSkloh+5pr\nrqFjx45MnDiR1atXU1BQwLJly5g8eTJOp7P5fuDTjCGCs9vjDXUJIiIiIkExmUzHzSjv2rWL1NRU\nUlNTef/991m7di0pKSkMGjSIr7/+utZjL7jgAiZPnswdd9xBamoqTz75ZK37O3TowMMPP8z8+fNJ\nTk6md+/egXZ0ERERLFiwgK5du3LrrbcycuRI/vjHP9KxY0fsdvtxdUrjmLZs2RLSLto7duygyxln\nER8VFsoyxEAcDgcARUVFIa5EjELnhNRF50Xbs3//fjp06BDqMqQVO9E55HA4yM7OpkePHkGNb4gZ\n55LyqlCXICIiIiJyUsYIzk4FZxERERExNkME51Kn69QPEhEREREJIUME5yNaqiEiIiIiBmeI4Fyq\npRoiIiIiYnCGCM6acRYRERERows6OFdUVDBz5kyGDBnC4MGD+eMf/wiAy+VixowZpKamMnz4cJYs\nWXLCMbTGWURERESMLugttzMyMtixYwcffPABDoeDvLw8AObOnUtubi5ZWVls2rSJSZMmkZKSQufO\nnY8bQ101RERERMTogppxrqioIDMzk9///ve0b98ek8lEr169AFi6dCnjx48nOjqatLQ0UlJSWLZs\nWZ3jKDiLiIiIiNEFFZwLCgowmUx89NFHXHzxxVx11VV89NFHgfsSExOZNm0aixcvJikpiW3bttU5\nTomWaoiIiIiIwQW1VKO0tBSXy8XOnTv55JNPWLduHZMnT+bDDz/E6XQSGRnJ1q1bSU5OJioqir17\n99Y5TqX7x61TRWw2G6BzQn6kc0LqovOi7Tl06FCoSxADGjJkCNdffz333HPPKR9rtVrrfE3wv14E\nK6jgHB4ejsfj4ZZbbsFutzNkyBASExP55ptviIiIwOl0kpmZCcDs2bOJioqqc5xvN21h1qxZAAwb\nNoz09PRgyhIRERGRNsJkMjXqeStWrCArKwsAi8XCsGHDgq4lqODco0ePOn8Yn89Hz549ycvLY8CA\nAQDk5eUxcuTIOseJa9eRKVOuCXxfVFQUTFnSyvnfKeo8ED+dE1IXnRdtj9vtDnUJjfLFF19w5513\nct5557Fy5UqmT5/O/Pnz2bdvH3//+9+55JJLOHLkCLNnz+Z///sfVVVVnHfeeTzyyCP07t0bgNzc\nXB599FFycnI4fPgwPXr0YNKkSdx4442B47hcLmbNmsUHH3xAcXExXbp04eabb+Y3v/kNADt27ODC\nCy9k1apVdOvWDYCnnnqKt99+my+//DIwzltvvcW9997L0qVLuf/++9m8eTMOh4PXXnuNAQMGUFVV\nxRNPPMGiRYs4cuQI/fr1Y+bMmZx//vlA9QxwWloay5cv5+KLL6ZHjx7MmzePcePGkZGRUes4c+bM\nYefOnYGf55e//GXg/u7du/P444/z9ttvs2HDBvr27cuzzz4buF5uyJAh7Nq1C4Cnn36ap59+GoB7\n772Xu+++u86/C7fbHXhNSE5OJjk5Gah+vcjOzm7sX3FAUME5Li6OwYMHM3fuXGbOnMm6devYtm0b\n5513HqNHj2bevHkMHz6cTZs2kZOTw5/+9Kc6x1EfZxEREamvrjWh8Fi7a0JWsI9vjP379zN58mTO\nPPNMHnroId5++20++ugjXnrpJS655BLGjx+PzWbj9ddfJy4ujpdffpkbbriBzz77jMjISA4ePEhK\nSgpTp07F4XCQlZXF9OnT6datW+CT+Ndee4133nmHl156icTERAoKCtixY8cpazvRjO2DDz7Ib3/7\nW/r168f69esDyxnuvvtutmzZwt///ne6du3KwoUL+eUvf8lnn31G586dMZlMJCQk8Prrr3PNNddw\nyy238Oabb/Kzn/2Me++9F4fDwRtvvEFGRgaPPfYYgwYN4ptvvuHuu+8mISGBK664IlDDK6+8wp/+\n9CdiY2OZMmUKf/zjH5k3bx4AS5YswePxcOWVVzJ27FgmT54MQGRkZFB/V8FoknZ0DzzwAIMHD6ZT\np048+eSTdOjQgQkTJpCfn096ejpxcXFkZGTQqVOnOsdQH2cRERFpzRwOB2lpaZSWlrJo0SIuuOAC\nnE4nH3/8MZ999hlr165l7dq1dOjQAYBZs2bxzjvv8NFHHzFmzBjS0tJIS0sLjHfjjTcyb948Pv74\n40Bw3rFjB506dWLo0KEAgVnlU/H5fHXefueddzJq1CgAzjjjDADy8/PJzMzkgw8+4NxzzwVg6tSp\nLFq0iIULFzJlyhQARowYwfnnn4/D4WDEiBGkpqbicDjYuXMnDoeDZ555hrvuuouxY8cC1bPLWVlZ\nzJ8/v1ZwvuWWWxgyZAgAN9xwA3/7298C97Vr1w6oXmYRFRVF+/bt6/XzNqegg3P37t0D7wxqDWy1\nkpGRUWvK/kTUjk5ERETqq6EzxU05s3wi4eHhgf/7vw4LC6OiooINGzbg8/m4+OKLaz2noqKCH374\nAQCn08mzzz7LsmXL2LdvHy6Xi4qKisCSV4Cf//znLFiwgEsuuYSLLrqIIUOG8NOf/hS73d6omv2B\n9WgbNmwA4Be/+MVxtW7fvr1eP++BAwfYt28fTz75ZGB5BVQvNenRo0etcc8666zA1/Hx8RQXFzfq\nZ2kpQQfnplDp8lDp8hBms4S6FBEREZEm45/tjY2NrXMX5fj4eKB6Bjo7O5uHHnqIs846C4Line truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAs4AAAF2CAYAAAB+nR6pAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4a9af45f28>"
+        "<matplotlib.figure.Figure at 0x7f9a216a1e10>"
        ]
       }
      ],
@@ -1768,9 +1768,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAtgAAAF2CAYAAABULe8GAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAtgAAAF2CAYAAABULe8GAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aa0041550>"
+        "<matplotlib.figure.Figure at 0x7f9a216e42e8>"
        ]
       }
      ],
@@ -1820,9 +1820,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAtgAAAF2CAYAAABULe8GAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAtgAAAF2CAYAAABULe8GAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4a9af80c88>"
+        "<matplotlib.figure.Figure at 0x7f9a21680588>"
        ]
       }
      ],
@@ -1931,7 +1931,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAs4AAAF2CAYAAAB+nR6pAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffaef28>"
+        "<matplotlib.figure.Figure at 0x7f9a2169e630>"
        ]
       },
       {
@@ -2022,7 +2022,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAF2CAYAAABtSl5dAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aaffd7390>"
+        "<matplotlib.figure.Figure at 0x7f9a41e44780>"
        ]
       }
      ],
@@ -2107,7 +2107,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAscAAAF2CAYAAACCiDVjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f4aa0032b38>"
+        "<matplotlib.figure.Figure at 0x7f9a205b3a90>"
        ]
       }
      ],