diff --git a/02-Discrete-Bayes.ipynb b/02-Discrete-Bayes.ipynb
index 594650c..dbeb90b 100644
--- a/02-Discrete-Bayes.ipynb
+++ b/02-Discrete-Bayes.ipynb
@@ -307,7 +307,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[ 0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1]\n"
+      "[0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]\n"
      ]
     }
    ],
@@ -337,9 +337,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "hallway = np.array([1, 1, 0, 0, 0, 0, 0, 0, 1, 0])"
@@ -359,9 +357,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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AAACGIqwDAAAAhiKsAwAAAIYirAMAAACGIqwDAAAAhiKsAwAAAIYirAMAAACGIqwDAAAA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\n1gEAAABDEdYBAAAAQxHWAQAAAEP9P/dQT1zQHEjoAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edafa955c0>"
+       "<matplotlib.figure.Figure at 0x1db568f9048>"
       ]
      },
      "metadata": {},
@@ -404,7 +402,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[ 0.333  0.333  0.0  0.0  0.0  0.0  0.0  0.0  0.333  0.0]\n"
+      "[0.333 0.333 0.    0.    0.    0.    0.    0.    0.333 0.   ]\n"
      ]
     }
    ],
@@ -432,9 +430,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "belief = np.array([0., 1., 0., 0., 0., 0., 0., 0., 0., 0.])"
@@ -481,15 +477,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "belief: [ 0.3  0.3  0.1  0.1  0.1  0.1  0.1  0.1  0.3  0.1]\n",
-      "sum = 1.6\n"
+      "belief: [0.3 0.3 0.1 0.1 0.1 0.1 0.1 0.1 0.3 0.1]\n",
+      "sum = 1.6000000000000003\n"
      ]
     },
     {
      "data": {
-      "image/png": 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xQvv27dNnn31mYnXmItRbwOHDh3XXXXe1CS6DBg1yb0dg+vrrr/XHP/5RycnJ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\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhYAAACMCAYAAAAgJeDfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADjpJREFUeJzt3X2MZXddx/H3hy4VWmAwLWjtLrbGgbBpjNtMWkuTUm2RLZKtD43pJjRCeDCGRbA+pFVSajUhoIgxVkRb5EFoXQroxmxYiBRBQ+sOLQ/dLmXXgnTYYpGHi4haKl//uKfrdZjZObP9tfee7fuVTPaec35z7mfu7t797Dm/c26qCkmSpBYeM+0AkiTp2GGxkCRJzVgsJElSMxYLSZLUjMVCkiQ1Y7GQJEnNrFkskrwlyX1J7lhle5L8UZKDST6V5Mz2MSVJ0hD0OWLxVmDrEbZfBMx3Xy8D3vTQY0mSpCFas1hU1UeArx5hyMXA22vsFuDJSU5pFVCSJA3Hhgb7OBW4Z2J5qVt37+Sg0WjkLT4lSTrGzM3NZXK5xeTNrLDOEiFJ0qNQi2KxBGyaWN4IHGqwX0mSNDAtToXsAnYkuRE4GxhV1b1H+oa5ubkGT9ve4uIiAAsLC1NOsj5DzQ3DzT7U3DDc7EPNDcPNPtTcMNzsQ8k9Go1W3bZmsUhyA3A+cHKSJeA1wGMBqupPgd3A84CDwLeAFz3kxJIkaZDWLBZVtX2N7QW8vFkiSZI0WN55U5IkNWOxkCRJzVgsJElSMxYLSZLUjMVCkiQ1Y7GQJEnNWCwkSVIzFgtJktSMxUKSJDVjsZAkSc1YLCRJUjMWC0mS1IzFQpIkNdOrWCTZmuSuJAeTXLHC9qcluTnJ7Uk+leR57aNKkqRZt2axSHIccC1wEbAZ2J5k87JhrwZ2VtUW4FLgT1oHlSRJsy9VdeQByTnA1VX13G75SoCqeu3EmDcDd1fV67rxb6iqZ03uZzQaHX6iAwcOtPsJJEnSI2p+fv7w47m5uUxu29Dj+08F7plYXgLOXjbmauADSV4BnAhceDRBJUnSsPUpFllh3fLDHNuBt1bVG7ojFu9IckZVfWelHS4sLKwz5iNjcXERmN18qxlqbhhu9qHmhuFmH2puGG72oeaG4WYfSu7RaLTqtj6TN5eATRPLG4FDy8a8GNgJUFUfAx4HnLyulJIkafD6FIu9wHyS05Mcz3hy5q5lY74AXACQ5JmMi8WXWwaVJEmzb81iUVUPADuAPcB+xld/7EtyTZJt3bBfBV6a5JPADcALa61ZoZIk6ZjTZ44FVbUb2L1s3VUTj+8Ezm0bTZIkDY133pQkSc1YLCRJUjMWC0mS1IzFQpIkNWOxkCRJzVgsJElSMxYLSZLUjMVCkiQ1Y7GQJEnNWCwkSVIzFgtJktSMxUKSJDVjsZAkSc30KhZJtia5K8nBJFesMubnk9yZZF+Sd7WNKUmShmDNj01PchxwLfAcYAnYm2RX91HpD46ZB64Ezq2qryV56sMVWJIkza5U1ZEHJOcAV1fVc7vlKwGq6rUTY14PfLaqrlttP6PR6PATHThw4CHGliRJ0zI/P3/48dzcXCa39TkVcipwz8TyUrdu0tOBpyf5xyS3JNl6lFklSdKArXkqBMgK65Yf5tgAzAPnAxuBjyY5o6q+vtIOFxYW1pPxEbO4uAjMbr7VDDU3DDf7UHPDcLMPNTcMN/tQc8Nwsw8l92g0WnVbnyMWS8CmieWNwKEVxvxNVX27qj4H3MW4aEiSpEeRPsViLzCf5PQkxwOXAruWjflr4McBkpzM+NTI3S2DSpKk2bdmsaiqB4AdwB5gP7CzqvYluSbJtm7YHuArSe4EbgZ+vaq+8nCFliRJs6nPHAuqajewe9m6qyYeF3B59yVJkh6lvPOmJElqxmIhSZKasVhIkqRmLBaSJKkZi4UkSWrGYiFJkpqxWEiSpGYsFpIkqRmLhSRJasZiIUmSmrFYSJKkZiwWkiSpmV7FIsnWJHclOZjkiiOMuyRJJVloF1GSJA3FmsUiyXHAtcBFwGZge5LNK4x7IvDLwK2tQ0qSpGHoc8TiLOBgVd1dVfcDNwIXrzDud4DXA//VMJ8kSRqQVNWRBySXAFur6iXd8mXA2VW1Y2LMFuDVVfVzST4M/FpVLU7uZzQaHX6iAwcOtPsJJEnSI2p+fv7w47m5uUxu29Dj+7PCusMlIcljgDcCLzy6eJIk6VjRp1gsAZsmljcChyaWnwicAXw4CcD3A7uSbFt+1OJBCwuzObdzcXEcd1bzrWaouWG42YeaG4abfai5YbjZh5obhpt9KLlHo9Gq2/rMsdgLzCc5PcnxwKXArgc3VtWoqk6uqtOq6jTgFmDVUiFJko5daxaLqnoA2AHsAfYDO6tqX5Jrkmx7uANKkqTh6HMqhKraDexetu6qVcae/9BjSZKkIfLOm5IkqRmLhSRJasZiIUmSmrFYSJKkZiwWkiSpGYuFJElqptflprNuyztaffbI3PiX/W32d/tl82uOaZP9kc8tSQ+HWXw/9z1xfTxiIUmSmrFYSJKkZiwWkiSpGYuFJElqxmIhSZKasVhIkqRmehWLJFuT3JXkYJIrVth+eZI7k3wqyd8l+cH2USVJ0qxbs1gkOQ64FrgI2AxsT7J52bDbgYWq+hHgJuD1rYNKkqTZ1+eIxVnAwaq6u6ruB24ELp4cUFU3V9W3usVbgI1tY0qSpCFIVR15QHIJsLWqXtItXwacXVU7Vhn/x8CXqup3J9ePRqPDT3TgQKs7q429dP9c0/218ufPHK05Zhaz98ktSQ8H3xOHYX7+/+5GOjc3l8ltfW7pnRXWrdhGkrwAWACevY58kiTpGNGnWCwBmyaWNwKHlg9KciHwW8Czq+q/j7TDhYWF9WRcW6PPyGit1885g9mb//4cweLi4iP+nC0MNTcMN/tQc8Nws08lt++Jj/hzHo3RaPWjOH3mWOwF5pOcnuR44FJg1+SAJFuANwPbquq+h5BVkiQN2JrFoqoeAHYAe4D9wM6q2pfkmiTbumG/BzwBeHeSTyTZtcruJEnSMazXx6ZX1W5g97J1V008vrBxLkmSNEDeeVOSJDVjsZAkSc1YLCRJUjMWC0mS1IzFQpIkNdPrqhBpuS3vaHUTm+72vY1uinP7ZfNrjmmTfai5oWX2PrnB19zXfKxv9qHyNR/ziIUkSWrGYiFJkpqxWEiSpGYsFpIkqRmLhSRJasZiIUmSmrFYSJKkZnoViyRbk9yV5GCSK1bY/j1J/qrbfmuS01oHlSRJs2/NYpHkOOBa4CJgM7A9yeZlw14MfK2qfhh4I/C61kElSdLsS1UdeUByDnB1VT23W74SoKpeOzFmTzfmY0k2AF8CnlITOx+NRkd+IkmSNDhzc3OZXO5zKuRU4J6J5aVu3YpjquoBYAScdPQxJUnSEPUpFllh3fKjD33GSJKkY1yfDyFbAjZNLG8EDq0yZqk7FTIHfHVywPJDJZIk6djT54jFXmA+yelJjgcuBXYtG7ML+IXu8SXAh2qtyRuSJOmYs2ax6OZM7AD2APuBnVW1L8k1SbZ1w64HTkpyELgc+K5LUmfdWpfUzqokb0lyX5I7pp1lPZJsSnJzkv1J9iV55bQz9ZXkcUn+Kcknu+y/Pe1M65HkuCS3J/nbaWdZjySfT/LpJJ9IsjjtPH0leXKSm5J8pvvzfs60M/WR5Bnda/3g1zeSvGraufpI8ivd3807ktyQ5HHTztRXkld2ufcN5fVebs2rQh4NuktqPws8h/Fpnb3A9qq6c6rBekhyHvBN4O1Vdca08/SV5BTglKq6LckTgY8DPz2Q1zzAiVX1zSSPBf4BeGVV3TLlaL0kuRxYAJ5UVc+fdp6+knweWKiqf5t2lvVI8jbgo1V1XXfU94Sq+vq0c61H9x75ReDsqvqXaec5kiSnMv47ubmq/jPJTmB3Vb11usnWluQM4EbgLOB+4P3AL1XVgakGWyfvvDl2FnCwqu6uqvsZ/8ZePOVMvVTVR1g2n2UIqureqrqte/zvjI+GLb/aaCbV2De7xcd2X4No6Ek2Aj8FXDftLI8GSZ4EnMf4qC5Vdf/QSkXnAuCfZ71UTNgAPL6b83cC3z0vcFY9E7ilqr7VnS34e+Bnppxp3SwWY30uqdXDpLtT6xbg1ukm6a87nfAJ4D7gg1U1lOx/CPwG8J1pBzkKBXwgyceTvGzaYXr6IeDLwF90p5+uS3LitEMdhUuBG6Ydoo+q+iLw+8AXgHuBUVV9YLqpersDOC/JSUlOAJ7H/794YhAsFmNeLjslSZ4AvAd4VVV9Y9p5+qqq/6mqH2V8ldRZ3SHMmZbk+cB9VfXxaWc5SudW1ZmM7wL88u404KzbAJwJvKmqtgD/wcDmoHWnb7YB7552lj6SfC/jI86nAz8AnJjkBdNN1U9V7Wd85+oPMj4N8knggamGOgoWi7E+l9SqsW5+wnuAd1bVe6ed52h0h7U/DGydcpQ+zgW2dXMVbgR+IslfTjdSf1V1qPv1PuB9jE9hzrolYGniiNZNjIvGkFwE3FZV/zrtID1dCHyuqr5cVd8G3gs8a8qZequq66vqzKo6j/Fp7kHNrwCLxYP6XFKrhroJkNcD+6vqD6adZz2SPCXJk7vHj2f8RvaZ6aZaW1VdWVUbq+o0xn/GP1RVg/ifXJITu0m+dKcSfpLxYeOZVlVfAu5J8oxu1QXAzE9QXmY7AzkN0vkC8GNJTujeZy5gPIdrEJI8tfv1acDPMqzXHuh3g6xjXlU9kOTBS2qPA95SVfumHKuXJDcA5wMnJ1kCXlNV1083VS/nApcBn+7mKgD8ZlXtnmKmvk4B3tbNlH8M40uwB3Xp5gB9H/C+8b8TbADeVVXvn26k3l4BvLP7T8vdwIumnKe37jz/c4BfnHaWvqrq1iQ3AbcxPo1wO/Bn0021Lu9JchLwbeDlVfW1aQdaLy83lSRJzXgqRJIkNWOxkCRJzVgsJElSMxYLSZLUjMVCkiQ1Y7GQJEnNWCwkSVIzFgtJktTM/wK9oV0Rin2vzgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edafa95550>"
+       "<matplotlib.figure.Figure at 0x1db568ddc50>"
       ]
      },
      "metadata": {},
@@ -526,8 +522,8 @@
     {
      "data": {
       "text/plain": [
-       "array([ 0.188,  0.188,  0.0625,  0.0625,  0.0625,  0.0625,  0.0625,\n",
-       "        0.0625,  0.188,  0.0625])"
+       "array([0.188, 0.188, 0.062, 0.062, 0.062, 0.062, 0.062, 0.062, 0.188,\n",
+       "       0.062])"
       ]
      },
      "execution_count": 8,
@@ -570,7 +566,7 @@
      "data": {
       "text/plain": [
        "array([ True,  True, False, False, False, False, False, False,  True,\n",
-       "       False], dtype=bool)"
+       "       False])"
       ]
      },
      "execution_count": 9,
@@ -611,14 +607,14 @@
      "text": [
       "sum = 1.0\n",
       "probability of door = 0.1875\n",
-      "probability of wall = 0.0625\n"
+      "probability of wall = 0.06249999999999999\n"
      ]
     },
     {
      "data": {
-      "image/png": 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AwFCEdQAAAMBQhHUAAADAUIR1AAAAwFCEdQAAAMBQhHUAAADAUIR1AAAAwFCEdQAAAMBQ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\nAADAUIR1AAAAwFD/B37nMeHwyGFnAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb023ecf8>"
+       "<matplotlib.figure.Figure at 0x1db56cdec50>"
       ]
      },
      "metadata": {},
@@ -656,6 +652,8 @@
     "\n",
     "$$\\mathtt{posterior} = \\frac{\\mathtt{likelihood} \\times \\mathtt{prior}}{\\mathtt{normalization}}$$ \n",
     "\n",
+    "When we talk about the filter's output we typically call the state after performing the prediction the *prior* or *prediction*, and we call the state after the update either the *posterior* or the *estimated state*. \n",
+    "\n",
     "It is very important to learn and internalize these terms as most of the literature uses them extensively.\n",
     "\n",
     "Does `scaled_update()` perform this computation? It does. Let me recast it into this form:"
@@ -664,9 +662,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def scaled_update(hall, belief, z, z_prob): \n",
@@ -702,8 +698,8 @@
     {
      "data": {
       "text/plain": [
-       "array([ 0.188,  0.188,  0.0625,  0.0625,  0.0625,  0.0625,  0.0625,\n",
-       "        0.0625,  0.188,  0.0625])"
+       "array([0.188, 0.188, 0.062, 0.062, 0.062, 0.062, 0.062, 0.062, 0.188,\n",
+       "       0.062])"
       ]
      },
      "execution_count": 12,
@@ -754,9 +750,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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mo+LWlJhVEVev16OwsNDu/VbUA5nvrcQcqCweX2VV1xxYU2JWJNfblAmHDx+O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\nREREpFIs1omIiIiIVOr/AfkuCxAbOH9xAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb09f14e0>"
+       "<matplotlib.figure.Figure at 0x1db5493f9b0>"
       ]
      },
      "metadata": {},
@@ -1580,7 +1576,7 @@
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\" width=\"800\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1665,9 +1661,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb0212828>"
+       "<matplotlib.figure.Figure at 0x1db576f4780>"
       ]
      },
      "metadata": {},
@@ -1707,7 +1703,7 @@
     {
      "data": {
       "text/plain": [
-       "array([ 0.0,  0.0,  0.0,  0.04,  0.38,  0.52,  0.06,  0.0,  0.0,  0.0])"
+       "array([0.  , 0.  , 0.  , 0.04, 0.38, 0.52, 0.06, 0.  , 0.  , 0.  ])"
       ]
      },
      "execution_count": 16,
@@ -1716,9 +1712,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb09e55c0>"
+       "<matplotlib.figure.Figure at 0x1db576ea128>"
       ]
      },
      "metadata": {},
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\" 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+       "<img 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\" width=\"800\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -2544,8 +2540,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Final Belief: [ 0.104  0.103  0.101  0.0987  0.0967  0.0959  0.0967  0.0987  0.101\n",
-      "  0.103]\n"
+      "Final Belief: [0.104 0.103 0.101 0.099 0.097 0.096 0.097 0.099 0.101 0.103]\n"
      ]
     }
    ],
@@ -2612,9 +2607,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def predict_move_convolution(pdf, offset, kernel):\n",
@@ -2652,9 +2645,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb1ca99e8>"
+       "<matplotlib.figure.Figure at 0x1db57707c50>"
       ]
      },
      "metadata": {},
@@ -2688,9 +2681,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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Q5Dnj1KyqzQzORPkx4CMMlu/vHnOqfTVRPQR63UfsIRPaQyYtWIzysbUlIcm+DJrBxVX1\ngZa1u+W7q4CTxyx1HLA+yc0MloSfnOTdY9YEoKpu6f69DfgggyXocWwHtg9tXV3OoEm0cArw+ar6\n7wa1TgS+WlW3V9WPgA8AvzBu0aq6sKqOrqrjGSy5bxm3Zk9NTA+BfvcRe8jk9pBJCxajfGxtr0sS\nBvvxNlfV3zSq+dAkD+4uP4jBL9+XxqlZVedW1aqqOpzB9/ITVTVWMu7md0CSg3ZcBn6FwVLcOHO9\nFdiW5HHdTU8Bbhhroj9xGg2WMDtfB45Nsn/3e/AUBvvGx5LkYd2/jwZ+jXbz7ZuJ6CHQ7z5iD5ns\nHjLKCbKWjKq6O8mOj62tAN5eVZvGqZnkPcAJwCFJtgOvqaoLx5zqccDpwBe7fZkAr6yqDWPUfCTw\nrgz+oNM+DD6y1+zjoY09HPjg4D3BSuCSqvpIg7ovBi7u/kO4CfjdcQt2+xufCrxw3FoAVXV1ksuB\nzzNYarwW+PsGpd+f5GDgR8CLquqOBjV7ZzF6CNhHFoE9ZIJ7yIJ/hEySJGlUk7YrRJIkLWEGC0mS\n1IzBQpIkNWOwkCRJzRgsJElSMwYLSZLUjMFCkiQ1Y7CQJEnN/D+6xaZaXbeK+wAAAABJRU5ErkJg\ngg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb0bce438>"
+       "<matplotlib.figure.Figure at 0x1db576ea3c8>"
       ]
      },
      "metadata": {},
@@ -2745,9 +2738,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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ehzVEWt3m15FhToWcDNw1sD7XbVtwTFXtBXrAiYefpqRVxBoiTZBhGouFjmjmHzkMM0bS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\nIQAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb0a1fa90>"
+       "<matplotlib.figure.Figure at 0x1db56d24e10>"
       ]
      },
      "metadata": {},
@@ -2778,9 +2771,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb09f1198>"
+       "<matplotlib.figure.Figure at 0x1db58889390>"
       ]
      },
      "metadata": {},
@@ -2807,9 +2800,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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f5OTWiUoaX9YQaXIs2Vgk2QBcBpwHbAG2Jdkyb9iPAndX1dcArwd+o3WiksaTNUSaLKmq\nxQckZwKvqapzuvWLAarqtQNjruvG/EuSo4A7gcfVQPBer7f4hiStuqmpqaz0Nqwh0vo2v44MMxWy\nEdg3sD7XPbbgmKo6APSAE5efpqR1xBoiTZBhGouF9mjm7zkMM0bSZLKGSBNkmDtvzgGbB9Y3AfsP\nMWauO4w5BXxmcMBqHHKVtCZZQ6QJMswRixuA6SSnJDkGOB/YMW/MDuCHu+XnA++rpU7ekDQprCHS\nBFmysejmO7cD1wG7gWuqaleSS5Ns7YZdAZyYZC/wKuBhl5O1stRla8uI9+YkdyW5uUV+XczNSf4u\nye4ku5K8okHMRyb51yQf6mL+cotcu9gbktyU5F0NY96R5N+TfDDJbKOYJyS5NslHup/tmSPGe1KX\n38GvzyZ5ZYM8f7L7Hd2c5O1JHtkg5iu6eLta5Lia1nsN6WJaRxrXEWvIGNeQqhqbL2AD8J/AE4Fj\ngA8BW0aMeRbwVODmhnk+Hnhqt3w88B8N8gxwXLd8NHA98PRG+b4KuAp4V8OfwR3AYxv//t8KvKRb\nPgY4ofF7607gCSPG2QjcDhzbrV8DXDBizCcDNwOPoj99+V5guuXPdlK+VqKGdHGtI43riDVkfGvI\nuN1583Rgb1XdVlX3AVcDzxslYFX9A/PmckdVVZ+oqhu75f+mv5c2/yz4w41ZVfW5bvXo7mvkQ8VJ\nNgHPAS4fNdZKSvIY+sX7CoCquq+q7mm4ibOB/6yqjzaIdRRwbHeuwKN4+PkEh+tU4ANV9T/V3/v/\ne+B7Row5qZrXELCOjEMdsYasXg0Zt8ZimMvW1pTuDoKn0d8zGDXWhiQfBO4C3lNVI8cEfgf4WeCB\nBrEGFfDuJP+W5GUN4j0R+BTwlu5w6+VJHt0g7kHnA28fNUhVfRz4LeBjwCeAXlW9e8SwNwNnJTkx\nyaOA7+ShJ0NqeGNXQ2Bi64g1ZExryLg1FmN1SVqS44B3AK+sqs+OGq+qvlBVT6F/Vv3pSZ48Yn7f\nBdxVVf82am4LeEZVPZX+3RYvTHLWiPGOon+o+Q+r6jTgXhrNw3cnFG4F/qxBrC+lvwd8CnAS8Ogk\nLxolZlXtpn8nyvcAf0P/8P2BEVOdVGNVQ2Ci64g1ZExryLg1FsNctrYmJDmafjG4sqr+vGXs7vDd\n+4FzRwz1DGBrkjvoHxJ+VpK3jRgTgKra3/17F/AX9A9Bj2IOmBvYu7qWfpFo4Tzgxqr6ZINYzwZu\nr6pPVdX9wJ8D3zxq0Kq6oqqeWlVn0T/kvmfUmBNqbGoITHYdsYaMbw0Zt8ZimMvWjrgkoT+Pt7uq\nfrtRzMclOaFbPpb+m+8jo8SsqouralNVnUz/Z/m+qhqpM+7ye3SS4w8uA99B/1DcKLneCexL8qTu\nobOBW0ZK9Iu20eAQZudjwNOTPKp7H5xNf258JEm+vPv3q4DvpV2+k2YsaghMdh2xhox3DRnmBllr\nRlUdSHLwsrUNwJuratcoMZO8HXgm8Ngkc8AvVdUVI6b6DODFwL93c5kAr66qnSPEfDzw1vQ/0OkR\n9C/Za3Z5aGNfAfxF/2+Co4CrqupvGsT9CeDK7j+E24AfGTVgN9/47cCPjRoLoKquT3ItcCP9Q403\nAW9sEPodSU4E7gcurKq7G8ScOCtRQ8A6sgKsIWNcQ5b8EDJJkqRhjdtUiCRJWsNsLCRJUjM2FpIk\nqRkbC0mS1IyNhSRJasbGQpIkNWNjIUmSmrGxkCRJzfw/N23O80hD6CAAAAAASUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb1d19978>"
+       "<matplotlib.figure.Figure at 0x1db58b2b6d8>"
       ]
      },
      "metadata": {},
@@ -2836,9 +2829,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhYAAACYCAYAAAC4YqBSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAEwhJREFUeJzt3X+U5XVdx/Hny4VNFBwKrWR3E6zJ2KwjNoLkiUwsIHPthyWrknRS6xw3NfsFVmScyjJPdkrqpKJ5FCTCH622J9TUOv0QmQCVZSU2QHdaEVO4JpWw8u6P+128DLMzd/d+Znbu3OfjnDn7/d77ue/ve+bOvPf9/X6+3+9NVSFJktTCQw53ApIkae2wsZAkSc3YWEiSpGZsLCRJUjM2FpIkqRkbC0mS1IyNhYaS5PuS3HS485A0WZK8MsmbDnceGl68j4UkaTkk+Utgrqp+43DnopXjEQstKckRI75+XatcJE2OUWrPqHVLh87GYoIluS3JBUluTHJnkrckeWiSpyaZS/JrSW4H3rL/sYHXnpTkI0nuSrIzyZaB5/4yyZ8n2ZHkbuAHDsf3J+ngHKgmdM+9KMnuJF9Msj3J8d3jSfK6JHck6SX5RJLHJ3kx8DzgV5N8Ocl7u/HHJ3lnks8nuTXJSwe2/6okVyZ5e5IvAed1j719YMyWrubc1dWgk+bl/2tJPgHcbXNxeNhY6HnAmcC3At8O7D9k+c3ANwCPAV48+IIkRwLvBd4PfCPwC8ClSR43MOy5wO8CxwD/tIz5S2rrQTUhydOAVwM/BTwa+DRweTf+h4DTu7HHAs8BvlBVbwAuBV5TVUdX1TOTPIR+7fg4sAE4A3h5kjMHtv8s4Mou1qWDiSX5duAdwMuBRwE7gPcmWT8wbCvwDODYqto3+o9DB8vGQq+vqj1V9UX6jcDW7vH7gN+qqq9U1f/Oe82TgaOB36+qe6rqQ8D7Bl4L8DdV9c9VdV9V/d9yfxOSmlmoJjwPeHNVXVtVXwEuAE5LcgJwL/0diO+gf97erqr67AFiPwl4VFVd1NWOW4A3AucMjPnXqnpPVzvm157nAH9bVR+oqnuB1wJHAd87MOZPuvznv1YrxMZCewaWPw0c3y1/fpGG4HhgT1XdN++1Gw4QV9L4WKgmHN8tA1BVXwa+AGzodixeD1wMfC7JG5I84gCxHwMc301j3JXkLuCVwDcdYPvzzc/jvm68tWcVsbHQpoHlbwH2dsuLXS60F9jUHdYcfO1/Dqx7uZE0nhaqCXvpNwUAJHk4cBzd33xV/UlVfQ/wnfSnRH6lGzq/DuwBbq2qYwe+jqmqHx4Ys1TtGcwjXb7WnlXExkIvSbIxyTfQ33P4qyFeczVwN/2Tso5M8lTgmXxtzlXS+FqoJlwG/EySJyT5OuD3gKur6rYkT0pyanfu1d3A/wFf7WJ9DnjsQOyPAV/qTrA8Ksm67kTPJw2Z2xXAM5Kc0W3vl4CvAP8y6jetdmwsdBn9kzBv6b5+Z6kXVNU9wBbgbOC/gD8DfrqqPrWMeUpaGQ+qCVX198BvAu8EPkv/xM7950U8gv55EnfSn6b4Av1zHwAuATZ30x7vqaqv0t8JeQJwK/368SZgapjEquom4PnAn3avfSbwzK4maZXwBlkTLMltwAur6oOHOxdJh581QS14xEKSJDUzVGOR5KwkN3U3Rzl/gefP6252cn339cL2qUoaV9YQaXIsORXS3Y7534EfBOaAa4CtVXXjwJjzgJmq2rZ8qUoaR9YQabIMc8TiFGB3Vd3SnSBzOf07o0nSMKwh0gQZ5j7qG3jgDUfmgFMXGPcTSU6nv2fyi1X1gJuU9Ho9zxKVVpmpqamswGasIdIaNr+ODHPEYqHCM/8P/L3ACVX13cAHgbceWnqS1iBriDRBhmks5njgndg28rW7MwJQVV/o7h8P/euZv6dNepLWAGuINEGGmQq5BphOciL926aeQ/+TK++X5NEDHzqzBdi1WMCpqaHuhbKg2dlZAGZmZg45xkrFNaYxW2oVt9frtUjnYKyqGgLj874bc/XHXK64qz3mYnVkycaiqvYl2QZcBayj/wl3O5NcBMxW1XbgpUm2APuALwLnjZy1pDXBGiJNlmGOWFBVO+h/7v3gYxcOLF9A/2N0JelBrCHS5PDOm5IkqRkbC0mS1IyNhSRJasbGQpIkNWNjIUmSmrGxkCRJzdhYSJKkZmwsJElSMzYWkiSpGRsLSZLUjI2FJElqxsZCkiQ1Y2MhSZKaGaqxSHJWkpuS7E5y/iLjnp2kkrT9sHtJY80aIk2OJRuLJOuAi4Gzgc3A1iSbFxh3DPBS4OrWSUoaX9YQabKkqhYfkJwGvKqqzuzWLwCoqlfPG/fHwAeBXwZ+uapmB5/v9Xr3b+jmm29ukrykgzc9PX3/8tTUVJZ7e9YQae1ZrI4MMxWyAdgzsD7XPXa/JCcDm6rqfYeepqQ1yhoiTZAjhhiz0B7N/XsOSR4CvA44b9iNzswc+vTp7OzsyDFWKq4xjdlSq7i9Xq9FOgdjVdUQGJ/33ZirP+ZyxV3tMRerI8McsZgDNg2sbwT2DqwfAzwe+EiS24AnA9s9+UpSxxoiTZBhGotrgOkkJyZZD5wDbN//ZFX1quqRVXVCVZ0AfBTYMn9+VNLEsoZIE2TJxqKq9gHbgKuAXcAVVbUzyUVJtix3gpLGmzVEmizDnGNBVe0Adsx77MIDjH3q6GlJWkusIdLk8M6bkiSpGRsLSZLUjI2FJElqxsZCkiQ1Y2MhSZKaGeqqEEnS8jj5bYt97slU/59dBx5z3bnTB3xOOhw8YiFJkpqxsZAkSc3YWEiSpGZsLCRJUjM2FpIkqRkbC0mS1IyNhSRJamaoxiLJWUluSrI7yfkLPP/zST6Z5Pok/5Rkc/tUJY0ra4g0OZZsLJKsAy4GzgY2A1sX+KO/rKq+q6qeALwG+KPmmUoaS9YQabKkqhYfkJwGvKqqzuzWLwCoqlcfYPxW4Ker6uzBx3u93v0buvnmxe40J2k5TU9/7U6NU1NTWe7tWUMW96JdUyO9/o0n9RplIg1vsToyzC29NwB7BtbngFPnD0ryEuAVwHrgaYeSqKQ1yRoiTZBhGouF9mgedJijqi4GLk7yXOA3gBccKODMzMzQCc43Ozs7coyVimtMY7bUKm6vt+J7uKuqhsAqe98X+RyQYRzs9lbV974GYi5X3NUec7E6MszJm3PApoH1jcDeRcZfDvzoUJlJmgTWEGmCDNNYXANMJzkxyXrgHGD74IAkgx+v9wxg7UyAShqVNUSaIEtOhVTVviTbgKuAdcCbq2pnkouA2araDmxL8nTgXuBOFjmEKWmyWEOkyTLMORZU1Q5gx7zHLhxYflnjvMbCyW9baqeqO9t7kTnU686dPuBz0lphDZEmh3felCRJzdhYSJKkZmwsJElSMzYWkiSpGRsLSZLUjI2FJElqxsZCkiQ1Y2MhSZKasbGQJEnN2FhIkqRmbCwkSVIzNhaSJKmZoRqLJGcluSnJ7iTnL/D8K5LcmOQTSf4+yWPapyppXFlDpMmxZGORZB1wMXA2sBnYmmTzvGHXATNV9d3AlcBrWicqaTxZQ6TJMswRi1OA3VV1S1XdA1wOPGtwQFV9uKr+p1v9KLCxbZqSxpg1RJogqarFByTPBs6qqhd26+cCp1bVtgOMfz1we1X9zuDjvV7v/g3dfPPNo+a9Krxo19TIMd54Uq9BJtLwpqen71+emprKcm/PGrK4UeuINUSHw2J15IghXr9Q4VmwG0nyfGAG+P6DyE/S2mYNkSbIMI3FHLBpYH0jsHf+oCRPB34d+P6q+spiAWdmZg4mxweYnZ0dOUazuLtG32s62O9jOb5/Y67+mC3j9norvoe7qmoIrLL3fcQ6Yg05vDGXK+5qj7lYHRnmHItrgOkkJyZZD5wDbB8ckORk4C+ALVV1xwi5Slp7rCHSBFmysaiqfcA24CpgF3BFVe1MclGSLd2wPwSOBv46yfVJth8gnKQJYw2RJsswUyFU1Q5gx7zHLhxYfnrjvCStIdYQaXJ4501JktSMjYUkSWpmqKmQteDkty115nV3LfkiZ2hfd+70AZ+TJEkesZAkSQ3ZWEiSpGYmZipEkibF4lO/S0/7glO/42i1TPl7xEKSJDVjYyFJkpqxsZAkSc3YWEiSpGZsLCRJUjM2FpIkqRkvN11lVsvlQlp5vveS1oKhjlgkOSvJTUl2Jzl/gedPT3Jtkn1Jnt0+TUnjzBoiTY4lG4sk64CLgbOBzcDWJJvnDfsMcB5wWesEJY03a4g0WYaZCjkF2F1VtwAkuRx4FnDj/gFVdVv33H0tkvKucdKasuI1RNLhM0xjsQHYM7A+B5w6ykZnZ2eXGDE1SvgDbGOSYy7v64zZKubKvPfT0yvedB+GGrKycUaLOdr7vvD2Dk8dWR0/z8MTc7niHlzMlXvfF6sjw5xjkQUeq6G2LEnWEGmiDHPEYg7YNLC+Edg7ykZnZmYWH7DENMchbWOSYy5hf4d6sK8zZuOYK/Te93q9kbdzkFa+hixhLb3vC25vhevIqvp5rnDM5Yp7SDFX8H1frI4Mc8TiGmA6yYlJ1gPnANuH2rIkWUOkibJkY1FV+4BtwFXALuCKqtqZ5KIkWwCSPCnJHPCTwF8k2bmcSUsaH9YQabIMdYOsqtoB7Jj32IUDy9fQP7wpSQ9iDZEmh7f0liRJzXhLb0kagrdcl4ZjYyFJWpI3LtSwnAqRJEnN2FhIkqRmnAqZAM4NS5JWio2FdAicb17dbKbHw3L8Ha18zOHiTtLvk1MhkiSpGY9Y6JCNumewUAc/LnswkqSFecRCkiQ1Y2MhSZKasbGQJEnNeI6FJEkrbC1faTLUEYskZyW5KcnuJOcv8PzXJfmr7vmrk5zQOlFJ48saIk2OJRuLJOuAi4Gzgc3A1iSb5w37WeDOqvo24HXAH7ROVNJ4soZIkyVVtfiA5DTgVVV1Zrd+AUBVvXpgzFXdmH9NcgRwO/CoGgje6/UW35CkFTc1NZXl3oY1RFrb5teRYaZCNgB7BtbnuscWHFNV+4AecNyhpylpDbGGSBNkmMZioT2a+XsOw4yRNJmsIdIEGeaqkDlg08D6RmDvAcbMdYcxp4AvDg5YiUOuklYla4g0QYY5YnENMJ3kxCTrgXOA7fPGbAde0C0/G/hQLXXyhqRJYQ2RJsiSjUU337kNuArYBVxRVTuTXJRkSzfsEuC4JLuBVwAPupyslaUuWzuEeG9OckeSG1rk18XclOTDSXYl2ZnkZQ1iPjTJx5J8vIv52y1y7WKvS3Jdkvc1jHlbkk8muT7JbKOYxya5Msmnup/taSPGe1yX3/6vLyV5eYM8f7F7j25I8o4kD20Q82VdvJ0tclxJa72GdDGtI43riDVkjGtIVY3NF7AO+A/gscB64OPA5hFjng48EbihYZ6PBp7YLR8D/HuDPAMc3S0fCVwNPLlRvq8ALgPe1/BncBvwyMbv/1uBF3bL64FjG/9u3Q48ZsQ4G4BbgaO69SuA80aM+XjgBuBh9KcvPwhMt/zZTsrXctSQLq51pHEdsYaMbw0Zt1t6nwLsrqpbquoe4HLgWaMErKp/ZN5c7qiq6rNVdW23/N/099LmnwV/sDGrqr7crR7ZfY18qDjJRuAZwJtGjbWckjyCfvG+BKCq7qmquxpu4gzgP6rq0w1iHQEc1Z0r8DAefD7BwToJ+GhV/U/19/7/AfixEWNOquY1BKwj41BHrCErV0PGrbEY5rK1VaW7g+DJ9PcMRo21Lsn1wB3AB6pq5JjAHwO/CtzXINagAt6f5N+SvLhBvMcCnwfe0h1ufVOShzeIu985wDtGDVJV/wm8FvgM8FmgV1XvHzHsDcDpSY5L8jDgh3ngyZAa3tjVEJjYOmINGdMaMm6NxVhdkpbkaOCdwMur6kujxquqr1bVE+ifVX9KksePmN+PAHdU1b+NmtsCnlJVT6R/t8WXJDl9xHhH0D/U/OdVdTJwN43m4bsTCrcAf90g1tfT3wM+ETgeeHiS548Ss6p20b8T5QeAv6N/+H7fiKlOqrGqITDRdcQaMqY1ZNwai2EuW1sVkhxJvxhcWlXvahm7O3z3EeCsEUM9BdiS5Db6h4SfluTtI8YEoKr2dv/eAbyb/iHoUcwBcwN7V1fSLxItnA1cW1WfaxDr6cCtVfX5qroXeBfwvaMGrapLquqJVXU6/UPuS32CkRY2NjUEJruOWEPGt4aMW2MxzGVrh12S0J/H21VVf9Qo5qOSHNstH0X/l+9To8SsqguqamNVnUD/Z/mhqhqpM+7ye3iSY/YvAz9E/1DcKLneDuxJ8rjuoTOAG0dK9Gu20uAQZuczwJOTPKz7PTiD/tz4SJJ8Y/fvtwA/Trt8J81Y1BCY7DpiDRnvGjJWH5teVfuS7L9sbR3w5qraOUrMJO8Ango8Mskc8FtVdcmIqT4FOBf4ZDeXCfDKqtoxQsxHA29N/wOdHkL/kr1ml4c29k3Au/t/ExwBXFZVf9cg7i8Al3b/IdwC/MyoAbv5xh8Efm7UWABVdXWSK4Fr6R9qvA54Q4PQ70xyHHAv8JKqurNBzImzHDUErCPLwBoyxjVkyQ8hkyRJGta4TYVIkqRVzMZCkiQ1Y2MhSZKasbGQJEnN2FhIkqRmbCwkSVIzNhaSJKkZGwtJktTM/wMYlMeMp+w8SQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb1e0a198>"
+       "<matplotlib.figure.Figure at 0x1db58ad2240>"
       ]
      },
      "metadata": {},
@@ -2868,9 +2861,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb1f56710>"
+       "<matplotlib.figure.Figure at 0x1db57752b00>"
       ]
      },
      "metadata": {},
@@ -2909,9 +2902,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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zOejm5ob58+dT3vGEio0NU6lUuH//Pu7du8cd4QQHB2PBggUme86mpiacP38e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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb0a2bfd0>"
+       "<matplotlib.figure.Figure at 0x1db58b25eb8>"
       ]
      },
      "metadata": {},
@@ -2943,17 +2936,16 @@
     "    \n",
     "**Predict**\n",
     "\n",
-    "    1. Based on the system behavior, predict state at the next time step\n",
+    "    1. Based on the system behavior, predict state for the next time step\n",
     "    2. Adjust belief to account for the uncertainty in prediction\n",
     "    \n",
     "**Update**\n",
     "\n",
     "    1. Get a measurement and associated belief about its accuracy\n",
-    "    2. Compute residual between estimated state and measurement\n",
-    "    3. Determine whether the measurement matches each state\n",
-    "    4. Update state belief if it matches the measurement\n",
+    "    2. Compute how likely it is the measurement matches each state\n",
+    "    3. Update state belief with this likelihood\n",
     "\n",
-    "When we cover the Kalman filter we will use this exact same algorithm; only the details of the computation will differ. \n",
+    "When we cover the Kalman filter we will use this exact same algorithm; only the details of the computation will differ.\n",
     "\n",
     "Algorithms in this form are sometimes called *predictor correctors*. We make a prediction, then correct them.\n",
     "\n",
@@ -3750,7 +3742,7 @@
     {
      "data": {
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\" 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\" width=\"800\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -3763,8 +3755,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Final posterior: [ 2.34e-19  2.92e-20  0.0089  0.144  0.605  0.215  0.0264  0.0011\n",
-      "  6.75e-20  3.09e-12]\n"
+      "Final posterior: [0.    0.    0.009 0.144 0.605 0.215 0.026 0.001 0.    0.   ]\n"
      ]
     }
    ],
@@ -4606,7 +4597,7 @@
     {
      "data": {
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Bv1bxTCPjnNo0M8oK7pPYnCQpG9L+qdp7zOX9DxJr5b0BEnvnWTQ9+zZI1tcY9bbjh07Zv2RjX3erl27Gtv3Zna8d+/e/elbtmzZzK4ayUUDjWBds9Oua6BJAk88/zu6YZ3SdtCi9O4n377Jj5563336DtigqYVTn/o1gX3SARqIaWAWWX3+e2BPI9q2zZZ3unFjFfdZqIrPgEBdAk0b9FqXuP+WpPdJ+o+S/nJKBEeVx7CdVWbe96etN4O+e/durax41qub8igmhO3caQvc92O7+OKL+zGQGY8CDcwYeLKPO/k9V21o0M97gpXJ9rc+fQeMJrUwpqk+6QANxDRA1uYILC0tafv27Rj0zWEkGwKtE2jaoNv95bYg3PgicbZwnK3qPu0icWbO7Xnmty2z6NOAGxp0uzTeZuoPaNCZQZ8G6YFjmDGIMWTWKMbNk9XnGZNJHJhBn0So/vvUwhhTamGMmycrcy0ccuozA2bQPd8GYiHQXQJNG3S7F/wDZSX380cwfFDS8VM+Zu1Xy+Xt75H0ZAfK0yS9StLjy+z7AQ36YDCQFbZZb9xz1zzxrt9zhwbQQJMEuAe9Sbrr75t70GPMqYUxbp6srv899IwlGttnBjwHPaoK8iDQLQJNG3QbrT3z/MRymfk3y4y6rcL+dElvLzjsmeb2jPO7SLIV2Ec3WxjOZsEfIemj6+B7sKQXlvvMbUG6m5d73p8t6UJJD2eRuNmIjqY0xpmmNMbNk9XnhmwSBwz6JEL136cWxphSC2PcPFmZa+GQU58ZYNA93wZiIdBdArMw6IdKepmkkyQdXlZat5XbzxvBck4x6HeWdMUYrm9I+hVJdlPNvnVQ3lXSaySdIOmIEnN52f+fS7p+PIdV3JsRJE1pjCtNaYybJ6vPDdkkDhj0SYTqv08tjDGlFsa4ebIy10IMukcpxEIAAm0SmIVBb3N86342Br2ZU0JTGuNKUxrj5snK3JRi0D1KqRNLLYxxpBbGuHmyMtdCDLpHKcRCAAJtEsCgF/rcg755GdKUxhjSlMa4ebIyN6UYdI9S6sRSC2McqYUxbp6szLUQg+5RCrEQgECbBDDoGPRq+qMpjaGkKY1x82Rlbkox6B6l1ImlFsY4Ugtj3DxZmWshBt2jFGIhAIE2CWDQMejV9EdTGkNJUxrj5snK3JRi0D1KqRNLLYxxpBbGuHmyMtdCDLpHKcRCAAJtEsCgY9Cr6Y+mNIaSpjTGzZOVuSnFoHuUUieWWhjjSC2McfNkZa6FGHSPUoiFAATaJIBBx6BX0x9NaQwlTWmMmycrc1OKQfcopU4stTDGkVoY4+bJylwLMegepRALAQi0SQCDjkGvpj+a0hhKmtIYN09W5qYUg+5RSp1YamGMI7Uwxs2TlbkWYtA9SiEWAhBokwAGHYNeTX80pTGUNKUxbp6szE0pBt2jlDqx1MIYR2phjJsnK3MtxKB7lEIsBCDQJgEMOga9mv5oSmMoaUpj3DxZmZtSDLpHKXViqYUxjtTCGDdPVuZaiEH3KIVYCECgTQIYdAx6Nf3RlMZQ0pTGuHmyMjelGHSPUurEUgtjHKmFMW6erMy1EIPuUQqxEIBAmwQw6Bj0avqjKY2hpCmNcfNkZW5KMegepdSJpRbGOFILY9w8WZlrIQbdoxRiIQCBNglg0DHo1fRHUxpDSVMa4+bJytyUYtA9SqkTSy2McaQWxrh5sjLXQgy6RynEQgACbRLAoGPQq+mPpjSGkqY0xs2TlbkpxaB7lFInlloY40gtjHHzZGWuhRh0j1KIhQAE2iSAQcegV9MfTWkMJU1pjJsnK3NTikH3KKVOLLUwxpFaGOPmycpcCzHoHqUQCwEItEkAg45Br6Y/mtIYSprSGDdPVuamFIPuUUqdWGphjCO1MMbNk5W5FmLQPUohFgIQaJMABh2DXk1/NKUxlDSlMW6erMxNKQbdo5Q6sdTCGEdqYYybJytzLcSge5RCLAQg0CYBDDoGvZr+aEpjKGlKY9w8WZmbUgy6Ryl1YqmFMY7Uwhg3T1bmWohB9yiFWAhAoE0CGHQMejX90ZTGUNKUxrh5sjI3pRh0j1LqxFILYxyphTFunqzMtRCD7lEKsRCAQJsEMOgY9Gr6oymNoaQpjXHzZGVuSjHoHqXUiaUWxjhSC2PcPFmZayEG3aMUYiEAgTYJYNAx6NX0R1MaQ0lTGuPmycrclGLQPUqpE0stjHGkFsa4ebIy10IMukcpxEIAAm0SwKBj0Kvpj6Y0hpKmNMbNk5W5KcWge5RSJ5ZaGONILYxx82RlroUYdI9SiIUABNokgEHHoFfTH01pDCVNaYybJytzU4pB9yilTiy1MMaRWhjj5snKXAsx6B6lEAsBCLRJAIOOQa+mP5rSGEqa0hg3T1bmphSD7lFKnVhqYYwjtTDGzZOVuRZi0D1KIRYCEGiTAAYdg15NfzSlMZQ0pTFunqzMTSkG3aOUOrHUwhhHamGMmycrcy3EoHuUQiwEINAmAQw6Br2a/mhKYyhpSmPcPFmZm1IMukcpdWKphTGO1MIYN09W5lqIQfcohVgIQKBNAhh0DHo1/dGUxlDSlMa4ebIyN6UYdI9S6sRSC2McqYUxbp6szLUQg+5RCrEQgECbBDDoGPRq+qMpjaGkKY1x82Rlbkox6B6l1ImlFsY4Ugtj3DxZmWshBt2jFGIhAIE2CWDQMejV9EdTGkNJUxrj5snK3JRi0D1KqRNLLYxxpBbGuHmyMtdCDLpHKcRCAAJtEsCgY9Cr6Y+mNIaSpjTGzZOVuSnFoHuUUieWWhjjSC2McfNkZa6FGHSPUoiFAATaJDALg36opDMlnSTpcEmXSnqlpPMmDPwUSX+zQcxtJP1g7L2TJZ0u6RhJP5T0TkkvkvTT8X0sLy8fubKycvXo64PBQIuLizM/FzQkzSPvekOCBtBAkwQw6E3SXX/fGPQYc2phjJsnq+t/Dz1jicb2mcHq6qqWl5fXoFlaWto6GAyuifIiDwIQmD2BWRj0j0jaWczzZZKeKulUSU+T9I4DDHlo0J9ZTP1o6Jck7R15wfb1NklvKvu8m6RXSfqCpEdg0GcjLJrSGGea0hg3T1afG7JJHDDokwjVf59aGGNKLYxx82RlroVDTn1mgEH3fBuIhUB3CTRt0B8j6YJiys8dwWCm/ThJ2yStbIBnaNDN3H/xAAiXJH1b0j9KeuRInP0Q8HZJdgwfHM1nBr0ZQdKUxrjSlMa4ebL63JBN4oBBn0So/vvUwhhTamGMmycrcy3EoHuUQiwEINAmgaYN+tmS7NLzW0u6YWSgTykz3Q+S9NlNGnTbx99Lsn2OXja/pVzqbj8MPBuD3rzMaEpjjGlKY9w8WZmbUgy6Ryl1YqmFMY7Uwhg3T1bmWohB9yiFWAhAoE0CTRv0z0myGe77jg3SZs+/Iuk5kt44waBfJelIST+R9ElJf1Jyh2m2j9eXGfmvje3r4nIp/AMx6M3LjKY0xpimNMbNk5W5KcWge5RSJ5ZaGONILYxx82RlroUYdI9SiIUABNok0LRBt3vOd0t61NggbZG370l6gaRXbADAcn5N0kWSrpV0r3Ifu83G26z5JSXP9vEySestHPdhSXeSdPdJBn3Pnj2ye3dmve3YsWPWH9nY5+3atauxfW9mx3v33rhcwZYtdmFFtzY00Pz56LoGmiTwxPO/oxvWKW0HLUrvfvLtm/zoqffdp++ADZpaOPWpXxPYJx2ggZgGZpHV578Httjxtm129+iNG4vEzUJVfAYE6hKYhUH/lqRHb2DQzygruk87KjPbdq/5JyT99phB/1VJNts+uplBv2NZ2X3/6+vdg757926trGx0O/y0h+eP27nTbrHvx3bxxXbBApuXABrwEiPeQ+Dk91y1oUE/7wlHeXbVWGyfvgMGiVoYk0qfdIAGYhoga3MElpaWtH379jU7waBvjinZEGiDQNMGfTOXuG/EwxZ8u4+kYWdZ5RJ3ZtA3Lz9mDGIMmTWKcfNk9XnGZBIHZtAnEar/PrUwxpRaGOPmycpcC4ec+syAGXTPt4FYCHSXQNMG3e4vt8XbxheJs4XjbPG2Ay0StxG1D0k6oVzSbjF2f/lnymJ0548kHSTpR+VzWCRuBhrkvssYZO67jHHzZGW+75J70D1KqRNLLYxxpBbGuHmyMtfCIac+M+Axa55vA7EQ6C6Bpg26Xdr+gXXMs82CHz/hMWvrUbuzpH+Q9DFJv1MCho9Zs3vSRy+lH/4IYK+Zqd+/8Zi1ZgRJUxrjSlMa4+bJ6nNDNokDBn0SofrvUwtjTKmFMW6erMy1EIPuUQqxEIBAmwSaNug2Nnvm+YmSni/pm2VG/VmSnl6eU24xb5b0DEl3kXRlAWIm/FPFkA8XiTtN0qDMmtsq8MPN9vXWsiK8zcwfLeksuxVQ0iPGAWPQm5EcTWmMK01pjJsnK3NTikH3KKVOLLUwxpFaGOPmycpcCzHoHqUQCwEItElgFgb90LLK+kmSDpd0aVm5ffSZ5ecUg24z5FcUIH9RzPUdJN1C0tVlcbiXSrLV4cc3u5T+9LIg3A8lvVPSCyX9FIM+G4nRlMY405TGuHmyMjelGHSPUurEUgtjHKmFMW6erMy1EIPuUQqxEIBAmwRmYdDbHN+6n80MejOnhKY0xpWmNMbNk5W5KcWge5RSJ5ZaGONILYxx82RlroUYdI9SiIUABNokgEEv9AeDgWz1y1lvNCTNE+96Q4IG0ECTBDDoTdJdf98Y9BhzamGMmyer638PPWOJxvaZAYvERVVBHgS6RQCDjkGvpkia0hhKmtIYN09WnxuySRww6JMI1X+fWhhjSi2McfNkZa6FQ059ZoBB93wbiIVAdwlg0DHo1dRJUxpDSVMa4+bJ6nNDNokDBn0SofrvUwtjTKmFMW6erMy1EIPuUQqxEIBAmwQw6Bj0avqjKY2hpCmNcfNkZW5KMegepdSJpRbGOFILY9w8WZlrIQbdoxRiIQCBNglg0DHo1fRHUxpDSVMa4+bJytyUYtA9SqkTSy2McaQWxrh5sjLXQgy6RynEQgACbRLAoGPQq+mPpjSGkqY0xs2TlbkpxaB7lFInlloY40gtjHHzZGWuhRh0j1KIhQAE2iSAQcegV9MfTWkMJU1pjJsnK3NTikH3KKVOLLUwxpFaGOPmycpcCzHoHqUQCwEItEkAg45Br6Y/mtIYSprSGDdPVuamFIPuUUqdWGphjCO1MMbNk5W5FmLQPUohFgIQaJMABh2DXk1/NKUxlDSlMW6erMxNKQbdo5Q6sdTCGEdqYYybJytzLcSge5RCLAQg0CYBDDoGvZr+aEpjKGlKY9w8WZmbUgy6Ryl1YqmFMY7Uwhg3T1bmWohB9yiFWAhAoE0CGHQMejX90ZTGUNKUxrh5sjI3pRh0j1LqxFILYxyphTFunqzMtRCD7lEKsRCAQJsEMOgY9Gr6oymNoaQpjXHzZGVuSjHoHqXUiaUWxjhSC2PcPFmZayEG3aMUYiEAgTYJYNAx6NX0R1MaQ0lTGuPmycrclGLQPUqpE0stjHGkFsa4ebIy10IMukcpxEIAAm0SwKBj0Kvpj6Y0hpKmNMbNk5W5KcWge5RSJ5ZaGONILYxx82RlroUYdI9SiIUABNokgEHHoFfTH01pDCVNaYybJytzU4pB9yilTiy1MMaRWhjj5snKXAsx6B6lEAsBCLRJAIOOQa+mP5rSGEqa0hg3T1bmphSD7lFKnVhqYYwjtTDGzZOVuRZi0D1KIRYCEGiTAAYdg15NfzSlMZQ0pTFunqzMTSkG3aOUOrHUwhhHamGMmycrcy3EoHuUQiwEINAmAQw6Br2a/mhKYyhpSmPcPFmZm1IMukcpdWKphTGO1MIYN09W5lqIQfcohVgIQKBNAhh0DHo1/dGUxlDSlMa4ebIyN6UYdI9S6sRSC2McqYUxbp6szLUQg+5RCrEQgECbBDDoGPRq+qMpjaGkKY1x82Rlbkox6B6l1ImlFsY4Ugtj3DxZmWshBt2jFGIhAIE2CXJPVYcAABzWSURBVGDQMejV9EdTGkNJUxrj5snK3JRi0D1KqRNLLYxxpBbGuHmyMtdCDLpHKcRCAAJtEsCgY9Cr6Y+mNIaSpjTGzZOVuSnFoHuUUieWWhjjSC2McfNkZa6FGHSPUoiFAATaJIBBx6BX0x9NaQwlTWmMmycrc1OKQfcopU4stTDGkVoY4+bJylwLMegepRALAQi0SQCDjkGvpj+a0hhKmtIYN09W5qYUg+5RSp1YamGMI7Uwxs2TlbkWYtA9SiEWAhBokwAGHYNeTX80pTGUNKUxbp6szE0pBt2jlDqx1MIYR2phjJsnK3MtxKB7lEIsBCDQJgEMOga9mv5oSmMoaUpj3DxZmZtSDLpHKXViqYUxjtTCGDdPVuZaiEH3KIVYCECgTQIYdAx6Nf3RlMZQ0pTGuHmyMjelGHSPUurEUgtjHKmFMW6erMy1EIPuUQqxEIBAmwQw6Bj0avqjKY2hpCmNcfNkZW5KMegepdSJpRbGOFILY9w8WZlrIQbdoxRiIQCBNgnMwqAfKulMSSdJOlzSpZJeKem8CQN/gqQnSdop6XaSrpL0GUkvkXT5WO4nJT1knf19WNKjxl9fXl4+cmVl5erR1weDgRYXF2d+LmhImkfe9YYEDaCBJglg0Juku/6+Megx5tTCGDdPVtf/HnrGEo3tM4PV1VUtLy+vQbO0tLR1MBhcE+VFHgQgMHsCszDoHykm+3RJl0l6qqRTJT1N0jsOMOTPS/qBpP8pabekO0h6Qfn3/pK+OpJrBt3et32Obj8uPwiseRGD3ozQaEpjXGlKY9w8WX1uyCZxwKBPIlT/fWphjCm1MMbNk5W5Fg459ZkBBt3zbSAWAt0l0LRBf4ykC4opP3cEg5n24yRtk7SyAZ6tktbMcku6raQrJP1tMfnDVDPoR0i65zSoMejTUPLH0JT6mVkGTWmMmyerzw3ZJA4Y9EmE6r9PLYwxpRbGuHmyMtdCDLpHKcRCAAJtEmjaoJ8t6WRJt5Z0w8hAn1Jmzx8k6bNOADabbpe4P3IkD4PuhNhEOE1pjCpNaYybJ6vrTem93zp+145ndAeO/dHXLpf27btp0MKCbn2Po+t90MievvxvfPvt03fAMFALY7Lqkw7QQEwDTdbC2BHFs7x1MP5JN2Yyg16DIvuAQPsEmjbon5O0JOm+Y0O12fOvSHqOpDc6MGwv5vw1kv7TmEG/n6SfSzpM0pXlHne7991eW7Mxg+4g7gilIXHAGgmlKY1x82Rh0DHoHr1sNpZaGCNILYxx82RlroUeTjViMeg1KLIPCOQk0LRBt3vObcZ7fKG220j6Xrmn/BVToj9I0kcl3adcyv7tkTwz4t8t95vfQtKjJT23zM4/VNLq6GesZ9D37Nkj++Vx1tuOHTtm/ZGNfd6uXbsa2/dmdrx379796Vu2bNnMrhrJRQONYF2z065r4JR/OLgxCG3MoJ9z/M9c4+nTd8AGTi10nf79wX3SARqIaaDJWhg7oniWtw7GP+nGTFvseNs2u3v0xo1F4mqQZR8QmC2BWRj0bxXDPDqyoUE/o6zoPmnUdpznlEXgnijpfZMSJD1P0qsl2Wrw7x2NX8+g7969WysrG90OP8WnBUN27rRF6vuxXXzxxf0YyIxHgQZmDLyDH/esr9+ysaNqw6CffexPXOPp03fABk4tdJ3+/cF90gEaiGmgyVoYO6J4lrcOxj9pjRnX9u12sSkGvQZP9gGBtgg0bdBrXOJux/gmSadIeoakt00J66iyCvxZkp4/yaAzgz4l1QOEMWMQY8isUYybJ4sZ9Nle4u6dOerTd8B0SS30fDtvjO2TDtBATAPMoMe4DbOYQd8cP7Ih0BUCTRt0u7/cFoQbXyTOFo6zVd0nLRI3NOfPlPR7kv7GAW5o0O2Z6zZTv3/jHnQHRUco9106YI2Ect9ljJsnK/N9l23MoHvvvezTd8B0SS30fDtvjO2TDtBATAMsEhfjNsxikbjN8SMbAl0h0LRBt3vBP1BWcj9/ZNAflHT8hMes2bHZKvC/WxaTs//t2U6T9CpJjx+/JB6D7sE4fSwNyfSsRiNpSmPcPFkY9NnOoGPQ1+HtEWxDsV3/HlALGzrxI7vtugYw6JvTAAZ9c/zIhkBXCDRt0G2c9szzE8tl5t8sM+rPkvR0SW8vIN5cLl+/S1mB3V7+75L+SNJbilEfZXa9pC+XFx4s6YXlPnNbkO7m5Z73Z0u6UNLDp1kkbjAYyC4NmvVGQ9I88a43JGgADTTZlDKD3ry+xj+BHytjzKmFMW6erK7/PWyyFno41Yj1/lBZ4zMx6DUosg8ItE9gFgb9UEkvk3SSpMPLSuu2cvt5I8O3BeDs/vI7S7qivG7/3nEDRPYYtTuV9+4qyR67doKkI+zqwvIoNtv/n0syM79mYwa9GeHRlMa40pTGuHmyMjelGHSPUurEUgtjHKmFMW6erMy10MOpRiwGvQZF9gGBnARmYdA7RxaD3swpoSmNcaUpjXHzZGVuSjHoHqXUiaUWxjhSC2PcPFmZa6GHU41YDHoNiuwDAjkJYNDLeecS981/AWhKYwxpSmPcPFmZm1IMukcpdWKphTGO1MIYN09W5lro4VQjFoNegyL7gEBOAhh0DHo15dOUxlDSlMa4ebIyN6UYdI9S6sRSC2McqYUxbp6szLXQw6lGLAa9BkX2AYGcBDDoGPRqyqcpjaGkKY1x82Rlbkox6B6l1ImlFsY4Ugtj3DxZmWuhh1ONWAx6DYrsAwI5CWDQMejVlE9TGkNJUxrj5snK3JRi0D1KqRNLLYxxpBbGuHmyMtdCD6casRj0GhTZBwRyEsCgY9CrKZ+mNIaSpjTGzZOVuSnFoHuUUieWWhjjSC2McfNkZa6FHk41YjHoNSiyDwjkJIBBx6BXUz5NaQwlTWmMmycrc1OKQfcopU4stTDGkVoY4+bJylwLPZxqxGLQa1BkHxDISQCDjkGvpnya0hhKmtIYN09W5qYUg+5RSp1YamGMI7Uwxs2TlbkWejjViMWg16DIPiCQkwAGHYNeTfk0pTGUNKUxbp6szE0pBt2jlDqx1MIYR2phjJsnK3Mt9HCqEYtBr0GRfUAgJwEMOga9mvJpSmMoaUpj3DxZmZtSDLpHKXViqYUxjtTCGDdPVuZa6OFUIxaDXoMi+4BATgIYdAx6NeXTlMZQ0pTGuHmyMjelGHSPUurEUgtjHKmFMW6erMy10MOpRiwGvQZF9gGBnAQw6Bj0asqnKY2hpCmNcfNkZW5KMegepdSJpRbGOFILY9w8WZlroYdTjVgMeg2K7AMCOQlg0DHo1ZRPUxpDSVMa4+bJytyUYtA9SqkTSy2McaQWxrh5sjLXQg+nGrEY9BoU2QcEchLAoGPQqymfpjSGkqY0xs2TlbkpxaB7lFInlloY40gtjHHzZGWuhR5ONWIx6DUosg8I5CSAQcegV1M+TWkMJU1pjJsnK3NTikH3KKVOLLUwxpFaGOPmycpcCz2casRi0GtQZB8QyEkAg45Br6Z8mtIYSprSGDdPVuamFIPuUUqdWGphjCO1MMbNk5W5Fno41YjFoNegyD4gkJMABh2DXk35NKUxlDSlMW6erMxNKQbdo5Q6sdTCGEdqYYybJytzLfRwqhGLQa9BkX1AICcBDDoGvZryaUpjKGlKY9w8WZmbUgy6Ryl1YqmFMY7Uwhg3T1bmWujhVCMWg16DIvuAQE4CGHQMejXl05TGUNKUxrh5sjI3pRh0j1LqxFILYxyphTFunqzMtdDDqUYsBr0GRfYBgZwEMOgY9GrKpymNoaQpjXHzZGVuSjHoHqXUiaUWxjhSC2PcPFmZa6GHU41YDHoNiuwDAjkJYNAx6NWUT1MaQ0lTGuPmycrclGLQPUqpE0stjHGkFsa4ebIy10IPpxqxGPQaFNkHBHISwKBj0Kspn6Y0hpKmNMbNk5W5KcWge5RSJ5ZaGONILYxx82RlroUeTjViMeg1KLIPCOQkgEHHoFdTPk1pDGX2pvTeb708Bq6jWZGmrEkGGPTZC4VaGGNOLaQWNlkLY6qMZ0X+FsQ/7ZeZq6urWl5eXrObpaWlrYPB4JrN7pt8CEBgdgQw6Bj0amqLNKV9+mNsICN/kGlKaUqb/B5g0KuVuKl3RC2kFqKBmAaarIVTf4ErBUb6gc1+NAZ9swTJh0A3CGDQMejVlEhDEmtIMOgY9CabUgx6tRI39Y6ohdRCNBDTQJO1cOovcKVADHolkOwGAgkJYNAx6NVkT0NCQxJpSPrUkEWvomiSAQa9WombekfUQmohtRANRDQwdZHZIJAZ9M0SJB8C3SCAQcegV1MiTSkNSaQhadKcVhO3Y0ddY4BBd5y8SqHUQmph1+pAJWm7dpOdQWT8LsDrBGPQN0uQfAh0gwAGHYNeTYk0pTSlkYYEgy41yQCDXq3ETb0jaiG1kFqIBiIamLrIMIO+WVTkQ6DTBGZh0A+VdKakkyQdLulSSa+UdN4UZLZKOkvS4yQdLOkSSS+S9PF1ch8m6aWSTpD0M0nvl3SapKvHY5eXl49cWVlZ8/pgMNDi4uIUh1Q3pMnGvO6RTt5b5I9Rn8ZvhLIzyD7+LmpgHgw6daDZH2kmV+/6EdlrQfbxd7EW1lf5gfcY0cBmj5EZ9M0SJB8C3SAwC4P+EUk7JZ0u6TJJT5V0qqSnSXrHATDcTNIXJd2q5Jqh/kNJj5VkZvzCkdyHSPqYpAskvVaSGftXSfqRpBMlXT/6ORj0ZsQX+WNEY96vxhwNdO9HGgx6M/XuQHvle9C978GsVYAG0EBEA5vVKQZ9swTJh0A3CDRt0B9TTLOZ8nNHhmym/ThJ2yStbIDiD4rZfqCkz5WYg8os+k8l3W8k7wuSDimz5zeU1y3vM5JsP6/DoDcvuMgfIww6Bh0NNKsBDHrztW/8E6iFmDM0gAYiGthstcKgb5Yg+RDoBoGmDfrZkk6WdGtJQ+NsI39KmT1/kKTPboDio5LuIOmYsffPkPRySbeX9F1Jt5P0HUn2ul06P7p9Q9KVkh4xZtC3rqysXDX62iGHHNLKJe6/8a7d3VBChaP4xJO2u/fSp/Hb4LMzyD7+LmrgJ9/YLe3bd9Pv5sKCbnl3/3d2mi+5VwfUAQkG/WLg/Q7Y9woN9ItBRAPT1NcDxZhBv+6669aELC0tHTUYDG5yu+dmP4t8CECgOQJNG3Sb+V6SdN+xIdjs+VckPUfSGzcY3vclfbrcuz4aYpe42/3lj5RkM/H274fKpe8fGNvXuyTZjwC3HX392muvPWZ1dfXrzWFlzxCAAAQgAAEIQAACEGiXwOLi4rGHHXaYrf/EBgEIzAmBpg263XNuU8SPGuNxG0nfk/QCSa/YgNUvJL1F0nPH3n9AmXUfXjZv/75dkr1+0VjsGySdIsnuZ9+/YdDnRJ0cJgQgAAEIQAACEIBAmAAGPYyORAi0RmAWBv1bkh69gUFf77L0YagZ9DdL+v0NDLpdJm8rwQ8N+v0lfX4dg/4MSTfHoLemMT4YAhCAAAQgAAEIQKAFAhj0FqDzkRDYJIGmDTqXuG/yBJEOAQhAAAIQgAAEIACBCAEMeoQaORBol0DTBt3uL7eZ7vFF4mzhOFvV/UCLxNn95bZI3LFjiOxxbXZZvC0OZ5fJDxeJs9ft0Wqjm91zs2d8kbh9+/YtLS8vHz0auLCw8ENJ66yk1O4J4tMhAAEIQAACEIAABCAwBYGFffv2HT4aNxgMLl9YWNjoiUlT7JIQCEBg1gSaNuh2abst3GaG/PyRwX1Q0vETHrNml7b/taTRS9ftMWu7JNlj1uz14WaXth8sacfIY9vsfZvBt/28ftZg+TwIQAACEIAABCAAAQhAAAIQgICHQNMG3Y7FZsJPlPR8Sd8sM+rPkvT0sribxdi95nav+F3KY9HsNVvY7UuSDpNks+P2iAh7pvlvSnqYpAtHBvrrkuyxbH9XTP3W8si1n5TPvt4DhVgIQAACEIAABCAAAQhAAAIQgMCsCczCoB8q6WXlcWl22Y1ddm6XqNsCb8PtnGLQ7yzpipHXj5J0lqTHlRlymz1/saSPrQPq4ZL+rMyi/6w8iu2Pi7GfNdcufJ5xP3OMuz0nfpR7F46zyWMYFL3YlRX3lnSEpD+V9JImP7RD+/6N8kPYA8vtIj+W9MXyPbEfv/q+2Xm32nMvSUdK+rmkb0h6raS39X3wG4zvVElnS7IH5VqN6PtmP97+rw0Gud6TP/rM49fKk1Ns3LZw6nck/a2kl/Z50JKG/cVGw8yiA/sb+F/KY29vVW7/e4ekV0uynqnvmz3u17Rufw+t971Y0oskfabvA2d8EIDA/BGYhUGfPyr9OGK7cmFnufrAHndnq91bc/40SfZHOcN2p3JLxCWSjIGNP5NBf5ekfyHJ/v1aManPK1eVPFLSJ3ouAjNndnvN30v6rqRDiv7tNfuhz37AyrTZeh1fLeb8lskMuj3Sc9yof6XcLpVBA1b/3yrpnaX+221idsXabcsPdn1mYOO0H+jGN7vizq6uu+PIrXF95XCPckWi/UD5ckn/V9K/LAb1Akm/3deBl3FZL/RpSV+Q9F+LQT+t/HD/0HI7ZM8RMDwIQGCeCGDQ5+lsTX+sj5Fkf3SHz4ofZpppP27Cvf/Tf0r3I4f6tsX/bPb8mmQG3W71sFtDRjebNbVbTcyc2K0iGbeLijHZlmzwZkjsu2ALYv7rZAb9SZL+R7LzPRyu/TBjxsxmy+02MTbpIZI+WX6ksx/r+r7Zj5EvlHRXSfbo2+H2BknPlmRXN/6oxxA+VK6u3D5ytYBdYbe7/HhvCxazQQACEOgMAQx6Z05F1QOxS1htlnB89XxbUd9mzw+0en7VA+nQzjIa9I3w28y5Ne1379D5meWhvF+SzShZs5ZlszU/bNFNG7c16xj0LGf+l5c12209dkXRlXmGfcCR2o8V9p2w2fX/k4DJUAN2JYHNng83e/LNfy5r/dhtL33dlsukhfVFo9u7JT2h/GD7/b4OnnFBAALzRwCDPn/nbJoj3szz56fZ/zzGYNB/edbs0mZr0s2kW2OSYVuUZP/ZD1Y2k/oaSX8kyWaPMmx2JYXd4vAnxaTbPbnZDLpdSWK3e9i9tlYf7V5Uu/Uhw/bxMntoV1SZIbtnuYriPZLsMt9rM0AYGaPVQDNjdu+xrV2TYbMfZ75c1u+xBXvtajK7isDW4rAfK/5dzyHYrQy2/o4tRjy62YSFTVzYLV92hSEbBCAAgU4QwKB34jRUPwi739ou3XrU2J5vU54db/dj2kJ9mTYM+i/PtjVkTy6PKcywUJyN2R6z+Jwi9l9I+g+SXpdI/HZpt333bZEwu8Q9k0G3hbGsKbfLmf+pXOJri4feTdJjJX04gQ5sYVa7z3pvqfv2A4Xdk2vrcfxvSQ8uukiA4p+H+Nzy/TdjlmnR1GMkvVeS/Tvc/luph1YX+rzZjxP2KN5jJa2Wgdpje+3WD7uSavx2wD6zYGwQgMAcEMCgz8FJChyiGXS7z8yeQz+6DQ36GeUxdIFdz20KBv2Xs4a2au2/lfRXc3sm/Qdu95rbLLL9Z49ptHsubRbJVi/u+/bEcluLGVWbRbctk0Ff7/zaCtb/WGaRT+i7AMo9tkdLGq/7/17SX5ZZ5PWejNJXNLZ6tz0xxm7zyfIIVptBt0fRXiXpL8oM+v3K3wP7Ae/3+nqyy7h+tzzO136YtSd72BVVdtn/KZKWyi2B5/ecAcODAATmiAAGfY5OluNQucT9prCyG/ThPYi2UJCt4pt5sybNVvS3FaztUs++bsMFAe2qidEV6+1e9N+SdPsyq9rne083OremAZtJtVk1e/xenzf7e3B/SfcplzkPx2pXEdgMov1YZY8zzbAdL8me6mG3udiVNFk2u1LAViu32eLR7/szJb1Fkj3x4sKewzCd2w/Uw8dL2vfiU0X/dhVJllteen6aGR4E+kEAg96P8zg+ijeW+6rGF4mzBVLOZZG4NM9BH+piaM5toSi7rDX7NmxKzbR8vscwbNZs0gJY75P0+B4z2Ghow9sebiHp//V8/MOVuscNui0SaZe/2yX/Ga4msdNsxtzut75XeZJFz0/9/uHZebb77s2kj262HoFdTWJrcrw2AYybSbKrSWzROFuLxb4b9uhZWzyv7z/UJTi9DBEC/SGAQe/PuWQkEIAABCAAAQhAAAIQgAAEIDDHBDDoc3zyOHQIQAACEIAABCAAAQhAAAIQ6A8BDHp/ziUjgQAEIAABCEAAAhCAAAQgAIE5JoBBn+OTx6FDAAIQgAAEIAABCEAAAhCAQH8IYND7cy4ZCQQgAAEIQAACEIAABCAAAQjMMQEM+hyfPA4dAhCAAAQgAAEIQAACEIAABPpDAIPen3PJSCAAAQhAAAIQgAAEIAABCEBgjglg0Of45HHoEIAABCAAAQhAAAIQgAAEINAfAhj0/pxLRgIBCEAAAhCAAAQgAAEIQAACc0wAgz7HJ49DhwAEIAABCEAAAhCAAAQgAIH+EMCg9+dcMhIIQAACEIAABCAAAQhAAAIQmGMCGPQ5PnkcOgQgAAEIQAACEIAABCAAAQj0hwAGvT/nkpFAAAIQgAAEIAABCEAAAhCAwBwTwKDP8cnj0CEAAQhAAAIQgAAEIAABCECgPwQw6P05l4wEAhCAAAQgAAEIQAACEIAABOaYAAZ9jk8ehw4BCEAAAhCAAAQgAAEIQAAC/SGAQe/PuWQkEIAABCAAAQhAAAIQgAAEIDDHBDDoc3zyOHQIQAACEIAABCAAAQhAAAIQ6A8BDHp/ziUjgQAEIAABCEAAAhCAAAQgAIE5JoBBn+OTx6FDAAIQgAAEIAABCEAAAhCAQH8IYND7cy4ZCQQgAAEIQAACEIAABCAAAQjMMQEM+hyfPA4dAhCAAAQgAAEIQAACEIAABPpDAIPen3PJSCAAAQhAAAIQgAAEIAABCEBgjglg0Of45HHoEIAABCAAAQhAAAIQgAAEINAfAhj0/pxLRgIBCEAAAhCAAAQgAAEIQAACc0wAgz7HJ49DhwAEIAABCEAAAhCAAAQgAIH+EMCg9+dcMhIIQAACEIAABCAAAQhAAAIQmGMCGPQ5PnkcOgQgAAEIQAACEIAABCAAAQj0hwAGvT/nkpFAAAIQgAAEIAABCEAAAhCAwBwTwKDP8cnj0CEAAQhAAAIQgAAEIAABCECgPwQw6P05l4wEAhCAAAQgAAEIQAACEIAABOaYAAZ9jk8ehw4BCEAAAhCAAAQgAAEIQAAC/SGAQe/PuWQkEIAABCAAAQhAAAIQgAAEIDDHBDDoc3zyOHQIQAACEIAABCAAAQhAAAIQ6A8BDHp/ziUjgQAEIAABCEAAAhCAAAQgAIE5JoBBn+OTx6FDAAIQgAAEIAABCEAAAhCAQH8IYND7cy4ZCQQgAAEIQAACEIAABCAAAQjMMQEM+hyfPA4dAhCAAAQgAAEIQAACEIAABPpDAIPen3PJSCAAAQhAAAIQgAAEIAABCEBgjglg0Of45HHoEIAABCAAAQhAAAIQgAAEINAfAhj0/pxLRgIBCEAAAhCAAAQgAAEIQAACc0wAgz7HJ49DhwAEIAABCEAAAhCAAAQgAIH+EMCg9+dcMhIIQAACEIAABCAAAQhAAAIQmGMCGPQ5PnkcOgQgAAEIQAACEIAABCAAAQj0hwAGvT/nkpFAAAIQgAAEIAABCEAAAhCAwBwTwKDP8cnj0CEAAQhAAAIQgAAEIAABCECgPwQw6P05l4wEAhCAAAQgAAEIQAACEIAABOaYAAZ9jk8ehw4BCEAAAhCAAAQgAAEIQAAC/SGAQe/PuWQkEIAABCAAAQhAAAIQgAAEIDDHBDDoc3zyOHQIQAACEIAABCAAAQhAAAIQ6A+B/w8AEcxTTFBcigAAAABJRU5ErkJggg==\" width=\"800\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -4619,8 +4610,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Final posterior: [ 0.0372  0.0648  0.055  0.0765  0.267  0.0372  0.0648  0.055  0.0765\n",
-      "  0.267]\n"
+      "Final posterior: [0.037 0.065 0.055 0.076 0.267 0.037 0.065 0.055 0.076 0.267]\n"
      ]
     }
    ],
@@ -5430,7 +5420,7 @@
     {
      "data": {
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\" 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+       "<img 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\" width=\"800\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -5443,8 +5433,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Final posterior: [ 0.121  0.102  0.0329  0.0938  0.151  0.121  0.102  0.0329  0.0938\n",
-      "  0.151]\n"
+      "Final posterior: [0.121 0.102 0.033 0.094 0.151 0.121 0.102 0.033 0.094 0.151]\n"
      ]
     }
    ],
@@ -5467,9 +5456,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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Ma57pYpprFmGuWdJE8sy0FjjHALcNLc/R8B/vaukuM38ig72fVjE3JPkkcDfwkapqFht4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\npodufv6A96rXZJ6BNf6dn2B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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb022a5f8>"
+       "<matplotlib.figure.Figure at 0x1db588608d0>"
       ]
      },
      "metadata": {},
@@ -5543,9 +5532,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "class Train(object):\n",
@@ -5594,34 +5581,36 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def train_filter(iterations, kernel, sensor_accuracy, \n",
     "             move_distance, do_print=True):\n",
     "    track = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])\n",
     "    prior = np.array([.9] + [0.01]*9)\n",
+    "    posterior = prior[:]\n",
     "    normalize(prior)\n",
     "    \n",
     "    robot = Train(len(track), kernel, sensor_accuracy)\n",
     "    for i in range(iterations):\n",
+    "        # move the robot and\n",
     "        robot.move(distance=move_distance)\n",
+    "\n",
+    "        # peform prediction\n",
+    "        prior = predict(posterior, move_distance, kernel)       \n",
+    "\n",
+    "        #  and update the filter\n",
     "        m = robot.sense()\n",
+    "        likelihood = lh_hallway(track, m, sensor_accuracy)\n",
+    "        posterior = update(likelihood, prior)\n",
+    "        index = np.argmax(posterior)\n",
+    "\n",
     "        if do_print:\n",
     "            print('''time {}: pos {}, sensed {}, '''\n",
     "                  '''at position {}'''.format(\n",
     "                    i, robot.pos, m, track[robot.pos]))\n",
     "\n",
-    "        likelihood = lh_hallway(track, m, sensor_accuracy)\n",
-    "        posterior = update(likelihood, prior)\n",
-    "        index = np.argmax(posterior)\n",
-    "        if i < iterations - 1:\n",
-    "            prior = predict(posterior, move_distance, kernel)       \n",
-    "\n",
-    "        if do_print:\n",
-    "            print('''        predicted position is {}'''\n",
+    "            print('''        estimated position is {}'''\n",
     "                  ''' with confidence {:.4f}%:'''.format(\n",
     "                  index, posterior[index]*100))            \n",
     "\n",
@@ -5630,7 +5619,7 @@
     "        print()\n",
     "        print('final position is', robot.pos)\n",
     "        index = np.argmax(posterior)\n",
-    "        print('''predicted position is {} with '''\n",
+    "        print('''Estimated position is {} with '''\n",
     "              '''confidence {:.4f}%:'''.format(\n",
     "                index, posterior[index]*100))"
    ]
@@ -5654,23 +5643,23 @@
      "output_type": "stream",
      "text": [
       "time 0: pos 4, sensed 4, at position 4\n",
-      "        predicted position is 4 with confidence 91.0665%:\n",
+      "        estimated position is 4 with confidence 99.9900%:\n",
       "time 1: pos 8, sensed 8, at position 8\n",
-      "        predicted position is 8 with confidence 99.9902%:\n",
+      "        estimated position is 8 with confidence 100.0000%:\n",
       "time 2: pos 2, sensed 2, at position 2\n",
-      "        predicted position is 2 with confidence 100.0000%:\n",
+      "        estimated position is 2 with confidence 100.0000%:\n",
       "time 3: pos 6, sensed 6, at position 6\n",
-      "        predicted position is 6 with confidence 100.0000%:\n",
+      "        estimated position is 6 with confidence 100.0000%:\n",
       "\n",
       "final position is 6\n",
-      "predicted position is 6 with confidence 100.0000%:\n"
+      "Estimated position is 6 with confidence 100.0000%:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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XAe9u/tJyP/DSnvO01pznfz7wy31naauq7kxyG3AX49MIdwN/0W+qdXlfkhOB7wKvrKpv\n9B1ovbzcVJIkdcZTIZIkqTMWC0mS1BmLhSRJ6ozFQpIkdcZiIUmSOmOxkCRJnbFYSJKkzlgsJElS\nZ/4PLUUv0TsVRkoAAAAASUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb212ae80>"
+       "<matplotlib.figure.Figure at 0x1db5768b400>"
       ]
      },
      "metadata": {},
@@ -5703,23 +5692,23 @@
      "output_type": "stream",
      "text": [
       "time 0: pos 4, sensed 4, at position 4\n",
-      "        predicted position is 0 with confidence 84.1121%:\n",
+      "        estimated position is 4 with confidence 96.0390%:\n",
       "time 1: pos 8, sensed 9, at position 8\n",
-      "        predicted position is 4 with confidence 59.4728%:\n",
+      "        estimated position is 9 with confidence 52.1180%:\n",
       "time 2: pos 3, sensed 3, at position 3\n",
-      "        predicted position is 3 with confidence 53.5807%:\n",
+      "        estimated position is 3 with confidence 88.3993%:\n",
       "time 3: pos 7, sensed 8, at position 7\n",
-      "        predicted position is 8 with confidence 37.5836%:\n",
+      "        estimated position is 8 with confidence 49.3174%:\n",
       "\n",
       "final position is 7\n",
-      "predicted position is 8 with confidence 37.5836%:\n"
+      "Estimated position is 8 with confidence 49.3174%:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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48ZTz9NZd538u8EvTztJXVd2W5GbgdsaXEe4A/my6qVblfUlOBr4NvKKqvjbtQKvl7aaS\nJKkZL4VIkqRmLBaSJKkZi4UkSWrGYiFJkpqxWEiSpGYsFpIkqRmLhSRJasZiIUmSmvlfv0E/M6UR\nPXEAAAAASUVORK5CYII=\n",
+      "image/png": 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SMxYLSZLUjMVCkiQ1Y7GQJEnN/C/3wjlXlj2KGgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb21244e0>"
+       "<matplotlib.figure.Figure at 0x1db58b4f9b0>"
       ]
      },
      "metadata": {},
@@ -5750,9 +5739,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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qxsZCkiQ1Y2MhSZKasbGQJEnNDNVYJNmS5NYke5NcMs+Yf5PkliS7kryzbZqS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\nAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1edb0bae898>"
+       "<matplotlib.figure.Figure at 0x1db58b1bac8>"
       ]
      },
      "metadata": {},
@@ -5923,7 +5912,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {