interactive plots now work correctly

01-g-h-filter.ipynb

@@ -17,9 +17,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline"
@@ -120,13 +118,11 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 800x200 with 1 Axes>"
       ]
@@ -170,13 +166,11 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x200 with 1 Axes>"
       ]
@@ -201,13 +195,11 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 800x200 with 1 Axes>"
       ]
@@ -236,15 +228,13 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average of measurements is 164.9683\n"
+      "Average of measurements is 164.9725\n"
      ]
     }
    ],
@@ -267,15 +257,13 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average of measurements is 164.9450\n"
+      "Average of measurements is 164.9719\n"
      ]
     }
    ],
@@ -300,13 +288,11 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -334,13 +320,11 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 800x250 with 1 Axes>"
       ]
@@ -363,13 +347,11 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x250 with 1 Axes>"
       ]
@@ -400,7 +382,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 800x250 with 1 Axes>"
       ]
@@ -425,13 +407,11 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 800x250 with 1 Axes>"
       ]
@@ -460,13 +440,11 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxYAAADvCAYAAABvy0LrAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAA9hAAAPYQGoP6dpAABaKElEQVR4nO3de3hU1b3/8ffMJOEariEQIHILyNUQQOROohZFDwqllVMtBa94LIjy04rCqdZa8YaXVsVqLcV6gae2yeHQaEMPhASCBjAQAlEgBomQiCEkJECS2bPX748hM4wkITuZyVz29/U887izM1mzlh8mzJe11t4WpZRCCCGEEEIIIVrA6u8OCCGEEEIIIYKfFBZCCCGEEEKIFpPCQgghhBBCCNFiUlgIIYQQQgghWkwKCyGEEEIIIUSLSWEhhBBCCCGEaDEpLIQQQgghhBAtFubvDgQrXdc5ceIEkZGRWCwWf3dHCCGEEEIIr1NKUVlZSe/evbFaG5+TkMKimU6cOEFsbKy/uyGEEEIIIYTPFRUV0bdv30afI4VFM0VGRgLO/8mdOnXyc2+EEEIIIYTwvjNnzhAbG+v67NsYKSyaqW75U6dOnfxSWOi6TnFxMTExMZedlhKhRbI3N8nfvCR7c5P8zStQsm/K0n/5kxmkdF2noKAAXdf93RXRyiR7c5P8zUuyNzfJ37x0XafgyJGgyN6ilFL+7kQwOnPmDJ07d6aiokKWQgkhhBBCCO+qrIQVK+B//xfsdggPh1mz4He/gyYsS/IWI595/TpjkZGRwaxZs+jduzcWi4WUlBSP7y9cuBCLxeLxmDBhgsdzCgoKmDNnDj169KBTp07cdtttfPfdd5d97TfffJMBAwbQtm1bxo4dS2ZmpjeH5nO6rvPNN98ERfUqvEuyNzfJ37wke3OT/E2mshImToQ33oCjR+H4ced/33jDeb6y0t89rJdfC4uzZ88SHx/P66+/3uBzbrzxRoqLi12P1NRUj5+fMWMGFouFLVu2sGPHDmpra5k1a1ajb7wNGzbw0EMPsWLFCnJycpg6dSozZ87k2LFjXh2fL+m6zvHjx+UXjAlJ9uYm+ZuXZG9ukr/JrFgB+fnww7x13Xl+5Ur/9OsyAmYplMViITk5mdmzZ7vOLVy4kPLy8ktmMuqkpaUxc+ZMTp8+7ZqaOX36NN26dWPz5s1cf/319f7cNddcw5gxY1izZo3r3LBhw5g9ezarVq2q92dqamqoqalxfV23Q76srIyuXbvicDgAsNlsHseapmGxWFzHVqsVq9Xa4LHdbsdms7mOw8LCsFgsrmMATdM8jsPDw1FKuY51XcfhcLiOdV0nLCyswWOHw4FSynVc3zhkTDImGZOMScYkY5IxyZhkTAbGVFqK44MPsCiFdfx4tPh4rB06NG1MAwdiOXqUBvXvj15Q0CpjOnv2bHAshWqK9PR0oqOjGTJkCPfeey8nT550fa+mpgaLxUKbNm1c59q2bYvVamX79u31tldbW8uePXuYMWOGx/kZM2aQlZXVYD9WrVpF586dXY+6e1jk5eUBkJ+fT35+PgC5ubkcPnwYgJycHAoLCwHIzs6mqKgIgKysLIqLiwHnkrDS0lIAtmzZQnl5OeAsnCovTHWlpqZSXV2NpmmkpqZSU1PDl19+6ZrBqaysJC0tDYDy8nK2bNkCQGlpKRkZGQAUFxe7xlhUVER2djYAhYWF5OTkAHD48GFyc3P9MiZN06iurpYxXWZMDoeDzz//nH379oXMmEIxJ1+OKS8vD4fDEVJjCsWcvD2mbdu2ceTIEY4fPx4yYwrFnHw1JofDQXp6Ot98803IjCkUc3KN6euvYfJkbMuWYf1//w+mTsXatSuOsWNhyRKOLFnCmV276h/T+fNQW0uj7HbKT59utTE1mQoQgEpOTvY4t379erVp0ya1f/9+tXHjRhUfH69GjBihqqurlVJKnTx5UnXq1EktXbpUnT17VlVVValf/vKXClD33Xdfva9z/PhxBagdO3Z4nP/d736nhgwZ0mD/qqurVUVFhetRVFSkAFVWVqaUUkrTNKVp2iXHdrvd49jhcDR6XFtb63Gs67rHsa7rqra2VtXW1qrPP/9cnTt3TimlXOeVUsrhcHgc2+32Ro81TfM4rm8crTGmi49lTA2PyW63q88//9z1PgiFMYViTr4a0/nz59Xnn3+u7HZ7yIwpFHPyxZjOnz+vsrOzVU1NTciMKRRz8tWY7Ha7+uyzz1RNTU3IjCkUc3L1fe9epaDRhw5KPfBA/WPq37/xn+/fv9XGVFFRoQBVUVGhLiegl0L9UHFxMf369WP9+vX8+Mc/BpxV3n/9139RWFiI1WrlZz/7GQcPHuSaa67hzTffvKSNEydO0KdPH7Kyspg4caLr/O9+9zv++te/8uWXXzapv3JVKCGEEEIIcQmlYN8+SEqCCzMtDQoPr3924sEHnRu169tTY7XC4sXw2mte6e7lBM1VoYyKiYmhX79+rikacC5hKigo4OTJk5SWlvLXv/6V48ePM2DAgHrbiIqKwmazUVJS4nH+5MmT9OzZ06f99yaHw8GXX37pWgsnzEOyNzfJ37wke3OT/AOYUs4N1WvWwG23Qc+ekJBw+aICICKi/vO/+x0MG+YsIi5mtTrPP/NMi7vtC0F15+1Tp05RVFRETEzMJd+LiooCnOvwTp48yS233FJvGxEREYwdO5bNmzczZ84c1/nNmzdz6623+qbjPnL+/Hl/d0H4iWRvbpK/eUn25ib5Bwil4NAhSE+HrVud/23CrQ4uYbPBH/9Y//ciI2HnTli5ErVxI/Zz5whv3x7LLbc4i4pWvI+FEX5dClVVVcWRI0cASEhI4OWXXyYpKYlu3brRrVs3nnrqKebOnUtMTAxHjx7liSee4NixY+Tn5xN54X/o2rVrGTZsGD169GDnzp0sXbqUhQsXsnr1atfrXHfddcyZM4fFixcDzsvNzp8/n7feeouJEyfy9ttv884773DgwAH69evXpL7LUighhBBCCBNQCgoK3EXE1q1wYZN5s/XtC2lpztmHpvbBYmnZazaTkc+8fp2x2L17N0lJSa6vly1bBsCCBQtYs2YN+/fv57333qO8vJyYmBiSkpLYsGGDq6gA+Oqrr3j88ccpKyujf//+rFixgocfftjjdQoKClxXFgCYN28ep06d4umnn6a4uJiRI0eSmpra5KIiEDgcDvLz8xk2bBg2m83f3RGtSLI3N8nfvCR7c5P8W5FSUFjoWUgcP268ndhYqK6G77/3PH/NNbBxI0RHN6mZYMrer4VFYmIijU2Y/Otf/7psG8899xzPPfdco885Ws91gB944AEeeOCBy7YvhBBCCCFC3NGjnkubmnPT5D59nBu2ExOd/x0wAGbMgH//2/2cn/wE3nsP2rXzTr8DTMBcFSrYyFIoIYQQQoggdeyYZyHR2M3oGhIT4y4iEhMhLu7S5UqHDsEdd8CJE84rOT322KUbsgNc0CyFEs3ncDjIzc3lqquuCvhpMeFdkr25Sf7mJdmbm+TfQt9+61lIfP218TZ69vQsJIYMufy+hyFD4MKN8JormLKXwiKItQvRaTRxeZK9uUn+5iXZm5vkb8CJE84Coq6YuHCxIEN69PAsJIYO9dsG6mDJXpZCNZMshRJCCCGECBAlJZ6FxKFDxtvo3t1ZQNQVE8OH+62QCCSyFMoENE0jJyeHhIQEwsIkRjOR7M1N8jcvyd7cJP8fOHkStm1zL23KzzfeRrduMH26u5AYMSIg9z8EU/aB3TvRIIvFQteuXbFIJW06kr25Sf7mJdmbm+nzLy31LCQOHDDeRpcuMG2as4hISoJRowKykPihYMpelkI1kyyFEkIIIYTwkbIyz0Ji/37jbXTq5C4kEhMhPt55t2thiCyFMgFN08jOzmb8+PEBPy0mvEuyNzfJ37wke3ML+fxPn4aMDPceidxc543qjIiMhKlT3UubEhJCopAIpuwDu3eiQVarlT59+mANgik84V2SvblJ/uYl2ZtbyOVfUQGZmc4iYutW2LvXeCHRoYNnITFmDAT4B+/mCKbsZSlUM8lSKCGEEEKIJjpzBrZvdy9t+uIL0HVjbbRvD1OmuAuJsWMhPNwXvRUXkaVQJqBpGllZWUyaNCngp8WEd0n25ib5m5dkb25Bl39lJezY4S4k9uwBh8NYG23bwuTJ7j0SV18NERG+6G1AC6bsA7t3okFWq5VBgwYFxbSY8C7J3twkf/OS7M0t4PM/e9ZZSNTtkdi1y3gh0aYNTJrkLiTGj3eeM7mAz/4ishSqmWQplBBCCCFM69w5yMpyFxLZ2aBpxtqIiICJE91Lm665xjlLIQKKLIUyAU3TyMjIYNq0aQE/LSa8S7I3N8nfvCR7c/N7/ufPw2efuZc2ffYZ2O3G2ggPhwkT3IXEhAnQrp0vehtS/J69AYHdO9Egq9XKyJEjg2JaTHiXZG9ukr95Sfbm1ur5V1fD5597FhI1NcbaCAtzLmequyHdxInODdjCkGB678tSqGaSpVBCCCGECBk1Nc7lTHWFxM6dzuLCCJvNucG6bo/E5MnOS8KKoCZLoUzAbrezZcsWrr32WsLlUmumItmbm+RvXpK9uXk9/9pa5wbruj0SWVnO5U5G2GzOS77WFRJTpkDHji3vm/AQTO99mbFoJn/PWOi6Tnl5OV26dAmKqTHhPZK9uUn+5iXZm1uL87fbYfdudyGxY4dzA7YRVqvzJnR1eySmTAFZteFz/n7vG/nMK4VFM/m7sBBCCCGEaJCmOW9CV7e0aft2qKoy1obFAgkJnoVEly4+6KwIZEY+88o/eQQpu93OP//5T+xGr8gggp5kb26Sv3lJ9uZ22fwdDueMxIsvws03Q7duzsu3Ll8On37atKLCYoHRo+Ghh+B//gdOnXLe2G71aviP/5Ciwk+C6b0vMxbN5O8ZC6UUlZWVREZGYrFYWv31hf9I9uYm+ZuXZG9ul+TvcMCLine truncated
       "text/plain": [
        "<Figure size 800x250 with 1 Axes>"
       ]
@@ -489,13 +467,11 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x250 with 1 Axes>"
       ]
@@ -541,7 +517,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x250 with 1 Axes>"
       ]
