Changed IPython Notebook to Jupyter Notebook.

00-Preface.ipynb

@@ -35,6 +35,7 @@
        "@import url('http://fonts.googleapis.com/css?family=Source+Code+Pro');\n",
        "@import url('http://fonts.googleapis.com/css?family=Vollkorn');\n",
        "@import url('http://fonts.googleapis.com/css?family=Arimo');\n",
+       "@import url('http://fonts.googleapis.com/css?family=Fira_sans');\n",
        "\n",
        "    div.cell{\n",
        "        width: 900px;\n",
@@ -125,9 +126,10 @@
        "        white-space: nowrap;\n",
        "    }\n",
        "    div.text_cell_render{\n",
-       "        font-family: 'Arimo',verdana,arial,sans-serif;\n",
-       "        line-height: 125%;\n",
-       "        font-size: 120%;\n",
+       "        font-family: 'Fira sans', verdana,arial,sans-serif;\n",
+       "        line-height: 150%;\n",
+       "        font-size: 110%;\n",
+       "        font-weight: 400;\n",
        "        text-align:justify;\n",
        "        text-justify:inter-word;\n",
        "    }\n",
@@ -240,7 +242,7 @@
        "<script>\n",
        "    MathJax.Hub.Config({\n",
        "                        TeX: {\n",
-       "                           extensions: [\"AMSmath.js\"]\n",
+       "                           extensions: [\"AMSmath.js\", \"autobold.js\"]\n",
        "                           },\n",
        "                tex2jax: {\n",
        "                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
@@ -278,7 +280,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Introductory textbook for Kalman filters and Bayesian filters. All code is written in Python, and the book itself is written in IPython Notebook so that you can run and modify the code in the book in place, seeing the results inside the book. What better way to learn?\n",
+    "Introductory textbook for Kalman filters and Bayesian filters. The book is written using Jupyter Notebook so that read the book in your browser and also run and modify the code, seeing the results inside the book. What better way to learn?\n",
     "\n",
     "<img src=\"https://raw.githubusercontent.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/animations/05_dog_track.gif\">\n"
    ]
@@ -434,13 +436,13 @@
     "\n",
     "`git clone --depth=1 https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python.git`\n",
     "    \n",
-    "This will create a directory named `Kalman-and-Bayesian-Filters-in-Python`. The `depth` parameter just gets you the latest version. Unless you need to see my entire commit history this is a lot faster and saves space. Navigate to the directory, and run IPython notebook with the command\n",
+    "This will create a directory named `Kalman-and-Bayesian-Filters-in-Python`. The `depth` parameter just gets you the latest version. Unless you need to see my entire commit history this is a lot faster and saves space. Navigate to the directory, and run Jupyter Notebook with the command\n",
     "\n",
     "    ipython notebook\n",
     "\n",
     "This will open a browser window showing the contents of the base directory. The book is organized into chapters. Each chapter is named *xx*-*name*.ipynb, where *xx* is the chapter number. .ipynb is the Notebook file extension.\n",
     "\n",
-    "This is admittedly a somewhat cumbersome interface to a book; I am following in the footsteps of several other projects that are somewhat re-purposing IPython Notebook to generate entire books. I feel the slight annoyances have a huge payoff - instead of having to download a separate code base and run it in an IDE while you try to read a book, all of the code and text is in one place. If you want to alter the code, you may do so and immediately see the effects of your change. If you find a bug, you can make a fix, and push it back to my repository so that everyone in the world benefits. And, of course, you will never encounter a problem I face all the time with traditional books - the book and the code are out of sync with each other, and you are left scratching your head as to which source to trust."
+    "This is admittedly a somewhat cumbersome interface to a book; I am following in the footsteps of several other projects that are somewhat re-purposing Jupyter Notebook to generate entire books. I feel the slight annoyances have a huge payoff - instead of having to download a separate code base and run it in an IDE while you try to read a book, all of the code and text is in one place. If you want to alter the code, you may do so and immediately see the effects of your change. If you find a bug, you can make a fix, and push it back to my repository so that everyone in the world benefits. And, of course, you will never encounter a problem I face all the time with traditional books - the book and the code are out of sync with each other, and you are left scratching your head as to which source to trust."
    ]
   },
   {
@@ -486,7 +488,7 @@
     "\n",
     "Code that is specific to the book is stored with the book in the subdirectory **/code**. It contains code for formatting the book. It also contains python files with names like *xxx*_internal.py. I use these to store functions that are useful for a specific chapter. This allows me to hide Python code that is not particularly interesting to read - I may be generating a plot or chart, and I want you to focus on the contents of the chart, not the mechanics of how I generate that chart with Python. If you are curious as to the mechanics of that, just go and browse the source.\n",
     "\n",
-    "Some chapters introduce functions that are useful for the rest of the book. Those functions are initially defined within the Notebook itself, but the code is also stored in a Python file in **/code** that is imported if needed in later chapters. I do document when I do this where the function is first defined, but this is still a work in progress. I try to avoid this because then I always face the issue of code in the directory becoming out of sync with the code in the book. However, IPython Notebook does not give us a way to refer to code cells in other notebooks, so this is the only mechanism I know of to share functionality across notebooks.\n",
+    "Some chapters introduce functions that are useful for the rest of the book. Those functions are initially defined within the Notebook itself, but the code is also stored in a Python file in **/code** that is imported if needed in later chapters. I do document when I do this where the function is first defined, but this is still a work in progress. I try to avoid this because then I always face the issue of code in the directory becoming out of sync with the code in the book. However, Jupyter Notebook does not give us a way to refer to code cells in other notebooks, so this is the only mechanism I know of to share functionality across notebooks.\n",
     "\n",
     "There is an undocumented directory called **/experiments**. This is where I write and test code prior to putting it in the book. There is some interesting stuff in there, and feel free to look at it. As the book evolves I plan to create examples and projects, and a lot of this material will end up there. Small experiments will eventually just be deleted. If you are just interested in reading the book you can safely ignore this directory. \n",
     "\n",
@@ -583,7 +585,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.5.0"
   }
  },
  "nbformat": 4,

01-g-h-filter.ipynb

@@ -120,8 +120,9 @@
        "    }\n",
        "    div.text_cell_render{\n",
        "        font-family: 'Fira sans', verdana,arial,sans-serif;\n",
-       "        line-height: 125%;\n",
-       "        font-size: 115%;\n",
+       "        line-height: 150%;\n",
+       "        font-size: 110%;\n",
+       "        font-weight: 400;\n",
        "        text-align:justify;\n",
        "        text-justify:inter-word;\n",
        "    }\n",
@@ -234,7 +235,7 @@
        "<script>\n",
        "    MathJax.Hub.Config({\n",
        "                        TeX: {\n",
-       "                           extensions: [\"AMSmath.js\"]\n",
+       "                           extensions: [\"AMSmath.js\", \"autobold.js\"]\n",
        "                           },\n",
        "                tex2jax: {\n",
        "                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
@@ -267,6 +268,8 @@
     "%autoreload 2  \n",
     "from __future__ import division, print_function\n",
     "import sys\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
     "sys.path.insert(0,'./code')\n",
     "from book_format import load_style\n",
     "load_style()"
@@ -328,9 +331,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAB6CAYAAADXnk6rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x810ac88>"
+       "<matplotlib.figure.Figure at 0x492d1d0>"
       ]
      },
      "metadata": {},
@@ -362,9 +365,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAB6CAYAAADXnk6rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAB6CAYAAADXnk6rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8148518>"
+       "<matplotlib.figure.Figure at 0x72f5a58>"
       ]
      },
      "metadata": {},
@@ -393,9 +396,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAB6CAYAAADXnk6rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAB6CAYAAADXnk6rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAETxJREFUeJzt3XtsVOW6x/HfTNtpoY0ESku5tZWLtMKBSIHkCFp0Y6mC\npaBy0y3iBYxSIBCRiwRIRKPYraAnoejhQBxqMSpylYsEim78wxLLRQ+Bbi4CoYAeQQu0lHadP9iM\nDDPTmc6s5fTy/SQT7TvvPOvtkyfDPF3vWmMzDMMQAAAAAJjMHu4FAAAAAGiaaDYAAAAAWIJmAwAA\nAIAlaDYAAAAAWIJmAwAAAIAlIs0KdOnSJbNCAQAAAH+5Vq1ahXsJTQ5nNgAAAABYgmYDAAAAgCVM\n20Z1K05BmaekpESS1K9fvzCvpGkhr9Ygr9Yht9Ygr9Ygr9Ygr9bgUgBrcWYDAAAAgCVoNgAAAABY\ngmYDAAAAgCVoNgAAAABYgmYDAAAAgCVoNgAAAABYgmYDAAAAgCVoNgAAAABYgmYDAAAAgCVoNgAA\nAABYgmYDAAAAgCVoNgAAAABYgmYDAAAAgCUiw70AAAAAoDGora3VtWvXwr2MBsXhcMhu933+gmYD\nAAAA8KO2tlZVVVWKiYmRzWYL93IaBMMwVFlZqejoaJ8NB9uoAAAAAD+uXbtGo3Ebm82mmJiYOs/2\n0GwAAAAAAaDR8OQvJzQbAAAAACxBswEAAAAEaOrSXE1dmmtJDCtjhwvNBgAAAABL0GwAAAAAsATN\nBgAAAACtXLlSdrtdaWlppsWk2QAAAAAgp9Op1NRUHTlyRCUlJabEpNkAAAAAmrnTp09rz549euut\nt9SpUyc5nU5T4tJsAAAAAM1cYWGhYmNjlZOTozFjxmjt2rWqra0NOW6kCWsDAAAAmr3tX2/Vx2v/\nR7XGddltkfr7mInKGpLdKOI7nU6NGDFC0dHRGjt2rPLz87Vjxw4NHTo0pLic2QAAAABCtP3rrXq3\n4E217lWl+P+oUeteVXq34E1t/3prg49/4MABHTp0SGPHjpUkZWRkqHv37qZspeLMBgAAAFBPt39x\n3neb/1f/OSzdbaz7oNZ6bck0bfrRfby+sc2Ofzun06n4+Hi3sxjjxo1Tfn6+rly5opYtWwYdmzMb\nAAAAQIjsdpvXcZvN+3hDiV9bW6tPPvlE999/v06cOKGysjKVlZWpf//+unz5sr788suQ4nNmAwAA\nAAhRba3hddwwvI83lPi7d+/WmTNntG7dOq1bt87jeafTqfHjxwcdn2YDAAAAqKdl09z/4r+9541r\nKroPau0aO/LN/+n1V5Z6XMTtbZtUXbHrE99f7Ns5nU61bdtWy5cv93hu69atWrVqlS5cuKCEhIR6\nxb2JZgMAAAAI0c0P/Gs+XaXrtdWKtEdpxotzTbtblBXxKysr9fnnn2vUqFEaNWqUx/M9e/bURx99\npKKiIuXl5QV1DJoNAAAAwARZQ7JNvdWt1fE3bNigP/74Qzk5OV6f79Gjh+uuVME2G1wgDgAAADRD\na9asUXR0tLKysnzOGTFihEpKSlRWVhbUMWg2AAAAgGZo/fr1unr1qmJjY33Oefvtt1VTU6Nu3boF\ndQyaDQAAAACWoNkAAAAAYAmaDQAAAACW4G5UAAAAQIC8fQeGWTGsjB0unNkAAAAAYAmaDQAAAACW\noNkAAAAAYAmaDQAAAACWoNkAAAAAYAmaDQAAACBA9oGG7AMNS2JYGTtcaDYAAAAAWIJmAwAAAIAl\naDYAAACAZmjVqlWy2+1uj8TERGVmZmr9+vWmHINvEAcAAACasUWLFqlr164yDEPnzp2T0+nUyJEj\nVVRUpNGjR4cUm2YDAAAAaMaGDh2qAQMGuH6ePHmyOnTooMLCwpCbDbZRAQAAAHCJjY1VbGysoqKi\nQo7FmQ0AAADABJu/Ktayj7arqjpS0VHXNfX5LA17OLPBx7948aJ++eUXSdKFCxdUUFCg8+fP6+mn\nnw45Ns0GAAAAEKLNXxVr2qJtOhax2DX2r0XzJMmUhsDK+NnZ2W4/OxwOFRQU6NFHHw0prkSzAQAA\nANTb7V+cZ/y8XbbkxW5jxyIWa/ik+bIl3x9SbLPj3+79999Xenq6JOncuXNas2aNXnzxRd1xxx16\n4oknQopNswEAAACEzNfH6ogGH79///5uF4iPHTtWGRkZmjp1qnJzc0O6doMLxAEAAICQXfcxXtNI\n4v/JZrMpMzNT586dU1lZWUixaDYAAACAeqr9p83tsWlFlrrUzHOb0+X6XG1a8ZDH3PrGrk98s1RX\nV0uSKioqQorDNioAAAAgRDcv0n7/v+er8lqEYhw1ynsu27S7UVkd/1bV1dXasWOHoqOjXddyBItm\nAwAAADDBsIczLfnwb3X8rVu36siRI5Kk8+fPq6ioSEePHtWcOXMUFxcXUmyaDQAAAKAZstlubLta\nuHChaywmJkbp6elavny5Jk2aFPIxaDYAAACAZmjChAmaMGGCpcfgAnEAAAAAlqDZAAAAAGAJmg0A\nAAAAluCaDQAAACBAZnyXha8YVsYOF85sAAAAALAEzQYAAAAAS9BsAAAAALAEzQaABsc+0JB9oBHu\nZQCAaXhfQ3NFswEAAAAEwDBoGG/nLyc0GwAAAIAfDodDlZWVNBy3MAxDlZWVcjgcPudw61sAAADA\nD7vdrujoaFVVVYV7KQ1KdHS07Hbf5y9oNgAAAIAA2O12xcTEhHsZjQrbqAAAAABYgmYDAAAAgCXY\nRgUAaJY2f1Ws1//xma5dj1LbNus09fksDXs4M9zLAoAmhWYDANDsbP6qWNMWbdOxiGU3Bsqlfy2a\nJ0k0HABgIpoNAJKkqUtzJUnLpn0Z5pX8iS/AulXGv/9LTsxg/LxdtuTFbmPHIhZr+KT5siXfH6ZV\nNSXUK4AbuGYDANAM+fpbW8RfugoAaOpoNgAAzdB1H+M1f+kqAKCpYxsVgAar9p+2cC+hwSgpKZEk\n9evXL8wraRo2f5WlaYvm6VjEn1upulyfq6UrsjXsYeouVNSrJ7aFormi2QAANDs3LwJf/I9pqroe\nqYT4lsp7LpuLwwHAZDQbAIBmadjDmWqXECuJv8ADgFW4ZgMAAACAJTizAcAU27/eqv9asVSGrUat\n7mitv4+ZqKwh2eFeFgAACCOaDQAh2/71Vr1b8Ka6D2r975EqvVvwpiTRcAAA0IzZDMMw5fYIly5d\nMiMMAAAAEBatWrUK9xKaHK7ZAAAAAGAJmg0AAAAAljBtGxUAAAAA3IozGwAAAAAsQbMBAAAAwBJ1\nNht79uxRTk6OOnXqJLvdrtWrV/ucO3nyZNntduXn57uNDx48WHa73e0xfvx4c1bfSPnL6zPPPOOR\ns3vvvddtTlVVlfLy8pSQkKC4uDiNGDFCZ86c+St/jQbHjLxSr54CeR84cuSIRo0apdatWys2NlYZ\nGRk6fPiw63nq1TszckvNevKX19vzdfMxZcoU1xxq1pMZeaVePfnLa0VFhfLy8tS5c2e1bNlSaWlp\neu+999zmUK+ezMgr9WqOOpuNy5cvq3fv3lq6dKlatGghm83mdd5nn32m77//Xh06dPCYY7PZ9Oyz\nz6q8vNz1KCgoMO83aIT85dVms+mhhx5yy9mWLVvc5kyfPl1ffPGFioqK9M033+j333/X8OHDVVtb\n+1f+Kg2KGXmlXj35y+vx48c1cOBAde3aVbt27dKPP/6oxYsXKy4uzjWHevXOjNxSs5785fXWXJWX\nl2vjxo2SpDFjxrjmULOezMgr9erJX15nzJihLVu2yOl06vDhw5o3b55mz54tp9PpmkO9ejIjr9Sr\nSYwAxcXFGatXr/YYP3HihNGxY0fj8OHDRmpqqpGfn+/2/ODBg40pU6YEephmx1teJ0yYYAwfPtzn\nay5evGg4HA6jsLDQNXbq1CnDbrcb27Zts2ytjUkweTUM6tUfb3kdN26c8dRTT/l8DfUamGByaxjU\nrD++/u261fPPP2+kpaW5fqZm/Qsmr4ZBvfrjLa+9evUyFi5c6DaWmZlp5OXlGYZBvQYimLwaBvVq\nlpCu2bh+/brGjRun+fPnq0ePHj7nFRUVKSEhQb169dIrr7yiioqKUA7b5NlsNn377bdq166devTo\noUmTJunChQuu5/ft26fq6mplZWW5xjp16qT09HTt3bs3HEtuFPzl9SbqNXC1tbXatGmT0tPTlZ2d\nrcTERA0YMECffvqpaw71GpxAcnsTNRu8iooKFRUV6YUXXnCNUbOh85bXm6jX+hk0aJA2bNig06dP\nS5L27t2r0tJSZWdnS6Jeg+UvrzdRr6GLDOXFCxYsUGJioiZPnuxzzvjx45WamqoOHTro0KFDmjNn\njg4cOKBt27aFcugmLTs7W4899pjuvPNOHT9+XK+99poefPBB7du3Tw6HQ+Xl5YqIiFB8fLzb69q1\na6dz586FadUNn7+8StRrfZ0/f14VFRV644039Prrr+vtt9/Wzp079eSTTyouLk6PPPII9RqkQHIr\nUbOhKiwsVHV1tSZMmOAao2ZD5y2vEvUajGXLlmnSpElKTk5WZOSNj20ffPCB6z2Aeg2Ov7xK1KtZ\ngm42du/erdWrV6u0tNRt3Ljtaztu/atGz5491bVrVw0YMEA//PCD7rnnnmAP36Tdur+1Z8+eysjI\nUEpKijZv3qyRI0eGcWWNWyB5pV7r5+Z+4NzcXE2fPl2S1Lt3b5WUlHi8aaN+As0tNRuaDz/8ULm5\nuR4f1BAaX3mlXutv2bJl+u6777Rx40alpKSouLhYM2fOVEpKioYOHRru5TVageSVejVH0NuoiouL\ndfbsWbVv315RUVGKiorSyZMn9eqrryo5Odnn6/r27auIiAiVlZUFe+hmp3379urUqLine truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x890d2b0>"
+       "<matplotlib.figure.Figure at 0x76ec8d0>"
       ]
      },
      "metadata": {},
@@ -430,7 +433,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average of measurements is 165.0140\n"
+      "Average of measurements is 165.0030\n"
      ]
     }
    ],
@@ -461,7 +464,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average of measurements is 164.8406\n"
+      "Average of measurements is 165.0638\n"
      ]
     }
    ],
@@ -493,9 +496,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwkAAAERCAYAAAAwgetTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwkAAAERCAYAAAAwgetTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8995d30>"
+       "<matplotlib.figure.Figure at 0x7f15710>"
       ]
      },
      "metadata": {},
@@ -524,9 +527,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvIAAAEtCAYAAABqG4QrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvIAAAEtCAYAAABqG4QrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8a2f9b0>"
+       "<matplotlib.figure.Figure at 0x7f94748>"
       ]
      },
      "metadata": {},
@@ -553,9 +556,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvIAAAEtCAYAAABqG4QrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvIAAAEtCAYAAABqG4QrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XtU1VXex/HPOVyU0ryggAwqaihKaSKaiRdSByHNy1RS\nOgLqMiszDScvZUM9y7TbMwqZM+YMZWCDTk+Pk9Yogze8TSFBXklMY7QJM1McSQ055/nDxzOeuHhI\n4Jzf8f1ai7U8+7fP73z32ipfvuzf3iar1WoVAAAAAEMxOzsAAAAAALVHIg8AAAAYEIk8AAAAYEAk\n8gAAAIABkcgDAAAABkQiDwAAABgQiTwAAABgQE5L5HNycjRy5EgFBQXJbDZr5cqVdtfPnz+v6dOn\nq23btrrlllsUGhqqJUuW2PWJioqS2Wy2+xo3blxDDgMAAABwCk9nfXBZWZm6d++uhIQExcfHy2Qy\n2V1PSkrSpk2blJGRoQ4dOmjbtm2aMmWKWrVqpV//+teSJJPJpEmTJmnhwoW29/n4+DToOAAAAABn\ncFpFPjY2VgsWLNADDzwgs7lyGLt371Z8fLwGDRqkdu3aacKECerbt68+/fRTu34+Pj7y8/OzfTVt\n2rShhgAAAAA4jcuuke/fv78+/PBDnThxQpK0a9cuFRQUKCYmxq5fZmamWrdurTvuuEPPPPOMzp8/\n74xwAQAAgAbltKU115OamqpHH31U7dq1k6fnlTCXLl2q++67z9Zn3LhxCg4OVmBgoPbv36958+Zp\n79692rhxo7PCBgAAABqESyfyu3fv1rp169S+fXtt27ZNs2bNUvv27TVs2DBJ0pQpU2z9w8LC1KlT\nJ/Xp00f5+fnq2bOn7VppaWmDxw8AAADUlWbNmlVqc8lE/sKFC3r22Wf1/vvva/jw4ZKkO+64QwUF\nBXr99ddtifxPhYeHy8PDQ0eOHLFL5AEAAAB345Jr5MvLy1VeXl7pIViz2Syr1Vrt+/bt26eKigq1\nadOmvkMEAAAAnMqp208WFRVJkiwWi4qLi1VQUCBfX1+1bdtWgwYN0ty5c9WkSRO1a9dO27ZtU3p6\nul577TVJ0tGjR5WRkaHhw4fL19dXBw8e1KxZsxQeHq7IyMhqP7eqX0vANezZs0eSFBER4eRIUBPm\nyRiYJ2NgnoyBeTIGd5yn6y0Pd1pFPjc3V+Hh4QoPD9fFixeVnJys8PBwJScnS7qyG03v3r01fvx4\nhYWF6dVXX9WCBQs0bdo0SZK3t7c2b96sYcOGKTQ0VDNmzFBMTIyys7Mr7UkPAAAAuBunVeSjoqJk\nsViqve7v76+0tLRqrwcFBWnr1q31EBkAAADg+lxyjTwAAACAmpHIAwAAAAZEIg8AAAAYEIk8AAAA\nYEAk8gAAAIABkcgDAAAABkQiDwAAABgQiTwAAABgQCTyAAAAgAGRyAMAAAAGRCIPAAAAGBCJPAAA\nAGBAJPIAAACAAZHIAwAAAAZEIg8AAAAYEIk8AAAAYEAk8gAAAIABkcgDAAAABkQiDwAAABiQ0xL5\nnJwcjRw5UkFBQTKbzVq5cqXd9fPnz2v69Olq27atbrnlFoWGhmrJkiV2fS5duqTp06erdevWatKk\niUaNGqWvv/66IYcBAAAAOIXTEvmysjJ1795dKSkp8vHxkclksruelJSkjz/+WBkZGSosLNRzzz2n\nuXPnKiMjw9Zn5syZ+uCDD5SZmant27fr3LlzGjFihCwWS0MPBwAAAGhQTkvkY2NjtWDBAj3wwAMy\nmyuHsXv3bsXHx2vQoEFq166dJkyYoL59++rTTz+VJJWWliotLU2vv/66hgwZop49eyo9PV179+5V\ndnZ2Qw8HAAAAaFAuu0a+f//++vDDD3XixAlJ0q5du1RQUKCYmBhJUl5ensrLyxUdHW17T1BQkLp2\n7apdu3Y5JWYAAACgoXg6O4DqpKam6tFHH1W7du3k6XklzKVLl+q+++6TJJWUlMjDw0O+vr527/P3\n99fJkycbPF4AAACgIbl0Ir97926tW7dO7du317Zt2zRr1iy1b99ew4YN+9n33bNnTx1GifrAHBkD\n82QMzJMxME/GwDwZgzvNU0hISI3XXTKRv3Dhgp599lm9//77Gj58uCTpjjvuUEFBgV5//XUNGzZM\nAQEBqqio0OnTp+2q8iUlJRo4cKCzQgcAAAAahEsm8uXl5SovL6/0EKzZbJbVapUk9erVS15eXsrK\nytIjjzwiSTpx4oQKCwvVr1+/au8dERFRf4Hjhlz9CZo5cm3MkzEwT8bAPBkD82QM7jhPpaWlNV53\nWiJfVlamoqIiSZLFYlFxcbEKCgrk6+urtm3batCgQZo7d66aNGmidu3aadu2bUpPT9drr70mSWrW\nrJkmT56s2bNny8/PTy1btlRSUpJ69OihoUOHOmtYAAAAQINw2q41ubm5Cg8PV3h4uC5evKjk5GSF\nh4crOTlZkpSZmanevXtr/PjxCgsL06uvvqoFCxZo2rRptnssWbJEY8aMUVxcnPr376/bbrtN69at\nq7QnPQAAAOBunFaRj4qKqvHgJn9/f6WlpdV4D29vb6Wmpio1NbWuwwMAAABcmsvuIw8AAACgeiTy\nAAAAgAG55K41AAAAwFVPpYx2uO+7O6/fJ3XG2huIxnVQkQcAAAAMiIo8AAAAXJojFfRrq/buUnG/\nHiryAAAAgAGRyAMAAAAGRCIPAAAAGBCJPAAAAGBAJPIAAACAAbFrDQAAgBupzZ7rjrhZdoAxIiry\nAAAAgAFRkQcAADctdzwxlD3Xbx5U5AEAAAADoiIPAABuWlSvYWRU5AEAAAADIpEHAAAADIhEHgAA\nADAgEnkAAADAgJyWyOfk5GjkyJEKCgqS2WzWypUr7a6bzeYqv5588klbn6ioqErXx40b19BDAQAA\nABqc03atKSsrU/fu3ZWQkKD4+HiZTCa76yUlJXavc3Nzdf/99ysuLs7WZjKZNGnSJC1cuNDW5uPj\nU7+BAwDqHCdRAkDtOS2Rj42NVWxsrCQpMTGx0nU/Pz+712vXrlWXLl00YMAAu3YfH59KfQEAAAB3\nZ4h95M+fP6/MzEy9+OKLla5lZmYqMzNT/v7+io2NVXJyspo0aeKEKAEAPxd7eQNA7RkikX/vvfdU\nXl6uhIQEu/Zx48YpODhYgYGB2r9/v+bNm6e9e/dq48aNTooUAAAAaBiGSORXrFih0aNHy9fX1659\nypQptj+HhYWpU6dO6tOnj/Lz89WzZ88q77Vnz556jRU3jjkyBubJGNx1ntxtXO42HnfmjnPFmFxX\nSEhIjdddfvvJgoIC5eXl2SXt1QkPD5eHh4eOHDnSAJEBAAAAzuPyFfm33npLHTt21JAhQ67bd9++\nfaqoqFCbNm2q7RMREVGX4aEOXf3pmTlybcyTMbjjPL278z9/dpdxueM8uSN3/LvHmIyhtLS0xutO\n3X6yqKhIkmSxWFRcXKyCggL5+vqqbdu2kqQffvhBq1at0ty5cyu9/+jRo8rIyNDw4cPl6+urgwcP\natasWQoPD1dkZGSDjgUAAABoaE5bWpObm6vw8HCFh4fr4sWLSk5OVnh4uJKTk219Vq9erQsXLmji\nxImV3u/t7a3Nmzdr2LBhCg0N1YwZMxQTE6Ps7OxKe9IDAAAA7sZpFfmoqChZLJYa+0ycOLHKJF6S\ngoKCtHXr1nqIDAAAAHB9Lv+wKwAAAIDKSOQBAAAAAyKRBwAAAAzI5befBADAiJ5KGe1w32u3zatO\n6oy1NxANAHdERR4AAAAwICryAADUA0cq6NdW7am4A6gtEnkAAAAYWlb2Bu3+6JDMZpMsFquywjYo\nemiMs8Oqdw4n8t9995127typQ4cO6bvvvpPJZFKrVq3UtWtX9evXT61atarPOAEAAIBKsrI3aPHy\nRbpneFdb2+LliyTJ7ZP5GhP5S5cuadWqVXr77be1c2fNT+L069dPEydO1K9//Ws1atSoToMEAAAA\nqpK++m2F9G9h1xbSv4VWrXnn5k3kf//73+ull17Sd999p+joaC1ZskS9evVSx44d1aJFC1mtVp05\nc0bHjh1TXl6e/v73v2vatGlKTk7W/Pnz9dhjjzXkOAAAQD2rzU48juC5ANQFi/Vyle2XLeUNHEnD\nqzaRf+mllzRr1ixNmjRJzZo1q7KPj4+PAgMDFRkZqaeeekpnz55VWlqaXnrpJRJ5AAAA1DuzyVNS\nRaV2T7NXwwfTwKpN5I8ePSpvb+9a3ax58+ZKSkrSk08+ecOBAQAA18JOPHBFE+ImavHyRXbLaw5v\n/15Jjz3rxKgaRrWJfG2T+Lp6LwAAAOCoq+vg5782QyaTSVarVQueSXH79fFSLXatKSkp0TfffKOe\nPXva2g4dOqTFixertLRUcXFx+tWvflUvQQIAAADViR4ao/UHutq9vhk4nMg/+eST+vbbb5WTkyNJ\n+v777zVo0CCdPXtWjRs31vvvv6+1a9fq/vvvr7dgAQAAcGNu1j3X3ZHDifzu3bv1xBNP2F5nZGTo\nzJkz+uyzzxQaGqohQ4bo9ddfJ5EHAABuw92S3pt5z3V3ZHa04+nTpxUYGGh7vW7dOg0YMEB33nmn\nvLy8FBcXp/3799dLkAAAAA3t2qT37thQ3TO8qxYvX6Ss7A3ODu1nq2nPdRiPw4l8y5Yt9c0330iS\nfvjhB+3cuVPR0dG26yaTSRcvXqz7CAEAAJzAHZPem3nPdXfk8NKa/v37a9myZQoNDdWGDRt08eJF\njRw50nb98OHD+sUvflEvQQIAADQ0d0x6b+Y9192RwxX5hQsXqlGjRnrwwQf1xz/+UUlJSerWrZsk\n6fLly/rLX/6iQYMGOfzBOTk5GjlypIKCgmQ2m7Vy5Ur7wMzmKr+u3aP+0qVLmj59uLine truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8a613c8>"
+       "<matplotlib.figure.Figure at 0x7fe66d8>"
       ]
      },
      "metadata": {},
@@ -584,9 +587,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA48AAAEtCAYAAACoIlXDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA48AAAEtCAYAAACoIlXDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x89d2908>"
+       "<matplotlib.figure.Figure at 0x7ff73c8>"
       ]
      },
      "metadata": {},
@@ -616,9 +619,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA48AAAEtCAYAAACoIlXDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA48AAAEtCAYAAACoIlXDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x889aeb8>"
+       "<matplotlib.figure.Figure at 0x7f35710>"
       ]
      },
      "metadata": {},
@@ -651,9 +654,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwkAAAEtCAYAAABDOSyFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xlc1WXax/HPQQU3XFBEFFRM04lQc8/EBQV1DEJFkRSk\nWZyZtplxxsoZi+lxdOrJZqpJZ54x9yZccoPSstHUJEstNXXMfcslEUQRc4Fznj9+eQw5Ehocbg7f\n9+vF69XvnIvfuY9X6Lm47+u+bQ6Hw4GIiIiIiMi3vMp7ACIiIiIiYhYVCSIiIiIiUoiKBBERERER\nKURFgoiIiIiIFKIiQUREREREClGRICIiIiIihahIEBERERGRQsq1SNiwYQMxMTEEBQXh5eXF3Llz\nCz2fnJyMl5dXoa8ePXoUijl48CBDhgyhUaNG1K1bl/j4eM6cOVPs686YMYPw8HD8/PyoX78+ERER\nZGRklPr7ExERERGpiMq1SMjLy6Ndu3a8+uqr1KhRA5vNVuh5m81GZGQkp0+fdn6tXLmy0PdHRUVh\ns9n48MMPycjI4OrVq0RHR1PcGXHr168nISGBDz/8kE8//ZQ2bdowYMAADhw4UGbvVURERESkorCZ\ncuKyr68v06ZNIykpyflYcnIyWVlZpKenu/ye1atXM2jQILKzs6lbty4AFy5coH79+qxevZp+/fqV\n+PUDAwOZOHEijz322A97IyIiIiIiFZzRPQk2m42NGzcSEBBAmzZtGDt2LJmZmc7nr1y5gs1mw8fH\nx/mYj48PXl5et7V86MqVK1y+fJn69euX6vhFRERERCoio4uEgQMHMn/+fNauXcvLL7/M5s2biYiI\n4OrVqwDcf//91K5dm/Hjx3Pp0iXy8vL4/e9/T0FBAadOnSrx60ycOBFfX19iYmLK6q2IiIiIiFQY\nVct7AMWJj493/ndoaCidOnWiefPmvPvuuwwZMoSGDRuyePFifvWrXzF9+nS8vLx4+OGH6dixI15e\nJat/Xn31Vf71r3+xZs0aateuXei58+fPl+r7ERERERFxp+tL8m+X0UXCzQIDAwkKCirUYBwZGcmB\nAwfIzs6matWq1KlTh8aNG5OQkPC993vllVd47rnneO+99+jcuXNZDl1EREREpMKoUEVCZmYmJ06c\nIDAwsMhzfn5+AKxZs4bMzMzvXTr017/+lT/96U+sXLmyyLaqIiIiIiKVWbkWCXl5eezfvx8Au93O\n0aNH2b59Ow0aNMDPz4+UlBTi4uJo3LgxR44cYcKECQQEBDBkyBDnPWbPnk3btm1p1KgRmzZt4je/\n+Q3jxo2jdevWzph+/frRrVs3pkyZAsBLL73ExIkTefPNN2nVqhWnT58GoGbNmtSpU8flWO90qkZ+\nuK1btwJotscAyoUZlAdzKBdmUB7MoDyYozSWzJfrFqjr1q0jIiLCGojN5jzbIDk5menTpxMbG8u2\nbdvIyckhMDCQiIgIJk2aRNOmTZ33mDBhAnPmzCE7O5uQkBB++ctf8pvf/KbQ64SEhNC3b19mzZrl\nvD527FiRsxSSk5OdMVD4D1hFgoiIiIhUBKXxGdaYcxJMpCJBRERERCqa0vgMa/QWqCIiIiIi4n4q\nEsR4W7duda5zlPKlXJhBeTCHcmEG5cEMyoNn0XKjYmi5kYiIiIhUNFpuJCIiIiIipU5FgoiIiIiI\nFKIiQYynNY7mUC7MoDyYQ7kwg/JgBuXBs6gnoRjqSRARERGRikY9CSIiIiIiUupUJIiIiIiISCEq\nEsR4WuNoDuXCDMqDOZQLMygPZlAePIt6EoqhngQRERERqWjUkyAiIiIiIqVORYKIiIiIiBSiIkGM\npzWO5lAuzKA8mEO5MIPyYAblwbOoJ6EY6kkQERERkYpGPQkiIiIiIlLqVCSIiIiIiEghKhLEeFrj\naA7lwgzKgzmUCzMoD2ZQHjyLehKKoZ4EEREREalo1JMgIiIiIiKlTkWCiIiIiIgUoiJBjKc1juZQ\nLsygPJhDuTCD8mAG5cGzqCehGOpJEBEREZGKpkL3JGzYsIGYmBiCgoLw8vJi7ty5hZ5PTk7Gy8ur\n0FePHj0KxRw8eJAhQ4bQqFEj6tatS3x8PGfOnPne116yZAn33HMP1atXJzQ0lOXLl5fqexMRERER\nqcjKrUjIy8ujXbt2vPrqq9SoUQObzVboeZvNRmRkJKdPn3Z+rVy5stD3R0VFYbPZ+PDDD8nIyODq\n1atER0dT3OTIpk2bGDlyJImJiezYsYNRo0YxfPhwNm/eXGbvVURERESkIjFiuZGvry/Tpk0jKSnJ\n+VhycjJZWVmkp6e7/J7Vq1czaNAgsrOzndMoFy5coH79+qxevZp+/fq5/L74+HhycnJ4//33nY9F\nRkbi7+/PW2+9VShWy43McH19Y+fOnct5JKJcmEF5MIdyYQblwQzKgzlK4zNs1dIaTGmz2Wxs3LiR\ngIAA6tWrR+/evZk8eTL+/v4AXLlyBZvNho+Pj/N7fHx88PLyIiMj45ZFwieffMKTTz5Z6LGoqCim\nTZtWdm9GfhD9ZWMO5cIMyoM5lAszKA/lz263E/btZzS73Y6Xl/bGqeiMzeDAgQOZP38+a9eu5eWX\nX2bz5s1ERERw9epVAO6//35q167N+PHjuXTpEnl5efz+97+noKCAU6dO3fK+p0+fJiAgoNBjAQEB\nnD59ukzfj4iIiIgnstvtXFm9mmrdu1Ote3eurF6N3W4v72HJD2RskRAfH8+DDz5IaGgoDz74IKtW\nrWLv3r28++67ADRs2JDFixezatUqfH19qVevHhcuXKBjx45lWr3evLWXrnWta13rWte61nVlvr52\n/Dg+jzyC1+nTeJ0+jc8jj3Dspl5Pk8ZbGa5Lg7HLjW4WGBhIUFAQBw4ccD4WGRnJgQMHyM7OpmrV\nqtSpU4fGjRuTkJBwy/s0bty4yKzB119/TePGjcts7PLDXP8fX9PJZti6datyUc7K4h8DuTP6+8kM\n+pkoZWlpNJ89G+65B0JCoGVLvHNzoUMHqFphPjrKD2Rs4/LNMjMzCQoKYubMmYwePdplzJo1a4iK\niuLLL7+kdevWLmNGjhzJuXPnCjUuR0VF4e/vz7///e9CsWpcFhERkUrlzBkIDoZvl3cXYrNB9eow\ndiy88orz4evLjXweeQSAK7Nn4xMVpb6EclShG5fz8vLYv38/YP3PdfToUbZv306DBg3w8/MjJSWF\nuLg4GjduzJEjR5gwYQIBAQEMGTLEeY/Zs2fTtm1bGjVqxKZNm/jNb37DuHHjChUI/fr1o1u3bkyZ\nMgWAX//61/Tq1YsXX3yRhx56iGXLlrFu3ToyMjLc+wcgIiIiYpr69aFBA3DV3+lwwDffwN//Dn/7\nm1U0AF5eXvhERXHtk08A8AkOVoHgAcotg1u2bKFjx4507NiRy5cvk5KSQseOHUlJSaFKlSrs2rWL\nhx56iDZt2pCcnMyPfvQjNm3aRK1atZz32LdvH0OHDuWee+7hz3/+MxMnTuSll14q9DqHDh0qtLzo\n/vvvZ8GCBcyZM4f27dvz5ptvsmjRIrp06eK29y4iIiJipH37YNQoaNTo1jGtWjkLhOu8vLzwad4c\nn+bNVSB4CCOWG5lKy43MoDW/5lAuzKA8mEO5MIPy8AMdPgwLFkBqKuzcWXxs+/aQkQHf+aXtdcqD\nOUrjM6yKhGKoSBARERGPdOoULFpkFQffLhMqonp1uHz5xnWPHvDee+Dr654xyh2r0D0JIiIiIuJG\n587BkiXWjMG6deDqLIPq1SE6Gvr1g0cfvfF4166wcqUKhEpERYKIiIiIp7p4EdLSrMLg/ffh2rWi\nMVWrwoABkJAAMTFWIbB5840iomNHawZBqyoqFRUJYjytcTSHcmEG5cEcyoUZlIebXLlifahPTYX0\ndLh0qWiMzQZ9+sDIkTBsmLWj0Xd16QLz5sGJE/DLX0K9et/7ssqDZ1FPQjHUkyAiIiIVQn4+fPih\nVRgsXQrf+QxTSNeu1ozBiBHQpIl7xyhuo54EERERkcrKbreajlNTrSbkM2dcx917r1UYxMfDXXe5\nd4xSYalIEBEREakoHA7YscMqDBYsgGPHXMe1bGktJUpIsIoEkdukIkGMpzWO5lAuzKA8mEO5MEOl\nyMO+fTfOMvjyS9cxgYHWbEFCgtVTcNOBZ2WtUuShElFPQjHUkyAiIiLl5vhxWLjQKgw+/9x1TP36\nEBdnFQa9ekGVKu4doxhJPQkiIiIiniQzExYvtmYNPvrIdUytWhAbay0niooCb2/3jlEqBRUJIiIi\nIuXp/HlYvtyaMfjPf6CgoGiMtzf8+MfWjMGDD0LNmu4fp1QqKhLEeFrjaA7lwgzKgzmUCzNUyDx8\n8w28845VGKxcaZ1tcLMqVayTjxMSrJmDEpxVUJ4qZB7kltSTUAz1JIiIiEipuXYNPvjAKgyWL7dO\nQ3blgQeswmD4cGjUyL1jFI+gngQRERERkxUUWL0Fqanw9tuQne067r77bpxl0KyZe8co4oKKBBER\nEZHS5HDAli1W8/HChXDypOu4u++2CoOEBGjTxr1jFPkeKhLEeFrjaA7lwgzKgzmUCzMYk4fdu28c\ncnbwoOuY4OAbh5x16OD2swzKkjF5kFKhnoRiqCdBREREinX48I1DznbudB3j7w8jRljFQY8e4OXl\n3jFKpaOeBBERERF3O3UKFi2yCoNPP3UdU6cODB1qzRhEREBVfeSSikX/x4qIiIh8n+xsWLrUKgzW\nrQO7vWhMjRoQHW0VBgMHQvXqbh+mSGlRkSDG0xpHcygXZlAezKFcmKHM8nDxIqSlWYXB++9bW5je\nrGpVGDDAKgxiYsDXt3THUIHo58GzqCehGOpJEBERqWSuXIFVq6w+g7Q069Czm9ls0Line truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwkAAAEtCAYAAABDOSyFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x816fa20>"
+       "<matplotlib.figure.Figure at 0x7fe9be0>"
       ]
      },
      "metadata": {},
@@ -680,9 +683,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvwAAAEtCAYAAAB00rSYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvwAAAEtCAYAAAB00rSYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x81789b0>"
+       "<matplotlib.figure.Figure at 0x7f8cb70>"
       ]
      },
      "metadata": {},
@@ -723,9 +726,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvwAAAEtCAYAAAB00rSYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8b38ba8>"
+       "<matplotlib.figure.Figure at 0x807d2b0>"
       ]
      },
      "metadata": {},
@@ -780,9 +783,9 @@
     },
     {
      "data": {
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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6sAAAEmCAYAAACEUwaqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9e992e8>"
+       "<matplotlib.figure.Figure at 0x840a470>"
       ]
      },
      "metadata": {},
@@ -844,9 +847,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6sAAAEmCAYAAACEUwaqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XdYFNfXwPHvLh0REbCLBYNgw9gr9oa9a6xoYozG3qMm\nion+jJpolCSm2CL22E3sEvurgiHGFuzRKMEGAtJ33j9GBlbBoCILeD7Pw6N35u7sWQZlz957z9Up\niqIghBBCCCGEEEJkI3pTByCEEEIIIYQQQjxNklUhhBBCCCGEENmOJKtCCCGEEEIIIbIdSVaFEEII\nIYQQQmQ7kqwKIYQQQgghhMh2zE0dQFaIiIgwdQhCCCGEEEK8tHz58pk6BCGynIysCiGEEEIIIYTI\ndiRZFUIIIYQQQgiR7bwR04BTkykUOVtgYCAA1atXN3Ek4lXJvcw95F7mHnIvcw+5l7mDLGUTbzoZ\nWRVCCCGEEEIIke1IsiqEEEIIIYQQItuRZFUIIYQQQgghRLYjyaoQQgghhBBCiGxHklUhhBBCCCGE\nENmOJKtCCCGEEEIIIbIdSVaFEEIIIYTIRhRFYfr06aYOQwiTk2RVCCGEEEKIbGT58uX4+vqaOgwh\nTE6SVSGEEEIIIbKR9evXmzoEIbIFSVaFEEIIIYTIRpKSkkwdghDZgiSrQgghhBBCZCNt27Y1dQhC\nZAvmpg5ACCGEEEIIkWLYsGFcvHjR1GEIYXImHVk9dOgQ7du3p3jx4uj1elasWGF0Xq/Xp/k1bNgw\nAB48eMDw4cMpV64ctra2lChRgqFDh/LgwQNTvBwhhBBCCCFemV6v55tvvjF1GEKYnEmT1ejoaDw9\nPfnqq6+wsbFBp9MZnQ8NDTX62r59OwA9evQA4M6dO9y+fZu5c+dy9uxZ/P39OXToEO+8806WvxYh\nhBBCCCGEEJnHpNOAvb298fb2BsDHx+eZ8wULFjRqb9myBXd3d7y8vACoUKECGzdu1M67uroyd+5c\n2rZtS1RUFHZ2dq8veCGEEEIIIYQQr02OKbAUFRXF2rVrGTRo0HP7RUREYGVlha2tbRZFJoQQQggh\nhBAis+WYZHX16tUkJCTQv3//dPuEh4fz8ccf8/7776PX55iXJoQQQgghhBDiKTpFURRTBwGQN29e\nvv76a/r165fm+Ro1alCmTBnWrl2b5vmoqCi8vb2xsLBg165dWFpaauciIiK0v1+6dClzAxdCCCGE\nECITbdu2jUaNGlGtWjXtWL58+UwYkRCmkSOGH4ODgwkKCkp3CnBUVBStW7dGr9ezY8cOo0RVCCGE\nEEKI7OzAgQPcunVLa+/du5egoCATRiRE9pAj9ln9/vvvcXV1pWnTps+ci4yMxNvbG51Ox86dO/9z\nrWr16tVfV5giCwQGBgJyH3MDuZe5h9zL3EPuZe4h9zJ727dvHw4ODtr9WbJkCebm5nTs2BGAKVOm\n4OjoaMoQhcgWTJqsRkdHa9NyDQYDN27cIDg4GCcnJ1xcXAB4/Pgxq1atYtKkSc88PjIykhYtWhAZ\nGcmWLVuIjIwkMjISACcnJywsLLLuxQghhBBCCJGGkydPEhERQfPmzQE4ffo0t27d0pLVvn37Eh4e\nrvVv27YtYLyUTYg3kUmnAZ86dYqqVatStWpVYmNjmTZtGlWrVmXatGlan3Xr1hETE8OAAQOeeXxQ\nUBAnTpzgwoULlC1blqJFi1K0aFGKFSvG8ePHs/KlCCGEEEIIAcDFixfZsGGD1r5+/ToLFy7U2h06\ndKB27dpau27durRu3TpLYxQiJzDpyGqjRo0wGAzP7TNgwIA0E9WMPl4IIYQQQojX6fbt2/zyyy9a\nfZXIyEhmzJhBt27dAGjSpAn37t3T+ru7u+Pu7m6SWIXISXJEgSUhhBBCCCGyi8jISObNm6e1zc3N\nGT9+PImJiQBUqVKF3r17k7zphrOzM0OHDjVJrELkZJKsCiGEEEII8RwGgwFfX18tGbWxseGzzz4j\nLCwMgIIFC+Lr60tsbCygJq+TJk1Cp9OZLGYhcgNJVoUQQgghhHjK/PnzuXv3LgB6vZ4NGzbw+++/\nA2oyumDBAqPlaCNHjsTOzs4ksQqRW0myKoQQQgghcpTDhw8zatQohg8fzu7duzPlmsuXL+fChQta\n+8CBAwQEBGjtTz/9FAcHB63t4+ND4cKFM+W5hRBpyxH7rAohhBBCCAGwbNky3n33XW09qJ+fH/Pm\nzWPs2LEvdJ2tW7fi5ORE/fr1AXWXibCwMMqVKwfA6NGjjZLTTp06ZdIrEEJklIysCiGEEEKIHCEq\nKooPP/wQRVH48MMPGT9+PAATJkzgzp07z33soUOH2Lp1q9a+cuUKq1at0toDBgygZs2aWrtJkyZU\nrVo1k1+BEOJFyMiqEEIIIUQuERUVxRdffMGRI0dwdnZm1qxZlC5d2tRhZZrr168TExNDqVKl8PPz\nA9TpukFBQYSEhFCkSBGt75kzZwgMDGTgwIEA3L9/n++//54OHToA0LFjR86ePav1l8RUiOxHklUh\nhBBCiFwgOjoaLy8vgoODtWO7d+/m2LFjeHh4mDCyzFO4cGF0Oh3Xr19n5cqV5MmThz///FM7P2/e\nPMaNGwdAUlISc+bM0ZLVRo0aER0drfV1dXXF1dU1a1+AEOKFyDRgIYQQQohcYPHixQQHB1O6dGk+\n/vhjqlevzsOHD/noo49MHVqmcXZ2ZuTIkQD069ePLl26EB8fT58+fahYsSIzZswgISEBgMqVKzN6\n9GhtbWv+/Pnp06ePyWIXQrw4SVaFEEIIIXKBS5cuATBs2DDat2/PsGHDjI7ndAaDgVGjRjF79mzm\nzZtHzZo1MTMzY+zYsSxduhQnJyf8/Py0ZFWv1zN48GDZ61SIHEySVSGEEEKIXKBEiRKAWi336NGj\nrFixAoCSJUuaMqxXMn36dEJDQwE1+Tx48CBBQUGMHTuWEydOsH79eiZNmoSFhQWgjrba2tqaMmQh\nRCaSZFUIIYQQIhcYMmQIrq6unD17llGjRhEQEIC1tTW+vr6mDi3D/Pz8+OOPP7T2H3/8wYEDB7T2\nnDlzKFasmNbu3Lkzzs7OWRpjVvll50FThyCEyUmyKoQQQgiRC+TPn5/jx4/zwQcfUKVKFZo3b87x\n48epXr26qUNL15o1a9i3b5/Wvnr1Kjt27NDaEydO5O2339bazZs3z9EjxRn1y86DjPTdbeowhDA5\nqQYshBBCCJFLFCxYkG+//ZbAwEAAo0QvO9izZw/379/nnXfeAeDu3bscOHCAZs2aAfDee+8ZVeyt\nXbu2SeI0tc+/3sNVs5nAI1OHIoRJyciqEEIIIYR4LQIDA1m4cKHWjo2NZenSpVq7c+fO9OrVS2uX\nL1+eGjVqZGmM2cWVWwqf+yvUGKhw+A8ZTxICZGRVCCGEEEJkkqtXr7J8+XJmzJgBgJWVFQsXLmTE\niBGAutdp6uq8xYsXp3jx4iaJNTu4dFNhwwH4OQCCjYo2J5oqJCGyFRlZFUIIIYQQLyU8PJyhQ4dq\nbUdHR+bPn09cXBwAFSpUYNasWdpep/b29rRr184ksWYXF28ofLZc4e3+Cu49Yer3TyeqYObYApt/\np5gmQCGyEUlWhRBCCCFEhhgMBnx8fLRk1N7eng0bNnDz5k0AHBwcWLVqlZac6vV6unfv/sbvdXr+\nmoLvUoVKfRTK94JPfoAzl437WFpAu3qw4mO4d6QB6xe1NE2wQmQjMg1YCCGEEEKka/To0YwdO5bi\nxYuj1+s5e/YsJ0+exMvLC71ez5o1a8ibN6/Wv3379iaMNntQFIWzV9XpvT8HwIXrafezsoRWtaBr\nY2hXH+zzpCT1bbwbEhERkTUBC5FNmWxk9dChQ7Rv3177jy954+pker0+za9hw4ZpfeLi4hg+fDgF\nChTAzs6ODh068M8//2T1SxFCCCGEyDX+97//adWEAW7dumW01+miRYtwc3PT2s2aNcPBwSFLY8yO\nFEXhj0sKU79XR08r94NPlz2bqFpbQueGsNoXwnbA5tk6erfUGSWqQgiVyUZWo6Oj8fT0pH///vTr\n1++Z6SGhoaFG7VOnTtGuXTt69OihHRs1ahTbtm1j7dq1ODo6MmbMGNq2bUtQUBB6vcxwFkIIIYT4\nL0uWLKFQoUK0bdsWgAcPHvDrr79q+7NOnToVe3t7rX+dOnVMEmd2pCgKv4ekjKBevpV2PxsraFNX\nHUFtXQfsbCUxFSIjTJasent74+3tDYCPj88z5wsWLGjU3rJlC+7u7nh5eQEQERHB0qVLWb58OU2b\nNgVg5cqVlCxZkn379tGiRYvX+wKEEEIIIXKg7du3ExYWxrvvvguoM9U2btyoJasffPCBtiYVoHLl\nyiaJM7tSFIWgi7AhADYGwNXbaffLYwNt60KXxuBdG/LYSIIqxIvKEWtWo6KiWLt2Lb6+vtqxoKAg\nEhISjJLS4sWLU65cOY4dOybJqhBCCCEEcPz4cQ4cOMCUKWp1WXNzc/z9/bVktUuXLtSqVUvrX6ZM\nGZPEmZ0pisLJ8+ro6cbf4PqdtPvZ2ahrT7s2hla1wcZKElQhXkWOSFZXr15NQkIC/fv3146FhoZi\nZmaGk5OTUd9ChQrx77//pnut1GswRM4l9zH3kHuZe8i9zD3kXuZsN2/eZN26dYwbN47AwEBu3bqF\nn58fLVq0QKfTYWdnR69evZ65z3LfjRkMcPZGHg4E5+fAHw6EPrRKs18e6yQaVAynydsPqe3xCCsL\ntRLyuT9fPYbUa4OFeBPliGT1hx9+oGPHjs8kpkIIIYQQb7pHjx4xe/ZsZs2aBah7nW7bto1hw4Zh\nbW1NqVKlmDp1qtbfxsaGKlWqmCrcbM1ggD+v52F/cH4O/JGfsHDLNPvZ2STSoGIETLine truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6sAAAEmCAYAAACEUwaqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XdYVMfXwPHvLh0REbCLBYOKBStWsDfsXWNFE2M09h41\nUUz0Z9REoyQxxRax95JYohL7qwIhxhbsJUqwgYD0ve8fKxdWwKAiC3g+z8Ojc+/s3bNclD07M2c0\niqIoCCGEEEIIIYQQOYjW2AEIIYQQQgghhBDPk2RVCCGEEEIIIUSOI8mqEEIIIYQQQogcR5JVIYQQ\nQgghhBA5jiSrQgghhBBCCCFyHFNjB5AdIiIijB2CEEIIIYQQr6xAgQLGDkGIbCcjq0IIIYQQQggh\nchxJVoUQQgghhBBC5DhvxTTg1GQKRe4WEBAAQO3atY0ciXhdci/zDrmXeYfcy7xD7mXeIEvZxNtO\nRlaFEEIIIYQQQuQ4kqwKIYQQQgghhMhxJFkVQgghhBBCCJHjSLIqhBBCCCGEECLHkWRVCCGEEEII\nIUSOI8mqEEIIIYQQQogcR5JVIYQQQgghchBFUZg5c6axwxDC6CRZFUIIIYQQIgdZuXIlPj4+xg5D\nCKOTZFUIIYQQQogcZOPGjcYOQYgcQZJVIYQQQgghcpCkpCRjhyBEjiDJqhBCCCGEEDlI+/btjR2C\nEDmCqbEDEEIIIYQQQqQYMWIEly5dMnYYQhidUUdWjxw5QseOHSlZsiRarZZVq1YZnNdqtel+jRgx\nAoBHjx4xcuRIXF1dsba2plSpUgwfPpxHjx4Z4+UIIYQQQgjx2rRaLd9++62xwxDC6IyarEZHR+Pm\n5sbXX3+NlZUVGo3G4HxoaKjB165duwDo1asXAPfu3ePu3bvMnz+fc+fO4efnx5EjR3j33Xez/bUI\nIYQQQgghhMg6Rp0G7OXlhZeXFwDe3t5pzhcuXNigvX37dipUqICnpycAlStXZsuWLep5Z2dn5s+f\nT/v27YmKisLGxubNBS+EEEIIIYQQ4o3JNQWWoqKiWL9+PUOGDHlhv4iICCwsLLC2ts6myIQQQggh\nhBBCZLVck6yuXbuWhIQEBg4cmGGf8PBwPvnkEz744AO02lzz0oQQQgghhBBCPEejKIpi7CAA8ufP\nzzfffMOAAQPSPe/u7k65cuVYv359uuejoqLw8vLCzMyMvXv3Ym5urp6LiIhQ/3758uWsDVwIIYQQ\nQogstHPnTpo0aUKtWrXUYwUKFDBiREIYR64YfgwODiYwMDDDKcBRUVG0bdsWrVbL7t27DRJVIYQQ\nQgghcrJDhw5x584dtf3bb78RGBhoxIiEyBlyxT6rP/zwA87OzjRv3jzNucjISLy8vNBoNOzZs+c/\n16rWrl37TYUpskFAQAAg9zEvkHuZd8i9zDvkXuYdci9ztgMHDmBnZ6fen2XLlmFqakrnzp0BmDZt\nGvb29sYMUYgcwajJanR0tDotV6fTcfPmTYKDg3FwcMDJyQmAp0+fsmbNGqZMmZLm8ZGRkbRq1YrI\nyEi2b99OZGQkkZGRADg4OGBmZpZ9L0YIIYQQQoh0nD59moiICFq2bAlAUFAQd+7cUZPV/v37Ex4e\nrvZv3749YLiUTYi3kVGnAZ85c4aaNWtSs2ZNYmNjmTFjBjVr1mTGjBlqnw0bNhATE8OgQYPSPD4w\nMJBTp05x8eJFypcvT/HixSlevDglSpTg5MmT2flShBBCCCGEAODSpUts2rRJbd+4cYPFixer7U6d\nOlGvXj213aBBA9q2bZutMQqRGxh1ZLVJkybodLoX9hk0aFC6iWpmHy+EEEIIIcSbdPfuXX755Re1\nvkpkZCSzZs2iR48eADRr1owHDx6o/StUqECFChWMEqsQuUmuKLAkhBBCCCFEThEZGcmCBQvUtqmp\nKRMnTiQxMRGAGjVq0LdvX5I33XB0dGT48OFGiVWI3EySVSGEEEIIIV5Ap9Ph4+OjJqNWVlZ8/vnn\nhIWFAVC4cGF8fHyIjY0F9MnrlClT0Gg0RotZiLxAklUhhBBCCCGes3DhQu7fvw+AVqtl06ZN/PHH\nH4A+GV20aJHBcrTRo0djY2NjlFiFyKskWRVCCCGEELnK0aNHGTNmDCNHjmTfvn1Zcs2VK1dy8eJF\ntX3o0CH8/f3V9meffYadnZ3a9vb2pmjRolny3EKI9OWKfVaFEEIIIYQAWLFiBe+99566HtTX15cF\nCxYwfvz4l7rOjh07cHBwwMPDA9DvMhEWFoarqysAY8eONUhOu3TpkkWvQAiRWTKyKoQQQgghcoWo\nqCg++ugjFEXho48+YuLEiQBMmjSJe/fuvfCxR44cYceOHWr76tWrrFmzRm0PGjSIOnXqqO1mzZpR\ns2bNLH4FQoiXISOrQgghhBB5RFRUFF9++SXHjh3D0dGROXPmULZsWWOHlWVu3LhBTEwMZcqUwdfX\nF9BP1w0MDCQkJIRixYqpfc+ePUtAQACDBw8G4OHDh/zwww906tQJgM6dO3Pu3Dm1vySmQuQ8kqwK\nIYQQQuQB0dHReHp6EhwcrB7bt28fJ06coGLFikaMLOsULVoUjUbDjRs3WL16Nfny5eOvv/5Szy9Y\nsIAJEyYAkJSUxLx589RktUmTJkRHR6t9nZ2dcXZ2zt4XIIR4KTINWAghhBAiD1i6dCnBwcGULVuW\nTz75hNq1a/P48WM+/vhjY4eWZRwdHRk9ejQAAwYMoFu3bsTHx9OvXz+qVKnCrFmzSEhIAKBatWqM\nHTtWXdtasGBB+vXrZ7TYhRAvT5JVIYQQQog84PLlywCMGDGCjh07MmLECIPjuZ1Op2PMmDHMnTuX\nBQsWUKdOHUxMTBg/fjzLly/HwcEBX19fNVnVarUMHTpU9joVIheTZFUIIYQQIg8oVaoUoK+We/z4\ncVatWgVA6dKljRnWa5k5cyahoaGAPvk8fPgwgYGBjB8/nlOnTrFx40amTJmCmZkZoB9ttba2NmbI\nQogsJMmqEEIIIUQeMGzYMJydnTl37hxjxozB398fS0tLfHx8jB1apvn6+vLnn3+q7T///JNDhw6p\n7Xnz5lGiRAm13bVrVxwdHbM1xuzyy57Dxg5BCKOTZFUIIYQQIg8oWLAgJ0+e5MMPP6RGjRq0bNmS\nkydPUrt2bWOHlqF169Zx4MABtX3t2jV2796ttidPnkz16tXVdsuWLXP1SHFm/bLnMKN99hk7DCGM\nTqoBCyGEEELkEYULF+a7774jICAAwCDRywn279/Pw4cPeffddwG4f/8+hw4dokWLFgC8//77BhV7\n69WrZ5Q4je2Lb/ZzzWQ28MTYoQhhVDKyKoQQQggh3oiAgAAWL16stmNjY1m+fLna7tq1K3369FHb\nlSpVwt3dPVtjzCmu3lH4wk/BfbDC0T9lPEkIkJFVIYQQQgiRRa5du8bKlSuZNWsWABYWFixevJhR\no0YB+r1OU1fnLVmyJCVLljRKrDnB5dsKmw7BZn8INijanGiskITIUWRkVQghhBBCvJLw8HCGDx+u\ntu3t7Vm4cCFxcXEAVK5cmTlz5qh7ndra2tKhQwejxJpTXLqp8PlKheoDFSr0huk/PJ+ogol9K6z+\nnWacAIXIQSRZFUIIIYQQmaLT6fD29laTUVtbWzZt2sTt27cBsLOzY82aNWpyqtVq6dmz51u/1+mF\n6wo+yxWq9lOo1Ac+/RHOXjHsY24GHRrCqk/gwbFGbFzS2jjBCpGDyDRgIYQQQgiRobFjxzJ+/HhK\nliyJVqvl3LlznD59Gk9PT7RaLevWrSN//vxq/44dOxox2pxBURTOXdNP793sDxdvpN/Pwhza1IXu\nTaGDB9jmS0nq23k1JiIiInsCFiKHMtrI6pEjR+jYsaP6H1/yxtXJtFptul8jRoxQ+8TFxTFy5EgK\nFSqEjY0NnTp14p9//snulyKEEEIIkWf873//U6sJA9y5c8dgr9MlS5bg4uKitlu0aIGdnV22xpgT\nKYrCn5cVpv+gHz2tNgA+W5E2UbU0h66NYa0PhO2GbXM19G2tMUhUhRB6RhtZjY6Oxs3NjYEDBzJg\nwIA000NCQ0MN2mfOnKFDhw706tVLPTZmzBh27tzJ+vXrsbe3Z9y4cbRv357AwEC0WpnhLIQQQgjx\nX5YtW0aRIkVo3749AI8ePeLXX39V92edPn06tra2av/69esbJc6cSFEU/ghJGUG9cif9flYW0K6B\nfgS1bX2wsZbEVIjMMFqy6uXlhZeXFwDe3t5pzhcuXNigvX37dipUqICnpycAERERLF++nJUrV9K8\neXMAVq9eTenSpTlw4ACtWrV6sy9ACCGEECIX2rVrF2FhYbz33nuAfqbali1b1GT1ww8/VNekAlSr\nVs0oceZUiqIQeAk2+cMWf7h2N/1++aygfQPo1hS86kE+K0lQhXhZuWLNalRUFOvXr8fHx0c9FhgY\nSEJCgkFSWrJkSVxdXTlx4oQkq0IIIYQQwMmTJzl06BDTpumry5qamuLn56cmq926daNu3bpq/3Ll\nyhklzpxMURROX9CPnm75HW7cS7+fjZV+7Wn3ptCmHlhZSIIqxOvIFcnq2rVrSUhIYODAgeqx0NBQ\nTExMcHBwMOhbpEgR/v333wyvlXoNhsi95D7mHXIv8w65l3mH3Mvc7fbt22zYsIEJEyYQEBDAnTt3\n8PX1pVWrVmg0GmxsbOjTp0+a+yz33ZBOB+du5uNQcEEO/WlH6GOLdPvls0yiUZVwmlV/TL2KT7Aw\n01dCPv/X68eQem2wEG+jXJGs/vjjj3Tu3DlNYiqEEEII8bZ78uQJc+fOZc6cOYB+r9OdO3cyYsQI\nLC0tKVOmDNOnT1f7W1lZUaNGDWOFm6PpdPDXjXwcDC7IoT8LEhZunm4/G6tEGlWJoLine truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8af1780>"
+       "<matplotlib.figure.Figure at 0x7280b70>"
       ]
      },
      "metadata": {},
@@ -886,9 +889,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6sAAAEmCAYAAACEUwaqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6sAAAEmCAYAAACEUwaqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8ab9128>"
+       "<matplotlib.figure.Figure at 0x840a7f0>"
       ]
      },
      "metadata": {},
@@ -979,9 +982,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgAAAAFoCAYAAAAhN0NQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XlcE3f+P/DX5CJcCeESEORSQQW0KOKtWNTWE126tdtu\nq631aO2xtrXXtlp7bOv23G7V1bZadf21q1VEt62KAmI9EBUVFVEQBZT7Jgkhyfz+8MusMQEBCZPj\n/Xw8eDyYTyYz7wkfMu/5zOfzGYZlWRaEEEIIsSsCvgMghBBCSM+jBIAQQgixQ5QAEEIIIXbIrAnA\nvHnzIBB0fBcrV66EQCDAjRs3urS/tLQ0CAQC/PDDD116PyGEEGIv2j07t55QP/vssy5tnGEYMAxj\nUJaUlIT33nuvw+t3db+EEEIIaVuHLs+7ekLdsGEDVCqVQVl7CcBf//pXqFQq9OnTp0v7I4QQQkjH\niMy6cZHpzbeVUAiFQgiFQnOGRAghhBB0sg9AYWEhBAIB3nvvPezduxcxMTFwdHSEn58fli9fDp1O\nZ7D+3X0AJkyYgM2bN4NlWQgEAu5n8+bNAEz3Abh58yZeeeUVDBkyBO7u7nB0dMSgQYOwevVq6PX6\n+zl2QgghxG51qQXgl19+wZo1a7BkyRIsWLAASUlJ+PTTT6FQKPDmm28arHvn1f5f//pXvP/++8jI\nyMDWrVu58lGjRrW5r3PnzmHXrl2YM2cOQkND0dLSgl9//RVvvPEGCgoKsG7duq4cAiGEEGLXupQA\nXLx4ERcuXODu1S9atAiRkZH4+uuvjRKAOycajI+Px9atW5GRkYE//elPHdrXhAkTUFBQYFD24osv\n4sknn8S3336LlStXwsfHpyuHQQghhNitLg0DTEhIMOqoN2HCBJSWlkKpVHZLYK2kUin3u0ajQXV1\nNSorKzF58mTo9XqcOnWqW/dHCCGE2IMutQCEhIQYlXl4eAAAqqqq4OTkdH9R3UGr1eLjjz/G5s2b\nkZ+fj7sfXVBTU9Nt+yKEEELsRZcSgPZ66nf3s4WWLVuGf/7zn5g7dy7eeecdeHt7QywW49SpU3j9\n9depIyAhhBDSBWYdBmhKZyf72bJlC8aPH49t27YZlOfl5XV3aIQQQojdMPuzAO4+2bu4uIBl2Q43\n3YtEIqOr/KamJnzxxRfdFiMhhBBib8yeANx9S2DkyJEAgOeeew5btmzBjz/+iMLCwjbfn5iYiIyM\nDMydOxcbNmzABx98gKioKMjlcnOGTQghhNi0brsFYKpp31TZY489hjNnzuDHH3/E9u3bwbIsNm7c\niKCgIJPrf/7553B1dcV//vMf7N69G3369MGiRYswbNgwxMfHm4yDEEIIIe1j2O7utUcIIYQQi2f2\nWwCEEEIIsTyUABBCCCF2iBIAQgghxA5RAkAIIYTYIUoACCGEEDtECQAhhBBihygBIIQQQuwQJQCE\nEEKIHbKZBCAoKAhxcXEGZWlpaRAIBPjhhx86tI3Ors+3nJwciEQiHDx40Czb3717NxwcHHD16lWz\nbJ8QQgh/OpUAKJVKfPnllxg7diw8PDwgkUjg4+ODadOm4YcffoBOpzNXnPfU1lMG7y7Pzs7GypUr\ncf369U5txxItW7YMY8eOxYMPPmiW7c+aNQuRkZF4/fXXzbJ9Qggh/OnwswCuXr2KadOm4cqVK5g0\naRLeeusteHp6ory8HAcOHMD8+fNx8eJFfPLJJ+aMt02mZjQeP348VCoVRKL/HWZ2djZWrVqFiRMn\nIjAw8J7rW6pjx44hJSUFu3fvNut+XnrpJTz11FO4ePEiBg4caNZ9EUII6TkdOtOpVCpMnz4dhYWF\n2LlzJxISEgxef+2115CVlYWsrCyzBNlVDMNAIpGYfM1UwtDe+pZmzZo18PLywtSpU826nzlz5mDJ\nkiVYt24d/vGPf5h1X4QQQnpOh24BfPvtt8jLy8Mrr7xidPJvNWzYMCxevJhbrqysxPPPP4+AgAA4\nODigT58+WLp0Kaqrqw3et2nTJggEAqSmpuLTTz9FaGgopFIpwsLCsHnzZqP9FBUV4Y9//CPkcjnk\ncjlmzpyJ/Px8kzG13tNv3c7KlSvx9NNPAwDi4uIgEAggEAgwf/58g/Xv7gNgjmNRq9VYuXIlwsLC\n4OzsDIVCgaioKCxfvtzksdxJq9UiKSkJ8fHxEAqF91z/fjg7O2Ps2LHYsWOHWfdDCCGkZ3WoBWDH\njh1gGAYLFy7s0Ebr6uowatQo5Ofn45lnnkF0dDROnz6NtWvX4tChQ8jMzISLi4vBe9566y2o1Wos\nWbIEEokEa9euxbx589C3b1+MGjUKAFBbW4tx48ahuLgYS5YswcCBA5GWloaJEydCpVLdM64//OEP\nKC0txfr16/H2229jwIABAIDQ0FCD9e7sA2CuY3n++eexceNGPPXUUxg1ahS0Wi3y8vKQmpp6z+M4\ndeoUmpqaMHz48Huu2x1GjBiBffv24fLlywgLC+uRfRJCCDEztgPc3d1ZNze3jqzKsizLvvXWWyzD\nMOzatWsNyr/55huWYRj2nXfe4co2btzIMgzDRkdHsy0tLVx5SUkJ6+DgwD722GNc2ZtvvskyDMNu\n2rTJYLsvv/wyyzAMGxcXZ1CemprKMgzD/vDDD0b7S09PN4rb1PrmOhaFQsFOmzbNKIaO+P7771mG\nYdg9e/YYvfbhhx+ykZGRLMMwrEwmY7ds2cK+8MILrEAgYPv27cs++eSTnd7fli1bWIZh2J07d3Yp\nXkIIIZanQ7cA6uvr4erq2uGkYteuXfD29jZqMVi0aBG8vLywa9cuo/c899xzBp3v/Pz80L9/f4Mh\naElJSfDx8cGTTz5p8F5z9lI317G4ubkhJycHFy5c6HRMFRUVAAB3d3ej19566y2cOHECISEhUKlU\nGDBgAB588EEMGTIEly5d6tIQRw8PDwBAeXl5p99LCCHEMnUoAZDJZGhoaOjwRq9du4awsDAIBIab\nFwqF6NevH65du2b0npCQEKMyd3d3VFVVccsFBQXo16+f0TA9Hx8fyOXyDsfXGeY6li+//BI1NTWI\njIxE37598eyzzyI5Odlk58S7tR5/W+s6Ojpi/fr10Gq1mDdvHl566SVs2bKly6MbWvdjLcMjCSGE\n3FuHEoCIiAjU1dWZPNl1l7Y6s3XkhGhpOnIsM2fORGFhIbZs2YKJEyfi4MGDSEhIwIQJE9DS0tLu\n9r28vADAqBPinSZOnIinn34aFy5cwIQJE4yG8KWkpOCdd97B+vXr8de//rXd/bXup3W/hBBCrF+H\nEoDExEQAt0cDdERISAhyc3ONJgZq7ehm6gq5o9vNy8uDXq83KL916xbq6uo6tI3OXsWa61gAQKFQ\n4PHHH8f69etRUFCA5cuXIyMj455j+yMjIwEAV65caXe9kSNHAgD+85//GNx+UCqVeOmll/Dee+9h\n4cKFqK+vR1JSUpvbaX1vREREh46LEEKI5etQArBgwQKEhYXh008/RXJyssl1Tp06hbVr1wIAZs+e\njYqKCqOEYcOGDaisrMTs2bO7FGxCQgLKysqMhtR1ZvKh1h77dzbHt8ccx6LX61FbW2tUPmTIEABA\nTU1Nu+8fMmQIZDIZjh071uY6xcXFeO+997B69Wqo1WqDPgzp6ekICQnhbmuMGjWq3aTj+PHj8PHx\nQb9+/dqNixBCiPXo0E1hR0dH7N27F9OmTUNCQgImT56M+Ph4eHh4oKKiAqmpqdi/fz83hn358uXY\nvn07nn/+eZw+fRpDhgzBmTNn8P333yM8PLxDY91b3dlsvnz5cmzbtg3PPvssTp06xQ0DPH78ODw9\nPTt0u2D48OEQCAT48MMPUV1dDWdnZ4SEhLQ5pM4cx1JfXw9fX1/MmjULQ4YMgbe3N65du4a1a9fC\n3d0dM2bMaHc7QqEQc+bMQVJSEjQajdHkRSzLYv78+XjnnXfw7LPP4siRI0hOTsa3336LBQsW4MaN\nG3Bzc+PWl8vluHTpksl9NTY2IiMjAwsWLOjwcRJCCLECnRkyoFQq2S+++IIdM2YMq1AoWLFYzHp7\ne7MPPfQQu3nzZlan03HrVlRUsM899xzr7+/PisViNiAggF26dClbVVVlsM2NGzeyAoHA5LC8CRMm\nsMHBwQZlN27cYBMTE1mZTMbKZDJ25syZbH5+PhsUFGRyGKBAIDAY1seyLPvDDz+wAwcOZCUSCcsw\nDDt//vx21+/uY9FoNOybb77JDh8+nPXw8GAdHBzY4OBg9plnnmGvXr1q8rO/W2ZmJsswDPvzzz8b\nlC9btowdOHAgKxAI2EceeYRlWZZ94IEHWIFAwMpkMnbChAnsqlWr2AULFnDvSUlJYQcOHGhyP5s2\nbWIZhmEvXLjQobgIIYRYB4ZlrbCXHQEAPPzww2hqasLhw4c79b5vvvkGZ86c4W5r7N27F6tXrza5\nnejoaISEhNBMgIQQYmNs5nHA9uizzz7jHgrUGf369UNlZSW3XFVVBX9/f6P1kpKSeH3AEyGEEPOh\nFgA7pFarERERgQsXLsDBwQELFizAQw89xI32IIQQYvsoAbBTO3fuxMmTJxEYGIjCwkJ8/PHHfIdE\nCCGkB1ECQAghhNgh6gNACCGE2CFKAAghhBA7RAkAIYQQYocoASCEEELsECUAPezuBxkRQgghfKAE\noIdotVr8/vvv+PXXX63yEceEEEJsS4ceBkTuT3l5OVJTU7lHFl+4cIEerUsIIYRX1ALQAzQaDXfy\nB4ATJ06YfBwwIYQQ0lMoAegB/v7+GDRoELes0+mQmppK/QEIIYTwhhKAHhIbGwu5XM4tV1RUIDs7\nm8eICCGE2DNKAHqISCRCXFwcGIbhyk6dOmXwVD5CCCGkp1AC0IO8vb0xZMgQbpllWLine truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgAAAAFoCAYAAAAhN0NQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8907898>"
+       "<matplotlib.figure.Figure at 0x7285400>"
       ]
      },
      "metadata": {},
@@ -1388,9 +1391,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5kAAAEPCAYAAADI9gBRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5kAAAEPCAYAAADI9gBRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9e58908>"
+       "<matplotlib.figure.Figure at 0x93ed160>"
       ]
      },
      "metadata": {},
@@ -1482,9 +1485,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5EAAAEPCAYAAADbIUClAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5EAAAEPCAYAAADbIUClAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9e68400>"
+       "<matplotlib.figure.Figure at 0x940bd30>"
       ]
      },
      "metadata": {},
@@ -1519,9 +1522,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuYAAAEWCAYAAAAq41LXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuYAAAEWCAYAAAAq41LXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsvXecHcWVNvzcCQqjMEhCEUnkDBJhvPsZ7772On2f39fL\nsvbafteL4+7ihAFjrw0GG2PLxoEkEQQIEAghEAIhRBISKKGskWYkjbI0mtFo8owm57nd3x/3dnd1\ndVV1VXffIKke/7Dmdlc4XeHUqVOnzomZpmlCQ0NDQ0NDQ0NDQyOjyMk0ARoaGhoaGhoaGhoaWjDX\n0NDQ0NDQ0NDQyApowVxDQ0NDQ0NDQ0MjC6AFcw0NDQ0NDQ0NDY0sgBbMNTQ0NDQ0NDQ0NLIAWjDX\n0NDQ0NDQ0NDQyAJowVxDQ0NDQ0NDQ0MjC5AywfyBBx5ATk4OfvrTn6aqCg0NDQ0NDQ0NDY3TBikR\nzLds2YJ58+ZhxowZiMViqahCQ0NDQ0NDQ0ND47RC5IJ5W1sbbr75ZsyfPx9jxoyJungNDQ0NDQ0N\nDQ2N0xKRC+a33HILvva1r+HTn/40TNOMungNDQ0NDQ0NDQ2N0xJ5URY2b948lJeXY9GiRQCgzVg0\nNDQ0NDQ0NDQ0JBGZYH7w4EHcc8892LBhA3JzcwEApml6tOZtbW1RVamhoaGhoaGhoaGRERQWFkZe\nZsyMyN7khRdewPe//31bKAeAeDyOWCyG3NxcdHV1IT8/XwvmGhoaGhoaGhoapzyyWjBva2tDdXW1\n/ds0TXzve9/DJZdcgl//+te44oor7HQaGhoaGhoaGhoapzJSIZhHZspSWFjoIbCgoABjxoyxhXJW\nHo1TF8XFxQCAoqKiDFOiERa6L08f6L48faD78vSB7svTB6lWMKc08mcsFtMXQDU0NDQ0NDQ0NDQk\nEKlXFhpr1qxJZfEaGhoaGhoaGhoapw1SqjHX0NDQ0NDQ0NDQ0JCDFsw1NDQ0NDQ0NDQ0sgBaMNfQ\n0NDQ0NDQ0NDIAmjBXENDQ0NDQ0NDQyMLoAVzDQ0NDQ0NDQ0NjSyAFsw1NDQ0NDQ0NDQ0sgBaMNfQ\n0NDQ0NDQ0NDIAmjBXENDQyMEapuPZ5oEDQ0NDY3TBFow19DQ0AgIw4jjgYW3ZZoMDQ0NDY3TBFow\n19DQ0AgIM9MEaGhoaGicVtCCuYaGhoaGhoaGhkYWQAvmGhoaGhoaGhoakeOpZb/Hm+ufzzQZpxS0\nYK6hoaEREqapjVo0NDQ0aOyr3InSw5syTcYpBS2Ya2hoaASFFsg1NDQ0NCKEFsw1NDQ0QsJUvAba\nN9ALw4iniBoNDQ2NLEIslmkKTilowVxDQ0MjIFQFcguvfvgE9leWREyNhoaGRhZCnywqIVLB/Ikn\nnsDMmTNRWFiIwsJC3HDDDXjvvfeirEJDQ0Mj+6C48PQP9qF/sD9FxGio4lDVblTUHco0GRoaGhrR\nCubTpk3DX//6V5SUlGDHjh347Gc/i5tuugl79uyJshoNDQ2NrEBQRZBJ/L9G5vH40t/i6eWzMk2G\nhsbpCW3KooS8KAu78cYbXb9nzZqFuXPnYsuWLbj66qujrEpDQ0MjCxBMxDZNQ3tyyTbo/tDQSA30\n3FJCpII5iXg8jiVLlqCrqws33HBDqqrR0NDQOPVgaheL2QbdGxoaGtmAyAXzPXv24JOf/CT6+vow\ncuRIvPnmm7jyyiuZaYuLi6OuXiMD0P14+kD3pRoG4wMAgB3FxcjJyZXO19rWiqPlR2F2DE8Vabov\nFTE4OJC1bZatdGmo40zsy77+/tPquy+++OKUlh+5V5bLLrsMu3fvxrZt2/CjH/0I3/72t7F3796o\nq9HQ0NA4hWHq491sg+4ODQ2NLEDkGvP8/HxccMEFAIBrr70W27dvxyOPPIJnn33Wk7aoqCjq6jXS\nCGsHrPvx1Ifuy2DoH+jDoi3Adddfh7zcfOl820+8h/POPw9Fl0ff3qp92TfQiyF5QxE7gy9oLdgI\n5ObmZN341/Py9MGZ2pcLNgJDhww5rb67ra0tpeWn3I95PB5Hf792C6ahoaFhIZsuf/7Pk/8XJYc3\nZpoMDQ0NDQ1ErDG/66678OUvfxlTp05FR0cHFi1ahHXr1mlf5hoaGqclrABDqjK2CTNrBHMAaOlo\nzDQJGhoaGhqIWDCvr6/HzTffjLq6OhQWFmLmzJlYsWIFvvCFL0RZjYaGhsapDTN41NBUIJs2CZmC\nbgGNINi6bzXau1rwhU98NdOkaJwmiFQwnz9/fpTFaWhoaGQ3bIFWTazLNo25RnZtlDROHSzfuAAd\n3a1aMBdAzy01pNzGXENDQ+N0ReDlxjRhmkaUpITCqXjx86UPHsWmspXRFag3ShoaGlkALZhraGho\nhISqRsjQGqTQ2H5gLTaVrco0GRoaGj6I4dTb+GcSWjDX0NDQCIjA5iimCSOLNObarEbbmGtopAra\nlEUNWjDX0NDQCAtlryxaGI4EUbah7g+NINDj5ozAzkMb0NZ5Mi11acFcQ0Mjcrz0waNYVbw002Sk\nAcE15tmkoz0VbcyjhtbqaWho8PDC+w/iwx3pWdO0YK6RERimgdtm35RpMjRShO0H1mJzlBfzshyq\nQp32yqKhoaGhwYIWzDUyA9MKzKKFk9MVZ4IGMug3mqZYMN9XsROGEQ9KViB6NDQ01KFnzpmDdPFJ\nLZgz0N3bqReqFMPx/qzb+bTFmdS1ivzCT2P+1Fu/x5HqfWGp0lDBmTReNTQ0AkAL5hnDXU/fjH0V\nOzJNxmkNy4ez3gCdvjgjNl1BP9EETPh5ZTkD2i8kohxjZ8R41YgcetykHlUNR7Fm5/JMk5G2e75a\nMOegs6ct0ySc1rAGeDYFWdGIGIpczDANdPV2BK6u/uSJwHmDwlqUVfl1QmMePT0awaEFLA2N7MSq\n7W/gzY+fzzQZaeMRWjDnQnspSC3cNuZ7jxXjxRUPZ5IgjQxjc9kq3P30twLlrT95An986daIKUoh\nJCJ/6tOkNEM3d0bQ0FKDvoHeTJMRHHqeclFZdwhABFMrW8QxbWOeWWSj+7DbZt+Etq70+NFMNSyh\nw9qBbtu/BjsOrs8kSRoS2HFwPVbvfEsqrSoLC+MjdiDeHzhvKAS8xOx3+VNDDtmo5b7r6W/5Cprl\nNQfSRE32Y9aCH2P5hgWZJkMjBXho8S8zTUKkOOMufxpGHK+teTrTZGQ9OrvbM01CJDARTKDRSB0G\n4wO+ad78eD6WfTxfrkDdt1yYyf+lEu1dLegf7EtpHacTouiPnYc2oLu3A109Yj796JK7zui+Wb7x\nJcx7+0/2757+rgxSEw7ZzuWqGysyTUJohXcsS1TmZ5wpS29/Dzbsfj/TZNjIRo15AtnOBiSh3SVm\nHRZt+QuqGsrt3/H4IE62NwYuL53azEwxbpPxl1y+1GvM7332e1iy5pmU1gEAW/d9lFbXji5kGftY\nvWOZdNpsETYygeIDa7GnfJvzwEzcMalImj5oRIe/LLoD7V0tKSnbkLwjlmXTVAq3zb4JNU0V1NMz\nTDDPPmSeaXb1tKOmqdL1zDhNBFnDFswTEzt7N0JnFjq6W+2/V+98C7+b/9+Byzo9RmqKYKbn4nOq\nFmQSL696DI1tdSmvJ+VIE2+VFWZOZ9AtbZoG9h3bgYfTZPqwp3wbHlh4WyRlnQorVyrG3N5jxbhj\nzlciLzeb0NHtdgJySnpleeCBB/CJT3wChYWFmDBhAm688Ubs3btXKm+22Qpmw2R75aMn8OeXb6ee\nZlc7BQetMQ/f4k+99Qe8teGF0OWcySCFRRUPKY2ttXh740t0YVGR5YtM8Q/6roR0PokcIo36xj0f\n4PCJPZ7nhmngZFe9qx4NOYRtqf2VJTjecMS/HiPpKvYM7ht6U2oCiKfx1OXg8VLUNh+PpKwztRer\nG4+lra5MKe5yc/Ncv09JU5Z169bh1ltvxebNm7F69Wrk5eXh85//PFpaUq+1iRrZoMHtH/ReaDtd\nTD8cN3PRfc++ih3YeWhjZOWFQW9/j0v7HCT/qx89ESFFcgg6vooPrMOq4jfcZZ0RS1aYyJ/BtViL\nV8/FWx+/6Hm+5+g2vFM6j6wocB0qyBS3jHSMhWyr4gPriF/8FjG0GZ/n27PFbe7ij+big22vZZqM\nyJGKsZZeTzoZEsxzct0PTsXLnytWrMB3vvMdXHHFFbjqqqvw0ksvobGxEZs2bfLNeybb2z2+9Ld4\nfe087wvGIMhWZl7VUK5Em5mqxSlL2ueZt/+Ie+Z9N3D+6sZj2FS2KjqCJOF75MlpXqaAlB1dkR4o\nOzI3w7cPQ3kwSHmnSd/m6Mzh39v2r5HgW/z3thCaJbwqE/AI5jBZwznt2Fj2ATbsXuGbrm+g17GR\nz8J+7O7t9JhhRI2+gZ6Ulp8NyM2hNebpQUptzNvb22EYBsaMGZPKalKCWCx95veHqnZjz9Gtnuen\nksbxb6/cifIahRDilI15VDCypM2a2+r9E2Uhnn3nAfT1R8Nww4zfo4rh6DN2+dMKlBXIlCXc2Gd9\nsVcTmSaNeaakqgi/T7YPF66cjf4Q2kJr85uK+0KGaeDR1+6OvNyo4TFlMU2kd3PHr8ujJWVg677V\nLq8yqYJhxPHIa3cp53v4tV9h1oIfR0ODaTD5SG9E60Q2gxbMT0mNOY3bb78d1157LT75yU/6pk2H\nELpw5WzMfv2eUGXUNldFJriQkBco5dupp69L+tJHZ097aBs/lfzWV1gTPiqWnC1HonFjMNMkBEZP\nf3c0BYVgYrNf/7WSKdCptIm14Cc0+36ThDDc1FqrQlIkOFS1BwMMM7zTCayekR2DDo+KfszG43GU\n1+4XpjGMeKgIu1HA8+VZpHX2CGNMkP6YUkd730AfjtWq+7xv7WxGT180Lih/OfebeLine truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8a9deb8>"
+       "<matplotlib.figure.Figure at 0x837e0b8>"
       ]
      },
      "metadata": {},
@@ -1573,9 +1576,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5kAAAEPCAYAAADI9gBRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5kAAAEPCAYAAADI9gBRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8a184e0>"
+       "<matplotlib.figure.Figure at 0x93f23c8>"
       ]
      },
      "metadata": {},
@@ -1636,9 +1639,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAAEPCAYAAAC6OWLnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAAEPCAYAAAC6OWLnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9fd8dd8>"
+       "<matplotlib.figure.Figure at 0x942a438>"
       ]
      },
      "metadata": {},
@@ -1701,9 +1704,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5oAAAEPCAYAAAAjwbtSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5oAAAEPCAYAAAAjwbtSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa03ad68>"
+       "<matplotlib.figure.Figure at 0x95a2048>"
       ]
      },
      "metadata": {},
@@ -1779,9 +1782,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5kAAAGNCAYAAACbjrWCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5kAAAGNCAYAAACbjrWCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa0179b0>"
+       "<matplotlib.figure.Figure at 0x9578400>"
       ]
      },
      "metadata": {},
@@ -1821,9 +1824,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5EAAAFSCAYAAABrMVuMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5EAAAFSCAYAAABrMVuMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa033d30>"
+       "<matplotlib.figure.Figure at 0x95920b8>"
       ]
      },
      "metadata": {},
@@ -1866,9 +1869,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5AAAAFLCAYAAACgKmPhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5AAAAFLCAYAAACgKmPhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa091f28>"
+       "<matplotlib.figure.Figure at 0x835def0>"
       ]
      },
      "metadata": {},
@@ -1913,9 +1916,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5MAAAFLCAYAAABLHdjiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5MAAAFLCAYAAABLHdjiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8178828>"
+       "<matplotlib.figure.Figure at 0x957c128>"
       ]
      },
      "metadata": {},
@@ -1943,7 +1946,7 @@
    "source": [
     "## Interactive Example\n",
     "\n",
-    "For those of you running this in IPython Notebook I've written an interactive version of the filter so you can see the effect of changing $\\dot{x}$, $g$ and $h$ in real time. As you adjust the sliders for $\\dot{x}$, $g$ and $h$ the date will be refiltered and the results plotted for you.\n",
+    "For those of you running this in Jupyter Notebook I've written an interactive version of the filter so you can see the effect of changing $\\dot{x}$, $g$ and $h$ in real time. As you adjust the sliders for $\\dot{x}$, $g$ and $h$ the date will be refiltered and the results plotted for you.\n",
     "\n",
     "If you really want to test yourself, read the next paragraph and try to predict the results before you move the sliders. \n",
     "\n",
@@ -1961,18 +1964,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvMAAAEWCAYAAADrZBh7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8188470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "None"
+       "<matplotlib.figure.Figure at 0x72f8908>"
       ]
      },
      "metadata": {},
@@ -2016,9 +2010,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAACXCAYAAADte/19AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAACXCAYAAADte/19AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa066940>"
+       "<matplotlib.figure.Figure at 0x95a2c50>"
       ]
      },
      "metadata": {},
@@ -2052,9 +2046,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAACdCAYAAABM4N4bAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAACdCAYAAABM4N4bAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8b297b8>"
+       "<matplotlib.figure.Figure at 0x9410c18>"
       ]
      },
      "metadata": {},
@@ -2118,9 +2112,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwMAAAE6CAYAAABKyI5vAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwMAAAE6CAYAAABKyI5vAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8b3a128>"
+       "<matplotlib.figure.Figure at 0x80c0438>"
       ]
      },
      "metadata": {},
@@ -2169,9 +2163,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa06e2e8>"
+       "<matplotlib.figure.Figure at 0x80ae208>"
       ]
      },
      "metadata": {},
@@ -2200,9 +2194,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5EAAAEjCAYAAACrT4XoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5EAAAEjCAYAAACrT4XoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9fff828>"
+       "<matplotlib.figure.Figure at 0x836fe48>"
       ]
      },
      "metadata": {},
@@ -2233,9 +2227,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8cbf828>"
+       "<matplotlib.figure.Figure at 0x8252390>"
       ]
      },
      "metadata": {},
@@ -2283,9 +2277,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa0ace10>"
+       "<matplotlib.figure.Figure at 0x8252438>"
       ]
      },
      "metadata": {},
@@ -2314,9 +2308,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA54AAAEjCAYAAABaRN5lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x898a828>"
+       "<matplotlib.figure.Figure at 0x8122940>"
       ]
      },
      "metadata": {},
@@ -2577,7 +2571,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.5.0"
   }
  },
  "nbformat": 4,

02-Discrete-Bayes.ipynb

@@ -832,7 +832,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "And, if you are viewing this on the web or in IPython Notebook, here is an animation of that output.\n",
+    "And, if you are viewing this on the web or in Jupyter Notebook, here is an animation of that output.\n",
     "<img src=\"animations/02_no_info.gif\">"
    ]
   },
@@ -1211,7 +1211,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Finally, for those viewing this in a Notebook or on the web, here is an animation of that algorithm.\n",
+    "Finally, for those viewing this in a Jupyter Notebook or on the web, here is an animation of that algorithm.\n",
     "<img src=\"animations/02_simulate.gif\">"
    ]
   },
@@ -1827,7 +1827,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.5.0"
   }
  },
  "nbformat": 4,

04-One-Dimensional-Kalman-Filters.ipynb

@@ -1326,7 +1326,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This chart is very similar to one we already saw in the *g-h Filter* chapter. At each predict step we take our existing estimate and update it based on our process model. We then make a measurement. We know neither the measurement or prediction is perfect, so we choose a value in between the two. This is scaled so that the new estimate is closer to the one we trust more. That scaling depends on the variance of the measurement vs the variance of the process model. We then step time forward one step, and what was the new estimate is considered to be the prior estimate, and the process repeats. "
+    "This chart is very similar to one we already saw in the *g-h Filter* chapter. At each predict step we take our existing estimate and update it based on our process model. We then make a measurement. The difference between the measurement and the prediction is called the *residual*. We know neither the measurement or prediction is perfect, so we choose a value in between the two. This is scaled so that the new estimate is closer to the one we trust more. That scaling depends on the variance of the measurement vs the variance of the process model. We then step time forward one step, and what was the new estimate is considered to be the prior estimate, and the process repeats. "
    ]
   },
   {

05-Multivariate-Gaussians.ipynb

@@ -683,7 +683,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "For those of you viewing this online or in IPython Notebook on your computer, here is an animation.\n",
+    "For those of you viewing this online or in Juptyer Notebook on your computer, here is an animation.\n",
     "<img src='animations/multivariate_ellipse.gif'>\n",
     "\n",
     "(source: http://git.io/vqxLS)"