Added scatterpoints=1 to legend where applicable.

01_gh_filter/g-h_filter.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:3629e2fdae20e09b4bc3545d5894210b005707cdba2c96a26450fcac7a6df90e"
+  "signature": "sha256:baea7682f826fcbcca71a2693a7d43c4f2b9b361029d9bab12908795ea315c61"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -261,7 +261,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7f6d1ef1ac50>"
+        "<IPython.core.display.HTML at 0x7f12aedfe1d0>"
        ]
       }
      ],
@@ -323,7 +323,7 @@
       "plt.errorbar([170], [1.05], xerr=8, fmt='o', label='B', capthick=2, capsize=10)\n",
       "plt.ylim(0, 2)\n",
       "plt.xlim(145, 185)\n",
-      "plt.legend()\n",
+      "plt.legend(scatterpoints=3)\n",
       "plt.gca().axes.yaxis.set_ticks([])\n",
       "plt.show()"
      ],
@@ -335,7 +335,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxUAAAGGCAYAAAANcKzOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06a4c160>"
+        "<matplotlib.figure.Figure at 0x7f1295f1b320>"
        ]
       }
      ],
@@ -372,7 +372,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxUAAAGGCAYAAAANcKzOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d067203c8>"
+        "<matplotlib.figure.Figure at 0x7f1295ed3a20>"
        ]
       }
      ],
@@ -406,7 +406,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxYAAAGGCAYAAADmRxfNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06a4c1d0>"
+        "<matplotlib.figure.Figure at 0x7f1295f1b1d0>"
        ]
       }
      ],
@@ -448,7 +448,7 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "Average of measurements is 165.0019\n"
+        "Average of measurements is 164.9904\n"
        ]
       }
      ],
@@ -484,7 +484,7 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "Average of measurements is 164.9496\n"
+        "Average of measurements is 164.9898\n"
        ]
       }
      ],
@@ -527,7 +527,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzsAAAGkCAYAAAAWgDuQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d066a7198>"
+        "<matplotlib.figure.Figure at 0x7f1295ddda20>"
        ]
       }
      ],
@@ -563,7 +563,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06689240>"
+        "<matplotlib.figure.Figure at 0x7f1295da9e10>"
        ]
       }
      ],
@@ -598,7 +598,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d0677d4a8>"
+        "<matplotlib.figure.Figure at 0x7f1295eca8d0>"
        ]
       }
      ],
@@ -636,7 +636,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d066d03c8>"
+        "<matplotlib.figure.Figure at 0x7f1295f106d8>"
        ]
       }
      ],
@@ -674,7 +674,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XtclGX+//HXDAfBEyDiEQTP5wOGrauieFgVtbZc0/KI\n9tVKYzN1TbeMrV/bZrababW7ah5SW1Oz7LBmWopmW4mCJ0Q8kqbmCTEQFJn5/TExMQzoqMAww/v5\nePDY5Z5rbj43tyZvrvtzXQaz2WxGRERERETERRidXYCIiIiIiMjtUIgRERERERGXohAjIiIiIiIu\nRSFGRERERERcikKMiIiIiIi4FIUYERERERFxKQoxIiIiIiLiUpwWYrZt28b9999PcHAwRqORZcuW\n2bx+5coVJk6cSEhICJUrV6ZFixbMnTvXZkxUVBRGo9HmY/jw4WV5GSIiIiIiUsY8nfWFs7KyaNeu\nHWPGjGH06NEYDAab1ydPnkx8fDwrVqygYcOGxMfHM378eGrWrMnIkSMBMBgMjBs3jpdfftn6Pl9f\n3zK9DhERERERKVtOm4mJjo7mpZde4g9/+ANGo30ZO3fuZPTo0fTo0YMGDRowatQoOnfuzPfff28z\nztfXl1q1alk/qlWrVlaXICIiIiIiTlBue2Kio6P5+OOPOXXqFADffPMNSUlJ9O/f32bcqlWrCAoK\nok2bNvzpT38iMzPTGeWKiIiIiEgZcdrjZLcye/ZsRo8eTYMGDfD0tJT55ptvMmDAAOuY4cOHExYW\nRr169di/fz8zZ85k7969bNy40eZcGRkZZVq7iIiIiIiUDD8/P7tj5TbETJs2je+++45PPvmE0NBQ\n4uPjmTp1KqGhofTr1w+A8ePHW8e3bt2axo0bc++995KYmEh4eLizShcRERERkVJULkNMVlYWb7zx\nBh9++CEDBw4EoE2bNiQlJfHaa69ZQ0xhHTt2xMPDgyNHjijEiIiIiIi4qXIZYsxmM2az2a7h32g0\nYjabi33fvn37yMvLo27dusWOKWo6SlxPQkICERERzi5DSojup/vQvXQvup/uQ/fSvVSE+3mrdhCn\nLrF8+PBhAEwmE2lpaSQlJREYGEhISAi9e/dmxowZVK1alQYNGhAfH8/y5cuZM2cOAMeOHWPFihUM\nHDiQwMBAkpOTmTp1Kh07dqRr167OuiwRERERESllTludbOfOnXTs2JGOHTuSk5NDXFwcHTt2JC4u\nDoCVK1fym9/8hpEjR9K6dWteffVVXnrpJSZNmgSAt7c3X331Ff369aNFixY89dRT9O/fn82bN9vt\nOSMiIiIiIu7DaTMxUVFRmEymYl8PCgpi0aJFxb4eHBzM1q1bS6EyEREREREpz8rtPjEiIiIiIiJF\nUYgRERERERGXohAjIiIiIiIupVwusSwiIiIi5Y/JZOL69evOLqPCCw0NJScnx9ll3DGDwYC3t/dd\nLcalECMiIiIit2Qymbh27Ro+Pj5aCdbJfHx8nF3CXcnLyyMnJ4dKlSrZ7QvpKD1OJiIiIiK3dP36\ndQUYKREeHh74+Pjc1ayeQoyIiIiIOEQBRkrK3f5ZUogRERERERGXohAjIiIiIiIuRSFGRERERERc\nikKMiIiIiFRIf/nLXzAajZw7d87Zpdy2qKgoWrZsWaZf88SJExiNRpYtW1amX7coCjEiIiIiIuVQ\ncnIyf/nLX0hLSyvydWcstGAwGMrFAg/aJ0ZEREREpBxKTk7mxRdfpFevXoSGhjq7HMLCwsjOzsbT\n0/kRwvkViIiIiIhIscxms7NLsPL29nZ2CYAeJxMRERGRCu7y5cvExMQQEBCAv78/48aNIzs7G4Cu\nXbvSvn37It/XsWNHOnfuDPzaLzJ79mzmz59Pw4YNqVy5Ml27diUhIcHuvXv27GHAgAH4+flRtWpV\nevbsyddff219fenSpQwdOhSAnj17YjQaMRqNvPvuuzbnSU5OplevXlSpUoXg4GDmzJlj97WuXbvG\nCy+8QNOmTfHx8SE4OJgpU6ZYrzHfl19+Sffu3alRowZVqlShSZMmxMbGWl8vqicmMzOTadOm0bBh\nQ3x8fKhVqxY9e/Zk+/btN/2e3y3NxIiIiIhIhfbwww/TuHFjXnnlFXbt2sWiRYuoVasWr7zyCjEx\nMTz22GPs27ePtm3bWt9z8OBBkpKSeOutt2zO9d5775Gens6kSZPIy8vjrbfeonfv3uzevZvGjRtb\n3xsZGUm1atWYPn06lSpVYuHChfTp04dNmzYRGRlJjx49+OMf/8i8efN49tlnrU38Xbp0sX6ty5cv\nM2DAAAYPHsywYcNYs2YNzzzzDG3btqV///6AZRbnwQcfZNu2bUyYMIFWrVqRnJzM22+/zYEDB9i4\ncSNgCUMDBw6kffv2vPDCC1SuXJkjR47wxRdf2H2/CvbEPPHEE6xZs4Ynn3yS1q1bc+nSJb7//nv2\n7t1LZGRkCd2hIpgrgMuXL1s/xD3s3LnT2SVICdL9dB+6l+5F99N9lMS9zM7OdnwwlO5HCYmLizMb\nDAbzo48+anN88ODB5po1a5rNZrM5PT3d7Ovra54+fbrNmJkzZ5orVapkvnjxotlsNpuPHz9uNhgM\nZl9fX3NaWpp1XGpqqtnLy8s8cuRI67EHH3zQXKlSJfORI0esxy5cuGCuWbOmOSIiwnpszZo1ZoPB\nYI6Pj7ervUePHmaDwWBevny59dj169fNdevWNQ8ZMsR6bOXKlWaj0Wjetm2bzftXrlxpNhgM5i++\n+MJsNpvNc+fONRsMBuv1FCX/GpctW2Y95u/vb46NjS32PTdzsz9Tt/r5XY+TiYiIiEiFNn78eJvP\nu3XrxsWLF8nMzMTf35/777+f9957z9qbYjabee+994iOjqZGjRo2773vvvto0KCB9fOmTZvSr18/\nPvvsMwDy8vLYuHEj9913n3VmBiAwMJCYmBh27drF+fPnHaq7cuXKjBw50vq5l5cX9957L8eOHbMe\nW716Nc2aNaNVq1ZcuHDB+tG9e3cMBgNbt24FwM/PD4APP/wQk8nk0NcH8Pf359tvv+X06dMOv6ck\nKMSIiIiISMkq7bmYElYwdAAEBAQAkJ6eDsCYMWP48ccf2bJlCwDbt2/nhx9+YNSoUXbnatq0aZHH\nLl++zJUrVzh//jzZ2dk0b97cblyLFi0AS++JI+rXr293zN/f31o3QGpqKocOHSIoKIhatWpZP/Kv\nOX+PnIcffphu3boxfvx4ateuzbBhw/jPf/5DXl7eTWuYM2cOBw4coEGDBnTq1IlZs2aRmprqUP13\nQyFGRERERCo0Dw+PIo/nz7z069eP2rVrs2LFCgBWrFhBQEAA9913X5nVWJRb1Q1gMplo3bo1mzdv\ntvvYtGkTU6dOBcDHx4f4+Hi2bNnCuHHjOHToECNGjKBz587k5OQUW8OQIUM4duwYb7/9NqGhocyb\nN4+2bdvyn//8p2QvthCFGBERERGRmzAajYwYMYIPPviAjIwM1q5dy0MPPYSXl5fd2KJmIVJTUwkI\nCKB69eoEBQVRuXJlUlJS7MblHwsLCwNKZjPLJk2acOHCBXr16lXkR/7sT/7X69GjB7NnzyYpKYm3\n336bXbt2sW7dupt+jdq1azNhwgTWrl3LDz/8QKNGjYiLi7vr2m9GIUZERERE5BbGjBnDzz//zIQJ\nE7h8+TKjR48uctynn35KWlqa9fPU1FQ2btzIgAEDAMvsSf/+/fnkk09selcuXbrEsmXL6NSpE0FB\nQQBUqVLF+trtKBh+hg0bxk8//cQ///lPu3HXrl0jMzOz2K8RHh4OQEZGRpFfx2Qy2b3m5+dHWFhY\nse8pKVpiWURERETkFtq2bUv79u1Zs2YNjRo1slnquKCmTZsSGRlpXWL5zTffpHLlyjYzEy+99BJf\nfPEF3bp1Y9KkSdYllq9cucLf//5367iOHTvi4eHB3/72N9LT0/H19aVz587WmRpzMf1BBY+PHDmS\ntWvXMmnSJOLj4+natStms5lDhw6xZs0a1q5dS/fu3XnxxReJj49n4MCBhIaGkp6ezr/+9S+qVq3K\noEGDivw6V65coX79+gwZMoR27dpRvXp1duzYwcaNG232lykNCjEiIiIiUiEZDIZiH9kq6viYMWOY\nMmWKzYpghY0YMYLKlSvzj3/8gzNnztCxY0fmzp1LkyZNrGNatGjB119/zcyZM5k9ezYmk4lOnTrx\nzjvv0K1bN+u4WrVqsXDhQl5++WUmTJiAyWRiyZIlhIWFFVt74eMGg4F169Yxd+5cli1bxvr16/H1\n9aVx48ZMmjTJuvfNAw88wMmTJ1m2bBnnz58nMDCQLl268PzzzxMSElLktVapUoUnn3ySTZs28fHH\nH5Obm0ujRo34+9//zlNPPVXs96gkGMzFRTg3UnA6K3/5OHFtCQkJREREOLsMKSG6n+5D99K96H66\nj5K4lzk5Ofj4+JRQRa7prbfeIjY2ltTUVJtQApYVxRo1asQrr7zC9OnTnVSha7nZn6lb/fyunhgR\nEREREQcsWrSILl262AUYKXt6nExEREREpBhXr15l/fr1xMfHs2fPHj744ANnlyQoxIiIiIiIFOvc\nuXOMGDGCgIAAnnnmGR588EFnlyQoxIiIiIiIFCssLAyTyVRi46RkqCdGRERERERcikKMiIiIiIi4\nFIUYERERERFxKQoxIiIiIiLiUhRiRERERETEpThtdbJt27bx2muvsXv3bk6fPs2SJUsYM2aM9fUr\nV64wY8YMPvnkEy5evEiDBg14/PHHmTx5snXMtWvXmDZtGqtWrSI7O5vevXvz9ttvU79+fWdckoiI\niIhbC19+uETPlziqaZmeX9yH02ZisrKyaNeuHW+88Qa+vr4YDAab1ydPnszGjRtZsWIFKSLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d0653e0b8>"
+        "<matplotlib.figure.Figure at 0x7f1295cb6b00>"
        ]
       }
      ],
@@ -713,7 +713,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAAGkCAYAAAAL/gULAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d066e2d68>"
+        "<matplotlib.figure.Figure at 0x7f1295de8358>"
        ]
       }
      ],
@@ -740,7 +740,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzoAAAGkCAYAAAD5QlCuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06430dd8>"
+        "<matplotlib.figure.Figure at 0x7f1295ba4a90>"
        ]
       }
      ],
@@ -780,7 +780,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzoAAAGkCAYAAAD5QlCuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XlcVXX+x/H3QUARQnDXUHHfyVCpJBTMBazUHNPUAtqm\ntEXG1DSncJzRGq3MJnPS1AxnRqypLHPUVBQzM3Gp3FJLTS3TXFBxxXt+f5wfV64s3isg3Ovr+Xjw\nAM7yPZ9zvjZz33zP+R7DNE1TAAAAAOBBvEq7AAAAAAAobgQdAAAAAB6HoAMAAADA4xB0AAAAAHgc\ngg4AAAAAj0PQAQAAAOBxCDoAAAAAPE6pBp309HT17NlTISEh8vLy0pw5c/Jss3PnTvXp00fBwcHy\n9/dX27ZttWPHDvv66OhoeXl5OXwNHDjwep4GAAAAgDKmVINOVlaWwsLCNGXKFPn5+ckwDIf1e/bs\nUWRkpBo2bKi0tDRt3bpV48ePV0BAgH0bwzD0yCOP6NChQ/avd95553qfCgAAAIAyxLs0Dx4XF6e4\nuDhJUmJiYp71Y8aMUWxsrCZNmmRfFhoammc7Pz8/Va9evaTKBAAAAOBmyuwzOjabTQsXLlTz5s0V\nGxur6tWrKyIiQvPnz8+z7bx581StWjW1atVKI0aM0OnTp0uhYgAAAABlRamO6BTm8OHDOn36tCZM\nmKC//e1vmjhxopYvX65BgwYpICBAPXr0kCQNHDhQoaGhql27trZs2aLRo0fru+++05IlS+xtZWZm\nltZpAAAAACiCSpUqXdN+ZTbo2Gw2SVLv3r2VlJQkSQoLC1NGRobeeuste9B5/PHH7fu0bNlSDRs2\nVEREhDZt2qRbb731+hcOAAAAoNSV2VvXqlatKm9vb7Vo0cJhebNmzfTzzz8XuF94eLjKlSun3bt3\nl3SJAAAAAMqoMjui4+vrq/bt2ztMJS1Z003nNyFBju+//16XLl1SrVq18l1/rUNfuL4yMjLUrl27\n0i4DTqCv3Av95T7oK/dBX7kX+ss9FMejJ6UadLKysrRr1y5J1q1q+/bt0+bNm1WlShXVqVNHI0eO\nVL9+/RQVFaWYmBilpaUpNTVVCxYskCT99NNPmjt3ru6++25VqVJF27Zt03PPPafw8HBFRkaW5qkB\nAAAAKEWleuva+vXrFR4ervDwcJ07d07JyckKDw9XcnKyJKlXr16aPn26Xn31VYWFhWnq1KlKSUmx\nT0nt6+urFStWqHv37mrWrJmGDh2q2NhYLVu2LM87eQAAAADcOEp1RCc6Oto+6UBBEhISlJCQkO+6\nkJAQrVy5sgQqAwAAAODOyuxkBAAAAABwrQg6AAAAADwOQQcAAACAxyHoAAAAAPA4BB0AAADAg2zZ\nInl7S8uXu7bfggVS+fLS7t0lU9f1RtABAAAAypjNm6WxY6V9+1zfd9gwKSpKuusu1/br1Utq3Vp6\n/nnXj1kWEXQAAACAMmbzZmncONeDztq10rJlVti5FkOHSh9/LG3bdm37lyUEHQAAALi1S5eks2dL\nu4qSYZqubf/221K1alKPHtd2vD59pIoVpX/+89r2L0sIOgAAAG7svfckLy9pxQrpb3+TQkOtD6q3\n3SatWWNts3KldOedUkCAVLu2td2Vzp+XJkyQWraU/Pyk4GCpZ09rZCG306elP//Zar9aNalCBalx\nY2n06Lxh49w56/arpk0lf3+rzbAwaeRIx+3GjrXO4eef89YVGirFxOQ93+XLpb/+VWrY0Kp3/nzX\nzqO4rtu1HDMtTXr1Vav2ChWs6/P++47X45FHrJ9jYqx9vLykhx/O//g5srOlTz6RunSRypUrfNuC\n+Ptbt719+OG17V+WeJd2AQAAACi6UaMkm01KSrI+eL/2mhQbK82cKQ0eLD35pPTQQ1JqqvTSS1L9\n+tKgQda+Fy9a265dK8XHS88+K504Ic2YIUVGSunpUtu21rYHDlht9u0rPfig9dD7ypXSxInSpk3S\n4sWXa3rqKWn2bCkhQerQwfogvnOn9UHfWYZhfV1p+HCrvSeekAIDpWbNnDuP4rxurl67HC+8YIXA\nwYMlX19p2jQpMVFq1Mi6Tn/4g3TokDR9ujRmjNS8ubVfw4aFX6sNG6SsLCkiwvnrm5/bb5eWLJF+\n+MEKYW7LvAGcOHHC/gX3sH79+tIuAU6ir9wL/eU+6Cv3Udp9NXu2aRqGabZta5oXL15e/umn1nJv\nb9PcsOHy8gsXTLNWLdO8447Ly15/3dp26VLHtk+eNM26dU0zOtpx/+zsvHW8+KLVxjffXF4WHGya\nd9999XNITrb23bcv77p69UwzJibv+TZrZppnzzpu68x55PRXcVw3Z495Ze3h4Y7HPHjQNMuXN80B\nA/Juu2pV3mtSkFmzrH0++yz/9adOmeZ995lmYKBp/uMf1rI5c0wzI8Nxu5QUq52PPnL+2MWtOD6/\nc+saAACABxg82BpdyXHnndb3O+6QwsMvL/fxkdq3l3bturxs7lxr1CA8XPr998tf589bt0F9+aX1\nc87+ObdFZWdLx49b2+bM8PXNN5fbDQqypjreurVkzrdCBcdlzpzHhQtGnnau9bo5e8yca5djyBDH\nY9auLTVpUvRpnY8csb5Xrpz/+r//3Tq/996TDh6UBg6Ujh3LO+JUpYr1/fDhotVT2rh1DQAAwAM0\naOD4e3Cw9b1+/bzbBgdLR49e/n37dutWqmrV8m/bMKwP7zffbP3+9tvWw+rbtlm3feV2/Pjln994\nw7rtq3Vrq76YGOnee62v/G5Hc0WTJnmXOXMeJ044fvwtynVz9pi5r11+x5SscLJ/f/5tOCvnmhY0\ngcGwYZfPr25d6/a0pKS82+XsX9Q+Km0EHQAAAA9Q0MPnzjyUbprWJAGvv17wNlWrWt9ff916PqZ7\nd+tDcu3a1nMmBw5Yz5nkDj49e0p790qLFkmrVlnTHs+caT3svmyZNUoiFf6BOjs7/+UVK17beVSo\n4NhgUa6bs8fMuXZXa9vVGdaulBO2jh3Lf31OyFm61ApoL7yQ/3Y5+xcU3twFQQcAAOAG16SJdZtS\nTMzV/4qfkmKNdvzvf47Lc09CkFtwsPXwfs4D/KNGWRMXLFhgTWggXb7V6tgxa6Qhx7lz0q+/5j96\nc63nkZFRxDRxDce8FtfSVuvW1vcrb6/L7T//sabjHjq04G1ybqFr1cr1GsoSntEBAAC4AeX+IB0f\nb83yVdCoxG+/Xf4559mS3CM32dnSK6847mOzWbOPXalNG+t77lvccmb2+uILx20nT3ZtlMOV87hW\nVwaQkjpmQID1/cpb5QrTpo01A93atfmvf+89a/roBx+0fjdNa1rwK339tVSzpjVtuDtjRAcAAOAG\nlDtADB1qhYwRI6z3ysTEWB+Yf/7Zel+Nn5+1XLJGYUaPluLipPvuk06elP79b+v2tdxOnpRq1ZJ6\n9bI+gFevLu3ZY02lXLmy9ZxOji5drLDz0kvWB/vQUOsh/nXrrNu+nA07zpzHxIlFumx5anHl2rnS\ndkSE9e6c8eOtkS5/f+vZnsKmji5Xznrh5yefSBcuOPbJRx9Zo2ihodZEBIGB0r/+ZU3Pndvp09Lq\n1dJjjzlXc1lG0AEAAHBzrt7mdOW7aby9pc8/tyYZSEmxXlgpWQ/QR0RY78HJMWKE9YF85kzrGZ1a\ntaT+/a3nc1q0uLydv7/0pz9ZH/aXLbM+QNeuLfXubQWlmjUvb+vlJX36qfUOmn/8w/qA3r279VxP\nZGTe8yvofF05j8LaKUh+7/QprmNe2XadOtKsWdZMaUOGWO/rSUy8+jtyBg+2Rm4WLrRCj2SNKv3w\ng/Txx1bY7N3bmiBh4kQriOb23/9aL369MgC5I8M0i/rYU9mXmZlp/7lSpUqlWAmclZGRoXbt2pV2\nGXACfeVe6C/3QV+5D/rKvdwI/RUXZ704NL8XpF5NeLg1cvThh8VflyuK4/M7z+gAAAAAHuS116zn\ndJYtc22/Tz6xpgz/+99Lpq7rjVvXAAAAAA/SooV1q5ureve2ZrrzFIzoAAAAAPA4BB0AAAAAHoeg\nAwAAAMDj8IwOAAAAPJZpmjp5MltbtmTrwAFDZ8400PnzZ9WqlbcCA71luDrHNNwGQQcAAAAeyTRN\nrVt3TsnJPlq6tIIkQ1IFSaa6d7+kv/zlnCIiKhB2PBS3rgEAAMDj5ISc2NgKWrrUW1bIyWFoyRJv\nde9eQevWndMN8FrJGxJBBwAAAB7n5MlsJSf7KDOz4NGazExDY8f66OTJ7OtYGa4Xgg4AAAA8zpYt\n2Vq6tNxVt1uypJy2biXoeCKCDgAAADzOgQOGHG9XK4ih/ft5RscTEXQAAAAAeByCDgAAADxOSIgp\nyZlJBkzVqcNkBJ6IoAMAAACP06qVt7p1u3TV7bp3v6SWLXnjiici6AAAAMDjBAZ6a9y4i6pUqeDR\nmqAgm8aOvajAQIKOJyq1oJOenq6ePXsqJCREXl5emjNnTp5tdu7cqT59+ig4OFj+/v5q27atduzY\nkWc70zQVFxcnLy8v/fe//70e5QMAAKAMMwxDEREVtHjxOXXvni3H29hMxcZm63//O6/bbuOFoZ6q\n1OJrVlaWwsLClJCQoPj4+Dz/wPbs2aPIyEglJibqpZdeUlBQkHbs2KGAgIA8bb322msqV86aPpB/\nqAAAAJCsz4W33VZBqanZ2rr1nPbvN3TmzBk1beqnli29FRhIyPFkpRZ04uLiFBcXJ0lKTEzMs37M\nmDGKjY3VpEmT7MtCQ0PzbLd+/Xq9+eab2rBhg2rUqFFS5QIAAMANGYahSpV81KGDjyQpI2OL2rVr\nV8pV4Xook8/o2Gw2LVy4UM2bN1dsbKyqV6+uiIgIzZ8/32G7U6dOaeDAgZoxY4aqVatWStLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d0652d278>"
+        "<matplotlib.figure.Figure at 0x7f1295ca4048>"
        ]
       }
      ],
@@ -848,7 +848,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzgAAAGkCAYAAAD9t4CTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d064437b8>"
+        "<matplotlib.figure.Figure at 0x7f1295ee3278>"
        ]
       }
      ],
@@ -877,7 +877,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzgAAAGkCAYAAAD9t4CTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06682dd8>"
+        "<matplotlib.figure.Figure at 0x7f1295d9e470>"
        ]
       }
      ],
@@ -946,9 +946,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzgAAAGkCAYAAAD9t4CTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzgAAAGkCAYAAAD9t4CTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d0662dcf8>"
+        "<matplotlib.figure.Figure at 0x7f1295de53c8>"
        ]
       }
      ],
@@ -1012,7 +1012,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAqgAAAH8CAYAAAAdT10gAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06769320>"
+        "<matplotlib.figure.Figure at 0x7f1295c923c8>"
        ]
       }
      ],
@@ -1149,9 +1149,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyEAAAGNCAYAAAAGr35PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyEAAAGNCAYAAAAGr35PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d066eab70>"
+        "<matplotlib.figure.Figure at 0x7f1295cfd400>"
        ]
       }
      ],
@@ -1228,9 +1228,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxkAAAGNCAYAAAB9i7yDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAGNCAYAAAB5fmy+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06623828>"
+        "<matplotlib.figure.Figure at 0x7f1295f418d0>"
        ]
       }
      ],
@@ -1284,9 +1284,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyYAAAGNCAYAAADkc2U2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d0650ba58>"
+        "<matplotlib.figure.Figure at 0x7f1295e3def0>"
        ]
       }
      ],
@@ -1347,9 +1347,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGNCAYAAADKNkSkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGNCAYAAADKNkSkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d064c3278>"
+        "<matplotlib.figure.Figure at 0x7f1295ce2470>"
        ]
       }
      ],
@@ -1423,7 +1423,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyIAAAGNCAYAAADtmMVMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d0651d1d0>"
+        "<matplotlib.figure.Figure at 0x7f1295cc1d68>"
        ]
       }
      ],
@@ -1496,25 +1496,25 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGaCAYAAADU5XaHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGaCAYAAADU5XaHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06764438>"
+        "<matplotlib.figure.Figure at 0x7f1295d21908>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGaCAYAAADU5XaHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGaCAYAAADU5XaHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d065450b8>"
+        "<matplotlib.figure.Figure at 0x7f1295c7a710>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGaCAYAAADU5XaHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd03NWZ//H3d0aj3nt1ly0X3LGNwQYHAyGQsCQEAtkQ\ndtmwSVg2QPbwW9jdH2xCYPmFTYCQJQsbEkInQGgJi+nYuBsXuRfJRZIlWb23mfv74zsaW1abkWYk\nCz6vc3wkfcv93rEHzjx67vNcyxhjEBERERERGUMcoz0BERERERGRQCmQERERERGRMUeBjIiIiIiI\njDkKZEREREREZMxRICMiIiIiImOOAhkRERERERlzFMiIiIiIiMiYo0BGRETGHLfbzcMPP8zs2bOJ\njo4mJSWFyy67jHXr1gU8VnFxMX/3d3/HuHHjiIiIICMjg6uvvprCwsIQzFxERILF0oaYIiIylhhj\nuOaaa3j55ZcpKCjgq1/9KtXV1bz44ou0tbXxyiuv8LWvfc2vsT777DNWrFhBY2MjK1asYMGCBZSV\nlfHqq69ijOGtt97iwgsvDPErEhGRoVAgIyIiY8rzzz/Pt7/9bc4991zef/99wsPDAdi8eTPnnXce\nCQkJHDp0iNjY2EHHmjt3Ljt27ODnP/85P/7xj33Hd+/ezaJFi0hMTOTAgQNERUWF7PWIiMjQaGmZ\niIgAdqbj4YcfZsaMGURFRZGbm8stt9xCfX09EyZMYOLEiaM9RQAee+wxAO69915fEAOwcOFCrrnm\nGk6cOMHLL7886DhFRUXs2LGDjIyMHkEMwIwZM7jhhhsoKyvjlVdeCe4LEBGRoFAgIyIiANx8883c\ndtttNDQ0cNNNN3Httdfy7rvvcvHFF9PV1YVlWaM9Rdra2li7di0xMTEsW7as1/lLL70UgA8//HDQ\nscrLywEYP358n+cnTZoEwPvvvz/U6YqISAiFjfYERERk9K1evZrf/OY35Ofns3HjRhISEgC47777\nWLlyJWVlZUyYMMHv8X7/+99z+PBhv69PSkriRz/60aDXHTp0CI/Hw6RJk3A4ev8ubsqUKQDs379/\n0LHS0tIAOHLkCMaYXoHaoUOHANi3b9+gY4mIyMhTICMiIjz11FMA3Hnnnb4gBsDlcnH//fdz3nnn\nBTzexx9/7Pf1EyZM8CuQqa+vB+gxx1N1H6+rqxt0rPz8fKZNm8a+fft46KGHuO2223zn9uzZ4/s7\nqa2tHXQsEREZeQpkRESErVu3AvQZsCxevBin0xnQeP4s7ToTPP7441xyySX8+Mc/5q233mL+/PmU\nl5fz6quvUlBQwNatW/vM/IiIyOjT/51FRIT6+nosyyIjI6PXOafTSUpKyijMqrfujEt3ZuZ03ccT\nExP9Gm/ZsmVs3LiRa665hl27dvHII4+wbt067rjjDn71q18B9Pl3IiIio08ZGRERIT4+HrAL4OPi\n4nqcc7vdVFdXEx0d7fd4oaqRmTx5Mg6Hg6KiItxud69M0YEDBwCYOnWq38+eNWsWzz//fK/jTz75\nJACLFi3yeywRERk5CmRERIT58+ezbds21qxZQ35+fo9z69evx+12BzReqGpkIiMjOffcc1m9ejWr\nV6/mggsu6HH+7bffBuBLX/pSQPPty1NPPYVlWXz7298e9lgiIhJ8WlomIiJcf/31ANx///09CuU7\nOjq46667Ah7vww8/xOPx+P2nqKjI77F/8IMfAPCv//qvtLe3+45v2rSJF198kfT0dL7xjW/0uOfo\n0aPs3buXhoaGHsdbWlp6BWnGGO655x5Wr17N9ddfz1lnnRXoyxcRkRFgGWPMaE9CRERG3/e//30e\nf/xxsrOz+frXv05ERARvvPEGSUlJlJSUEBkZycGDB0d7mgBcffXVvPzyyxQUFHD55ZdTXV3Niy++\nSEdHB6+88gpf/epXe1x/wQUX8Mknn/C73/2O7373u77jb731FjfeeCMXXXQROTk5tLW18e6777J3\n715WrlzJ66+/TlRU1Ei/PBER8UNQMzLHjx/nu9/9Lunp6URFRTFz5kw++eSTHtfcc8895OTkEB0d\nzYoVK9i9e3eP8+3t7dxyyy2kpaURGxvLFVdcQWlpaTCnKSIifXjsscf4xS9+QVxcHI8//jjPP/88\nF198MatWraK+vt5XR3MmeOGFF/jlL39JWFgYjz76KK+99povWDk9iAGwLMv351TTpk1j2bJlfPLJ\nJzz88MM8/fTTpKWl8T//8z+sWrVKQYyIyBksaBmZuro65s+fz/Lly/mHf/gH0tLSKCoqIisri4KC\nAgAeeOABfvazn/HUU08xdepUfvKTn7BmzRr27dtHbGwsYC8ZeOONN/jDH/5AcnIyt99+O3V1dWzZ\nskUtMEVERsGBAweYNm0a1157Lc8+++xoT0dERAQIYiBz1113+Yov+2KMITs7m3/8x3/kzjvvBKCt\nrY309HQefPBBbrrpJurr60lPT+f3v/891157LQAlJSWMHz+et99+m4svvjgYUxURkT5UVlaSmpra\n45dGLS0tfPOb3+Ttt9/mpZde4qqrrhrFGYqIiJwUtBTHa6+9xqJFi7jmmmvIyMhg3rx5/PrXv/ad\nLy4upqKiokcwEhkZyfLly1m7di0AW7ZsobOzs8c1ubm5TJ8+3XeNiIiExiOPPMLEiRO54YYb+Od/\n/mduuOEGpk2bxttvv81XvvIVBTEiInJGCVr75aKiIv7rv/6L22+/nbvuuoutW7dyyy23AHDzzTdT\nXl4O9N5YLD09nbKyMsDev6CvjdcyMjKoqKjocay/zdBERGRolixZwqZNm3jnnXeora3F5XIxefJk\n/v7v/54f/vCH+v+uiIgETfcGx8MRtEDG4/GwaNEifvaznwEwZ84cDhw4wK9//WtuvvnmAe89vfhS\nRERG3rJly1i2bNloT0NERMQvQVtalp2dzYwZM3ocKygo4OjRowBkZmYC9MqsVFRU+M5lZmb6dpA+\nVXl5ue8aERERERGRoGVkzj33XPbu3dvj2P79+5kwYQIAEydOJDMzk1WrVrFgwQLALvZfs2YNDz74\nIAALFizA5XKxatWqHsX+e/fuZenSpf0+OxipKZFumzdvZuHChaM9Dfkc0ntLQkHvKwkFva8kFIK9\nRDlogcxtt93G0qVLue+++7j66qvZunUrv/rVr7j//vsBe/nYrbfeyn333UdBQQH5+fnce++9xMXF\ncd111wF2QHLjjTdyxx13kJ6e7mu/PGfOHFauXBmsqYqIiIiIyBgXtEBm4cKFvPbaa9x111389Kc/\nZfz48dx777384Ac/8F1zxx130Nrays0330xtbS1Llixh1apVxMTE+K556KGHCAsL45prrqG1tZWV\nK1fyzDPPqI5GRERERER8graPzEg7NTWlpWUSTEqnS6jovSWhoPeVhILeVxIKwf78HrRifxERERER\nkZGiQEZERERERMYcBTIiIiIiIjLmKJAREREREZExR4GMiIiIiIiMOQpkRERERERkzFEgIyIiIiIi\nY44CGRERERERGXMUyIiIiIiIyJijQEZERERERMYcBTIiIiIiIjLmKJAREREREZExR4GMiIiIiIiM\nOQpkRERERERkzFEgIyIiIiIiY44CGRERERERGXMUyIiIiIiIyJijQEZERERERMYcBTIiIiIiIjLm\nKJAREREREZExR4GMiIiIiIiMOQpkRERERERkzFEgIyIiIiIigzJVFbj/6dt43nxutKcCKJARERER\nERE/dL74BBzcTccff4vxeEZ7OgpkRERERERkYKa6Ej54AwBXQw3mwM5RnpECGRERERERGYR57Q84\n3Z24sQCo+PiDUZ6RAhkRERERkTHFVJTh/oev43nvtZF5Xl0N5p1XAFh34d/ZBzd9MiLPHogCGRER\nERGRMcSs+V8oKcb85cWRed4bT0NHG5y9nMyrv0NzWCTpJ4rpPF46Is/vjwIZEREREZExxOzZZn9z\neD+mtTm0z2qsx/zlJQAc3/weU9NjKcydD0D5KC8vUyAjIiIiIjJGGI8H925vIOPxwP7CkD7P8+az\n0NYCc8/BmjoLy7IYd+GFAGTvWRvSZw9GgYyIiIiIyFhRUoyzpdH3oy87EwKepgaaX7f3jGn5q7/1\nHc89fwU4HLBrM6alKWTPH4wCGRERERGRMaI7cGl0RQPQXLg1ZM8qevFZYtqb2ZE+A8fM+b7jVnwS\nTJsDXV2wbV3Inj8YBTIiIiIiImPFXjuQ2b7gqwC4DhRi3F1Bf0xXSwspq14AoParf0OMq2fYYJ29\nHACz8eOgP9tfCmRERERERMYI462PcZ27kpLodFwdrXDkYNCfs+u5Z4lvb2Bf6lSWXfqlXud9gcyW\nTzFud9Cf7w8FMiIiIiISFKbmBJ4//hbTUDfaU/lcMjUnoKIEIqOZvfAs4mbby70CqZMxbjeeN5/D\nrP+g30xOa3Mr2e/ZtTGtV/4trrA+QobciZCVB411FH66IfAXEwQKZEREREQkKMyfn8c8+yjmvT+N\n9lQ+n7zLyph2FrFRESTOnd/zuB/M6v/F/PbneP7jx3huugzPi4/bAdIpPO+/TnJbHUdSJjLv0ov6\nHMeyLEqmnQNA0XvvB/5agkCBjIiIiIgER2WZ/bV8dDdK/LzqbrtsTZ/X46vZs93vMbrW2kFHa0QM\nVFdinn+Mrr+7lI4H7sDs3Izp7CTyzacAyPubH+Jw9B8uZF1gLzmbVbyBQ3Xtgb+gYVIgIyIiIiJB\nYaor7a9V5aM8k8+n2m1bAPg0bop9IG8SxMRBVTnmxOB/56a9Dc9Wu8vYVV/6OT9Y9m98kL0I4/Hg\nXPcunn/9Hp6bvgInyiF3ImFLe9fGnMo1az6tEbFMbCzl0y17h/fihkCBjIiIiIgER7V3iVLine truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGaCAYAAADU5XaHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d064db2b0>"
+        "<matplotlib.figure.Figure at 0x7f1295c804e0>"
        ]
       }
      ],
@@ -1553,7 +1553,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d0651d160>"
+        "<matplotlib.figure.Figure at 0x7f1295bad518>"
        ]
       },
       {
@@ -1561,7 +1561,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xl4lPW9///XPTNJJntCyEIWtpAAYRWQgxUoWLVilbau\nB1ygtu7aWu3RqlT0HIpLOVqtSqvfVjkuRy391dqeWqkWRW0VogRkD2tYwp4Esmdm7t8fk4zETEKW\nmdwzmefjunIluecz9/2euRHm5WczTNM0BQAAAABBYrO6AAAAAAB9G6EDAAAAQFAROgAAAAAEFaED\nAAAAQFAROgAAAAAEFaEDAAAAQFAROgAAAAAEFaEDABB0brdbTz75pMaOHau4uDilpaXpW9/6lv71\nr3916TwvvviibDZbu1+/+c1vgvQKAAA94bC6AABA32aapubMmaPly5drxIgRuv3223Xs2DG9/vrr\nmj59uv7whz9o9uzZXTrnjBkzNGPGjDbHzzzzzABVDQAIJEIHACCoXnvtNS1fvlxnn3223nvvPUVH\nR0uSbrrpJk2dOlXXX3+9zjnnHCUkJHT6nDNmzNADDzwQrJIBAAHG8CoACFOmaerJJ59UUVGRYmNj\nlZubq9tvv11VVVUaPHiwhgwZYnWJkqSlS5dKkhYtWuQLHJI0adIkXXnllTpy5IiWL19uVXkAgF5A\nTwcAhKlbb71Vv/71r5Wdna0bbrhB0dHR+vOf/6zVq1fL5XK1+oBvlfr6ev3zn/9UfHy8pk2b1ubx\nWbNm6aWXXtLKlSs1f/78Tp9327Zt+tWvfqXq6moNGDBAM2fO1KBBgwJYOQAgkAgdABCGPvzwQ/36\n179WQUGBVq9ereTkZEnS4sWLde655+rAgQMaPHhwp8/34osvavfu3Z1un5qaqh/96Eenbbdjxw55\nPB4NHTpUNlvbzvVhw4ZJ8oaIrnj11Vf16quv+n632Wy69tpr9cwzzyg2NrZL5wIABB+hAwDC0LJl\nyyRJ9957ry9wSFJUVJQefvhhTZ06tcvn++CDDzrdfvDgwZ0KHVVVVZLUqsZTtRyvrKzs1HWHDh2q\np59+Wueff75yc3NVVVWlDz/8UPfee69efPFFVVdX64033ujkqwAA9BZCBwCEobVr10qS33Dxb//2\nb7Lb7V0638qVKwNSV7BNnz5d06dP9/3udDp12WWXacqUKRo3bpyWL1+ukpISjR8/3sIqAQBfxURy\nAAhDVVVVMgxDmZmZbR6z2+1KS0uzoKq2WnoyWno8vqrleEpKSo+uk5ubqwsvvFCS9PHHH/foXACA\nwKOnAwDCUFJSkiTp4MGDSkxMbPWY2+3WsWPHFBcX1+nzBWtOR35+vmw2m3bu3Cm3292mB6a0tFSS\nVFhY2Olrt6d///6SpJqamh6fCwAQWIQOAAhDEyZMUElJiT766CMVFBS0euyTTz6R2+3u0vmCNafD\n6XTq7LPP1ocffqgPP/ywzYZ+b7/9tiTpnHPO6VK9/nz66aeSvPM+AAChheFVABCGrr32WknSww8/\n3GoSdmNjo+67774un2/lypXyeDyd/tq5c2enz33zzTdLkhYsWKCGhgbf8TVr1uj1119XRkaGLr30\n0lbPKSsr05YtW3TixIlWx4uLi9uc3+Px6OGHH9Ynn3yi9PR0XXDBBV156QCAXmCYpmlaXQQAoOtu\nuukmPffcc8rOztYll1yimJgYvfXWW0pNTdW+ffvkdDq1fft2q8uUJF1xxRVavny5RowYoYsuukjH\njh3T66+/rsbGRv3hD3/QxRdf3Kr9jBkztGrVKr3wwguaN2+e77jNZtPo0aM1duxY5eTkqKqqSh9/\n/LE2btyo+Ph4/fGPf9S5557b2y8PAHAaHfZ0rFq1SrNnz1Zubq5sNptvicZTbdu2TZdccolSU1MV\nHx+viRMnasuWLUErGADgtXTpUj3++ONKTEzUc889p//93//V+eefrxUrVqiqqso37yMUvPbaa3ri\niSfkcDj09NNP68033/QFi68GDkkyDMP3daqf/OQnSk1N1cqVK/XUU0/p5Zdfltvt1m233aYvvviC\nwAEAIarDno63335bH3/8sc444wxde+21Wrp0qa9LX5J27dqlyZMna/78+brqqquUkpKiLVu2aPTo\n0crNze2VFwAAaK20tFTDhw/XnDlz9Morr1hdDgAAnR9elZiYqGeeeaZV6Jg7d67sdrteeumloBUI\nAPDv8OHD6t+/f6udvmtra3X55Zfr7bff1htvvKHLLrvMwgoBAPDq9kRyj8ejv/zlLxo5cqQuuOAC\nZWRkaPLkyewECwC95KmnntKQIUM0f/58/fSnP9X8+fM1fPhwvf3227rwwgsJHACAkNHtJXMPHz6s\n6upqLV68WIsWLdJjjz2m9957T1dddZUSEhJ8mzS1aG9jKABA90yZMkVr1qzRO++8o4qKCkVFRSk/\nP1833nijbrnlFv7eBQAERMtGrz3R7dDh8XgkSd/5znd0xx13SJLGjh2r4uJiPf30021CBwAgsKZN\nm6Zp06ZZXQYAAKfV7eFV/fv3l8PhUFFRUavjI0aMUFlZWY8LAwAAANA3dLunIzo6WmeeeWab5XG3\nbdumwYMHd/jcQHTRIDwUFxdr0qRJVpeBXsQ9jzzc88jEfY883PPIEughuh2GjpqaGpWWlkryDqfa\ns2ePSkpKlJaWpry8PN1999264oorNG3aNM2cOVMrV67U66+/rj/96U8BLRIAAABA+OpweNWaNWs0\nYcIETZgwQfX19Vq4cKEmTJighQsXSpK+/e1v67nnntOSJUs0duxYPfPMM3rppZc0a9asXikeAAAA\nQOjrsKdjxowZvgnj7Zk3b57mzZsX0KIAAAAA9B3dnkgOAAAAAJ1B6AAAAAAQVIQOAAAAAEFF6AAA\nAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAAAEFF\n6AAAAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAA\nAEFF6AAAAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAAAEFF6AAAAAAQVIQOAAAAAEHlsLoAdF5FvVsH\nappU1eBWVYNbsQ6bZuQltGm3/2STXtxUIZskw5BiHTbFR9mUHe/QhUOT2rR3e0y5TVPRdjIoAAAA\nAo/QEQY2Hq3X/R8f1J4TTa2Oj+nv9Bs6jta7tHxbVZvjY/o7/YaOzccbdM3be+W0G0qKsSs52qbk\nGLuK0mL044npbdrXuzw6Xu9WqtOuWAdBBQAAAB0jdISB/rF27TnRJKfd0ODkaF8oGJoc7bd9TkKU\n7p2cLlPeXow6l6lal0fpsf5vd22TRw5Dqnebqq916XCt97jN8F/PhmP1un7FfkmS024oJcauVKdd\nEzJj9ZNJbUNKbZNHR+pcSo2xKzHaJsNo58QAAADokwgdIeJgTZOWb6vSzePSZP/Kp/3M+Ci9cmGe\nClJjFNVeEjhF/1iHrhie0ulrTx4Qp9VXDVOdy9SJRreqGjyqbHArxu7/Wi6PlBnnUEW9W/VuUwdr\nXTpY61J6nP8/Tp8frtPt/zggSXIYUnJzSDkrO053+ulJOdHgVnmNS6lOu1JibAz7AgAACHOEDoud\nbHTrdxsq9OrmSjV6TOUlRunbw5LbtCtKcwa1DsMwFBdlKC7Kpqz4jttOGRCnv106RKZpqtZlqqLe\nrcoGt6LbCSmmpNyEKFU2uFXd5NGxereO1bvb7alZfbBW/7HqoO/3+CibUmJsmpmXoLv89KQcrXNp\n94lGpUTbleK0Kznarqh2agEAAEDvI3RYpMlj6vdbK/X8F8dV2eCRJJ0/KEETMmMtrqzzDMNQfJSh\n+CibchOj2m03LSde077rTTKNbo8qGzyqqG+/J8VhMzQsJVqVDW5V1rtV0+RRTZNHJxs9ftv/60Ct\nHvjnoVbH4qNsmp2fpLvPbBtS9pxo1KZjDUqJsSkpxq6UaLuSY7yT7Rn6BQAAEHiEDou8urlSv/z8\nqCRpQkasfjyxv0b3D25vRiiIttuUEWdTRjtDsSRpRl6Cb4K8aZqqbvJOXG+vJyUx2qYzMpyqbPCo\nst6tE43eoOIxTb/tPy2v1cOrj7Q5fsmwJP3srMw2xzccrdcn5bVKap5LkxztDSuZcQ6ltTNPBgAA\nAF/iE5NFrhqZomP1Lp2RHqsZefH8H/Z2GIahxGi7EqPt7bY5NaRIksc0Vd1Or4gkZSdE6fxBCaps\n8M5fqWpwq6rRraQY/9f4/FCdnik51ub43BEp+g8/PSkf7K3W33afVFK0XUnRNiU2B5UR/Zwa3i+m\no5cLAADQJxE6LOKwGX4nUaPnbIbRboCQpKk58Zqa03biSns9I6P7O3Xd6FRVNbh1otHj+56T4H9I\n2ZaKBv1td3Wb49eNTvUbOl7fWqn/3VKppGjv6l4JUd6elOm58Zrmp86TjW65PFJCtK1TCwsAAABY\njdABNLO109s0ITO2S3Ntzh2YoNyEKJ1o9OhEo1snGzyqanRrVDuLARyscTXvwdJ6H5aMWIff0PHS\nJu9cIEmKdTT3BEXZNHdkii4paLsIweZj9So72eQLNAnRdiU0T85nZTAAANAbCB1AgOWnxCg/pfPD\nqK4bnaqL85N0stHbg1Ld/L29OT52Q0qOtulkk0d1LlN1LpcOy7sfij9v7z6plzZVtjn+wzPS9L3R\n/doc/7+dJ/RJea0voCRGeSfZj89wdul1AQAAtCB09ILj9S79Ys0R/cekdPVj4jG+4nRzVr7qxnFp\nunFcmm/J4pONbp1s9Kif0/85ClJidN6gBJ1oXrK4usmj6kaPUtoZgrbuSL3+svNkm+P/MSLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d065c19e8>"
+        "<matplotlib.figure.Figure at 0x7f1295bad9e8>"
        ]
       },
       {
@@ -1569,7 +1569,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d064c8dd8>"
+        "<matplotlib.figure.Figure at 0x7f1295e7d5c0>"
        ]
       }
      ],
@@ -1604,7 +1604,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxkAAAGaCAYAAABjWI6gAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d064302b0>"
+        "<matplotlib.figure.Figure at 0x7f1295c88630>"
        ]
       },
       {
@@ -1612,7 +1612,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxkAAAGaCAYAAABjWI6gAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Wl4FUX+9vFvdfaNBJIQCGEXiWxCBhVBEdRBUAeXUf8i\nCoyKjiIKLiAqIiOioIhR0RlXGMV5VGYRdVQUAQEFQcANQWTfIUBC9uScrudFIGM8SQhwst+f68qF\nVFf3+ZG0Se5TXVXGWmsRERERERHxE6e6CxARERERkbpFIUNERERERPxKIUNERERERPxKIUNERERE\nRPxKIUNERERERPxKIUNERERERPxKIUNERCrdI488guM4zJo1q7pLERGRKqCQISLiZ16vl9TUVLp0\n6UJ4eDixsbFccsklfPXVV8d1nZkzZ+I4Tpkff/vb3455jf3799OkSRMcx+Hss88ut+/8+fO54oor\naNKkCaGhoTRr1oz+/fvz0UcfHVfd5THG+O1alenQoUOMHj2aVq1aFX8ubrrpJnbu3Fnha3g8Hv7z\nn/8wfPhwOnfuTExMDOHh4XTo0IH77ruPtLS0Ms/dsWMHN910E4mJiYSGhtK6dWtGjx5Nenq6T98t\nW7aUe58MGjTohD4HIiInI7C6CxARqUustQwaNIg5c+aQnJzMyJEjOXDgAG+//Ta9e/fmn//8JwMH\nDjyua/bp04c+ffr4tJ9xxhnHPHf48OHk5OQA5f+CP2bMGJ566imaN2/O5ZdfTlxcHPv27WPVqlUs\nWrSIAQMGHFfNtdmBAwfo1asXP//8MxdccAHXXXcdP/30E6+//joffvghX331Fa1btz7mdX755Reu\nvPJKwsPD6dOnDxdffDEFBQXMnz+fadOmMXv2bBYvXkzbtm1LnLdp0yZ69uzJvn37uPzyy0lOTmb5\n8uWkpqby8ccfs3TpUho1auTzeq1atWLYsGE+7Z06dTrhz4WIyAmzIiLiN2+99ZY1xthzzjnH5ufn\nF7evWLHChoSE2MaNG9vMzMwKXev111+3xhg7ceLEE6rllVdescYY+9JLL1ljjD377LNL7Xf0+J/+\n9CdbWFjoc7y0tuM1YcIEa4yxs2bNOulrVbZbbrnFGmPsvffeW6L92WeftcYY279//wpdZ+fOnfb5\n55+3WVlZJdpd17XDhw+3xhg7cOBAn/P69etnjTH2+eefL9F+9913W2OM/fOf/1yiffPmzdYYY/v2\n7VuhukREqoIelxKRWsFaS2pqKh06dCAsLIykpCRGjhxJRkYGrVq1qtA7y1XhxRdfBGDSpEkEBwcX\nt3fv3p3/+7//Y//+/cyZM6fS69i0aROjRo3i1ltvpV+/fmX2y8/P58EHH6Rly5a89NJLBAb6DnCX\n1nairLUsWLCAPn360KBBA6Kjo7n00ktZt26d317jZGRlZfHGG28QGRnJI488UuLYHXfcQYsWLfjk\nk0/YvHnzMa+VmJjIiBEjiIiIKNFujGHixIkALFy4sMSxjRs38umnn9K6dWtGjBhR4tjEiRMJDw/n\nzTffLB6dEhGpqRQyRKRWGDFiBKNHj+bw4cPccsstDBo0iE8//ZR+/frh8XhqxLP+eXl5fPnll0RE\nRHDuuef6HD/6yNGCBQuO67o///wzzz33HI8//jgzZ85k69at5fb3er3ccMMNJCQkMG3aNKy1Zfb9\n9NNPSUtL48orrwTggw8+YMqUKaSmprJs2bLjqrMiPvjgAy666CJiYmK47bbbOPfcc/nvf//Leeed\nx4EDB/z+esdr2bJl5OXl0atXr1LDQf/+/YHj/xr+1tHg9tsAd/S6pQXDyMhIevXqRXZ2dqlfm0OH\nDvHqq68yefJkXnjhBVatWnVSNYqInAzNyRCRGm/x4sX89a9/pV27dnz99ddER0cDMHnyZC688EJ2\n7dpFq1atKny9mTNnsmXLlgr3b9iwIXfdddcx+23cuBHXdWnTpg2O4/sezimnnAIUhYbj8dZbb/HW\nW28V/91xHIYMGcKMGTMICwvz6f/EE0+wbNkyFi5cSHh4eLnXXrFiBQAhISF07dqVtWvXljjeu3dv\n5syZQ1xc3HHVXJb33nuPTz75hL59+xa3PfDAAzzxxBO89tpr3HfffRW6zm9HGY6lW7duXHbZZcfs\nt379egBOPfXUUo8f/Rpu2LDhuF7/t1599VWA4tBS0ddv164dn376KRs2bOD8888vcezbb79l+PDh\nJdp69uzJm2++eVz/f4iI+INChojUeEeXPR03blxxwAAICgri8ccf55xzzjnu6y1atKjC/Vu1alWh\nkJGRkQFQosZfO9pe2gpBpWnTpg3PP/88/fr1IykpiYyMDBYvXsy4ceOYOXMmWVlZvPPOOyXO+eab\nb5g4cSKjRo0qdTTlt/bt2wfAk08+SceOHVmyZAldu3Zl06ZN3HvvvcybN4+rr776pN+5P+raa68t\nETAAbrnlFp544oniwFMRf/nLXzDGlDtKc5QxhqFDh1YoZPj7a1iaZcuWMXHiRKKjo3nsscdO+vUj\nIiJ4+OGHufzyy2nTpg1QFDgeeeQRFixYwAUXXMB3333nMzIjIlKZFDJEpMZbvXo1QKlh4qyzziIg\nIOC4ruevX5grW+/evendu3fx30NDQ7nqqqvo0aMHp59+OnPmzGHNmjV07doVgNzcXK6//npOOeUU\nJk+eXHxeeY+Sua4LFAW2uXPn0qJFC6BoRaJ///vftG/fnkWLFrFs2TJ69Ohx0v+m7t27+7QlJSUB\nRY/7VNTRumub77//nksvvRRrLW+99ZZfRhji4+N9RnbOPfdc5s2bxznnnMPy5ct5+eWXGTVq1Em/\nlohIRWlOhojUeBkZGRhjSEhI8DkWEBBAbGxsNVTl6+i7zEffjf6to+0xMTEn9TpJSUlcfPHFACxZ\nsqS4/aGHHuKXX35h1qxZhISEFLeX927/0Vq6detWHDCOCgsL46KLLgI4rlGG8pT2bz86L8Hr9frl\nNU5GZX4Nv/32W84//3yys7OZM2dOqcsC+/P1AwICuPnmmwFYunTpcdcrInIyNJIhIjVegwYNANiz\nZw9RUVEljnm9Xg4cOHDMuQe/VllzMtq2bYvjOGzatAmv1+szwnL0Of6ynrc/HkfnSPx6laFvvvkG\nr9fLWWedVeo5y5Ytw3EcoqOji0cNkpOTgbJ/aT3anpube9I1+1Nlzck4+vkoa97MiX4NV6xYwUUX\nXUR+fj7vvfdemSt+HX39o3MzTvb1j94n2dnZx1WviMjJUsgQkRovJSWFNWvWsGTJEtq1a1fi2LJl\ny477HfDKmpMRGhpKr169WLx4MYsXL/bZQO/oztm/nbB7IpYvXw5Q/Aw+wKWXXlrqL5+ZmZm8/fbb\nxMfHc9lll5UIZBdccAHGGNauXYu11ufRqh9++AGgxiwRfFRlzcno0aMHoaGhLF26lKysLCIjI4uP\nua7LvHnzMMb4zCspz+LFi7nkkksA+PDDD0vdWPGoo9f99NNPfb4emZmZLF26lIiIiAo/unZ0Fapf\n3yciIlWi2nboEBGpoEWLFlljjG3Xrp09dOhQcXt+fr7t3bu3NcbY1q1bV2OF//OPf/zDGmNsr169\nbF5eXnH7119/bYODg21CQoLPZnxbt261P/30k83IyCjRvmLFCp/re71eO3nyZGuMqfDGflu2bCl3\nM77LLrvMGmPs9OnTS7R/8skn1hhjGzVqZA8fPlziWMuWLa0xxi5cuPCYr2/tsTfjq0mbyd16663W\nGGPvueeeEu2pqanWGGMHDBjgc85PP/1k161b57Nx4WeffWbDw8NtTEyMXbp0aYVe/6KLLrLGGPvc\nc8+VaB89erQ1xtjbbrutRPs333xjXdf1uc5nn31mQ0JCrOM49quvvqrQa4uI+ItGMkSkxuvduze3\n3HILL730Ep06deLKK68kJCSEuXPn0rBhQxITE0tdMrY6XHvttfzrX/9izpw5dOvWjUsvvZQDBw7w\n9ttvY63l5ZdfLvHuOMCQIUP44osveP311xk6dGhx+5lnnkmnTp3o0qULzZo1IyMjg6VLl/Ljjz8S\nERHB7Nmzfa5VGnuMd/tnzJjB6tWrufvuu/nwww/p2rUrmzdv5j//+Q9BQUG88sorPo+pua6LMabE\nhoN1xeTJk1m0aBFPP/00a9as4YwzzuCnn35i7ty5JCQkMGPGDJ9zOnToAMCWLVuK57asX7+eSy+9\nlPz8fC644ALmzZvHvHnzfM4dPXp0idWkXnjhBXr27Mmdd97J/PnzSU5OZvny5SxcuJD27dv7rEh1\n991388svv9CzZ0+aNWsGwHfffceCBQswxvDoo4/6ZdK+iMhxKS+BLFq0yP7hD3+wzZo1s8YYO3Pm\nzBLHMzIy7G233WaTkpJsWFiYbd++vc87YSIi/uC6rp0+fbpNTk62ISEhtlmzZvaOO+6wGRkZNjIy\n0nbr1q26Syzm9XrtM888Yzt37mzDwsJso0aN7CWXXFLmu8l9+vSxjuP4vMt/33332d69e9vExEQb\nGhpqIyIi7GmnnWZHjhxpN2/eXOF6Nm/eXO5IhrXW7t+/344cOdK2bNnSBgcH2/j4eHvllVeWOppy\n4MABa4yxycnJpb6DXppHHnmk1H/jUTVpJMNaaw8dOmRHjRpV/PlITEy0N910k925c2ep/Y0x1nEc\nu3Xr1uK2BQsWFLcbY0r9+O05R+3YscPeeOONtmnTpjY4ONi2atXKjh492qanp/v0ffXVV+0ll1xi\nW7VqZSMjI21ISIht2bKlvfbaa+2SJUv890kRETkOxtqy3+L66KOPWLp0Kd26dWPIkCG8+OKLDBky\npPj4jTfeyKJFi3jttddo3bo1ixYtYvjw4bzyyitcf/31VRKSRKR+27BhA+3bt2fQoEHMnjLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d04be41d0>"
+        "<matplotlib.figure.Figure at 0x7f1295bf7f28>"
        ]
       }
      ],
@@ -1660,7 +1660,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGaCAYAAACBhJXZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d04bf65c0>"
+        "<matplotlib.figure.Figure at 0x7f1294302160>"
        ]
       },
       {
@@ -1668,7 +1668,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAGaCAYAAABnrV6dAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d04b378d0>"
+        "<matplotlib.figure.Figure at 0x7f1294302860>"
        ]
       },
       {
@@ -1676,7 +1676,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAGaCAYAAABnrV6dAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d04bdd668>"
+        "<matplotlib.figure.Figure at 0x7f1294382be0>"
        ]
       }
      ],
@@ -1753,9 +1753,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAA0IAAAGkCAYAAAAc3JXCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAA0IAAAGkCAYAAAAc3JXCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06705b70>"
+        "<matplotlib.figure.Figure at 0x7f1295de43c8>"
        ]
       }
      ],
@@ -1784,9 +1784,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d06638908>"
+        "<matplotlib.figure.Figure at 0x7f1295e8f0f0>"
        ]
       }
      ],
@@ -1813,9 +1813,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d066e8c50>"
+        "<matplotlib.figure.Figure at 0x7f1295de5278>"
        ]
       }
      ],
@@ -1844,9 +1844,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGaCAYAAACBhJXZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xl8VOW9P/DPM5M9mewbIYEESAJugLK5sqlFrVorbtd7\nXX5ttbeoVNtata3Xal161bpUq/X2tlbUq6gVxQVbAVEkyCLIDkGSQDZCQvZ95jy/P84yM8msyUxm\nJnzerxcvkpnJOU/CAOd7nu8ipJQSREREREREQWQK9QKIiIiIiGj0Y+BBRERERERBx8CDiIiIiIiC\njoEHEREREREFHQMPIiIiIiIKOgYeREREREQUdAw8iIgopEwmE4qKikK9DCIiCjIGHkREYe7DDz/E\n/PnzkZKSAovFgjlz5uCVV14Z0rHKyspwySWXID09HQkJCZg6dSqeeeYZKIoy6LXV1dV4+OGHcdVV\nV2HSpEkwmUwwmUw4cODAcL+lQYQQAT+mL/bu3Yurr74a2dnZiI+Px+TJk/HAAw+gp6fHr+O8/fbb\nuP3223HuueciOTkZJpMJ1113XZBWTUQUmaJCvQAiInLv+eefx+23347MzEzccMMNiImJwVtvvYWb\nbroJO3fuxOOPP+7zsd577z1ceeWVSEhIwDXXXIP09HS8//77uPPOO/Hll19i+fLlTq/fsmULfvOb\n3xg7EqmpqWhtbQ30txgymzZtwoIFC2C1WrF48WIUFBRg9erVePDBB7F69WqsXr0aMTExPh3rd7/7\nHXbs2AGLxYL8/Hzs27cvZMEUEVHYkkREFJYqKipkbGyszMzMlFVVVcbjzc3NctKkSVIIIcvKynw6\nVmtrq8zKypJxcXFy69atxuM9PT3yrLPOkkII+cYbbzh9TXV1tVy/fr1sb2+XUko5d+5cKYSQ+/fv\nD8B3ZyeEkEVFRQE9pjdWq1VOmTJFmkwmuXLlSuNxRVHk4sWLpRBCPvbYYz4fb+3atfLgwYNSSik/\n++wzKYSQ1113XcDXTUQUyZhqRUTkAyklnnnmGZx00kmIj49Hfn4+br/9drS2tqKwsDAoNQp//etf\n0dfXh9tuuw3jxo0zHk9NTcV9990HAHjxxRd9Otbbb7+NxsZGXHvttTj99NONx2NjY/G73/0OAPDC\nCy84fc3YsWNx9tlnIykpabjfik+6urrwi1/8AuPGjUNcXByKi4vx3//930E517p167Bv3z6cd955\n+O53v2s8LoQwzunrzxYA5s2bh4kTJwJQ3ytERDQYU62IiHywZMkSvPjii8jLy8Mtt9yCmJgYrFy5\nEps2bYLVavU5Jccfa9asAQAsWrRo0HMXXXQRAGDt2rXDPtZ5552H+Ph4lJWVob+/H9HR0UNd8pD1\n9fXhwgsvRF1dHS655BJERUXh3XffxT333IOenh7cf//9AT2fp59HUVERiouLcfDgQRw6dAgTJkwI\n6LmJiE5UDDyIiLz44osv8OKLL6K4uBibNm1CSkoKAOCRRx7B+eefj9raWhQWFjp9TWtrK5566im/\nzjN//nzMnTvX+Hz//v0QQqCkpGTQa3Nzc5GQkIDq6mr09PQgLi7O47H3798PAC6PZTabUVRUhL17\n9+LQoUMoLS31a92BUFtbi2nTpmH16tWIjY0FANx///0oKSnBU089hfvuuw9RUfb/sp5++mm0tLT4\nfPyioiLceOONxueefh4AUFxcjPLycpSXlzPwICIKEAYeRERe/P3vfwcA3HvvvUbQAQDR0dF49NFH\ncc455wz6mubmZjz44IM+n0MIAZPJ5BR46IXcjud0lJKSgu7ubrS2tnoNPFpbWyGE8HgsKaVfF/OB\nJITAs88+awQdAJCVlYXLLrsMy5Ytw4EDB3DSSScZzz3zzDOoqqry+fjz5s1zCjx8+dkCCNnPg4ho\nNGLgQUTkxbZt2wDAZYAxe/ZsmM3mQY8XFha6bFFLrqWkpLjcWSgoKACgBnKOKioqRmRdREQUOCwu\nJyLyQt8tyMnJGfSc2WxGRkZGUM6r33V318LW2137gceSUno9Vmpq6lCWOmzuzqunV9lstoCez9ef\nbah+HkREoxF3PIiIvEhOTgYA1NfXw2KxOD1ns9nQ1NSEhIQEp8cDUeNRWlqKDRs2YP/+/ZgzZ47T\na+vq6tDV1YWCggKvaVb6sbZu3Yr9+/dj+vTpTs9ZrVZUVFQgOjo6YuoZhlvjMXnyZAD2Wo+BysvL\n3dbXEBHR0DDwICLy4vTTT8f27duxfv16FBcXOz23ceNGl3fj9RoPIYRP7VVd1XgsXLgQGzZswKpV\nqwYFHh9//DEAYMGCBT59DwsXLsTrr7+OVatW4dprr3V67vPPP0d3dzfmzp0bko5WQzHcGo8FCxbg\n4YcfxqpVq3DPPfc4vfbQoUMoLy8PWptkIqITFVOtiIi8uOGGGwAAjz76qNNd9r6+PmOexkB6jYfN\nZoOiKF5/2Wy2QS1jb775ZsTGxuK5555zushubm7GI488AiEEfvzjHzt9TVNTE/bt24f6+nqnxxcv\nXozMzEy88cYb2Lp1q/F4T08Pfv3rXwMA/vM//9Onn4enQOrll1+GyWTC/PnzfTrWUFVUVPj0c9V/\n6e1zdXPnzsWUKVPw+eefY+XKlcbjiqLgl7/8JQAM+tl2d3dj3759OHToUFC/NyKi0Yo7HkREXpx3\n3nm45ZZb8NJLL+GUU07B97//fcTGxuL9999HWloa8vLyYDIF/j5OYWEhnnjiCdx+++2YMWMGrrnm\nGkRHR+Ptt99GTU0Nfv7zn2P27NlOX/PHP/4RDz74IG688Ub87W9/Mx63WCz4y1/+giuvvBLz5s3D\ntddei7S0NLz//vs4cOAArrrqKlx99dWD1nDTTTcZH+/btw+A2t1LTz+74oorcPnllxuv0QvqgzHX\nJJBMJhP+9re/YcGCBVi8eDEWL16MgoICrF69Glu3bsU555yDO++80+lrvvrqKyxYsADjx48fVNy+\nYsUKrFixAgCMoG/jxo3Gz08I4fTnQUR0QvI01vyRRx6RM2bMkMnJyTIrK0teeumlcteuXU6vEUK4\n/LVkyZIgDVsnIhp5iqLIp556Sk6ePFnGxsbKsWPHyttuu022trbKpKQkOX369KCd+8MPP5Rz586V\nFotFJiUlyVmzZslXXnnF5WsfeOABaTKZ5M033+zy+bKyMnnxxRfLtLQ0GR8fL0877TT59NNPS0VR\nXL5eCCFNJpPxu/5L//y3v/2t0+uXLl0qhRDy1Vdf9fn7E0LIoqIij9/PunXrfD6eP/bs2SOvvvpq\nmZWVJWNjY2Vpaal84IEHZE9Pz6DXfvbZZ27X+sADDwz6GQ38WRERneiElO73zBctWoTrrrsOM2fO\nhKIouP/++1FWVoY9e/YgLS0NANDQ0OD0NZs3b8all16KdevW4dxzzw1u1EREFGLl5eUoLS3Fdddd\nh9deey3Uywm5adOmoa+vD7t374YQItTLISKiMOIx1WrVqlVOny9btgwpKSnYsGEDLrnkEgBAdna2\n02tWrFiB0tJSBh1ENKo0NDQgMzPTKaWqq6sLP/3pTwGoKUcnuuPHj2Pnzp14/fXXGXQQEdEgftV4\ntLW1QVEUY7djoI6ODrzxxhv47W9/G5DFERGFi2effRbLli3D/PnzkZubi/r6eqxevRo1NTW4+OKL\nsXjx4lAvMeTS09MDPm+DiIhGD78Cj6VLl2L69Ok488wzXT7/+uuvo7+/36lloc7dkCYiokgwZ84c\nbN68GZ988gmam5sRHR2NiRMn4tZbb8VPfvIT/htHRESjmi/Dar3xWOPh6K677sLy5cuxfv16FBYW\nunzNzJkzMXHiRLzxxhuDnuN/ykREREREkSkQgYdP/R/vvPNOvPnmm1izZo3boGP79u3YunUrfvSj\nHw17UURERERENLp4TbVaunQp3nrrLaxduxYlJSVuX/fSSy9hwoQJWLhwodeTBiJiItJt2bIFM2bM\nCPUyaBTie4uCge8rCga+rygYAp2x5DHwWLJkCV599VWsWLECKSkpxlAki8WCxMRE43VdXV147bXX\ncM899wR0cURERERENDp4TLV64YUX0NHRgYULFyIvL8/49eSTTzq97s0330R3dzduvvnmoC6WiIiI\niIgik8cdD0VRfDrIzTffzKCDiIiIiIjc8qm4nIiIiIiIaDgYeBARERERUdAx8CAiIiIioqBj4EFE\nREREREHHwIOIiIiIiIKOgQcREREREQUdAw8iIiIiIgo6Bh5ERERERBR0DDyIiIiIiCjoGHgQERER\nEVHQMfAgIiIiIqKgY+BBRERERERBx8CDiIiIiIiCjoEHEREREREFHQMPIiIiIiIKOgYeREREREQU\ndAw8iIiIiIgo6Bh4EBERERFR0DHwICIiIiKioGPgQUREREREQcfAg4iIiIiIgo6BBxERERERBR0D\nDyIiIiIiCjoGHkREREREFHQMPIiIiIiIKOgYeBARERERUdAx8CAiIiIioqBj4EFEREREREHHwIOI\niIiIiIKOgQcREREREQUdAw8iIiIiIgo6Bh5ERERERBR0DDyIiIiIiCjoGHgQEREREVHQMfAgIiIi\nIqKgY+BBRERERERBx8CDiIiIiIiCjoEHEREREREFHQMPIiIiIiIKOgYeREREREQUdAw8iIiIiIgo\n6Bh4EBERERFR0DHwICIiIiKioGPgQUREREREQcfAg4iIiIgi2vqaTnx9tBs9ViXUSyEPokK9ACIi\nIiIiX0gpIYQY9PgfthxDRVs/ogRQkh6LBQVJuPmUNJhcvJZChzseRERERBT2mntsuOmTamxr6HZ6\nXJESM3ITUJIWAwXAnqZePLe9Cc9vbwrNQskt7ngQERERUViTUuKBsqPYcawHz29vwv9cMNLine truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xl8VPXZN/7Pd2ayL5OE7ARIgBBAXJBFUBYFtCgWRXGh\n7QP01962dflRfOTW+rOW9rbSu9WfWu0j9e59twhtRSmCVkQtmyJYlorKDhIgBBKW7Otk5nyfP86c\nMzPJLGeSmcwM+bxfL15Jzpw5cyYZknPN9b2uS0gpJYiIiIiIiKKMKdInQERERERE5A2DFSIiIiIi\nikoMVoiIiIiIKCoxWCEiIiIioqjEYIWIiIiIiKISgxUiIiIiIopKDFaIiCgmmUwmlJSURPo0iIgo\njBisEBFdpt577z3cdNNNsFqtSEtLw4QJE/D6669361g7d+7ErFmzkJWVheTkZFx99dV46aWXoChK\nl33PnDmDX/7yl7jnnnswdOhQmEwmmEwmHD16tKdPqQshRMiPacShQ4dw7733Ijc3F0lJSRg+fDiW\nLl2Ktra2oI6zZs0aPPLII5g8eTLS09NhMpkwb968MJ01EVHssUT6BIiIKPR+97vf4ZFHHkF2djbm\nz5+P+Ph4vPXWW1i4cCG++uor/OY3vzF8rPXr1+Puu+9GcnIy7rvvPmRlZeGdd97B4sWL8emnn+LN\nN9/02H/Pnj346U9/qmc+MjIyUF9fH+qnGDG7du3CtGnTYLfbMXfuXAwYMACbNm3CL37xC2zatAmb\nNm1CfHy8oWM988wz+PLLL5GWloaioiIcPnw4YgEYEVFUkkREdFkpLy+XCQkJMjs7W546dUrfXltb\nK4cOHSqFEHLnzp2GjlVfXy9zcnJkYmKi3Lt3r769ra1NXn/99VIIId944w2P+5w5c0Zu375dNjY2\nSimlnDp1qhRCyCNHjoTg2bkIIWRJSUlIjxmI3W6XI0aMkCaTSb777rv6dkVR5Ny5c6UQQv7qV78y\nfLwtW7bI48ePSyml3Lp1qxRCyHnz5oX8vImIYhWXgRERhZGUEi+99BJGjhyJpKQkFBUV4ZFHHkF9\nfT2Ki4vDUnPxP//zP7DZbHj44YcxcOBAfXtGRgaefPJJAMDy5csNHWvNmjW4ePEi7r//flx77bX6\n9oSEBDzzzDMAgFdffdXjPv3798cNN9yA1NTUnj4VQ1paWrBkyRIMHDgQiYmJKC0txa9//euwPNa2\nbdtw+PBhTJkyBbfffru+XQihP6bR7y0A3HjjjRgyZAgA9bVCRESeuAyMiCiMHnroISxfvhyFhYV4\n4IEHEB8fj3fffRe7du2C3W43vFwoGJs3bwYAzJw5s8ttt956KwBgy5YtPT7WlClTkJSUhJ07d6Kj\nowNxcXHdPeVus9lsuOWWW3Du3DnMmjULFosFb7/9Np544gm0tbXh6aefDunj+ft+lJSUoLS0FMeP\nH8eJEycwePDgkD42EVFfxGCFiChMPvnkEyxfvhylpaXYtWsXrFYrAODZZ5/FjBkzcPbsWRQXF3vc\np76+Hi+88EJQj3PTTTdh6tSp+tdHjhyBEALDhg3rsm9+fj6Sk5Nx5swZtLW1ITEx0e+xjxw5AgBe\nj2U2m1FSUoJDhw7hxIkTKCsrC+q8Q+Hs2bO45pprsGnTJiQkJAAAnn76aQwbNgwvvPACnnzySVgs\nrj91L774Iurq6gwfv6SkBAsWLNC/9vf9AIDS0lIcO3YMx44dY7BCRBQCDFaIiMJkxYoVAICf/OQn\neqACAHFxcVi2bBkmTZrU5T61tbX4xS9+YfgxhBAwmUwewYpWzO7+mO6sVitaW1tRX18fMFipr6+H\nEMLvsaSUQQUAoSSEwG9/+1s9UAGAnJwczJ49GytXrsTRo0cxcuRI/baXXnoJp06dMnz8G2+80SNY\nMfK9BRCx7wcR0eWGwQoRUZh8/vnnAOA1KLnuuutgNpu7bC8uLvbaDpi8s1qtXjMYAwYMAKAGf+7K\ny8t75byIiCg0WGBPRBQmWlYiLy+vy21msxn9+vULy+Nq7+77ahccKDvQ+VhSyoDHysjI6M6p9piv\nx9WWfjkcjpA+ntHvbaS+H0RElxtmVoiIwiQ9PR0AUFVVhbS0NI/bHA4HLl26hOTkZI/toahZKSsr\nw44dO3DkyBFMmDDBY99z586hpaUFAwYMCLgETDvW3r17ceTIEYwePdrjNrvdjvLycsTFxcVMfUZP\na1aGDx8OwFW70tmxY8d81gsREVHwGKwQEYXJtddei3379mH79u0oLS31uO2zzz7z+q6/VrMihDDU\nytZbzcr06dOxY8cObNy4sUuw8v777wMApk2bZug5TJ8+HX/5y1+wceNG3H///R63ffzxx2htbcXU\nqVMj0gmsO3paszJt2jT88pe/xMaNG/HEE0947HvixAkcO3YsbC2piYj6Ii4DIyIKk/nz5wMAli1b\n5vFuvs1m0+eddKbVrDgcDiiKEvCfw+Ho0p73u9/9LhISEvDKK694XJjX1tbi2WefhRACP/zhDz3u\nc+nSJRw+fBhVVVUe2+fOnYvs7Gy88cYb2Lt3r769ra0NTz31FADgRz/6kaHvh7/g609/+hNMJhNu\nuukmQ8fqrvLyckPfV+2f1qpYM3XqVIwYMQIff/wx3n33XX27oih4/PHHAaDL97a1tRWHDx/GiRMn\nwvrciIguR8ysEBGFyZQpU/DAAw/gtddew6hRo3DXXXchISEB77zzDjIzM1FYWAiTKfTvGRUXF+O5\n557DI488grFjx+K+++5DXFwc1qxZg8rKSjz22GO47rrrPO7z8ssv4xe/+AUWLFiAP/7xj/r2tLQ0\n/OEPf8Ddd9+NG2+8Effffz8yMzPxzjvv4OjRo7jnnntw7733djmHhQsX6p8fPnwYgNoVTVsaN2fO\nHNxxxx36PlpTgXDMnQklk8mEP/7xj5g2bRrmzp2LuXPnYsCAAdi0aRP27t2LSZMmYfHixR73+ec/\n/4lp06Zh0KBBXQr8161bh3Xr1gGAHih+9tln+vdPCOHx8yAi6nP8jbd/9tln5dixY2V6errMycmR\n3/zmN+X+/fu77HfkyBE5Z84cmZGRIZOTk+W1114rDx065O/QcuvWrfLaa6+ViYmJcvDgwXL58uV+\n9yciikWKosgXXnhBDh8+XCYkJMj+/fvLhx9+WNbX18vU1FQ5evTosD32e++9J6dOnSrT0tJkamqq\nHD9+vHz99de97rt06VJpMpnkd7/7Xa+379y5U952220yMzNTJiUlyauuukq++OKLUlEUr/sLIaTJ\nZNI/av+0r3/+85977L9o0SIphJCrVq0y/PyEELKkpMTv89m2bZvh4wXj4MGD8t5775U5OTkyISFB\nlpWVyaVLl8q2trYu+27dutXnuS5durTL96jz94qIqC8TUvrOy8+cORPz5s3DuHHjoCgKnn76aezc\nuRMHDx5EZmYmADWlPn78eCxcuBDf/va3kZGRgcOHD2PUqFEoKiryetzy8nKMGjUK3//+9/Hggw/i\nk08+wYMPPog33ngDd911V3iiMiKiKHLs2DGUlZVh3rx5+POf/xzp04m4a665BjabDQcOHIAQItKn\nQ0REUcJvsNJZc3MzrFYr1q9fj1mzZgEAvvWtb8FsNmPlypWGH/Txxx/HunXrPLqp/Nu//RsOHDiA\nHTt2BHH6RETR7fz588jOzvZY7tXS0oJ77rkH77//Pt58803MnTs3gmcYeTU1NcjJycFf/vIX3Hff\nfZE+HSIiiiJBLZZuaGiAoih6VkVRFPz973/HiBEjMHPmTOTm5mL8+PF48803/R5n586duOWWWzy2\n3XLLLdizZ0/Ie+ITEUXSb3/7W5SUlGDhwoV44oknsHDhQpSVleH999/Hbbfd1ucDFQDIysqCw+Fg\noEJERF0EVWC/aNEijB49GhMnTgSgvmPY1NSEZ599Fs888wx+/etfY9OmTfj2t7+N1NRU3HbbbV6P\nU11d3WVIWl5eHux2Oy5evKjf5mvoFhFRrJgwYQJ2796NDz74ALW1tYiLi8OQIUPwgx/8AA8++CB/\nzxER0WXLyPDhQAwHK48++ih27NiB7du36+uJte4td955J3784x8DAK666irs2bMHr7zyis9ghYio\nr5g8eTImT54c6dMgIiKKSYaWgS1evBirV6/G5s2bUVxcrG/Pzs6GxWLByJEjPfYfPnw4Tp8+7fN4\n+fn5XXr5V1dXw2KxIDs7O4jTJyIiIiKiy1XAzMqiRYvw1ltvYcuWLRg2bJjHbfHx8Rg3bpzeQ19z\n9OhRj6Cms4kTJ+Ltt9/22PbRRx9h3LhxMJvNXu8TijQSkbs9e/Zg7NixkT4NuszwdUXhwNcVhQtf\nWxRqoV7e7DdYeeihh7Bq1SqsW7cOVqtVz4akpaUhJSUFAPDv//7vuPfeezF58mTcdNNN2LJlC1av\nXo3169frx5k/fz6EEFixYgUAdbrvK6+8gsWLF+OBBx7Ap59+ihUrVuCNN94I6ZMjIiIiIqLY5XcZ\n2KuvvoqmpiZMnz4dhYWF+r/nn39e3+eOO+7Aa6+9hueeew5XXXUVfve732HlypW49dZb9X0qKipQ\nUVGhf11cXIwNGzbg448/xujRo7Fs2TK8/PLLmDNnThieIhERERERxSK/mRWtgD6QBQsWYMGCBT5v\n37JlS5dtU6ZMwd69ew0dn4iIiIiI+p6g5qwQERERERH1FgYrREREREQUlRisEBERERFRVGKwQkRE\nREREUYnBChERERERRSUGK0REREREFJUYrBARERERUVRisEJERERERFGJwQoREREREUUlBitERERE\nRBSVGKwQEREREVFUYrBCRERERERRicEKERERERFFJQYrREREREQUlRisEBERERFRVGKwQkLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d064c5c88>"
+        "<matplotlib.figure.Figure at 0x7f1295e83400>"
        ]
       }
      ],
@@ -1892,9 +1892,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGaCAYAAACBhJXZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d04b2b470>"
+        "<matplotlib.figure.Figure at 0x7f1295cccac8>"
        ]
       }
      ],
@@ -1921,9 +1921,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGaCAYAAAAPXtylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f6d066342b0>"
+        "<matplotlib.figure.Figure at 0x7f1295ccdc50>"
        ]
       }
      ],

05_Kalman_Filters/Kalman_Filters.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:44f0c7d31117a0f475fc5fa3ccc569d793496bbb0fcf21b5d742f997d42e78f3"
+  "signature": "sha256:2ead90ce1b4a67e39b677b6425cac07822bea68fe52acd7383dfb277392ba6ec"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -259,7 +259,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7fd828471ba8>"
+        "<IPython.core.display.HTML at 0x7f29a9f40780>"
        ]
       }
      ],
@@ -353,10 +353,10 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        " 0.0873\t-0.9021\t-0.9935\t-0.5323\t 1.0992\t\n",
-        "-0.5785\t 0.2325\t 0.0777\t 1.7463\t-0.2352\t\n",
-        " 0.2466\t-0.1751\t 1.5194\t 1.4882\t-0.0404\t\n",
-        " 0.9118\t 0.0419\t 0.5892\t-0.1217\t-0.1987\t\n"
+        " 0.5332\t-0.6438\t 1.0778\t-1.5408\t 0.7009\t\n",
+        "-0.1204\t-1.4358\t 1.0115\t-0.6912\t 0.5493\t\n",
+        " 0.7769\t 0.9842\t 0.8198\t 1.0959\t 0.7743\t\n",
+        "-1.2463\t 1.3107\t-0.8946\t 0.0512\t-1.9209\t\n"
        ]
       }
      ],
@@ -403,7 +403,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxQAAAGNCAYAAACIdTczAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bfb87f0>"
+        "<matplotlib.figure.Figure at 0x7f298d0a8ac8>"
        ]
       }
      ],
@@ -447,9 +447,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAz0AAAGxCAYAAABIhdj/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAz0AAAGxCAYAAABIhdj/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bd002e8>"
+        "<matplotlib.figure.Figure at 0x7f298d05aa58>"
        ]
       }
      ],
@@ -481,9 +481,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAz0AAAGxCAYAAABIhdj/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAz0AAAGxCAYAAABIhdj/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bfb8320>"
+        "<matplotlib.figure.Figure at 0x7f298d0a84a8>"
        ]
       }
      ],
@@ -501,9 +501,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAz0AAAGxCAYAAABIhdj/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd0FdXexvHvnLSTHhJIoYXQpEhHehFEQSmicFFRJOKV\njiAqCiig9KpIEQsqRYWr96UoSFE6iBC6dKkCSYCQRnpy5v0jkksEBDThpDyftbJWMrNn5pdkOJwn\ne/behmmaJiIiIiIiIgWUxd4FiIiIiIiI5CaFHhERERERKdAUekREREREpEBT6BERERERkQJNoUdE\nRERERAo0hR4RERERESnQFHpEROS2Ro0ahcViYePGjfYuRURE5K4p9IiIyG0ZhpH1ITln/vz51K9f\nH09PT3x8fGjRogUrVqy4q3Ns2LABi8Vyy4+hQ4fmUvUiIvmHocVJRUTkdqKiooiKiqJUqVK4urra\nu5wC4fXXX2fq1KmUKlWKzp07k5KSwqJFi7hy5QozZsygX79+d3SeDRs20LJlS2rWrEnHjh1v2N+k\nSRNatmyZ0+WLiOQrCj0iIiL32LZt22jSpAnly5dn586deHt7A3DmzBnq1KlDQkICR44cITg4+Lbn\nuhZ6QkND+eyzz3K7dBGRfEmPt4mI5GHbt2/HYrHQoUOHW7apW7cuDg4OnDlzBoC0tDRmzpzJY489\nRnBwMFarFV9fX1q1anXLR6fKlCmDxWIhNTWVUaNGUaFCBVxcXHjllVeA/43p2bRpU7bjli5dynPP\nPUfFihXx8PDAw8ODOnXqMH36dGw22w3XCQ0NzRob9O2331KvXj3c3d3x8/PjmWee4cKFCzetLzo6\nmrfffptq1arh4eGBt7c31apV4/XXXycmJiZb29jYWEaMGMH999+Pu7s7Xl5eNG3alG+//fbWP+h7\nbM6cOQAMHz48K/AABAcH069fP1JSUvj888/tVZ6ISIHjaO8CRETk1ho0aEClSpVYtWoVly5dolix\nYtn2Hzx4kN27d/Pggw9m9QpERUUxaNAgGjduTOvWrSlWrBgXLlzgu+++o3379syZM4eePXve9HpP\nPvkke/bs4dFHH6Vo0aKEhIT8ZX1Dhw7FwcGBhg0bUqJECWJjY/npp5945ZVX2LFjB19++eVNj5s9\nezbLly/n8ccfp0WLFmzfvp3Fixezb98+9u7di7Ozc1bbU6dO0aJFC86ePUvt2rXp3bs3AMeOHWP2\n7Nl069YNHx8fAM6fP0+LFi347bffaNasGa1bt+bq1ausWLGCLl26MHLkSEaOHHlnP/xctG7dOgzD\noE2bNjfse/TRRxk9ejTr169n1KhRd3zO8+fPM2fOHK5cuUKxYsVo2rQplSpVysGqRUTyL4UeEZE8\nLjQ0lDfffJMvv/ySQYMGZds3b968rDbX+Pr6cvbsWYoXL56tbVxcHI0bN2bo0KE8//zzWK3WG651\n7tw5Dhw4gK+v7x3VtnLlyhuCkWmavPDCC8yfP5+XX36Z+vXr33Dc6tWrCQsLo2rVqlnbnn32Wb7+\n+muWLVvGv/71r2zbz549y+jRoxk+fPgN35ODg0PW1927d+fkyZN8/fXXPPXUU1nb4+PjefDBB3n3\n3Xd54oknqF69+m2/t6VLl7J3797b/xD+YBjGHQWqhIQELly4gKenJwEBATfsL1++PJAZ6u7G2rVr\nWbt2bbZt7du357PPPsPPz++uziUiUuCYIiKSp124cMF0dHQ0a9asmW17enq6GRQUZHp6epoJCQl3\ndK6pU6eahmGYmzZtyrY9ODjYNAzDXL58+U2PGzlypGkYhrlx48Y7us6uXbtMwzDM0aNHZ9vevXt3\n0zAM8+23377hmPXr15uGYZivv/561rawsDDTMAyzRo0at73m/v37TcMwzE6dOt10//Lly03DMMwh\nQ4bc0fcQGhpqGoZxxx8Wi+WOznv+/HnTMAyzVKlSN92fmppqGoZhWq3WOzrfwYMHzUmTJpkHDx40\nExISzKioKHPVqlVm7dq1TcMwzAYNGpg2m+2OziUiUlCpp0dEJI8LCgri4YcfZtWqVezbt48aNWoA\nsGbNGiIiIggNDcXNzS3bMQcPHmTy5Mls2rSJiIgIkpOTs+2/2dgZwzCoV6/eXdUWFRXF5MmTWbly\nJSdPniQxMTHb/vPnz9/0uLp1696wrWTJkkDm+J1rtm/fDsAjjzxy21q2bt0KZI7pudljYZcuXQLg\n8OHDtz0XwOeff54vxtVUqVKFKlWqZH3t5uZG69atadSoETVr1uSXX35h2bJlN53ZTUSksFDoERHJ\nB1544QVWrVrFvHnzmDZtGnDzR9sgMyi0bNkSm83GQw89RMeOHfHy8sJisbBnzx6WLVtGSkrKTa9z\ns8etbiUmJoYHHniA06dPU79+fUJDQ/H19cXR0ZHo6GimT59+y+tcG4NzPUfHzP+SMjIysl0DoESJ\nEretJyoqCoCffvqJn3766aZtDMMgISHhtufKTdcmLoiNjb3p/mvbb/Yzuhuenp507dqVsWPHsnXr\nVoUeESnUFHpERPKBxx9/nCJFivDVV18xZcoU4uLiWLZsGWXLlqVZs2bZ2o4ZM4bk5GQ2bNhww77x\n48ezbNmyHKnp008/5fTp04waNYoRI0Zk2/fzzz8zffr0f3yNa2/8z507d9u218LEtGnTbhj79Hfk\n1pged3d3ihcvTnh4OBEREQQGBmbbf/z4cQAqVqx4dwXfRNGiRQHsHvREROxNoUdEJB9wdnbm6aef\n5sMPP2TFihVcuHCBlJQUnn/++Rva/vbbb/j5+d0QeAA2btyYYzX99ttvAHTq1CnXrtOwYUMg81G+\nSZMmYRjGLds2atQIgE2bNuVI6Fm2bFlWb9qduNPQA/DQQw+xYMECVq1adUNP3Q8//ACQIwuKXns8\nsGzZsv/4XCIi+ZnW6RERySdeeOEFIPOxtnnz5mGxWOjevfsN7UJCQoiKiuLAgQPZts+dO5c1a9bk\nWD3XZm1bv359tu179uxh/PjxOXKN2rVr06hRIw4cOMDYsWNv2B8bG5vVi1G7dm2aN2/OsmXL+PTT\nT296vmPHjvH777/f0bU///xzbDbbHX9c/1je7Vybdnvs2LHZ1hk6ffo0s2bNwmq1Zv2+r4mIiODI\nkSNZj/FdExYWdtNrLFy4kMWLF+Pi4kKXLl3uuDYRkYJIPT0iIvlE3bp1qVq1KsuXLyc9PT3b2jzX\nGzRoEKtXr6ZJkyZ06dIFLy8vwsLC2Lp1K507d86xRTqff/55Jk+ezKBBg1i/fj3ly5fn+PHjrFix\ngk6dOrFo0aIcuc7ChQt58MEHGTFiBEuXLuXBBx8E4MSJE6xZs4aff/45awrqr776ioceeoiePXsy\nY8YM6tevj6+vL+fPn+fgwYPs3buXpUuXUqpUqRyp7e9q2LAhr776KlOnTqV69ep06tSJ1NRUFi9e\nTExMDDNmzKB06dLZjnnzzTeZP3/+DWsNde7cGScnJ+rUqUPJkiVJTk5m586d7Ny5EycnJz766KMb\nziUiUtjYradn06ZNdOjQgZIlS2KxWG76CMGoUaMoUaIEbm5utGjRgkOHDmXbn5KSwoABAyhWrBge\nHh48/vjjt5wpSESkIAgNDSU9PR3DMG54LOqa1q1b891331GlShUWL17M559/jqurKxs2bKBt27Y3\nfUTsrx4bu7b/z22CgoLYvHkzbdu2ZcuWLcyaNYvff/+dDz/88JY9PTc7z+2UKVOG3bt38+abb5KQ\nkMCsWbOYO3cuJ0+eZMCAAdmCX1BQEGFhYUyYMAEXFxcWLVrE9OnT2bp1K/7+/syYMeOmj/3Zw+TJ\nk5k3bx5BQUF88sknLFy4kGrVqvHdd9/Rt2/fG9pf+9n9+efXt29fQkJC2LZtG7Nnz+azzz7jypUr\nvPDCC4SFhd30EUgRkcLGME3TtMeFf/jhB7Zu3UqtWrV4/vnn+fDDD7O9ME+cOJGxY8cyb948Klas\nyLvvvsuWLVs4evQoHh4eAPTp04fly5czf/58fH19GTx4MDExMezatQuLRU/uiYiIiIiIHUPP9Tw9\nPZk1a1ZW6DFNk+LFi/Pyyy8zdOhQAJKTk/H392fKlCn07NmT2NhY/P39+eKLL3jmmWeAzNl9goOD\n+eGHH+5oTQcRERERESn48mR3yKlTp4iMjMwWXKxWK82aNWPbtm0A7Nq1i7S0tGxtSpYsSeXKlbPa\niIiIiIiI5MmJDCIiIoAbF8nz9/fPWkU8IiICBwcH/Pz8srUJCAggMjIy27ZbLQAnIiIiIiJ527V1\n2P6JPNnT81fudgCsiIiIiIgUbnky9FxbnfrPPTaRkZFZ+wIDA8nIyLhhvYKbrW4tIiIiIiKFV558\nvC0kJITAwEDWrFlDnTp1gMyJDLZs2cKUKVMAqFOnDk5OTqxZsybbRAZHjhzJWpX7ZnKie0zkemFh\nYdStW9feZUgBo/tKcoPuK8kturckNcPG7/FpnI5L43RsKmfiUok/eYYWi+fwyNpFWFOTAdhRuQEf\ndHmVg+VqMLReMbrc53PT8+X08BS7hZ6EhASOHz8OgM1m48yZM+zduxc/Pz9KlSrFoEGDGDduHJUq\nVaJChQqMGTMGT09PunbtCmSGlxdffJEhQ4bg7++fNWV1jRo1aNWqlb2+LRERERGRAi82JYPVp+PZ\ncj6B03FpnL+ahu1Pc0I/s+Z7Oqz4AoCNtVryWbteHKtUGzcnCyUdLbg43LthK3YLPTt37qRly5ZA\n5jidaytMh4aG8tlnnzFkyBCSkpLo168f0dHRNGjQgDVr1uDu7p51jvfffx9HR0eeeuopkpKSaNWq\nFQsXLtS4HxERERGRHJZuM/n5QiLLT8Sx8VwCadelHIsBpTydCPZyItjLmTJezpRtPJB4ywLine truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAz0AAAGxCAYAAABIhdj/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bc44048>"
+        "<matplotlib.figure.Figure at 0x7f298cfcaeb8>"
        ]
       }
      ],
@@ -539,7 +539,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAx8AAAGNCAYAAABwlczEAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bbbb550>"
+        "<matplotlib.figure.Figure at 0x7f298cf08e80>"
        ]
       }
      ],
@@ -576,9 +576,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGNCAYAAACfV6f6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGNCAYAAACfV6f6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bfb83c8>"
+        "<matplotlib.figure.Figure at 0x7f298d0a8ba8>"
        ]
       }
      ],
@@ -681,7 +681,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAycAAAGNCAYAAAALsQ4IAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd808273a20>"
+        "<matplotlib.figure.Figure at 0x7f29841508d0>"
        ]
       }
      ],
@@ -727,9 +727,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAycAAAGNCAYAAAALsQ4IAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAycAAAGNCAYAAAALsQ4IAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd8zXf///HH55yMEyQhItOIFYQWTVC79v6q1mzRqlpX\ndbmuS0t79dehqC5tXaqbi1ItiqqRaG1aYpTS2KtIiBFk55zP749U2tQKkpyM5/12c7vlvM/7836/\nPvmEnJf3MkzTNBEREREREXEyi7MDEBERERERASUnIiIiIiJSQCg5ERERERGRAkHJiYiIiIiIFAhK\nTkREREREpEBQciIiIiIiIgWCkhMRERERESkQcpScTJ06lcqVK+Ph4UFERATr16+/bt09e/bQqlUr\nAgIC8PDwoGrVqrzwwgukp6dnq7dmzRrCw8Oz6nz00Ud3diciIiIiIlKo3TQ5mTt3Ls888wwvvvgi\nO3bsoEmTJnTq1Injx49fs767uzuDBg0iKiqKffv2MXnyZD777DPGjh2bVefw4cN07tyZZs2asWPH\nDsaMGcOTTz7JggULcu/ORERERESkUDFudkJ8o0aNqFevXraRjdDQUHr27Mn48eNz1MmoUaP46aef\n2LhxIwDPPfccCxcuZO/evVl1hgwZwu7du7PqiIiIiIhI8XLDkZO0tDS2bdtG+/bts5W3b98+x0nE\ngQMHWLFiRbY2Nm3adM02o6OjsdvtOY1dRERERESKEJcbvRkfH4/dbsff3z9buZ+fH7GxsTdsuEmT\nJmzfvp3U1FQeffRRXn755az34uLirmrT39+fjIwM4uPjs95LSEi4lXsREREREZECwtvb+5avybPd\nur7++mu2b9/O7NmziYqKYvTo0XnVlYiIiIiIFAE3HDnx9fXFarUSFxeXrTwuLo7AwMAbNly+fHkA\natasid1u57HHHmPChAlYrVYCAgKuGnmJi4vDxcUFX1/f27kPEREREREp5G6YnLi5uREeHk5kZCQP\nPvhgVnlUVBS9evXKcSd2ux2Hw4HD4cBqtdK4cWO+/fbbbHWioqJo0KABVqv1mm3czrCQ5L/o6Ggi\nIiKcHYbkgJ5V4aLnVXjoWRUeelaFi55X4XCnyzJumJxA5k5bAwYMoGHDhjRp0oRp06YRGxvL8OHD\nARgzZgxbtmxh5cqVAMycORMPDw/q1KmDm5sb0dHRjB07lj59+uDq6grA8OHDmTJlCs8++yxDhw5l\nw4YNzJgxg6+++uqObkZERERERAqvmyYnvXv35uzZs4wbN45Tp05x1113sXTpUipUqABAbGwshw4d\nyqrv6urKhAkT2L9/P6ZpUqlSJUaOHMmzzz6bVSckJISlS5fy7LPP8uGHHxIcHMwHH3xAjx498uAW\nRURERESkMLhpcgIwYsQIRowYcc33vvjii2yv+/btS9++fW/aZosWLdi6dWtOuhcRERERkWIgz3br\nEhERERERuRVKTkREREREpEBQciIiIiIiIgVCjtaciIiIiEjh5nA4SEtLc3YYt61SpUqkpKQ4O4xi\nzTAM3NzcMAwjz/pQciIiIiJSxDkcDlJTU7HZbHn6wTIv2Ww2Z4dQ7NntdlJSUnB3d8diyZsJWJrW\nJSIiIlLEpaWlFerERAoGq9WKzWbL0xE4JSciIiIixYASE8kNef1zpOREREREREQKBCUnIiIiIiJS\nICg5ERERERGRAkHJiYiIiIiIFAhKTkREREREiqFp06bRp08fKleujMVioVOnTs4OSeeciIiIiIgU\nR2+88QYXL16kQYMGnD17tkDs6KbkRERERESkEElMTKRkyZJ33M7atWupUKECACEhIXfcXm7QtC4R\nERERKbRefvllLBYLMTEx9O/fn9KlS1OuXDleeOEFAI4fP0737t3x9vYmICCAt95666o2UlNTeeWV\nV6hevTo2m43y5cszatQokpOTs9WbPn06bdu2JTAwEJvNRmhoKBMnTsQ0zWz1Dhw4QO/evQkKCsJm\nsxEcHEzPnj2JjY0F4MiRI1gsFmbMmHFVLBaLhVdeeeWq+9u9ezcDBgzAx8eHu+66K+v9yMhIWrZs\niaenJ56ennTq1IlffvklR9+7K4lJQaKRExEREREp9Pr160etWrV44403+P7775kwYQLe3t58+umn\ntG3blkmTJjFr1ixGjx5NeHg4rVq1AsA0TXr06MHatWsZOnQoYWFh7Nmzh6lTp7J7925WrFiR1cfU\nqVMJCwuja9eu2Gw2Vq5cydixY0lISGDChAkApKen06FDB1JTUxk5ciSBgYGcPHmSFStWcOrUKQIC\nArLau940qmuV9+nThypVqjB+/PisE9pnz57NgAEDaN++PRMnTiQlJYWPP/6Y5s2bs2XLFmrUqJFr\n39/8ouRERERERLKpP3N/nrW9fUD1PGk3IiKCTz75BIAhQ4YQEhLC888/z+uvv86YMWMA6Nu3L0FB\nQXz++edZycmcOXNYsWIFq1evpnnz5tna69+/P1FRUbRr1w7InAZls9my6gwfPpxhw4YxZcoUXn31\nVVxdXdmzZw+HDx9m3rx5PPDAA1l1r4zk3K5atWrxzTffZL1OTExk5MiRDBo0iE8//TSrfPDgwdSo\nUYNXX32VL7/88o76dAZN6xIRERGRQu/xxx/P+tpisRAeHo5hGAwePDir3Nvbmxo1anD48OGssq+/\n/prQ0FDCwsKIj4/P+tOiRQsMw2DVqlVZda8kJna7nfPnz2fVS0xMJCYmBgAvLy8Ali9fTlJSUq7d\n34gRI7K9joqK4sKFC/Tr1y9b3BkZGTRr1ixb3IWJRk5EREREJJu8Gt3ISxUrVsz22tvbG1dXV/z8\n/LKVe3l5cebMmazX+/btY+/evZQrV+6qNg3DyFZ3/fr1jB07ls2bN2dNrboiISEBgMqVKzNq1Cje\neecdZs2aRdOmTenWrRv9+/fHx8fntu+vatWq2V7v27cPIGtU5++sVutt9+VMSk5EREREpNC71ofx\n663p+OsCdofDQe3atXnvvfeuWTcoKAiAQ4cO0bZtW2rWrMnkyZOpWLEiNpuNrVu38txzz+FwOLKu\neeutt3jsscdYvHgxkZGR/POf/2TcuHGsWbOGWrVqXTcuu91+3fvz8PDI9vpKfzNmzCA4OPi61xU2\nSk5EREREpNiqVq0aW7dupXXr1jest3jxYtLS0vjuu++y7XJ18ODBa9YPCwsjLCyM559/nl27dhEe\nHs67777Lxx9/TJkyZQC4cOFCtmuOHj16S3ED+Pr63jT2wkRrTkRERESkSMrJoYJ9+vQhLi6ODz/8\n8Kr3UlNTuXz5MvDnyMxfR0hSU1OZMmVKtmsuXbpERkZGtrKaNWtis9mypn55eXnh6+vLmjVrstWb\nOnVqDu4qU4cOHShdujTjx48nPT39qvfj4+Nz3FZBopETERERESmS/n7+yLXK+/fvz7x583jiiSdY\ns2YNTZs2xTRN9u7dyzfffMO8efNo0aIFHTt2xM3Nja5duzJs2DBSUlKYOXPmVdPJfvjhB5544gl6\n9epFaGgopmkyd+5cEhMT6dOnT1a9xx9/nIkTJzJkyBDCw8NZu3Yt+/fnfJc0T09Ppk2bxsMPP0z9\n+vXp168ffn5+HDt2jOXLl1OnTh2++OKLG7bx3XffZZ2JkpCQwMGDBxk3bhwA3bt3z3aeSn5RciIi\nIiIihZZhGNccIclpuWEYLFiwgMmTJzNjxgwWLVqEh4cHVatW5Yknnsj6gF69enUWLlzI2LFjGT16\nNOXKlWPgwIG0bNmSDh06ZLVXr149OnfuzNKlS/nkk0+w2WzUqVOHhQsX0q1bt6x6L730EmfOnGHe\nvHl8/fXXdO7cmWXLll21gP969wFkHfQ4fvx43n77bVJSUggODqZp06YMHz78pt+7BQsWZB0EaRgG\nFy9e5KWXXsIwDCpWrOiU5MQwr5dSFgBXhr4gc8cFKfiio6OJiIhwdhiSA3pWhYueV+GhZ1V4FKdn\nlZKSku18DpE7caOfpzv9/K41JyIiIiIiUiAoORERERERkQJByYmIiIiIiBQISk5ERERERKRAUHIi\nIiIiIiIFgpITEREREREpEJSciIiIiIhIgaDkRERERERECgQlJyIiIiIiUiAoORERERERkQJByYmI\niIiIiBQISk5ERERERKRAUHIiIiIiIiIFgpITEREREZFi5vjx47zyyis0bNgQHx8fypUrR6tWrfjh\nhx+cGpeSExERERGRYmbRokVMmjSJ0NBQXn/9df7zn/9w6dIl2rVrxxdffOG0uFyc1rOIiIiIiNyy\nxMRESpYseUdttG7dmuPHj+Pj45NVNnz4cOrVq8eLL77IoEGD7jTM26KRExEREREptF5++WUsFgsx\nMTH079+f0qVLU65cOV544QUgc/pS9+7d8fb2JiAggLfeeuuqNlJTU3nllVeoXr06NpuN8uXLM2rU\nKJKTk7PVmz59Om3btiUwMBCbzUZoaCgTJ07ENM1s9Q4cOEDv3r0JCgrCZrMRHBxMz549iY2NBeDI\nkSNYLBZmzJhxVSwWi4VXXnnlqvvbvXs3AwYMwMfHh7vuuivr/cjISFq2bImnpyeenp506tSJX375\n5abft7CwsGyJCYCbmxudOnXi1KlTJCQk3LSNvKCRExEREREp9Pr160etWrV44403+P7775kwYQLe\n3t58+umntG3blkmTJjFr1ixGjx5NeHg4rVq1AsA0TXr06MHatWsZOnQoYWFh7Nmzh6lTp7J7925W\nrFiR1cfUqVMJCwuja9eu2Gw2Vq5cydixY0lISGDChAkApKen06FDB1JTUxk5ciSBgYGcPHmSFStW\ncOrUKQICArLaMwzjmvdyrfI+ffpQpUoVxo8fT1paGgCzZ89mwIABtG/fnokTJ5KSksLHH3Line truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bbc9d68>"
+        "<matplotlib.figure.Figure at 0x7f29840a30b8>"
        ]
       }
      ],
@@ -777,9 +777,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAycAAAGNCAYAAAALsQ4IAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAycAAAGNCAYAAAALsQ4IAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd8080bfa90>"
+        "<matplotlib.figure.Figure at 0x7f297bf1c748>"
        ]
       }
      ],
@@ -895,26 +895,26 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "time: 0 \tposition = 1.485 \tvariance = 2.500\n",
-        "time: 1 \tposition = 0.922 \tvariance = 1.667\n",
-        "time: 2 \tposition = 0.676 \tvariance = 1.250\n",
-        "time: 3 \tposition = 0.483 \tvariance = 1.000\n",
-        "time: 4 \tposition = 0.271 \tvariance = 0.833\n",
-        "time: 5 \tposition = 0.254 \tvariance = 0.714\n",
-        "time: 6 \tposition = 0.027 \tvariance = 0.625\n",
-        "time: 7 \tposition = 0.107 \tvariance = 0.556\n",
-        "time: 8 \tposition = 0.183 \tvariance = 0.500\n",
-        "time: 9 \tposition = 0.083 \tvariance = 0.455\n",
-        "time: 10 \tposition = 0.026 \tvariance = 0.417\n",
-        "time: 11 \tposition = 0.049 \tvariance = 0.385\n",
-        "time: 12 \tposition = 0.021 \tvariance = 0.357\n",
-        "time: 13 \tposition = 0.008 \tvariance = 0.333\n",
-        "time: 14 \tposition = -0.056 \tvariance = 0.312\n",
-        "time: 15 \tposition = 0.003 \tvariance = 0.294\n",
-        "time: 16 \tposition = -0.039 \tvariance = 0.278\n",
-        "time: 17 \tposition = -0.005 \tvariance = 0.263\n",
-        "time: 18 \tposition = 0.113 \tvariance = 0.250\n",
-        "time: 19 \tposition = 0.100 \tvariance = 0.238\n"
+        "time: 0 \tposition = 1.071 \tvariance = 2.500\n",
+        "time: 1 \tposition = 1.317 \tvariance = 1.667\n",
+        "time: 2 \tposition = 0.980 \tvariance = 1.250\n",
+        "time: 3 \tposition = 1.014 \tvariance = 1.000\n",
+        "time: 4 \tposition = 0.917 \tvariance = 0.833\n",
+        "time: 5 \tposition = 0.967 \tvariance = 0.714\n",
+        "time: 6 \tposition = 0.887 \tvariance = 0.625\n",
+        "time: 7 \tposition = 0.866 \tvariance = 0.556\n",
+        "time: 8 \tposition = 0.791 \tvariance = 0.500\n",
+        "time: 9 \tposition = 0.737 \tvariance = 0.455\n",
+        "time: 10 \tposition = 0.544 \tvariance = 0.417\n",
+        "time: 11 \tposition = 0.555 \tvariance = 0.385\n",
+        "time: 12 \tposition = 0.512 \tvariance = 0.357\n",
+        "time: 13 \tposition = 0.473 \tvariance = 0.333\n",
+        "time: 14 \tposition = 0.467 \tvariance = 0.312\n",
+        "time: 15 \tposition = 0.428 \tvariance = 0.294\n",
+        "time: 16 \tposition = 0.343 \tvariance = 0.278\n",
+        "time: 17 \tposition = 0.286 \tvariance = 0.263\n",
+        "time: 18 \tposition = 0.242 \tvariance = 0.250\n",
+        "time: 19 \tposition = 0.242 \tvariance = 0.238\n"
        ]
       }
      ],
@@ -1034,24 +1034,24 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "PREDICT:     1.0000   502.0000\tUPDATE:     1.1885     9.8047\n",
-        "PREDICT:     2.1885    11.8047\tUPDATE:     3.6759     5.4138\n",
-        "PREDICT:     4.6759     7.4138\tUPDATE:     4.7428     4.2574\n",
-        "PREDICT:     5.7428     6.2574\tUPDATE:     4.9930     3.8490\n",
-        "PREDICT:     5.9930     5.8490\tUPDATE:     4.6504     3.6904\n",
-        "PREDICT:     5.6504     5.6904\tUPDATE:     6.6897     3.6267\n",
-        "PREDICT:     7.6897     5.6267\tUPDATE:     8.8587     3.6007\n",
-        "PREDICT:     9.8587     5.6007\tUPDATE:     6.5856     3.5900\n",
-        "PREDICT:     7.5856     5.5900\tUPDATE:     8.5575     3.5856\n",
-        "PREDICT:     9.5575     5.5856\tUPDATE:    10.1568     3.5838\n"
+        "PREDICT:     1.0000   502.0000\tUPDATE:     5.9904     9.8047\n",
+        "PREDICT:     6.9904    11.8047\tUPDATE:     2.7834     5.4138\n",
+        "PREDICT:     3.7834     7.4138\tUPDATE:     4.0761     4.2574\n",
+        "PREDICT:     5.0761     6.2574\tUPDATE:     5.6457     3.8490\n",
+        "PREDICT:     6.6457     5.8490\tUPDATE:     4.4591     3.6904\n",
+        "PREDICT:     5.4591     5.6904\tUPDATE:     7.7529     3.6267\n",
+        "PREDICT:     8.7529     5.6267\tUPDATE:     9.4817     3.6007\n",
+        "PREDICT:    10.4817     5.6007\tUPDATE:     9.3966     3.5900\n",
+        "PREDICT:    10.3966     5.5900\tUPDATE:    10.0462     3.5856\n",
+        "PREDICT:    11.0462     5.5856\tUPDATE:    13.3613     3.5838\n"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxQAAAGNCAYAAACIdTczAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxcAAAGNCAYAAABjQowwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd8080e2e48>"
+        "<matplotlib.figure.Figure at 0x7f297bed0128>"
        ]
       }
      ],
@@ -1186,9 +1186,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGNCAYAAADghrULAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxoAAAGNCAYAAACWvAeAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmcjXX/x/HX98xgDGOsYxj7OkiyhkQUSlosEakopChS\nuYuyJVGSSlKU3FkiSlFZ6rbmZ5nshGSNDBVjhpnBnO/vj4thGMxwZs6Zmffz8TiP68z3uq7v9blO\nl/s+n/PdjLXWIiIiIiIi4kEubwcgIiIiIiKZjxINERERERHxOCUaIiIiIiLicUo0RERERETE45Ro\niIiIiIiIxynREBERERERj1OiISIiIiIiHnfNRGPw4MG4XK4kr6JFi152TFhYGIGBgTRu3Jht27al\nWcAiIiIiIuL7UtSiER4ezuHDhxNfmzdvTtw3cuRIRo8ezdixY1m7di0hISE0bdqUmJiYNAtaRERE\nRER8W4oSDT8/P0JCQhJfBQoUAMBay5gxY3jllVdo1aoVVapUYfLkyURHRzNt2rQ0DVxERERERHxX\nihKN3bt3ExYWRpkyZejQoQN79uwBYM+ePURGRtKsWbPEYwMCAmjYsCErV65Mm4hFRERERMTn+V/r\ngLp16zJ58mTCw8OJjIxk2LBh1K9fn61bt3L48GEAChcunOSckJAQDh06lKQsKirKg2GLiIiIiEh6\nCQ4OTvU510w07r777sT3N910E/Xq1aN06dJMnjyZW2+99YrnGWNSHYyIiIiIiGQOqZ7eNjAwkCpV\nqrBr1y6KFCkCQGRkZJJjIiMjCQ0N9UyEIiIiIiKS4VyzReNScXFx/PbbbzRp0oTSpUsTGhrKwoUL\nqVmzZuL+FStWMGrUqCvWcT1NLyJXExERQa1atbwdhmQyeq4kLei5krSiZ0s87UaHPlyzRePFF19k\n2bJl7Nmzh9WrV9O2bVtiY2N5/PHHAejTpw8jR47km2++YcuWLXTu3JmgoCA6dux4Q4GJiIiIiEjG\ndc0WjYMHD9KhQwf+/vtvChUqRL169Vi1ahXFixcHoF+/fsTGxtKzZ0+OHTtG3bp1WbhwIbly5Urz\n4EVERERExDddM9GYPn36NSsZNGgQgwYN8khAIiIiIiLiIdaClyZpSvVgcBERERERyQC++QaaN4fY\nWK9cXomGiIiIiEhm8/nn0LYtLFoEU6Z4JYRUzzolIiIiIiI+7JdfoEsXAOyrAzBdu3olDJ9MNNxu\nN6dPn/Z2GJKBlCxZkri4OK9c2xhD9uzZtUiliIiI+Ib69bE9umM5hv1nC67T8ZgcAekehs8lGm63\nm/j4eAICAvTFTVIsICD9//Gcl5CQQFxcHDly5MDlUm9EERER8S776wrcp/fCP0fAPxts3wjVbk33\nOHwu0Th9+rSSDMlQ/Pz8CAgISEyQRURERLzBRkdhP30bu+R7p6BCVVzPDsIUL+uVeHwu0QCUZEiG\no2dWREREvCIuDv79F7t/O+7xw+H4P5A9B+aRnpiWHTF+fl4LzScTDRERERERuYboaGyr+7EJf2OD\nz32tr1wdV69BmKIlvRsbSjRERERERDIc+/ff2NZ3Y3PFQ25/pxXj8T6Ye9phfGTMqBINEREREZEM\nxG7bjPu5TpDfBfhD+aq4XnwTUzjM26EloURDRERERCQDsNZi532J/Xgk5HZBgsU81hvTtrNPjhdV\noiGSjB9++IG1a9cyaNAgb4ciIiIigj36F+6PhsG6leBvIM7g+mAapnwlb4d2Rb7RgUvEx/zwww8M\nGTLE22GIiIhIFmdjT+GeNw33cw85SUbuPJjeQ3HNXu7TSQaoRUPSwMmTJ8mVK5e3w7hhvtgEKSIi\nIlmD3b0Du3AWdumPEHvSKby1Ma6nXsHkL+Td4FJILRrpYPDgwbhcLrZv306nTp3ImzcvhQoVYsCA\nAQAcOHCABx54gODgYEJDQxk1alSS8+Pj4xkyZAjly5cnICCAYsWK0bdvX2JjY5Mc9/nnn3PXXXdR\npEgRAgICqFChAiNGjMBam+S4Xbt20a5dO4oWLUpAQABhYWG0bduWw4cPA7B3715cLheTJ0++7F5c\nLleSX/rP39vWrVt59NFHyZ8/P1WrVk3cv3DhQho1akRQUBBBQUHcc889bNy4MUmdnTt3JmfOnBw4\ncICWLVsSFBREWFgY77//PgCbNm2iSZMm5M6dm5IlSzJlypTL4oqKiqJv376UKFGCHDlyULZsWYYN\nG4bb7U485vx9jRw5kgkTJlC2bFkCAgKoU6cOERERSeIZN24c1lpcLlfia//+/cn81xURERHxDBsX\ni/unOSS89Cjuvg9j589ykoxKt+D6zyhcL7+TYZIMUItGuurQoQOVKlVi5MiRfP/997z55psEBwcz\nceJE7rrrLt566y2mTJlCv379qFmzJo0bN8ZaS6tWrVi2bBndu3encuXKbNu2jXHjxrF161YWLFiQ\nWP+4ceOoXLkyLVu2JCAggJ9++on+/fsTFRXFm2++CcCZM2do3rw58fHx9OrViyJFinDo0CEWLFjA\nX3/9RWhoaGJ9V/pFP7ny9u3bU6ZMGYYPH87p06cBmDZtGo8++ijNmjVjxIgRxMXF8cknn3D77bez\ndu1aKlasmHi+2+2mRYsWNGjQgFGjRjFlyhT69OlDzpw5GTRoEI8++iht27blo48+onPnztSrV4+y\nZZ1VLmNjY2ncuDH79++nR48elCpVitWrVzN48GD27dvHhAkTksQ6Y8YMYmJiePrppwF46623aN26\nNbt378bf358ePXrw119/sWjRoiRJTcGCBVP131tEREQyqS+/hO3boVs3CLvxmZ7s3t+xC2c7K3qf\ninEK3WD2HsVEJWCmj4OcOW/4OunOppPjx48nvq4mNjY25ZVC8i9PHe8hgwYNssYY27Vr18SyhIQE\nW7x4cWuMscOHD08sP378uA0MDLSdOnWy1lo7depU63K57LJly5LUOXXqVGuMsQsXLkwsS+6z6969\nu82dO7c9ffq0tdbaDRs2WGOMnT179hXj3bNnjzXG2MmTJ1+2zxhjhwwZctm9tW3bNslxMTExNl++\nfPbJJ59MUn7s2DEbEhJiO3bsmFj2+OOPW2OMHTZs2GWfgzHGTps2LbF8x44d1hhjX3311cSyN954\nwwYGBtodO3YkudYbb7xhjTGJ5efvq1ChQkmew++++84aY+y8efMSy3r27GmNMVf8jJKTqmdXMoS1\na9d6OwTJhPRcSVrRs5VO3G5rq1VzvkP6+VnburW1ixZZm5CQumriYm3Cz9/as/0es2cfuOXCq2lV\nm1A8v3X7GWsLFrR2yBBro6PT6GauLqXf369EXafSUdeuXRPfu1wuatasiTGGJ598MrE8ODiYihUr\nsmfPHgBmzpxJhQoVqFy5Mn///Xfiq2HDhhhjWLx4ceK5AQEBACQkJHDs2LHE406ePMn27dsByJMn\nDwDz58/n1KlTHru3860D5y1atIjjx4/ToUOHJHGfPXuWBg0aJIn7vIs/n+DgYCpUqEBgYCAdOnRI\nLK9QoQJ58+ZN/HzA+Yxuv/12ChQokORad955JwBLlixJcp02bdoQHByc+HeDBg0AktQpIiIickWj\nR0PbtmAMfP01NG0K4eHw55/XPNUe+AP3xLdwP9EM+/4g2LEJAnNj7mmH62Qe/BZtxuWXB/PeB7Bv\nHwwcCLlzp8NNeV7G7jp1ydgDjx/vYSVKlEjyd3BwMNmyZSMkJCRJeZ48eTh69CgAO3fuZMeOHRQq\ndHl/PGNM4nEAK1asoH///qxZsyax+9J5UVFRAJQuXZq+ffsyevRopkyZwm233cZ9991Hp06dyJ8/\n/3Xf2/luTOft3LkTgKZNmyZ7vJ+fX5K/s2fPTuHChZOUBQcHE5ZMc2SePHk4duxYkmtt2rQpRZ8R\nXP7fIV++fABJ6hQREREBLnx/PN913Bho0sR5HToEEyfCJ584+4oWTb6K2JPYVYuxi76Gbesv7Chf\nBdOsDeb2uzEBOaFqI3hyv5PE+Gfsr+mQ0RONDObSL9dw5XEQ9txD7Xa7qVKlCu+9916yxxU990Dv\n3r2bu+66i/DwcMaMGUOJEiUICAjg119/5T//+U+SQdGjRo3iiSee4LvvvmPhwoW88MILDBs2jKVL\nl1KpUqUrxpSQkHDFe8t5Sb/B89ebPHlyssnCpa50zeQ+MyDJAHdrLXfeeSevvPJKsseWLl061XWK\niIiIADBjBnzwAbz9NtSvn3Rf0aJOi0P//rB/P7gudBay8XGw7hfc/5sHG1bCmXM/AmcPwBSriOn1\nMqZMeNL66te//BoZmBINH1e2bFnWrVtHkyZNrnrcd999x+nTp5k7dy7FixdPLP/jjz+SPb5y5cpU\nrlyZl19+mc2bN1OzZk3effddPvnkk8Rf+I8fP57knH379qU47nLlygHOAOprxX6jypYty4kTJzx6\nHU1tKyIiIpw96yQSv/8OW7deOQnw94cyZbBnz8DG1dgVC7CrFl+YlhYgRx5MrB/m66WY7BvhlbfT\n5x68SGM0vOxaX2gffvhhIiMj+eijjy7bFx8fT0yMMzPB+V/pL265iI+PZ+zYsUnOiY6O5uzZs0nK\nwsPDCQgISOxelSdPHgoWLMjSpUuTHDdu3LgU3hU0b96cvHnzMnz4cM6cOXPZ/ku7M93IF/v27duz\ndu1afvzxx8v2RUdHX9aNLCXOrwNyabIlIiIiWcjkyU6SUa4cdO6c7CHW7cZuicA9/g3cTzTD/fqz\n2MXznCSjbCWMX0FcC7biN3MZrrmLMdmyO3Vd9J0ts1KLhpddqbvO+fJOnToxa9YsevbsydKlS7nt\nttuw1rJjxw6++uorZs2aRcOGDbn77rvJnj07LVu25KmnniIuLo4vvvjism5CP//8Mz179uLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd8080e2ef0>"
+        "<matplotlib.figure.Figure at 0x7f297bec9438>"
        ]
       },
       {
@@ -1196,7 +1196,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyEAAAGaCAYAAAAYfExsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Xl0VGWe//HPrVRCUgmUbJWQxIGgQZBNINKYdqLYEEfb\nQRkbBXREdMzYjQriHFps20SHhsbxICDiIO0SFw7qtO30otOxmzVGuxMFBOKCBhGQlD8QAgkJWer+\n/oAUlhCWVFKp5/p+nZOTyr3PvfeJ53uAj899nseybdsWAAAAAESIq6M7AAAAAOD7hRACAAAAIKII\nIQAAAAAiihACAAAAIKIIIQAAAAAiihACAAAAIKIIIQCAVvviiy/kcrk0derUju4KAMAghBAAMNRN\nN90kl8ulJ5544rRtJ0yYIJfLpWeeeaZd+mJZVrvcFwDgTBabFQKAmdavX6/LLrtMgwcP1qZNm1ps\n9/XXXys9PV0ej0dfffWVPB5Pm/WhsbFRFRUV8nq9Sk5ObrP7AgCcjZEQADDUP/7jP6p///7avHmz\n/v73v7fYrrCwUI2NjZo0aVKbBhBJcrvd6tevHwEEAHBWCCEAYLC8vDxJ0vLly1ts85vf/EaWZSkv\nL0+rV69WXl6eLrzwQnm9Xnk8Hg0aNEgFBQWqq6s74dqCggK5XC4VFhbqzTffVE5Ojrp06aJu3bpJ\nanlOyKeffqr7779fWVlZ6tmzp+Lj49WnTx/dcccd2rlz5wnPWbNmTfA+X3zxhSZOnKgePXooISFB\nF198sf70pz+1+Pu9+uqrGjt2rLp37x58zg033KB33nnnhLa//e1vNWbMGHXr1k3x8fHq16+fZs+e\nrUOHDrV4fwBA2yOEAIDBpkyZori4OL3yyiuqrq4+4fzatWu1bds2DR8+XMOGDdP8+fP1l7/8RcOH\nD9edd96pO+64Q506ddIjjzyiK6+8Uk1NTSd9zmuvvaZrr71W3bt317Rp03TdddeFnP/unJDXX39d\ny5YtU+/evXXTTTfpnnvu0YUXXqhnn31WF198sXbv3n3S5+zYsUM/+MEP9OWXX2rKlCm68cYbtWXL\nFl177bVas2ZNSFvbtnXrrbdq4sSJ2rRpk8aPH6/77rtPl112mUpLS/Xb3/42pP3PfvYzTZgwQdu2\nbdP111+ve+65R8nJyZo/f74uvfTSk/73AwC0ExsAYLSbb77ZtizLfvrpp084N3ny5JBzFRUVJ73H\nL3/5S9uyLHvlypUhx/Pz823LsuyYmBj7z3/+8wnXbd++3bYsy546dWrI8d27d9v19fUntC8qKrJj\nYmLsO++8M+T46tWrbcuybMuy7EceeSTk3J///Gfbsiz76quvDjm+bNky27Is++KLL7YPHDgQci4Q\nCNi7d+8O/vziiy/almXZ119/vV1XVxfSds6cObZlWfZ99913Qn8BAO2DiekAYLji4mLl5OQoKysr\nZG7IN998o9TUVHXq1ElfffWVEhMTW7zHN998ox49eui2227Tb37zm+DxgoICPfLIIxo/fvwJIwvS\n0dex+vbtq1tvvVXPPvvsGfV3yJAhqqmp0eeffx48tmbNGl1xxRXq06ePPv/88xNGVnr37q3a2lp9\n/fXXwWODBw9WeXm5/v73v2vEiBGnfOaIESO0efNmff311zrnnHNCzjU1NSklJUVut1t79uw5o98B\nABAed0d3AAAQnksvvVQDBgxQWVmZPvzwQw0ZMkSS9OKLL6q+vl5TpkwJBpCamhotWrRIv/vd7/Tp\np5+qurpa3/5/US29JjVy5Miz7tdLL72k559/Xps2bdKBAwdCXvXq1KnTSa+56KKLTrrc77nnnqu/\n/e1vwZ9ramq0detW9ejR47QB5PDhw9qwYYO6d++uhQsXnrRNXFyc9uzZo/3796tr165n8usBAMJA\nCAEAB8jLy9O9996r5cuXB/cNWb58eXBCuiQ1NDToiiuuUGlpqQYPHqxJkyapZ8+eio2NlW3bevjh\nh3XkyJGT3j8lJeWs+nPvvfdq0aJFSk1N1VVXXaW0tDQlJCRIkp577jl9+eWXJ73uu6MUzdxutwKB\nQPDnAwcOSJLS0tJO25f9+/dLkvbt26dHHnmkxXaWZam6upoQAgARQAgBAAe45ZZbdP/992vFihX6\nr//6L23YsEHl5eUaNmxYcKTgf//3f1VaWqqpU6eesGnhnj179PDDD7d4/7PZjPDrr7/W4sWLNXjw\nYJWUlJzwGtjLL798Fr/ZyTWHlZZGbr7N6/VKOvoa2MaNG8N+NgAgfKyOBQAO0LVrV02YMEH79+/X\na6+9Flyyt3kURJI+++wzSdK//Mu/nHD92rVr26wvFRUVsm1bubm5JwSQXbt2qaKiIuxnJCYmatCg\nQdq7d6/KyspO2TYpKUmDBg3SRx99pH379oX9bABA+AghAOAQzYFj0aJFevXVV5WUlKSbbropeD4j\nI0OStHr16pDrKioq9POf/7zN+tH8nPXr14e8QlVdXa077rijxWWAz9Y999wjSfrpT3+qqqqqkHO2\nbYdMMr/vvvvU0NCgqVOnBl/P+rZDhw6dcsNHAEDb4nUsAHCI5gnqH3zwgSTp9ttvV1JSUvD8P//z\nP+v888/XggULtHnzZl100UX68ssv9ac//UnXXHONVq5c2Sb9SE5O1sSJE7Vy5UpddNFFGjt2rKqq\nqvT222/L4/HooosuatVrUd9dzPHf/u3fVFxcrBdeeEHnn3++rrvuOvXs2VN79uzR2rVrde211+rx\nxx+XdHQ/lQ8++EBPPPGEzjvvPF155ZXq3bu3Dhw4oC+++ELr16/XlVdeqddff71N/hsAAE7tlCMh\n69at07hx45Senh7cMbdZY2Ojfv7zn2vo0KFKSkpSamqqbrrpphN2wj1y5Ijuvvtu9ezZU0lJSbr2\n2mvP6B1eAMDZ+/d//3dJCpmQ3szj8WjVqlWaPHmytm7dqieeeEJbtmzRQw89pBdffPGk97Ms66zm\ngzR75pln9MADD6i2tlZLly7V22+/rXHjxumdd96R1+s963u21I/nn39eL7/8sgYNGqT/+Z//0eOP\nP641a9Zo5MiRuvHGG0PaLlq0SG+99ZZycnK0Zs0aPf7443rjjTe0d+9e3XXXXcrPzz/r3xMA0Dqn\n3Cfkrbfe0jvvvKNhw4bplltu0VNPPaVbbrlFklRVVaUJEybojjvu0EUXXaQDBw7ovvvu0759+/Th\nhx8qJiZG0tFh8t///vd64YUX1K1bN82cOVMHDhzQ+++/L5eLt8EAAACA75sz3qywc+fOevLJJ4Mh\n5GQ++ugjDRw4UJs3b9bAgQNVVVUln8+n559/XpMmTZJ0dFJi79699dZbbyk3N7dtfgsAAAAAxmjT\noYjmiYHNa6y///77amhoCAkb6enpGjBggEpKStry0QAAAAAM0WYT0+vr63Xfffdp3LhxSk1NlSRV\nVlYqJiZG3bt3D2mbnJwsv98fcuy7K5sAAAAAMEPznkxnqk1CSGNjo26++WYdPHhQf/zjH9vilgAA\nAAAcKuzXsRobGzVp0iRt2bJFf/3rX4OvYklSSkqKmpqaTtgcqrKyUikpKeE+GgAAAICBwhoJaWho\n0MSJE1VeXq41a9bI5/OFnB8xYoRiY2NVVFQUMjH9448/VnZ2dov3PdvhHOB0ysrKlJWV1dHdgMNQ\nV2gP1BXaC7WFthbOdIpThpCamhpt27ZNkhQIBLRjxw5t3LhR3bt3V2pqqiZMmKCysjL94Q9/kG3b\nqqyslCSdc845io+Pl9fr1e23365Zs2bJ5/MFl+gdOnSoxowZ0+pOAwAAADDXKV/HKi0t1fDhwzV8\n+HDV1dUpPz9fw4cPV35+vnbt2qXf//732rNnj0aMGKHU1NTg16uvvhq8x8KFCzV+/HjdeOONuvTS\nS9WlSxf94Q9/aNXmVwAAAADMd8qRkMsvv1yBQKDF86c61ywuLk6LFy/W4sWLz753AAAAAByHLcsB\nAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBE\nEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAA\nAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQh\nBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAA\nRBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIA\nAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBEEUIAAAAARBQhBAAAAEBE\nEUIAAAAARBQhBAAAAEBEEUIAAAAARNQpQ8i6des0btw4paeny+VyqbCw8IQ2BQUFSktLk8fj0ejR\no1VeXh5y/siRI7r77rvVs2dPJSUl6dprr9Xu3bvb9rcAAAAAYIxThpCamhoNGTJEixYtUkJCgizL\nCjk/f/58LViwQEuWLFFpaal8Pp/Gjh2r6urqYJsZM2bo9ddf18qVK7V+/XodPHhQ11xzjQKBQPv8\nRgAAAACi2ilDyFVXXaU5c+bo+uuvl8sV2tS2bS1cuFCzZ8/W+PHjNXDgQBUWFurQoUNasWKFJKmq\nqkrPPvusHnvsMf3oRz/SsGHD9OKLL+rDDz/UX/7yl/b7rQAAAABErVbPCdm+fbv8fr9yc3ODx+Lj\n45WTk6OSkhJJ0vvvv6+GhoaQNunp6RowYECwDQAAAIDvl1aHkMrKSklScnJyyHGfzxc8V1Line truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd8082d0eb8>"
+        "<matplotlib.figure.Figure at 0x7f298cff7048>"
        ]
       },
       {
@@ -1508,7 +1508,7 @@
       "# plot the filter output and the variance\n",
       "plt.scatter(range(N), zs, marker='+', s=64, color='r', label='measurements')\n",
       "p1, = plt.plot(estimates, label='filter')\n",
-      "plt.legend(loc='best')\n",
+      "plt.legend(loc='best', scatterpoints=1)\n",
       "plt.xlim((0,N));plt.ylim((0,30))\n",
       "plt.show()\n",
       "plt.plot(ps)\n",
@@ -1522,9 +1522,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxkAAAGNCAYAAAB9i7yDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxkAAAGNCAYAAAB9i7yDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd808071cf8>"
+        "<matplotlib.figure.Figure at 0x7f297bede3c8>"
        ]
       },
       {
@@ -1532,7 +1532,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGaCAYAAACBhJXZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd8082be4e0>"
+        "<matplotlib.figure.Figure at 0x7f298cd93fd0>"
        ]
       },
       {
@@ -1650,9 +1650,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyIAAAGNCAYAAADtmMVMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyIAAAGNCAYAAADtmMVMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd8080d8080>"
+        "<matplotlib.figure.Figure at 0x7f297be83160>"
        ]
       }
      ],
@@ -1728,9 +1728,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80812e860>"
+        "<matplotlib.figure.Figure at 0x7f297bf18978>"
        ]
       },
       {
@@ -1738,7 +1738,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80832d978>"
+        "<matplotlib.figure.Figure at 0x7f297be162e8>"
        ]
       }
      ],
@@ -1814,9 +1814,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzYAAAGNCAYAAADD3eTeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzYAAAGNCAYAAADD3eTeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80811fd30>"
+        "<matplotlib.figure.Figure at 0x7f297beaca58>"
        ]
       }
      ],
@@ -1878,9 +1878,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80811f6d8>"
+        "<matplotlib.figure.Figure at 0x7f297bd7c438>"
        ]
       }
      ],
@@ -1941,9 +1941,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzYAAAGNCAYAAADD3eTeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzYAAAGNCAYAAADD3eTeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd7fa6f2b00>"
+        "<matplotlib.figure.Figure at 0x7f297bcf4e48>"
        ]
       }
      ],
@@ -1993,9 +1993,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzYAAAGNCAYAAADD3eTeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzYAAAGNCAYAAADD3eTeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd7fa6f2ac8>"
+        "<matplotlib.figure.Figure at 0x7f297bcf9898>"
        ]
       }
      ],
@@ -2124,7 +2124,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxkAAAGNCAYAAAB9i7yDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd80bb92e80>"
+        "<matplotlib.figure.Figure at 0x7f297be717b8>"
        ]
       },
       {
@@ -2214,7 +2214,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd808278550>"
+        "<matplotlib.figure.Figure at 0x7f297be64668>"
        ]
       }
      ],
@@ -2299,7 +2299,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fd808262710>"
+        "<matplotlib.figure.Figure at 0x7f297bf1f080>"
        ]
       }
      ],

08_Designing_Kalman_Filters/Designing_Kalman_Filters.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:53ed1038531ab2e0f1c6f53a7e50712c5b86128a3451c66ae19912cb6b7f0203"
+  "signature": "sha256:a37ccdfe2b40c1c2e9e4dc6c1512db6c9e4c2398316fe30f509bed9c5a50579c"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -261,7 +261,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7fed72695208>"
+        "<IPython.core.display.HTML at 0x7f4026f471d0>"
        ]
       }
      ],
@@ -354,9 +354,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGNCAYAAACfV6f6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGNCAYAAACfV6f6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3X90U/d9//GXLghhE+LkSyILbMVA54TEazgEhwmnh4Su\n1kqS0XK6NIPll7ozzhqHBGgPK4TWbCNw3OVwSAN0OexMh61jIT1LsnNalqg90ICP8WaXHwvxoPTg\nGacgLTRgMANhc+/3D2LNAtvyD11LV3o+zvE58NFHVx/OG9t66fP53I/LsixLAAAAAGAjI9MDAAAA\nAJD7CB4AAAAAbEfwAAAAAGA7ggcAAAAA2xE8AAAAANiO4AEAAADAdgQPAAAAALYbVPA4c+aMnn32\nWXm9XhUUFKiiokL79u1L6rNu3TqVlJSosLBQ8+fPV0tLiy0DBgAAAOA8KYPH+fPn9dBDD8nlcmn3\n7t06duyYtmzZIq/Xm+hTV1enTZs2acuWLWpqapLX61V1dbU6OzttHTwAAAAAZ3ClOrl8zZo12r9/\nv/bv39/n45ZlacqUKXrxxRe1evVqSdKVK1fk9Xr16quvaunSpekfNQAAAABHSTnj8e6772rOnDl6\n8sknVVxcrFmzZmnr1q2Jx1tbWxWLxRQMBhNt48eP17x589TQ0GDPqAEAAAA4ythUHU6ePKlt27Zp\n5cqVWrNmjQ4dOqRly5ZJkmpqahSNRiVJxcXFSc/zer06ffp04u8dHR3pHDcAAACAUVJUVDTia6QM\nHqZpas6cOXrllVckSTNnztSJEye0detW1dTUDPhcl8s14gECAAAAcL6US62mTJmi++67L6ltxowZ\nOnXqlCTJ5/NJkmKxWFKfWCyWeAwAAABAfks54/HQQw/p2LFjSW2/+tWvNHXqVEnStGnT5PP5FIlE\nNHv2bEnXN5fX19fr1Vdf7fOa6Ziqgf2am5tVWVmZ6WFgEKiVc1ArZ6FezkGtnIV6OUO6t0qknPFY\nsWKFGhsbtWHDBv3617/Wj3/8Y73++uuJZVYul0vLly9XXV2d3nnnHR09elTPPfecJk6cqCVLlqR1\nsAAAAACcKeWMR2Vlpd59912tWbNGf/3Xf62ysjKtX79e3/zmNxN9Vq1apcuXL6umpkbnzp1TIBBQ\nJBLRhAkTbB08AAAAAGdIGTwk6dFHH9Wjjz46YJ/a2lrV1tamZVAAAAAAckvKpVYAAAAAMFIEDwAA\nAAC2I3gAAAAAsB3BAwAAAIDtCB4AAAAAbEfwAAAAAGA7ggcAAAAA2xE8AAAAANiO4AEAAADAdgQP\nAAAAALYjeAAAAACwHcEDAAAAgO0IHgAAAABsR/AAAAAAYDuCBwAAAADbETwAAAAA2I7gAQAAAMB2\nBA8AAAAAtiN4AAAAALAdwQMAAACA7QgeAAAAAGxH8AAAAABgO4IHAAAAANsRPAAAAADYjuABAAAA\nwHYEDwAAAAC2I3gAAAAAsB3BAwAAAIDtCB4AAAAAbEfwAAAAAGA7ggcAAAAA2xE8AAAAANiO4AEA\nAADAdgQPAAAAALYjeAAAAACwHcEDAAAAgO0IHgAAAABsR/AAAAAAYDuCBwAAAADbETwAAAAA2G5s\npgcAAACA/GaaptrbuyRJfr9bhsFn47mIqgIAACBjTNNUJBJXIOBWIOBWJBKXaZpJj7e1xdXWltwO\n5yF4AAAAIGPa27sUCnkUjRqKRg2FQp7E7EeqUAJnIXgAAAAgKw0USuA8BA8AAABkjN/vVjgcl89n\nyuczFQ7H5fe7Mz0s2IDN5QAAAMgYwzAUDHrU2NizudyT2FzeE0pCIY8kfRZKPBkbK0aG4AEAAICM\nMgxDZWU3B4qBQgmch+ABAACArNVfKIHzEBkBAAAA2C5l8Fi3bp0Mw0j6mjJlyk19SkpKVFhYqPnz\n56ulpcW2AQMAAMB5ep/HwXKp/DSoqs+YMUPRaDTx9eGHHyYeq6ur06ZNm7RlyxY1NTXJ6/Wqurpa\nnZ2dtg0aAAAAznHjeRxtbVM5jyMPDSp4jBkzRl6vN/E1adIkSZJlWdq8ebNWr16tRYsWqaKiQjt2\n7NDFixe1c+dOWwcOAAAAZ7jxPI7nn7+N8zjy0KCCx8mTJ1VSUqLp06dr8eLFam1tlSS1trYqFosp\nGAwm+o4fP17z5s1TQ0ODPSMGAAAA4Dgpg0cgENCOHTv0/vvva/v27YpGo6qqqtKnn36qaDQqSSou\nLk56jtfrTTwGAACA/HbjIYHbtp3nkMA85LIsyxrKE/73f/9X06ZN03e+8x393u/9nr7whS/o1KlT\nKi0tTfT5xje+oTNnzujf/u3fEm0dHR2JP584cSINQwcAAIBTGIahq1f/nyRp3LhP2ePhAOXl5Yk/\nFxUVjfh6Qz7Ho7CwUBUVFfr1r3+tr371q5KkWCyWFDxisZh8Pl+/16isrBzGUDHampubqZVDUCvn\noFbOQr2cg1o5S3PzWerlAL0nDtJhyPcyu3Lliv7rv/5LkydP1rRp0+Tz+RSJRJIer6+vV1VVVVoH\nCgAAgKHrfRtbZhmQSSmDx7e//W3t27dPra2t+vd//3f90R/9kS5fvqxnn31WkrR8+XLV1dXpnXfe\n0dGjR/Xcc89p4sSJWrJkie2DBwAAQP9uvI1tJDL08EFwQbqkXGr1m9/8RosXL9bZs2d15513au7c\nuWpsbJTf75ckrVq1SpcvX1ZNTY3OnTunQCCgSCSiCRMm2D54AAAA9K/3bWwlKRTyqLGxS2VlnkE9\nvye4hELX+4fDcQWDHg4AxLCkDB7//M//nPIitbW1qq2tTcuAAAAAkB1GGlyA3oirAAAAOerG29iG\nw3FuY4uMGfJdrQAAAOAMhmEoGLw+SyFJfv/Qlkn1BJfeS638fmY7MDwEDwAAgBxmGMawl0aNNLgA\nvRE8AAAA0K/hBBfTNNXe3hNW3IQVSGKPBwAAANIoHbfwRW4ieAAAACBtet8JKxo1FAp5ErMfyG8s\ntQIAAHAoljTBSfjfCQAA4EDZuqSJW/iiP8x4AAAAOFC2Hu7HnbDQH4IHAAAA0mokt/BF7iJ+AgAA\nOBBLmuA0zHgAAAA4EEua4DQEDwAAAIdiSROchFgMAAAAwHYEDwAAAAC2I3gAAAAAsB3BAwAAAIDt\nCB4AAAAAbEfwAAAAAGA7ggcAAAAA2xE8AAAAANiO4AEAAADAdpxcDgAAkIJpmmpv75Ik+f1uGYbR\nZxuA/vEdAgAAMADTNBWJxBUIuBUIuBWJxNXd3X1Tm2maaXmttra42tpuvt5AjwFOQPAAAAAYQHt7\nl0Ihj6JRQ9GooVDIo5aWqze19cx+DFdfAacnYAz0GOAUBA8AAIAs0FfA6QkzAz0GOAXBAwAAYAB+\nv1vhcFw+nymfz1Q4HNd99427qc3vd2d6qEBWY3M5AADAAAzDUDDoUWNjz0Zyz2dtxk1tI9ETcEIh\njyR9FmY8KR8DnILgAQAAkIJhGCor86RsG+lr9BVwUj0GOAXBAwAAIEsMFGbSHXSA0UZUBgAAAGA7\nggcAAAAA2xE8AAAAANiO4AEAAADAdgQPAAAAALYjeAAAAACwHcEDAAAAgO0IHgAAAABsxwGCAAAg\n75imqfb2nlPA3ZwCDowCvssAAEBeMU1TkUhcgYBbgYBbkUhcpmlmelhAziN4AACAvNLe3qVQyKNo\n1FA0aigU8iRmPwDYh6VWAADAUVgmBTgT36kAAMAx0rFMyu93KxyOy+cz5fOZCofj8vvdNo0YQA9m\nPAAAgGP0XiYlSaGQR42NQ1smZRiGgsH/e57f72HWBBgFBA8AAJB3DMNQWZkn08MA8grxHgAAOAbL\npADnYsYDAAA4BsukAOcieAAAAEdhmRTgTHxEAAAAAMB2QwoeGzdulGEYWrZsWVL7unXrVFJSosLC\nQs2fP18tLS1pHSQAAAAAZxt08GhsbNT27dt1//33y+VyJdrr6uq0adMmbdmyRU1NTfJ6vaqurlZn\nZ6ctAwYAAADgPIMKHh0dHXrqqacUDod1++23J9oty9LmzZu1evVqLVq0SBUVFdqxY4cuXryonTt3\n2jZoAAAAAM4yqOCxdOlSPfHEE3r44YdlWVaivbW1VbFYTMFgMNE2fvx4zZs3Tw0NDekfLQAAyHmm\naaqtLa62tqGfSg4ge6UMHtu3b9fJkye1fv16SUpaZhWNRiVJxcXFSc/xer2JxwAAAAbLNE1FInEF\nAm4FAm5FIoQPIFcMeDvd48eP6+WXX1Z9fb3GjBkj6fryqt6zHv3pHVBu1NzcPMRhIlOolXNQK+eg\nVs5CvUZXd/cdCoXuUjR6/bPRUMijd945pbFjz6Z8LrVyFuqV/crLy9N6vQGDx4EDB3T27FlVVFQk\n2q5du6b9+/frjTfe0NGjRyVJsVhMpaWliT6xWEw+n6/f61ZWVo503BgFzc3N1MohqJVzUCtnoV6j\nr60tflPb5MmTVVY2dcDnUStnoV7O0NHRkdbrDbjUatGiRTp69KiOHDmiI0eO6PDhw6qsrNTixYt1\n+PBhlZeXy+fzKRKJJJ5z5coV1dfXq6qqKq0DBQAAuc/vdyscjsvnM+XzmQqH4/L73ZkeFoA0GHDG\no6ioSEVFRUlthYWFuv3223XfffdJkpYvX64NGzZoxowZKi8v1/r16zVx4kQtWbLEvlEDAICcZBiG\ngkGPGhu7JEl+v0eGwXnHQC4YMHj0xeVyJe3fWLVqlS5fvqyamhqdO3dOgUBAkUhEEyZMSOtAAQBA\nfjAMQ2VlnkwPA0CaDTl47N2796a22tpa1dbWpmVAAAAAAHIPc5cAAAAAbEfwAAAAAGC7IS+1AgAA\n+cs0TbW392z8drPxG8Cg8dMCAAAMCqeKAxgJggcAABiU9vYuhUIeRaOGolFDoZAnMfsxFKLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed72695e48>"
+        "<matplotlib.figure.Figure at 0x7f400e344f28>"
        ]
       }
      ],
@@ -707,9 +707,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGNCAYAAABuXPx3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxkAAAGNCAYAAAB9i7yDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed72695438>"
+        "<matplotlib.figure.Figure at 0x7f400e344be0>"
        ]
       }
      ],
@@ -788,9 +788,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGGCAYAAAAEmwy0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xm0XWV5wP/vHs7e+8zDne/NHDIiyKQFFSmIirNFW8Si\nBcukUtvaX61FSlErgos69OcCK1q1olbl56LYqqitiB0EgpRBICFkvPM598zDnvfvj0tucnMz3CSX\nIcnzWSsrufvs/e4hB/I++32f91GiKIoQQgghhBBCiHlSX+gLEEIIIYQQQhxdJIgQQgghhBBCHBIJ\nIoQQQgghhBCHRIIIIYQQQgghxCHRF6qhWq22UE0JIYQQQgghnifZbPaQj5GRCCGEEEIIIcQhkSBC\nCCGEEEIIcUgWbDrTng5nSESI/dmwYQNnnHHGC30Z4hgj3yvxXJHvlnguyPdKLLQjTUWQkQghhBBC\nCCHEIZEgQgghhBBCCHFIJIgQQgghhBBCHBIJIoQQQgghhBCHRIIIIYQQQgghxCGRIEIIIYQQQghx\nSJ6TJV4PJAxDXNd9vk8rjmJLly7Ftu0X7PyGYaCqEm8LIYQQQuzyvAYRYRjiOA6WZaEoyvN5anEU\nsyzrBTt3FEXYto1pmhJICCGEEEI863ntFbmuKwGEOKooioJlWTJ6JoQQQgixh+f91aoEEOJoI99Z\nIYQQQojZZH6GEEIIIYQQ4pBIECGEEEIIIYQ4JBJECCGEEEIIIQ6JBBEL6OGHH+bss88mnU6jqipv\nf/vb56zo87u/+7uce+65L9AVCiGEEEIIceSe9zoRx6owDLnooosA+OxnP0symeSBBx6Yk5SrKMqs\nbZ1Oh5tvvplzzz2Xc84553m9ZiGEEEIIIQ6HBBELZHR0lM2bN/OFL3yBK664AoCLLrqIz3zmM7P2\ni6JoVhDRarX4xCc+gaqqEkQIIYQQQoijgkxnWiCTk5MAZDKZmW2apmEYxryOj6JoQa/HdV2CIFjQ\nNoUQQgghhAAJIhbEpZdeyhlnnAHAZZddhqqqnHvuudxwww0HrHK8bds2ent7Afj4xz+Oqqqoqspl\nl102s8/Y2BiXX345/f39WJbF+vXr+dKXvjSrnXvvvRdVVfn2t7/NDTfcwJIlS0gkEoyMjDwHdyuE\nEEIIIY53Mp1pAVx99dWccMIJXH/99Vx11VWcffbZ9PX18atf/eqAx/X29nLbbbfx/ve/nwsvvJAL\nL7wQgJUrVwLToxtnnnkmURRxzTXX0Nvby89//nM+8IEPMDU1xcc+9rFZ7d14441omsaf//mfE0UR\nyWTyublhIYQQQghxXHtxBxH7qxS8v6k/h7r/AjnzzDPRdZ3rr7+es846i3e/+90ABw0iEokE73jH\nO3j/+9/PySefPHPcLtdddx2e5/HYY4/R1dUFwJVXXsmVV17JjTfeyDXXXEM2m53Zv9ls8uSTTxKP\nxxf4DoUQQgghhNhNpjO9SEVRxJ133smb3vQmoiiiVCrN/Hrta19Lp9Ph/vvvn3XMe9/7XgkghBBC\nCCHEc+7FPRJxqCMIz/GIw/OpWCxSrVb56le/yle/+tU5nyuKQrFYnLVt1zQoIYQQQgghnksv7iDi\nOBaGIQDvfve7ed/73rfPfdavXz/rZxmFEEIIIYQ4sCAIaXZcWrZH2/GwXZ8wnH4RraoKZkwjaRkk\nrBipuIGuycSdfZEg4gW2dzG6XXp6ekin03iex3nnnfc8X5UQQgghxLGlbXsUqy2m6m0abgvbt7G9\nDk7gEkbTy+IrioqpGcT1OJZukTZTFDIJerIJkvH5Ldt/vJAg4gWWSCQAKJfLs7ZrmsY73/lO7rjj\nDh599FFOPvnkWZ8Xi0V6enqet+sUQgghhDgauV7AjskapXqDql2lalcxDIibGpmkhhkz0NTpl7ph\nFOG4IbbboOxUGGtCppklX85TSCVZ1p/DNKT7DBJEvCD2LCwXj8c58cQT+Zd/+RdWr15NoVBgxYoV\nvPzlL+emm27i3nvv5ayzzuKKK65g/fr1VCoV/u///o+77rqLTqfzAt6FEEIIIcSLW6nWZudkjYnm\nJBW7TDYVY+lgHCOm7fcYI6aRTsYA8PyQaqPF9nqFcidH03ZY3JOjNy/L6EsQsYD2npqkKMq8tn31\nq1/lQx/6EH/xF3+B4zhceumlvPzlL6enp4f777+fT37yk9x1113cdtttFAoF1q9fz2c/+9kDnlsI\nIYQQ4ni2fbzK8FSZ0eYYhhmwYlHqkPMbYrpKT96ikDWZmGqyudyk7Q3SaOdZMZg/rvtfShQtzJJG\ntVpt5s971i7Yk23bWJa1EKcT4nkl391jz4YNG2YqzQuxkOS7JZ4Lx+L3yvUC2o5H2/YIwpAomi75\npWsqCTNG8giSmreOVdgxVWK0MUJfl0k2tTD5DM22x1ipQ19ikEWFbk4YKhy1gcR8+u4HIiMRQggh\nhBDieeG4PsVam3K9Q8d1ppObfRs/DIAIUNA1fSaxOWEadGXidGcTxPT9T0Has/1NO6d4enyc0eYw\nA91xbM8laATEDR3T0FGPoNOfSsRY3K8yPDGGUpkOeJYP5A+7vaOZBBFCCCGEEOI51XE8RkoNphot\nanaNil0hjHwsU8UyNExdRVEUwjDC80NKThm7HmBoJrl6jlwpR1cmwVB3Zk4+Q6vjUqy1qTZtSvUG\nG0fH2NnYSiGnMlxVQVGIaTqmZmJqJnEzRi5lkUmahxVQWIbGor4EO8fGiKkG2aRFIXP8LbMvQYQQ\nQgghhHhORFHERKXFzskqk61J6m6ddEJjUZ+JZSYOenyr41NpTFEsFym181SbvSzuzdKdTVBr2oxO\nNai22lTsCtVOlZFikylngkw+IJnWUZTpWsSuH9KwAzw/Iq7HSTfTpM0kuZRFdy55yMGEZWj0FEzG\nqqMkJy3SCWNeIyXHEgkihBBCCCHEgvODkM0jZSbqFcYbY6SSKiv7UjPLqc5HMq6TjOv4fsh4ucbm\ncpOG3UcY6BgxhWJ7gk7QIpuKkUAhmfYhoTDQt+8AJYwi2rZPtVViqlMmb+epd1wGu9IkzNgh3V8u\nbdBotZhoFMkWreNuWpMEEUIIIYQQYkF5fsDGnVMMV8eoOWUGehMk44ff7dR1lUW9SSbLHf736SdR\nIg0tFrB+RZ6hXJowgqe316jaVfp7938eVVFIxWOk4jEcN6BULdHymthuN325ND25Q1u6daA7zpaR\nMlP1Lhb1ZI6r0Qip4y2EEEIIIRaMH4Rs2jnFjsooTb/CsqHUEQUQu7Rtn3LdAaPOuLMVPdGi7TgA\n1JsuTbeFYYYYxvy6t6ahMdibwLB8RhojjJQrjJebh3RNuq6SiKtU7SqlWvuQ7+loJiMRQgghhBBi\nwWwfrzJaL9IOqiwZOLTpS/tjOwE7xpuMNcaJxV1O6k8xPlWj1IwRN3VarYi60yCTPbSRAAWFfNrE\njPlMVMcBUBXozafm3UYhYzJerFKsdjPQlT6k8x/NJIgQQgghhBALolzvMFGrM9UusmwouSABRBhG\nDE+2GG9MosZcerumcxd6CxYTU1MYFRPP1XFDh0T80PIadklYOt05mKhOoCoaCStGKm7O+9ggatNx\nHRzXxzSOj+61TGcSQgghhBBHzA9Cdk7WGGuM0lMwiekL082crNiUW3V8OvQUdnfQzZhGOqkxWisy\nVqmi69ERFX5LWDrZlE6xVWRsqkkQhvM+1jI0On6HtuMd9vmPNhJECCGEEEKII1aqtSm1yqgxj1x6\nYSpEt22fUrVNxS7TU9DnBAm5tEHb7VDt1Agi/4jPl00ZKJrHVKfKRKU17+Pipobt27RtCSKEEEII\nIYSYt2K1RcWu0JW1FqzNqapDuVMhnVL2mTCtoJCwYjScOrZ7aEFEy5s99emJp6Z/786ZVO0KlUYb\nzw/m1VYspuIGHu489z8WSBAhhBBCCCGOSLVpU+s0CRVvzkpMbQ/GWipRdGhtul5AreXQ9ltk0/tP\nmE5YOk7oYrsuzjw78VN2nC89eSp3bVs1s+3JJ6d/j+kaCUuj4TaoNDrzak9VFCIiwvAQb/Iodnxk\nfgghhBBCiOdMveVQs+tkU3MTm297PMGTZZ0uK+TUHo9Te3xOyAZoB3mVXW24NN0GybiCeoAEbUWB\nuKHRCWw6joc5j1oNT1ULgEJc83niqekA4q4fTH+2bh2sXBGjWG5Sbdr05JIHzbWIiFBQjign42gj\nQYQ4Lv3oRz/iwQcf5G//9m9f6EsRQgghjnot28X2bXqtuV3LlD79dn7KVvn5TpOf7zRJ6iHr8w4n\nFRzW5FwSMQ3T0FH36IQ32z5Nt0VX14GDAlVRMHQNx2/jeAcfiSg8toVtjeWQgrW5KZYuhvVrpz97\nx+/t2ktDUW3ank3H9Q9azToIIjRFXZDVqI4WEkSI49KPfvQjbr31VgkihBBCiCMURREdx8cJbCxj\nbp2El/W5PDgZI6kHnJhusKmZoOoZPFiM82Axjq4ELI23WJPusDbnUEjoZBImjhvghS6mceAkbSOm\nEDcN6vU6rr//vAhrqsYp/+/3cB4pM/7xi0kHLRan6jOfr1s3e3/T0HACB3seQYTtBMR1i/hB9juW\nSBAhDlmr1SKZPLSy8C9Gx9OQoxBCCPFccbwAx3fRNGZNO/LDkKlaG6vjYChLaPkaBWUjr8m1sJUU\nw3YPOzvdlL00z7QzPNPO8JOJkH6zwcp4m4xTQzM9FOXA9RpMUyVpWNhegOcHM1OLdlE9nzXf+Skn\nffkujGaHv3/3RwFYla+w58DBrtGImXYNDaftzith23YD8gmLpHX8BBGSWL0AbrjhBlRV5amnnuKS\nSy4hl8vR09PDxz72MQB27tzJ2972NrLZLP39/dxyyy2zjncch49//OOsWrUKy7JYtGgRH/Line truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGGCAYAAAAEmwy0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed557d2208>"
+        "<matplotlib.figure.Figure at 0x7f400e058630>"
        ]
       },
       {
@@ -875,7 +875,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyEAAAGNCAYAAAAGr35PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4de1f828>"
+        "<matplotlib.figure.Figure at 0x7f400264a780>"
        ]
       }
      ],
@@ -997,7 +997,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxoAAAGNCAYAAACWvAeAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4de1f438>"
+        "<matplotlib.figure.Figure at 0x7f400264a6d8>"
        ]
       }
      ],
@@ -1336,7 +1336,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed557e4dd8>"
+        "<matplotlib.figure.Figure at 0x7f400dfc5e10>"
        ]
       }
      ],
@@ -1386,7 +1386,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAA0AAAAGxCAYAAABLMtbXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c5805f8>"
+        "<matplotlib.figure.Figure at 0x7f4000e202e8>"
        ]
       }
      ],
@@ -1417,7 +1417,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAA0AAAAGxCAYAAABLMtbXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed5580a278>"
+        "<matplotlib.figure.Figure at 0x7f400e344940>"
        ]
       }
      ],
@@ -1450,7 +1450,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed55484550>"
+        "<matplotlib.figure.Figure at 0x7f400dcd1128>"
        ]
       }
      ],
@@ -1481,7 +1481,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGxCAYAAAC5joNyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c5745c0>"
+        "<matplotlib.figure.Figure at 0x7f4000d92828>"
        ]
       }
      ],
@@ -1520,7 +1520,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c4e2d30>"
+        "<matplotlib.figure.Figure at 0x7f4000cfb320>"
        ]
       }
      ],
@@ -1561,7 +1561,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGxCAYAAAC5joNyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c4df550>"
+        "<matplotlib.figure.Figure at 0x7f4000d99e10>"
        ]
       }
      ],
@@ -1601,7 +1601,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzMAAAGxCAYAAABWTOhMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xl8TFf/B/DPneyZJJOI7FRiiRARIrGEiIh9e5SSeooG\n5alSKlptVKu2qrU/D6pK7WpvkdKKJbSWImprRSUioggikgiJbOf3hye3RiZkYpLJxOf9ennJOffc\ne78zc8L9zjn3XEkIIUBERERERGRgFPoOgIiIiIiIqCyYzBARERERkUFiMkNERERERAaJyQwRERER\nERkkJjNERERERGSQmMwQEREREZFBYjJDRFRGBw8ehEKhwJQpU/QdynMZUqwvol27dlAoKva/Nnd3\nd3h4eFToOSurpKQkKBQKDBkypNT7rFq1CgqFAqtXry7HyDQLDw+HQqFAcnJyhZ+biHSDyQwRlVph\nYSG+/fZbhISEwN7eHqampnB0dISPjw/Cw8OxadMmfYeoF5Ikab3Pjh070KdPH7i5ucHc3Bz29vZo\n2bIlZsyYgYyMjHKI8rGyxPqiMjIyoFQqYW5ujrt37z6zbVpaGszNzWFlZYX79++X6XwV/RolSSp2\nzs8++6xCLtCLkocn/xgbG8PBwQGhoaFYt25duZ6/JGX5DPTRN/V5XiLSDWN9B0BEhqGwsBC9evXC\n7t27YWtrix49eqBGjRrIy8vDn3/+iW3btuHEiRMICwvTd6iVWmZmJl5//XX8/PPPsLGxQbdu3eDh\n4YH79+9j7969+OSTT7Bw4UJ8//33CAwM1He4OqFSqfD6669j5cqVWLNmDcaNG1di2zVr1iA3Nxdv\nvPEGrK2tKzDKsjtw4ECJ2yrqQtnW1hbvvfceACA3Nxd//fUXduzYgZiYGJw4cQL//e9/KySOGjVq\n4OLFi1CpVBVyPl3gs8OJDBuTGSIqlY0bN2L37t1o0qQJDh06VOxCMzc3F4cPH9ZTdIahsLAQ/fr1\nw969e9GhQwds2LAB9vb2am0WLFiAiIgIdO3aFSdOnED9+vX1FK1ujRgxAitXrsTy5cufmcwsW7YM\nkiRhxIgRFRjdi3nWFLOKulC2tbXFp59+qlb366+/IiQkBIsXL0ZERATc3d3LPQ5jY2N4enqW+3mI\niIpwmhkRlcqRI0cAPJ5jrukbc1NTU7Rv317jvjExMejVqxccHBxgZmYGd3d3jBo1Crdu3dLY/t69\ne/jkk0/g4+MDKysrqFQq+Pj44IMPPkB6erpa28TERAwZMgQ1atSAmZkZnJ2dERYWhvPnzxc7btHc\n/ClTpuDMmTPo3r07bG1toVQq0a5dOxw7dkxjPLdu3cKwYcPg5OQES0tLNG3aFGvWrHnm+6XJhg0b\nsHfvXtSuXRvbt28vlsgAwNixYzF+/Hjcv38fY8eOVdv25NSl3bt3o23btrCxsUG1atVeKNaMjAx8\n+umnaNSoEZRKJWxsbBAUFIStW7cWa1t0782QIUPw119/oV+/fnBwcICRkRHOnTtX4jlatGiBxo0b\nIy4uTu5LTzt69Cji4uLQqFEjtGjRQq7Xtv9oIoTA8uXL0bJlS1hbW0OpVMLPzw/z589Hfn6+xn2u\nX7+O9957D56enrC0tES1atXg7++PyZMnq+3z9D0z7dq1w9SpUwEAQ4YMUZsCdvXqVURGRkKhUJT4\nuVy8eBEKhQJBQUGlfn2aBAUFoX79+hBC4NSpU8W2//7773j99dfh6uoKMzMzuLq6YvDgwbh8+XKx\ntrdv38aECRPg5eUl/056enrijTfeUPvcn3XPTEJCAvr16wc7OztYWVmhdevW2L17d4nxKxQKhISE\naNxW9Lvwyy+/qNVv374dAwcOhKenJ6ysrGBlZYVmzZphwYIFKCwsLPFcT4uKikKHDh3g6uoKc3Nz\nuLq6ok2bNpg5c2apj0FEFYMjM0RUKkUX3n/99ZdW+82aNQuRkZGwt7dH9+7d4ezsjLNnz2LJkiXY\nuXMnfvvtN7i5ucntr1y5gpCQECQnJ8PPzw9vv/02AODSpUv46quvMGjQINja2gJ4fDEWGhqKzMxM\n9OjRAz4+PkhISMD333+PqKgo7NixAx07diwWU2xsLGbPno3AwECMGDECV69exbZt2xAaGoozZ86o\nfbOcmpqKwMBAXLlyBa1bt0bbtm1x48YNjBw5Eh06dNDqvfjmm28AAO+//z4sLS1LbBcZGYn//ve/\n2Lt3L65evYpatWqpbd+yZQv27NmDHj16qF3UlyXW69evIyQkBAkJCWjbti06d+6MrKws7Nq1C/37\n98fkyZMxefLkYvslJCSgZcuWaNiwId58801kZmY+8zUBj0dnRo8ejWXLlqF169bFti9btkxuV0Tb\n/lOSN998E+vWrUONGjUwbNgwmJiYYOfOnXj//fcRHR2NXbt2wcjISG4fGxuLLl26IC0tDW3btkWf\nPn2Qk5ODuLg4fPHFFxg/fjxsbGzk9k9OJxsyZAgkScKhQ4fQu3dvNGnSRN5ma2uLkSNHYs6cOVi6\ndCkGDx5cLNalS5cCAEaOHPnc1/U8RSNDZmZmavXr169HeHg4zM3N0atXL9SsWRPx8fHYsGEDoqKi\ncPDgQfj6+gIAHj58iMDAQCQmJqJDhw7o1asXACA5ORn79+9HaGgoGjdurHb8p6fXxcfHo1WrVkhL\nS0PXrl3RtGlTJCQkoHfv3ujatWuJ8Ws7TS8yMhJGRkZo1aoV3NzckJGRgf3792PcuHE4ceIE1q9f\n/9xjfPPNN3j77bfh7OyMHj16wNHREampqfjzzz+xdOlSREZGahUTEZUzQURUCqdPnxampqZCoVCI\ngQMHiq1bt4rExERRWFhY4j6HDh0SkiSJwMBAkZGRobZt7dq1QpIk0bdvX7X6Vq1aCUmSxPTp04sd\nLyMjQ2RlZQkhhCgsLBQNGzYUkiSJNWvWqLXbt2+fUCgUwtHRUTx8+FCuX7lypZAkSUiSJFavXq22\nz9KlS4UkSeKdd95Rqx8+fLiQJEmMGTNG4/shSZKYMmVKie9Bkby8PPn9S0hIeG77ovdh3bp1ct3k\nyZOFJEnCyMhI7Nmzp9g+ZYk1NDRUGBkZiY0bN6rVZ2ZmCj8/P6FQKMTZs2fl+piYGPk9nDRp0nNf\nx5MyMjKEpaWlUCqVIj09XW1benq6vK2or5Sl/wQHBwuFQqFWt3HjRiFJkmjSpIm4f/++XJ+bmytC\nQ0OFJEli7ty5cv2jR4+Eu7u7UCgUYu3atcVex61bt0R+fr5crlWrlvDw8FBrU/RZPd3PivTs2VNI\nkiTOnTunVp+dnS3s7OyEg4ODyM3N1bjvk65cuSIkSSp2fiEef1YKhUJYWlqK27dvy/Xx8fHCzMxM\n1K1bV9y4cUNtn4MHDwpjY2PRrFkzuW7nzp1CkiQxbty4YucoLCxU+yyL4hkyZIhau44dOwpJksT8\n+fPV6n/88ccSfyclSRIhISEaX3fR+3vo0CG1+sTERI0xvvnmm0KSJPHbb7+pbSuqv3r1qlzn5+cn\nzM3N1d6zInfv3tUYDxHpD5MZIiq1zZs3CxcXF/niQ5IkoVKpRPfu3cXGjRuLJTZ9+vQRkiSJ8+fP\nazxe06ZNhbGxsZygxMbGCkmShK+v73NjOXz4sJAkSbRo0ULj9r59+wpJksSGDRvkuqJkJigoqFj7\nvLw8YWxsLAICAuS63NxcYWlpKaytrYtdfAshxNChQ0udzNy6dUtIkiQUCoV49OjRc9v3799fSJIk\n5syZI9cVXcD16dOnWPuyxHru3DmNCUGRoovYCRMmyHVFyYyLi0upLrafNmzYMCFJkli8eLFa/eLF\ni4UkSSI8PFyuK23/eTJB0ZTMdOjQQUiSJH766adixyh6D+rXry/Xbd26VUiSJHr06FGq11SWZOan\nn34SkiSJUaNGqdWvXr1aSJIkPvjgg1Kduyh5sLW1FZMnTxaTJ08WkZGRom/fvsLY2FiYmpqKVatW\nqe0TEREhJEkSUVFRGo/56quvCkmSxIULF4QQ//SDyMjIUsfzZDJz7do1IUmScHd3FwUFBcX2ad++\nvc6SmZKcOnVKSJIkpk2bplZfUjKjVCpFWlpaqY5NRPrFaWZEVGr9+vXDq6++ipiYGBw5cgSnT5/G\n4cOHsXv3buzevRurVq3Czp07YWJiAuDxfTbGxsbYtm2bxvsvHj16hIKCAly6dAlNmzbFb7/9BgDo\n1KnTc2P5/fffAaDE+3Q6dOiA77//HqdPn8brr7+uts3f379Ye2NjYzg5OeHevXty3cWLF5GdnY3A\nwECNqzO1bdsWK1eufG6suta8efNidWWJtejelYyMDHz22WfF9rlz5w4AIC4urtg2X19f+XPWxogR\nI7BixQosX74c77zzjlyvaYqZNv3Hz8+vxHP+/vvvkCRJ4/0XPj4+cHBwQHx8PB4+fAhLS0u5Hz5r\n+tOL6tKlC2rXro1169Zh9uzZ8hS9pUuXQqFQ4D//+Y9Wx8vIyJDv0yliZGSEdevWoV+/fmr1RZ/7\noUOHEBsbW+xYRdMW4+Li0KBBA7Rr1w5ubm6YNWsWYmNj0a1bN7Ru3Rp+fn5qU/NKcvr0aQBA69at\nNT4DqG3btoiJiSndC32Ou3fvYs6cOdi9ezcSExPx8OFDte3Xr19/7jEGDhyI8ePHo2HDhggLC0NQ\nUBACAwPh4uKikxiJSLeYzBCRVoyNjdGxY0f5XpTCwkJs27YNQ4cOxZ49e7BkyRKMGTMGwOMLi4KC\ngmc+qFGSJGRlZQGAfHN/ae6BKHoWi7Ozs8btRfVPLxgAQL7nRtNrKygoKHYOJycnje1LqtekWrVq\nMDExQX5+PpKTk1G3bt1ntr927RoAwNXVtdg2Ta+5LLEWPfNl//792L9/v8b9JEnCgwcPShLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c5d1898>"
+        "<matplotlib.figure.Figure at 0x7f4000d7f898>"
        ]
       }
      ],
@@ -1638,7 +1638,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzEAAAGkCAYAAAABoqtZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c4e7588>"
+        "<matplotlib.figure.Figure at 0x7f4000cfb2e8>"
        ]
       }
      ],
@@ -1676,7 +1676,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAz4AAAGkCAYAAADwqfDUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c574588>"
+        "<matplotlib.figure.Figure at 0x7f4000d51c88>"
        ]
       },
       {
@@ -1684,7 +1684,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAA0AAAAGxCAYAAABLMtbXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c499d68>"
+        "<matplotlib.figure.Figure at 0x7f400dcac588>"
        ]
       }
      ],
@@ -1724,7 +1724,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAA0sAAAGkCAYAAADgyb4IAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmYjfXj//HnObOdM4sZM2axb5mylITsZFfZshMie9ao\nKUuMPRLqI6SEiJKsZd/DJJQK2bJkG02MMTNmPef+/eHr/JpQI8aZ5fW4Ltdl7vt97vO6p7txXnPf\n9/s2GYZhICIiIiIiImmYnR1AREREREQkM1JZEhERERERuQOVJRERERERkTtQWRIREREREbkDlSUR\nEREREZE7UFkSERERERG5A5UlERERERGRO3BaWZo4cSIVK1bE19eXoKAgmjZtyuHDh28bFx4eTv78\n+fH09KR27docOXIkzfqkpCT69+9PYGAg3t7eNGvWjAsXLqQZEx0dTadOnfDz88PPz4/OnTsTExOT\nofsnIiIiIiJZm9PK0o4dO+jXrx8RERFs3boVV1dX6tWrR3R0tGPMpEmTmDp1KjNmzGDfvn0EBQVR\nv3594uLiHGMGDRrE8uXL+fzzz/n222+5fv06jRs3xm63O8Z06NCBgwcPsmHDBtavX88PP/xAp06d\nHur+ioiIiIhI1mIyDMNwdgiA+Ph4fH19WbVqFc8//zyGYZAvXz4GDBjA0KFDAUhMTCQoKIgpU6bQ\ns2dPYmJiCAoKYv78+bRv3x6A8+fPU7hwYdatW0eDBg349ddfKV26NLt376ZKlSoA7N69mxo1anD0\n6FFCQ0Odts8iIiIiIpJ5ZZp7lq5fv47dbid37twAnD59msuXL9OgQQPHGIvFQs2aNdmzZw8ABw4c\nICUlJc2YAgUKULJkSSIiIgCIiIjA29vbUZQAqlatipeXl2OMiIiIiIjI37k6O8AtAwcOpFy5co5S\nExkZCUBwcHCacUFBQVy8eNExxsXFhYCAgDRjgoODHa+PjIwkMDAwzXqTyURQUJBjzC26j0lERERE\nJOvx9fXNkO1mirI0ePBg9uzZw65duzCZTP86/t/GZJIrC0VEREREJAtz+mV4r776Kl988QVbt26l\nSJEijuUhISEAXL58Oc34y5cvO9aFhIRgs9m4cuXKP46JiopKs94wDP744w/HGBERERERkb9z6pml\ngQMH8uWXX7Jt27bbJlooWrQoISEhbNy4kfLlywM3J3jYtWsXU6ZMAaB8+fK4ubmxcePGNBM8HD16\nlKpVqwJQpUoV4uLiiIiIcFziFxERQXx8vGPMnWTUqTyRzGT//v1UqFDB2TFEHgod75JT6FiX7Ob8\n6TN88PoQjCPf425PAeCaNTdjt3+X4e/ttLLUt29fFi1axMqVK/H19XXcP+Tj44OXlxcmk4lBgwYx\nYcIEHnvsMUqUKMG4cePw8fGhQ4cOwM1C061bN8LCwggKCsLf35/BgwdTtmxZ6tWrB0DJkiVp1KgR\nvXr1Ys6cORiGQa9evWjSpAklSpRw1u6LiIiIiMg/OH/iN1aMD+fS3q24GTYAkvzz82T7brTq3YMb\nN25keAanlaVZs2ZhMpmoW7dumuXh4eGMHDkSgLCwMBISEujbty/R0dFUrlyZjRs34uXl5Rg/ffp0\nXF1dadu2LQkJCdSrV49Fixalua9p8eLF9O/fn4YNGwLQrFkzZsyY8RD2UkRERERE0isxMZEtX3/D\n/k8/IeX4j5ix4wokBBfl2YFvUvuFpuma4+BByTTPWcoM/jobni7Dk5xAl2pITqLjXXIKHeuSVX01\nfwGb5nxA4NVzmDAwMJFS6DHKte/C861b4u3tnWb8w/jsnilmwxMRERERkZzFMAxsNhtfzJ7D7oUf\nkSfmEkGAzWTmev6SlGvVlvYvdcZqtToto8qSiIiIiIg8VDabjSnDhnNu89f4x/9JHiDF7EpUvlB6\njR5PxWpVnB0RUFkSEREREZGHxJaSwjez57Bl7v/wTbyGP5Dk4s6N4mV5ZfxEHitT+qHek/RvVJb+\nA7vdTnJysrNjiNy3woULk5iYiMlkwt3dPVP9cBIREZHsIzH+Bqvff49zqz8jJvpPfIEbrlYsT9Wk\n35ixFCxSyNkR70hl6R7Z7XaSkpKwWCz6YClZnsViAW6eCk9MTMTDwwOz2enPqhYREZFs4krkZeaN\nHsWNvVtIvRELwA0PH3JXb0DbPn0oXaaMkxP+M5Wle5ScnKyiJNmOi4sLFovF8YsAERERkftxcN9+\nPnhrOP7nfsXDdvOKLFuuQIo834aW/V7BPyDAyQnTR2XpP1BRkuxIx7WIiIjcrzNHj7No1HDif4kg\nrz0VAM98RSnZoQeNOnfEw93dyQnvjcqSiIiIiIjclzOHj/BF+HBif9mLGTtuQJRvPl4cMZZqjZ/L\nsr+UVVkSEREREZH/5MdtO4iYNY1rh/eRaLNhwoStUEnq9B1M3WZNnB3vvqksiYiIiIhIutlsNjYs\n+ZyfFn1EwpmjANgxYy/+JA0HvEbNBnWz7Jmkv1NZkkwjPDycMWPGEBkZSVBQkLPjiIiIiMhf2Gw2\n1s//lHWzpuEf9wcAqSZXfJ+qQYMBg3ny6QrZpiTdorIkDnv27GHTpk0MGjQIX19fZ8cRERERkUwg\n9vp1ti1cxN5PZ+ESE4U/kGx2J6ByPRq/OoSSj5d2dsQMo7IkDnv27GH06NF07dpVZUlEREQkh7t+\nLYYl77zDmXXLcLtxDRcgwdVCSM3naDnkNYoUL+bsiBlOZUluYxjGv45JSEjAarU+hDQiIiIi8jBd\nvnCRDTM/4NTapdgTYnED4ty9Kd6oJR2HDcPXL+f8Ut3s7ACSOYSHhxMWFgZA0aJFMZvNmM1mduzY\nQZEiRXj22WfZsmULlSpVwmq1MnnyZABWr15NkyZNKFiwIBaLhSJFihAWFkZSUtJt73H8+HHat29P\nUFAQVquV0NBQXn311X/MdfHiRUqVKkVoaCjnz59/8DsuIiIiIgCcO32GUR07MK1hFU5+NRd7Qiwx\nFl8KtOvL+O9+oe/kSTmqKIHOLMn/admyJSdOnGDJkiVMnz6dPHnyAFCyZElMJhMnT56kdevW9OzZ\nkx49elCoUCEA5s+fj9VqZeDAgfj6+hIREcG0adM4d+4cS5YscWz/8OHDVKtWDVdXV3r27EmxYsU4\nffo0S5cuZdq0aXfMdPbsWerWrYvFYuHbb78lODg4478RIiIiIjnM2aPH+XrK21yM2ISLLQV3wCO4\nEMHPtuLFAf2xeubcq4lUljJYuYUnMmzbP3Yq8cC29fjjj1OuXDmWLFlC8+bNHWUIbl6W99tvv7F6\n9WoaN26c5nWfffZZmsvxevToQYkSJRgxYgTvvPMOBQoUAKBv377Y7XYOHDhA4cKFHePHjx9/xzwn\nT56kbt26BAQEsGnTJgICAh7YvoqIiIgIHPp+HyveHkfir/twMey4AFG5QqjcsTsd+/bBxcXF2RGd\nTmVJ0qVgwYK3FSXAUZTsdjuxsbGkpKRQrVo1DMPgxx9/pECBAkRFRbFz50769euXpijdzZEjR+jQ\noQOFChViw4YNmmxCRERE5AHat2Ub66ZOJOW3XzBhYMZEcv5QyrbrwqiXX1JJ+guVpQz2IM/+OFOx\nYnee7eTQoUOEhYWxY8cOEhIS0qyLiYkB4NSpUwCUKVMmXe/VtGlTgoKC2Lx5M97e3veRWkREREQA\nUlNTWTFvAT8umYfrxZMAGJhJLlKG5mEjqFKnlpMTZk4qS5Iud5r5LiYmhtq1a+Pj48OECRN45JFH\nsFqtnD9/ni5dumC32//Te7Vu3Zp58+Yxf/58+vXrd7/RRURERHIsm83Gqo8/Zv+ij3GNOocrYDO5\ncKNIGap1fpnmrVvi6qpKcDf6zojDvT5xedu2bVy5coXly5dTo0YNx/JNmzalGVe8eHEAfvnll3Rt\nd+LEiVgsFgYOHIi3tzddunS5p1wiIiIiOZ3dZuPrD+dwfOk8rkf+jiuQbHbD+mR1Xhw+ikdLP+bs\niFmCypI4eHl5AXD16tU0Ezzcza3rWf96BslutzN16tQ04/LkyUOtWrWYP38+Q4YMoUiRIo51hmHc\nsaR98MEHxMfH06NHD7y8vGjduvV/2SURERGRHCUlKYkv3pnCiVWLMWKvAJDqZqV4w5Y0f3MYAXn8\nnZwwa1FZEoeKFSsCMHToUNq3b4+7uzt16tS56/jq1asTEBDASy+9RP/+/XF1dWXZsmXEx8ffNvZ/\n//sf1atXp3z58vTq1YuiRYvy+++/88UXX3D8+PE7bv+TTz4hLi6Ojh074uXlxXPPPfdgdlREREQk\nm7l84Twz3xqJ5Zc9JMReAyDezZOQZ5rQaehQQvKFODlh1qSyJA7ly5dn4sSJzJw5k5dffhnDMNi6\ndetdL8/LnTs333zzDUOGDGHUqFH4+PjQsmVLevfuzRNPPJFmbJkyZfjuu+946623+PDDD0lISKBQ\noUI0bdrUMcZkMqV5L7PZzJIlS2jWrBmtW7fmm2++4ZlnnsmQfRcRERHJiqIuXOSjt4Zzbe9WLLYk\nEoAbVj8K1H+B7n17UygdMxHL3ZkMwzCcHSKzuDV7G3DX6aoTExOxWCwPK5LIQ6XjW7Kz/fv3U6FC\nBWfHEMlwOtZzht8OH2HzjOmc3rEOd3sKANe8Aqj0Yk9a9OmF1Zr9/z1Pz2f3+6UzSyIiIiIiWcQP\nu3Yzb8wocp37FRfDhjvwp08wFdu/TKcBfTWz3QOm76aIiIiISCa3a916Fk4cQ+Afp8nNzQvDTAUf\no2Tbl2jVpZNKUgbRd1VEREREJJP6aet2dn8whcjD+wkG7Ji4lKcond8aS42G9ZwdL9tTWRIRERER\nyURSU1PZ+dVX7J7zPikXfgNuPkj2cnBxek2YQsWqTzs5Yc6hsiQiIiIikgkkJSby6ZR3+WLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c47a518>"
+        "<matplotlib.figure.Figure at 0x7f4000c7b128>"
        ]
       },
       {
@@ -1732,7 +1732,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAA0kAAAGxCAYAAAC3J/0dAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed557b0f60>"
+        "<matplotlib.figure.Figure at 0x7f400e07e1d0>"
        ]
       }
      ],
@@ -1765,7 +1765,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAGNCAYAAADKNkSkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c5c84e0>"
+        "<matplotlib.figure.Figure at 0x7f400de0bac8>"
        ]
       }
      ],
@@ -1833,7 +1833,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyIAAAGNCAYAAADtmMVMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed55732b38>"
+        "<matplotlib.figure.Figure at 0x7f4000e0c710>"
        ]
       }
      ],
@@ -1866,7 +1866,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzsAAAGkCAYAAAAWgDuQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c47ae48>"
+        "<matplotlib.figure.Figure at 0x7f4000c7b2b0>"
        ]
       },
       {
@@ -1874,7 +1874,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzMAAAGxCAYAAABWTOhMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c5a28d0>"
+        "<matplotlib.figure.Figure at 0x7f4014114470>"
        ]
       }
      ],
@@ -1909,7 +1909,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzsAAAGkCAYAAAAWgDuQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c52b860>"
+        "<matplotlib.figure.Figure at 0x7f4014114e48>"
        ]
       },
       {
@@ -1917,7 +1917,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzMAAAGxCAYAAABWTOhMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c3af400>"
+        "<matplotlib.figure.Figure at 0x7f4000d20710>"
        ]
       }
      ],
@@ -1950,7 +1950,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzsAAAGkCAYAAAAWgDuQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd0VNX+/vH3TNqEVBJSIIHQErqIoNIREoqCNFEEUbFQ\npAiiRkEuoCIIKiJSVCwgSBew0jvGAojSm9SEJAQIgYT0Ob8/+DFfIsUAgRmS57VW1mLO2efM5+w7\n9955Zu+zj8kwDAMREREREZFCxmzvAkRERERERG4FhR0RERERESmUFHZERERERKRQUtgREREREZFC\nSWFHREREREQKJYUdEREREREplBR2RERERESkUHK4sDN69GjMZjP9+/fPs33EiBGEhIRQrFgxmjZt\nyq5du/Lsz8zMpH///gQEBODp6Um7du2Ii4u7naWLiIiIiIgDcaiw89tvvzF16lTuuusuTCaTbfuY\nMWMYN24cEydOZNOmTQQGBtK8eXNSU1NtbQYOHMjChQuZM2cOGzZs4OzZs7Rp0war1WqPSxERERER\nETtzmLCTkpJCt27d+OqrryhevLhtu2EYjB8/nsGDB9OhQweqVavG9OnTOXfuHLNmzbId++WXX/L+\n++8TGRlJrVq1mDFjBtu2bWPlypX2uiQREREREbEjhwk7PXv25NFHH6VJkyYYhmHbfujQIRITE2nR\nooVtm8VioXHjxsTExACwZcsWsrOz87QJDQ2lSpUqtjYiIiIiIlK0ONu7AICpU6dy8OBB20jNpVPY\nEhISAAgKCspzTGBgIMePH7e1cXJywt/fP0+boKAgEhMT82xLSUkp8PpFREREROTW8/Hxua72dg87\ne/fu5Y033mDjxo04OTkBF6auXTq6czWXhiIREREREZFL2X0a26+//srJkyepVq0aLi4uuLi4sH79\neiZPnoyrqyslSpQAuGyEJjExkeDgYACCg4PJzc3l1KlTedokJCTY2oiIiIiISNFi95GdDh06cN99\n99leG4bBM888Q0REBEOGDCE8PJzg4GCWL19O7dq1AcjIyGDjxo28//77ANSuXRsXFxeWL19Oly5d\nAIiNjWXPnj3Ur1//qu99vcNgcnM2b95MnTp17F1GkaN+tw/1u32o3+1D/W4f6nf7UL8XjD8T0+mz\nKo4yXi580TIUL1enq7a9mdtQ7B52fHx8LgsdxYoVo3jx4lStWhW4sKz0qFGjqFy5MuHh4YwcORIv\nLy+6du1qO8dzzz1HdHQ0gYGB+Pn5MWjQIGrWrElUVNRtvyYREREREbmy/cmZDFhznMxcg7sCLHi6\n3LrJZnYPO1diMpny3I8THR1Neno6ffv2JTk5mbp167J8+XI8PDxsbcaPH4+zszOdO3cmPT2dqKgo\nZs6cqft6REREREQcxPHUbPqsiiM120qzMh4Mvi/wln5fd8iws2bNmsu2DR8+nOHDh1/1GFdXVyZM\nmMCECRNuZWkiIiIiInIDTmfk0GdVHCfTc6kT5M6ohsE4mW/twIRDhh0REREREblz/bhwIQdi1lHM\nZOCBFUtuLvsSz9EoK5Ouzrnc7Wkl+Zt0fDp0w739k7esDoUdEREREREpMHv+3sofowZDagqn/7Uv\nHUgBdvz/1w2CK9BSYUdERERERBxddnY2S975H6Sm8EDFMMrdXZtfkg12pJk4b3aibpgPZhdn0jCR\nlgvFH3jgltajsHMNVquVrKwse5dRaISFhZGRkWHvMoqcS/vd1dUVs9nuj9cSERGRQmrj7Okkb9tC\nkMWNxuOnMS65BLP3nMHDxczU5iFU8bfc1noUdq7CarWSmZmJxWLRim4FxGK5vR9uueBivxuGQUZG\nBm5ubgo8IiIiUuBOn0hkw+RxgMFDTz/L9PQgZu85hYvZxLgmJW970AHQN56ryMrKUtCRQsVkMmGx\nWDRaKSIiIrfEkreHkHPmNHeVLcO2li8w8a9TmIB3GgZxX8lidqlJIzvXoKAjhY0+0yIiInIr7F27\nkr2rluBmNhPQbySD/kwB4PX7Amge5mW3ujSyIyIiIiIiNyw7M5Of3x4MVit3RT7IqynlsRrQ6y4/\nHqvka9faFHZEREREROSGbRw3kuS4Y/j7+vLRPX3Jtho8XsmHXnf52bs0hR0REREREbkxp/ftYsOs\n6QDsiezLKWcvWpfz4tV7Axxi+rzCjtxWI0aMwGw2c+LECXuXIiIiIiI3wTAMlg4ZSE52Fk7la/Jb\n5VY0DvFgeP0gzA4QdEBhp8iJiYnhzTffJCUlxd6liIiIiMgdbN83U9mzYxuGi4XVDw7mnkB3xjQO\nxsXsGEEHFHaKHIUdEREREblZ2adO8PNHYwGIrduZUuXLM75pSSzOjhUvHKsauW0Mw/jPNunp6beh\nEhERERG506z/30skn0slzT+M0616MKlZKbxcnexd1mUUdoqQESNGEB0dDUC5cuUwm82YzWbWrVtH\n2bJlefDBB1m1ahX3338/7u7ujB17Ia1///33PPzww5QuXRqLxULZsmWJjo4mMzPzsvfYt28fXbp0\nITAwEHd3dyIiInjppZeuWdfx48epWrUqERERxMbGFvyFi4iIiEiBSVr1EzFrVpNjcuJw+2imtAzD\nz90xH9/pmFXJLfHII4+wf/9+Zs+ezfjx4ylRogQAVapUwWQyceDAAR599FF69uxJjx49KFOmDADT\npk3D3d2dAQMG4OPjw6+//sqHH37IsWPHmD17tu38O3fupEGDBjg7O9OzZ0/Kly/PoUOHmDdvHh9+\n+OEVazpy5AiRkZFYLBY2bNhAUFDQre8IEREREbluhmFg3fM3340YTLZhcOKu5rzX82FKebrYu7Sr\nUtgpALVm7L+l59/6ZHiBnKdGjRrUqlWL2bNn0759e1uYgQsf3n/++Yfvv/+eNm3a5Dnum2++wd3d\n3fa6R48ehIeHM3ToUN577z1CQ0MB6Nu3L1arlS1bthAWFmZr/84771yxngMHDhAZGYm/vz8rVqzA\n39+/QK5TRERERAqOkZnB+VXfs23m5/y1azfxGdmkeJSgx6hRlPdxtXd516SwIzalS5e+LOgAtqBj\ntVo5d+4c2dnZNGjQAMMw2Lp1K6GhoSQlJbF+/Xr69euXJ+hcza5du+jatStlypRh2bJl+Pj4FPj1\niIiIiMiNsybE8s/Xn7D1x0XsTjpNrmGQ4eTGoeDqdHplMPdXLGXvEv+Twk4BKKiRF3srX778Fbfv\n2LGD6Oho1q1bd9miBRdXdTt48CAA1atXz9d7tW3blsDAQFauXImnp+dNVC0iIiIiBcWwWklev4w/\nv57K35v+ICU7B4B07xLsK3MfR+9pxwddm9CsrK+dK80fhR2xuXSq2kUpKSk0bdoULy8vRo0aRcWK\nFXF3dyc2Npbu3btjtVpv6L0effRRvvrqK6ZNm0a/fv1utnQRERERuUnHV/7E8lFDOXg8/sIGsxPF\nq9xFdoP2LPaqi3MxL95tFEyzsl72LfQ6KOwUMabrfJrtmjVrOHXqFAsXLqRRo0a27StWrMjTrkKF\nCgBs3749X+cdPXo0FouFAQMG4OnpSffu3a+rLhEREREpOKnHDjEzuj+p58/j7OlN1abNuafb82wr\nVo43f0vCCfhf3UBa3kFBB7T0dJHj4eEBwOnTp/PV3snpwnrpl47gWK1Wxo0bl6ddiRIlaNKkCdOm\nTePw4cN59l3tmT6TJk3iySefpEePHsyfPz+/lyAiIiIiBchqtfLdoN6knj9PWJVqvLruTzq9N4l/\nfCvy9u9JALxSpwQdwu+8e6w1slPE3HvvvQAMHjyYLl264OrqSrNmza7avmHDhvj7+/P000/Tv39/\nnJ2dWbBgAWlpaZe1/fjjj2nYsCG1a9emV69elCtXjqNHjzJ37lz27dt3xfN/+eWXpKam0q1bNzw8\nPHjooYcK5kJFREREJF82T/mAvdv/xuLuTsdxn+Du4cmGuDSGbEzAakDvmn48UaW4vcu8IRrZKWJq\n167N6NGj2bVrF88++yxPPPEEu3fvvur0tuLFi/PTTz9RunRphg8fzrvvvkvNmjX5+uuvL2tbvXp1\nfvvtN5o1a8ann37KgAEDmD9/Pm3btrW1MZlMed7LbDYze/ZsIiMjefTRR1m7dm2BX7OIiIiIXFnS\nrh0s+3QiAG1ejKZ4uXA2J57n1XXx5Fjhyaq+9KzhZ+cqb5zJuNoco0Lq4uphwDWXO87IyMBisdyO\nkkRuK322b4/NmzdTp04de5dR5Kjf7UP9bh/qd/soTP2ek53N1HbNiD+4n5r33k/Hrxez81QmvVbE\ncj7HoGNFb4bWDbzue74LWn6/v1+JRnZERERERIqgVWOGE39wP8W9vWj9wSccOJNF31VxnM8xaFXW\nkyH32z/o3CyFHRERERGRIubgbxuJmT0DEyYeGfIWCW7+9F4Zx9ksK41DPXirQTBO5js76IDCjoiI\niIhIkXI+NZWFQ17CyM2mSWQU5shO9FoZx+mMXO4Pdmds42BcCkHQAa3GJiIiIiJSZBiGwfcjXuPs\n8WOElvCj8v/G8fyKWE6cz6FWoIUPHyiFm1PhGQ9xiCuZNGkSNWvWxMfHBx8fH+rXr8/PP/9s29+9\ne3fMZnOev/r16+c5R2ZmJv379ycgIABPT0/atWtHXFzc7b4UERERERGH9dfSH9n182JczWZaDB1L\n79/SiE/LoUYJCx83C8HdxSHiQYFxiKspXbo0Y8eOZevWrWzZsoVmzZrRvn17/v77b+DCcsXNmzcn\nISHB9ndpGAIYOHAgCxcuZM6cOWzYsIGzZ8/Spk2bPA/DFBEREREpqk6dSOSnd4aCNZfmD7fj5awa\nHDuXTWU/NyZFlsKjkAUdcJBpbJc+hwVg5MiRTJkyhT/++IOaNWtiGAaurq4EBgZe8fiUlBLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c52b780>"
+        "<matplotlib.figure.Figure at 0x7f4000d20ba8>"
        ]
       },
       {
@@ -1958,7 +1958,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAzsAAAGxCAYAAABFm6i4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed5554d780>"
+        "<matplotlib.figure.Figure at 0x7f400dca50b8>"
        ]
       }
      ],
@@ -2083,7 +2083,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyYAAAGNCAYAAADkc2U2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed5551ec50>"
+        "<matplotlib.figure.Figure at 0x7f400de127b8>"
        ]
       }
      ],
@@ -2243,7 +2243,7 @@
       "print('std: {:.3f}'.format (np.std(res)))\n",
       "\n",
       "plt.plot(xs[:,0], label='Kalman filter')\n",
-      "plt.plot(zs[:,0],linestyle=':', label='wheel')\n",
+      "plt.plot(zs[:,0], linestyle=':', label='wheel', lw=5)\n",
       "plt.legend(loc=4)\n",
       "plt.show()"
      ],
@@ -2260,9 +2260,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyYAAAGNCAYAAADkc2U2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd8FVX+xvHPmZub3PQGSegECARCUxARXRQVrICggqKi\n4tqWtay7sooFLIviYkdX3Z8FC2tvq6JZFxVYFEFBpPcOAdJ7cu+c3x/BYFZklYTcJDzvf+TOnJn5\nHl5juE/OnDnGWmsREREREREJIifYBYiIiIiIiCiYiIiIiIhI0CmYiIiIiIhI0CmYiIiIiIhI0CmY\niIiIiIhI0CmYiIiIiIhI0CmYiIiIiIhI0B00mMyZM4dhw4bRunVrHMdhxowZP2kzefJkWrVqRURE\nBIMGDWLFihU19peXl3PdddfRvHlzoqKiGD58ONu3b6/bXoiIiIiISKN20GBSXFxMz549efTRRwkP\nD8cYU2P/1KlTeeihh5g+fToLFy4kKSmJwYMHU1RUVN3mxhtv5O233+bVV19l7ty5FBQUcPbZZ+O6\n7uHpkYiIiIiINDrml678Hh0dzRNPPMHYsWMBsNbSsmVLrr/+em699VYAysrKSEpKYtq0aVx11VXk\n5+eTlJTECy+8wIUXXgjAtm3baNeuHbNmzWLIkCGHqVsiIiIiItKYHPIck40bN5KVlVUjXPh8PgYO\nHMj8+fMB+Oabb6isrKzRpnXr1nTt2rW6jYiIiIiISMihHrhr1y4AkpOTa2xPSkpix44d1W08Hg+J\niYk12iQnJ5OVlVVjW35+/qGWIiIiIiIiQRQbG1vrcxyWt3L991wUERERERGRgznkYJKSkgLwk5GP\nrKys6n0pKSkEAgGys7NrtNm1a1d1GxERERERkUN+lCs1NZWUlBQyMzPp06cPUDX5fd68eUybNg2A\nPn364PV6yczMrDH5fdWqVQwYMOBnz10XQ0EiP7Zo0SL69u0b7DKkidF9JYeD7is5XHRvSV2r66kY\nBw0mxcXFrF27FgDXddm8eTNLliwhMTGRNm3acOONNzJlyhTS09NJS0vj3nvvJTo6mjFjxgBVAeOK\nK65gwoQJJCUlkZCQwE033USvXr049dRT67QjIiIiIiLSeB00mCxcuJCTTz4ZqJo3MmnSJCZNmsRl\nl13Gc889x4QJEygtLWX8+PHk5ubSv39/MjMziYyMrD7HI488QkhICKNHj6a0tJRTTz2Vl19+WfNQ\nRERERESCKOBadhX7aRXtDXYpwK9Yx+Rw+/FQkB7lkrqm4Ws5HHRfyeGg+0oOF91b8oPiSpf31hXw\nj1V5GCzvDG+Px/n1gwZ1/f39kOeYiIiIiIhI45FVXMk/VuXz1tp8iipdAFpHeckq8dMyKvijJgom\nIiIiIiJN2PLsMl5Zkce/Nhfiui7nrc9kff+hjMloxomtIw9ptORwUDAREREREWli/K7l861FzFyV\nx+LdZQB4DAxuH834Zd8S5W2D0/acIFdZk4KJiIiIiEgjZsvLsLPfxzljFIUVAd5bmc3yufP5ODYD\ngBOzv+fkZnDMiKG0iPRiW02AstIgV/1TCiYiIiIiIo2ILSuFJV9i+le9PZeiAipf+z8eSjiJf24o\nILIwm5fmPcbyC55jTHocwwIdCXv4FpxRZwFgOnYNYvU/T8FERERERKSBs3t2QrOU6iU33Mcm4XQ7\nmuUVPl5ekE3rloN4fU3VW7JOSIrA7dWfd4e3wzEGiMP+fhJ4GvZX/4ZdnYiIiIjIEcju2AzxzTDh\nVesDuneNx/nTVGifhvGFk3XGpTzz6TreK44FQgjrfj4jU6O5MD2OTvFhcE6PGuczvfsHoRe/joKJ\niIiIiEiQ2W0bITwSk5gEgPvsNJxTz4HjTgHAHH08bN/E8qg2PLU0m3mcCMUQHmK4oEscF3eLI8HX\nuL/aN+7qRUREREQaOVteivuXGzCnn48ZfgkApu9vsCXF/PAi35XDxvP00mzmztoKVAWS0V3iuKQJ\nBJIfNI1eiIiIiIg0UiYsHGfaK9hFc6u3OWeMAmBtbjlPLMnmi23FAPg8hgvSm1Yg+UHT6o2IiIiI\nSCNiXRfjOJjIaMyJZ1Zv31pYwVPf5TBrYyGWqkAyukscYzOaXiD5QdPslYiIiIhIA2dXLcF99kGc\nG+/BtGoPwO4SP88szea9dQX4LYQ4cF5aLFf0SKBZeNP+6t60eyciIiIi0lB16YU5eSh2yVfkJbbh\n+eU5vL46n/KAxTEwrGM0V/dMpGWUN9iV1gsFExERERGRIDDGUDHkPGauzOO5dzdRVOkCcGrbKK7t\nnUiH2NAgV1i/FExEREREROqROy8THIfMFsfy2OK97Cz2AzCgZQTjeyfSLdEX5AqDQ8FERERERKQe\nrfMmEPXEnbzR+2p2Nu9GWlwof+jTjONaRga7tKBSMBERERERqSN25xbs2y/gjL/zJ/u2F1by2OK9\nZG6OJezkvxIV4eOOo5oxvGMMHscc4GxHFgUTEREREZFDZCsrsB+/iTlzNMbjwc7+J4RH7N+/cwvb\nCip4KS+GDV8tYGlsR3yhoVzcI4XLMuKJ9DpBrL5hUTARERERETlUxmC//gLy9mIuuR5z5miwFmst\nX+4swT7+OF+FpPBG2lDuWZfJXWXb8dz/PCmJscGuvMFRMBERERER+ZVswI/xhGBCvDgTHoC9uwAo\ni0rgg40F/GPuZjYWVHKj38fsTgM5t3MsXYf+lZa7VmEUSg5IwURERERE5Few+Tm4t/0W566nMIlJ\nmOhY8kOjmPHtXt5am09BRdVrf5MiQghc+gdeSYslLsxTdXB87yBW3rApmIiIiIiI/AomNgEz6Gxs\n5ttUjLqK11bl83/LcijcF0h6NPNxUdc4Tm4bhVeT2n8xBRMRERERkf/BBgKwcjGme9+qzyMu4+ON\nhUx/bzO79q1D0i8lnPG9E+nZPDyYpTZaCiYiIiIiIv9LXjbuQxNxrriZBR2O59Fv97IqpxyAtLhQ\nbji6GQNaRmCMRkgOlYKJiIiIiMj/YBKT2HL9Q7z9/Q5e3rAdqJpDMr53ImelRmsdkjqgYCIiIiIi\nTYYNBLBffIjp0hPTqn3tzlWYj33zWdadfTVPL89n9tYwIJVIr8PlGfGM6RpHeIjWIakrCiYiIiIi\n0nR8vxA782+YcTdBLYPJurIQypauZtHKB5jd42LCPIbz0mIZ1yOeBJ++Rtc1/Y2KiIiISNPRoy/O\n+Dsg6tDXClmfU8LTy/L51+YiwnpdT1yglAvT47g8I57mEfr6fLjob1ZEREREGj3ruhjHwXhC4KgB\n+7db+4snpK/ILuPVb7dx0Us3sfK4m/HGtOCcLs0Z1z2BJAWSw05/wyIiIiLS6NnHJ2NTWmPOuwLj\n8WDXfI/74mOYISMxA8/42eNca5mzrZiXV+bxTVYpAKFpZ3Lnnn/RduwdJEd666sLRzwFExERERFp\n9MzFv8f9+1RMfg4kNIe8bMzJQzHHDz5g+9JKl39uKOCVlXlsKawEINLrMKJTDGNGXkFKRIhe/VvP\nFExEREREpNEziUl4bnlw/+d+J3GgWLGtsJJ31+Xz5pp88vet1N4iMoRJuZ/TMz4C39HnYxy9aSsY\nFExEREREpFGyJUXYZ6dhLrkOE5d4wDaBgMuGufP4ODKNz3ZWsDG/onpfj2Y+LukWx6A2UXi2DcR9\nfDJ06gLpveupB/JjCiYiIiIi0jiF+SChOe70u/Dc/lj15qKKAF/uLOGLbcUc99YDdN6zhk8G/Jnt\nUSlEeR1+0yqS0emx9Goevv9cbTviTJ2h0ZIgUjARERERkUbJeEIwF43HVlbNEakMWF5amcvfl+ZQ\nFrAALOpyPr4TkjipbQwnto6kd1I43h+t0m6/Xwgdu2IiohRKgkzBREREREQaFbtlPeTnYnr0BcB4\nvXybVcqUBbtZv+9Rrd7NfZzUJoqBrdvRPsb7sxPZ7YLPsI/difPgTExMfL31QX5KwUREREREGpf8\nHNyHJuJcext5PX/Do9/u5b31BQC0ifYysV9z+reMrG5urcUunIP7yZs4E/6KCQ2r3uf8dgL2lOEK\nJQ2AgomIiIiINCqmxzGYB2fy4c4AD76/ibxyF69jGNc9nsu7xxPm+a9HsqzFzvkI59RzIKRqXRJb\nXooJq5pjYlK71HcX5AAUTERERESkUbA7t0JyK9bmV3L/wjIW7y4DoF9KOLf2S6J9bOgBjzOOg/nj\n/fvPU1mBe/0ozGnnYs4Zq7klDYSCiYiIiIg0CoX/9xA79+RxRe8bKfZGkODz8Mc+zTgjNfoXL4Zo\nXRf27sK5+ynsFx+BFlFsMBRMRERERKRB21xQwTNLc8hsezWnM5fK0HAu7BLHNT0TiAnz/OLz2Lxs\n3DuvgZRWeCY+ghl15WGsWn4tBRMRERERaZC2FVby9++zmbUuj0rjISTEQ/iQ4bzfPZ7kSO+vP2Fs\nAs6VE6B737ovVmpNwUREREREGpSV2WW8viafD9YXEFVWwOuf387cs67nlKGn0jLqEALJPsYY6HFM\nHVYqdUnBRERERESCLr88wKyNhby7roDVueUAOAYGdmtFRLfbuGj9tzhRZwS5SjmcFExEREREJChc\na/l6Vynvrsvnsy3FVLhVq7XHhjqc2SGG0V1iaRcTCqTAgBOCW6wcdgomIiIiIlKvskv9vL22gHfW\n5bOz2A+AAY5rEcE5nWI4qU0k3qVfYT9ejj13HMbzyye4S+OlYCIiIiIih521lu/2lPHa6jw+3VKE\n363a3iIyhOGdYhjaIYYW+TugchfGk4Zt0xH79gvQLBlz8rCg1i71Q8FERERERA6bUr/LrI2FvL46\nv8bckZNaR3KlfwVd/Ll4ep4PgPvFl7BlHeba2zHNknEm/y2YpUs9UzARERERkToVcC3f7yLine truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyYAAAGNCAYAAADkc2U2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed56657d30>"
+        "<matplotlib.figure.Figure at 0x7f400de12b38>"
        ]
       }
      ],
@@ -2403,7 +2403,7 @@
       "    print('fusion std: {:.3f}'.format (np.std(res)))\n",
       "    if do_plot:\n",
       "        plt.plot(xs[:,0], label='Kalman filter')\n",
-      "        plt.plot(zs_wheel, linestyle=':', label='wheel', lw=4)\n",
+      "        plt.plot(zs_wheel, linestyle=':', label='wheel', lw=5)\n",
       "        plt.plot(*zip(*zs_ps), linestyle='--', label='PS')\n",
       "        plt.legend(loc=4)\n",
       "        plt.ylim(0,100)\n",
@@ -2424,9 +2424,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyYAAAGNCAYAAADkc2U2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyYAAAGNCAYAAADkc2U2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c5c3278>"
+        "<matplotlib.figure.Figure at 0x7f4000c60320>"
        ]
       }
      ],
@@ -2582,7 +2582,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGGCAYAAAB7Sh5FAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c3eb358>"
+        "<matplotlib.figure.Figure at 0x7f4000c60438>"
        ]
       },
       {
@@ -2590,7 +2590,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAysAAAGGCAYAAAB7Sh5FAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c3ebda0>"
+        "<matplotlib.figure.Figure at 0x7f4000c60198>"
        ]
       }
      ],
@@ -2764,7 +2764,7 @@
       "                     color='green', marker='o', s=75, \n",
       "                     alpha=0.5)\n",
       "\n",
-      "plt.legend([p1, p2], ['Kalman filter', 'idealized'])\n",
+      "plt.legend([p1, p2], ['Kalman filter', 'idealized'], scatterpoints=1)\n",
       "plt.show()"
      ],
      "language": "python",
@@ -2773,9 +2773,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c4d3b70>"
+        "<matplotlib.figure.Figure at 0x7f4000da3e10>"
        ]
       }
      ],
@@ -2960,7 +2960,7 @@
       "    p1 = plt.scatter(x, y, color='green', marker='.', s=75, alpha=0.5)\n",
       "\n",
       "p2, = plt.plot (xs, ys,lw=2)\n",
-      "plt.legend([p2, p1], ['Kalman filter', 'Measurements'])\n",
+      "plt.legend([p2, p1], ['Kalman filter', 'Measurements'], scatterpoints=1)\n",
       "plt.show()"
      ],
      "language": "python",
@@ -2969,9 +2969,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed5546f748>"
+        "<matplotlib.figure.Figure at 0x7f400dfb9da0>"
        ]
       }
      ],
@@ -3099,11 +3099,11 @@
       "    return xs, ys\n",
       "        \n",
       "x,y = solve(x=0, y=1, vel=v, v_wind=0, launch_angle=theta)\n",
-      "p1 = plt.scatter(x, y, color='blue')\n",
+      "p1 = plt.scatter(x, y, color='blue', label='no wind')\n",
       "\n",
       "x,y = solve(x=0, y=1,vel=v, v_wind=mph_to_mps(10), launch_angle=theta)\n",
-      "p2 = plt.scatter(x, y, color='green', marker=\"v\")\n",
-      "plt.legend([p1,p2], ['no wind', '10mph wind'])\n",
+      "p2 = plt.scatter(x, y, color='green', marker=\"v\", label='10mph wind')\n",
+      "plt.legend(scatterpoints=1)\n",
       "plt.show()"
      ],
      "language": "python",
@@ -3112,9 +3112,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed55799f28>"
+        "<matplotlib.figure.Figure at 0x7f400dfb0940>"
        ]
       }
      ],
@@ -3241,7 +3241,7 @@
       "p3, = plt.plot (xs2, ys2, lw=4, c='#e24a33')\n",
       "plt.legend([p1,p2, p3], \n",
       "           ['Measurements', 'Kalman filter(R=0.5)', 'Kalman filter(R=10)'],\n",
-      "           loc='best')\n",
+      "           loc='best', scatterpoints=1)\n",
       "plt.show()"
      ],
      "language": "python",
@@ -3250,9 +3250,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed554d3ef0>"
+        "<matplotlib.figure.Figure at 0x7f400dd9af60>"
        ]
       }
      ],
@@ -3306,7 +3306,7 @@
       "        p1 = plt.scatter(x, y, color='green', marker='o', s=75, alpha=0.5)\n",
       "\n",
       "    p2, = plt.plot (xs, ys,lw=2)\n",
-      "    plt.legend([p1, p2], ['Measurements', 'Kalman filter'])\n",
+      "    plt.legend([p1, p2], ['Measurements', 'Kalman filter'], scatterpoints=1)\n",
       "    plt.show()\n",
       "    \n",
       "plot_ball_with_q(0.01)\n",
@@ -3318,17 +3318,17 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGNCAYAAAB0YBz5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGNCAYAAAB0YBz5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed557c7e10>"
+        "<matplotlib.figure.Figure at 0x7f4000e1db38>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed4c570a20>"
+        "<matplotlib.figure.Figure at 0x7f4000d92eb8>"
        ]
       }
      ],
@@ -3356,17 +3356,17 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed5578f320>"
+        "<matplotlib.figure.Figure at 0x7f40026658d0>"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGNCAYAAADpbRVxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fed5578f710>"
+        "<matplotlib.figure.Figure at 0x7f4000d101d0>"
        ]
       }
      ],

10_Unscented_Kalman_Filters/Unscented_Kalman_Filter.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:5dcd9e2170b6dd3b4854a622f15d1432c9897ce652b0994c6b8ab0a32b67d2a7"
+  "signature": "sha256:d06fb32e6aee455bb9d541df8972b8f773a454b227d9a76a72d950bc93a76084"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -259,13 +259,13 @@
        ],
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 40,
+       "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7facfd875a90>"
+        "<IPython.core.display.HTML at 0x7f7386ca0198>"
        ]
       }
      ],
-     "prompt_number": 40
+     "prompt_number": 1
     },
     {
      "cell_type": "markdown",
@@ -300,7 +300,7 @@
       "plt.scatter(sum(xs)/N, sum(ys)/N, c='r', marker='*', s=200, label='mean')\n",
       "plt.scatter(0, 50, c='k', marker='v', s=200, label='intuition')\n",
       "plt.axis('equal')\n",
-      "plt.legend()\n",
+      "plt.legend(scatterpoints=1)\n",
       "plt.show()"
      ],
      "language": "python",
@@ -309,13 +309,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxoAAAGGCAYAAAD8e/dDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XlYFWX7B/DvzOEsgAhSEsqmgqhombmklpam4lpvWRku\nCaRmkblkipp7Ki65b6mppMWbaYvmArZp/dLKt8XU3BJxSbQUMPVsnJnfH9MZOJzDIhwE5fu5Lq8L\n5syZeYY5yHPP/Tz3I8iyLIOIiIiIiMiNxIpuABERERER3XkYaBARERERkdsx0CAiIiIiIrdjoEFE\nRERERG7ncatOlJOTc6tORUREREREbuTr63vT72FGg4iIiIiI3I6BBhERERERud0tGzqVX2lSL3T7\nOnDgAFq0aFHRzaBbiPe86uE9r3p4z6sm3veqpaxTH5jRICIiIiIit2OgQUREREREbsdAg4iIiIiI\n3I6BBhERERERuR0DDSIiIiIicjsGGkRERERE5HYVUt6WiIiI6HYiyzIsFgtkWa7oplSosLAwmEym\nim4GuYEgCNDpdBAEodzOwUCDiIiIqAiSJMFsNkOn00Gj0VR0cyqUwWCo6CaQm9hsNphMJuj1eohi\n+Qxy4tApIiIioiJYLBYYDIYqH2TQnUWj0cBgMMBisZTbORhoEBERERWjPIeXEFWU8v5cM9AgIiIi\nIiK3Y6BBRERERERux0CDiIiIiIjcjoEGERERERG5HQMNIiIiIqLbwI4dOzB16tSKbkaJMdAgIiIi\nIroNMNAgIiIiIqpkrl+/XtFNcIvbqdQyAw0iIiKiCiLLcoWde8qUKRBFEUePHkX//v3h5+eHmjVr\nYsKECQCAs2fP4oknnoCvry8CAwMxb948h/ebzWZMnToV9evXh8FgQHBwMEaNGgWj0eiw3/r169Gp\nUyfUqlULBoMBkZGRSEpKcrr2kydP4tlnn0Xt2rVhMBgQFBSEp59+GpmZmQCA06dPQxRFJCcnO12L\nKIoOT/rt13b48GEMGDAA/v7+uPfee9XX09LS8Mgjj8DHxwc+Pj7o1q0bfv31V4djxsbGwtPTE2fP\nnkXPnj3h4+ODoKAgLF68GABw8OBBdOzYEdWqVUNYWBg2btzo1K6cnByMGjUKoaGh0Ov1CA8Px5tv\nvglJktR97Nc1e/ZsrF69GuHh4TAYDGjVqhUOHDjg0J7ly5dDlmWIoqj+O3PmDADgiy++QPv27eHv\n7w9vb29ERERg2LBhTm26lTwq9OxEREREVZAsy/jxRxN++01ArVoyHnpIC1/fiumWxcTEoFGjRpg9\neza2b9+OWbNmwdfXF2vWrEGnTp0wZ84cbNy4EWPGjEHz5s3RoUMHyLKMJ598Env37sWQIUMQFRWF\nI0eOYPny5Th8+DBSU1PV4y9fvhxRUVHo2bMnDAYDPv/8c4wfPx45OTmYNWsWAMBqtSI6Ohpmsxmv\nvPIKatWqhT///BOpqam4cOECAgMD1eMV9kTf1fY+ffqgXr16mDlzproC9vvvv48BAwagS5cuSEpK\ngslkwqpVq9CuXTv8+OOPaNCggfp+SZLQvXt3PPzww5g3bx42btyIESNGwNPTE5MnT8aAAQPw9NNP\nY8WKFYiNjUWbNm0QHh4OADAajejQoQPOnDmDoUOHok6dOvj+++8xZcoUZGRkYPXq1Q5t/eCDD3Dt\n2jW89NJLAIA5c+bgqaeewqlTp+Dh4YGhQ4fiwoUL2L17t0NQc/fdd+PIkSPo0aMHmjZtiqlTp8LL\nywsnT55EWlraTX0W3E6+RbKzs9V/VLX8+OOPFd0EusV4z6se3vOqpyrdc6PRWKL9LBabfOyYUf7j\nD5Nss9mK3PeXX4xyjRo2GZBlQJI3bbohS5LkjuaW2OTJk2VBEORBgwap22w2mxwSEiILgiDPnDlT\n3Z6dnS17eXnJ/fv3l2VZlt977z1ZFEV57969Dsd87733ZEEQ5LS0NHWbq5/fkCFD5GrVqskWi0WW\nZVn+5ZdfZEEQ5C1bthTa3vT0dFkQBDk5OdnpNUEQ5KlTpzpd29NPP+2w37Vr1+QaNWrIL7zwgsP2\nrKwsOSAgQO7bt6+6beDAgbIgCPKbb77p9HMQBEF+//331e3Hjh2TBUGQ33jjDXXbjBkzZC8vL/nY\nsWMO55oxY4YsCIK63X5dNWvWdOgnb926VRYEQf7ss8/UbQkJCbIgCE7Xv3DhQlkQBPny5ctOrxWn\nqM93WfvvHDpFREREVEZWqw3//a8ZTZvq0bKlFl9+aS5yWNT580BWlr0bJuDbbzVF7i/LMn7+2YSd\nO004csTk1iFXgwYNUr8WRRHNmzeHIAh44YUX1O2+vr5o0KAB0tPTAQCbNm1CZGQkoqKi8Pfff6v/\n2rdvD0EQ8NVXX6nvNRgMAACbzYasrCx1v+vXr+Po0aMAgOrVqwMAdu3ahRs3brjt2uzZAbvdu3cj\nOzsbMTExDu3Ozc3Fww8/7NBuu/w/H19fX0RGRsLLywsxMTHq9sjISPj5+ak/H0D5GbVr1w533XWX\nw7kee+wxAMDXX3/tcJ7evXvD19dX/f7hhx8GAIdjFsbPzw8A8PHHHzsMy6poHDpFREREVEYnT1rx\nwgsGWK0CTCYBr76qw549VtSsqXO5f0gIEBAg4dIlEYCMRx+1QRC0hR5//34TunUzICdHQEiIhG3b\nzGja1OCWtoeGhjp87+vrC61Wi4CAAIft1atXx19//QUAOH78OI4dO4aaNWs6HU8QBHU/APj2228x\nfvx4/PDDD+rwJbucnBwAQN26dTFq1CjMnz8fGzduxEMPPYRevXqhf//+8Pf3L/W12Ycx2R0/fhwA\n0LlzZ5f7azQah+91Oh3uueceh22+vr4ICgpyem/16tWRlZXlcK6DBw+W6GcEON+HGjVqAIDDMQvT\np08fvPPOOxg8eDASExPRsWNH/Oc//8Gzzz7rdE23EgMNIiIiojISRUCrBaxW5Xu9HtBoCq8O1KSJ\nHjt2mHDkiIDAQBlt2+oKnXsgyzL+9z8BOTnK62fPivj9d6BpU/e03VVHtKi2AMrchcaNG2PRokUu\n96tduzYA4NSpU+jUqRMaNmyIhQsXIjQ0FAaDAf/73/8wduxYh6fv8+bNQ3x8PLZu3Yq0tDS89tpr\nePPNN7Fnzx40atSo0DbZbLZCr83T09Phe/v5kpOTXQYLBRV2zsI67/kzTbIs47HHHsO4ceNc7lu3\nbt2bPmZhDAYD9uzZg71792LHjh1ITU1Fv379MH/+fHzzzTdqVulWY6BBREREVEb16+vw3/+aMGyY\nHtWqyVi2zIIaNQrv3AmCgObNPdG8ecmOHxyc19kUBBkBARVXrQpQMgU//fQTOnbsWOR+W7duhcVi\nwbZt2xASEqJu/+OPP1zuHxUVhaioKCQmJuK3335D8+bNsWDBAqxatUp9wp+dne3wnoyMjBK3OyIi\nAoAygbq4tpdVeHg4rl696tbzFFXaVhAEPPLII3jkkUcwe/ZsrFy5Ei+//DI++ugj9O3b121tuBmc\no0FERERURqIookcPPb77LhdffmlDmzYGt613IAgC2rfXYuNGI15+2YKPPzahTRvXQ7Lcpbi2P/fc\nc7h48SJWrFjh9JrZbMa1a9cA5D2lz5+5MJvNWLp0qcN7/vnnH+Tm5jpsa9iwIQwGgzq8qnr16rj7\n7ruxZ88eh/2WL19ewqsCoqOj4efnh5kzZ8JqTz/lU3A4U1nuYZ8+ffDjjz9i586dTq/9888/TsPI\nSsLb2xuAc7B15coVp32bNWsGIG94WkVgRoOIiIjIDURRRO3a5RMA+Pt7oG9fDZ57ToIoast90bbC\nhuvYt/fv3x+bN29GQkIC9uzZg4ceegiyLOPYsWP48MMPsXnzZrRv3x5du3aFTqdDz5498eKLL8Jk\nMmHDhg1Ow4S++OILJCQk4JlnnkFkZCRkWcYHH3yA69evo0+fPup+gwYNQlJSEgYPHozmzZtj7969\nOHHiRImvy8fHBytXrkS/fv3QrFkzxMTEICAgAGfOnMGuXbvQpEkTrFu3rsQ/h6K8/vrr2LZtG554\n4gkMHDgQDzzwAIxGIw4dOoTNmzfj0KFDTvMyitOyZUsAwCuvvIKuXbvCw8MDjz/+OKZNm4Y9e/ag\nR48eCAsLQ1ZWFlauXIlq1aqhZ8+eN3UOd2KgQURERHQbEATBrRN7BUFwGbCUZLsgCPjoo4+wcOFC\nJCcn49NPP4WnpyfCw8ORkJCgLo5Xv359fPLJJxg/fjzGjBmDmjVr4vnnn8cjjzyC6Oho9dj3338/\nunfvjh07dmD16tUwGAxo0qQJPvnkE/Tq1Uvdb9KkSfjrr7+wefNmbNq0Cd27d8fOnTudJq4Xdg0A\n1EUBZ86cibfeegsmkwlBQUF46KGHMHTo0DL9fPIzGAz4+uuvMWvWLGzatAkbNmyAj48PIiMjMWnS\nJKdJ5iXx1FNPYcSIEUhJSUFKSgoApSrVf/7zH5w9exbJycn466+/cNddd6Ft27aYNGmSw5C1W02Q\n3VkfrQj50zb5S3fRne/AgQNo0aJFRTeDbiHe86qH97zqqUr33GQyVdhkWqLyVtTnu6z9d87RICIi\nIiIit2OgQUREREREbsdAg4iIiIiI3K5EgcaFCxcwcOBABAQEwNPTE40bN8bevXsd9pkyZQqCgoLg\n5eWFDh064MiRI+XSYCIiIiIiqvyKDTSys7Px0EMPQRAE7NixA0ePHsXSpUsdZvfPnj0b8+fPx9Kl\nS/Hjjz8iICAAnTt3VmsoExERERFR1VJseds5c+YgKCgI69evV7eFhYWpX8uyjIULF2LcuHF48skn\nASjLugcEBOD999/HkCFD3N9qIiIiIiKq1IrNaHzyySdo1aoV+vTpg3vuuQfNmjXDsmXL1NLine truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxIAAAGNCAYAAACFa0d0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfaeb5d68>"
+        "<matplotlib.figure.Figure at 0x7f736ddddeb8>"
        ]
       }
      ],
-     "prompt_number": 41
+     "prompt_number": 2
     },
     {
      "cell_type": "markdown",
@@ -347,13 +347,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAxgAAAGaCAYAAACMmuWeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAxgAAAGaCAYAAACMmuWeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfadfdeb8>"
+        "<matplotlib.figure.Figure at 0x7f736dddd2b0>"
        ]
       }
      ],
-     "prompt_number": 42
+     "prompt_number": 3
     },
     {
      "cell_type": "markdown",
@@ -396,11 +396,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAv4AAAF0CAYAAABbpj2aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfade7c88>"
+        "<matplotlib.figure.Figure at 0x7f736e0c4cf8>"
        ]
       }
      ],
-     "prompt_number": 43
+     "prompt_number": 4
     },
     {
      "cell_type": "markdown",
@@ -442,7 +442,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 44
+     "prompt_number": 5
     },
     {
      "cell_type": "heading",
@@ -514,20 +514,20 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGGCAYAAAB/v854AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAykAAAGNCAYAAAAVeD67AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsnXlwnMWZ/7/d7ytZli3NPfIhWza2bGMvEGJz83M4DMkG\nCGE3GwjrTdiQNdk4BELtQiAVbFIkDoSlHELsqqUWcLgSYDmylV3iZDFmzRFsQhLAsSwsXxg00tyy\nLVmat/v3xzP9zow0OmzP6LCeT5XKM+/09NstRPf77ecSWmsNhmEYhmEYhmGYUYIc6QEwDMMwDMMw\nDMPkwyKFYRiGYRiGYZhRBYsUhmEYhmEYhmFGFSxSGIZhGIZhGIYZVbBIYRiGYRiGYRhmVMEihWEY\nhmEYhmGYUQWLFIZhGIZhGIZhRhVlEylr1qyBlBI33nhjwfXVq1dj+vTpqK6uxoUXXojt27eXawgM\nwzAMwzAMw4xByiJS3nzzTTz00EM49dRTIYRwr99zzz24//778eCDD2Lr1q0Ih8O45JJLcPDgwXIM\ng2EYhmEYhmGYMUjJRUoqlcLy5cvxyCOPwOfzude11li7di1uv/12XHXVVVi0aBE2bNiAjo4OPPnk\nk6UeBsMwDMMwDMMwY5SSi5QVK1bg7/7u7/CpT30KWmv3+u7duxGJRHDppZe616qqqrB06VK8/vrr\npR4GwzAMwzAMwzBjFLuUnT300ENoaWlxLSP5rl6tra0AgLq6uoLvhMNhfPTRRwXXUqlUKYfFMAzD\n5OHxeEZ6CCMO7zMMwzDloxT7TMlESlNTE7773e9iy5YtsCwLALl45VtT+iNfzDAMwzAMwzAMM74p\nmbvXG2+8gWg0ikWLFqGiogIVFRV49dVXsW7dOlRWViIYDAIAIpFIwfcikQimTJlSqmEwDMMwDMMw\nDDPGKZkl5aqrrsKZZ57pvtda4x//8R8xb9483HHHHWhsbMSUKVOwceNGLF68GADQ1dWFLVu24L77\n7uu337HglrBt2zYsWbJkpIdREnguo5cTaT48l+GH3Zv6ZyzsM8fKWPn7PB7KOUelyBtEykKPj0xG\n4S9/UYjHgblzBUIhaiulQCJB57+BgEYsJtzXUoo+/QyVY5mjUhrt7fSvcVjRGhCC/pWSxg0AkQjN\nMxQCotHcXISgNsc67qOB/1bHPqXeZ0omUjweT5+Fvrq6Gj6fDwsXLgQA3HzzzfjhD3+IBQsWoLGx\nEXfffTdqampw7bXXlmoYDMMwDMMwx415yAeAUEgXPKhLKeD3C/h82n2Izxcn1Law/XA86OdDIkRD\nKbhiye9XeePJiQ8TLiylQDhc+B2GGSlKGjjfGyFEQbzJrbfeis7OTqxcuRKJRAJnn302Nm7ciEmT\nJpVzGAzDMAzDMMeNUhqZDD3o27aE1hqxGH0mhIYQokCQhELFLTHDhRkLiRWNaFQgFgP8/pwwyR+f\nsRzZtiwYe38WJYYpJ2UVKZs2bepzbdWqVVi1alU5b8swDMMwDHNcmId781opjUhEobkZ8PmA+fMV\npBS9XLr6PvCP1EN+/j1z9+0/mVF/lqNMRqG9vfD3YfplmHJSVpHCMAzDMAwzVjECw/xQxlLhfpZv\ncch378p/4A8ElCtkeruNlYtigoNcuYBgsDA+pnB+hR4wZH0B4nHA7y90AxuuuTDjFxYpDMMwDMMw\nRTAP+1RSARBCYskSJ/uQL11rhWnX29ow2igmTqJRIBql+QUCGuEwAOSsP0IIBAIawSBbT5jhhUUK\nwzAMwzBMlsFcs5JJiURCZIPQc25U8biA30+WlkJXMTnssSm9XdV6Y0RVJqMhRKF1yAgXk9krEMjF\nqQAjH2fDjB9YpDAMwzAMw6Cvm1YuTW8uPiMazbU3BaulFAgE4FobegudkXigH+yeSilo3YNJkzQ8\nHp1NdgR0dgIVFfRz5AjQ00PtKyrKW3y7oaEBXV1dZet/NDCW51hZWQkpS1ZecUiwSGEYhmEYZlxj\nRIVBa+O+BTfFsFIaiYSEEBqNjdTeuHgZcWLa9Ze6eLSglILHcwSVlZWw7cJHwYkTMeD7clFVVTU8\nNxpBxuoctdbo6urChAkThlWoDK8kYhiGYRiGGUUYUZETFhgw/sKIkXhcIJkUBddMf1rngtFHG5mM\nQkdHNyZOnNhHoDBMMYQQqKqqQnd397Del/86GYZhGIZhsuTXFjHvjdgwFdoBco3KDyg3oiQWE8hk\nHEgJxGLWqLKmmHiTcrtuMSceI/H3wiKFYRiGYZhxS39B5vmWkXwri7keCOSKOuaygJErVSJBIiYY\nzAWlMwxzdLBIYRiGYRhmXHO0lg5jMQHgVnNXysSnaPfUeaTS9vaXocyM79ChYR8Swxw1LFIYhmEY\nhmH6YSjpfEmwKPh8GpWVFkKhnJVluBkscN+2JSorh31YDHPUsEhhGIZhGIYZgGLiJBAwAkBAa6qT\nAgChEFWYV0ojFFIjIlQG43jiC3bs2IHXXnvtuO69dOlSzJ0795j7YMYHLFIYhmEYhmEGIT9TV1sb\nZfAKhcgy4fcrOA6y6VnJ/SseB4QAwuHhDZwfzPJzvFRXV+Oee+5Bc3PzMX3/S1/6Er74xS+WeFTM\nicjok/cMwzAMwzCjCONC1dam0d3tIBrV2LlT48ABB93dDhIJCcsSCAQ0bFtmK7WPXAat/JTIxTBF\nKI+FGTNm4O677z6m7woh8PWvfx2TJ08+5vsz4wcWKQzDMAzDMHkopZHJqALridYasRgQiwl4vQpa\na+zZI9DeTlYVIXLCwLYlgsF8l7CRI79eSylqtwghcPbZZ6OxsfGov3vNNdfgk5/85HHdnxk/sEhh\nGIZhGIbJopRGW5tGUxMQidBDvakq7/eTAAmHJebOFfD7cxXnAwFd0EcsJhCNUvHEkZyLKVSZyaiC\nopXHw7FYU4bDirJ69WpIKbFjxw4sX74cXq8XoVAI3/3udwEA+/fvx5VXXgmPx4MpU6bgvvvuK/j+\nkSNHcNddd6GxsRFVVVWor6/HLbfcgs7OzoJ2jz76KJYtW4apU6eiqqoK8+bNw49+9KM+FqoLLrgA\nJ598MrZv346LLroIkyZNQn19PX784x+X7XdwIsEihWEYhmEYphemanwmo5DJUAB8XZ1AKARUVlqY\nMkXC56PaKABZWNrbc7ErxvKSf220cBzeXgCOzZoynFaUL33pS1BK4Z577sE555yDNWvW4N5778XF\nF1+M6dOn495770VjYyNuvfVWbNq0CQD997rqqqvw4x//GFdccQUefPBBfPGLX8S6devw+c9/vqD/\ndevWob6+HrfddhvWrl2LU089FXfccQfuuOOOgnZCCKRSKXz2s5/FJz7xCdx///1YsGABbrvtNrz0\n0kvD8rsYy3DgPMMwDMMwTBZTS0QpANBoahKQEpg/v2+mrlSK3lPgPBVwVEpk3b00tB6ZOimGwiB6\niVCIRFdHB1BdfXx9G2vK1VdfPWjb4Y5FWbJkCR566CEAwD/90z9h1qxZ+M53voMf/OAHuP322wGQ\naJo2bRoefvhhXHjhhXjqqafwm9/8Bq+88gr+3//7fwV9LV++HL/97W9xySWXAABeffVVVFVVuW2+\n/vWv44YbbsCDDz6Iu+66C5XZHM9aa7S2tuLnP/85li9fDgD46le/ioaGBvzHf/wHPvOZzwzL72Os\nwpYUhmEYhmGYPKQUsCw5YOC7lOTu5fVqJBICsRi5iUWjZDnJt7yMtFAB4LqtlWosR2NNGe5YlK99\n7WvuayklFi9eDCEErr/+eve6x+PB/PnzsXv3bgDA008/jXnz5mHhwoWIRqPuz9KlSyGEcC0uAFyB\n4jgOEomE2+7QoUNoamoqGEt1dbUrUACgoqICZ555JlpaWsoy9xMJtqQwDMMwDMPkYSwQSolsrInO\nphcu1gaIx8mK0qvJsIuTYpXmexd3tG153FYUw1CsKSOR0WvmzJkF7z0eDyoqKhAOhwuu19bWoj37\ny9m5cyeampoQCoX69CeEcNsBwJYtW3DHHXfgrbfeQnd3d0HbVCpV8H769Ol9+vN6vfjzn/98dJMa\nh7BIYRiGYRiGKUIsJqA1sm5buQruJlaFxAm5dgWDJAxKaa04GgarNJ9PqVIj51tT+qubMhIZvSzL\n6nOtvzmbYHelFBYtWoSf/OQnRdtNmzYNANDS0oJly5ZhwYIFWLt2LWbOnImqqiq8/fbbuO2226BU\nYaKEYmPJvy/TPyxSGIZhGIZhhojJ/hWNwi3oCIycOOmPfKtKOYs7DmRNGUt1UebMmYM//OEPuOii\niwZs96tf/Qrd3d34r//6L8yYMcO9vmvXrnIPcdzBMSkMwzAMwzC9oId7IBwWRWNLhKCYFL+fLBiR\nSN/aKiMxXiOaTLrhYrEopTzFHyg2ZTTVRRnMenTNNdcgEolg/fr1fT47cuQIDh48CCBnGcm3mBw5\ncgQPPvhgScfDsCWFYRiGYRimD8XiO8z7cBgIBilORSmNeNykLAZsWwzqblUu8oPk+0MpjZ4eYOLE\n0t23mDVltFlR+hNm5vry5cvx7LPPYuXKldi8eTPOO+88aK3R1NSEZ555Bs8++yyWLl2Kz3zmM6is\nrMTll1+OG264AV1dXXjssceO2q2L3b0Gh0UKwzAMwzBMHoPFd/S2TAQCOlt7RGSruo98Rq9yunj1\nplhsykhYUYQQRS0UQ7kuhMBzzz2HtWvXYsOGDXjxxRcxceJEzJkzBytXrsQpp5wCAGhsbMQLL7yA\nO+64A7feeitCoRC+/OUv41Of+hQ+/elPH9d4mEKEHoVSLj8zgsfjGcGRDI1t27ZhyZIlIz2MksBz\nGb2cSPPhuQw/Y21dLTfj5fcxVv4+j4dyzDFfpJhK8r1T+fZubwLqo1F6CB0o9XB/Vpr+KPLine truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf319c390>"
+        "<matplotlib.figure.Figure at 0x7f736de0cef0>"
        ]
       },
       {
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "Difference in mean x=-0.008, y=43.321\n"
+        "Difference in mean x=-0.009, y=43.177\n"
        ]
       }
      ],
-     "prompt_number": 45
+     "prompt_number": 6
     },
     {
      "cell_type": "markdown",
@@ -575,11 +575,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAyoAAAGNCAYAAAD+T4W4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfb08a828>"
+        "<matplotlib.figure.Figure at 0x7f736dc83400>"
        ]
       }
      ],
-     "prompt_number": 46
+     "prompt_number": 7
     },
     {
      "cell_type": "markdown",
@@ -615,11 +615,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAv4AAAF0CAYAAABbpj2aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfa8e9f28>"
+        "<matplotlib.figure.Figure at 0x7f73606337f0>"
        ]
       }
      ],
-     "prompt_number": 47
+     "prompt_number": 8
     },
     {
      "cell_type": "markdown",
@@ -670,11 +670,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAxQAAAGNCAYAAACIdTczAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmMZfld3/33ufu+VN26tfQy3T0L0PawiMEW5rHHxA6a\n2CaAEfBEgAgJQnEwJjgif0DwgxQrIKwnfxgIkWwpZAEJUMAW4AxLnsnEljWICdix3QZ7pmemu9Zb\nd9/Ofn7PH9Xd9nh6eqZrbvW999TnJbW751ZXnV9VX59zPuf3/f2+ljHGICIiIiIicgyJeQ9ARERE\nRESWlwKFiIiIiIgcmwKFiIiIiIgcmwKFiIiIiIgcmwKFiIiIiIgcmwKFiIiIiIgcmwKFiIiIiIgc\n20wDxd7eHj/2Yz9Gs9kkn8/zute9jv/1v/7XLA8hIiIiIiILJDWrL9Tv9/mO7/gO3vKWt/CJT3yC\ntbU1rl69SrPZnNUhRERERERkwViz6pT98z//83zyk5/kk5/85Cy+nIiIiIiILIGZlTx97GMf4w1v\neAM/9EM/xPr6Ot/yLd/Cb/zGb8zqy4uIiIiIyAKa2QxFLpfDsize//7384M/+IP8zd/8DT/90z/N\nr/zKr/BTP/VTt/7eYDCYxeFEREREROQeq1arL3ltZoEik8nwhje8gU996lO3XvuFX/gF/vAP/5Ar\nV67cek2BQkRERERkOd0uUMys5Glra4vLly+/6LWv//qv59q1a7M6hIiIiIiILJiZ7fL0Hd/xHfzt\n3/7ti1770pe+xIULF172c26XcOTlPf300zzyyCPzHobEiN5TMmt6T8lJ0PtKZk3vqbvzShVGM5uh\n+Nmf/Vmeeuop/u2//bc888wz/P7v/z6/9mu/9qL1EyIiIiIiEi8zCxSPPPIIH/vYx/i93/s9Hn74\nYX7xF3+RD37wg7znPe+Z1SFERERERGTBzKzkCeAd73gH73jHO2b5JUVEREREZIHNbIZCRERERERO\nHwUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUK\nERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERER\nERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5\nNgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUK\nERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERER\nERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5\nNgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5NgUK\nERERERE5NgUKERERERE5NgUKERERERE5NgUKERERERE5thMLFL/8y79MIpHgp3/6p0/qECIiIiIi\nMmcnEiieeuopPvKRj/CN3/iNWJZ1EocQEREREZEFMPNAMRgM+JEf+RH+43/8j9Tr9Vl/eRERERER\nWSAzDxQ/+ZM/yQ/8wA/w6KOPYoyZ9ZcXERGZO13fRES+IjXLL/aRj3yEq1ev8ju/8zsAKncSEZGl\nEEUGxwvwgpAgjAjDiODGrzAyX/Xno9+j6ChQJBIWCct62d+TyQS5TIpcJkU+kyKbmellV0RkIVhm\nRo9Z/u7v/o43v/nNfOpTn+Khhx4C4K1vfSsPP/wwv/Zrv3br7w0Gg1t//vKXvzyLQ4uIiLwqxhi8\nIML1I1w/xPVDnCDC80P8yCMwAaGJiExIaCIMEaEJCaMIYyJCjj5mMICFxdHDM4sEN/8XyyJhJUhg\nkbCSpKwUmWSGtJUmm0qTTiXIppNkb/yeufG7iMiievDBB2/9uVqtvuTjMwsUv/Vbv8U/+Sf/hGTy\nKyfFMAyxLItkMslkMiGdTr8oUNxuQPLynn76aR555JF5D0NiRO8pmbVFek9FkWFse0xdH9v1sd0A\nxwtwAw83dHADFyd0cQMXP/LIpBJk0gmSCYtk8miWIZU8+u/EjddSN/6cSFi3jhEZgzFHfzYGImNu\n/TmMDK4X4t0IMEEA2VSGTDJLNpUlm8yQTeYoZnPUSjmqxSyVYlYz/F9jkd5XEg96T92dV7p/n9nc\n6/d93/fxhje84dZ/G2P48R//cR566CF+/ud/nnQ6PatDiYiIvMTNADGauoxt7yhMBDa2b+OGLm7g\n4IUeySTkMkmymSSVTIJsOkMmnTvWTXwicWNW4i7GeBQufFzPYeBHOJMQSFEelClny5SzRSqF7K2A\nkUyqZZSILLaZBYpqtfqSxFIoFKjX61y+fHlWhxEREbnFdn0GE5fhxGU0dZkGNlNvwsSf4gQ22UyC\nfDZJIZ9kJZMmk87eml2Yh0TCIpdNksu+uMTJ8ULGkwkH0z7bA4tytkQpc/SrUshRL+dYrRTmOnYR\nkZdzoqvDLMvStK2IiMxMFBkGE4fhxGUwcZm4DhN/zNgbM/WnZDMJCrkkq+UUhVx5aW7Ac5kkuUyS\nRj2HH0SMpy696ZjdUURxWKTar7JSqNGsF2nWikvzfYnI6XCigeKJJ544yS8vIiKnxHDi0h3Z9EY2\nQ3fM2B0z9sdAQDGfolZLs5Uvk4zBjXY6laBeyVKvZAkjw3jq0xnuczht056sctD9SrBQOZSILALt\nXyciIgtp6vh0hlN6I4ehM2bgDBl5Q9JpKBfTnM1nyWUK8x7miUomLKqlDNVShokd0O4f0G4fBYv9\nbo31eolmvUhKwUJE5kiBQkREFobrBXRHNt2hzdC2GboD+u4AKxFSLaW5sFYgnTqdN8/FfIpivsTU\nCWj3W7Q7bTrTFfa7dTZWymyullRmLCJzoUAhIiJzFYQRvRshoj+1GbpDhs4A37hUimnO1rIvWcR8\nmhVyKc5vlLCdgM6gQ6fTYeiuM5iscHGzTk7N80TkHtNZR0RE5sJ2fVq9CZ3hlL4zZOgOsIMppUKK\nxmqaUqEy7yEutHwuxdlcCtsJ2DncPVqY7nqcb9ZYqxXnPTwROUUUKERE5DUzxhCGIblcDmPMHUtv\nhhOXg96Y7mhCz+nRd/rkshbVWpoz+eXZmWlR5HMpLp0pc9CZ8mz3ORx/i8GkxoWNmtZWiMg9oUAh\nIiLHZozhc59zeeop+PjHkxjzEN/7vS7f/u3w+td/peOzMYbO0OagO6Y/ndB1uoy9IZVSmvu28mTS\nKml6LRIJi821AqOJz/XOC4z9CVPH5771KtVSbt7DE5GYU6AQEZFjMcbwxBMO7353jsHgK7MK//2/\nQ7Vq+IM/cHjzWzIc9qcc9if07SEdu4sf2dSrWdbX47HN6yIpF9Pks0l2212+3B4z9bY426hzdk3l\nYyJychQoRETkWD73OfclYeKmwSjge/9vh4/81j6rZ6Z07R7JVMhKPUO5UNZuRCcolUpwfqNEd+Dy\nfP85/CggCCMubNTmPTQRiSkFChERuWvGGJ56ipeGiYQP2RGkx4wSPf7HZ1q8YzPLZjNLIZefz2BP\nqZVqlmwmyXbrOpGJiCLDxc2awpyIzJxWa4mIyF0Lw5CPf/yr1j1YAeR6UNqHygtQvwqZEZ//6xKb\njSyFnJ5fzUMxn+Lcep798Q7XOi2e3e1hjJn3sEQkZnSGFxGR47NCyIwhM4JC5yhURCnwikCChBXM\ne4SnXj6X4uxGgev7uwAkLItLW/U5j0pE4kQzFCIicgwWb/n7fSgeQOU6rDwLmeFRkAjy3Ly8fOd3\nhiQT2sFp3nKZJOc2iuyP97jebfPCfn/eQxKRGNEMhYiIvGpRZGj1J+x3x6xc2Cd/ZoBtW+Dnwbw4\nOJRKhte/HtXsL4hcJsnZ9TzXD3ZIWglSyQRntPuTiMyAZihEROQVGWM47E/4/HMtvri9w5faz7B6\nbsCvfNCilC3cNkx86EMu99+fmdOI5XbyuRRnmnm2h9tst/uMpu68hyQiMaAZChERuaP+2GH7cEhn\n3OdweoiVDNhYy1HM5zm/YfjoRz0+/3l44okkxhj+3t+LeP3r4f77s5qdWEDFfIp6JcXuaI/CfpbL\n962RVEdtEXkNFChEROS2PD/kWmtAazBkf7xPiMPaSo5y8Sudly3L4oEHstx/v+Fd3x3y/PMvcP+l\n+xUkFlyjnuN5e8z+qE3xIKNF2iLymihQiIjIixhjOOhN2GkPaI3b9N0ua/Us9Ur5ZT/HsixSyRSe\n5ylMLIkzzQLP7xxS6BWoFrOsVgvzHpKILCkFChERuWU0dbl2MKA97rM/OaCQh0tnS6RUEhM76VSC\ntZUsu/1dCq0cpXyGbEa3BSJy93TmEBERgjBi+3DIfm/AwfgA10zZXMtTzOsyEWe1coaxPWFvdEBh\nP83XnW/Me0gisoR0pRAROeUO+xN22kNa4w5du029muZMtaTSpVNis1HguZ0++8MitW6O9ZXSvIck\nIktGgUJE5JSaOj7XWgMORwP2x/uk0yEXzhRJp1TedJokExYbqzkO2gfUumXWakUSCYVJEXn1FChE\nRE4ZYww77RG7nQGtSYtJMGL9a3ZvktOlVEjTTrl0pwMO+yXNUojIXVGgEBE5RaaOz/P7fQ6GXQ4m\n+1RKSS6tl/REWmjUsrQ6bQ56NZr1okreRORVU6AQETkl9rtjrrf67I33caMx5zYK5LLJV/5EORVK\nhTSHPYfedEB7UGKtVpz3kERkSShQiIjEnOeHN2Yl+uwOdyiVElxc0aJrealGLUe722a/W6Line truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfbe58320>"
+        "<matplotlib.figure.Figure at 0x7f736dc78f98>"
        ]
       }
      ],
-     "prompt_number": 48
+     "prompt_number": 9
     },
     {
      "cell_type": "markdown",
@@ -932,7 +932,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 49
+     "prompt_number": 10
     },
     {
      "cell_type": "markdown",
@@ -977,7 +977,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 50
+     "prompt_number": 11
     },
     {
      "cell_type": "markdown",
@@ -1081,13 +1081,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAzkAAAGkCAYAAAASdeutAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAzkAAAGkCAYAAAASdeutAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf185c2e8>"
+        "<matplotlib.figure.Figure at 0x7f736063e198>"
        ]
       }
      ],
-     "prompt_number": 51
+     "prompt_number": 12
     },
     {
      "cell_type": "markdown",
@@ -1113,13 +1113,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAKNCAYAAAA01T3TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAKNCAYAAAA01T3TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfad775f8>"
+        "<matplotlib.figure.Figure at 0x7f736059e0b8>"
        ]
       }
      ],
-     "prompt_number": 52
+     "prompt_number": 13
     },
     {
      "cell_type": "markdown",
@@ -1148,7 +1148,6 @@
       "plt.plot ([4,0], [0,3], c='#E24A33')\n",
       "plt.text(-4, -.5, \"A\", fontsize=16, horizontalalignment='center')\n",
       "plt.text(4, -.5, \"B\", fontsize=16, horizontalalignment='center')\n",
-      "#plt.scatter ([-4],[0], 'r')\n",
       "\n",
       "ax.add_artist(circle1)\n",
       "ax.add_artist(circle2)\n",
@@ -1162,11 +1161,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAp4AAAJ2CAYAAAD2YYJ8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfafed518>"
+        "<matplotlib.figure.Figure at 0x7f73605a5b38>"
        ]
       }
      ],
-     "prompt_number": 53
+     "prompt_number": 14
     },
     {
      "cell_type": "markdown",
@@ -1285,11 +1284,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAqkAAAJ9CAYAAAAWiev+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfb02c6d8>"
+        "<matplotlib.figure.Figure at 0x7f73605f1400>"
        ]
       }
      ],
-     "prompt_number": 54
+     "prompt_number": 15
     },
     {
      "cell_type": "markdown",
@@ -1317,11 +1316,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAJ9CAYAAAA2ZbQDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf310b320>"
+        "<matplotlib.figure.Figure at 0x7f736dd81710>"
        ]
       }
      ],
-     "prompt_number": 55
+     "prompt_number": 16
     },
     {
      "cell_type": "markdown",
@@ -1354,7 +1353,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 56
+     "prompt_number": 17
     },
     {
      "cell_type": "heading",
@@ -1417,11 +1416,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAArQAAAJ2CAYAAACuHhFlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfb000a58>"
+        "<matplotlib.figure.Figure at 0x7f7361ecd0f0>"
        ]
       }
      ],
-     "prompt_number": 57
+     "prompt_number": 18
     },
     {
      "cell_type": "heading",
@@ -1468,11 +1467,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAArQAAAJ2CAYAAACuHhFlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf183ec88>"
+        "<matplotlib.figure.Figure at 0x7f736dc1fe80>"
        ]
       }
      ],
-     "prompt_number": 58
+     "prompt_number": 19
     },
     {
      "cell_type": "markdown",
@@ -1505,7 +1504,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 59
+     "prompt_number": 20
     },
     {
      "cell_type": "heading",
@@ -1543,11 +1542,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAArQAAAJ2CAYAAACuHhFlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf1831898>"
+        "<matplotlib.figure.Figure at 0x7f736055c780>"
        ]
       }
      ],
-     "prompt_number": 60
+     "prompt_number": 21
     },
     {
      "cell_type": "markdown",
@@ -1580,7 +1579,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 61
+     "prompt_number": 22
     },
     {
      "cell_type": "heading",
@@ -1622,7 +1621,7 @@
        ]
       }
      ],
-     "prompt_number": 62
+     "prompt_number": 23
     },
     {
      "cell_type": "heading",
@@ -1664,11 +1663,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAp0AAAJ9CAYAAAB3kcm8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf18e7be0>"
+        "<matplotlib.figure.Figure at 0x7f7361f43d30>"
        ]
       }
      ],
-     "prompt_number": 63
+     "prompt_number": 24
     },
     {
      "cell_type": "heading",
@@ -1735,11 +1734,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAApMAAAJ8CAYAAACiBCqqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf1898f98>"
+        "<matplotlib.figure.Figure at 0x7f7361eebc50>"
        ]
       }
      ],
-     "prompt_number": 64
+     "prompt_number": 25
     },
     {
      "cell_type": "markdown",
@@ -1835,11 +1834,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAowAAAJ2CAYAAADVOtOpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfb083ef0>"
+        "<matplotlib.figure.Figure at 0x7f736dbabb70>"
        ]
       }
      ],
-     "prompt_number": 65
+     "prompt_number": 26
     },
     {
      "cell_type": "markdown",
@@ -1870,11 +1869,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAo8AAAJ2CAYAAAA+DWiqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfad5f2b0>"
+        "<matplotlib.figure.Figure at 0x7f7360587d68>"
        ]
       }
      ],
-     "prompt_number": 66
+     "prompt_number": 27
     },
     {
      "cell_type": "heading",
@@ -1907,7 +1906,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 67
+     "prompt_number": 28
     },
     {
      "cell_type": "heading",
@@ -1982,7 +1981,7 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAqsAAAJ2CAYAAAB4u8sAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf3148c18>"
+        "<matplotlib.figure.Figure at 0x7f7361ecd3c8>"
        ]
       },
       {
@@ -1993,7 +1992,7 @@
        ]
       }
      ],
-     "prompt_number": 68
+     "prompt_number": 29
     },
     {
      "cell_type": "heading",
@@ -2097,7 +2096,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 69
+     "prompt_number": 30
     },
     {
      "cell_type": "heading",
@@ -2191,13 +2190,13 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 70,
+       "prompt_number": 31,
        "text": [
         "array([410, 520, 630])"
        ]
       }
      ],
-     "prompt_number": 70
+     "prompt_number": 31
     },
     {
      "cell_type": "markdown",
@@ -2282,7 +2281,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 71
+     "prompt_number": 32
     },
     {
      "cell_type": "heading",
@@ -2328,7 +2327,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 72
+     "prompt_number": 33
     },
     {
      "cell_type": "heading",
@@ -2403,7 +2402,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 73
+     "prompt_number": 34
     },
     {
      "cell_type": "heading",
@@ -2718,7 +2717,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 74
+     "prompt_number": 35
     },
     {
      "cell_type": "heading",
@@ -2754,11 +2753,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAAJ3CAYAAAAEWuCCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfaefaf60>"
+        "<matplotlib.figure.Figure at 0x7f736db2c4e0>"
        ]
       }
      ],
-     "prompt_number": 75
+     "prompt_number": 36
     },
     {
      "cell_type": "markdown",
@@ -2872,11 +2871,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsUAAAKUCAYAAADsGUVKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf310bd68>"
+        "<matplotlib.figure.Figure at 0x7f736dc7f358>"
        ]
       }
      ],
-     "prompt_number": 76
+     "prompt_number": 37
     },
     {
      "cell_type": "markdown",
@@ -2982,11 +2981,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsUAAAKUCAYAAADsGUVKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facf313e0b8>"
+        "<matplotlib.figure.Figure at 0x7f736de0c320>"
        ]
       }
      ],
-     "prompt_number": 77
+     "prompt_number": 38
     },
     {
      "cell_type": "heading",
@@ -3046,11 +3045,11 @@
        "output_type": "display_data",
        "png": "iVBORw0KGgoAAAANSUhEUgAAAsAAAAKUCAYAAAAKMI4OAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7facfbe58828>"
+        "<matplotlib.figure.Figure at 0x7f736056cb00>"
        ]
       }
      ],
-     "prompt_number": 78
+     "prompt_number": 39
     },
     {
      "cell_type": "markdown",