@@ -574,9 +550,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -635,9 +609,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -662,7 +634,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -694,13 +666,11 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -739,13 +709,11 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -827,13 +795,11 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 400x400 with 1 Axes>"
       ]
@@ -947,9 +913,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from kf_book.gh_internal import plot_g_h_results\n",
@@ -972,9 +936,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -987,7 +949,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1065,9 +1027,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# your code here"
@@ -1083,13 +1043,11 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1120,13 +1078,11 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1156,9 +1112,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# your code here"
@@ -1174,13 +1128,11 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1219,9 +1171,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# your code here"
@@ -1237,13 +1187,11 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1284,9 +1232,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# your code here"
@@ -1302,13 +1248,11 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1360,9 +1304,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# your code here"
@@ -1378,13 +1320,11 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x400 with 1 Axes>"
       ]
@@ -1418,13 +1358,11 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1462,13 +1400,11 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1509,13 +1445,11 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1555,15 +1489,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "scrolled": false
-   },
+   "execution_count": 53,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "696326f270d74e9b96e1e2ad77c7250d",
+       "model_id": "5cd5b4a0e6864c52b247e6b33f19024a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1594,6 +1526,7 @@
     "    plt.scatter(range(len(zs1)), zs1, edgecolor='k', \n",
     "                facecolors='none', marker='o', lw=1)\n",
     "    plt.plot(data, color='b')\n",
+    "    plt.show()\n",
     "\n",
     "interact(interactive_gh,           \n",
     "         x=FloatSlider(value=0, min=-200, max=200), \n",
@@ -1614,13 +1547,11 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1650,13 +1581,11 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1715,13 +1644,11 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1772,7 +1699,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1797,13 +1724,11 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1830,13 +1755,11 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1863,9 +1786,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def gen_train_data_with_acc(pos, vel, count):\n",
@@ -1880,13 +1801,11 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1911,13 +1830,11 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x400 with 1 Axes>"
       ]
@@ -1966,9 +1883,7 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from filterpy.gh import GHFilter\n",
@@ -1987,9 +1902,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2016,9 +1929,7 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2042,9 +1953,7 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2068,9 +1977,7 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2152,7 +2059,7 @@
   "anaconda-cloud": {},
   "celltoolbar": "Raw Cell Format",
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -2166,7 +2073,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.12"
   },
   "nbdime-conflicts": {
    "local_diff": [
@@ -2761,5 +2668,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

02-Discrete-Bayes.ipynb

@@ -148,7 +148,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -270,7 +270,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -397,7 +397,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -535,7 +535,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -581,7 +581,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "69e1cf784fd743ddaeae41d5fa161216",
+       "model_id": "58750089b43e46f89e82c8deb8ec6b50",
        "version_major": 2,
        "version_minor": 0
       },
@@ -606,6 +606,7 @@
     "\n",
     "def simulate(time_step):\n",
     "    book_plots.bar_plot(perfect_beliefs[time_step], ylim=(0, .4))\n",
+    "    plt.show()\n",
     "    \n",
     "interact(simulate, time_step=IntSlider(value=0, max=len(perfect_beliefs)-1));"
    ]
@@ -666,7 +667,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -715,7 +716,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -744,20 +745,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Final Belief: [0.104 0.103 0.101 0.099 0.097 0.096 0.097 0.099 0.101 0.103]\n"
+      "Final Belief: [0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b7f90f29b9394f82b4c64982c8eab901",
+       "model_id": "90a9c588242a4ef1a0d8d576479e9f79",
        "version_major": 2,
        "version_minor": 0
       },
@@ -783,6 +784,7 @@
     "def show_prior(step):\n",
     "    book_plots.bar_plot(predict_beliefs[step-1])\n",
     "    plt.title(f'Step {step}')\n",
+    "    plt.show()\n",
     "\n",
     "interact(show_prior, step=IntSlider(value=1, max=len(predict_beliefs)));"
    ]
@@ -883,7 +885,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -919,7 +921,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -974,7 +976,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -1007,7 +1009,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -1036,7 +1038,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -1065,7 +1067,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -1095,7 +1097,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -1136,7 +1138,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 400x400 with 1 Axes>"
       ]
@@ -1188,7 +1190,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 42,
    "metadata": {
     "scrolled": true
    },
@@ -1211,13 +1213,15 @@
     "    plt.title('Posterior')\n",
     "    book_plots.bar_plot(hallway, c='k')\n",
     "    book_plots.bar_plot(posteriors[i], ylim=(0, 1.0))\n",
-    "    plt.axvline(i % len(hallway), lw=5)    \n",
+    "    plt.axvline(i % len(hallway), lw=5)\n",
+    "    plt.show()\n",
     "    \n",
     "def plot_prior(hallway, priors, i):\n",
     "    plt.title('Prior')\n",
     "    book_plots.bar_plot(hallway, c='k')\n",
     "    book_plots.bar_plot(priors[i], ylim=(0, 1.0), c='#ff8015')\n",
-    "    plt.axvline(i % len(hallway), lw=5)    \n",
+    "    plt.axvline(i % len(hallway), lw=5)\n",
+    "    plt.show()\n",
     "\n",
     "def animate_discrete_bayes(hallway, priors, posteriors):\n",
     "    def animate(step):\n",
@@ -1240,13 +1244,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5e52dc4ac04b4244ad4357a4fd837902",
+       "model_id": "8dfe58d0c1d8407e9f59642e705785c3",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1293,13 +1297,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "562f60dcb79f4651953d34fd40c1cab7",
+       "model_id": "f1b9fe2517d1461b83529c81a64a4c02",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1335,7 +1339,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1364,7 +1368,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
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truncated
       "text/plain": [
        "<Figure size 800x550 with 10 Axes>"
       ]
@@ -1559,7 +1563,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1608,7 +1612,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1639,7 +1643,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x550 with 4 Axes>"
       ]
@@ -1758,7 +1762,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -1772,7 +1776,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.12"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

03-Gaussians.ipynb

@@ -154,7 +154,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x200 with 1 Axes>"
       ]
@@ -325,7 +325,7 @@
     {
      "data": {
       "text/plain": [
-       "1.499952"
+       "1.49911"
       ]
      },
      "execution_count": 7,
@@ -537,7 +537,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -569,7 +569,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -581,8 +581,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "mean = 1.811\n",
-      "std  = 0.130\n"
+      "mean = 1.820\n",
+      "std  = 0.146\n"
      ]
     }
    ],
@@ -611,7 +611,7 @@
     {
      "data": {
       "text/plain": [
-       "69.0"
+       "68.0"
       ]
      },
      "execution_count": 14,
@@ -719,7 +719,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -806,7 +806,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -844,7 +844,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -882,7 +882,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -936,7 +936,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -983,7 +983,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1162,7 +1162,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1212,7 +1212,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1237,13 +1237,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a07afca115cb406abe449c6fdd78d44f",
+       "model_id": "05debbefed5e4c919bdb8d0d1ff0e72e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1265,6 +1265,7 @@
     "    ys = gaussian(xs, mu, variance)\n",
     "    plt.plot(xs, ys)\n",
     "    plt.ylim(0, 0.04)\n",
+    "    plt.show()\n",
     "\n",
     "interact(plt_g, mu=FloatSlider(value=5, min=3, max=7),\n",
     "         variance=FloatSlider(value = .03, min=.01, max=1.));"
@@ -1299,7 +1300,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1335,7 +1336,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1389,7 +1390,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1434,7 +1435,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1643,9 +1644,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[ 3.026  7.51  -2.588  6.081 -3.413 -1.11   6.484\n",
-      "  5.935  2.313  1.912  1.895  7.964  4.876 -0.841\n",
-      " -0.174]\n"
+      "[ 5.104 -0.949  1.323 -0.166  5.918  2.401  4.119\n",
+      " -2.755  4.728  5.28   0.605  0.072 -1.683 -2.43\n",
+      "  0.846]\n"
      ]
     }
    ],
@@ -1733,7 +1734,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1786,7 +1787,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1835,7 +1836,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1879,7 +1880,7 @@
     {
      "data": {
       "text/plain": [
-       "DescribeResult(nobs=5000, minmax=(1.7707248080804092, 17.824961707265643), mean=10.004201301507253, variance=2.721973140216924, skewness=-0.03534037712630867, kurtosis=1.583968849611276)"
+       "DescribeResult(nobs=5000, minmax=(-0.6480611393883731, 19.206083601495237), mean=9.98754109921001, variance=2.7270546769082125, skewness=0.02144542351190797, kurtosis=1.8212868971014897)"
       ]
      },
      "execution_count": 46,
@@ -1910,9 +1911,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "DescribeResult(nobs=10, minmax=(-1.1170056026895896, 1.0389413316321683), mean=-0.14317693801053674, variance=0.63137454114842, skewness=0.23966670696111078, kurtosis=-1.3702119526058378)\n",
+      "DescribeResult(nobs=10, minmax=(-1.7903777051133176, 3.1447477851173296), mean=0.18101268693045508, variance=2.819092515876096, skewness=0.4602090958850016, kurtosis=-1.0764261587819526)\n",
       "\n",
-      "DescribeResult(nobs=300000, minmax=(-4.262303362805642, 4.603650808299195), mean=-0.00040808441709135014, variance=0.998953112076118, skewness=-0.0010979017079029859, kurtosis=-0.00030025117171517124)\n"
+      "DescribeResult(nobs=300000, minmax=(-4.760889923616689, 4.585117857857077), mean=-2.5122502492841646e-07, variance=0.999216059680056, skewness=-0.0001267418313482679, kurtosis=0.0026735205760863856)\n"
      ]
     }
    ],
@@ -2131,7 +2132,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -2145,7 +2146,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.12"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

04-One-Dimensional-Kalman-Filters.ipynb

@@ -97,13 +97,11 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -136,12 +134,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean of readings is 10.021\n"
+      "Mean of readings is 10.044\n"
      ]
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -193,13 +191,11 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -537,7 +533,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -576,12 +572,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -605,6 +601,7 @@
     "    ys = [stats.gaussian(x, product.mean, product.var) for x in xs]\n",
     "    plt.plot(xs, ys, label='product', ls='--')\n",
     "    plt.legend();\n",
+    "    plt.show()\n",
     "    \n",
     "z1 = gaussian(10.2, 1)\n",
     "z2 = gaussian(9.7, 1)\n",
@@ -634,7 +631,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -644,7 +641,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -681,14 +678,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "faea7e888fad41cbaff75f4babf87e46",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<Figure size 900x400 with 1 Axes>"
+       "interactive(children=(FloatSlider(value=7.5, description='m1', max=10.0, min=5.0, step=0.5), FloatSlider(value…"
       ]
      },
      "metadata": {},
@@ -809,16 +810,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "scrolled": true
-   },
+   "execution_count": 42,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "328703e9ffe94521af8947d93adac80f",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<Figure size 900x400 with 1 Axes>"
+       "interactive(children=(IntSlider(value=1, description='step', max=300, min=1), Output()), _dom_classes=('widget…"
       ]
      },
      "metadata": {},
@@ -860,10 +863,12 @@
     "    else:\n",
     "        book_plots.plot_measurements(zs[:i])\n",
     "        book_plots.plot_filter(xs[:i])\n",
-    "\n",
+    "    \n",
     "    plt.xlim(-1, 10)\n",
     "    plt.ylim(0, 20)\n",
     "    plt.legend(loc=2);\n",
+    "    plt.show()\n",
+    "    \n",
     "interact(plot_filter, step=IntSlider(value=1, min=1, max=len(predictions)*3));"
    ]
   },
@@ -983,7 +988,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1134,7 +1139,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1100x300 with 1 Axes>"
       ]
@@ -1278,13 +1283,11 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 800x200 with 1 Axes>"
       ]
@@ -1311,13 +1314,11 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1356,7 +1357,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1429,7 +1430,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1446,7 +1447,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1546,7 +1547,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1602,7 +1603,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1657,7 +1658,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1709,7 +1710,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1755,7 +1756,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAFfCAYAAADd+nNsAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOyddVgU2/vA311i6ZaSshVBsbswsbsQwULBRLG9YmFeO67d3R2Y126wEwsDRaRz2X1/f/Db852zM7ssSHj1fJ7nfZ6dOTNnzsyZ3X3POW+IEBGBwWAwGAwGg8Fg/LaIi7oBDAaDwWAwGAwGo2BhSj+DwWAwGAwGg/Gbw5R+BoPBYDAYDAbjN4cp/QwGg8FgMBgMxm8OU/oZDAaDwWAwGIzfHKb0MxgMBoPBYDAYvzlM6WcwGAwGg8FgMH5ztIu6AYWBXC6Hz58/g7GxMYhEoqJuDoPBYDAYDAaD8dMgIiQlJYG9vT2Ixern8v8Ipf/z58/g6OhY1M1gMBgMBoPBYDDynaioKHBwcFB7zB+h9BsbGwNA9gMxMTEp9OtLpVIICwuDFi1agI6OTqFfn1F0sL7/c2F9/+fC+v7PhPX7n0tR9n1iYiI4OjoSXVcdf4TSrzDpMTExKTKl38DAAExMTNgPwR8G6/s/F9b3fy6s7/9MWL//ufwKfa+J+Tpz5GUwGAwGg8FgMH5zmNLPYDAYDAaDwWD85jCln8FgMBgMBoPB+M1hSj+DwWAwGAwGg/Gb80c48mpCeno6xMTEFEjdcrkcHB0d4fPnzznGUGX8Xmhrs68Yg8FgMBiMoodpJJCt8H/79g2KFy8OWlpa+V6/XC4HU1NTMDExYUr/H8a3b99AX1+/qJvBYDAYDMYfj1wuh4iICPjx4wfY2NiAm5vbH5W0lWmgABATE1NgCj/jz8bS0hLMzc2LuhkMBoPBYPyxICKsWrUKypQpA9WqVYPmzZtDpUqVwM3NDbZv317UzSs0mNL//zCFn1EQiEQitrrDYDAYDEYRgYgQEBAAQ4cOhTdv3lBlT58+BR8fH5g6dWoRta5wYdoIg1HA/ElLhwwGg8Fg/Ers378f1qxZQ7abNWsGEyZMgHr16pF9M2fOhH///bcomleoMKWfwWAwGAwGg/FbsnTpUvJ5w4YNcPbsWZgzZw5cvXoV5syZQ8qWLVtWFM0rVJjSz2AwGAwGg8H47UhOToZr164BAEC5cuWgX79+VPmYMWPAysoKAADOnDlT6O0rbFj0nnzi27dvcPbsWUhMTAQHBwdo0aIFSCSSom4Wg8FgMBgMxh9Jamoq+ezi4sIzt9XR0QEHBwf4/v07pKamAiL+1ia5bKb/J0lKSoIBAwaAo6Mj9OnTBwIDA6F9+/bg6OgIixcvBkQssGv7+fmBSCSCIUOG8MoCAwNBJBKBn59fgV3/T0AkEsHhw4eLuhkMBoPBYDByiYWFBRgbGwMAwJUrVyA2NpYqf/v2LTx8+BAAhAcFvxtM6f8JUlJSoFmzZrBx40bIzMykymJiYmD06NEwduzYAm2Do6Mj7N69G9LS0si+9PR02LVrFzg5ORXotX8W5WfGYDAYDAaDkV9oa2uDj48PAGTP+nfq1AkePXoEAAC3b9+Gzp07g1wuBwD4IyZJmdL/EyxYsABu374NAABGRkYwevRoWL9+PXTv3p0cs3DhQrhx40aBtaFq1arg5OQEBw8eJPsOHjwIjo6OUKVKFbIPEWH+/PlQsmRJ0NfXh8qVK8P+/ftJuUwmgwEDBkCJEiVAX18fypUrRzm/AABcunQJatasCYaGhmBmZgb16tWD9+/fA0D2l6Vjx47U8aNGjYLGjRuT7caNG8OwYcNg9OjRYGVlBc2bNweA7JBZrVu3BiMjI7CxsQEfHx/4/v07dd7w4cNh1KhRYG5uDjY2NrB27VpISUmBfv36gbGxMZQqVQpOnTpFXV+TekeMGAHjxo0DCwsLsLW1hWnTppFyFxcXAADo1KkTiEQisv3gwQNo0qQJGBsbg4mJCVSrVg3u3r2bQ08xGAwGg8EobIKDg8HMzAwAsmf7K1WqBLq6ulCrVi2IiIgAAAB7e3sIDAwsukYWEkzpzyNZWVkkBJSWlhZcuXIFFi5cCAMGDIA9e/bA33//TY5dtWpVgbalX79+sGnTJrK9ceNG6N+/P3XMlClTYNOmTfDPP//AkydPICgoCPr06UNCVMnlcnBwcIC9e/fC06dPYerUqTBp0iTYu3cvud+OHTtCo0aN4OHDh3Djxg3w9/fP9VLYli1bQFtbG65duwZr1qyBL1++QKNGjcDDwwPu3r0Lp0+fhq9fv1IDJ8V5VlZWcPv2bRg+fDgEBARAt27doG7dunD//n1o2bIl+Pj4EPu93NRraGgIt27dgvnz58OMGTPg7NmzAABw584dAADYtGkTfPnyhWx7e3uDg4MD3LlzB+7duwcTJkwAHR2dXD0HBoPBYDAYBU+JEiXg1KlTUKxYMbJPKpWSz87OznD27Fni0Ptbg38ACQkJCACYkJAgWP7hw4dc1/ns2TMEAAQAbN26Na88LS0NDQwMEADQ2dkZ4+LiUCaT5fo66vD19cUOHTpgTEwMSiQSfPv2Lb579w719PQwJiYGO3TogL6+vpicnIx6enp4/fp16vwBAwZgr169VNYfGBiIXbp0QUTE2NhYBAC8dOmS2rZwGTlyJDZq1IhsN2rUCD08PKhj/vrrL2zRogW1LyoqCgEAX7x4Qc6rX78+Kc/KykJDQ0P08fEh+758+YIAgDdu3MhzvYiINWrUwPHjx5NtAMBDhw5RxxgbG+PmzZsFn4MyMpkM7927h5mZmRodz/h9yMzMxMOHD7O+/wNhff9nwvr91yY+Ph6XL1+OjRs3Rnd3d2zWrBmuX78eU1JSfrruouz7nHRcLix6Tx7JysoinxXLRlwkEgno6+tDamoqNaIsCKysrKBNmzawZcsWQERo06YNNWJ9+vQppKenE3MaBZmZmZQJ0OrVq2H9+vXw/v17SEtLg8zMTPDw8ACAbGcYPz8/aNmyJTRv3hyaNWsG3bt3Bzs7u1y1tXr16tT2vXv34OLFi2BkZMQ7NjIyEsqWLQsAAJUqVSL7tbS0wNLSEtzd3ck+GxsbAMiOopTXegEA7OzsSB2qGD16NAwcOBC2bdsGzZo1g27dukGpUqXUnsNgMBgMBqPoMDU1hWHDhsGwYcOKuilFBlP684iLiwvo6elBeno6HD9+HH78+AEWFhak/PTp08RLvEKFCgXenv79+5MXeeXKlVSZwknlxIkTULx4capMEVZ07969EBQUBAsXLoQ6deqAsbExLFiwAG7dukWO3bRpE4wYMQJOnz4Ne/bsgSlTpsDZs2ehdu3aIBaLeZGKhAY7hoaGvLa1a9cO5s2bxzuWO6BQNp8RiUTUPoWZkeJef6ZeRR2qmDZtGvTu3RtOnDgBp06dgpCQENi9ezd06tRJ7XkMBoPBYDAYRQVT+vOIkZER9OrVCzZt2gSJiYnQrFkzmDVrFri6ukJYWBhMnDiRHDtw4MACb0+rVq1INJyWLVtSZa6uriCRSODDhw/QqFEjwfOvXLkCdevWpRxZIiMjecdVqVIFqlSpAhMnToQ6derAzp07oXbt2lCsWDF4/PgxdWxERESOtu5Vq1aFAwcOgIuLC2hr59/rmF/16ujogEwm4+0vW7YslC1bFoKCgsh7wJR+BoPBYDAYvyrMkfcnmDp1KlhaWgIAQHh4OLRp0wZKlCgBgwcPhh8/fgAAQMOGDaFz584F3hYtLS149uwZPHv2DLS0tKgyY2NjCA4OhqCgINiyZQtERkZCeHg4rFy5ErZs2QIAAKVLl4a7d+/CmTNn4OXLl/DXX38Rx1WA7Fi2EydOhBs3bsD79+8hLCwMXr58SVYxPD094e7du7B161Z49eoVhISE8AYBQgwdOhR+/PgBvXr1gtu3b8ObN28gLCwM+vfvL6hsa0p+1evi4gLnz5+H6OhoiIuLg7S0NBg2bBhcunQJ3r9/D9euXYM7d+4UymoOg8FgMBgMRl5hSv9P4OLiAhcuXICSJUsKlrdu3RqOHj2arzPY6jAxMQETExPBspkzZ8LUqVNhzpw5UKFCBWjZsiUcO3YMSpQoAQAAQ4YMgc6dO0OPHj2gVq1aEBsbS836GxgYwPPnz6FLly5QtmxZ8Pf3h2HDhsHgwYMBIHt14a+//oJx48ZBjRo1ICkpCfr27Ztjm+3t7eHatWsgk8mgZcuW4ObmBiNHjgRTU1MQi/P+euZXvQsXLoSzZ8+SEKhaWloQGxsLffv2hbJly0L37t3By8sLpk+fnue2MhgMBoPBYBQ0IlQ2xP4NSUxMBFNTU0hISBBUiqOiosDR0THP9WdlZcGxY8fg2LFjkJiYCMWLFwcfHx/itCqXyyExMRFMTEx+SpFl/PeQy+UQEREB7u7uLKznH4ZUKoWTJ09C69atWd//YbC+/zNh/f7nUpR9n5OOy4XZ9OcD2tra0KlTJ2bTzWAwGAwGg8H4JWHTzgwGg8FgMBgMxm8OU/oZDAaDwWAwGIzfHKb0MxgMBoPBYDAYvzlM6WcwGAwGg8FgMH5zmNLPYDAYDAaDwWD85jCln8FgMBgMBoPB+M1hSj+DwWAwGAwGg/Gbw5T+35DGjRvDqFGjyLaLiwssWbKkyNrDYDAYDAaDwShamNL/H8bPzw9EIhFP5s+fDzNnzlR5nkgkgsOHDxdeQxkMBoPBYDAYRQrLyPsfp1WrVrBp0yZqX7FixUBLS6vAry2VSlmqcQaDwWAwGIz/AGym/z+ORCIBW1tbSpo2bUqZ93BxcXEBAIBOnTqBSCQi2wAAx44dg2rVqoGenh6ULFkSpk+fDllZWaRcJBLB6tWroUOHDmBoaAizZs0qwDtjMBgMBoPBYOQXbKZfCUSENKksX+uUy+WQlikD7cwsEItVj7P0dbRAJBLl67WVuXPnDlhbW8OmTZugVatWZEXgzJkz0KdLine truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1807,6 +1808,20 @@
    "execution_count": 32,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cfdbef69c66e4e038955bc834989191f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(IntSlider(value=0, description='start_pos', max=10, min=-10), FloatSlider(value=5.0, con…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "text/plain": [
@@ -1846,14 +1861,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f2dce4f79c934bc6bc59839a3c215481",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<Figure size 900x400 with 1 Axes>"
+       "interactive(children=(IntSlider(value=0, description='start_pos', max=10, min=-10), FloatSlider(value=5.0, con…"
       ]
      },
      "metadata": {},
@@ -1885,6 +1904,7 @@
     "    plt.plot(zs, c='k', marker='o', linestyle='', label='measurement')\n",
     "    plt.plot(ps, c='#004080', alpha=0.7, label='filter')\n",
     "    plt.legend(loc=4);\n",
+    "    plt.show()\n",
     "\n",
     "interact(plot_kalman_filter,\n",
     "         start_pos=(-10, 10), \n",
@@ -1937,13 +1957,11 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2037,9 +2055,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2118,7 +2134,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -2132,7 +2148,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.12"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

06-Multivariate-Kalman-Filters.ipynb

@@ -28,9 +28,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -155,7 +153,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1100x300 with 1 Axes>"
       ]
@@ -467,7 +465,6 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "scrolled": true,
     "tags": [
      "raises-exception"
     ]
@@ -774,9 +771,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -836,7 +831,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -890,9 +885,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1165,8 +1158,6 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[1. 0.]] [[680.587 301.175]\n",
-      " [301.175 502.35 ]] [[5.]]\n",
       "x = [ 1.085 -0.64 ]\n"
      ]
     }
@@ -1328,7 +1319,7 @@
        "likelihood = 2.2250738585072014e-308\n",
        "mahalanobis = 0.0\n",
        "alpha = 1.0\n",
-       "inv = <function inv at 0x00000296F726A948>"
+       "inv = <function inv at 0x7f16b4494050>"
       ]
      },
      "execution_count": 29,
@@ -1425,7 +1416,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1435,7 +1426,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -1473,7 +1464,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x500 with 1 Axes>"
       ]
@@ -1634,7 +1625,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAFfCAYAAAAPqnk0AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAA9hAAAPYQGoP6dpAABFrElEQVR4nO3deXxU9b3/8fdMMkkIJIEQyL4QgiA7AglBNkFcsC51xaCgrWIr2PZ6/fV6bW/VW29tH91bWwpCFZQILYpaRQUrEJYQdkRkD9nIRliykslk5vz+CI6lrJkkc5LJ6/l45PFgvjmT8+Hjl+TtN+d8j8UwDEMAAAAAvMJqdgEAAABAZ0IABwAAALyIAA4AAAB4EQEcAAAA8CICOAAAAOBFBHAAAADAiwjgAAAAgBf5e/uELpdLxcXFCgkJkcVi8fbpAQAAgFZnGIaqq6sVExMjq/Xya9xeD+DFxcWKj4/39mkBAACANldYWKi4uLjLHuP1AB4SEiKpqbjQ0FCvntvhcGj16tW66aabZLPZvHpuX0D/PEfvPEfvPEfvWob+eY7eeY7eec7s3lVVVSk+Pt6ddS/H6wH8q8tOQkNDTQngwcHBCg0NZVJ7gP55jt55jt55jt61DP3zHL3zHL3zXHvp3dVcYs1NmAAAAIAXEcABAAAALyKAAwAAAF5EAAcAAAC8iAAOAAAAeBEBHAAAAPAiAjgAAAA6tIaGBm3cuFFbt27Vzp07ZRiG2SVdFgEcAAAAHVJjY6N++tOfKj4+XpMnT9bPfvYzjRkzRgMHDtTSpUvNLu+SmhXAX3jhBVkslvM+oqKi2qo2AAAA4KKcTqfuv/9+/eQnP1F5efl5nztw4IAeeugh/exnPzOpustr9pMwBw0apE8//dT92s/Pr1ULAgAAAK5k/vz5WrlypaSmp0/eddddCggM0vGiQm3cuFGS9KMf/Ug33XSTRo0aZWapF2j2JSj+/v6Kiopyf/Tq1ast6gIAAAAuyjAM/eEPf3C/fuudf2jSky/rQL8M/eGNd/WTn/zE/bk//vGPZpR4Wc1eAT98+LBiYmIUGBiotLQ0/exnP1NycvIlj7fb7bLb7e7XVVVVkiSHwyGHw+FByZ776nzePq+voH+eo3eeo3eeo3ctQ/88R+88R++uTlFRkQ4ePKiA6GuUfNMj+vE2ixzOI5Is+vuOQv3X00/r17/+tWpra/Xpp596pZ/NOYfFaMZtoh999JHq6up0zTXXqKysTC+99JIOHDigffv2qWfPnhd9zwsvvKAXX3zxgvHMzEwFBwdfdaEAAACAwyV9dviMVn5xSoEx17jHE7sZGh/l0oiehvyt0uOPP64TJ06oW7duevPNN9u8rrq6OmVkZKiyslKhoaGXPbZZAfzf1dbWqm/fvvrhD3+op59++qLHXGwFPD4+XhUVFVcsrrU5HA6tWbNGU6dOlc1m8+q5fQH98xy98xy98xy9axn65zl65zl6d2nFZ87qrW1FWr69SKfrmlabjUaHHLlbtPynT2pknwh37/bu3asxY8ZIkq677jpt2bKlzeurqqpSRETEVQXwZl+C8q+6du2qIUOG6PDhw5c8JjAwUIGBgReM22w20yaWmef2BfTPc/TOc/TOc/SuZeif5+id5+hdE8MwlH30pBZn52nNl2VynVs2jgkLUkDhVm14/edyna3S82e26he/+IWcTqfWrl2r73//++6v8e1vf9srvWzOOVoUwO12u/bv36/x48e35MsAAAAAbjX2Rq3cWaQl2fk6XF7jHr8+padmpidpyoDeOnokTqPffFnVktauXavU1NQLvk7//v01a9YsL1Z+dZoVwJ955hndfvvtSkhIUHl5uV566SVVVVW1y78YAAAAOpajJ2r0Rna+VuwoUo29UZIUHOCne66L08z0RPWLDHEf279/f61atUrf/OY3VVFRccHXGjJkiD744AN17drVa/VfrWYF8KKiIj344IOqqKhQr169NGbMGG3ZskWJiYltVR8AAAB8mNNlaO2Bci3OztOGw18H6eSIrpqZnqi7R8YpNOjil3eMGzdOR48e1ZtvvqmVK1cqPz9f1157rWbOnKk77rij3V7G06wAvmzZsraqAwAAAJ3I6doG/W17od7Ykq+i02clSRaLNGVApGaNTdT1fSNktVqu+HVCQ0P15JNP6vHHH9eqVas0bdq0dhu8v9Kia8ABAACA5vjieKWWZOfpvd3Fsje6JEndg216YHS8HkpLVHy4729TTQAHAABAm2podOmjL0q0JDtfO/JPu8cHxYRq1tgk3TEsRkE2PxMr9C4COAAAANpEWVW9luYUKDOnQBU1Tc+FsflZNG1ItGamJ+m6hO6yWK58mYmvIYADAACg1RiGoW15p7U4O0+ffFGqxnObd0eGBmpGWqKmp8ard0iQyVWaiwAOAACAFqtraNR7u4u1eHOeDpRWu8dTk8I1c2yibh4UJZuf1cQK2w8COAAAADyWf7JWb2Tn62/bC1VV37R3d5DNqm+OaNq7+9royz+WvTMigAMAAKBZXC5D6w+f0JLNeVp36ISMc4+ITwgP1sz0RN03Ml5hwe17K0AzEcABAABwVSrPOvT37YV6c0u+8k7Wuccn9e+lWelJmnhNr6vau7uzI4ADAADgsg6UVmlJdr5W7jyusw6nJCkkyF/3j4rXw2MSlRTR/h733p4RwAEAAHABh9OlNV+WafHmPOUcO+UeHxAVopnpSbprRIyCA4iSnqBrAAAAcDtRbdeyrQVamlOg0qp6SZKf1aJbBkVpZnqiUvuEd8q9u1sTARwAAKCTMwxDuwrPaMnmPH24t0QOZ9NdlRHdApSRmqAH0xIUHdbF5Cp9BwEcAACgk6p3OPWPPcVakp2vvccr3eMjErrrkbFJumVwlAL9O88j4r2FAA4AANDJFJ2u05tbCrR8W4FO1zkkSQH+Vt0xLEYz0xM1NK67uQX6OAI4AABAJ2AYhjYdOanF2Xn65/4ynXtCvGK7d9HD6Ym6f1S8wrsGmFtkJ0EABwAA8GHV9Q69s/O4lmTn6eiJWvf4uJQIzUxP1JRrI+XH3t1eRQAHAADwQUfKa7QkO09v7yhSbUPT3t1dA/x078g4PZyeqJTeISZX2HkRwAEAAHyE02Xon/vLtCQ7XxuPVLjH+/bqqlljk/TNEbEKCeIR8WYjgAMAAHRwp2obtHxb0yPij585K0myWqQbr43UrLFJGtu3J3t3tyMEcAAAgA5qb1GlFmfn6f09xWpodEmSegTbND01QTPSEhTXI9jkCnExBHAAAIAOxN7o1Ed7S7U4O0+7Cs64x4fEhmnW2CR9Y2i0gmzs3d2eEcABAAA6gJLKs8rMKdBbWwtUUdMgSbL5WfSNoU17dw+P785lJh0EARwAAKCdMgxDOcdOaUl2nj7ZVybnuc27o0KDNCMtQdNTE9QrJNDkKtFcBHAAAIB2pq6hUR/sLNaSzfk6WFbtHh+THK5Z6Um6cWCkbH5WEytESxDAAQAA2om8k7V6J8+qH/8yS9X1jZKkLjY/ffO6WM1MT9SAqFCTK0RrIIADAACYyOUytO5QuRZvztf6QyckWSU1KqlnsB5OT9K9I+MU1oW9u30JARwAAMAElXUO/W17od7Ykq+CU3WSJItFujbMpf+8Y5RuGBAlK4+I90kEcAAAAC/6srhKb2zJ08pdx1XvaNq7OzTIXw+MjtcDo2K1b8s6TegXQfj2YQRwAACANuZwuvTJvlIt2ZyvrXmn3OMDokL0yNgk3Tk8Vl0C/ORwOLTPxDrhHQRwAACANlJeXa+3cgq1NCdf5dV2SZK/1aJbBkdp1tgkjUrswd7dnRABHAAAoBUZhqGdBae1eHO+PvqiRA5n097dvUIClZGaoIy0BEWGBplcJcxEAAcAAGgF9Q6n3t9drMXZedpXXOUeH5XYQw+nJ+rWwdEK8GfvbhDAAQAAWqTwVJ3e3JKv5dsLdabOIUkK9LfqruGxejg9UYNjw0yuEO0NARwAAKCZXC5DG49UaEl2nv55oFxG01UmiuvRRQ+PSdT9o+LVo2uAuUWi3SKAAwAAXKWqeofe3lGkN7LzlVtR6x4f3y9Cs9KTdMOA3vJj+0BcAQEcAADgCg6VVWtJdp7e2XlcdQ1OSVK3QH/dOzJOD6cnqm+vbiZXiI6EAA4AAHARjU6XPt1friXZedp89KR7vF/vbpo5NknfHBGrboFEKTQfswYAAOBfnKyxa9m2Qi3dkq/iynpJktUi3TQwSjPHJio9uSd7d6NFCOAAAACS9hSe0eLsPH2wp0QNzqZHxId3DdCDqfHKSEtUbPcuJlcIX0EABwAAnZa90akPPy/R4ux87Sk84x4fFhemWWOTNG1ItIJsfuYVCJ9EAAcAAJ1O8ZmzWpqTr2VbC3WytkGSFOBn1TeGRWtmepKGx3c3t0D4NAI4AADoFAzDUHbuSS3ZnK/VX5bKdW7v7piwIM0Yk6gHRscroluguUWiUyCAAwAAn1Zrb9Q7u45ryeY8HS6vcY+nJ/fUrLGJuvHaSPn78Yh4eA8BHAAA+KSjJ2r0Rna+3t5RpGp7oyQpOMBPd18Xq5npSbomMsTkCtFZEcABAIDPcLoMrT1QrsXZedpwuMI93ieiq2amJ+qekXEKDbKZWCFAAAcAAD7gTF2D/ra9UG9syVfhqbOSJItFmjKgt2amJ2lcSoSsPCIe7QQBHAAAdFhfHK/UG9n5enf3cdkbm/buDuti0/TR8XpoTKLiw4NNrhC4EAEcAAB0KA2NLn28r1RLNudpe/5p9/jA6FA9MjZJtw+LUZcA9u5G+0UABwAAHUJZVb0ycwqUubVAJ6rtkiR/q0XThkRr1thEXZfQg0fEo0MggAMAgHbLMAxtzz+txZvz9PEXpWo8t3l375BAzUhL1IOp8eodGmRylUDzEMABAECLuVwuffjhh3r11Ve1f/9+1dfX6+abb9acOXM0YsSIZn+9sw1Ovbf7uBZn52t/SZV7PDULine truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1789,7 +1780,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -1828,13 +1819,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a828518321f448be916ab551fe70519e",
+       "model_id": "93c7d13ec7be48cd9a81d98f58fdbf3f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1864,6 +1855,7 @@
     "    #plt.title(str(F))\n",
     "    plt.xlabel('position')\n",
     "    plt.ylabel('velocity')\n",
+    "    plt.show()\n",
     "                 \n",
     "interact(plot_FPFT, \n",
     "         F00=IntSlider(value=1, min=0, max=2), \n",
@@ -2033,7 +2025,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2156,13 +2148,11 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2252,7 +2242,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2279,7 +2269,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2379,7 +2369,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2389,7 +2379,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2431,7 +2421,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2459,7 +2449,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2488,7 +2478,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2528,7 +2518,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGMCAYAAAClAC/SAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAA9hAAAPYQGoP6dpAADuiklEQVR4nOzddXQUVxvA4d9q3D3EBUIIkEBwd/cCxVqgirQF2lL7KtAWqXtpaSlWXIprcSdACAQChIQkhLhvdO37Y2FhG9oSCATofc7JYXfuzJ27y2Yz71x5JXq9Xo8gCIIgCIIgCMIdktZ0AwRBEARBEARBeLSIIEIQBEEQBEEQhCoRQYQgCIIgCIIgCFUigghBEARBEARBEKpEBBGCIAiCIAiCIFSJCCIEQRAEQRAEQagSEUQIgiAIgiAIglAlIogQBEEQBEEQBKFKRBAhCIIgCIIgCEKViCBCEARBEARBEIQqEUGEIAiCINyivLycMWPG4O3tja2tLc2bN+fQoUM13SxBEISHiggiBEEQBOEWGo0Gf39/Dh48SH5+PuPGjaNv376UlJTUdNMEQRAeGhK9Xq+v6UYIgiAIwsPM0dGR3bt307Bhw5puiiAIwkNB9EQIgiA8hjZv3oxEIjH+yGQyfH19mThxIoWFhfflnHv27DE5560/R44cqbS/SqVi0qRJeHp6Ym5uTnh4OMuWLbvr/e6XuLg4SktLCQwMfGDnFARBeNjJa7oBgiAIQvU7efIkAKtXr8bT05OysjJWrlzJ999/j0qlYv78+fft3DNmzKBDhw4m28LCwirtN3DgQI4fP86sWbOoXbs2S5YsYdiwYeh0OoYPH17l/e6HkpISRo0axf/+9z+sra3v67kEQRAeJWI4kyAIwmNo4MCBbNu2jaKiIqTSm53OoaGhZGRkkJOTU+3n3LNnDx06dGDlypU88cQT/7jv5s2b6dWrlzEguKFr167ExsaSnJyMTCa74/3uB7VazYABA3BycmL+/PlIJJL7ch5BEIRHkRjOJAiC8Bg6ceIE9evXNwkgAGxtbSkuLq6hVt20du1arK2tGTx4sMn2MWPGcO3aNY4ePVql/W6na9eutG7dmu3bt9O6dWssLS3x8/Nj+fLlACxfvpzIyEgsLS0JDQ1l9+7dxmN1Oh1PPfUUMpmMX3/9VQQQgiAIfyGCCEEQhMdMTk4OycnJlSYBZ2VlcfbsWZo0aVLpGL1ej0ajuaOffzNhwgTkcjm2trZ069aNAwcOVNrn7Nmz1K1bF7ncdFRtgwYNjOVV2e92Tp06RXJyMv/73/+YOHEia9aswc7OjqeeeorJkyczZ84c3n77bZYuXUpJSQkjR440HvvCCy+QlpbG8uXLK51bEARBEHMiBEEQHjs35kOEhYWh0WgoLy/n7NmzTJkyhfLycqZPn17pmL1791aax/B3EhMT8fPzq7Tdzs6OV155hfbt2+Pk5ER8fDyffvop7du3Z9OmTXTr1s24b05ODgEBAZXqcHR0NJZXZb+/SkpKIjs7myZNmnDgwAGUSqVx/5EjR3LhwgV27dpl7GGIi4vjzTffJC8vj8LCQn755RfMzc1xdnY21rllyxbatGlzJ2+RIAjCY08EEYIgCI+ZEydOAPDyyy/z8ssvG7dHRkaybdu22wYLjRs35vjx43dUv6en5223R0REEBERYXzepk0bBgwYQP369Zk6dapJEAH84xChW8vudL9b3XgPPvzwQ2MAARhXppo1a5bJsSqVCoVCgY2NDQ4ODojpgoIgCP9MBBGCIAiPmZMnT2Jubs6+ffuQSCQolUpq1aqFk5PT3x5jbW1NeHj4HdVfleE99vb29O7dmzlz5lBaWoqFhQUATk5Ot+1FyM3NBW72NNzpfn918uRJzMzM6Nixo8n2EydO4OnpaRwOdcOpU6cICwsTQ5cEQRDukJgTIQiC8Jg5efIkDRo0oEmTJkRGRtKgQYN/DCDAMJxJoVDc0c+VK1eq1J4bd/VvvfNfv359zp8/X2mOxZkzZ4CbS8Le6X5/deLECRo2bIhCoTDZHhUVRWRk5G33b9y4cVVeliAIwn+auOUiCILwGCkoKCAhIYGuXbtW6bjqGM50O3l5eWzcuJHw8HDMzc2N2wcMGMDcuXNZvXo1Q4cONW5fsGABnp6eNGvWrEr7/dXJkycrLTNbVlZGbGwsgwYNMtmelpZGenq6CCIEQRCqQAQRgiAIj5GTJ0+i1+urfEFsY2Nz2zv0VTF8+HB8fHyIjIzE2dmZS5cu8fnnn5ORkVEpuV2PHj3o0qUL48aNo7CwkKCgIJYuXcrWrVtZvHixMffDne53q6tXr5KZmVnp9Zw+fRqNRlNp+435E/f6+gVBEP5LRBAhCILwGLmxMlOjRo0e+LkbNGjA8uXLmTNnDiqVCkdHR1q3bs2iRYtuu6zsmjVreOedd3jvvffIzc0lJCSEpUuX8uSTT97Vfjf8XVDwT9sVCgX169e/69cuCILwXyMyVguCIAiCIAiCUCViYrUgCIIgCIIgCFUigghBEARBEARBEKpEBBGCIAiCIAiCIFSJCCIEQRAEQRAEQaiSRyqISE1NZeTIkTg5OWFpaUl4eLhxtQ0wJDT64IMP8PT0xMLCgvbt2xMbG1uDLRYEQRAEQRCEx88jE0Tk5eXRqlUrFAoFW7Zs4dy5c3z++efY29sb9/nkk0/44osv+O677zh+/Dju7u506dKFoqKimmu4IAiCIAiCIDxmHpklXt98800OHjzI/v37b1uu1+vx9PRk0qRJvPHGGwCUl5fj5ubG7NmzeeGFFx5kcwVBEARBEAThsfXIBBGhoaF069aNq1evsnfvXmrVqsX48eN57rnnAEhISCAwMJCTJ08SERFhPK5fv37Y29uzYMGC29ZbXl5OeXm58blOpyM3NxcnJyckEsn9fVGCIAiCIAiC8ADo9XqKiorw9PREKr33wUiPTMbqhIQEfvzxR6ZMmcLbb7/NsWPHePnllzEzM+Opp54iPT0dADc3N5Pj3NzcSEpK+tt6Z86cybRp0+5r2wVBEARBEAThYZCSkoKXl9c91/PIBBE6nY7IyEhmzJgBQEREBLGxsfz444889dRTxv3+2nug1+v/sUfhrbfeYsqUKcbnBQUF+Pj4cPHiRRwdHav5VQiPE7Vaze7du+nQoQMKhaKmmyM85MTnRbhT4rPy6HjyySfZuXMnAFu3biUyMtKkfMiQIezatQuAbdu20bhx42pvw/38vCxatIjJkycDYG9vz6uvvkqLFi2Ijo7m888/Jy0tDYA33niD119//Z7P99ZbbzF37lwAGjduzKxZs2jYsCGHDh3ijTfe4MKFCwC88847xnY9isrLy9mwYQN79uyhrKwMX19fhg0bRlBQ0H09b25uLrVr18bGxqZa6ntkgggPDw9CQ0NNttWtW5fVq1cD4O7uDkB6ejoeHh7GfTIzMyv1TtzKzMwMMzOzStsdHR1xcnKqjqYLjym1Wo2lpSVOTk7iD73wr8TnRbhT4rPy6BgxYoQxiHj77bdZt24dXl5e6HQ6fvnlF2MA4efnR6dOnZDJZNXehvv5efn999+Nj//44w/atWsHQKdOnejVqxf16tVDp9OxePFiZs6cec/DwP/3v/+xevVqcnNzOXHiBF26dKm0j4+PD6+++ioODg73dK6a9sILL9TYfN3qGq7/yKzO1KpVK2MEesPFixfx9fUFwN/fH3d3d3bs2GEsr6ioYO/evbRs2fKBtlUQBEEQhMff0KFD8fHxAeDkyZMEBATQunVrAgICTC4QX3vttfsSQNxvp0+fBiA4ONgYQNwQEhJCmzZtAMMS/NnZ2fd8Ph8fH3bs2IGnp+dty4ODg9m5c+cjH0A8Lh6ZnojJkyfTsmVLZsyYwZAhQzh27Bg///wzP//8M2CIqiZNmsSMGTMIDg4mODiYGTNmYGlpyfDhw2u49YIgCIIgPG4sLCzYuHEjXbp0ISMjA7VazcGDB032mTBhAuPHj6+hFt6bG5NvKyoqbjs8vKKiotK+96pRo0ZcvHiRpUuXGnslXF1dGTZsGIMGDbrt6BGhZjwyQUSTJk1Yu3Ytb731FtOnT8ff35+vvvqKESNGGPeZOnUqpaWljB8/nry8PJo1a8b27durbeyXIAiCIAjCrerXr090dDTffPMN8+bNIyMjA6lUSocOHXj55Zfp06fPI7vaY9OmTdm/fz9JSUls2LCBvn37GsuOHz/O4cOHAQgMDKzWeaRWVlY8++yzPPvss9VWp1D9HpkgAqB379707t37b8slEgkffPABH3zwwYNrlCAIgiAI/2nu7u7MmDGDjz/+mNLSUpRKJXL5I3WJdVvjxo0z5ucaOnQoEydOpG3btkRFRfHVV1+Z7PeoBkrC3Xv0P+GCIAiCIAgPAYlEgqWlZU03o9oMGTKEJUuWsHHjRsrKyvjss8/47LPPTPZp3rz5IztcS7g3j8zEakEQBEEQBOHBkclkrFq1ivHjx6NUKk3KpFIpw4cPZ9u2bVhYWNRQC4WaJHoiBEEQBEEQhNsyMzPj+++/5/3332fNmjVkZmbi4OBAv379jCtTCf9NIogQBEEQBEEQ/pGrqysvvvhiTTdDeIiI4UyCIAiCIAiCIFSJ6IkQBEEQBEEQhAeouFzDFzsuciQhB39nK+p52hHqaUuohy0uNo9GLgwRRAiCIAiCIAjCA3LgUjZvrI4hNb8UgNhrhWyMSTOWu9iYUe96QHEjsPBzskIqfbiW0RVBhCAIgiAIgiDcZ4VlamZuPs/SYykAeDlY8HKnYLJV5Zy7Vsi5tEISs4vJKipnz4Us9lzIMh5rqZRR1+NmYNE8wAl/Z6uaeimACCIEQRAEQRCE/7gLFy6wadMmioqK8PLyYuDAgTg4OFRb/XsuZPLWmjOkFZQB8FQLX97oHoKVmemleHG5hrj0Is6lFRoDi7i0QkoqtJxIyuNEUh4AcqmEBWOb0irIudraWFUiiBAEQRAEQRDLine truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2538,7 +2528,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -2581,7 +2571,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2591,7 +2581,7 @@
     },
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 2 Axes>"
       ]
@@ -2623,7 +2613,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2654,7 +2644,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2685,7 +2675,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 1000x600 with 2 Axes>"
       ]
@@ -2767,7 +2757,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAooAAAF4CAYAAADTxtgDAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAA9hAAAPYQGoP6dpAADTnklEQVR4nOzdd3xb93k2/At7gxgEMbj3EEUta3pIciw7suvEduw0Ho3jNG3qxEkTPx1ZTZzUdkbb9HnepE2aVTvxiJ3EM5FlybaGZVuTlChR3AQ3ARB77/P+geCIEECKlDhA8f7qgw9FzHNAjOv8xv3jMAzDgBBCCCGEkItwl3oDCCGEEEJIfqKgSAghhBBCcqKgSAghhBBCcqKgSAghhBBCcqKgSAghhBBCcqKgSAghhBBCcqKgSAghhBBCcqKgSAghhBBCcqKgSAghhBBCcqKgSAghhBBCcqKgSAghsxSJRPDQQw+htLQUSqUSW7Zswfvvv7/Um0UIIQuGgiIhhMxSPB5HZWUl3nvvPbjdbjz88MP4yEc+gmAwuNSbRgghC4LDMAyz1BtBCCHLlUajwYEDB7BmzZql3hRCCJl31KJIyAqxZ88ecDgc9sTn81FRUYFHH30Ufr9/QR/7nXfewac//Wk0NDRAJpOhuLgYH/3oR3Hq1Kms6/r9fnzpS1+CyWSCWCzG2rVr8dvf/jbn/c7luguhq6sLoVAI1dXVi/aYhBCymPhLvQGEkMXR2toKAPjDH/4Ak8mEQCCAZ599Fv/5n/8Jt9uNX/3qVwv22D/5yU/gcDjw93//92hqasLk5CT+4z/+A1u2bMGbb76JG2+8kb3uXXfdhRMnTuB73/se6urq8Nxzz+Hee+9FMpnEfffdl3G/c7nufAsGg/irv/orfOMb34BcLl/QxyKEkKVCXc+ErBB33XUX3njjDfj9fvB4PABAMplEdXU1/H4/JicnF+yxbTYbioqKMs7z+/2oqalBc3Mz3nrrLQCpVs/bbruNDXxpN998Mzo6OjA8PMxu+1yuO99isRjuvPNOaLVaPPXUU+BwOAvyOIQQstSo65mQFeLUqVNobGzMCE9cLhc6nQ58/sJ2LlwcEgFALpejqakJIyMj7Hkvv/wy5HI57rnnnozrPvTQQxgfH8exY8cu67pT3Xzzzbjuuuuwb98+XHfddZBKpaioqMALL7wAAHjhhRdwzTXXQCqVoqmpCQcOHMi4fTKZxCc/+UnweDz88pe/pJBICLmqUVAkZAVwOBwYHh7G6tWrM863Wq3o6OjICltpDMMgHo/P6jRXHo8Hra2tWLVqFXveuXPn0NjYmBVcW1pa2Msv57pTtbW1YXh4GN/4xjfwyCOP4KWXXkJBQQE++clP4stf/jJ++tOf4mtf+xqef/55BINBPPDAAxm3/+xnP4uJiQm88MILCx6wCSFkqdGnHCErQHp8YlNTE+LxOGKxGNrb2/H3f//3uOWWW/Dkk0/mvN2hQ4ewc+fOWT2G2WxGRUXFrLfp85//PAKBAL7+9a+z5zkcDlRVVWVdV6PRsJdfznXThoaGYLfbsXHjRhw5cgRCoZC97gMPPIDu7m688847bCthV1cXvvKVr8DlckGtVmNoaAi/+MUvIBaLUVhYyN7vG2+8geuvv37W+04IIcsFBUVCVoD07OKvfOUr+MpXvsKev2vXLrzwwgsQCAQ5b7dhwwacOHFiVo9hMplmvT3/8i//gmeffRY/+tGPsGHDhozLZurKvfiyuVwXuPA8/Ou//isbEgHA6/UCAL73ve9l3M7v90MgEEChUAAAysvLQcO6CSErCQVFQlaA1tZW8Hg8vPvuuxAIBHA4HPjBD36A/fv34+c//zk+97nP5bydXC7H2rVrZ/UYs+2G/fa3v43HH38cTzzxBB555JGMy7Rabc6WQKfTCeBCa+Fcr5vW2toKkUiUMcsaSAVIk8nEdluntbW1obm5mbqYCSErFo1RJGQFaG1tRVNTE7Zu3YprrrkGt9xyC/7whz9AJpPhF7/4xbS3O3ToEAQCwaxOg4ODl9yOb3/723jsscfw2GOP4Wtf+1rW5atXr0ZnZ2fWmMezZ88CAJqbmy/rummnTp3CmjVrslpQT548iWuuuSbn9S9u8SSEkJWEgiIhVzmPx4OBgQFs3Lgx43yVSoW77roLbW1tGBgYyHnbdNfzbE6X6nr+13/9Vzz22GP4xje+gW9961s5r3PnnXfC7/fjD3/4Q8b5Tz/9NEwmEzZv3nxZ101rbW3NCoThcBgdHR1Z509MTMBisVBQJISsaNSfQshVrrW1FQzDYNOmTVmX3X333fjNb36Dl19+Gf/n//yfrMsVCkXOlra5+o//+A9885vfxIc//GHcdtttOHr0aMblW7ZsAQDs3r0bu3btwsMPPwyv14uamho8//zz2Lt3L5555pmM0j5zuS4AjI6OwmazZe3PmTNnEI/Hs85Pj2ecj/0nhJDlioIiIVe59Izni1sUAeCWW26BQqHAK6+8kjMozpfXX38dALB3717s3bs36/KpE0ReeuklfP3rX8c3v/lNOJ1ONDQ04Pnnn8cnPvGJrNvN5brTBb+ZzhcIBFklhQghZCWhlVkIIYQQQkhONEaREEIIIYTkREGREEIIIYTkREGREEIIIYTkREGREEIIIYTkdNlB8bvf/S42btwIhUKBoqIi3HHHHeju7s64DsMweOyxx2AymSCRSLBjxw50dHRc8UYTQgghhJCFd9lB8dChQ/j85z+Po0ePYv/+/YjH47j55psRCATY6/zgBz/AD3/4Q/z4xz/GiRMnYDAYsGvXLvh8vnnZeEIIIYQQsnDmrTzO5OQkioqKcOjQIdxwww1gGAYmkwlf+tKX8M///M8AgEgkAr1ej+9///v47Gc/m3UfkUgEkUiE/T2ZTMLpdEKr1YLD4czHZhJCCCEkzzAMA5/PB5PJBC6XRsXlk3kruO3xeAAAGo0GAGA2m2GxWHDzzTez1xGJRNi+fTvef//9nEHxu9/9Lr797W/P1yYRQgghZBkZGRlBSUnJUm8GmWJegiLDMHj00Udx3XXXobm5GQBgsVgAAHq9PuO6er0eQ0NDOe/nq1/9Kh599FH2d4/Hg7KyMpjNZigUiivezlgshgMHDmDnzp0QCARXfH/LwUrcZ2Bl7vdK3GeA9nsl7fdK3GdgZey3z+dDZWXlvHzXk/k1L0HxkUceQXt7O44cOZJ12cVdxgzDTNuNLBKJIBKJss7XaDRQKpVXvJ2xWAxSqRRarfaqfbNdbCXuM7Ay93sl7jNA+72S9nsl7jOwMvY7vV80zCz/XPFAgC984Qt47bXXcODAgYzmYoPBAOBCy2KazWbLamUkhBBCCCH557KDIsMweOSRR/DSSy/hnXfeQWVlZcbllZWVMBgM2L9/P3teNBrFoUOHsG3btsvfYkIIIYQQsiguu+v585//PJ577jm8+uqrUCgUbMthQUEBJBIJOBwOvvSlL+HJJ59EbW0tamtr8eSTT0IqleK+++6btx0ghBBCCCEL47KD4k9+8hMAwI4dOzLO/9///V986lOfAgD80z/9E0KhED73uc/B5XJh8+bN2LdvHw1WJYQQQghZBi47KM6m/CKHw8Fjjz2Gxx577HIfhhBCCCGELBGqakkIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnKioEgIIYQQQnK67KB4+PBh3H777TCZTOBwOHjllVcyLv/Upz4FDoeTcdqyZcuVbi8hhBBCCFkklx0UA4EA1qxZgx//+MfTXufDH/4wJiYm2NOePXsu9+EIIYQQQsgi41/uDXfv3o3du3fPeB2RSASDwXC5D0EIIYQQQpbQZQfF2Th48CCKioqgUqmwfft2PPHEEygqKpr2+pFIBJFIhP3d6/UCAGKxGGKx2BVvT/o+5uO+louVuM/AytzvlbjPAO33StrvlbjPwMrY76t535Y7DsMwzBXfCYeDl19+GXfccQd73gsvvAC5XI7y8nKYzWb8y7/8C+LxOE6dOgWRSJTzfh577DF8+9vfzjr/ueeeg1QqvdLNJIQQQkgeCgaDuO++++DxeKBUKpd6c8gUCxYULzYxMYHy8nL89re/xV133ZXzOrlaFEtLS2G32+flhROLxbB//37s2rULAoHgiu9vOViJ+wyszP1eifsM0H6vpP1eifsMrIz99nq9KCwspKCYhxa063kqo9GI8vJy9Pb2TnsdkUiUs7VRIBDM65tjvu9vOViJ+wyszP1eifsM0H6vJCtxn4Gre7+v1v26GixaHUWHw4GRkREYjcbFekhCCCGEEHIFLrtF0e/3o6+vj/3dbDbj9OnT0Gg00Gg0eOyxx/Cxj30MRqMRg4OD+NrXvobCwkLceeed87LhhBBCCCFkYV12UDx58iR27tzJ/v7oo48CAB588EH85Cc/wdmzZ/HrX/8abrcLine truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2889,7 +2879,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAugAAAFfCAYAAAAcfTnAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAA9hAAAPYQGoP6dpAACSiElEQVR4nOzdd1gVx9fA8e+99C6IigqKDbF3sWvsJSaWGHvvRqPRxB5LYotvNCbRaNTYe4y9l9hixd47AiJIkyL1wt33D8LG+0MTpSPn8zw87u7Mzp7FFQ9zZ2c0iqIoCCGEEEIIIbIFbVYHIIQQQgghhPiHJOhCCCGEEEJkI5KgCyGEEEIIkY1Igi6EEEIIIUQ2Igm6EEIIIYQQ2Ygk6EIIIYQQQmQjkqALIYQQQgiRjRhndQD/S6/X8+zZM2xsbNBoNFkdjhBCCCGEEOlCURQiIyMpVKgQWu2b+8mzXYL+7NkzXFxcsjoMIYQQQgghMoSvry/Ozs5vLM92CbqNjQ2QFLitrW2a2tLpdBw6dIjmzZtjYmKSHuGJHEieAyHPgJBnQIA8ByLrn4GIiAhcXFzUfPdNsl2CnjysxdbWNl0SdEtLS2xtbeUfYi4mz4GQZ0DIMyBAngORfZ6B/xrGLS+JCiGEEEIIkY1Igi6EEEIIIUQ2Igm6EEIIIYQQ2Ygk6EIIIYQQQmQj2e4l0bcRGxtLUFDQf9bT6/W4uLjw7Nmzf51rUrzf3uU5yJcvH+bm5pkUmRBCCCFESjkuQY+NjSUwMJDChQtjZGT0r3X1ej12dnbY2tpKgp6Lve1zkJiYiJ+fH/nz55ckXQghhHjPxMbG4unpybVr13B3d6d06dJZHdIb5bisNSgo6K2ScyHelZGREYULF36rT2eEEEIIkTPExMQwadIknJ2dadCgAVOnTsXd3Z0GDRpw/PjxrA7vtXJcgg5Ici4yjDxbQgghxPsjJiaGVq1aMWvWLEJCQgzKTp06RdOmTfn999+zKLo3y5EJuhBCCCGEEP9lxowZnDhxAgBjY2M6duxIu3btcHNzA5KGt/bu3ZuAgICsDDMFSdCFEEIIIcR7JzY2liVLlgBJyfnp06fZuHEjffr04dq1a3Tt2hVI6mVftmxZVoaagiToQgghhBDivXPp0iVCQ0MB6NixIzVr1lTLjIyMmD17trp/8ODBTI/v3+S4WVzSg6Io/PXXX9y+fRsTExPq1aunftQhhBBCCCFyvqioKHW7WLFiKcqdnZ3RarXo9XqDutlBrutB37t3L2XKlKFBgwYMGTKE/v37U7p0aZo3b86jR48y7Lp9+vRBo9EwZMiQFGXDhg1Do9HQp0+fDLt+bqDRaNixY0dWhyGEEEKIbMDV1VXd3rVrF3q93qB879696rHXJfBZKVcl6Fu2bKFt27bcu3cvRdnhw4epU6dOhibpLi4ubNq0iZiYGPVYbGwsGzdupEiRIhl23fQQHx+f1SEIIYQQQrw1Nzc36tSpA8Dt27fp06cPT58+Ra/Xs2fPHoNO0759+2ZVmK+VaxL08PBwBgwYgKIoANSpU4dFixYxY8YMXFxcAAgMDOSzzz7LsBiqVq1KkSJF2LZtm3ps27ZtuLi4UKVKFfWYoijMnTuX4sWLY2FhQaVKldi6datanpiYSP/+/SlWrBgWFhaULl2aH3/80eBax48fp2bNmlhZWZEnTx7q1q2Lt7c3kNSb365dO4P6o0aNolGjRup+o0aNGD58OKNHj8bR0ZFmzZoBSQ9469atsba2pkCBAvTs2ZPg4GCD80aMGMGoUaOwt7enQIECLF26lKioKPr27YuNjQ0lSpRg//79Btd/m3Y///xzxo4di4ODA05OTkybNk0tT/4tuX379mg0GnX/2rVrNGnSBBcXF/LkyUO1atW4ePHif/xNCSGEEOJ98M0336iLFK5du5bixYvTqVMnOnTogL+/PwC1a9emdevWWRlmCrkmQV+3bh2RkZEAfPLJJ/z1118MGzaMSZMmce3aNZydnYGklwQePHiQYXH07duXlStXqvsrVqygX79+BnUmT57MypUrWbx4Mbdu3eKLL76gR48e6jRBer0eZ2dntmzZwu3bt5kyZQoTJ05ky5YtACQkJNCuXTsaNmzI9evXOXv2LIMGDUKj0bxTrKtXr1bfev7111/x9/enYcOGVK5cmYsXL3LgwAGeP3/Op59+muI8R0dHLly4wIgRIxg6dCidOnWiTp06XL58mRYtWtCzZ0+io6MB3qldKysrzp8/z9y5c/nmm284fPgwAJ6engCsXLkSf39/db979+4ULlyYo0eP4unpyfjx4zExMXmn74MQQgghcqYmTZqwbt06zMzM1GOJiYnqdu3atdm1a1f2WwdFyWbCw8MVQAkPD39tuY+Pz1u3lZiYqLx48UJJTExUOnfurAAKoFy4cCFF3W+++UYtX7lyZWrDf6PevXsrH3/8sRIUFKSYmZkpXl5eypMnTxRzc3MlKChI+fjjj5XevXsrL1++VMzNzZUzZ84YnN+/f3+la9eub2x/2LBhSseOHRVFUZSQkBAFUI4fP/6vsbxq5MiRSsOGDdX9hg0bKpUrVzao8/XXXyvNmzc3OObr66sAyr1799Tz6tWrp5YnJCQoVlZWSs+ePdVj/v7+CqCcPXs21e0qiqLUqFFDGTdunLoPKNu3bzeoY2Njo6xYsUJ9Dt7GuzxjImeIj49XduzYocTHx2d1KCKLyDMgFEWeg9zs6dOnytSpU5VatWoprq6uykcffaTs2LFDSUhIyNQ4/ivPTZZrZnFJSEhQt/PkyZOi3N7eXt3W6XQZFoejoyNt2rRh9erVKIpCmzZtcHR0VMtv375NbGysOqQkWXx8vMEwmCVLlrB8+XK8vb2JiYkhPj6eypUrA+Dg4ECfPn1o0aIFzZo1o2nTpnz66acULFjwnWKtXr26wf6lS5c4duwY1tbWKeo+evRInQmnYsWK6nEjIyPy5s1LhQoV1GMFChQAkoYUpbZdgIIFC6ptvMno0aMZNGgQq1evpkWLFnz66aeUKFHiX88RQgghxPulcOHCTJs2jUmTJrFv3z5at26drT9RzzVDXMqUKaNur1271qBMr9ezbt06db9s2bIZGku/fv1YtWoVq1evTjG8Jflt4r1793L16lX16/bt2+o49C1btvDFF1/Qr18/Dh06xNWrV+nbt6/Bi5wrV67k7Nmz1KlTh82bN+Pm5sa5c+cA0Gq16lj8ZK/7pcTKyipFbG3btjWI6+rVqzx48IAGDRqo9f73gddoNAbHkofaJN9rWtr93zey/9e0adO4ceMGzZs3588//6Rs2bJs3779X88RQgghhMhKuaYHvV+/fsycORNFUZg1axaKotCjRw9evHjB//3f/3H+/HkgKZFPfuM3o7Rs2VJNplu0aGFQVrZsWczMzPDx8aFhw4avPf/UqVPUqVOHYcOGqcdeN/tMlSpVqFKlChMmTKB27dps2LCBWrVqkS9fPm7evGlQ9+rVq//5m2TVqlX5448/cHV1xdg4/R6d9GrXxMTEYFxZMjc3N4YNG8b48ePp3r07K1eupH379mkJWQghhBAiw+SaHvRixYoxZswYIOnlgBkzZuDu7k7t2rXVWVW0Wi3z589/55cp35WRkRF37tzhzp07KV5KsLGx4csvv+SLL75g9erVPHr0iCtXrrBo0SJWr14NQMmSJbl48SIHDx7k/v37fP311+pLkQBeXl5MmDCBs2fP4u3tzaFDh7h//776KULjxo25ePEia9as4cGDB0ydOjVFwv46n332GaGhoXTt2pULFy7w+PFjDh06RL9+/V6bGL+t9GrX1dWVo0ePEhAQwIsXL4iJiWH48OEcP34cHx8fTp8+jaenp8GnKUIIIYQQ2U2uSdABvvvuO8aMGfPaBNzW1pbNmzfTsmXLTInF1tYWW1vb15Z9++23TJkyhdmzZ1OmTBlatGjB7t271Un0hwwZQocOHejcuTMeHh6EhIQY9KZbWlpy9+5dOnbsiJubG4MGDWL48OEMHjwYSOq1//rrrxk7diw1atQgMjKSXr16/WfMhQoV4vTp0yQmJtKiRQvKly/PyJEjsbOzU6cwSo30anfevHkcPnxYnbbSyMiIkJAQ+vTpQ40aNejSpQutWrVi+vTpqY5VCCGEECKjaZT/HYycxSIiIrCzsyM8PPy1Cayvr686b/l/0ev1REREYGtra5DoPXnyhJUrV3Lnzh1MTEyoX78+3bt3x8bGJt3uQ2Qfb3oO3uRdnjGRM+h0uhzxUpDIOPIMCJDnQGT9M/BfeW6yXDMG/VWurq7SiyqEEEIIIbKlXDXERQghhBBCiOxOEnQhhBBCCCGyEUnQhRBCCCGEyEYkQRdCCCGEECIbkQRdCCGEEEKIbEQSdCGEEEIIIbIRSdCFEEIIIYTIRiRBz2KNGjVi1KhR6r6rqysLFizIsniEEEIIIUTWkgQ9k/Tp0weNRpPia+7cuXz77bdvPE+j0bBjx47MC1QIIYQQQmSpXLmSaFZp2bIlK1euNDiWL18+jIyMMvzaOp1OljUWQgghRK521TeMXd5amifqyc5pkfSgZyIzMzOcnJwMvpo0aWIwxOVVrq6uALRv3x6NRqPuA+zevZtq1aphbm5O8eLFmT59OgkJCWq5RqNhyZIlfPzxx1hZWTFjxowMvDMhhBBCiOwtMCKW4RuvcfSZliUnvbI6nH+V43vQFUUhRpf42jK9Xk9MfCLG8Qloten/u4iFiREajSbd203m6elJ/vz5WblyJS1btlR72g8ePEiPHj346aefqF+/Po8ePWLQoEEATJ06VT1/6tSpzJ49mx9++CFTeumFEEIIIbKjuIREBq+7xPPIOJwsFPrUKZrVIf2rHJ+gx+gSKTvlYJZc+/Y3LbA0fftv4Z49e7C2tlb3W7Vq9a/18+XLB0CePHlwcnJSj8+cOZPx48fTu3dvAIoXL863337L2LFjDRL0bt260a9fv7eLine truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2924,7 +2914,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -2965,7 +2955,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -3005,7 +2995,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": "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 truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -3060,7 +3050,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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 truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -3135,7 +3125,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -3149,7 +3139,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.12"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

Supporting_Notebooks/Interactions.ipynb

@@ -12,7 +12,7 @@
        "        <style>\n",
        "        .output_wrapper, .output {\n",
        "            height:auto !important;\n",
-       "            max-height:100000px; \n",
+       "            max-height:100000px;\n",
        "        }\n",
        "        .output_scroll {\n",
        "            box-shadow:none !important;\n",
@@ -93,23 +93,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "scrolled": true
-   },
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Anaconda3\\lib\\site-packages\\IPython\\html.py:14: ShimWarning: The `IPython.html` package has been deprecated since IPython 4.0. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
-      "  \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n"
-     ]
-    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "609e5b01d9564d6b8c6e025cab5df9cb",
+       "model_id": "5f6d72e65be24e628d9f6f144f309234",
        "version_major": 2,
        "version_minor": 0
       },
@@ -160,6 +150,7 @@
     "    plt.title(str(F))\n",
     "    plt.xlabel('position')\n",
     "    plt.ylabel('velocity')\n",
+    "    plt.show()\n",
     "                 \n",
     "interact(plot_FPFT, \n",
     "         F00=widgets.IntSlider(value=1, min=0, max=2.), \n",
@@ -188,7 +179,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "94a56f8ac01144e0b32bbb39a353e40a",
+       "model_id": "cc2e30d2d25946d598ba42683e49c891",
        "version_major": 2,
        "version_minor": 0
       },
@@ -255,7 +246,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "690c1af2d34845dd837f33de97469854",
+       "model_id": "c8a6dc551eae4845beaae8da7b8f72b3",
        "version_major": 2,
        "version_minor": 0
       },
@@ -313,7 +304,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -327,9 +318,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.12"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }