{
 "metadata": {
  "name": "",
  "signature": "sha256:294c484342e32ceca58f2c7bb93ee9f5a0c3d347fe840425870ddfb1a33ce140"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[Table of Contents](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/table_of_contents.ipynb)"
     ]
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Multivariate Kalman Filters"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#format the book\n",
      "%matplotlib inline\n",
      "from __future__ import division, print_function\n",
      "import matplotlib.pyplot as plt\n",
      "import book_format\n",
      "book_format.load_style()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<style>\n",
        "@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",
        "\n",
        "    div.cell{\n",
        "        width: 850px;\n",
        "        margin-left: 0% !important;\n",
        "        margin-right: auto;\n",
        "    }\n",
        "    div.text_cell code {\n",
        "        background: transparent;\n",
        "        color: #000000;\n",
        "        font-weight: 600;\n",
        "        font-size: 11pt;\n",
        "        font-style: bold;\n",
        "        font-family:  'Source Code Pro', Consolas, monocco, monospace;\n",
        "   }\n",
        "    h1 {\n",
        "        font-family: 'Open sans',verdana,arial,sans-serif;\n",
        "\t}\n",
        "\t\n",
        "    div.input_area {\n",
        "        background: #F6F6F9;\n",
        "        border: 1px solid #586e75;\n",
        "    }\n",
        "\n",
        "    .text_cell_render h1 {\n",
        "        font-weight: 200;\n",
        "        font-size: 30pt;\n",
        "        line-height: 100%;\n",
        "        color:#c76c0c;\n",
        "        margin-bottom: 0.5em;\n",
        "        margin-top: 1em;\n",
        "        display: block;\n",
        "        white-space: wrap;\n",
        "    } \n",
        "    h2 {\n",
        "        font-family: 'Open sans',verdana,arial,sans-serif;\n",
        "    }\n",
        "    .text_cell_render h2 {\n",
        "        font-weight: 200;\n",
        "        font-size: 20pt;\n",
        "        font-style: italic;\n",
        "        line-height: 100%;\n",
        "        color:#c76c0c;\n",
        "        margin-bottom: 0.5em;\n",
        "        margin-top: 1.5em;\n",
        "        display: block;\n",
        "        white-space: nowrap;\n",
        "    } \n",
        "    h3 {\n",
        "        font-family: 'Open sans',verdana,arial,sans-serif;\n",
        "    }\n",
        "    .text_cell_render h3 {\n",
        "        font-weight: 300;\n",
        "        font-size: 18pt;\n",
        "        line-height: 100%;\n",
        "        color:#d77c0c;\n",
        "        margin-bottom: 0.5em;\n",
        "        margin-top: 2em;\n",
        "        display: block;\n",
        "        white-space: nowrap;\n",
        "    }\n",
        "    h4 {\n",
        "        font-family: 'Open sans',verdana,arial,sans-serif;\n",
        "    }\n",
        "    .text_cell_render h4 {\n",
        "        font-weight: 300;\n",
        "        font-size: 16pt;\n",
        "        color:#d77c0c;\n",
        "        margin-bottom: 0.5em;\n",
        "        margin-top: 0.5em;\n",
        "        display: block;\n",
        "        white-space: nowrap;\n",
        "    }\n",
        "    h5 {\n",
        "        font-family: 'Open sans',verdana,arial,sans-serif;\n",
        "    }\n",
        "    .text_cell_render h5 {\n",
        "        font-weight: 300;\n",
        "        font-style: normal;\n",
        "        color: #1d3b84;\n",
        "        font-size: 16pt;\n",
        "        margin-bottom: 0em;\n",
        "        margin-top: 1.5em;\n",
        "        display: block;\n",
        "        white-space: nowrap;\n",
        "    }\n",
        "    div.text_cell_render{\n",
        "        font-family: 'Arimo',verdana,arial,sans-serif;\n",
        "        line-height: 135%;\n",
        "        font-size: 125%;\n",
        "        width:750px;\n",
        "        margin-left:auto;\n",
        "        margin-right:auto;\n",
        "        text-align:justify;\n",
        "        text-justify:inter-word;\n",
        "    }\n",
        "    div.output_subarea.output_text.output_pyout {\n",
        "        overflow-x: auto;\n",
        "        overflow-y: scroll;\n",
        "        max-height: 50000px;\n",
        "    }\n",
        "    div.output_subarea.output_stream.output_stdout.output_text {\n",
        "        overflow-x: auto;\n",
        "        overflow-y: scroll;\n",
        "        max-height: 50000px;\n",
        "    }\n",
        "    code{\n",
        "      font-size: 70%;\n",
        "    }\n",
        "    .rendered_html code{\n",
        "    background-color: transparent;\n",
        "    }\n",
        "    ul{\n",
        "        margin: 2em;\n",
        "    }\n",
        "    ul li{\n",
        "        padding-left: 0.5em; \n",
        "        margin-bottom: 0.5em; \n",
        "        margin-top: 0.5em; \n",
        "    }\n",
        "    ul li li{\n",
        "        padding-left: 0.2em; \n",
        "        margin-bottom: 0.2em; \n",
        "        margin-top: 0.2em; \n",
        "    }\n",
        "    ol{\n",
        "        margin: 2em;\n",
        "    }\n",
        "    ol li{\n",
        "        padding-left: 0.5em; \n",
        "        margin-bottom: 0.5em; \n",
        "        margin-top: 0.5em; \n",
        "    }\n",
        "    ul li{\n",
        "        padding-left: 0.5em; \n",
        "        margin-bottom: 0.5em; \n",
        "        margin-top: 0.2em; \n",
        "    }\n",
        "    a:link{\n",
        "       font-weight: bold;\n",
        "       color:#447adb;\n",
        "    }\n",
        "    a:visited{\n",
        "       font-weight: bold;\n",
        "       color: #1d3b84;\n",
        "    }\n",
        "    a:hover{\n",
        "       font-weight: bold;\n",
        "       color: #1d3b84;\n",
        "    }\n",
        "    a:focus{\n",
        "       font-weight: bold;\n",
        "       color:#447adb;\n",
        "    }\n",
        "    a:active{\n",
        "       font-weight: bold;\n",
        "       color:#447adb;\n",
        "    }\n",
        "    .rendered_html :link {\n",
        "       text-decoration: underline; \n",
        "    }\n",
        "    .rendered_html :hover {\n",
        "       text-decoration: none; \n",
        "    }\n",
        "    .rendered_html :visited {\n",
        "      text-decoration: none;\n",
        "    }\n",
        "    .rendered_html :focus {\n",
        "      text-decoration: none;\n",
        "    }\n",
        "    .rendered_html :active {\n",
        "      text-decoration: none;\n",
        "    }\n",
        "    .warning{\n",
        "        color: rgb( 240, 20, 20 )\n",
        "    } \n",
        "    hr {\n",
        "      color: #f3f3f3;\n",
        "      background-color: #f3f3f3;\n",
        "      height: 1px;\n",
        "    }\n",
        "    blockquote{\n",
        "      display:block;\n",
        "      background: #fcfcfc;\n",
        "      border-left: 5px solid #c76c0c;\n",
        "      font-family: 'Open sans',verdana,arial,sans-serif;\n",
        "      width:680px;\n",
        "      padding: 10px 10px 10px 10px;\n",
        "      text-align:justify;\n",
        "      text-justify:inter-word;\n",
        "      }\n",
        "      blockquote p {\n",
        "        margin-bottom: 0;\n",
        "        line-height: 125%;\n",
        "        font-size: 100%;\n",
        "      }\n",
        "</style>\n",
        "<script>\n",
        "    MathJax.Hub.Config({\n",
        "                        TeX: {\n",
        "                           extensions: [\"AMSmath.js\"]\n",
        "                           },\n",
        "                tex2jax: {\n",
        "                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
        "                    displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ]\n",
        "                },\n",
        "                displayAlign: 'center', // Change this to 'center' to center equations.\n",
        "                \"HTML-CSS\": {\n",
        "                    styles: {'.MathJax_Display': {\"margin\": 4}}\n",
        "                }\n",
        "        });\n",
        "</script>\n"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 1,
       "text": [
        "<IPython.core.display.HTML at 0x7f860c7ed780>"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Introduction"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The techniques in the last chapter are very powerful, but they only work in one dimension. The gaussians represent a mean and variance that are scalars - real numbers. They provide no way to represent multidimensional data, such as the position of a dog in a field. You may retort that you could use two Kalman filters for that case, one tracks the x coordinate and the other tracks the y coordinate. That does work in some cases, but put that thought aside, because soon you will see some enormous benefits to implementing the multidimensional case.\n",
      "\n",
      "In this chapter I am purposefully glossing over many aspects of the mathematics behind Kalman filters. If you are familiar with the topic you will read statements that you disagree with because they contain simplifications that do not necessarily hold in more general cases. If you are not familiar with the topic, expect some paragraphs to be somewhat 'magical' - it will not be clear how I derived a certain result. I prefer that you develop an intuition for how these filters work through several worked examples. If I started by presenting a rigorous mathematical formulation you would be left scratching your head about what all these terms mean and how you might apply them to your problem. In later chapters I will provide a more rigorous mathematical foundation, and at that time I will have to either correct approximations that I made in this chapter or provide additional information that I did not cover here. \n",
      "\n",
      "To make this possible we will restrict ourselves to a subset of problems which we can describe with Newton's equations of motion. In the literature these filters are called \n",
      "*discretized continuous-time kinematic filters*. In the next chapter we will develop the math required for solving any kind of dynamic system. \n",
      "\n",
      "\n",
      "In this chapter we are dealing with a simpler form that we can discuss in terms of Newton's equations of motion: given a constant velocity v we can compute distance exactly with:\n",
      "\n",
      "$$ x = vt + x_0$$\n",
      "\n",
      "If we instead assume constant acceleration we get\n",
      "\n",
      "$$ x = \\frac{1}{2}at^2 + v_0 t + x_0$$\n",
      "\n",
      "And if we assume constant jerk we get\n",
      "\n",
      "$$ x = \\frac{1}{6}jt^3 +  \\frac{1}{2}a_0 t^2 + v_0 t + x_0$$\n",
      "\n",
      "As a reminder, we can generate these equations using basic calculus. Given a constant velocity v we can compute the distance travelled over time with the equation\n",
      "\n",
      "$$\\begin{aligned} v &= \\frac{dx}{dt}\\\\\n",
      "dx &= v\\, dt \\\\\n",
      "\\int_{x_0}^x\\, dx &= \\int_0^t v\\, dt\\\\\n",
      "x - x_0 &= vt - 0\\\\\n",
      "x &= vt + x_0\\end{aligned}$$"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Multivariate Normal Distributions"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "What might a *multivariate normal distribution* look like? In this context, multivariate just means multiple variables. Our goal is to be able to represent a normal distribution across multiple dimensions. Consider the 2 dimensional case. Let's say we believe that $x = 2$ and $y = 17$ This might be the *x* and *y* coordinates for the position of our dog, or the temperare and wind speed at our weather station, it doesn't really matter. We can see that for $N$ dimensions, we need $N$ means, like so:\n",
      "\n",
      "$$\n",
      "\\mu = \\begin{bmatrix}{\\mu}_1\\\\{\\mu}_2\\\\ \\vdots \\\\{\\mu}_n\\end{bmatrix}\n",
      "$$\n",
      "\n",
      "Therefore for this example we would have\n",
      "\n",
      "$$\n",
      "\\mu = \\begin{bmatrix}2\\\\17\\end{bmatrix} \n",
      "$$\n",
      "\n",
      "The next step is representing our variances. At first blush we might think we would also need N variances for N dimensions. We might want to say the variance for x is 10 and the variance for y is 4, like so. \n",
      "\n",
      "$$\\sigma^2 = \\begin{bmatrix}10\\\\4\\end{bmatrix}$$ \n",
      "\n",
      "This is incorrect because it does not consider the more general case. For example, suppose we were tracking house prices vs total $m^2$ of the floor plan. These numbers are *correlated*. It is not an exact correlation, but in general houses in the same neighborhood are more expensive if they have a larger floor plan. We want a way to express not only what we think the variance is in the price and the $m^2$, but also the degree to which they are correlated. It turns out that we use the following matrix to denote *covariances* with multivariate normal distributions. You might guess, correctly, that *covariance* is short for *correlated variances*."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "$$\n",
      "\\Sigma = \\begin{bmatrix}\n",
      "  \\sigma_1^2 & \\sigma_{12} & \\cdots & \\sigma_{1n} \\\\\n",
      "  \\sigma_{21} &\\sigma_2^2 & \\cdots & \\sigma_{2n} \\\\\n",
      "  \\vdots  & \\vdots  & \\ddots & \\vdots  \\\\\n",
      "  \\sigma_{n1} & \\sigma_{n2} & \\cdots & \\sigma_n^2\n",
      " \\end{bmatrix}\n",
      "$$\n",
      "\n",
      "If you haven't seen this before it is probably a bit confusing at the moment. Rather than explain the math right now, we will take our usual tactic of building our intuition first with various physical models. At this point, note that the diagonal contains the variance for each state variable, and that all off-diagonal elements (covariances) are represent how much the $i$th (row) and $j$th (column) state variable are linearly correlated to each other. In other words, it is a measure for how much they change together. No correlation will have a covariance of 0. So, for example, if the variance for x is 10, the variance for y is 4, and there is no linear correlation between x and y, then we would say\n",
      "\n",
      "$$\\Sigma = \\begin{bmatrix}10&0\\\\0&4\\end{bmatrix}$$\n",
      "\n",
      "If there was a small amount of correlation between x and y we might have\n",
      "\n",
      "$$\\Sigma = \\begin{bmatrix}10&1.2\\\\1.2&4\\end{bmatrix}$$\n",
      "\n",
      "where 1.2 is the covariance between x and y. Note that this is always symmetric - the covariance between x and y is always equal to the covariance between y and x. That is, $\\sigma_{xy}=\\sigma_{yx}$ for any x and y."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now, without explanation, here is the full equation for the multivariate normal distribution in $n$ dimensions.\n",
      "\n",
      "$$\\mathcal{N}(\\mu,\\,\\Sigma) = (2\\pi)^{-\\frac{n}{2}}|\\Sigma|^{-\\frac{1}{2}}\\, e^{ -\\frac{1}{2}(\\mathbf{x}-\\mu)^\\mathsf{T}\\Sigma^{-1}(\\mathbf{x}-\\mu) }$$\n",
      "\n",
      "I urge you to not try to remember this function. We will program it in a Python function and then call it when we need to compute a specific value. However, if you look at it briefly you will note that it looks quite similar to the *univariate normal distribution*  except it uses matrices instead of scalar values, and the root of $\\pi$ is scaled by $n$. Here is the *univariate* equation for reference:\n",
      "\n",
      "$$ \n",
      "f(x, \\mu, \\sigma) = \\frac{1}{\\sigma\\sqrt{2\\pi}} e^{{-\\frac{1}{2}}{(x-\\mu)^2}/\\sigma^2 }\n",
      "$$\n",
      "\n",
      "If you are reasonably well-versed in linear algebra this equation should look quite manageable; if not, don't worry! Let's just plot it and see what it looks like."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import mkf_internal\n",
      "import numpy as np\n",
      "mkf_internal.plot_3d_covariance((2, 17), np.array([[10., 0], [0, 4.]]))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAv4AAAF0CAYAAABbpj2aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkUgkEolEUgWQhb9EIpFIJBKJRFIF+H+GwbtsVNbuiwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e84c5ef0>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here we have plotted a two dimensional multivariate Gaussian with a mean of $\\mu=[\\begin{smallmatrix}2\\\\17\\end{smallmatrix}]$ and a covariance of $\\Sigma=[\\begin{smallmatrix}10&0\\\\0&4\\end{smallmatrix}]$. The three dimensional shape shows the probability of for any value of (x,y) in the z-axis. I have projected just the variance for x and y onto the walls of the chart - you can see that they take on the normal Gaussian bell curve shape. You can also see that, as we might hope, that the curve for x is wider than the curve for y, which is explained by $\\sigma_x^2=10$ and $\\sigma_y^2=4$. Also, the highest point of the curve is centered over (2,17), the means for x and y. I hope this demystifies the equation for you. Any multivariate Gaussian will create this sort of shape. If we think of this as a the Gaussian for our dog's position in a two dimensional field, the z-value at each point of (x,y) is the probability density for the dog being at that position. So, he has the highest probability of being near (2,17), a modest probability of being near (5,14), and a very low probability of being near (10,10).\n",
      "\n",
      "We will discuss the mathematical description of covariances in the Kalman Filter math chapter. For this chapter we just need to understand the following.\n",
      "\n",
      "1. The diagonal of the matrix contains the variance for each variable. \n",
      "\n",
      "2. Each off-diagonal element contains $\\sigma_{ij}$ - the covariance between *i* and *j*. This tells us how much linear correlation there is between the two variables. 0 means no correlation, and as the number gets higher the correlation gets greater.\n",
      "\n",
      "3. $\\sigma_{ij} = \\sigma_{ji}$\n",
      "\n",
      "4. The covariance between x and itself is just the variance of x: $\\sigma_{xx} = \\sigma_x^2$.\n",
      "\n",
      "5. This chart only shows a 2 dimensional Gaussian, but the equation works for any number of dimensions >= 1. It's kind of hard to show a chart for the higher dimensions."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I have programmed the multivariate Gaussian equation and saved it in the file `stats.py` with the function name `multivariate_gaussian`. I am not showing the code here because I have taken advantage of the linear algebra solving apparatus of numpy to efficiently compute a solution - the code does not correspond to the equation in a one to one manner. If you wish to view the code, I urge you to either load it in an editor, or load it into this worksheet by putting `%load -s multivariate_gaussian stats.py` in the next cell and executing it with ctrl-enter. \n",
      "\n",
      "However, please note that the Kalman filter equations incorporate this computation automatically; you will not be using this function very often in this book, so I would not spend a lot of time mastering this function unless it interests you."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      ">As of version 0.14 scipy.stats has implemented the multivariate normal equation with the function `multivariate_normal()`. It implements a 'frozen' form where you set the mean and covariance once, and then calculate the probability for any number of values for x over any arbitrary number of calls. This is much more efficient then recomputing everything in each call. So, if you have version 0.14 or later you may want to substitute my function for the built in version. Use `scipy.version.version` to get the version number. I deliberately named my function `multivariate_gaussian()` to ensure it is never confused with the built in version. I will say that for a single call, where the frozen variables do not matter, mine consistently runs faster as measured by the `timeit` function.\n",
      "\n",
      "> The <a href=\"http://docs.scipy.org/doc/scipy/reference/tutorial/stats.html\">tutorial</a>[1] for the `scipy.stats` module explains 'freezing' distributions and other very useful features. As of this date, it includes an example of using the multivariate_normal function, which does work a bit differently from my function."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from stats import gaussian, multivariate_gaussian"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's use it to compute a few values just to make sure we know how to call and use the function, and then move on to more interesting things.\n",
      "\n",
      "First, let's find the probability density for our dog being at (2.5, 7.3) if we believe he is at (2, 7) with a variance of 8 for $x$ and a variance of 4 for $y$.\n",
      "\n",
      "Start by setting $x$ to (2.5, 7.3):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = [2.5, 7.3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Next, we set the mean of our belief:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mu = [2.0, 7.0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Finally, we have to define our covariance matrix. In the problem statement we did not mention any correlation between $x$ and $y$, and we will assume there is none. This makes sense; a dog can choose to independently wander in either the $x$ direction or $y$ direction without affecting the other. If there is no correlation between the values you just fill in the diagonal of the covariance matrix with the variances. I will use the seemingly arbitrary name $\\textbf{P}$ for the covariance matrix. The Kalman filters use the name $\\textbf{P}$ for this matrix, so I will introduce the terminology now to avoid explaining why I change the name later. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P = [[8.,  0.], \n",
      "     [0., 4.]]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now just call the function"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print('{:.4}'.format(multivariate_gaussian(x, mu, P)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0.02739\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "> Note that the function can accept lists, np.array, or np.matrix as arguments, or even scalars. Type `multivariate_gaussian?` in a cell and press ctrl-enter to get the help for this function. \n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "These numbers are not easy to interpret. Let's plot this in 3D, with the $z$ (up) coordinate being the probability distribution."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import mkf_internal\n",
      "mkf_internal.plot_3d_covariance(mu, P)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAv4AAAF0CAYAAABbpj2aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWtUr2gAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f860c7f2588>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The result is clearly a 3D bell shaped curve. We can see that the gaussian is centered around (2,7), and that the probability density quickly drops away in all directions. On the sides of the plot I have drawn the Gaussians for $x$ in greens and for $y$ in orange."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's look at this in a slightly different way. Instead of plotting a surface showing the probability distribution I will just generate 1,000 points with the distribution of $[\\begin{smallmatrix}8&0\\\\0&4\\end{smallmatrix}]$."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mkf_internal.plot_3d_sampled_covariance(mu, P)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAv4AAAF0CAYAAABbpj2aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nn5BbjQD5ZAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f860c7f2390>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can think of the sampled points as being possible locations for our dog given those particular mean and covariances. The contours on the side show the variance in the points for $x$ and $y$ only."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "As beautiful as this is, it is perhaps a bit hard to get useful information. For example, it is not easy to tell if $x$ and $y$ both have the same variance or not. So for most of the rest of this book we will display multidimensional Gaussian using contour plots. I will use some helper functions in `stats.py` to plot them. If you are interested in linear algebra go ahead and look at the code used to produce these contours, otherwise feel free to ignore it. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import stats\n",
      "\n",
      "P = np.array([[2, 0], [0, 2]])\n",
      "plt.subplot(131)\n",
      "stats.plot_covariance_ellipse((2, 7), cov=P, facecolor='g', alpha=0.2, \n",
      "                              title='|2 0|\\n|0 2|', axis_equal=False)\n",
      "plt.ylim((4, 10))\n",
      "plt.gca().set_aspect('equal', adjustable='box')\n",
      "\n",
      "plt.subplot(132)\n",
      "P = np.array([[2, 0], [0, 9]])\n",
      "plt.ylim((4, 10))\n",
      "plt.gca().set_aspect('equal', adjustable='box')\n",
      "stats.plot_covariance_ellipse((2, 7), P,  facecolor='g', alpha=0.2, \n",
      "                              axis_equal=False, title='|2 0|\\n|0 9|')\n",
      "\n",
      "plt.subplot(133)\n",
      "P = np.array([[2, 1.2], [1.2, 2]])\n",
      "plt.ylim((4, 10))\n",
      "plt.gca().set_aspect('equal', adjustable='box')\n",
      "stats.plot_covariance_ellipse((2, 7), P,  facecolor='g', alpha=0.2, \n",
      "                              axis_equal=False, \n",
      "                              title='|2 1.2|\\n|1.2 2|')\n",
      "\n",
      "plt.tight_layout()\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAA1AAAAGwCAYAAACnwISaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7d1a0f0>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And for those of you viewing this online or in IPython Notebook on your computer, here is an animation.\n",
      "<img src='animations/multivariate_ellipse.gif'>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "From a mathematical perspective these display the values that the multivariate gaussian takes for a specific standard deviation. This is like taking a horizontal slice out of the 3D plot. By default it displays one standard deviation, but you can use the `variance` parameter to control what is displayed. For example, `variance=3**2` would display the 3rd standard deviation, and `variance=[1,4,9]` would display the 1st, 2nd, and 3rd standard deviations as in the chart below. This takes 3 different horizontal slices of the multivariate Gaussian chart and displays them in 2D."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P = np.array([[2, 0], [0, 9]])\n",
      "\n",
      "stats.plot_covariance_ellipse((2, 7), P,  facecolor='g', alpha=0.2, \n",
      "                              variance=[1, 2**2, 3**2],\n",
      "                              axis_equal=True, title='|2 0|\\n|0 9|')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxMAAAGxCAYAAAAZEeucAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7cf4278>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Thinking about the physical interpretation of these plots clarifies their meaning. The first plot uses the mean and covariance matrices of\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{\\mu} &= \\begin{bmatrix}2\\\\7\\end{bmatrix} \\\\\n",
      "\\Sigma &= \\begin{bmatrix}2&0\\\\0&2\\end{bmatrix}\n",
      "\\end{aligned}\n",
      "$$ \n",
      "\n",
      "Let this be our current belief about the position of our dog in a field. In other words, we believe that he is positioned at (2,7) with a variance of $\\sigma^2=2$ for both x and y. The contour plot shows where we believe the dog is located with the '+' in the center of the ellipse. The ellipse shows the boundary for the $1\\sigma$ probability, where $1\\sigma$ is one *standard deviation*. In other words, for this Gaussian 68% of the data will fall within this ellipse. Recall from the Gaussians chapter the the 68-95-99.7 rule - 68% of all values will fall within 1 standard deviation ($1\\sigma$), 95% within $2\\sigma$, and 99.7% within $3\\sigma$. The dog could be at (356443,58483), but the chances for values that far away from the mean are infitestimally small.\n",
      "\n",
      "An equivalent way of thinking about this is the circle/ellipse shows us the amount of error in our belief. A tiny circle would indicate that we have a very small error, and a very large circle indicates a lot of error in our belief. We will use this throughout the rest of the book to display and evaluate the accuracy of our filters at any point in time. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The second plot uses the mean and covariance matrices of\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mu &=\\begin{bmatrix}2\\\\7\\end{bmatrix} \\\\\n",
      "\\Sigma &= \\begin{bmatrix}2&0\\\\0&9\\end{bmatrix}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "This time we use a different variance for $x$ (2) vs $y$ (9). The result is an ellipse. When we look at it we can immediately tell that we have a lot more uncertainty in the $y$ value vs the $x$ value. Our belief that the value is (2,7) is the same in both cases, but errors are different. In this case the standard deviation in $x$ is $\\sigma_x = \\sqrt{2}=1.414$ and the standard deviation for $y$ is $\\sigma_y = \\sqrt{9}=3$. This sort of thing happens naturally as we track objects in the world - one sensor has a better view of the object, or is closer, than another sensor, and so we end up with different error rates in the different axis."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The third plot uses the mean and covariance matrices of:\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mu &=\\begin{bmatrix}2\\\\7\\end{bmatrix} \\\\\n",
      "\\Sigma &= \\begin{bmatrix}2&1.2\\\\1.2&2\\end{bmatrix}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "This is the first contour that has values in the off-diagonal elements of $cov$, and this is the first contour plot with a slanted ellipse. This is not a coincidence. The two facts are telling use the same thing. A slanted ellipse tells us that the $x$ and $y$ values are somehow **correlated**. We denote that in the covariance matrix with values off the diagonal. What does this mean in physical terms? Think of trying to park your car in a parking spot. You can not pull up beside the spot and then move sideways into the space because most cars cannot go purely sideways. $x$ and $y$ are not independent. This is a consequence of the steering system in a car. When your tires are turned the car rotates around its rear axle while moving forward. Or think of a horse attached to a pivoting exercise bar in a corral. The horse can only walk in circles, he cannot vary $x$ and $y$ independently, which means he cannot walk straight forward to to the side. If $x$ changes, $y$ must also change in a defined way. \n",
      "\n",
      "So when we see this ellipse we know that $x$ and $y$ are correlated, and that the correlation is \"strong\". The size of the ellipse shows how much error we have in each axis, and the slant shows how strongly correlated the values are."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's look at this in a graph and then reason about it. Let's assume that we have a covariance for the position of our dog, which we believe is at coordinate (5, 10) meters. If the standard deviation in x and y is each 2 meters, but they are strongly correlated, our covariance contour would look like this."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P = np.array([[4, 3.9], [3.9, 4]])\n",
      "stats.plot_covariance_ellipse((5, 10), P, edgecolor='k', \n",
      "                              variance=[1, 2**2, 3**2])\n",
      "plt.xlabel('X')\n",
      "plt.ylabel('Y')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAygAAAGkCAYAAADaGQF7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRCQa/weKYGYwFmg+wAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e779d438>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now suppose I were to tell you that the actual position of the dog in the *x* dimension is 7.5, what can we infer about his position in *y*? The position is extremely likely to lie within the 3$\\sigma$ covariance, as in the chart below. We can *infer* the like position in *y* based on the covariance matrix because there is a correlation between *x* and *y*."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P = np.array([[4, 3.9], [3.9, 4]])\n",
      "stats.plot_covariance_ellipse((5, 10), P, edgecolor='k', \n",
      "                              variance=[1, 2**2, 3**2])\n",
      "plt.xlabel('X')\n",
      "plt.ylabel('Y')\n",
      "plt.gca().autoscale(tight=True)\n",
      "plt.axvline(7.5, ls='--', lw=1)\n",
      "plt.axhline(12.5, ls='--', lw=1)\n",
      "plt.scatter(7.5, 12.5, s=2000, alpha=0.5)\n",
      "plt.plot()\n",
      "plt.show()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAygAAAGdCAYAAAD5bFceAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7774b70>"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A word about **correlation** and **independence**. If variables are **independent** they can vary separately. If you walk in an open field, you can move in the $x$ direction (east-west), the $y$ direction(north-south), or any combination thereof. Independent variables are always also **uncorrelated**. Except in special cases, the reverse does not hold true. Variables can be uncorrelated, but dependent. For example, consider the pair$(x,y)$ where $y=x^2$. Correlation is a linear measurement, so $x$ and $y$ are uncorrelated. However, they are obviously dependent on each other. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Multiplying Multidemensional Gaussians"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In the previous chapter we incorporated an uncertain measurement with an uncertain estimate by multipling their Gaussians together. The result was another Gaussian with a smaller variance. If two piece of uncertain information corroborate each other we should be more certain in our conclusion. The graphs look like this:\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import stats\n",
      "xs = np.arange(-5, 10, 0.1)\n",
      "\n",
      "mean1, var1 = 0, 5\n",
      "mean2, var2 = 5, 1\n",
      "mean, var = stats.mul(mean1, var1, mean2, var2)\n",
      "\n",
      "ys = [stats.gaussian(x, mean1, var1) for x in xs]\n",
      "plt.plot(xs, ys, label='M1')\n",
      "\n",
      "ys = [stats.gaussian(x, mean2, var2) for x in xs]\n",
      "plt.plot(xs, ys, label='M2')\n",
      "\n",
      "ys = [stats.gaussian(x, mean, var) for x in xs]\n",
      "plt.plot(xs, ys, label='M1 x M2')\n",
      "plt.legend()\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyYAAAGNCAYAAADkc2U2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nE0mSJEmSJEmSFCcTE0mSJEmSJEmSFPd/y8FEyNatw1kAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7be6198>"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The combination of measurement 1 and 2 yields more certainty, so the new Gaussian is taller and narrower - the variance became smaller. The same thing happens in multiple dimensions with multivariate Gaussians.\n",
      "\n",
      "Here are the equations for multiplying multivariate Gaussians. You will not need to remember these equations, as they are backed into the Kalman filter equations that will be presented shortly. This computation is also available in FilterPy using the `multivariate_multiply()` method, which you can import from `filterpy.common`. \n",
      "\n",
      "$$\\begin{aligned}\n",
      "\\mu &= \\Sigma_2(\\Sigma_1 + \\Sigma_2)^{-1}\\mu_1 + \\Sigma_1(\\Sigma_1 + \\Sigma_2)^{-1}\\mu_2 \\\\\n",
      "\\Sigma &= \\Sigma_1(\\Sigma_1+\\Sigma_2)^{-1}\\Sigma_2\n",
      "\\end{aligned}$$\n",
      "\n",
      "To give you some intuition about this, recall the equations for multiplying univariate Gaussians:\n",
      "\n",
      "$$\\begin{aligned}\n",
      "\\mu &=\\frac{\\sigma_1^2 \\mu_2 + \\sigma_2^2 \\mu_1} {\\sigma_1^2 + \\sigma_2^2}, \\\\\n",
      "\\sigma^2 &= \\frac{1}{\\frac{1}{\\sigma_1^2} + \\frac{1}{\\sigma_2^2}}\n",
      "\\end{aligned}$$\n",
      "\n",
      "This looks similar to the equations for the multivariate equations. This will be more obvious if you recognize that matrix inversion, denoted by the -1 power, is *like* division since $AA^{-1} =I$. I will rewrite the inversions as divisions - this is not a mathematically correct thing to do as the order of operations becomes ambiguous (matrix multiplication is not commutative), but it does help us see what is going on.\n",
      "\n",
      "\n",
      "\n",
      "$$\\begin{aligned}\\mu &\\approx \\frac{\\Sigma_2\\mu_1 + \\Sigma_1\\mu_2}{\\Sigma_1 + \\Sigma_2} \\\\\n",
      "\\Sigma &\\approx \\frac{\\Sigma_1\\Sigma_2}{(\\Sigma_1+\\Sigma_2)}\n",
      "\\end{aligned}$$\n",
      "\n",
      "In this form we can see that these equations are just the linear algebra form of the univariate equations.\n",
      "\n",
      "Now Let's explore multivariate Gaussians in terms of a concrete example. Suppose that we are tracking an aircraft with a couple of radar systems. I will ignore altitude as this is easier to graph in two dimensions. Radars give us the range and bearing to a target. We start out being uncertain about the position of the aircraft, so the covariance, which is just our uncertainty about the position, might look like this. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P0 = np.array([[6, 0], [0, 6]])\n",
      "stats.plot_covariance_ellipse((10, 10), P0, facecolor='y', alpha=0.6)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGNCAYAAABuXPx3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAIgLJQIAAABAXP4Pph9g4aXHsesAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e77832e8>"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now suppose that there is a radar to the lower right of the aircraft. Further suppose that the radar is very accurate in the bearing measurement, but not very accurate at the range. That covariance, which is just the uncertainty in the reading might look like this (plotted in blue):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P1 = np.array([[2, 1.9], [1.9, 2]])\n",
      "stats.plot_covariance_ellipse((10, 10), P0, facecolor='y', alpha=0.6)\n",
      "stats.plot_covariance_ellipse((10, 10), P1, facecolor='b', alpha=0.6)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGNCAYAAABuXPx3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7c20a90>"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "To combine the information we multiply the two Gaussians together. Let's see the result of that. I will use FilterPy's `multivarite_multiply` method to perform the multiplication."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from filterpy.common import multivariate_multiply\n",
      "\n",
      "P2 = multivariate_multiply((10,10), P0, (10,10), P1)[1]\n",
      "\n",
      "stats.plot_covariance_ellipse((10, 10), P0, facecolor='y', alpha=0.2)\n",
      "stats.plot_covariance_ellipse((10, 10), P1, facecolor='b', alpha=0.6)\n",
      "stats.plot_covariance_ellipse((10, 10), P2, facecolor='y')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGNCAYAAABuXPx3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTj4AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7bdb1d0>"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here I have plotted the orignal estimate it a very transparent yellow, the radar reading in blue, and the estimate generate by multiplying the two Gaussians together in yellow.\n",
      "\n",
      "It retained the same shape and position as the radar measurement, but is smaller. We've seen this with the one dimensional Gaussians - multiplying two Gaussians makes the variance smaller because we are incorporating more information, hence we are less uncertain.  But the main point I want to make is that the covariance shape reflects the physical layout of the aircraft and the radar system.\n",
      "\n",
      "Now lets say we get a measurement from a second radar bank, this one to the lower right, which I will plot in blue against the yellow covariance of our current belief. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P3 = np.array([[2, -1.9], [-1.9, 2.2]])\n",
      "stats.plot_covariance_ellipse((10, 10), P2, facecolor='y', alpha=0.6)\n",
      "stats.plot_covariance_ellipse((10, 10), P3, facecolor='b', alpha=0.6)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGNCAYAAACfV6f6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7787a90>"
       ]
      }
     ],
     "prompt_number": 66
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Again, to incorprate this new information we will multiply the Gaussians together."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P4 = multivariate_multiply((10,10), P2, (10,10), P3)[1]\n",
      "\n",
      "stats.plot_covariance_ellipse((10, 10), P2, facecolor='y', alpha=0.2)\n",
      "stats.plot_covariance_ellipse((10, 10), P3, facecolor='b', alpha=0.6)\n",
      "stats.plot_covariance_ellipse((10, 10), P4, facecolor='y')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGNCAYAAACfV6f6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7966438>"
       ]
      }
     ],
     "prompt_number": 67
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can see how the multivariate Gaussian's shape reflects the geometry of the problem. The first radar system was at a 45 degree angle to the aircraft, and its error in the bearing measurement was much smaller than the error in the range. This resulted in a long and narrow covariance ellipse whose major axis was aligned with the angle to the radar system. The next radar system was also at a 45 degree angle, but to the right, so the two measurements were orthogonal to each other. This allowed us to *triangulate* on the aircraft, which resulted in a very accurate final estimate. We didn't explicitly write any code to perform triangulation; it was a natural outcome of multiplying the Gaussians of each measurement together.\n",
      "\n",
      "To make sure you understand this, what would the Gaussian look like if we only had one radar station, and we receive several measurements from it over a short period of time? Clearly the Gaussian would remain elongated in the axis of the bearing angle. Without a second radar station no information would be provided to reduce the error on that axis, so it would remain quite large. As the aircraft moves the bearing will typically change by a small amount, so over time some of the error will be reduced, but it will never be reduced as much as a second radar station would provide.\n",
      "\n",
      "To round this out lets quickly redo this example but with the first radar system in a different position. I will position it directly to the left of the aircraft. The only change I need to make is to the Gaussian for the measurement from the radar. I used\n",
      "\n",
      "$$\\Sigma = \\begin{bmatrix}2&1.9\\\\1.9&2\\end{bmatrix}$$\n",
      "\n",
      "Why did this result in a 45 degree ellipse? Think about that before reading on. It was 45 degrees because the values in the diagonal were identical. So if x=10 then y=10, and so on. We can alter the angle by making the variance for x or y different, like so:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P1 = np.array([[2, 1.9], [1.9, 8]])\n",
      "stats.plot_covariance_ellipse((10, 10), P1, facecolor='y', alpha=0.6)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGNCAYAAABuXPx3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7b46b00>"
       ]
      }
     ],
     "prompt_number": 70
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The radar is to the left of the aircraft, so I can use a covariance of \n",
      "$$\\Sigma = \\begin{bmatrix}2&1.9\\\\1.9&2\\end{bmatrix}$$\n",
      "to model the measurement. In the next graph I plot the original estimate in a very light yellow, the radar measurement in blue, and the new estimate based on multiplying the two Gaussians together in yellow."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P1 = np.array([[2, 0], [0, .2]])\n",
      "\n",
      "P2 = multivariate_multiply((10,10), P0, (10,10), P1)[1]\n",
      "\n",
      "stats.plot_covariance_ellipse((10, 10), P0, facecolor='y', alpha=0.2)\n",
      "stats.plot_covariance_ellipse((10, 10), P1, facecolor='b', alpha=0.6)\n",
      "stats.plot_covariance_ellipse((10, 10), P2, facecolor='y')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGNCAYAAABuXPx3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAALSEEgEAAACgJZQIAAAAAC35/w5em7Ad7IJCAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7c96860>"
       ]
      }
     ],
     "prompt_number": 81
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now we can incorporate the measurement from the second radar system, which we will leave in the same position as before."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P3 = np.array([[2, -1.9], [-1.9, 2.2]])\n",
      "P4 = multivariate_multiply((10,10), P2, (10,10), P3)[1]\n",
      "\n",
      "stats.plot_covariance_ellipse((10, 10), P2, facecolor='y', alpha=0.2)\n",
      "stats.plot_covariance_ellipse((10, 10), P3, facecolor='b', alpha=0.6)\n",
      "stats.plot_covariance_ellipse((10, 10), P4, facecolor='y')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAGNCAYAAACfV6f6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xl0lPed5/v389RepQXtQhICITaxI8AGG+MdGydxmnQn\nnXa7bSaJPZnJzZ3kdLtzfafPkLmT04knGV/7Zhk7naSbTtpZuoNjJ20ndmIWYzBGGLFIAgm0oH1f\nSyrV8tT9Q0Y2wQgQKpWWz+ucOpSerb7Pg06pPvV7fr+fEY1Go4iIiIiIiMSQGe8CRERERERk5lPw\nEBERERGRmFPwEBERERGRmFPwEBERERGRmFPwEBERERGRmFPwEBERERGRmFPwEBERERGRmBszeBw4\ncIAHH3yQvLw8TNNk9+7do+vC4TBf+cpXWLNmDQkJCeTk5PCXf/mX1NfXX/VF9+/fz/r16/F4PBQW\nFvL888/f+JmIiIiIiMiUNWbw8Pv9rF69mmeffRaPx4NhGJesO378OH/3d3/H8ePHeemll6ivr+f+\n++8nEolc8Zg1NTU88MADbNmyhdLSUp588km++MUvsmfPnok7KxERERERmVKMa525PDExke9+97s8\n8sgjV9ymoqKCFStWcOrUKVasWPGh23zlK1/hV7/6FWfPnh1d9thjj1FWVsahQ4eus3wREREREZkO\nJrSPR29vLwApKSlX3Obw4cNs27btkmXbtm2jpKRkzJYSERERERGZvuwTdaBgMMhf//Vf8+CDD5KT\nk3PF7VpbW8nKyrpkWVZWFuFwmI6OjkvWXQwyIiIiIiIyfSQnJ1+2bEKCRzgc5uGHH6avr4/f/OY3\nE3FIERERERGZQW44eITDYf7iL/6CsrIy9u3bN+ZtVgDZ2dm0tLRcsqy1tRW73U56evqNliMiIiIi\nIlPQDQWPUCjEpz/9acrLy9m3bx+ZmZlX3Wfz5s28+OKLlyx7/fXX2bhxIzab7Yr7fVhzzbUoKSkB\nYMOGDePaX66NrnPs6RpPDl3nyaHrHHu6xpND13ly6DrH3kRc46t1k7jqcLqlpaWUlpZiWRZ1dXWU\nlpZSX19PJBLhk5/8JEeOHOGFF14gGo3S0tJCS0sLgUBg9BiPPPIIjz766OjPn//852lsbOTLX/4y\nFRUV/OAHP2D37t38zd/8zbhPUkREREREprYxg8fRo0cpLi6muLiYQCDArl27KC4uZteuXTQ0NPDy\nyy/T3NzM+vXrycnJGX384he/GD1GfX39JZMKLliwgFdeeYUDBw6wbt06vv71r/Ptb3+bHTt2xO4s\nRUREREQkrsa81eqOO+7Asqwrrh9r3UV79+69bNnWrVs5duzYNZQnIiIiIiIzwYTO4yEiIiIiIvJh\nFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxE\nRERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERE\nRCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTm\nFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxE\nRERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERERCTmFDxERERE\nRCTmFDxERERERCTmxgweBw4c4MEHHyQvLw/TNNm9e/cl6/fs2cN9991HZmYmpmmyf//+q77gvn37\nME3zskdlZeWNnYmIiIiIiExZYwYPv9/P6tWrefbZZ/F4PBiGccn6wcFBtmzZwtNPPw1w2fqxlJeX\n09LSMvpYtGjROMoXEREREZHpwD7Wyu3bt7N9+3YAdu7cedn6hx9+GICOjo7rfuGMjAzS0tKuez8R\nEREREZl+4tbHY8OGDeTk5HDPPfewb9++eJUhIiIiIiKTwIhGo9Fr2TAxMZHvfve7PPLII5et6+jo\nIDMzk3379rF169Yxj1NZWcm+ffvYuHEjw8PD/PjHP+a5555j//79bNmy5ZJte3t7R59XVVVdS5ki\nIiIiIhIHixcvHn2enJx82foxb7WKhSVLlrBkyZLRnzdt2kRtbS3f/OY3LwseIjK7WVaUlp4hhoIR\nIlb0vYdFJBLF67KTOcdNksdxXf3LREREJD4mPXh8mJtuuomf//znY26zYcOGcR27pKTkhvaXa6Pr\nHHuz5RpHo1HOXOjgWGUzJ8630Nw+THAYLAui0ff/dTqH8fn8pCQ5yc1IJC89ibyMJArmpjA3LWHc\nYWS2XOd403WOPV3jyaHrPDl0nWNvIq7xB+9W+jBTIniUlpaSk5MT7zJEJM4a2/v42d7THD/TSWsr\ndHZCNOTFY/NhGjZMTAzDwMRk2AowEO7FsAXx+TpHHgmQnAzzsxNYv2Qu65fmkJueqBYRERGRKWDM\n4OH3+0f7VliWRV1dHaWlpaSlpTFv3jy6u7upq6ujp6cHGOmHkZSUxNy5c8nKygLgkUcewTCM0TlA\nnnnmGQoKCli+fDnBYJCf/OQnvPTSS+zZsyeW5ykiU9y7lc18/9fvUnXOorPNRbZ7PkXeufjsVw4O\n0WiUoDWMP9yHv7eP7s4+qoPtVPgGKDlVRUZ6FflzfaxfksP6JXPJy0hSCBEREYmTMYPH0aNHueuu\nu4CROTp27drFrl272LlzJz/60Y946aWX+MxnPjO6/rHHHgPgq1/9Kv/tv/03AOrr6y/5Qx8KhXji\niSdoaGjA4/GwcuVKXnnlFe6///6YnKCITH2nqlv53ovHOHEySoKVz/rU5dhNx1X3MwwDl82Ny+Ym\n1ZUJjISR3lAnHS3NlNY1U+71c+xkFekZVcyf6+OONQu4dVU+bueUaPAVERGZNcb8y3vHHXdgWdYV\n1+/cufND5/f4oL17917y8xNPPMETTzxx7RWKyIw2MBRk9+9OcLosSiqLmZ+49IZaJQzDYI4znTnO\ndAqjK0dCSGszJy40c9bnp6yyjJcPVXLb6nzuXLuAtGTvBJ6NiIiIXIm+8hORuHr5rbOcqRrGGEpj\nfsqNhY4/9schpCvYSuP5ampqOjlXfZ7fvVPNxmVzuWf9QhbmpEzY64qIiMjlFDxEJG6Gg2HeLm+g\nvgFWJa2Kaf8LwzBIc2WT5spmINRLQ3M1R+qbqKlp4q2TTSxfmMI9xQuxrCimqX4gIiIiE03BQ0Ti\npvRcC81tYdzRFHz2xEl73QRHMsuS1zEcKaKpp4bSlgtUV3dTeuYYSa5+bl+ZzfpoVB3RRUREJpCC\nh4jEzTtnGmltgSz3vLi8vsvmpiCxiHzfYloDDZw5fR7LNsCF1noaBw+x47YiFuWmxqU2ERGRmUbB\nQ0Tipr1nEL8f5nvj++HeZtrJ8S4g25PPmeYTnK+sY2ioi9PVb7GxKIsdW5aRm5EU1xpFRESmOwUP\nEYmb/qFhQiFwmK54lwKAaZhkOPJItWcz7O/j+LFqGhtaOV7ZxpbVuXzslqWkaxQsERGRcVHwEJG4\niEQs/EMhImEDu3H1OTsmk82wMz9hKXO9C6jvqeJoWx2NjQ28XdbEXcXz+ejmJfg8zniXKSIiMq0o\neIhIXPgDIcJhsJmOKduJ22m6KExcSW5kIbVtZ3m7uZGm5hqOVDTyia1F3Lpy3pStXUREZKpR8BCR\nuBgYCo7cZmVM/ZYDt83LsuR1DIQKqa4vo6Wlg+b2E7x1+gIP3b2KeZnJ8S5RRERkylPwEJG4sNtM\nDBMsrHiXcs0SHEmsmrOJ9uEmKk6W09rSTVX9m2zbWMCDty7F7dRbqoiIyJXor6SIxEVqkgeP2yBo\nDWFFLUzDjHdJ18QwDDLduaQ6M6nrq+To0Rra26s5eraJT92xnA1Lc3T7lYiIyIdQ8BCRuLDbTFIS\n3TidQwStAG7b9Botym46KExcQVYoj3O1p2hp7aa57V02LK/nL+5aSVZqQrxLFBERmVIUPEQkbtKS\nPLjdQwQig9MueFyU4EhmTcqttAbqOVVaQUtrOxW1+9m+qZCPbFqMw26Ld4kiIiJTgoKHiMRNerIX\nt7uLwNBgvEu5IYZhkO3JJ82VTU1XBW+3X6C9s4p3K5t59L41FGr2cxEREQUPEYmfkeABgYHpHTwu\ncphOliStoS+YT1XVCTra+2loO8T2TQV8/NZlOB1q/RARkdlLwUNE4iYrJQGvF1pCvfEuZUIlOVNY\nl7qVC/5Kjh07R09PNaeq23jkvjUsUuuHiIjMUgoeIhI3y/LTmTMHKkOdWNEIpjFzWgRMw2RBwjLS\nQtlUnjtBe3sfDW2HuP/mAnbctkx9P0REZNaZHuNXisiMlORzUZCTjDchQl+oO97lxESiYw7rUm/D\nG1jCsWPws99V87UfH6C2pSfepYmIiEwqBQ8Riaui/HRSUqB7uD3epcTMSOvHUlYkbqGuKpG9hwb4\n2j8f5OW3zhKJTJ8JFEVERG6EgoeIxNXyBRkjwSM4c4PHRYmOORSn3YbLv5CSEvjxq5V846cHaero\nj3dpIiIiMac+HiISV4tyU0lNsRGI9hKMDOO0ueJdUkyZho2FiStIDWZTWVFKZ0cvDW1v8um7lrN1\nzXzNei4iIjOWWjxEJK4cdhtL56UxZw70BDviXc6kmeNMozj1dqK9+bxzNML3XzrF878+hn8oGO/S\nREREYkLBQ0TibvmCDFJSoXO4Jd6lTCq7aWdJ0hrmO9dz+qSD3+xr5n/8+ADnGrviXZqIiMiEU/AQ\nkbhbv2QumRkG3aEWQtbs+8Y/w53D2pSttNencPDtIb7xL4f498OVWFY03qWJiIhMGAUPEYm7lEQP\nqxamk5pm0R5ojHc5ceG2eVmdcgvewCJKSuCfXz3LM//2Nj0DgXiXJiIiMiEUPERkSrh1VT5Z2dAy\nVB/vUuLGNEwKEotY4r2Zs2UufvdmB//P7v2cPN8a79JERERumIKHiEwJawqzyM12Erb1MhDqjXc5\ncZXiymBdyu30t2Zw6EiQp3/+Dr/YW0ZYc36IiMg0puAhIlOCw27jpmU5ZGVBa2D2tnpc5LS5WDnn\nZtKs5Rw/bvLz16p56qcHae0aiHdpIiIi46LgISJTxq0r88nKgrZAI1ZU3+4bhkGer5AVibdSU+nj\njbd6+R///CYlZ5viXZqIiMh1U/AQkSljXmYSi/OT8SUG6RpWv4aLEh1zWJd6G+HuXI4cDfPtfzvG\nv+4rI6Jbr0REZBpR8BCRKcMwDG5ZMY/sbGgeqot3OVOK3XSwNGkd2eZKSktNfvH7ap755dv0+Yfj\nXZqIiMg1UfAQkSnl5qJccuba8NPOQKgv3uVMKYZhkOMtYHnCZqrK3bx+sJOv/eQA5zXhoIiITAMK\nHiIypfg8Trauzic3FxoGz8W7nCkpyZnKutSt9DSncehIgKdeOMze4zVEo5pwUEREpi4FDxGZcu5Z\nv5B5uSbd4SYCkcF4lzMlOW0uVqVswhNYSMkxix/++jT/+GopwVAk3qWJiIh8qDGDx4EDB3jwwQfJ\ny8vDNE127959yfo9e/Zw3333kZmZiWma7N+//5pedP/+/axfvx6Px0NhYSHPP//8+M9ARGactGQv\nm1fmMndulAb/+XiXM2WZhsnCxBXMdxVz8oSNl/c38NRPD9Le4493aSIiIpcZM3j4/X5Wr17Ns88+\ni8fjwTCMS9YPDg6yZcsWnn76aYDL1n+YmpoaHnjgAbZs2UJpaSlPPvkkX/ziF9mzZ88NnIaIzDTb\nNhSSmwvtwXqCljpQjyXTncvqObdRfy6BfYf7+NqP3+RUtUYFExGRqcU+1srt27ezfft2AHbu3HnZ\n+ocffhiAjo6Oa37B5557jry8PJ599lkAli5dypEjR/jWt77FJz7xiWs+jojMbDnpiWxYlk1dXQtN\nfTUsSFgW75KmNJ89kbWpW6jsKuXtoy30DrzDn96+hI9uXnJNXwqJiIjE2qT38Th8+DDbtm27ZNm2\nbdsoKSkhEtG9ySLyvvs2FpKXB81DtYStcLzLmfLspoOi5A2kWUWUHjf4l99W8t1fHWVoOBTv0kRE\nRMZu8YiF1tZWsrKyLlmWlZVFOBymo6PjsnUXlZSU3NDr3uj+cm10nWNvtl3jOa5B7E6Lsy0nyXTM\nm7TXbW9vn7TXmmhukkmPLObdoxU0NlZysuIcn7xlPikJrniXdpnZ9vscD7rGk0PXeXLoOsfejVzj\nxYsXj7leo1qJyJS2eVkmmVlB2kINWFHN1H2tkmypLHYV09GUyvEy+Mc/nKeufSDeZYmIyCw26S0e\n2dnZtLS0XLKstbUVu91Oenr6FffbsGHDuF7vYmob7/5ybXSdY2+2XuP10ShVXQcYGOgjHPST610Y\n09e72NKRkZER09eZLNlWDmd636WmvpXfnvbzyH0F3LZ6frzLmrW/z5NJ13hy6DpPDl3n2JuIa9zb\n2zvm+klv8di8eTOvv/76Jctef/11Nm7ciM1mm+xyRGSKMwyDj9+6jAULoN5fRdhSf4XrYTftrJiz\nkYRgIcfetfj+yyf5+RunsSxNNigiIpNrzBYPv99PVVUVAJZlUVdXR2lpKWlpacybN4/u7m7q6uro\n6ekBoKqqiqSkJObOnTvaV+ORRx7BMIzROUA+//nP853vfIcvf/nLPP7447z11lvs3r2bn/3sZ7E8\nTxGZxlYtzGTtkjQaGzppGDivEa6uk2EYLExcjm8okROlJxkO1NDSNcBjH12P1+2Id3kiIjJLjNni\ncfToUYqLiykuLiYQCLBr1y6Ki4vZtWsXAC+99BLFxcXcddddGIbBY489RnFx8SUTAtbX11NfXz/6\n84IFC3jllVc4cOAA69at4+tf/zrf/va32bFjR4xOUUSmO8Mw+MRtRcyfD82BaoYjgXiXNC1leeax\nPHEzZ8udvH64nad+epC2bk02KCIik2PMFo877rgDy7pyZ86dO3d+6PweH7R3797Llm3dupVjx45d\nW4UiIsDCnBQ2r5xLU1MzFzorWZy0Ot4lTUvJzlTWpt5GWd1R3vT30es/yOcfXM+y/Cv3sRMREZkI\nGtVKRKaNP9myjPnzDTrDFxgMa4Sm8XLbvKxJuZVgdzZHjgb51s/eZn9pbbzLEhGRGU7BQ0SmjazU\nBG5fm09uXpTagTPxLmdas5t2lidvIDG0iHffjfKDX5/ip384pU7nIiISMwoeIjKtfHTzEgrm2+in\nmb5gd7zLmdYMw6AgsYh851pOnjDZs7eWb+85opnORUQkJhQ8RGRamZPg5t4NC5mfDzUDFUSj+ob+\nRl3sdF5V4eL3h9v55s8O0d0/FO+yRERkhlHwEJFp576NhSyc7yTs6KQr2BbvcmaEJGcqa1K20FSb\nwMGjfXzjhbdoaO+Ld1kiIjKDKHiIyLTjcTn4yObFFBRATX85VvTKo+/JtXPbvKxJvZW+1lQOlwzx\nP396iIq69niXJSIiM4SCh4hMS3esXUBRYQKe5AGaBmviXc6M4TCdrErZBH05vHMsxP/7i3c4XFZ/\n9R1FRESuQsFDRKYlu83kU3euYOFCqB+qJKhJBSeMadhYllxMYqiQY+9aPPdSKf9+uFL9aURE5IYo\neIjItLWyIJNNK7PJzglTM1AR73JmFMMwWJi4nBz7Sk6UGvzLa2f5yesniUR0W5uIiIyPgoeITGuf\nvGM5hQU2eqIN9AW74l3OjJPjLaDQs4HTJ228vP8C33vpKIFgON5liYjINKTgISLTWsYcH9tvLmRh\nAZzrP63bgWIg3Z3NiqTNVFY4ef1wG9/6+SF6BnRrm4iIXB8FDxGZ9u6/aRFLCz3Yfb00D9XGu5wZ\nKcmZwpqULTRU+3jznV6+8cJBmjr6412WiIhMIwoeIjLtOR02Pn3nShYthjr/WXU0jxGP3cfa1C30\ntKTydskQ33jhLc5e6Ih3WSIiMk0oeIjIjLC6MItNK7LIzg1RPVAe73JmLIfpZHXKJiK9czl6LMT/\n+vkRjp1tindZIiIyDSh4iMiMYBgGf37XSgoLbPRFG+kJ6pv4WDENG0XJ6/GFCjheavHdF9/lwIm6\neJclIiJTnIKHiMwY6clePnbLYgoL4VzfKc1oHkOGYbAwYQXpLKO0NMoPf3OSV49UqXO/iIhckT3e\nBYiITKRtGwt5u7yBltYB6v3nmJ+wJN4lzViGYZCfsBjHoJMTJ04RiZxhYCjIn92+HMMw4l2eiIhM\nMWrxEJEZxW4zefje1SxaBE3DVfhDffEuacab653PQk8xp06a7NlbzT/9tlQTDYqIyGXU4iEiM86S\neWls27iA7q5aKmtPsDZli76Bj7EMdw52w0H56RLCkQYGAyEe/9h6HHZbvEsTEZEpQi0eIjIjfWJr\nEcuXeLD7emgcrI53ObNCiiuD5cmbqKxw8vu3W3n2l0cYDITiXZaIiEwRCh4iMiO5nXYevmc1i5dA\n/dBZBsMD8S5pVkhypLB6zi3UnvOw751Onv7Xw/T5h+NdloiITAEKHiIyY60oyOTO4nnMXxChqu+E\nRlyaJF57IqtTbqG5NoGDR3v5nz97i47ewXiXJSIicabgISIz2idvX86yxW7wdNE8VBvvcmYNt83L\n6tRb6Gqaw+ESP0/99C0a2tXRX0RkNlPwEJEZzedx8tDdK1myBOoGzxCI6Jv3yeI0XaxK2cxgZzpH\njgX45s8Ocb6xK95liYhInCh4iMiMt27xXLasySEvP0xV30ndcjWJ7KadlXNuIto3l6Pvhvhfv3ib\nspq2eJclIiJxoOAhIrPCp+9aybJFTsKudloD9fEuZ1YxDRtFyetxBfI59m6EZ395lLONvfEuS0RE\nJpmCh4jMCkk+F5++ayVLFkPNQDnDkUC8S5pVDMNgceJqEiMLOV5q8a9v1VNe3xPvskREZBIpeIjI\nrLFxWQ6bV2WRkxfiXP8p3XI1yQzDYGHCclKjizlb6eGXbzVwuEytTyIis4WCh4jMGoZh8Jf3rmbp\nYgfDjhbdchUHhmEw37eUlMhCKqs8PP9yKQdO1MW7LBERmQQKHiIyq8xJcPOX96xi2VKo9ZcxFPbH\nu6RZxzAMsh0LSLUWcfIE/PDfT/KHY5pdXkRkplPwEJFZ56aiXG4vziV/QZizfcd1y1WcZDnyyXWs\n5OQJ2P1qGb9951y8SxIRkRiyx7sAEZF4eOjuVVQ1dNHV1c0FfxXzE5bEu6RZKcdbgGnYOHnyJNFo\nBaFwhI9uXoJhGPEuTUREJpiCh4jMSl63g89sX0t799scO1ZJSiiDJEdKvMualbI9+ZiYnDpZSjRa\nSTAU4RNbixQ+RERmGAUPEZm1luan85HNC+ntPc/ZyuMUp26Nd0mzVqYnD9OwcerUu1jWeUIRiz+/\nc4XCh4jIDDJmH48DBw7w4IMPkpeXh2ma7N69+7JtvvrVr5Kbm4vX6+XOO++kvLx8zBfct28fpmle\n9qisrLyxMxERGYePb1nG2qIkktP9VA+M/f4lsZXunsti3wbKTpu8tL+Gn7x+EstS/xsRkZlizODh\n9/tZvXo1zz77LB6P57Jvnp566imefvppvvOd73D06FEyMzO59957GRgYuOoLl5eX09LSMvpYtGjR\njZ2JiMg42G0mn9m+jqVLbfRE6+gNd8S7pFktzZXF0oSbKC+z8ZuDF/in35YqfIiIzBBj3mq1fft2\ntm/fDsDOnTsvWReNRnnmmWd48skn2bFjBwC7d+8mMzOTF154gccff3zMF87IyCAtLe0GShcRmRi5\nGUl88vZl9PaWceyds3htSfEuaVZLcWWwzLiZM2XvELUaCEcsPvvAOmw2DcQoIjKdjftdvKamhtbW\nVrZt2za6zO12s3XrVg4dOnTV/Tds2EBOTg733HMP+/btG28ZIiIT4q7iAm5elUFapp8Lw2c1xG6c\nzXGmsTxpE2crHLz+dhM/fOW4Wj5ERKa5cXcub2lpASArK+uS5ZmZmTQ1NV1xv5ycHJ577jk2btzI\n8PAwP/7xj7n77rvZv38/W7ZsueJ+JSUl4y11QvaXa6PrHHu6xrGzOjPKO/kRTvS1cab5BOmO3HiX\nNOO1t7ePuT47spgTx0/Q3V1G3YU6Pr5xHqapDufXQ+8Zk0PXeXLoOsfejVzjxYsXj7k+JqNajTUK\nyZIlS1iy5P3x8jdt2kRtbS3f/OY3xwweIiKxluR1sH19Lj0D9VSdPU+CLQW36Y13WbOaz5ZEAaup\nrj0JDGBQz4MKHyIi09K4g0d2djYAra2t5OXljS5vbW0dXXetbrrpJn7+85+Puc2GDRuuv0jeT23j\n3V+uja5z7OkaT5YSNi7pw2G301hTy7rULZiGLd5FzTgXWzoyMjKuum0GGaQG0yhvfZvK1DCn2m38\nh+3rFD6uQu8Zk0PXeXLoOsfeRFzj3t7eMdePu49HQUEB2dnZvPbaa6PLAoEABw8e5JZbbrmuY5WW\nlpKTkzPeUkREJtS2tTmsKUrAl9LH+f6yeJcjQJIzheVJN3O2ws7v3m7UaFciItPQmC0efr+fqqoq\nACzLoq6ujtLSUtLS0pg3bx5f+tKX+Pu//3uWLVvG4sWL+drXvkZiYiIPPfTQ6DEeeeQRDMMYnQPk\nmWeeoaCggOXLlxMMBvnJT37CSy+9xJ49e2J4miIi187lsPH4x9bT1nOQo0fraAukkelWf494S3Km\nUpR0MxXlRzBowDQNHtm2Ri0fIiLTxJjB4+jRo9x1113ASL+NXbt2sWvXLnbu3MmPfvQj/vZv/5ah\noSG+8IUv0N3dzaZNm3jttdfw+Xyjx6ivr7+kz0coFOKJJ56goaEBj8fDypUreeWVV7j//vtjdIoi\nItcvLyOJh+5eQf/ASU6fOEmifQ4eu+/qO84wVjRK1IqO/Bu9+O/IcqIQZeRnGBlmPQqXLB/5eWSD\nD7ZP9A4GATD7BgEY/SthGKPPDWPkb4/B+30HbYaP+c51nDpVQiBYg38oyEP3rMJht2G3mdhMA7vN\n1IznIiJT0JjB44477sCyrDEPcDGMXMnevXsv+fmJJ57giSeeuI4SRUTi47bV+Zyt76C/r4mK2mOs\nTb11RvQClThvAAAgAElEQVT3iEajWFaUiBXFilofeH4xXDAaNkbiQpRo1Hr/OdHRMPH++vefv798\nZOsPvPLoM8vqBwyCodGYMbruA9HjA/8ajGQJAxM7OeYyyspOMhiooq2nm+03FWKadgzDhmGY2G22\n0RBit5k47DacdhsOu4nTbsPpsI2GFRERmRwxGdVKRGQmMAyDv9q2hrrWXnp6e6nuL2dR0qp4l3VV\n0WiUiGUReS9QRCIW1nthwxoNGBYw8rj4PBodeVhEsLCwYWIzDAxzJAqYhvFeK8Slzy8GhIs/j7RQ\nmKPL3t/ifUZ4ZH1KwqV/hqJwWQtKNHppuIlGwR1NwGkv4nz1aWxmI3ajh20bMolYELaiRKMmhmGO\nBBHsGKYdw7BjGI7Rf03Tgc20XRJK3E47Lof9vX9tmrRQRGQCKXiIiIzB7bTz+EfX09FzkHeO1tIe\nSCPDPTUGw4hYFpHIxZBhjYaMiHUxWESIYkE0QtgK0h/pYiDcw6DVi9/qY9DqJ2QNE4wOE4mGiUQj\nWERGj28zbLhNDx6bF4/di8f04LZ58djeW2bz4LH7SLQnYRrX9wH9YreMsftnjH27lJd03M41VNae\n4oTHT3ZqH39+Ry6GYWBZUcKRKGErSjhiEQoHCYUDhCJRgiGLUNgiGIoSjoBpOjCww3thxDRcGKYD\n03ThtI8EELfzvTDifD+U6HYuEZHro+AhInIV+VnJ/Pldy+kfOM3pkydIsCdPan+Piy0Y4chI0AhH\nRp5b0chIKwURiFpEo+8FDSwwLLrDLXSGm+kIttAZbLskVIzFbkYwTYtgGPyRAfyRAQiOsb3hIN2V\nQYYra/ThnaTrM8eZwhJWcabiJNCDYcCnbs/FNA2cpoETgCvfHmdZUUKRkRASDAcJhgIEQj0EQxaB\nIYshbO8FESem6cQwnJimC7vNicflwOty4HHZ3/vXoY7uIiJjUPAQEbkGd6xdQGV9J319zVTUHWNt\n6pbr/pb/WoUjEUJhazRshCPWe/3tIiPhIhomSgSTKDabgc0ceZgmdIXaqBmsosZ/jqA1fMlx89Pb\nyU/vIDe1i9zULnJSukjx+Un0BPA4gzhsYRz2CKYxcq9TIOSge8BH10AC3f4EugZ87/2bQLffR/dA\nAm29ybT1JdMSaKIl0DT6Wl6b7/0g4s4i3ZmB3XTE5Hq9Hz5OgdGDYRh8cmvONbVImKaBy7ThukJp\nobBFIGgxHAowHBp873mE/iGDwUEXXaYbm+nGMF3YTDeeDwQRn8eJz+1Qy4iIyHsUPERErsHF/h4X\n2nrp7e2lZqCcwsSVN3zcaPS9W4EiFqFwhHDYImJFgPB7IWPkYTOj2Gwmdpsx8jDto9+uW1GLGn8V\npT3H6Av1jB57YWYr6xeeZ82COlbOu0Cyd+i6anM7QsxN6WFuSs+Y23UN+DjTmEtFYx7lDXmcbcrB\nPwx1g9XUDVYDIx3G012ZzPcuZIGv8Pou0jWY40xlMas4W3EKg27sNoMdt8694Q/9DruJw26S+Ed/\nLiORKEPBCEPDQwwODzA0HGFw2GIo4MI03aMPh92L1+Ug0esi4b0gon4jIjJbKXiIiFwjr9vBYx9d\nT3vPWxwtqSE5kEa6e+51HSMajRIKW4QiIyEjFIlgWRGihIlaYaKEsRnR90ZjGgkZNtOB+SGfVaPR\nKHWD1bzb/Q69oW4A0hP7uHvVKbatPsHCrLaJOO2rSk3wc8vSSm5ZWgmAFTW40JFORcNIGKlozKW6\nNYv24Vbah1sp6T7MHFsquY55FIVWkehImpA6UpypLGIlFRWnMMwuXHaTj2zKnpBj/zGbzSDBYyfB\n8/6f0Wg0ylDQYmg4yODwEIOBMAN+GBz00NXnwTS92G1evG4HCR7naBjRyFoiMlsoeIiIXIcF2XP4\n8zuLGBgoo+zUCRIcybht3jH3iVgWwVCEYDhCKBzBssIjt0u9d8uU3QSHzcDhMnHY7NfUTyAQCXCo\nY99oi0L2nG7+ausB7ltzAps59jDosWYaURZktLMgo53t60oBGAo6eedcIfvLV3C4cgk9oS56Il2U\nNZwgzZnBAl8hBb5CEh3JN/TaKc40CqMrqCgv41dGB06Hyb3rMyfitK7KMAy8Lhtel42095ZFIlEG\nAmH8gT78Q934hyIEAh56+r2Ypge7zUeCx0VygptknwvPle75EhGZARQ8RESu013FBVQ2dNLX30JF\n3THWpN5yyfweF2+fuhg2wpEI0WgIywoRJYzdBKfDwGEzsds+vDVjLM1DjRxo/z2DET9e5zCP3fN7\nPlL8Lg7btXUejwePM8jtyyu4fXkFgZCDd84tYn/5cg6dXUpnsJ3OYDvHut8eDSELExaTYE8c12ul\nuTKwKKK8vJx/M9tw2k1uX5M+wWd0bWw2g2Sfg2TfSKCwrCiDwxEGhgYYCPTgH4oSCHjo7k/AZkvA\n7XST7BsJIYlelzqri8iMouAhInKdDMPg0fvW0tB+gDf7ejjXd4pFiasJR0Y6HgdDESJWmGg0RDQa\nAiI47SYOp4nTfm0tGldyYbCWva2/xcJixbwL/Ncde67aB2OqcTtCbC2qYGtRBcMhO++cW8S+91pC\nLoaQd7uPMN+3kOVJq8l0ZV93X40MVxZW1KKsrIIXjGZcDpNNy1NjdEbXzjQvvUXLsqL0D4XpG+ym\nz99G77CDfn8CzbYEHHYvST43KQlu5iS41TdERKY9BQ8RkXHwuh38p49vpLVrP++U1GJ1eki1ZxON\nBrGiIWwmuBwGTruJ3eZkIgY2qvPXsK/td1hY7LjpCF+473dxv63qRrkcYW4rOsNtRWcYDtk5er6Q\nP5xexZsVRdT6z1PrP0+qM53lSasp8C3Cbl77n60s91wi0QjlZZX8s9mIw2GyfvGcGJ7N9TPND7SI\nZHgYGo7QN+in19+LfzDKUCCBzp5EHI5Ekn1uUpM8zElwa6QsEZmWFDxERK7TcDBMZ98Q3f1D3LIy\ni8bWM1SeKcVtrCHVPQenw45tgm+R6RhuHw0dn9p8iM/f+9qEhJmpxOUIs2XZWbYsO0t7XyK/LtnA\nr49toGsQDna8QUnXYVYkr2ZZ0kqcpuuajpnjycMajHD69Hn+0ajH8TGD1QtvrB9JLHlcNjwuG1kp\nEI5Y9PpDdPW34B9sJjCcSEdvMm5nAimJHtKSPPg8zniXLCJyzRQ8RESuUc9AgLZuP73+QSKRXsLh\nXlbkB+m7yYfdGKDuXCUZjvXYzCtPWDceYSvEgfbXsbD42PqSGRk6/lhGUj+fuWsvD299kzdOr+CX\nRzZxrmUux7qPcLLnXZYlrWRF8ho8V+nYD5DnnU/EH+F0WS0/tNXznz9usnTe+PqPTCa7zSQtyUla\nkpNQ2KJnYJiu/gb6BkwGA8m0ds/B5/aSmeIjNdGj/iAiMuUpeIiIjCESsejsG6Ktx89goJ9QqBui\n/cxJsJOa6CTB42ZJXgIDgRqGBvupbC1nedLqCZ1csKT7bXpDPcxPb+cL9/12xoeOD3Law9y/9gT3\nrTnBseqFvHDwNo7XFnCq9zjlfSdZnFDE2pQNVw0g+d4CIv4Ip8ou8Lytji/uKKAge/Jmn79RDrtJ\nxhwXGXNcBIIRuvr76erronvYQ/9gKo3OJNKTR0KIwz6xwVdEZKIoeIiIfIjhYJj23kE6egcZHu4l\nFO7EYRtmboqLtKTES75dtttMdt6XT3tvFUf8HdQNVlPgWzQhdfSH+jjTdxrTsPivn/glLkd4Qo47\n3RgGbCisZkNhNeUNebxwcAtvnV3Gmf7TnB84y9qUjRQlrcJmfPiHbsMwKPAt4txAhJOnG/jftlr+\nyycWkpvumeQzuXFup42cNA9zU930+EO09zTTN9DK0HAqLV1zSE3ykjln+oQqEZk9FDxERD4gFLZo\n6wtg1LQQDHUTDnfjc0fJTXOR7LvyRHfJPgefuX8+vQPVHD9+gYThRDJcWTdcT1nfCaJEuWfVKRbP\nbbnh480Ey/Ma+Nqnf0ZNWybPv34vR84t5mjXISr7y7kpdQt53vwP3c8wDBYlLOVsf4QTp5v5nr2G\n/7KjkMyUa+svMtUYhkFKgpOUBCf+QJj2ni56/O0MB+fQ0ZvChfYBMpPd8S5TRGSUxuYTEWGkI299\nWy/nmnvpGWhjcOgcie4elua5WZybMDoPw1gWzvXxqTvmsmxZgJrBs/jDAzdWkxXmXP9ZAD61+dAN\nHWsmKshs4xt/+S/8/V/8C3mpnfSGeni99Tf8vvUV+kK9H7qPYRgsSSwi0pfB8ZM2vvtyNV39wUmu\nfOL53HYWZHtZnu8jLXGAULCagaFWalp7qW7qJhCcnS1lIjK1KHiIyKxmWVGaO/s5Vd1KY3sDVrSB\nJE8fy/N9zM/y4nFd3/3yW1amcef6ZAoWDnKmr4ywFRp3be3DrYSiQRZmtbAou3Xcx5npNi+p4kf/\n+Xv8x3tew+Mcpn6wlhcbf0pJ12FC1uWhwjRMliWtJNCdzrunTL73cg19g+P/f5pKnA6TnDQPy/MT\nSUschGgjrV0XKKtp4UJrL6Hw1J1kUkRmPgUPEZm1OnsHOV3TxoWWRgb853DbO1mQaZKT6sDpGN/b\no2EYfOr2XNYWOUjJ6qNq4AzRaHRcx2oNNAOwZn7duPafTRy2CJ++9RA/+eK3uX/tcayoxane4/yy\n4QXO9V/+f2AzbBQlraSvLYVjJ6M89+tahoZnzodym80gI8lOYbadZG8/Q0Pnaeqo51R1K82d/eP+\nnRQRuREKHiIy64TCEc43dnG+qZW+gfPYzVYW5TgpzPHhHmfg+CCH3eSz2+ezYmmYsLuNhqHxBYe2\nYQWP65WaMMBXPv4S3/vcP1CU28BQZJA3O97gleYXGQj1X7Kt3XSwInk1Hc1zKDkV5oev1hEKT+8J\nGf+Y3WYwL8PDsnwPXmcX/sFzXGht5syFDoaGZ0Yrj4hMHwoeIjKrdPUNUV7bTlt3A6FgLXnpBkvy\nEkjwTOxYG2lJTh69L59lSwO0hmvoCnZe9zH8YT8AeWnXv+9sV5TbyHc++0P+rz95kdSEftqGW3ip\n6efU+s9fsp3DdLI8aTWNFxI5fCLAj39fj2XNvNYAl8NGQbaPRTkusBrp6r1Aea1aP0Rkcil4iMis\nEI5YVDd1c66xlX5/NR5HD0X5CaQlxW7m56L8RP7ktiyWLB3i3EA5g+8FiWsVtIYB8LkCsShvxjON\nKPetOcGP/tP3uGXJWYJWkL1tv+NwxwHC1vudrd02N0WJq6k+52P/uwP825tNM/bDeILHzrJ5iaQm\nDDE4VM2F1hbOXOhQ53MRmRQKHiIy4wWCYc5c6KCtu3G0laMwx4fDHvu3wHuLM9i6NpEFC/1U9J0m\ndB2dzS9u63MNx6q8WSHZO8TXPv1TvnDfq9jNCGf6T/Pvzb+kN9g9uo3PnsDSxFVUnvHyu7e7+V1J\nWxwrji3TNMjL8FA41wVWA919F6ioa6d3QAFXRGJLwUNEZrT+weGRD1X99TjMTpbN88W0leOPGYbB\nQ3fnUbzCQVp2L5X95VjRa+tHcHH281BEUy7dKMOAP9t0hO989gfkpHTRFezk5aZ/5Vz/mdFtkh1z\nKPSu4EyFlz0H2nnr9My+xS3RO9L6kegexD9YQ1VDO+0919cqJyJyPRQ8RGTG6uoborK+ncHBOhI9\nfhbn+sY9WtWNcDlsfO6B+awssjAS2i/rZ3AlXvvI7NPtfVeeuFCuz9KcZr7/H5/nrpWnCEfDvNnx\nBgfafz/aupTmSmeeaynlZW7+5fdNlJ7/8PlAZgrTNFiQ7SVrTpShQC21LR00tvfFuywRmaEUPERk\nRmrtGuB8UxtDgVrSksIUZPswDCNu9aQkOPncA/NZURSk16inZajxqvv4bBeDR2Ksy5tVfK5h/u4T\nv+SJB1/CZQ9xfqCSl5v+le73BgDIcs8l01ZIWbmHf3y1nqrGG5sIcjrITnUzL8POcKCWhvZ2apq7\nr76TiMh1UvAQkRmnq2+IC22dDAfqyE0zyU33xLskAAqyfTx0dy5FRQHqg1X0BMf+cJdgH2npqG3L\nnIzyZhXDgAfWHee5x79PQWYrfaEeXml+kfbAyESNeZ58kiLzOF3u4vu/qaOhfSjOFcdeWpKThXPd\nhEP1tHV30qCWDxGZYAoeIjKj+IeC1LZ0MTzcQE6anfRkV7xLusRNy1L46C1pLFkyROVAGUORwStu\nm+3OAeB4bcFklTfrLMho539/7h+4dekZglaQ37a8RPNQI4ZhUOBbhGNoLifLHDz3mxo6+y6fBX2m\nSfTaKcj2EAo20tzZTUfvlX8/RUSul4KHiMwYwVCE803dDA01kJYYJWPO1AodF33k5mxuXesjf4Gf\nM32nLxna9YOyPSPB43T9PIJh22SWOKu4HGG++slfcM+qk4SjYV5v/TX1g7UYhsHixGVE+jIoPWXj\ney/X0D8484edTfTayctwMjxcT11LF/2DGlVNRCaGgoeIzBjnm7oYGGzC6w6QlzE1bq/6MKZp8Ff3\nzGPdChvJGSMjXX3YvBEem5c5jlSCYQcn6hZMep2zid1m8eSOF3lw/VEiUYs3Wl+leqAK0zBZmriC\ngc4U3j0d5bnf1BAIRuJdbsylJTnJSIZAoIHzTV2EIzNrRncRiQ8FDxGZETp6B+nz92EzeijI8sW7\nnKtyO2089sACVhZFiHrbqRus/tDtCnyFALxyfN1kljcrmUaUL33k3/n0LQexiLK//XUq+8uxm3aK\nklbT3phMyakwP3y1blZ8EM9J8+B1DxMY7qSpoz/e5YjIDKDgISLTnmVFaeroJxRqZW6aG5stfqNX\nXY+0JCeffSCfoqIAXdE6WgPNl22zOLEIA4ODFUX0+L1xqHJ2MQx4/J7f89m7/gDAWx37KOs9gdN0\nsiJ5NQ21iRw+EeCnbzTM2NnNPygv3UM41El7T79mNxeRG6bgISLTXkvXAEOBbjzOECkJkzc54ERY\nlJMwOtJVXeAsfaFL543w2RPI9eQTtmz8tnRtnKqcXQwDHr7tTb54/ysAvNP1FqXdJbhtHpYlreJ8\nlY83jvXx6jutca409txOG2lJNoaDHRrlSkRumIKHiExrlhWlpaufYKiN3HR3vMsZl83LU7l/UyqL\nFw9xtv80gUjgkvXLklYA8IvDtzAUnF7Bajr7xM3v8JWP/wrTsDje8w5V/WdIsCeyOGE5Z894eelg\nB0cquuJdZsxlp7qIWt109/czGAjFuxwRmcbGDB4HDhzgwQcfJC8vD9M02b1792XbfPWrXyU3Nxev\n18udd95JeXn5VV90//79rF+/Ho/HQ2FhIc8///z4z0BEZrWBoSCh8BBeVxSf2x7vcsbtT26Zy6bV\nHvLmD1DRd4qw9f4HvDzPfDJcWXT7E/jl2zfHscrZ5/61pfyXB0ZaPg517qM10EyKM415ziWUl7v5\nyetNnK2f2f0f7DaTlEQHkUg/vf7A1XcQEbmCMYOH3+9n9erVPPvss3g8nstm/X3qqad4+umn+c53\nvsPRo0fJzMzk3nvvZWDgyrO81tTU8MADD7BlyxZKS0t58skn+eIXv8iePXsm5oxEZFbpGxzGsgZI\n9Ezf0AEjI13tvG8+61bYmJPZw9n+cqzoSAdmwzAoThkJHD87dCt9Q1N3xK6Z6MENJey46QjWe6Nd\n9Yf6yPbkkGrMp6zCxQ9euUBT58yeYDDRYycS9tPn19C6IjJ+YwaP7du387WvfY0//dM/xTQv3TQa\njfLMM8/w5JNPsmPHDlasWMHu3bvp7+/nhRdeuOIxn3vuOfLy8nj22WdZunQpn/vc53j00Uf51re+\nNTFnJCKzSu9AgEhkgETv9A4eAF6Xjcc/soDVKyKYie2cH6gc7cCc48kjx52Hf9jNj964M86Vzj5f\nuO93bCg8R8AK8Ie2VwlbIeZ7F+IMZHO63MHzv6mlZ2Dm3oaU5LVjRQcZGAoSmQUjeolIbIy7j0dN\nTQ2tra1s27ZtdJnb7Wbr1q0cOnToivsdPnz4kn0Atm3bRklJCZHIzB8bXUQmTjhiMRQMYhDE554Z\nE+ylJTl5/CMLWLk8yJCjkYahutF1G9NuwcDgpZKbKK2dH8cqZx+babHrz/6NeWkddAc7Odx5AIDF\nicsY7knjRJnBP7xSy3BoZv4dM00Dn8skHBnEr34eIjJO4w4eLS0tAGRlZV2yPDMzc3Tdh2ltbb1s\nn6ysLMLhMB0dHeMtR0RmoUjEIhqNYLdx2a2g01l+ppfP3J/P8uUB2iLVtAVG3lNTnemsmbMegG++\n/HECIUc8y5x1EtwB/vunfoHLEeTcwFmq/ZWYho1lSSvpbEnm2OkQ//S7C1jWzBxm1243IBohYqnF\nQ0TGJyb3JsTiA0BJSUlc95dro+sce7rG7wuEIlS3dOG0NYF/Ykd7upaBMmLJBDYtDNLe3svZqhAB\n+zCJtiTyowupNqto6oYf/OFu/o/7fxvXOmebgsw2/s/tr/LNlz/O4Y4DeIcTcZsecqx8Ks8MEAi0\nMNjXzrY1vikThifqd7mpK0R/oIv+jk7m+DS62h/Te/Pk0HWOvRu5xosXLx5z/bhbPLKzs4GRFowP\nam1tHV13pf3+uEWktbUVu91Oenr6eMsRkVnINAAMZugXzKwv9LB1lZMFBd3UhaoIWEOYho113psx\nMPjlkU0cPLM03mXOOtvXHmdj4TlC0RAnhkqIRqO4TDcFjsVcqEvhUFmId87N1M7mBuYUCVQiMv2M\nu8WjoKCA7OxsXnvtNdavH2n6DwQCHDx4cMyO4ps3b+bFF1+8ZNnrr7/Oxo0bsdmufI/2hg0bxlXn\nxdQ23v3l2ug6x56u8eXCEQvnuSaGAy6WL0yakGNe/HZ4+fLlE3K8G1VUFMWbfIHfu/1cOH+BVcnF\npJgp+B39lHQf5hu/2sFzj32fvLSZP5/EVGEY8Ncf+zX/4Xv/meZgA73OLgoSFpFCCu5hN7VNZRyp\nHmTdylzWFibHrc6J/l12NAwQiuZSNH8eST7XhBxzJtB78+TQdY69ibjGvb29Y66/6nC6paWllJaW\nYlkWdXV1lJaWUl9fj2EYfOlLX+Kpp57ixRdf5PTp0+zcuZPExEQeeuih0WM88sgjPProo6M/f/7z\nn6exsZEvf/nLVFRU8IMf/IDdu3fzN3/zN+M+SRGZnew2E4/TSRQn/kA43uXEhGEY/NU989i4yklm\nbh9n+k4RiUZYmbyWfG8B/mE3//dPH2IgMD0nT5yuspJ7+fy9rwNwtOsQYWvk9y/dlclceyEVFR7+\n6bf1VDf741nmhLGsKP5hC7vNg8+tvkUiMj5jBo+jR49SXFxMcXExgUCAXbt2UVxczK5duwD427/9\nW7785S/zhS98gY0bN9La2sprr72Gz+cbPUZ9fT319fWjPy9YsIBXXnmFAwcOsG7dOr7+9a/z7W9/\nmx07dsToFEVkJkvyubDZEugfnJnBA8BhN/nc9gWsXQmelC4q+ysA2JpxNymOVOo70/nv//pJIta4\n756Vcfjo+mMszGzFHxngbH/Z6PIczzwSI7mUlTv5h3+vo71n+s990T8UxjS8JHhc2Gz6PROR8Rnz\n3eOOO+7AsiwsyyISiYw+/9GPfjS6za5du2hqamJoaIi9e/de1qS7d+9e3njjjUuWbd26lWPHjhEI\nBDh//jyPP/74BJ6SiMwmSV4XpumjbwYHD4BEr53Pf6SA1SvCWJ5WavznsBsO7sn6CG6bh5LqQr77\n2/viXeasYhpRPnvXHwA40XOMkBUERlqpFvqWgD+Tk+U2vv9KLYPD03uY3f7BMDa7T7dYicgN0dcW\nIjKtJXpdOOxeBoeNaf/h7moyU1x87iPzWbF8mF6znuZAIwmORO7KvB/TMHnx6M38wx/uJjpDO9tP\nRZuXVLIir55hK0B538nR5YZhsCRxOQMdcygtt9j92vQdZjcSidI9EMJmSyTJq+AhIuOn4CEi05pp\nGmSlJOB0ZNDYPlNHEnrfopwE/mpbLkVFQzSGqugcbifLPZet6fdgYPDCwdv4/159ACuqkYcmg2HA\no3f8/+3deXhU9aE+8Pcss09msu97CGQBwo4QBbVAFRFQKxS0CtZuWn8utdfCxdrbqsXeVh9bl2uv\nLYJdbG+vV6u1CiqiKCpLEshKQkhCyELWSWbLbOf3RzBKWWUyOcnk/TxPniRnzsy8OeJk3nzP93ve\nAwDU9FUioHx+jQtZlJFnmYLjjWZ8fNCJVz5qVSllcNp63IBgRaTZDJOBy+gS0cVj8SCiMS8x2gy9\nLgpOj4xee/hfVXnWxCjcsDAB+fkuHHFWwubtRZZ5Aq44OfLxyt45eOzVFZzzMUJmZtcjKbIHDr8d\nLa5jp9yml/SYGFGIw4cNePPjbuypHFurjw14/eiw+aDVxCE1bnhWjiOi8Yu/lYhozJMkEcmxEdBo\nEtDa7R6zp7R8GYtnxOGrc6MwMc+Jmv5DcPjsyDBlYXHCNZAFGdvLpuE//vY1eHxnX6achocoKFg6\n4wAAoKb/9Iv1WTWRyNBPQlWVHn965zjqWuwjHfGiHe90Q5ZjEBcZAYOOq1kRUXBYPIgoLMRajYgw\nWuELWNDQ7lQ7TsgJgoCvXZaMhTPMyJ7gQFX/Qbj9biQb0rAk8VpoRS0+qCrAppfWwO3lG8ZQu3pa\nCUQhgGZnI7yB00fdEvRJiBLSUVWlx+/eaEJXn0eFlF9OW7cbdpcGel0skmMj1I5DRGGAxYOIwoIg\nCMhJjoLRkAS7S4fjneE/30MUB6/xMa9Ij5T0flT2HYQ34EGCPglXJa6EXtRj75EJ+Lc/3Ay7m5OC\nQykmwo4JiW0IIIATA21n3CfTmAPBGYfyKgn//UYD3J7RuxhCd78HbT0B6HSpyEmOhkbmyBkRBY/F\ng4jChk4rY0JKDPT6FHT2YUz8VTlYGlnEN6/OwKwpMmKTelF18gKDMbpYXJ10HYySCYeaMnDftlvR\n4zCd/wHpok3POgoAaHU1n/H2z1a6snVYUVLhx4tvHxuVpwU63D4cOzEAnS4N6QnRXEKXiIYNiwcR\nhSNhOS8AACAASURBVBWzQYvMxGjodGlo7vCMi/Jh0En4zrJMTJ8MGGO6Ud1XjoASQKQ2CkuTrkOE\nbEFtazK+9dx3UNqQoXbcsDU9c7B4tLvPvnrV4EpXk9HUYMKHpQ7845Mzj46oxe7yob7VCY02BUkx\nUYiPYlklouHD4kFEYSfGakRqXDR0+kwc6/ChtcutdqSQs5o0+N61WSgq9EOM6ECdvRqKoiBCY8HS\npOsQr0tEV78FP9h2K7a+txD+AJfbHW7ZCScAAP2+vnPuZ5CMmGgeXOnq9Y868Wl1z0jEO68euwdH\nWlyQ5DTEWmOQFm9VOxIRhRkWDyIKS0kxEchKioNBn4kOm4jGdieUML+yXlykDt+9NhNTCz0Y0LWi\nwXEEiqLAKJtwddJKTLXOREAR8cKuK3D/i7egs58ThodTtNkOUQjA5XcioJx7/kakNgpp2lxUVRnw\nx7eP42ibY4RSnll7jxuN7V5odRlIjo1DTkq0qnmIKDyxeBBR2Iq1GjExLR5GYyZsTj3qWhzw+gLn\nv+MYlh5vxLeuyUBhgRu9YtPQdSVEQcTM6Ln4auK1MEgGlDZk4fb/+i4+qZ2gcuLwIYkBRJsHl8p1\n+s+/slqiIQUWJRWV1Vo8/0Yjeuwjf1pgIKCg6YQTbT2AQZ+FzMR4jnQQUciweBBRWLOYdMhLj4XF\nnI4BXxSqj9nR3R/e8z4mpUXgtqvTMLnQhTZ/3SlzDpINaViRshrJhjTYnCb86E8349ntS+D1c9Wi\n4aCVfQAA/3lGPD6TZZqAgD0W5VUinn+jEQPekVvpyuH2oabZjl6HAUZDJiakxnFOBxGFFIsHEYU9\ng06DvPRYxEWlQtZk4FhHAEfbHPD5w3f0Y/qESHz9yiQUFLjRNFCDbk/n0G0GyYglCcswM+oSCBDw\n1z3z8f+2rEdLT5SKicODY2BwBSitqL2g/UVBxKSIQnS1WXGgwou/7Dwe8lMCFUVBS5cLdccHoCAJ\nUZYM5KXHI9KsD+nzEhGxeBDRuKCRJUxIiUZOciJMxmw4BqyoarKrcnrLSFkwNRYrLo1FXr4TdY4K\n9HltQ7cJgoCpkTOwNOk6mCQzqo+n4lv/9V389aN5HP0IgvNk8dAIF1Y8AEAjapBvmYyGehN2lfZh\n18GuUMWDc8CP6mN2dPbpoddnIS0hGfkZsTDqeZFJIgo9Fg8iGldirEYUZsYjNnJw9KPpRAC1x+1w\nDozei7kFY+ncBCyeE4mJk5yo7j8Ep+/USczx+kSsSFmFDGM2nB4dnt3xVXzz2e9x7sdFaOu1wuuX\noRV1kIQvV96MsgnZpjzUVOvxt12tqD1uH9ZsHm8Aje1O1Da7oSAJkRHpKMhMRHJsBASBK5wR0chg\n8SCicUerkZCbGoPs5EREmHLg8cfhcLMbR9sc8PjCa+UrQRCwemEKLptuQlaOHZX9ZXD7T72qu07S\n48qEq7A44RpYNJE41hWLH/3pZmz401o0d3F1owt1qGnwGikJusSLejMfq4tDjJiB6mo9XniraVhG\n43x+Bcc7XahqcqDfbYXBkIPU+CQUZMZxlIOIRhyLBxGNW7FWIyZnxSMtPhUm4wQ4BqJQ3+5DW68v\nrFa/EkUBty5Jx/xpeqRm9KPCVoYB/8Bp+6UaM7AyZTVmR8+HRtDg49qJWP/MnfivHYuH5i7Q2ZWd\nvDhjgj75oh8jw5gNOGNRUS3ihbeaLnoeUiCgoKvfh/p2L7rtJuj1OUiKTceU7ESkxFk4ykFEqmDx\nIKJxTZJEpMRZMCU7AcmxaRCFVPQ6TKhsdOBYhwtuT3icgqWRRdy+NANzizRISOtDZV8ZvIHT/6Iu\nCRImW6fh+tSbkGvOgy8g4S8fFeOWp76PN0unIaDwDeuZDHhlvF9VAABINqRe9OMIgoCJEfnobIvA\n/goPXt599qugn4nPH0BbtxuVjXZ09OmhIAXx0RkozEpEZmIktBrO3yEi9bB4EBFhcPJ5RmIkshOt\nsBoToNPnwOaMQPUxF460ONDn9KodMWh6rYTvLMvE7KkiohN7Udl3EL6A74z7GmUjLo27EsuSb0Cc\nLgHd9gg89upK3Pm7b+JQU9oIJx/93iydhn63AbHaOMTo4oJ6LI2oxSTzZBypM+DtvT34pKr7vPdx\nDfjRdMKJigYHOvoMkDSZMOmTkBEXiQkp0TDoeFoVEalPVjsAEdFootNISI01YXJ2Ek70WNBpc2DA\na8PRtm7oZDfiInWIjtCM2VNVTHoZ37s2Cx7fEewt6UFV5yEUWKeedTJ0nC4B1yRdjyP2w9jXswfV\nx1Px/7Z8E9Myj2JN8W7MzjmCMXooho3drccfPlgAAJgcOX1YHtOsiUCGYSKqq6vwZ0MLkmL0SI83\nnrafzeHFid4BONwCZDkKBkMUIs1GJESbITo6z/DIRETqYfEgIjoDvVZGeoIVybER6LRZ0NEbDae7\nH8e7utHS1Y8oswbRFi2MurF36orVpMGdy7PxpO8I9pV2oaa3AnmWyRCFMw+CC4KACRGTkGHKwiFb\nCSptB1HakIXShizkJrVgbfFuXJZfBUkMr4n5F+rJN5ais9+CWG08Mo05w/a4Cfok2O19qKo5ht//\nsxH3r8qF2SBjwOtHd58XPXYPvH4dNHIiIsxWxFqNiLMaodPyVzsRjU58dSIiOgdZEpEYbUZClAk9\n/Rac6I1Ev9OBXmcfuvpt0Mo+REdoEGXWQqsZO2evxli0uHNFFp7012N/6Qkc7q/CpIiCc47kaEQt\nZkTNxWTrNFT3VaDCVoba1mT8x99WISW6C9fP+QRXTSuFURe+10b5V9vLpuLtQ1MhCzIWxC8a9pGw\nLFMuym0OHKzqwLOvHcXySxLh8gqQJCtkORmRJhPiI02IsRggSWPn3x8RjU8sHkREF0AQBERbDIi2\nGOAasKKrLwrdfS64PXacsNnQ2t0Pkw6INGsQadZAI4/+N4EJUXrcsTwLT/rqUXKwFXV2ERPMeed9\n86wVdZgaOQMFlqmotVej3FaC493Ab95cit+9+xVcPb0E1835FCnR55+bMJa9V1GAx15dCQCYHV0M\nqyZyWB8/EAA8PiBZmoTKow74RTtMBj8Wz8pHtMWIGIsBEUauNkZEYweLBxHRl2TQaZAap0FKbAT6\nHFZ090ej1+6Gx2tHa08fjnfZYdAqsBg1sJhkmPSj96U2Nc6AO1Zk4inlKErLWlDvkJBtyr2gv9zL\noox8y2RMiihAk/MoKm0H0T7Qiv/95BK8/MlczM2txeKpZZg3sRYGbXiNguw4OAWbX7kOAUXEVOsM\nTIooGJbH9fkVeH0BeHwBeP0KBGggiVZkGWaj+dgBlMT04SszgMzE4S05REQjYfT+NiQiGuUEQYDV\nrIfVrEcgoMDmcKO7z4U+5wA8Xie67HacsNkhCU5EGGVYTDIsBg0kaXTNxs5KNOG712biaX8Dyg4e\nQ6NTQoYx+4JPGxIFEZmmHGSactA10IGqvkOod9Ti49qJ+Lh2InSyF3Nya3F5QSXmTTw8pkuIy6PB\n029dhX8cmAkAKIqciemRcy76FCtFAbz+ADzeALy+APyKCFGQIQh6yJIGWlmCViMhVhsJrdOL+roK\nbH2rDClxEUiKiRjOH42IKORYPIiIhoEoCoiKMCAqwgBFUdDv9MDmcMPmGIBrwAX7gB02hx0BpR8m\nvYgIw+BIiEkvQRTVLyK5KWZ8e1k6ng004uChRoguCenGzC/9ODG6OFwadyVmRc/DEfthHHXUoWOg\nHR9UFeCDqgJoZS/mTqjDwoIKzJt4eMzMB1EU4MDRbDz5xlIc64qFJIiYFTUf+ZYpX6p0KMrgtTZ8\nfgXek6MbgAxB0EIQNNBKMrSawbKhlaVTHjvFmIV+Ww8qqlrw29f3Y8Pay3hdDiIaU1g8iIiGmSAI\nsJh0sJh0SAPg9vhgsw+WkH6nG16/E539TpzodSKgOGHUiTDpJZgNMsx6WbURkYIMC25fmo7fBppw\n6FA9JKeIFGP6RT2WXjKg0FqEQmsR7L5+NDrq0eA4ghMDbfigOh8fVOdDI/kw52QJmT/pMEy606+m\nPhocbEzH73deibLGTABApCYaC+MXI1obc977fjai4fMpg5/9CgAJgiBDEGRIkgxZ+rxoaOSzFwlB\nEJBrKUJpRx9KK/vxl53l+MaSouH5IYmIRgCLBxFRiOm1MvTRZiREm+H3B9Dv8sB+8sPh8sDnd6HH\n4URXnxP+gB0GLWAyyDDqJBh0EgxaccSuG1KUY8X6q1Pxu8BxHDpUB9ElIcmQEtRjmuWIoRLi8NnR\n6KhHna0GXf4OfFiThw9r8iAKAWTGn0B+ynHkpzSjIPU40mM7VFuit8dhws7yQuw4WITqlsGfXyvq\nMMU6DQWWIsjimX99+vwKfH4F/sDJshFQIECGIGhOFg0JsiRBlsSTRUOEKF74QgSyKCPPOhPlR3Zj\nR0QTJqXFYk5+cP99iIhGCosHEdEIkiQRkWY9Is16AEAgoAyVELvLA4fbA6/PhT6XC70ONwIBNxRl\nAHqNCINO+kIZkUI2MjJrYhS8PgUvBI6joqIGggtIDLJ8fMYkm1FgnYqkQBpcASd65a6hkZD69kTU\ntycOzZ8wagcwKbkF+SnNyE8dLCPRZvuw5PhXXr+Ewy1JONiUgZKjWdhfn42AMlgItKIWBZYiFFqn\nQisOriKlKIA/oJwsGoGTZUMBIAKQIYgaCJAgS/JQyZBlERpZghhkiTRrLMgwFKKq6iC2vXUQGQlW\nJESbgzwCREShx+JBRKQiUfz8tCwAUBQFTrcXDrcXzgEvnG4vXANe+AMDcAy40edyQwm44Q+4oNMo\n0Gkk6LUi9FoJWlmEXisOy1K+8wqi4fUF8Ee0oryiBnALSNQnB/24X2QQjUi2pqDAOhW+gBddnk50\nDLQPfrjb4fAAJQ1ZKGnIGrpPgrUXiZG9iDLbEW2yI8rsQJTJjmizA9FmO6JMdkSaHNDK/qH7KArg\nC0gY8Mqwuw2wOY1o6YnC8e5oHO+ORnNXDGpbkzDg0wzdR4CANEM6sk0TkaTLgAAZPo8Cd8CHQECB\nL6BAgARBkABhsGRIkgxJEiGLImR58LNGDs1oVaIhHba+LlRWH8dvX9+PH6299JynaRERjQYsHkRE\no4ggCDAZtDAZtEPbAgEFrgEvXB4fnCcLiWvAC5/fgwH/ANxODwL2ASgBLwKKEwL80GtF6DQSdBoR\nOq0IrSxCIwvQfok3wgumxkJRgD+hFeXlNRAgIEGfFJKfWxY1SNAnnfL4Tp8THQPt6DxZRjoHTqDd\nFol22/mXkjXp3AAGRzK8PhkKzv8zW+RIxGmTECMnIU6TDBl6BBQBTrcIQIQgiINFA+LQ6VL/+jFS\np8QNXk1+Kko6elFS2Ye/7qzATYunjshzExFdLBYPIqJRThS/UEasg9sURcGA1w+3xwe3x4eBk5/d\nHh+8fj8CgQE4PR7YBzwIBDyA4kVA8UFRfJAlQCsL0MiDf5HXysLJ04FEyJIw9CEIAhYWxSKgKHgJ\n7SgvrwaAkJWPf2WUjciQs5BhGhzxCCgB9HltcPodcPmdcPtdcPqdcPudcPldcPmdQ9sdA/pTHkuA\nAEmQoRG00Ip6GEUzjJIFRtECkxQJqxQDnWiCIEgQhM+KhgRZECFJAiRRhCSe/Hzy+5EqGWcjizLy\nrTNxqG433jI3YlJ6LGZNGt5RKSKi4cTiQUQ0BgmCMDhpXXv6y7jfHxgsIyeLyYDXB4/Xf/J6EX74\nAz4EFC/cPh9cXi8UxYdAwAcoXigYLCeKEoAoKJAlAckxelxWZEG/qxu1NVVwe/yI1yVh8H23cDLP\nyY+T2Ya24fN9Ps8+ePoTMHh17lMpUPD57Ypy6vd6WKGXLFBEQJGBgKJAUT7/rCiDcy08gQFAECAJ\nGkiQT64iJQCCCAEiAOHkCMZggZBEAaJwslx8VjQkMej5GKFm1lgH53tUH8LWN8uQHm9FfJRJ7VhE\nRGfE4kFEFGYkSTw5QnLm230nC4jH54fX5z+llAxOlB78CCgBKIofAcWPGZNS4fU3w+dvRt3hOnh9\nGkRrEgEoJ0uBcvIDAAbbhHLKtlO/7HcO7hOQvIMbTnl/L0AY2vDFz8IpZQcYbDufFQlAgCAKkEUB\nGmHwMURx8D6flQrxsw/h889qj1wEK8mQAZutC5XVLfjvf+zHv329mPM9iGhUGpbi0d/fjwcffBCv\nvPIKTpw4genTp+PJJ5/ErFmzzrh/Q0MDsrOzT9v+5ptvYsmSJcMRiYiIzuKz+QhGaM65XyAwuGKT\nPzBYRCampSAxNg7/885hVFYcgUE0IkY7uNrVZyMTUAYLh6KcrCKfffEvBGFwo1bzL/M1hMERk6Fq\n8YXvTx1JEYZuE8XPSsbJ78OgTHwZg9f3mIqSEzYcqLDhb7sqseYrU9SORUR0mmEpHrfffjvKy8ux\nbds2pKam4sUXX8SiRYtQWVmJ5OSzn2/61ltvoajo84sfRUVFDUccIiIaBqIoQCtKAD7/6/mqywth\nMerwR10VDh2shFHQIf4iltoNeBwAgBircbjijmuyqEGedQbKaz/Em+YGTEqLVTsSEdFpgl5z0eVy\n4eWXX8bmzZuxYMECZGdn46GHHsKECRPw7LPPnvO+0dHRiI+PH/rQaM791zciIlLfVXMmYM2iPEyZ\nouCouwQn3MfVjkQAIjSRSDcUoKoaeOHNMvQ6PGpHIiI6RdDFw+fzwe/3Q6fTnbJdr9dj9+7d57zv\n9ddfj4SEBFx66aX43//932CjEBHRCFl6SS6+vmgSJk9RcNRVgg53i9qRCECyIRM6TxIqa7z4v0+a\nTl7UkIhodBAURQn6Vam4uBiSJOGll15CQkIC/vznP2PdunXIzc1FVVXVaft3dXVh27ZtKC4uhizL\nePXVV/HII49g69atuOmmm4b2s9lsQ1/X1tYGG5OIiIbZ+5XtePtAJ+rqjEgRCxAlx6sdadzzKV7U\nuPchLasXSy+JwYKCBLUjEdE4kZubO/S11Wo97fZhKR719fW47bbb8P7770OSJMycORO5ubnYv38/\nKisrL+gxvv/97+ODDz5AWVnZ0DYWDyKi0U1RFLxfeWKofKRJhYiU49SONe71+3vR6C9Bfr4T6xdl\nIzWGc2mIKPTOVzyGZXJ5dnY23nvvPbhcLvT19SEhIQGrV69GTk7OBT/G7Nmz8fvf//6st59thazz\n2bdvX1D3pwvD4xx6PMYjg8f5y5s1S8GEnBr8z7u1OHSoHpHGSMTpz30hu46ODgBAXBxLSijEIQ59\nx7vQ2HQU+5p9uOqKaWe85gsFj68ZI4PHOfSG4xh/cdDgTIKe4/FFBoMBCQkJ6Onpwfbt27FixYoL\nvm9paek5V8AiIqLRSRAELC+ehK9dmYspUxTUuw6g3XVM7VjjXpImC56+SByqduCvOyvUjkNENDwj\nHtu3b4ff70deXh7q6urwwx/+EPn5+Vi/fj0AYMOGDdi7dy/efvttAMDWrVuh1Woxbdo0iKKI1157\nDc888wx+8YtfDEccIiIaYYIgYEXxJGgkEX8Ra3DwUCkCSgBJxgy1o41boiAiU5ePhqOVeHtfE6Zk\nx2N6bpLasYhoHBuW4mGz2bBhwwY0NzcjOjoaX/va1/DII49AkgbXfm9ra0N9ff3Q/oIg4OGHH0Zj\nYyMkScKkSZOwZcsWrF27djjiEBGRCgRBwDXzJkIjS/ijUImDBw8igABSjFlqRxu39KIJaYZ81FSX\n48XtB5GdFAWrWa92LCIap4aleNx444248cYbz3r7li1bTvn+lltuwS233DIcT01ERKPMktk50Mgi\ntgrlOHioHAGHH2mmCWrHGreSDZno7m1H5eEObNtehu9fN2dcXdmdiEaPYZ3jQUREBABXTM/C7dcW\nYVqRgPZAFRrtNRiGRRTpIgiCgImWaWht1mLPwRPYVdaodiQiGqdYPIiIKCQunZKO7yyfhulFArpw\nGEftVSwfKtFJekwwT0V1DfCXdyvR2tWvdiQiGodYPIiIKGTmFqTijutmYto0ETbpCI70V7B8qCRW\nnwSrkoaaw378/p8l8PkDakcionGGxYOIiEJqxsQk3HX9LMyYJsKuOYra/oMsHyrJjpiMng4jSipt\neO2jGrXjENE4w+JBREQhNzUnAXd/bQ5mTpfg1jah0VPN8qECWZSRZ5mOuloBr314BEeOd6sdiYjG\nERYPIiIaEfkZcbjna3Mxa4YMv/E4GjyVCCg83WekWbTRSNBOQG2tgm3by+D1+dWORETjBIsHERGN\nmIlpMbj3xkuQN9EDxdyKKtt+BBS+8R1p6aaJcPZG4NBhO17fc1jtOEQ0TrB4EBHRiMpOjsI3Ls9G\nwUQvREsbKnr3whfwqR1rXBEFERMtRag/IuAfe46gsa1X7UhENA6weBAR0YhLjDLg5suzMWeGDvro\nDhzq3QNvwKN2rHHFoo1CnJyFurrBU664yhURhRqLBxERqSLeqscDa4oxb5YRUYm9KOv+EAN+l9qx\nxpUMcx76ukwoq+nDW5/WqR2HiMIciwcREakmLtKEf/t6MYpnWZCUYUdZz4dw+uxqxxo3JEFCrmUq\n6uqAVz+sRUsnLyxIRKHD4kFERKqymvW4f/V8LJwTjYwJLhzq/RD9Xs45GCmR2lhEixmoqwtg61ul\nCAS4zDERhQaLBxERqc6o1+DuGy7BoksSMCHPgwrbHvR6OtWONW5kmQvQfcKA0upevHOgXu04RBSm\nWDyIiGhU0GokfG/5LCwtTkV+oQ/V/Z+g092qdqxxQRZl5Fqm4nAt8PL7NTjR41A7EhGFIRYPIiIa\nNSRJxPqrp+G6y7MweWoAR1z70eZqUjvWuBCti4cVaait82Pb9jJeWZ6Ihh2LBxERjSqCIGDVFYVY\nu3gSpk5V0OQpwzFHHd8Ij4DsiAJ0tuuwv7IL75c1qh2HiMIMiwcREY06giDgmnkT8c1lUzB9moAT\nShWO2qtYPkJMI2qRY56Cw4eBv+2qQq/drXYkIgojLB5ERDRqLZyWiTuum4EZ00T0yUdwuI+nAIVa\nrD4JxkAi6up9+J/3KtSOQ0RhhMWDiIhGtVmTknH312Zj5nQJXsMxVNr2wa/41Y4V1rIjCnG8WcLu\nshZUNXaoHYeIwgSLBxERjXqFWfG4f/U8zJ6phRzZhkM9e+AJDKgdK2zpJSNSDRNx5Ajw53fK4fMH\n1I5ERGGAxYOIiMaE7OQoPLBmPubPMiIqqQdl3bzKeSilGLPhsplRUWvH9r1H1I5DRGGAxYOIiMaM\npJgI/GjtpbhsjhVp2Q4c6v0QfZ5utWOFJVEQMcEyBfX1wGsf1aLT5lQ7EhGNcSweREQ0plhMOty/\naj4Wz0/AxHwPKvs/5oUGQyRSGwuLkIojR/2caE5EQWPxICKiMUenlXHHitlYvjADk6f6ccS1H8ed\n9WrHCkvZ5ny0tcjYc6gNFUdPqB2HiMYwFg8iIhqTRFHATYum4BtX5WPaNAVt/goc6a/gcrvDTCvp\nkWaYiPp64C87KzjRnIguGosHERGNWYIg4Ko5Ewav9TFdhENTjyrbfgS43O6wSjZmwWUzo/KIHe/s\n58gSEV0cFg8iIhrz5uSn4Aer52L2TA1ESysO9nwMb8CjdqywIQoiciImo/4I8PqeWl7RnIguCosH\nERGFhUnpsfjR2mLMm21AZGI3yro/hMvnUDtW2IjSxcGkJOLIUR9e2V2tdhwiGoNYPIiIKGwkx36+\n3G5Klh0Hez9En7dH7VhhI8tcgOZmER+UNeN4R5/acYhojGHxICKisBJp1uP+1fOxaF48cvMGUNm3\nBx3uFrVjhQWDbEKcJgONTQpHPYjoS2PxICKisKPXyrhz5WwsX5iOyVP9OOrejyb7Ya54NQzSzbk4\n0Sbj06p21DZ3qR2HiMYQFg8iIgpLkiTi5sVTsf6aQsyYIaBbrEG17QD8XPEqKFpRh2R9DhobgJc/\nqGKZI6ILxuJBRERhSxAELJqZjXtXzcGcWTJEawsO9nyEAT9XZQpGijEbPZ06HKztQWldm9pxiGiM\nYPEgIqKwNzkrHhtuuhTFc4yITelFac8H6Pf2qh1rzJJFGemmiWg4CryyuxqBAEc9iOj8gi4e/f39\nuOeee5CZmQmj0Yji4mLs27fvnPc5dOgQFi5cCKPRiNTUVPzsZz8LNgYREdE5JcdGYMNNl+Er82Mw\nYZIbFX0fcdJ5EBIN6XD1mVBdb8dHFcfUjkNEY0DQxeP222/Hjh07sG3bNpSXl2PJkiVYtGgRWlrO\n/GLe19eHxYsXIykpCfv27cOTTz6J//zP/8Tjjz8ebBQiIqJzMhu0uPuGS7Di8nRMOTnpvMFew3kK\nF0EURGSa83C0AXj1wxp4vJw7Q0TnFlTxcLlcePnll7F582YsWLAA2dnZeOihhzBhwgQ8++yzZ7zP\nH//4R7jdbmzduhUFBQW44YYb8MADD7B4EBHRiJC/MOl85gwBvdJhVNn2wx/wqR1tzInVJQGuSBxp\ndOPdkqNqxyGiUS6o4uHz+eD3+6HT6U7ZrtfrsXv37jPeZ8+ePbjssstOuc+SJUvQ0tKCxsbGYOIQ\nERFdEEEQ8JWZ2bhn1RzMnaWBFNmKsp6PMOB3qR1tTBEEAVkR+WhoAP75SR2cbq/akYhoFBOUIMeX\ni4uLIUkSXnrpJSQkJODPf/4z1q1bh9zcXFRVVZ22/5IlS5Ceno7nn39+aFtTUxMyMzOxZ88ezJ07\nd2i7zWYb+rq2tjaYmERERGfU2efG/3zUiOojCjrbIpCpnQyTZFE71phS6y5FTGobrl8Qg/l58WrH\nISKV5ObmDn1ttVpPuz3oOR4vvvgiRFFEamoq9Ho9nnrqKaxZswaCIJxx/7NtJyIiUkOsRY91V+Zg\nzmQtUjNtqPeWoMvXqnasMSVBk472E1rsre2Czx9QOw4RjVJysA+QnZ2N9957Dy6XC319fUhISMDq\n1auRk5Nzxv0TExPR1nbqmt/t7e1Dt53NrFmzLirfZytsXez96cLwOIcej/HI4HEeGaPxOM+fWV5X\n6gAAGQBJREFUOwd/2VmBf+5pQGVlIyQAORGTIQpjc+X5jo4OAEBcXFzInytWiYWtux0unw0efQIu\nKcoI+XOOFqPx33I44nEOveE4xl88W+lMhu3V1GAwICEhAT09Pdi+fTtWrFhxxv3mzZuHDz74AAMD\nA0PbduzYgZSUFGRkjJ8XKiIiGl0kScTaRVPw3ZVFmD1bgs/UePJig5z3cT6CICDNNAHHjgHb9x3h\ndT2I6IyCLh7bt2/HP//5Txw9ehQ7duzAFVdcgfz8fKxfvx4AsGHDBixatGho/7Vr18JoNGLdunWo\nqKjAyy+/jMceewz33XdfsFGIiIiCVjwlHRvWzselc42ISe1BSff76PV0qh1r1IvVJcHrMKGuyYED\ntTxVjYhOF3TxsNlsuOuuu5Cfn49bb70VCxYswFtvvQVJkgAAbW1tqK+vH9rfYrFgx44daGlpwaxZ\ns3DXXXfh/vvvx7333htsFCIiomGRkRiJjTdfhq8WxyGv0IMa+8c45qjj9T7OQRAEpBpz0HwMePNT\nHisiOl3QczxuvPFG3HjjjWe9fcuWLadtmzx5Mnbt2hXsUxMREYWM2aDFXdfPRWZiDf7PUIuqqir0\n23ox0TINshj0r8+wlGBIRWNnDaqP2lDZ0IHCLK5wRUSfG5sz5oiIiEaAKApYcWke7l01G3Nna6CJ\nbkVp9wdw+vrVjjYqiYKEFGM2mpuBt/YeUTsOEY0yLB5ERETnUTQhEZu+cRkuv8SCtBw7DvbuRqeb\n8xjOJMmQge5ODcrqOnG0tUftOEQ0irB4EBERXYD4KBMeWFOMZQtTMHmqD/UD+1DfX8m5DP9CFjVI\n0KejtQV4v6xR7ThENIqweBAREV0gnVbGN5dOxzevnYxZM0U4dUdwqGcPl9z9F4mGdLS3A/sOt2LA\n41M7DhGNEiweREREX4IgCLhyRhb+bc0lmD9Xj6iULpT2vI+ugXa1o40aRtkMA6LR2ubD/sM8JY2I\nBrF4EBERXYTc1Bj8+JYFuHpBPPKneHDE9SmO9JcjoATUjjYqJBjS0dYOfFjepHYUIholWDyIiIgu\nUoRRh+9fNwe3LSvA7FkiPMajKO3eDafPrnY01cXpktDXI6OyoRvt3TweRMTiQUREFBRBELB4Vg42\nfqMYC+aZkJRpw8HeD9DuOjauJ55LoowYXTJOtAMfVRxTOw4RjQIsHkRERMMgMzESm76xACuuSMGU\naT40+0pR01cKX2D8Tq5O0KehvR34uLIZgcD4LWFENIjFg4iIaJjotTJuWzodd14/DXPnSJAim1HS\n/T76vb1qR1OFRRMFZcCMplY3Khs71I5DRCpj8SAiIhpGgiBgXmEaHrxlAa4stiJrogMVfR+i2VE/\n7k69EgQBCYY0nGgHPq06rnYcIlIZiwcREVEIJEab8cCaYqxanIVpMwLoFCtQ0fspPH632tFGVIwu\nAd09QFVTx7grXkR0KhYPIiKiENHIElZfORn3rZqN+XO0iEg8gQM9u9DhblE72ogxSGYoHgPaOwdw\nvLNf7ThEpCIWDyIiohArmpCIh9YtxNKF8Sic6kGjdz+qevfDG/CoHS3kBEFAlDYWPT1AZQPneRCN\nZyweREREIyDSrMdd18/Bd1dOxbw5MnSxLTjQtQvdAyfUjhZykbo49PSCE8yJxjkWDyIiohEiCAIW\nFGXgoXULsOSyaORNdqPO/QkO95XBF/CqHS9korRxsPUKqG3uhsfrVzsOEamExYOIiGiExUWa8INV\n83HbtQWYO1uEGNmEA93hO/qhEbUwCFZ0dftR29yldhwiUgmLBxERkQpEUcCS2Tl4aN0CLL4sChML\nXIOjH7bSsBz9iNLFobcXqG7qVDsKEamExYOIiEhFSTER+LevF+P2FQW4ZI4EMeoY9ne/h66BNrWj\nDSuzbIXDAbT3ONSOQkQqkdUOQERENN6JooDFs3IwJTsB294qw4GqbtTW7kWbKxE5EYXQS0a1IwZN\nLxnhdgOdNqfaUYhIJRzxICIiGiUSo824f/V8fHvlZMy/RIYlqQ0lPe+hyVGLgBJQO15Qvlg8eCFB\novGJxYOIiGgUEUUBV87IwsPfvAI3LE7B9Jl+9OuqcaBrF3o9Y3d+hCxqgIAGdpcPdlf4X7+EiE7H\n4kFERDQKWc16fPOaGdhw8zx85VIzsibZcdi1B9W2A/D43WrHuyifjXp09bnUjkJEKmDxICIiGsXy\n0mPx4C0LcfvKfMybK0Efdxz7e3biuPPomDtlSS8ZMcB5HkTjFieXExERjXKyJOKqORMwe1Iy/rKz\nAh+Xt6Gurhzt3ceQE1EIqzZG7YgXRBIk+P2A18eLCBKNRyweREREY0SM1Yg7Vs5G8eQ2/GVnBaqP\n2FDT8BGMjgRkmvNg1ljUjnhO3oAHGi1gNmjVjkJEKmDxICIiGmOKJiQiPyMOO/YdwZufHkFDUzsq\njp2AVUxBpnnSqF1+16t4oJFZPIjGKxYPIiKiMUirkXDNvIlYUJSBf35Sh3cPNKChqRklx1sQr82A\nQYmCRhhdb/C9AQ80GhYPovGKxYOIiGgMizDqsOqKQnxlRhZe23MYH5Q1o7HpKKp7DiNWSkNUIAqy\nODp+3ftYPIjGtdHxSkRERERBibEase6qaVg8MxuvfliDN96vQGtrLfZ1dSPFmIMkQ8bgtTRUYvfa\nIGt9sJi00Gv59oNoPOL/+URERGEkJc6CO1bORpLeiffK29Dl8qC5uQp7Ow4jTpeGFGM2DLJpxHO1\nu5uRkADMzkuGIAgj/vxEpD4WDyIiojCUFmvCzQuzYYzNwNv761Fa24GWlgaUtTUiQkxAijEbVk30\niJSAgOJHh7sZ0xKA+YVpIX8+IhqdWDyIiIjClCAIKMyKR2FWPFo6+/HOgXrsqTiO5uNtqDveBrHf\nihRjNuL0yRCF0F1TuNF+GNZoD3LTrUhPsIbseYhodGPxICIiGgeSYyPwjSVFWHlpHnaVNWJnSQOa\nWmw43lyC+s4KxGgTEKtPRqQ2dlhLSPdAO9q9RzA7V8Dar0zhaVZE41jQryw+nw8bN25EdnY2DAYD\nsrOz8eCDD8LvP/tVSRsaGiCK4mkf27dvDzYOERERnUOEUYdl8yZi87e/gntWF+HqKy2YMcsDU/Ix\nNAU+wSed21FjK0X3QDsCSuCin0dRFBx3HsVhxz4UFipYfmkuspOjhvEnIaKxJugRj0cffRTPPfcc\ntm3bhilTpqCsrAzr1q2DTqfDpk2bznnft956C0VFRUPfR0XxBYmIiGgkaGQJxVPSUTwlHa1d/dh/\nuBX7D7fgaEs/OjuP4VjHMVR3ahCliYNZY4VJtsAkW6AVdecctfD4B9A10IZWVyNkkw1FRcCKy3Jw\n7fyJI/jTEdFoFHTx2Lt3L5YvX45rrrkGAJCeno5ly5bh008/Pe99o6OjER8fH2wEIiIiCkJSTASW\nzYvAsnkT0drVjwOHW7H/cCvqW/rQ29sCh70Fxx2AwwYofi1MsgUGaXBlrIASQEDxQ0EAnsAAnEov\noqMUZKQDuZkGrLq8ENNzk1T+CYloNAi6eFx99dV47LHHUFNTg0mTJqGyshI7d+7Exo0bz3vf66+/\nHm63G7m5ubj33ntxww03BBuHiIiIgpAUE4Fr5kXgmnkT0d5tR93xbjR39KG5sw/NHX3o7ffAYe+E\n290JQQAEARDFwc8aDRAdJaEwMxbTJiRidl4KtBpJ7R+JiEYJQVEUJdgH2bhxIzZv3gxZluHz+bBp\n0yb89Kc/Pev+XV1d2LZtG4qLiyHLMl599VU88sgj2Lp1K2666aah/Ww229DXtbW1wcYkIiKiICiK\ngj6XFyd63bA5PZBEEZIoQJIEyKIAWRKRGmOEjmWDaFzKzc0d+tpqPX0Fu6BHPH79619jy5YteOml\nl1BYWIiSkhLcfffdyMzMxG233XbG+8TExODee+8d+n7GjBno6urCL37xi1OKBxEREY0egiDAatTC\natSqHYWIxqCgRzwSEhKwadMm3HXXXUPbHnnkEbzwwgtfapRi69at+N73vgen0zm07YsjHmdqTRdi\n3759AIBZs2Zd1P3pwvA4hx6P8cjgcR4ZPM6hx2M8MnicRwaPc+gNxzE+33v3oJfTVRQFonjqw4ii\niC/bZ0pLS5GcnBxsHCIiIiIiGoWCPtVq5cqV2Lx5M7KyslBQUICSkhI88cQTuPXWW4f22bBhA/bu\n3Yu3334bwODohlarxbRp0yCKIl577TU888wz+MUvfhFsHCIiIiIiGoWCLh5PPPEELBYL7rzzTrS3\ntyMpKQnf/va38eMf/3hon7a2NtTX1w99LwgCHn74YTQ2NkKSJEyaNAlbtmzB2rVrg41DRERERESj\nUNDFw2Qy4Ze//CV++ctfnnWfLVu2nPL9LbfcgltuuSXYpyYiIiIiojEi6DkeRERERERE58PiQURE\nREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQURERERE\nIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfi\nQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQURE\nREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQURERERE\nIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfiQUREREREIcfi\nQUREREREIRd08fD5fNi4cSOys7NhMBiQnZ2NBx98EH6//5z3O3ToEBYuXAij0YjU1FT87Gc/CzYK\nERERERGNUnKwD/Doo4/iueeew7Zt2zBlyhSUlZVh3bp10Ol02LRp0xnv09fXh8WLF+Pyyy/Hvn37\nUFVVhfXr18NkMuG+++4LNhIREREREY0yQRePvXv3Yvny5bjmmmsAAOnp6Vi2bBk+/fTTs97nj3/8\nI9xuN7Zu3QqdToeCggJUV1fj8ccfZ/EgIiIiIgpDQZ9qdfXVV+Pdd99FTU0NAKCyshI7d+7E0qVL\nz3qfPXv24LLLLoNOpxvatmTJErS0tKCxsTHYSERERERENMoIiqIowT7Ixo0bsXnzZsiyDJ/Ph02b\nNuGnP/3pWfdfsmQJ0tPT8fzzzw9ta2pqQmZmJvbs2YO5c+cCAGw2W7DRiIiIiIhohFmt1tO2BX2q\n1a9//Wts2bIFL730EgoLC1FSUoK7774bmZmZuO222854H0EQgn1aIiIiIiIaQ4IuHo888gg2bdqE\nVatWAQAKCwvR2NiIn//852ctHomJiWhraztlW3t7+9BtREREREQUXoIuHoqiQBRPnSoiiiLOdQbX\nvHnz8MADD2BgYGBonseOHTuQkpKCjIyMof3ONERDRERERERjT9CTy1euXInNmzfjjTfeQENDA/7v\n//4PTzzxBK677rqhfTZs2IBFixYNfb927VoYjUasW7cOFRUVePnll/HYY49xRSsiIiIiojAV9IjH\nE088AYvFgjvvvBPt7e1ISkrCt7/9bfz4xz8e2qetrQ319fVD31ssFuzYsQN33nknZs2ahejoaNx/\n//249957g41DRERERESj0LCsakVERERERHQuQZ9qNZq1trbi1ltvRXx8PAwGAwoLC/H++++rHSts\nZGZmQhTF0z6WLVumdrSw4vP5sHHjRmRnZ8NgMCA7OxsPPvgg/H6/2tHCSn9/P+655x5kZmbCaDSi\nuLgY+/btUzvWmPb+++9j+fLlSE1NhSiK2Lp162n7/OQnP0FKSgqMRiOuuOIKVFZWqpB0bDvfcX75\n5Zfx1a9+FfHx8RBFEbt27VIp6dh1rmPs8/nwwAMPoKioCGazGcnJybjppptw7NgxFROPTef7t/zg\ngw8iPz8fZrMZ0dHRWLRoEfbs2aNS2rHpQl6XP/Od73wHoijiV7/61bA9f9gWj97eXhQXF0MQBLzx\nxhuorq7GU089hfj4eLWjhY39+/ejra1t6OPAgQMQBAGrV69WO1pYefTRR/Hcc8/hN7/5DWpqavDk\nk0/imWeewc9//nO1o4WV22+/HTt27MC2bdtQXl6OJUuWYNGiRWhpaVE72pjlcDgwdepUPPnkkzAY\nDKctpf7YY4/h8ccfx1NPPYW9e/ciPj4eixcvht1uVynx2HS+4+x0OnHppZfi8ccfB8Al7S/GuY6x\nw+FASUkJNm3ahJKSErz66qs4duwYrrrqKv6B6Es637/lvLw8PPPMMygvL8fu3buRlZWFr371q0Mr\no9L5ne8Yf+Zvf/sb9u7di+Tk5OF9zVDC1IYNG5RLL71U7RjjysMPP6xERUUpbrdb7ShhZdmyZcq6\ndetO2XbLLbco1157rUqJwo/T6VRkWVb+/ve/n7J95syZyqZNm1RKFV7MZrOydevWoe8DgYCSmJio\nPProo0PbXC6XEhERoTz33HNqRAwL/3qcv6ijo0MRBEHZtWvXCKcKL+c6xp+prKxUBEFQysvLRyhV\n+LmQ42yz2RRBEJTt27ePUKrwcrZj3NDQoKSkpCjV1dVKZmam8qtf/WrYnjNsRzxeeeUVzJkzB6tX\nr0ZCQgKmT5+Op59+Wu1YYUtRFPzud7/DzTffPLREMg2Pq6++Gu+++y5qamoAAJWVldi5cyeWLl2q\ncrLw4fP54Pf7T/u3q9frsXv3bpVShbejR4+ivb0dS5YsGdqm1+uxYMECfPTRRyomIwqezWYDAERF\nRamcJHx5PB789re/RUxMDGbOnKl2nLDh8/mwZs0aPPjgg5g0adKwP37YFo/6+no888wzmDBhArZv\n3467774bP/rRj1g+QmTHjh1oaGjAt771LbWjhJ077rgDN910E/Lz86HVajF58mSsW7cO3/3ud9WO\nFjYiIiIwb948PPzww2hpaYHf78cf/vAHfPzxx6dd7JSGx2fHNSEh4ZTt8fHxPOY0pnk8HvzgBz/A\n8uXLkZycrHacsPP6668jIiICBoMBv/zlL/GPf/wD0dHRascKGw899BDi4+Pxne98JySPH/RyuqNV\nIBDAnDlz8MgjjwAAioqKUFtbi6effhp33nmnyunCz3//939jzpw5mDJlitpRws6vf/1rbNmyBS+9\n9BIKCwtRUlKCu+++G5mZmbjtttvUjhc2XnzxRdx2221ITU2FJEmYOXMm1qxZg/3796sdbdzhHAQa\nq3w+H26++Wb09fXh9ddfVztOWLryyitRVlaGzs5O/Pa3v8W1116LTz/99JQLUNPFee+997B161aU\nlpaesl0ZxgVww3bEIzk5GQUFBadsy8vLQ1NTk0qJwteJEyfw97//naMdIfLII49g48aNWLVqFQoL\nC3HzzTfjvvvu4+TyYZadnY333nsPDocDzc3N+Pjjj+HxeJCTk6N2tLCUmJgIAKdNCm1vbx+6jWgs\n+ewUlfLycrzzzjs8zSpEjEYjsrOzMWfOHDz//POwWq144YUX1I4VFnbt2oXW1lYkJSVBo9FAo9Gg\nsbERDzzwANLT04flOcK2eBQXF6O6uvqUbYcPH0ZmZqY6gcLYCy+8AL1ejzVr1qgdJSwpigJRPPV/\nVVEUh/UvEPQ5g8GAhIQE9PT0YPv27VixYoXakcJSVlYWEhMTsX379qFtbrcbu3fvxvz581VMRvTl\neb1erF69GuXl5di5cydX0BxBfr8fgUBA7Rhh4Y477sChQ4dQVlaGsrIylJaWIjk5Gffddx/eeeed\nYXmOsD3V6t5778X8+fPx6KOPYtWqVSgpKcFvfvMb/pV4mCmKgueffx5f//rXYTQa1Y4TllauXInN\nmzcjKysLBQUFKCkpwRNPPIFbb71V7WhhZfv27fD7/cjLy0NdXR1++MMfIj8/H+vXr1c72pjlcDhQ\nW1sLYPD018bGRpSWliImJgZpaWm455578OijjyIvLw+5ubl4+OGHERERgbVr16qcfGw533Hu6elB\nY2Mjent7AQC1tbWwWCxISko6bY4Nndm5jnFycjJuvPFG7Nu3D6+99hoURRmapxQZGQm9Xq9m9DHl\nXMc5MjISjz32GJYvX47ExER0dHTg6aefRktLC1atWqVy8rHjfK8XcXFxp+yv0WiQmJiI3Nzc4Qkw\nbOtjjUL/+Mc/lKKiIkWv1yuTJk1SfvOb36gdKey8++67iiiKyt69e9WOErbsdrvygx/8QMnMzFQM\nBoOSnZ2t/Pu//7syMDCgdrSw8te//lXJyclRdDqdkpSUpNx1111KX1+f2rHGtJ07dyqCICiCICii\nKA59vX79+qF9fvKTnyhJSUmKXq9XLr/8cqWiokLFxGPT+Y7zli1bznj7f/zHf6icfOw41zFuaGg4\nbftnH+dbDpZOda7j7HQ6leuuu05JTk5WdDqdkpycrKxcuZLvP76kC3ld/qLhXk5XUBSer0FERERE\nRKEVtnM8iIiIiIho9GDxICIiIiKikGPxICIiIiKikGPxICIiIiKikGPxICIiIiKikGPxICIiIiKi\nkGPxICIiIiKikGPxICIiIiKikPv/wK8a8hAa350AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e77842e8>"
       ]
      }
     ],
     "prompt_number": 82
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In this result our final estimate is not as accurate as the previous example. Why is that? The two radar stations were no longer othogonal to the aircraft's position so the triangulation is not optimal. Imagine standing on the ground and trying to triangulate on an aircraft in the sky with a transit. If you took a measurement, moved the transit 5 meters and took a second measurement the tiny change in angle between the two measurements would result in a very poor measurement because a very small error in either measurement would give a wildly different result. Think of the measurements as two nearly parallel lines. Changing the angle between them slightly will move the intersection between the two by a large amount. If you were to take the measurements from positions 100km apart the lines might be nearly perpendicular to each other, in which case a small measurement error would result in a very small shift in the intersection point."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Unobserved Variables"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's say we are tracking an aircraft and we get the following data for the $x$ and $y$ coordinates at time $t$=1,2, and 3 seconds. What does your intuition tell you the value of $x$ will be at time $t$=4 seconds?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import mkf_internal\n",
      "mkf_internal.show_position_chart()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx8AAAGdCAYAAABzQ85fAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKf4f56q07wtUXl8AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e78df470>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It appears that the aircraft is flying in a straight line because we can draw a line between the three points, and we know that aircraft cannot turn on a dime. The most reasonable guess is that at $t$=4 the aircraft is at (4,4). I will depict that with a green arrow."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mkf_internal.show_position_prediction_chart()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAGdCAYAAADquxfqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7964c88>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You made this inference because you *inferred* a constant velocity for the airplane. The *reasonable* assumption is that the aircraft is moving one unit each in *x* and *y* per time step.\n",
      "\n",
      "Think back to the g-h filter chapter when we were trying to improve the weight predictions of a noisy scale. We incorporated *weight gain* into the equations because it allowed us to make a better prediction of the weight the next day. The g-h filter uses the *g* parameter to scale the amount of significance given to the current weight measurement, and the *h* parameter scaled the amount of significance given to the weight gain.\n",
      "\n",
      "We are going to do the same thing with our Kalman filter. After all, the Kalman filter is a form of a g-h filter (I have not proven this yet, but I will later on). In this case we are tracking an airplane, so instead of weight and weight gain we need to track position and velocity. Weight gain is the *derivative* of weight, and of course velocity is the derivative of position. Its hard to plot and understand the 3D chart that would be needed to plot *x* and *y* against time, so let's just do the 1D case.\n",
      "\n",
      "So at time 1 we might be fairly certain about the position (x=0) but have no idea about the velocity. We can plot that with a covariance matrix like this. The narrow width expresses our relative certainty about position, and the tall height expresses our lack of knowledge about velocity."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mkf_internal.show_x_error_chart(1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAzQAAAGkCAYAAADni2AdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n4Fj/HwzWm0ynOCnbAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e79ab080>"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now after one second we get a position update of x=5. This implies that our velocity is roughly 5 m/s."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mkf_internal.show_x_error_chart(2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAzQAAAGkCAYAAADni2AdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7b4ec88>"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "But of course position and velocity are correlated. If the velocity is 5 m/s the position would be 5, but if the velocity was 10 m/s the position would be 10. So let's draw a velocity covariance matrix in red."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mkf_internal.show_x_error_chart(3)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAzQAAAGkCAYAAADni2AdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7c85908>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This superposition of the two covariances is where all the magic happens. The only reasonable estimate at time t=1 (where position=5) is roughly the *intersection* between the two covariance matrices! More exactly, we can use the math from the last section and *multipy* the two covariances together. If we multiply the position covariance with the velocity covariance using the equations above, we get the result shown in the next chart."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mkf_internal.show_x_error_chart(4)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAzQAAAGkCAYAAADni2AdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niCht/X8rEkT91v1iZgAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7cf18d0>"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can see that the new covariance lies at the intersection of the position covariance and the velocity covariance. It is slightly tilted, showing that there is some correlation between the position and velocity. Far more importantly, it is far smaller than either the position or velocity covariances that make it up. In the previous chapter our variance would get smaller each time we performed an `update()` because the previous estimate's Gaussian was multiplied by the new measurement's Gaussian. The same thing is happening here. However, the amount that the covariance got smaller by is a huge amount in this chapter. This is because we are using two different kinds of infomation which are nevertheless correlated. Knowing the velocity approximately and the position approximately allows us to very quickly hone in on the correct answer. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is the **key point** in Kalman filters, so read carefully! Our sensor is only detecting the position of the aircraft (how doesn't matter). It does not have any kind of sensor that provides velocity to us. But based on the position estimates we can compute velocity. In Kalman filters we would call the velocity an *unobserved variable*. Unobserved means what it sounds like - there is no sensor that is measuring velocity directly. Since the velocity is based on the position, and the position has error, the velocity will have error as well. But as we can see the correlation between velocity and position means that we can very quickly eliminate most of that error."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "What makes this possible? Imagine for a moment that we superimposed the velocity from a *different* airplane over the position graph. Clearly the two are not related, and there is no way that combining the two could possibly yield any additional information. In contrast, the velocity of the this airplane tells us something very important - the direction and speed of travel. So long as the aircraft does not alter its velocity the velocity allows us to predict where the next position is. After a relatively small amount of error in velocity the probability that it is a good match with the position is very small. Think about it - if you suddenly change direction your position is also going to change a lot. If the position measurement is not in the direction of the assumed velocity change it is very unlikely to be true. The two are correlated, so if the velocity changes so must the position, and in a predictable way. \n",
      "\n",
      "We are going to see this again and again in the rest of the book, so don't worry if this feels a bit magical to you. But it is important to understand that we are taking advantage of the fact that velocity and position are correleated coupled with the ability to infer velocity by looking at the distance and time between two measurement, to produce very accurate estimates after only a few observations. Please reread this section if you have any doubts. If you grasp this point the rest is straightforward. If you do not you will quickly find it impossible to reason about what you will learn in the rest of this chapter."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In summary we have taken advantage of the geometry and correlations of the system to produce a very accurate estimate. The math does not care whether we are working with two positions, or a position and a correlated velocity. If we can express our uncertainties as a multidimensional Gaussian we can then multiply our uncertainty in position with our uncertainty in velocity and get a much more accurate result, in exactly the same way we can multipy the uncertainty in two position estimates to get a more accurate result."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Kalman Filter Algorithm"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now that we have that under our belts we can show how a multidimensional Kalman filter works. In the example above, we compute velocity from the previous position measurements using something called the *measurement function*. Then we predict the next position by using the current estimate and something called the *state transition function*. In our example above,\n",
      "\n",
      "$$new\\_position = old\\_position + velocity*time$$ \n",
      "\n",
      "Next, we take the measurement from the sensor, and compare it to the prediction we just made. In a world with perfect sensors and perfect airplanes the prediction will always match the measured value. In the real world they will always be at least slightly different. We call the difference between the two the *residual*. Finally, we use something called the *Kalman gain* to update our estimate to be somewhere between the measured position and the predicted position. I will not describe how the gain is set, but suppose we had perfect confidence in our measurement - no error is possible. Then, clearly, we would set the gain so that 100% of the position came from the measurement, and 0% from the prediction. At the other extreme, if he have no confidence at all in the sensor (maybe it reported a hardware fault), we would set the gain so that 100% of the position came from the prediction, and 0% from the measurement. In normal cases, we will take a ratio of the two: maybe 53% of the measurement, and 47% of the prediction. The gain is updated on every cycle based on the variance of the variables (in a way yet to be explained). It should be clear that if the variance of the measurement is low, and the variance of the prediction is high we will favor the measurement, and vice versa. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The chart shows a prior estimate of $x=2$ and a velocity $\\dot{x}=1$. \n",
      "\n",
      "> We use the familar dot notation $\\dot{x}$ to denote the derivative of x with respect to time.\n",
      "\n",
      "With the time step $\\Delta t = 1$ we predict $x= 2+(1 \\times 1) = 3$.\n",
      "\n",
      "However, the new measurement is $z=2.3$, giving a residual $r=0.7$. Finally, the Kalman filter gain $K$ gives us a new estimate of $x=2.8$.\n",
      "\n",
      "> We use the notation $z$ to denote a measurement. I will address notation in more detail later. It is an unfortunate reality that nearly every text on Kalman filtering uses different notation and variables - there is almost no agreement across texts. Be sure to read the introductory material very carefully to avoid being led astray."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from mkf_internal import *\n",
      "show_residual_chart()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxYAAAGaCAYAAACSU9UtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAIDL/gdIbaLw6+733QAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7ab3b70>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "The Equations"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The brilliance of the Kalman filter is taking the insights of the chapter up to this point and finding an optimal mathematical solution. The Kalman filter finds what is called a *least squared fit* to the set of measurements to produce an optimal output. We will not trouble ourselves with the derivation of these equations. It runs to several pages, and offers a lot less insight than the words above, in my opinion. Furthermore, to create a Kalman filter for your application you will not be manipulating these equations, but only specifying a number of parameters that are used by them. It would be going too far to say that you will never need to understand these equations; but to start we can pass them by and I will present the code that implements them. So, first, let's see the equations. \n",
      "> Kalman Filter Predict Step:\n",
      "\n",
      "> $$\n",
      "\\begin{aligned}\n",
      "\\hat{\\textbf{x}}^-_{k+1} &= \\mathbf{F}_{k}\\hat{\\textbf{x}}_{k} + \\mathbf{B}_k\\mathbf{u}_k\\;\\;\\;&(1) \\\\\n",
      "\\textbf{P}^-_{k+1} &=  \\mathbf{F}_k \\textbf{P}_k\\mathbf{F}_k^\\mathsf{T} + \\textbf{Q}_{k}\\;\\;\\;&(2)\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "> Kalman Filter Update Step:\n",
      "\n",
      ">$$\n",
      "\\begin{aligned}\n",
      "\\textbf{y}_k &= \\textbf{z}_k - \\textbf{H}_k\\hat{\\textbf{}x}^-_k\\;\\;\\;&(3) \\\\\n",
      "\\mathbf{S}_k &= \\textbf{H}_k\\textbf{P}^-_k\\textbf{H}_k^\\mathsf{T} + \\textbf{R}_k \\;\\;\\;&(4) \\\\\n",
      "\\textbf{K}_k &= \\textbf{P}^-_k\\textbf{H}_k^\\mathsf{T}\\mathbf{S}_k^{-1}\\;\\;\\;&(5) \\\\\n",
      "\\hat{\\textbf{x}}_k  &= \\hat{\\textbf{x}}^-_k +\\textbf{K}_k\\textbf{y} \\;\\;\\;&(6)\\\\\n",
      "\\mathbf{P}_k &= (\\mathbf{I}-\\mathbf{K}_k\\mathbf{H}_k)\\mathbf{P}^-_k\\;\\;\\;&(7)\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "Dash off, wipe the blood out of your eyes, and we'll disuss what this means. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "These are nothing more than linear algebra equations that implement the algorithm we used in the last chapter, but using multidimensional Gaussians instead of univariate Gaussians, and optimized for a least squares fit.\n",
      "\n",
      "\n",
      "Different texts use different notation and variable names for the Kalman filter. Later we will expose you to these different forms to prepare you for reading the original literature. In the equations above I have adopted the variable names used by the Wikipedia article[2] on Kalman filters. Each bold letter denotes a matrix or vector. The subscripts indicate which time step the data comes from; $k$ is now, $k+1$ is the next step. The caret (^) indicates that the value is an estimate. Finally, I particularly like how Brown [3] uses a raised $^-$ to denote a prediction, and so I have adopted that approach. For a matrix $\\mathbf{A}$, $\\mathbf{A}^\\mathsf{T}$ signifies its transpose, and $\\mathbf{A}^{-1}$ its inverse. So, taken together, $\\hat{\\mathbf{x}}^-_{k+1}$ represents the prediction for the estimate of $\\mathbf{x}$ at time step $k+1$, where $\\mathbf{x}$ is some vector in the form $\\mathbf{x} = \\begin{bmatrix}x_1&x_2&..&x_n\\end{bmatrix}^\\mathsf{T}.$ The notation does not specify that $\\mathbf{x}$ is a column vector - we will learn the shapes and sizes of all of the variables later in the chapter."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Kalman Equations Expressed as an Algorithm"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "However, I still find  the notation to be a bit dense, and unnecessarily complicated for writing code. The subscripts indicate the time step, but when we write code it is very clear what is being calculated at each time step. For most of this book I'm going to use the following simplified equations, which express an algorithm.\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\text{Predict Step}\\\\\n",
      "\\mathbf{x^-} &= \\mathbf{F x} + \\mathbf{B u}\\;\\;\\;&(1) \\\\\n",
      "\\mathbf{P^-} &= \\mathbf{FP{F}}^\\mathsf{T} + \\mathbf{Q}\\;\\;\\;&(2) \\\\\n",
      "\\\\\n",
      "\\text{Update Step}\\\\\n",
      "\\textbf{y} &= \\mathbf{z} - \\mathbf{H x^-} \\;\\;\\;&(3)\\\\\n",
      "\\textbf{S} &= \\mathbf{HP^-H}^\\mathsf{T} + \\mathbf{R} \\;\\;\\;&(4)\\\\\n",
      "\\mathbf{K} &= \\mathbf{P^-H}^\\mathsf{T} \\mathbf{S}^{-1}\\;\\;\\;&(5) \\\\\n",
      "\\mathbf{x} &=\\mathbf{x^-} +\\mathbf{K\\textbf{y}} \\;\\;\\;&(6)\\\\\n",
      "\\mathbf{P} &= (\\mathbf{I}-\\mathbf{KH})\\mathbf{P^-}\\;\\;\\;&(7)\n",
      "\\end{aligned}\n",
      "$$"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "What do all of the variables mean? What is $\\mathbf{P}$, for example? Don't worry right now. Instead, I am just going to design a Kalman filter, and introduce the names as we go. Then we will just pass them into Python function that implement the equations above, and we will have our solution. Later sections will then delve into more detail about each step and equation. I think learning by example and practice is far easier than trying to memorize a dozen abstract facts at once.  "
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Implementation in Python"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Before we go any further let's gain some familiarity with the equations by programming them in Python. I have written a production quality implementation of the Kalman filter equations in my `FilterPy` library, and we will be using that later in the chapter and the remainder of the book. We could just look at that code, but it contains a significant amount of code to ensure that the computations are numerically stable, that you do not pass in bad data, and so on. Let's just try to program this.\n",
      "\n",
      "The filter equations are *linear algebra* equations, so we will use the Python library that implements linear algebra - numpy. In the filter equations a **bold** variable denotes a matrix. Numpy provides two types to implement matrices: `numpy.array` and `numpy.matrix`. You might suspect that the latter is the one we want to use. As it turns out `numpy.matrix` does support linear algebra well, except for one problem - most of the rest of `numpy` uses `numpy.array`, not `numpy.matrix`. You can pass a `numpy.matrix` into a function, and get a `numpy.array` back as a result. Hence, the standard advice is that `numpy.matrix` is deprecated, and you should always use `numpy.array` even when `numpy.matrix` is more convienient. I ignored this advice in a early version of this code and ended up regretting that choice, and so now I use 'numpy.array' only.\n",
      "\n",
      "`numpy.array` implements a one or more dimensional array. You can construct it with any list like object. The following constructs a 1-D array from a list:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "x = np.array([1, 2, 3])\n",
      "print(x)\n",
      "print(type(x))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[1 2 3]\n",
        "<class 'numpy.ndarray'>\n"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can create a 2D array with nested lists:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = np.array([[1, 2 ,3],\n",
      "              [4, 5, 6]])\n",
      "print(x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[[1 2 3]\n",
        " [4 5 6]]\n"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can create arrays of 3 or more dimensions, but we have no need for that here, and so I will not elaborate.\n",
      "\n",
      "By default the arrays use the data type of the values in the list; if there are multiple types than it will choose the type that most accurately represents all the values. So, for example, if your list contains a mix of `int` and `float` the data type of the array would be of type `float`. You can override this with the `dtype` parameter."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = np.array([1, 2, 3], dtype=float)\n",
      "print(x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[ 1.  2.  3.]\n"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can perform matrix addition with the `+` operator, but matrix multiplication requires the `dot` method or function. The `*` operator performs element-wise multiplication, which is **not** what you want for linear algebra."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = np.array([[1, 2],\n",
      "              [3, 4]], dtype=float)\n",
      "print('addition:\\n', x+x)\n",
      "print('\\nelement-wise multiplication\\n', x*x)\n",
      "print('\\nmultiplication\\n', np.dot(x,x))\n",
      "print('\\ndot is also a member\\n', x.dot(x))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "addition:\n",
        " [[ 2.  4.]\n",
        " [ 6.  8.]]\n",
        "\n",
        "element-wise multiplication\n",
        " [[  1.   4.]\n",
        " [  9.  16.]]\n",
        "\n",
        "multiplication\n",
        " [[  7.  10.]\n",
        " [ 15.  22.]]\n",
        "\n",
        "dot is also a member\n",
        " [[  7.  10.]\n",
        " [ 15.  22.]]\n"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can get the transpose with `.T`, and the inverse with `numpy.linalg.inv`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print('transpose\\n', x.T)\n",
      "print('\\ninverse\\n', np.linalg.inv(x))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "transpose\n",
        " [[ 1.  3.]\n",
        " [ 2.  4.]]\n",
        "\n",
        "inverse\n",
        " [[-2.   1. ]\n",
        " [ 1.5 -0.5]]\n"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Finally, there are helper functions like `zeros` to create a matrix of all zeros, `ones` to get all ones, and `eye` to get the identity matrix."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print('zeros\\n', np.zeros((3, 2)))\n",
      "print('\\neye\\n', np.eye(3))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "zeros\n",
        " [[ 0.  0.]\n",
        " [ 0.  0.]\n",
        " [ 0.  0.]]\n",
        "\n",
        "eye\n",
        " [[ 1.  0.  0.]\n",
        " [ 0.  1.  0.]\n",
        " [ 0.  0.  1.]]\n"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There is a lot of useful functionality in `numpy`, but let's move on to implementing the Kalman filter. Let's start with the prediction equations.\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{x^-} &= \\mathbf{F x} + \\mathbf{B u}\\;\\;\\;&(1) \\\\\n",
      "\\mathbf{P^-} &= \\mathbf{FPF}^\\mathsf{T} + \\mathbf{Q}\\;\\;\\;&(2) \\\\\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "Those are linear algebra equations using matrix multiplication and addition. Assuming each variable is already defined somewhere, we can implement these equations in Python and numpy with:\n",
      "\n",
      "    x = dot(F, x) + dot(B, u)\n",
      "    P = dot(F, P).dot(F.T) + Q\n",
      "\n",
      "That is all there is to it! Okay, we need to put these in a function or a class somehow, but that is the 'hard' code, which is actually pretty easy.\n",
      "\n",
      "Now let's do the update step. Again, they consist of matrix multiplication and addition.\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\textbf{y} &= \\mathbf{z} - \\mathbf{H x} \\;\\;\\;&(3)\\\\\n",
      "\\textbf{S} &= \\mathbf{HP^-H}^\\mathsf{T} + \\mathbf{R} \\;\\;\\;&(4)\\\\\n",
      "\\mathbf{K} &= \\mathbf{P^-H}^\\mathsf{T} \\mathbf{S}^{-1}\\;\\;\\;&(5) \\\\\n",
      "\\mathbf{x}&=\\mathbf{x^-} +\\mathbf{K\\textbf{y}} \\;\\;\\;&(6)\\\\\n",
      "\\mathbf{P}&= (\\mathbf{I}-\\mathbf{KH})\\mathbf{P^-}\\;\\;\\;&(7)\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "\n",
      "In Python we would write:\n",
      "\n",
      "    y = z - dot(H, x)\n",
      "    S = dot(H, P).dot(H.T) + R\n",
      "    K = dot(P, H.T).dot(np.linalg.inv(S))\n",
      "    x = x + dot(K,y)\n",
      "    P = (I - dot(K, H)).dot(P)\n",
      "    \n",
      "And that is it, we have implemented a Kalman filter!\n",
      "\n",
      "Well, you probably do not want to cut and paste that code into every project that uses a Kalman filter. So let's put this into a class. I don't intend to teach you how to program here, so I will instead point you to my `KalmanFilter` class from my FilterPy module, available on github [4]. However, I have written a simplified version of that class below for your inspection."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "    import numpy as np\n",
      "    import scipy.linalg as linalg\n",
      "    import matplotlib.pyplot as plt\n",
      "    import numpy.random as random\n",
      "    from numpy import dot\n",
      "\n",
      "    class KalmanFilter:\n",
      "\n",
      "        def __init__(self, dim_x, dim_z, dim_u=0):\n",
      "            \"\"\" Create a Kalman filter. You are responsible for setting \n",
      "            the various state variables to reasonable values; the defaults \n",
      "            below will not give you a functional filter.\n",
      "\n",
      "            **Parameters**\n",
      "\n",
      "            dim_x : int\n",
      "                Number of state variables for the Kalman filter. For \n",
      "                example, if you are tracking the position and velocity \n",
      "                of an object in two dimensions, dim_x would be 4.\n",
      "\n",
      "                This is used to set the default size of P, Q, and u\n",
      "\n",
      "            dim_z : int\n",
      "                Number of of measurement inputs. For example, if the sensor\n",
      "                provides you with position in (x,y), dim_z would be 2.\n",
      "\n",
      "            dim_u : int (optional)\n",
      "                size of the control input, if it is being used.\n",
      "                Default value of 0 indicates it is not used.\n",
      "            \"\"\"\n",
      "\n",
      "            self.x = np.zeros((dim_x,1)) # state\n",
      "            self.P = np.eye(dim_x)       # uncertainty covariance\n",
      "            self.Q = np.eye(dim_x)       # process uncertainty\n",
      "            self.u = np.zeros((dim_x,1)) # motion vector\n",
      "            self.B = 0                   # control transition matrix\n",
      "            self.F = 0                   # state transition matrix\n",
      "            self.H = 0                   # Measurement function\n",
      "            self.R = np.eye(dim_z)       # state uncertainty\n",
      "\n",
      "            # identity matrix. Do not alter this. \n",
      "            self._I = np.eye(dim_x)\n",
      "\n",
      "\n",
      "        def update(self, Z, R=None):\n",
      "            \"\"\"\n",
      "            Add a new measurement (Z) to the kalman filter. If Z is\n",
      "            None, nothing is changed.\n",
      "\n",
      "            **Parameters**\n",
      "\n",
      "            Z : np.array\n",
      "                measurement for this update.\n",
      "\n",
      "            R : np.array, scalar, or None\n",
      "                Optionally provide R to override the measurement noise \n",
      "                for this one call, otherwise  self.R will be used.\n",
      "            \"\"\"\n",
      "\n",
      "            if Z is None:\n",
      "                return\n",
      "\n",
      "            if R is None:\n",
      "                R = self.R\n",
      "            elif np.isscalar(R):\n",
      "                R = np.eye(self.dim_z) * R\n",
      "\n",
      "            # error (residual) between measurement and prediction\n",
      "            y = Z - dot(H, x)\n",
      "\n",
      "            # project system uncertainty into measurement space \n",
      "            S = dot(H, P).dot(H.T) + R\n",
      "\n",
      "            # map system uncertainty into kalman gain\n",
      "            K = dot(P, H.T).dot(linalg.inv(S))\n",
      "\n",
      "            # predict new x with residual scaled by the kalman gain\n",
      "            self.x += dot(K, y)\n",
      "\n",
      "            I_KH = self._I - dot(K, H)\n",
      "            self.P = dot(I_KH).dot(P).dot(I_KH.T) + dot(K, R).dot(K.T)\n",
      "\n",
      "\n",
      "        def predict(self, u=0):\n",
      "            \"\"\" Predict next position.\n",
      "\n",
      "            **Parameters**\n",
      "\n",
      "            u : np.array\n",
      "                Optional control vector. If non-zero, it is multiplied\n",
      "                by B to create the control input into the system.\n",
      "            \"\"\"\n",
      "\n",
      "            self.x = dot(self.F, self.x) + dot(self.B, u)\n",
      "            self.P = self.F.dot(self.P).dot(self.F.T) + self.Q"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We will see how to use this class in the rest of the chapter, so I will not belabor its use here. There are several additions to the version in `FilterPy` that make it more usable. For example, instead of using variables for the $R$, $P$, and so on, the `FilterPy` version uses properties. This allows you to write something like:\n",
      "\n",
      "    dog_filter.R = 3\n",
      "    \n",
      "and the class will recognize that $R$ is actually supposed to be a matrix and convert the $3$ into an appropriate matrix (we don't yet know what an 'appropriate' matrix for $R=3$ would be, but we will learn that soon).\n",
      "\n",
      "You can import the class from `FilterPy` using the following import statement, and that is what we will do in the rest of this chapter and book:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from filterpy.kalman import KalmanFilter"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 33
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Tracking a Dog"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's go back to our tried and true problem of tracking our dog. This time we will include the fundamental insight of this chapter - that of using *unobserved variables* to improve our estimates. In simple terms, our algorithm is:\n",
      "\n",
      "    1. predict the next value for x with \"x + vel*time\".\n",
      "    2. adjust covariance for x for uncertainty caused by prediction\n",
      "    3. get measurement for x\n",
      "    4. compute residual as: \"x - x_prediction\"\n",
      "    5. compute kalman gain based on noise levels\n",
      "    6. compute new position as \"residual * kalman gain\"\n",
      "    7. compute covariance for x to account for additional\n",
      "       information the measurement provides\n",
      "    \n",
      "That is the entire Kalman filter algorithm. It is both what we described above in words, and it is what the rather obscure Kalman Filter equations do. The Kalman filter equations just express this algorithm by using linear algebra.\n",
      "\n",
      "As I mentioned above, there is actually very little programming involved in creating a Kalman filter. We will just be defining several matrices and parameters that get passed into  the Kalman filter algorithm code. \n",
      "\n",
      "Rather than try to explain each of the steps ahead of time, which can be a bit abstract and hard to follow, let's just do it for our by now well known dog tracking problem. Naturally this one example will not cover every use case of the Kalman filter, but we will learn by starting with a simple problem and then slowly start addressing more complicated situations. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### **Step 1:** Choose the State Variables and Set Initial Conditions\n",
      "\n",
      "\n",
      "In the previous chapter we tracked a dog in one dimension by using a Gaussian. The mean $(\\mu)$ represented the most likely position, and the variance ($\\sigma^2$) represented the probability distribution of the position. In that problem the position is the *state* of the system, and we call $\\mu$ the *state variable*.\n",
      "\n",
      "In this chapter we will be tracking both the position and velocity of the dog, so we have two state variables. It is important to understand that this is a design choice with implications and assumptions that we are not yet prepared to explore. For example, we could optionally also track acceleration, or even jerk. For now I will only state that the decision to track position and velocity contains an assumption that acceleration is zero, which of course often not true. If the object being tracked *is* accelerating, then the performance of the filter will be suboptimal, or even diverge. However, this is a good way to introduce the concept of Kalman filtering without getting bogged down into too many details, or having to deal with large matrices.\n",
      "\n",
      "State variables can either be *observed variables* - directly measured by a sensor, or *unobserved variables* - inferred from the observed variables. For our dog tracking problem, our observed state variable is position, and the unobserved variable is velocity. \n",
      "\n",
      "In the previous chapter we would denote the dog's position being 3.2 meters as:\n",
      "$$\\mu = 3.2$$\n",
      "\n",
      "In this chapter we will use the multivariate Gaussian as described at the beginning of this chapter. For example, if we wanted to specify a position of 10.0 m and a velocity of 4.5 m/s, we would write:\n",
      "\n",
      "$$\\mu = \\begin{bmatrix}10.0\\\\4.5\\end{bmatrix}$$\n",
      "\n",
      "The Kalman filter is implemented using linear algebra. We use an $n\\times 1$ matrix to store  $n$ state variables. For the dog tracking problem, we use $x$ to denote position, and the first derivative of $x$, $\\dot{x}$, for velocity. The Kalman filter equations use $\\mathbf{x}$ for the state, so we define $\\mathbf{x}$ as:\n",
      "\n",
      "$$\\mathbf{x} =\\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}$$\n",
      "\n",
      "We use $\\mathbf{x}$ instead of $\\mu$, but recognize this is just the mean of the multivariate Gaussian.\n",
      "\n",
      "The other half of the Gaussian is the covariance $\\Sigma$. The Kalman filter equations use the alternative symbol $\\mathbf{P}$, but it means the same thing. In the one dimensional Kalman filter we specified an initial value for $\\sigma^2$, and then the filter took care of updating its value as measurements were added to the filter. The same thing happens in the multidimensional Kalman filter.\n",
      "\n",
      "In the last chapter we initialized the dog's position at 0.0 m, and set the $\\sigma^2=500$ to indicate that we were very unsure about this initial value. We need to do the same thing for the multidimensional Kalman filter. We will set the initial position to 0.0 m, the initial velocity to 0.0 m/s, and then set $\\sigma^2$ to a 500 for both the position and velocity to reflect our uncertainty. \n",
      "\n",
      "Recall that the diagonals of the covariance matrix contains the variance of each variable. So to initialize the Kalman filter to the values in the previous paragraph we would write:\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{x} &= \\begin{bmatrix}0 \\\\ 0\\end{bmatrix} \\\\\n",
      "\\mathbf{P} &= \\begin{bmatrix}500 & 0 \\\\ 0&500\\end{bmatrix} \\\\\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "I am often frustrated when books use the same value for multiple variables in an example as it can be unclear which value corresponds to which variable. To ensure that there is no confusion let's look at the example of setting the initial position to 1 m, the initial velocity to 2.3 m/s, the $\\sigma^2$ of the position to 500, and the $\\sigma^2$ of the velocity to 400. In that case we would write:\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{x} &= \\begin{bmatrix}1 \\\\ 2.3\\end{bmatrix} \\\\\n",
      "\\mathbf{P} &= \\begin{bmatrix}500 & 0 \\\\ 0&400\\end{bmatrix} \\\\\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "We have chosen our state variables and set our initial conditions, so this step is complete."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### **Step 2:** Design the State Transition Function\n",
      "\n",
      "\n",
      "The next step in designing a Kalman filter is telling it how to predict the next state from the current state. We do this by providing it with equations that describe the physical model of the system. For example, for our dog tracking problem we are tracking a moving object, so we just need to provide it with the Newtonian equations for motion. If we were tracking a thrown ball we would have to provide equations for how a ball moves in a gravitational field, and perhaps include the effects of things like air drag. If we were writing a Kalman filter for a rocket we would have to tell it how the rocket responds to its thrusters and main engine. A Kalman filter for a bowling ball would incorporate the effects of friction and ball rotation. You get the idea. \n",
      "\n",
      "In the language of Kalman filters the physical model is sometimes called the *process model*. That is probably a better term than *physical model* because the Kalman filter can be used to track non-physical things like stock prices. We describe the process model with a set of equations we call the *State Transition Function.* \n",
      "\n",
      "\n",
      "We know from elementary physics how to compute a future position given our current position and velocity. Let $x$ be our current position, and $\\Delta t$ be the amount of time in the future. The velocity is then the derivative of $x$ with respect to time, which we notate as $\\dot{x}$. We can then write \n",
      "\n",
      "$$x_t = \\dot{x}_{t-1}\\Delta t + x_{t-1}$$\n",
      "\n",
      "To avoid subscripts we will adopt notation that uses $x^-$ to denote our predicted position, and write\n",
      "\n",
      "$$x^- = \\dot{x}\\Delta t + x$$\n",
      "\n",
      "Equation (1) of the Kalman filter $\\mathbf{x^-} = \\mathbf{Fx} + \\mathbf{B u}$ implements the *state transition function* that we are discussing. This requires us to formulate the motion equations with matrices, so let's learn how to do that now. For the moment we will ignore the $\\mathbf{B u}$ term, as for our problem it turns out that it is equal to zero. This will be explained in step 3. Thus, we must express our equations in the form \n",
      "$\\mathbf{x}^- = \\mathbf{Fx}.$\n",
      "\n",
      "A quick review on how to represent linear equations with matrices. Take the following two equations:\n",
      "$$2x+3y = 8\\\\3x-y=1$$\n",
      "\n",
      "We can put this in matrix form by writing:\n",
      "\n",
      "$$\n",
      "\\begin{bmatrix}2& 3 \\\\ 3& -1\\end{bmatrix}\\begin{bmatrix}x\\\\y\\end{bmatrix}=\\begin{bmatrix}8\\\\1\\end{bmatrix}$$\n",
      "If you perform the matrix multiplication in this equation the result will be the two equations above.\n",
      "\n",
      "So, given that $\\mathbf{x} = \\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}$ we can write:\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{x}^- &= \\mathbf{Fx} \\\\\n",
      "\\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}^- &= \\mathbf{F}\\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "Since $\\mathbf{x}$ is a $2{\\times}1$ matrix $\\mathbf{F}$ must be a $2{\\times}2$ matrix to yield another $2{\\times}1$ matrix as a result. The first row of the F is easy to derive:\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "{\\begin{bmatrix}x\\\\\\dot{x}\\end{bmatrix}}^- &=\\begin{bmatrix}1&\\Delta t \\\\ ?&?\\end{bmatrix} \\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "When we multiply the first row of $\\mathbf{F}$ that out we get:\n",
      "\n",
      "$$ \n",
      "\\begin{aligned}\n",
      "x^- &= 1  x + \\Delta t \\dot{x} \\mbox{, or} \\\\\n",
      "x^- &= \\dot{x}\\Delta t + x\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "which is our equation for computing the new position based on velocity, time, and the previous position.\n",
      "\n",
      "Now we have to account for the second row. I've left it somewhat unstated up to now, but we are assuming constant velocity for this problem. Naturally this assumption is not true; if our dog moves it must accelerate and decelerate. If you cast your mind back to the *g-h Filter* chapter we explored the effect of assuming constant velocity. So long as the acceleration is small compared to $\\Delta t$ the filter will still perform well. \n",
      "\n",
      "Therefore we will assume that\n",
      "\n",
      "$$\\dot{x}^- = \\dot{x}$$\n",
      "\n",
      "which gives us the second row of $\\mathbf{F}$ as follows, once we set $\\Delta t = 1$:\n",
      "\n",
      "\n",
      "$$\n",
      "{\\begin{bmatrix}x\\\\\\dot{x}\\end{bmatrix}}^- =\\begin{bmatrix}1&1 \\\\ 0&1\\end{bmatrix} \\times \\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}\n",
      "$$\n",
      "\n",
      "Which, when multiplied out, yields our desired equations:\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "x^- &= x + \\dot{x} \\\\\n",
      "\\dot{x}^- &= \\dot{x}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "In the vocabulary of Kalman filters we call this *transforming the state matrix*. We take our state matrix, which for us is $(\\begin{smallmatrix}x \\\\ \\dot{x}\\end{smallmatrix})$, and multiply it by a matrix we will call $\\mathbf{F}$ to compute the new state. In this case, $\\mathbf{F}=(\\begin{smallmatrix}1&1\\\\0&1\\end{smallmatrix})$. \n",
      "\n",
      "\n",
      "You will do this for every Kalman filter you ever design. Your state matrix will change depending on how many state random variables you have, and then you will create $\\mathbf{F}$ so that it updates your state based on whatever the physics of your problem dictates. If this is not fully clear, don't worry, we will do this many times in this book. The important thing to understand is that we have described how to predict the state of the system based on the current state. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### **Step 3**: Design the Motion Function\n",
      "\n",
      "The Kalman filter does not just filter data, it allows us to incorporate control inputs for systems like robots and airplanes. Consider the state transition function we wrote for the dog:\n",
      "\n",
      "$$x_t = \\dot{x}(\\Delta t) + x_{t-1}$$\n",
      "\n",
      "Suppose that instead of passively tracking our dog we were actively controlling a robot. At each time step we would send control signals to the robot based on its current position vs desired position. Kalman filter equations incorporate that knowledge into the filter equations, creating a predicted position based both on current velocity *and* control inputs to the drive motors. \n",
      "\n",
      "We will cover this use case later, but for now passive tracking applications we set those terms to 0. In step 2 there was the unexplained term $\\mathbf{Bu}$ in equation (1):\n",
      "\n",
      "$$\\mathbf{x^-} = \\mathbf{Fx} + \\mathbf{Bu}$$.\n",
      "\n",
      "Here $\\mathbf{u}$ is the control input, and $\\mathbf{B}$ is its transfer function. For example, $\\mathbf{u}$ might be a voltage controlling how fast the wheel's motor turns, and multiplying by $\\mathbf{B}$ yields $[\\begin{smallmatrix}x\\\\\\dot{x}\\end{smallmatrix}]$. Since we do not need these terms we will set them both to zero and not concern ourselves with them for now.\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### **Step 4**: Design the Measurement Function\n",
      "\n",
      "The Kalman filter computes the update step in what we call *measurement space*. We mostly ignored this issue in the previous chapter because of the complication it adds. In the last chapter we tracked our dog's position using a sensor that reported his position. Computing the *residual* was easy - subtract the filter's predicted position from the measurement:\n",
      "\n",
      "$$ residual = measurement - position$$\n",
      "\n",
      "However, consider what would happen if we were trying to track temperature using a thermometer that outputs a voltage corresponding to the temperature reading. The equation for the residual computation would be nonsense; you can't subtract a temperature from a voltage.\n",
      "\n",
      "$$ residual = z_{volts} - temp_C\\;\\;\\;(BAD!)$$\n",
      "\n",
      "The Kalman filter generalizes this problem by having you supply a *measurement function*. It is somewhat counterintuitive at first. As I already stated the Kalman filter performs its calculations in *measurement space.*  It needs to do that because it only really makes sense to talk about the residual of the measurement in terms of the measurement. So it does something like this:\n",
      "\n",
      "    residual = measurement - convert_to_measurement(predicted state)\n",
      "\n",
      "In other words, for the thermometer tracking problem, it would take the filter's current prediction of temperature, convert that to whatever voltage would represent that temperature, and then subtract it from the current thermometer voltage output. This gives it a residual in the correct units (volts).\n",
      "\n",
      "It does this with a *measurement function* matrix that you provide. At first it might seem counterintuitive: to use the thermometer we need to know how to convert the output voltage into a temperature, but we tell the Kalman filter how to convert a temperature into a voltage!  But if you think about it, what you are really telling the filter is how your sensor works. Your sensor converts temperature into voltage, and you are just telling the Kalman filter how it does it. The Kalman filter equations can take that information and figure out how to perform the inverse operation without you explicitly telling it the computation.\n",
      "\n",
      "The Kalman filter equation that performs this step is:\n",
      "\n",
      "$$\\textbf{y} = \\mathbf{z} - \\mathbf{H x^-} \\;\\;\\;(3)$$\n",
      "\n",
      "where $\\textbf{y}$ is the residual, $\\mathbf{x^-}$ is the predicted value for $\\mathbf{x}$, $\\textbf{z}$ is the measurement, and $\\textbf{H}$ is the measurement function. It is just a matrix that we multiply the state into to convert it into a measurement.\n",
      "\n",
      "For our dog tracking problem we have a sensor that measures position, but no sensor that measures velocity. So for a given state $\\mathbf{x}=\\begin{bmatrix}x & \\dot{x}\\end{bmatrix}^\\mathsf{T}$ we will want to multiply the position $x$ by 1 to get the corresponding measurement of the position, and multiply the velocity $\\dot{x}$ by 0 to get the corresponding measurement of velocity (of which there is none).\n",
      "\n",
      "We only have 1 measurement in this example, so the dimension of the residual matrix needs to be $1\\times 1$. $\\mathbf{x}$ is $2\\times 1$, so $\\mathbf{H}$ needs to be $1\\times 2$ to get the right result. If we put this in linear algebra terms we get:\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      " \\textbf{y} &= \\mathbf{z} - &\\begin{bmatrix}1&0\\end{bmatrix} &\\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}, or \\\\\n",
      "\\textbf{y} &= \\mathbf{z} - &\\textbf{H}&\\begin{bmatrix}x \\\\ \\dot{x}\\end{bmatrix}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "And so, for our Kalman filter we set\n",
      "\n",
      "$$\\mathbf{H}=\\begin{bmatrix}1&0\\end{bmatrix}$$\n",
      "\n",
      "Believe it or not, we have designed the majority of our Kalman filter!! All that is left is to model the noise in our sensors."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### **Step 5**: Design the Measurement Noise Matrix\n",
      "\n",
      "The *measurement noise matrix* is a matrix that models the noise in our sensors as a covariance matrix. This can be admittedly a very difficult thing to do in practice. A complicated system may have many sensors, the correlation between them might not be clear, and usually their noise is not a pure Gaussian. For example, a sensor might be biased to read high if the temperature is high, and so the noise is not distributed equally on both sides of the mean. Later we will address this topic in detail. For now I just want you to get used to the idea of the measurement noise matrix so we will keep it deliberately simple.\n",
      "\n",
      "In the last chapter we used a variance of 5 meters for our position sensor. Let's use the same value here.  The Kalman filter equations uses the symbol $R$ for this matrix. In general the matrix will have dimension $m{\\times}m$, where $m$ is the number of sensors. It is $m{\\times}m$ because it is a covariance matrix, as there may be correlations between the sensors. We have only 1 sensor here so we write:\n",
      "\n",
      "$$R = \\begin{bmatrix}5\\end{bmatrix}$$\n",
      "\n",
      "If we had two position sensors, the first with a variance of 5 meters, the second with a variance of 3 meters, we would write\n",
      "\n",
      "$$R = \\begin{bmatrix}5&0\\\\0&3\\end{bmatrix}$$\n",
      "\n",
      "We put the variances on the diagonal because this is a *covariance* matrix, where the variances lie on the diagonal, and the covariances, if any, lie in the off-diagonal elements. Here we assume there is no correlation in the noise between the two sensors, so the covariances are 0."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### **Step 6**: Design the Process Noise Matrix\n",
      "\n",
      "What is *process noise*? Consider the motion of a thrown ball. In a vacuum and with constant gravitational force it moves in a parabola. However, if you throw the ball on the surface of the earth you will also need to model factors like rotation and air drag. However, even when you have done all of that there is usually things you cannot account for. For example, consider wind. On a windy day the ball's trajectory will differ from the computed trajectory, perhaps by a significant amount. Without wind sensors, we may have no way to model the wind. The Kalman filter models this as *process noise*, and calls it $\\mathbf{Q}$.\n",
      "\n",
      "Astute readers will realize that we can inspect the ball's path and extract wind as an unobserved state variable, but the point to grasp here is there will always be some unmodeled noise in our process, and the Kalman filter gives us a way to model it.\n",
      "\n",
      "Designing the process noise matrix can be quite demanding, and we will put it off until the Kalman math chapter. In this chapter we will focus on building an intuitive understanding on how modifying this matrix alters the behavior of the filter. \n",
      "\n",
      "We think of the the underlying system as behaving as\n",
      "\n",
      "$$f(x) = \\mathbf{F}x + w$$\n",
      "\n",
      "where $\\mathbf{F}x$ is the state transition and $w$ is the process noise. In other words $\\mathbf{F}x$ is the 'true' behavior of the process as we understand it, and $w$ is things like winds, control surface fluctuations, maybe circuit noise - whatever affects our process that is not modelled."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Recall what happened to our variance when we performed the predict step in the *Discrete Bayes* chapter and the *Kalman Filter* chapter. Because we are predicting forward in time we lose some certainty about the state. In the *Discrete Bayes* chapter we used this code to implement that:\n",
      "\n",
      "    sigma = sigma + movement_sigma\n",
      "    \n",
      "That equation did not take the loss of knowledge due to the process noise into account. We can model the process noise as additional uncertainty, so we could write\n",
      "\n",
      "In pseudocode we might express this equation as:\n",
      "\n",
      "    sigma = sigma + movement_sigma + process_noise\n",
      "\n",
      "\n",
      "In this chapter we do not have multiple state variables, so we have to use linear algebra to perform this computation. \n",
      "  \n",
      "In pseudocode we might express this equation as:\n",
      "    \n",
      "    P = project_forward(P) + process_noise\n",
      "\n",
      "where $P$ is the covariance matrix. The Kalman filter equation corresponding to this pseudocode is\n",
      "\n",
      "$$\\mathbf{P} = \\mathbf{FP{F}}^\\mathsf{T} + \\mathbf{Q}$$\n",
      "\n",
      "In this equation $\\mathbf{FP{F}}^\\mathsf{T}$ is just some linear algebra 'magic' that projects $\\mathbf{P}$ forward to the next time step, and $\\mathbf{Q}$ is the *process noise matrix*. We are just adding matrices, so hopefully it is clear that each element in $\\mathbf{Q}$  specifies how much uncertainty is added to the system due to the process noise. \n",
      "\n",
      "We have not given the math for computing the elements of $\\mathbf{Q}$ yet, but if you suspect the math is sometimes difficult you would be correct. One of the problems is that we are usually modelling a *continuous* system - the behavior of the system is changing at every instant, but the Kalman filter is *discrete*. That means that we have to somehow convert the continuous noise of the system into a discrete value, which usually involves calculus. There are other difficulties I will not mention now."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "However, for the class of problems we are solving in this chapter (*discretized continuous-time kinematic filters*), where we can directly compute the state equations for moving objects by using Newton's equations.\n",
      "\n",
      "For these kinds of problems we can rely on precomputed forms for $\\mathbf{Q}$. We will learn how to derive these matrices in the next chapter. For now I present them without proof. If we assume that for each time period the acceleration due to process noise is constant and uncorrelated, we get the following.\n",
      "\n",
      "For constant velocity the form is\n",
      " $$\\begin{bmatrix}\n",
      " \\frac{1}{4}{\\Delta t}^4 & \\frac{1}{2}{\\Delta t}^3 \\\\\n",
      " \\frac{1}{2}{\\Delta t}^3 & \\Delta t^2\n",
      " \\end{bmatrix}\\sigma^2\n",
      " $$\n",
      "\n",
      "and for constant acceleration we have\n",
      "\n",
      " $$\\begin{bmatrix}\n",
      " \\frac{1}{4}{\\Delta t}^4 & \\frac{1}{2}{\\Delta t}^3 & \\frac{1}{2}{\\Delta t}^2 \\\\\n",
      " \\frac{1}{2}{\\Delta t}^3 & {\\Delta t}^2 & \\Delta t \\\\\n",
      " \\frac{1}{2}{\\Delta t}^2 & \\Delta t & 1\n",
      " \\end{bmatrix} \\sigma^2\n",
      " $$\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It general it is not true that acceleration will be constant and uncorrelated, but this is still a useful approximation for moderate time period, and will suffice for this chapter. Fortunately you can get a long way with approximations and simulation. Let's think about what these matrices are implying. We are trying to model the effects of *process noise*, such as the wind buffeting the flight of a thrown ball. Variations in wind will cause changes in acceleration, and so the effect on the acceleration is large. However, the effects on velocity and position are proportionally smaller. In the matrices, the acceleration term is in the lower right, and this is the largest value. **A good rule of thumb is to set $\\sigma$ somewhere from $\\frac{1}{2}\\Delta a$ to $\\Delta a$, where $\\Delta a$ is the maximum amount that the acceleration will change between sample periods**. In practice we pick a number, run simulations on data, and choose a value that works well. \n",
      "\n",
      "The filtered result will not be optimal, but in my opinion the promise of optimal results from Kalman filters is mostly wishful thinking. Consider, for example, tracking a car. In that problem the process noise would include things like potholes, wind gusts, changing drag due to turning, rolling down windows, and many more factors. We cannot realistically model that analytically, and so in practice we work out a simplified model, compute $\\mathbf{Q}$ based on that simplified model, and then add *a bit more* to  $\\small\\mathbf{Q}$ in hopes of taking the incalculable factors into account. Then we use a lot of simulations and trial runs to see if the filter behaves well; if it doesn't we adjust $\\small\\mathbf{Q}$ until the filter performs well. In this chapter we will focus on forming an intuitive understanding on how adjusting $\\small\\mathbf{Q}$ affects the output of the filter. In the Kalman Filter Math chapter we will discuss the analytic computation of $\\small\\mathbf{Q}$, and also provide code that will compute it automatically for you.\n",
      "\n",
      "For now we will just import the code from the `FilterPy` module, where it is already implemented. I will import it and call help on it so you can see the documentation for it."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from filterpy.common import Q_discrete_white_noise\n",
      "help(Q_discrete_white_noise)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Help on function Q_discrete_white_noise in module filterpy.common.discretization:\n",
        "\n",
        "Q_discrete_white_noise(dim, dt=1.0, var=1.0)\n",
        "    Returns the Q matrix for the Discrete Constant White Noise\n",
        "    Model. dim may be either 2 or 3, dt is the time step, and sigma is the\n",
        "    variance in the noise.\n",
        "    \n",
        "    Q is computed as the G * G^T * variance, where G is the process noise per\n",
        "    time step. In other words, G = [[.5dt^2][dt]]^T for the constant velocity \n",
        "    model.\n",
        "    \n",
        "    **Paramaeters**\n",
        "    \n",
        "    dim : int (2 or 3)\n",
        "        dimension for Q, where the final dimension is (dim x dim)\n",
        "    \n",
        "    dt : float, default=1.0\n",
        "        time step in whatever units your filter is using for time. i.e. the\n",
        "        amount of time between innovations\n",
        "    \n",
        "    var : float, default=1.0\n",
        "        variance in the noise\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Q = Q_discrete_white_noise(dim=2, dt=0.1, var=2.35)\n",
      "Q"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 35,
       "text": [
        "array([[ 0.00005875,  0.001175  ],\n",
        "       [ 0.001175  ,  0.0235    ]])"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Implementing the Kalman Filter"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "As we already explained, the Kalman filter equations are already implemented for you in the `FilterPy` library, so let's start by importing it and creating a filter."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "from filterpy.kalman import KalmanFilter\n",
      "\n",
      "dog_filter = KalmanFilter(dim_x=2, dim_z=1)\n",
      "help(KalmanFilter.__init__)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Help on function __init__ in module filterpy.kalman.kalman_filter:\n",
        "\n",
        "__init__(self, dim_x, dim_z, dim_u=0)\n",
        "    Create a Kalman filter. You are responsible for setting the\n",
        "    various state variables to reasonable values; the defaults below will\n",
        "    not give you a functional filter.\n",
        "    \n",
        "    **Parameters**\n",
        "    \n",
        "    dim_x : int\n",
        "        Number of state variables for the Kalman filter. For example, if\n",
        "        you are tracking the position and velocity of an object in two\n",
        "        dimensions, dim_x would be 4.\n",
        "    \n",
        "        This is used to set the default size of P, Q, and u\n",
        "    \n",
        "    dim_z : int\n",
        "        Number of of measurement inputs. For example, if the sensor\n",
        "        provides you with position in (x,y), dim_z would be 2.\n",
        "    \n",
        "    dim_u : int (optional)\n",
        "        size of the control input, if it is being used.\n",
        "        Default value of 0 indicates it is not used.\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "That's it. We import the filter, and create a filter that uses 2 state variables. We specify the number of state variables with the 'dim=2' expression (dim means dimensions).\n",
      "\n",
      "The Kalman filter class contains a number of variables that you need to set. x is the state, F is the state transition function, and so on. Rather than talk about it, let's just do it!"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dog_filter.x = np.array([0., 0.])        # state (location and velocity)\n",
      "dog_filter.F = np.array([[1, 1], [0, 1]])  # state transition matrix\n",
      "dog_filter.H = np.array([[1, 0]])          # Measurement function\n",
      "dog_filter.R *= 5                          # measurement noise\n",
      "dog_filter.Q = Q_discrete_white_noise(2, dt=0.1, var=0.1) # process noise\n",
      "dog_filter.P *= 500.                       # covariance matrix "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 37
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's look at this line by line. \n",
      "\n",
      "**1**: We just assign the initial value for our state. Here we just initialize both the position and velocity to zero. \n",
      "\n",
      "**2**: We set $\\textbf{F}=\\begin{bmatrix}1&1\\\\0&1\\end{bmatrix}$, as in design step 2 above. \n",
      "\n",
      "**3**: We set $\\textbf{H}=\\begin{bmatrix}1&0\\end{bmatrix}$, as in design step 3 above.\n",
      "\n",
      "**4**: We set $\\textbf{R} = \\begin{bmatrix}5\\end{bmatrix}$. $\\textbf{R}$ is initialized to the identity matrix, so multiplying by 5 performs this assignment for us.\n",
      "\n",
      "**5** We use the `Q_discrete_white_noise()` method to set $\\mathbf{Q}$'s variance to 0.1.\n",
      "\n",
      "**5**: $\\mathbf{P}$ is initialized to the identity matrix of size $n{\\times}n$, so multiplying by 500 assigns a variance of 500 to $x$ and $\\dot{x}$. So $\\verb,f.P,$ contains\n",
      "\n",
      "$$\\begin{bmatrix} 500&0\\\\0&500\\end{bmatrix}$$\n",
      "\n",
      "All that is left is to run the code! The `DogSensor` class from the previous chapter has been placed in `DogSensor.py`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "from DogSensor import DogSensor\n",
      "from filterpy.kalman import KalmanFilter\n",
      "\n",
      "def dog_tracking_filter(R, Q=0, cov=1.):\n",
      "    dog_filter = KalmanFilter(dim_x=2, dim_z=1)\n",
      "    dog_filter.x = np.array([0., 0.])    # (location and velocity)\n",
      "    dog_filter.F = np.array([[1, 1],\n",
      "                             [0, 1]]) # state transition matrix\n",
      "    dog_filter.H = np.array([[1, 0]]) # Measurement function\n",
      "    dog_filter.R *= R                 # measurement uncertainty\n",
      "    dog_filter.P *= cov               # covariance matrix \n",
      "    if np.isscalar(Q):\n",
      "        dog_filter.Q = Q_discrete_white_noise(dim=2, dt=0.1, var=Q)\n",
      "    else:\n",
      "        dog_filter.Q = Q\n",
      "    return dog_filter\n",
      "\n",
      "\n",
      "def filter_dog(noise_var=0, count=0, R=0, Q=0, P=500., data=None, \n",
      "               initial_x=None):\n",
      "    \"\"\" Kalman filter 'count' readings from the DogSensor.\n",
      "    'noise_var' is the variance of the noise from the measurements.\n",
      "    'data' provides the measurements. If set, noise will\n",
      "    be ignored and data will not be generated for you.\n",
      "    \n",
      "    returns a tuple of (positions, measurements, covariance)\n",
      "    \"\"\"\n",
      "    if data is None:    \n",
      "        dog = DogSensor(velocity=1, noise_var=noise_var)\n",
      "        zs = [dog.sense() for t in range(count)]\n",
      "    else:\n",
      "        zs = data\n",
      "\n",
      "    dog_filter = dog_tracking_filter(R=R, Q=Q, cov=P)\n",
      "    if initial_x is not None:\n",
      "        dog_filter.x = initial_x\n",
      "\n",
      "    pos = [None] * count\n",
      "    cov = [None] * count\n",
      "    \n",
      "    for t in range(count):\n",
      "        z = zs[t]\n",
      "        pos[t] = dog_filter.x[0]\n",
      "        cov[t] = dog_filter.P\n",
      "    \n",
      "        # perform the kalman filter steps\n",
      "        dog_filter.update(z)\n",
      "        dog_filter.predict()\n",
      "        \n",
      "    return (pos, zs, cov)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 38
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is the complete code for the filter, and most of it is just boilerplate. The first function `dog_tracking_filter()` is a helper function that creates a `KalmanFilter` object with specified $\\mathbf{R}$, $\\mathbf{Q}$ and $\\mathbf{P}$ matrices. We've shown this code already, so I will not discuss it more here. \n",
      "\n",
      "The function `filter_dog()` implements the filter itself.  Lets work through it line by line. The first line creates the simulation of the DogSensor, as we have seen in the previous chapter.\n",
      "\n",
      "    dog = DogSensor(velocity=1, noise=noise)\n",
      "\n",
      "The next line uses our helper function to create a Kalman filter.\n",
      "\n",
      "    dog_filter = dog_tracking_filter(R=R, Q=Q, cov=500.)\n",
      "    \n",
      "We will want to plot the filtered position, the measurements, and the covariance, so we will need to store them in lists. The next three lines initialize empty lists of length *count* in a pythonic way.\n",
      "\n",
      "    pos = [None] * count\n",
      "    zs  = [None] * count\n",
      "    cov = [None] * count\n",
      "    \n",
      "Finally we get to the filter. All we need to do is perform the update and predict steps of the Kalman filter for each measurement. The `KalmanFilter` class provides the two functions `update()` and `predict()` for this purpose. `update()` performs the measurement update step of the Kalman filter, and so it takes a variable containing the sensor measurement. \n",
      "\n",
      "Absent the bookkeeping work of storing the filter's data, the for loop reads:\n",
      "\n",
      "    for t in range (count):\n",
      "        z = dog.sense()\n",
      "        dog_filter.update (z)\n",
      "        dog_filter.predict()\n",
      "    \n",
      "It really cannot get much simpler than that. As we tackle more complicated problems this code will remain largely the same; all of the work goes into setting up the `KalmanFilter` variables; executing the filter is trivial.\n",
      "\n",
      "Now let's look at the result. Here is some code that calls `filter_track()` and then plots the result. It is fairly uninteresting code, so I will not walk through it."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import book_plots as bp\n",
      "\n",
      "def plot_track(noise_var=None, count=0, R_var=0, Q_var=0, P=500., \n",
      "               initial_x=None,data=None, plot_P=True, y_lim=None,\n",
      "               title='Kalman Filter'):\n",
      "    \n",
      "    ps, zs, cov = filter_dog(noise_var=noise_var, data=data, count=count,\n",
      "                             R=R_var, Q=Q_var, P=P, initial_x=initial_x)\n",
      "    \n",
      "    actual = np.linspace(0, count-1, count)\n",
      "    cov = np.asarray(cov)\n",
      "    std = np.sqrt(cov[:,0,0])\n",
      "    std_top = np.minimum(actual+std, [count+10])\n",
      "    std_btm = np.maximum(actual-std, [-50])\n",
      "\n",
      "    std_top = actual+std\n",
      "    std_btm = actual-std\n",
      "    \n",
      "    bp.plot_track(actual)\n",
      "    bp.plot_measurements(range(1, count+1), zs)\n",
      "    bp.plot_filter(range(1, count+1), ps)\n",
      "\n",
      "    plt.plot(actual+std, linestyle=':', c='k', lw=2)\n",
      "    plt.plot(actual-std, linestyle=':', c='k', lw=2)\n",
      "    plt.fill_between(range(count), std_btm, std_top,\n",
      "                     facecolor='yellow', alpha=0.2)\n",
      "    plt.legend(loc=4)\n",
      "    if y_lim is not None:\n",
      "        plt.ylim(y_lim)\n",
      "    else:\n",
      "        plt.ylim((-50, count+10))\n",
      "        \n",
      "    plt.xlim((0,count))\n",
      "    plt.title(title)\n",
      "    plt.show()\n",
      "    \n",
      "    if plot_P:\n",
      "        ax = plt.subplot(121)\n",
      "        ax.set_title(\"$\\sigma^2_x$\")\n",
      "        plot_covariance(cov, (0, 0))\n",
      "        ax = plt.subplot(122)\n",
      "        ax.set_title(\"$\\sigma^2_y$\")\n",
      "        plot_covariance(cov, (1, 1))      \n",
      "        plt.show()\n",
      "    \n",
      "def plot_covariance(P, index=(0, 0)):\n",
      "    ps = []\n",
      "    for p in P:\n",
      "        ps.append(p[index[0], index[1]])\n",
      "    plt.plot(ps)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Finally, call it. We will start by filtering 50 measurements with a noise variance of 10 and a process variance of 0.01."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_track(noise_var=10, R_var=10., Q_var=0.01, count=50, y_lim=(-20,50))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGaCAYAAAD+VYcoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85f07c9f60>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyIAAAGgCAYAAABWqtOkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7cb3b00>"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There is still a lot to learn, but we have implemented our first, full Kalman filter using the same theory and equations as published by Rudolf Kalman! Code very much like this runs inside of your GPS and phone, inside every airliner, inside of robots, and so on. \n",
      "\n",
      "The first plot plots the output of the Kalman filter against the measurements and the actual position of our dog (drawn in green). After the initial settling in period the filter should track the dog's position very closely. The yellow shaded portion between the black dotted lines shows 1 standard deviations of the filter's variance, which I explain in the next paragrah.\n",
      "\n",
      "The next two plots show the variance of $x$ and of $\\dot{x}$. If you look at the code, you will see that I have plotted the diagonals of $\\mathbf{P}$ over time. Recall that the diagonal of a covariance matrix contains the variance of each state variable. So $\\mathbf{P}[0,0]$ is the variance of $x$, and $\\mathbf{P}[1,1]$ is the variance of $\\dot{x}$. You can see that despite initializing $\\mathbf{P}=(\\begin{smallmatrix}500&0\\\\0&500\\end{smallmatrix})$ we quickly converge to small variances for both the position and velocity. The covariance matrix $\\mathbf{P}$ tells us the *theoretical* performance of the filter *assuming* everything we tell it is true. Recall from the Gaussian chapter that the standard deviation is the square root of the variance, and that approximately 68% of a Gaussian distribution occurs within one standard deviation. Therefore, if at least 68% of the filter output is within one standard deviation we can be sure that the filter is performing well. In the top chart I have displayed the one standard deviation as the yellow shaded area between the two dotted lines. To my eye it looks like perhaps the filter is slightly exceeding that bounds, so the filter probably needs some tuning. We will discuss this later in the chaper."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In the previous chapter we filtered very noisy signals with much simpler code than the code above. However, realize that right now we are working with a very simple example - an object moving through 1-D space and one sensor. That is about the limit of what we can compute with the code in the last chapter. In contrast, we can implement very complicated, multidimensional filter with this code merely by altering are assignments to the filter's variables. Perhaps we want to track 100 dimensions in financial models. Or we have an aircraft with a GPS, INS, TACAN, radar altimeter, baro altimeter, and airspeed indicator, and we want to integrate all those sensors into a model that predicts position, velocity, and accelerations in 3D (which requires 9 state variables). We can do that with the code in this chapter."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Compare to Univariate Kalman Filter"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The equations in this chapter look very different from the equations in the last chapter, yet I claimed the last chapter implemented a full 1-D (univariate) Kalman filter. \n",
      "\n",
      "Recall that the univariate equations for the update step are:\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mu &=\\frac{\\sigma_1^2 \\mu_2 + \\sigma_2^2 \\mu_1} {\\sigma_1^2 + \\sigma_2^2}, \\\\\n",
      "\\sigma^2 &= \\frac{1}{\\frac{1}{\\sigma_1^2} + \\frac{1}{\\sigma_2^2}}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "and that the 1-D equations for the predict step are:\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mu &= \\mu_1+\\mu_2, \\\\ \\sigma^2 &= \\sigma_1^2 + \\sigma_2^2\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "Let's implement a simple 1-D kalman filter using the Kalman filter from this chapter, and compare its output to the kalman filter from the previous chapter by plotting it. We will use a simple model of tracking an object that starts at x=0 and moves by 1 at each step. We will assume the arbitrary value 5 for the measurement noise and .02 for the process noise.\n",
      "\n",
      "First, let's implement the filter from the last chapter:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division\n",
      "import numpy as np\n",
      "from numpy.random import randn\n",
      "from filterpy.kalman import KalmanFilter\n",
      "\n",
      "# 1-D Kalman filter equations\n",
      "def predict(pos, variance, movement, movement_variance):\n",
      "    return (pos + movement, variance + movement_variance)\n",
      "\n",
      "\n",
      "def update (mu1, var1, mu2, var2):\n",
      "    mean = (var1*mu2 + var2*mu1) / (var1+var2)\n",
      "    variance = 1 / (1/var1 + 1/var2)\n",
      "    return (mean, variance)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 41
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now, let's implement the same thing using the kalman filter. I will implement it as a function that returns a KalmanFilter object so that you can run the analysis code several times with the KalmanFilter initialized to the same starting conditions each time."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from filterpy.kalman import KalmanFilter\n",
      "\n",
      "def mkf_filter(R, Q):\n",
      "    f = KalmanFilter(dim_x=1, dim_z=1, dim_u=1)\n",
      "    f.P = 500.\n",
      "    f.H = np.array([[1.]])\n",
      "    f.F = np.array([[1.]])\n",
      "    f.B = np.array([[1.]])\n",
      "    f.Q = Q\n",
      "    f.R = R\n",
      "    \n",
      "    return f"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 42
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Finally, let's compare the two. I will plot the data from the 1-D Kalman filter as a blue line, and the output of the filter from this chapter as red dots. I wrote it as a function so you can easily modify the parameters and regenerate the plots."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def plot_kf_compare(x0, p0, R, Q, move):\n",
      "    # storage for filter output\n",
      "    x1,x2 = [], []\n",
      "    p1, p2 = [], []\n",
      "\n",
      "    # initialize the filters\n",
      "    f = mkf_filter(R, Q)\n",
      "    f.x[0] = 0.\n",
      "    f.P[0, 0] = p0\n",
      "    pos = (x0, p0)\n",
      "    for i in range(50):\n",
      "        z = i*move + randn()\n",
      "        pos = update(pos[0], pos[1], z, R)\n",
      "        f.update(z)\n",
      "\n",
      "        x1.append(pos[0])\n",
      "        x2.append(f.x[0])\n",
      "\n",
      "        p1.append(pos[1])\n",
      "        p2.append(f.P[0, 0])\n",
      "\n",
      "        u = move + randn()\n",
      "        pos = predict(pos[0], pos[1], u, Q)\n",
      "        f.predict(u=u)\n",
      "\n",
      "    plt.scatter(range(len(x2)), x2, c='r')\n",
      "    plt.title('State')\n",
      "    plt.plot(x1)\n",
      "    plt.xlim([0, 50])\n",
      "\n",
      "    plt.figure()\n",
      "    plt.plot(p1)\n",
      "    plt.scatter(range(len(x2)), p2, c='r')\n",
      "    plt.title('Variance')\n",
      "    plt.xlim([0, 50])\n",
      "    plt.show()\n",
      "    \n",
      "plot_kf_compare(x0=0., p0=500., R=5., Q=.2, move=1.)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGaCAYAAAD+VYcoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAADANAQSAAAAAKb5PzfAF6Jghqx4AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7ba50f0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxEAAAGaCAYAAABwj85UAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e798a518>"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### Discussion\n",
      "\n",
      "As you can see, both filters produce the same results. Feel free to vary the initial guess, the measurement noise, and the process noise; so long as you make the same changes to both filters the output should be the same. This is a solid demonstration, albeit not a rigorous proof, that both filters in fact implement the same math for the 1-D case. "
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Converting the Multivariate Equations to the Univariate Case"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\n",
      "As it turns out the Kalman filter equations are quite easy to deal with in one dimension, so let's do the mathematical proof. \n",
      "\n",
      "> **Note:** This section will provide you with a strong intuition into what the Kalman filter equations are actually doing. While this section is not strictly required, I recommend reading this section carefully as it should make the rest of the material easier to understand. It is not merely a proof of correctness that you would normally want to skip past! The equations look complicated, but they are actually doing something quite simple.\n",
      "\n",
      "Let'start with the predict step, which is slightly easier. Here are the multivariate equations. \n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{x}^- &= \\mathbf{F x} + \\mathbf{B u} \\\\\n",
      "\\mathbf{P^-} &= \\mathbf{FP{F}}^\\mathsf{T} + \\mathbf{Q}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "The state $\\mathbf{x}$ only has one variable, so it is a $1\\times 1$ matrix. Our motion $\\mathbf{u}$ is also be a $1\\times 1$ matrix. Therefore, $\\mathbf{F}$ and $\\mathbf{B}$ must also be $1\\times 1$ matrices. That means that they are all scalars, and we can write\n",
      "\n",
      "$$x = Fx + Bu$$\n",
      "\n",
      "Here the variables are not bold, denoting that they are not matrices or vectors. \n",
      "\n",
      "Our state transition is simple - the next state is the same as this state, so $F=1$. The same holds for the motion transition, so, $B=1$. Thus we have\n",
      "$$x = x + u$$\n",
      "\n",
      "which is equivalent to the Gaussian equation from the last chapter\n",
      "\n",
      "$$ \\mu = \\mu_1+\\mu_2$$\n",
      "\n",
      "Hopefully the general process is clear, so now I will go a bit faster on the rest. Our other equation for the predict step is\n",
      "\n",
      "$$\\mathbf{P}^- = \\mathbf{FP{F}}^\\mathsf{T} + \\mathbf{Q}$$\n",
      "\n",
      "Again, since our state only has one variable $\\mathbf{P}$ and $\\mathbf{Q}$ must also be $1\\times 1$ matrix, which we can treat as scalars, yielding  \n",
      "$$P^- = FPF^\\mathsf{T} + Q$$\n",
      "\n",
      "We already know $F=1$. The transpose of a scalar is the scalar, so $F^\\mathsf{T} = 1$. This yields\n",
      "\n",
      "$$P^- = P + Q$$\n",
      "\n",
      "which is equivalent to the Gaussian equation of \n",
      "$$\\sigma^2 = \\sigma_1^2 + \\sigma_2^2$$\n",
      "\n",
      "This proves that the multivariate equations are performing the same math as the univariate equations for the case of the dimension being 1."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here our our multivariate Kalman filter equations for the update step.\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\textbf{y} &= \\mathbf{z} - \\mathbf{H x^-}\\\\\n",
      "\\mathbf{K}&= \\mathbf{P^-H}^\\mathsf{T} (\\mathbf{HP^-H}^\\mathsf{T} + \\mathbf{R})^{-1} \\\\\n",
      "\\mathbf{x}&=\\mathbf{x}^- +\\mathbf{K\\textbf{y}} \\\\\n",
      "\\mathbf{P}&= (\\mathbf{I}-\\mathbf{KH})\\mathbf{P^-}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "As above, all of the matrices become scalars. $H$ defines how we convert from a position to a measurement. Both are positions, so there is no conversion, and thus $H=1$. Let's substitute in our known values and convert to scalar in one step. One final thing you need to know - division is scalar's analogous operation for matrix inversion, so we will convert the matrix inversion to division.\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "y &= z - x^-\\\\\n",
      "K &=P^- / (P^- + R) \\\\\n",
      "x &=x +Ky \\\\\n",
      "P &= (1-K)P^-\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "Before we continue with the proof, I want you to look at those equations to recognize what a simple concept these equations implement. The residual $y$ is nothing more than the measurement minus the previous state. The gain $K$ is scaled based on how certain we are about the last prediction vs how certain we are about the measurement. We choose a new state $x$ based on the old value of $x$ plus the scaled value of the residual. Finally, we update the uncertainty based on how certain we are about the measurement. Algorithmically this should sound exactly like what we did in the last chapter.\n",
      "\n",
      "So let's finish off the algebra to prove this. It's straightforward, and not at all  necessary for you to learn unless you are interested. Feel free to skim ahead to the last paragraph in this section if you prefer skipping the algebra.\n",
      "\n",
      "Recall that the univariate equations for the update step are:\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mu &=\\frac{\\sigma_1^2 \\mu_2 + \\sigma_2^2 \\mu_1} {\\sigma_1^2 + \\sigma_2^2}, \\\\\n",
      "\\sigma^2 &= \\frac{1}{\\frac{1}{\\sigma_1^2} + \\frac{1}{\\sigma_2^2}}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "Here we will say that $\\mu_1$ is the state $x$, and $\\mu_2$ is the measurement $z$. That is entirely arbitrary, we could have chosen the opposite assigment. \n",
      "Thus it follows that that $\\sigma_1^2$ is the state uncertainty $P$, and $\\sigma_2^2$ is the measurement noise $R$. Let's substitute those in.\n",
      "\n",
      "$$ \\mu = \\frac{Pz + Rx}{P+R} \\\\\n",
      "\\sigma^2 = \\frac{1}{\\frac{1}{P} + \\frac{1}{R}}\n",
      "$$\n",
      "\n",
      "I will handle $\\mu$ first. The corresponding equation in the multivariate case is\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "x &= x + Ky \\\\\n",
      " &= x + \\frac{P}{P+R}(z-x) \\\\\n",
      " &= \\frac{P+R}{P+R}x + \\frac{Pz - Px}{P+R} \\\\\n",
      " &= \\frac{Px + Rx + Pz - Px}{P+R} \\\\\n",
      " &= \\frac{Pz + Rx}{P+R} \\quad \\blacksquare\n",
      "\\end{aligned}\n",
      "$$"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now let's look at $\\sigma^2$. The corresponding equation in the multivarate case is\n",
      "\n",
      "$$ \n",
      "\\begin{aligned}\n",
      "P &= (1-K)P \\\\\n",
      " &= (1-\\frac{P}{P+R})P \\\\\n",
      " &= (\\frac{P+R}{P+R}-\\frac{P}{P+R})P \\\\\n",
      "  &= (\\frac{P+R-P}{P+R})P \\\\\n",
      "  &= \\frac{RP}{P+R}\\\\\n",
      "  &= \\frac{1}{\\frac{P+R}{RP}}\\\\\n",
      "  &= \\frac{1}{\\frac{R}{RP} + \\frac{P}{RP}} \\\\\n",
      "  &= \\frac{1}{\\frac{1}{P} + \\frac{1}{R}}\n",
      " \\quad\\blacksquare\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "So we have proven that the multivariate equations are equivalent to the univariate equations when we only have one state variable. I'll close this section by recognizing one quibble - I hand waved my assertion that $H=1$ and $F=1$. In general we know this is not true. For example, a digital thermometer may provide measurement in volts, and we need to convert that to temperature, and we use $H$ to do that conversion. I left that issue out of the last chapter to keep the explanation as simple and streamlined as possible. It is very straightforward to add that generalization to the equations of the last chapter, redo the algebra above, and still have the same results. In practice we do not use the equations in the last chapter to perform Kalman filtering due to the material in the next section which demonstrates how much better the Kalman filter performs when we include unobserved variables. So I prefer to leave the equations from the last chapter in their simplest form so that they economically represent our central ideas without any extra complications."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### Exercise: Compare to a Filter That Incorporates Velocity\n",
      "\n",
      "The last example did not use one of the fundamental insights of this chapter, unobserved variables. In this example velocity would the the unobserved variable. Write a Kalman filter that uses the state $\\mathbf{x}=\\begin{bmatrix}x & \\dot{x}\\end{bmatrix}^\\mathsf{T}$ and compare it against the filter in the last exercise which used the state $\\mathbf{x}=\\begin{bmatrix}x\\end{bmatrix}$."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# your code here"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 44
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### Solution\n",
      "\n",
      "We've already implemented a Kalman filter for position and velocity, so I will provide the code without much comment, and then plot the result."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def pos_vel_filter(R,Q):\n",
      "    f = KalmanFilter(dim_x=2, dim_z=1)\n",
      "    f.R = R\n",
      "    f.Q = Q_discrete_white_noise(dim=2, dt=0.1, var=Q)\n",
      "   \n",
      "    f.F = np.array([[1, 1],\n",
      "                    [0, 1]])  # state transition matrix\n",
      "    f.H = np.array([[1, 0]])  # Measurement function\n",
      "    return f\n",
      "\n",
      "def plot_compare_pos_vel(x0, p0, R, Q, move):\n",
      "    # storage for filter output\n",
      "    x1, x2 = [], []\n",
      "\n",
      "    # initialize the filters\n",
      "    f1 = mkf_filter(R, Q)\n",
      "    f1.x[0] = 0.\n",
      "    f1.P[0, 0] = p0\n",
      "    \n",
      "    f2 = pos_vel_filter(R, Q)\n",
      "    f2.x[0] = 0.\n",
      "    f2.x[1] = 1.\n",
      "    f2.P *= p0\n",
      "    \n",
      "    for i in range(50):\n",
      "        u = move + randn()\n",
      "        f1.predict(u=u)\n",
      "        f2.predict(u=u)\n",
      "        \n",
      "        z = i*move + randn()\n",
      "        f1.update(z)\n",
      "        f2.update(z)\n",
      "        \n",
      "        x1.append(f1.x[0, 0])\n",
      "        x2.append(f2.x[0, 0])\n",
      "\n",
      "    plt.plot(x1, label='1D Filter')\n",
      "    plt.scatter(range(len(x2)), x2, c='r', label='2D Filter')\n",
      "    plt.title('State')\n",
      "    plt.legend(loc=4)\n",
      "    plt.xlim([0,50])\n",
      "    plt.show()\n",
      "    \n",
      "plot_compare_pos_vel(x0=0., p0=500., R=5., Q=.2, move=1.)    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGaCAYAAAD+VYcoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nDCREREREROQwDCREREREROQw/x/SpEwHbiuEnQAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e79ab668>"
       ]
      }
     ],
     "prompt_number": 45
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### Discussion\n",
      "\n",
      "The output of the filter that incorporates velocity into the state produces much better output than the filter that only tracks position - the output is much closer to a straight line. We've already discussed why unobserved variables increase the precision of the filter, so I will not repeat that explanation here. But the last exercise and this one is intended to trigger a train of thought:\n",
      "\n",
      "1. The equations in this chapter are mathematically equivalient to the equations in the last chapter when we are only tracking one state variable.\n",
      "    \n",
      "2. Therefore, the simple Bayesian reasoning we used in the last chapter applies to this chapter as well.\n",
      "\n",
      "3. Therefore, the equations in this chapter might 'look ugly', but they really are just implementing multiplying and addition of Gaussians.\n",
      "\n",
      "> The above might not seem worth emphasizing, but as we continue in the book the mathematical demands will increase significantly. It is easy to get lost in a thicket of linear algebra equations when you read a book or paper on optimal estimation. Any time you start getting lost, just go back to the basics of the predict/update cycle based on residuals between measurements and predictions and the meaning of the math will usually be much clearer. The math *looks* daunting, and can sometimes be very hard to solve analytically, but the concepts are quite simple."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Adjusting the Filter"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Your results will vary slightly depending on what numbers your random generator creates for the noise component of the noise, but the filter in the last section should track the actual position quite well. Typically as the filter starts up the first several predictions are quite bad, and varies a lot. But as the filter builds its state the estimates become much better. \n",
      "\n",
      "Let's start varying our parameters to see the effect of various changes. This is a *very normal* thing to be doing with Kalman filters. It is difficult, and often impossible to exactly model our sensors. An imperfect model means imperfect output from our filter. Engineers spend a lot of time tuning Kalman filters so that they perform well with real world sensors. We will spend time now to learn the effect of these changes. As you learn the effect of each change you will develop an intuition for how to design a Kalman filter. As I wrote earlier, designing a Kalman filter is as much art as science. The science is, roughly, designing the ${\\mathbf{H}}$ and ${\\mathbf{F}}$ matrices - they develop in an obvious manner based on the physics of the system we are modeling. The art comes in modeling the sensors and selecting appropriate values for the rest of our variables.\n",
      "\n",
      "Let's look at the effects of the noise parameters ${\\mathbf{R}}$ and ${\\mathbf{Q}}$. We will want to see the effect of different settings for ${\\mathbf{R}}$ and ${\\mathbf{Q}}$, so I have hard coded our measurements in `zs` based on a variance of 50 meters. That is very large, but it magnifies the effects of varius design choices on the graphs, making it easier to recognize what is happening. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# dog = DogSensor(velocity=1, noise_var=50)\n",
      "# zs = [dog.sense() for t in range(50)]\n",
      "# I've hard coded zs to ensure we are all looking at the same data\n",
      "zs = [3.59, 1.73, -2.575, 4.38, 9.71, 2.88, 10.08, 8.97, 3.74,\n",
      "      12.81, 11.15, 9.25, 3.93, 11.11, 19.29,  16.20, 19.63,\n",
      "      9.54, 26.27, 23.29, 25.18, 26.21, 17.1, 25.27, 26.86,\n",
      "      33.70, 25.92, 28.82, 32.13, 25.0, 38.56, 26.97, 22.49,\n",
      "      40.77, 32.95, 38.20, 40.93, 39.42, 35.49, 36.31, 31.56,\n",
      "      50.29, 40.20, 54.49, 50.38, 42.79, 37.89, 56.69, 41.47, 53.66]\n",
      "    \n",
      "plot_track(data=zs, R_var=50, Q_var=20, count=50, plot_P=False, \n",
      "           title='R_var = 50 m, Q_var = 20 m')\n",
      "\n",
      "plot_track(data=zs, R_var=50, Q_var=.02, count=50, plot_P=False, \n",
      "           title='R_var = 50 m, Q_var = 0.02 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGZCAYAAAB4wfWGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\naliQEBERERGRav4PxlSN8cxKX14AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e778ccc0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGZCAYAAAB4wfWGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nERGp5v8A2L+dufEwuuYAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7c71048>"
       ]
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The filter in the first plot should follow the noisy measurement almost exactly. In the second plot the filter should vary from the measurement quite a bit, and be much closer to a straight line than in the first graph. \n",
      "\n",
      "In the Kalman filter ${\\mathbf{R}}$ is the *measurement noise* and ${\\mathbf{Q}}$ is the *process uncertainty*. ${\\mathbf{R}}$ is the same in both plots, so ignore it for the moment. Why does ${\\mathbf{Q}}$ affect the plots this way?\n",
      "\n",
      "Let's remind ourselves of what the term *process uncertainty* means. Consider the problem of tracking a ball. We can accurately model its behavior in static air with math, but if there is any wind our model will diverge from reality. \n",
      "\n",
      "In the first case we set `Q_var=20 m`, which is quite large. In physical terms this is telling the filter \"I don't trust my motion prediction step\" as we are saying that the variance in the velocity is 10. Strictly speaking, we are telling the filter there is a lot of external noise that we are not modeling with $\\small{\\mathbf{F}}$, but the upshot of that is to not trust the motion prediction step. So the filter will be computing velocity ($\\dot{x}$), but then mostly ignoring it because we are telling the filter that the computation is extremely suspect. Therefore the filter has nothing to use but the measurements, and thus it follows the measurements closely. \n",
      "\n",
      "In the second case we set `Q_var=0.02 m`, which is quite small. In physical terms we are telling the filter \"trust the motion computation, it is really good!\". Again, more strictly this actually says there is very small amounts of process noise (variance 0.02 m), so the motion computation will be accurate. So the filter ends up ignoring some of the measurement as it jumps up and down, because the variation in the measurement does not match our trustworthy velocity prediction."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now let's set `Q_var=0.2 m`, and bump `R_var` up to 10,000 m. This is telling the filter that the measurement noise is very large. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_track(data=zs, R_var=10000., Q_var=.2, count=50, plot_P=False, \n",
      "           title='R_var = 10000 m, Q_var = 0.2 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGZCAYAAAB4wfWGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwzZeYZXMAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7c0ada0>"
       ]
      }
     ],
     "prompt_number": 47
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The effect of this can be subtle. We have created an suboptimal filter because the actual measurement noise variance is 30 m, not 10,000 m. By setting the filter's noise variance so high we force the filter to favor the prediction over the measurement. This can lead to apparently very smooth and good looking results. In the chart above the track may look extremely good to you since it follows the ideal path very closely. But, the 'great' behavior at the start should give you pause - the filter has not converged yet ($\\mathbf{P}$ is still large) so it should not be able to be so close to the actual position. We can see that $\\mathbf{P}$ has not converged because the entire chart is colored with the yellow background denoting the size of $\\mathbf{P}$. Let's make $\\mathbf{R}$ larger yet. Let's see the result of a bad initial guess for the position by guessing the initial position to be 20 m and the initial velocity to be 1 m/s."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_track(data=zs, R_var=10000., Q_var=.2, count=50, \n",
      "           initial_x=np.array([20., 1.]), plot_P=False, \n",
      "           title='R_var = 10000 m, Q_var = 0.2 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGZCAYAAAB4wfWGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n0xJPK8CLAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7b70940>"
       ]
      }
     ],
     "prompt_number": 48
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here we can see that the filter cannot acquire the actual track at all. This happens because even though the filter is getting reasonable good measurements it assumes that the measurements are bad, and eventually just predicts forward from a bad position at each step. If you think that perhaps that bad initial position would give similar results for a smaller measurement noise, let's set it back to the correct value of 50 m."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_track(data=zs, R_var=30, Q_var=.2, count=50, \n",
      "           initial_x=np.array([20., 1.]), plot_P=False, \n",
      "           title='R_var = 30 m, Q_var = 0.2 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGZCAYAAAB4wfWGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n99SgrAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e79657b8>"
       ]
      }
     ],
     "prompt_number": 49
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here we see that the filter initially struggles for several iterations to acquire the track, but then it accurately tracks our dog. In fact, this is nearly optimum - we have not designed $\\mathbf{Q}$ optimally, but $\\mathbf{R}$ is optimal, and thus will yield optimal results. Recall that our rule of thumb for the variance of $\\mathbf{Q}$ was to set it between $\\frac{1}{2}\\Delta a$ to $\\Delta a$, where $\\Delta a$ is the maximum amount that the acceleration will change between sample period. This only applies for the assumption we are making in this chapter - that acceleration is constant and uncorrelated between each time period. In the Kalman Math chapter we will discuss several different ways of designing $\\mathbf{Q}$.\n",
      "\n",
      "To some extent you can get similar looking output by varying either ${\\mathbf{R}}$ or ${\\mathbf{Q}}$, but I urge you to not 'magically' alter these until you get output that you like. Always think about the physical implications of these assignments, and vary ${\\mathbf{R}}$ and/or ${\\mathbf{Q}}$ based on your knowledge of the system you are filtering."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "A Detailed Examination of the Covariance Matrix"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So far I have not given a lot of coverage of the covariance matrix $\\mathbf{P}$. It is nothing more than the variance of our state - such as the position and velocity of our dog. It has many elements in it, but don't be daunted; we will learn how to interpret a very large $9{\\times}9$ covariance matrix, or even larger.\n",
      "\n",
      "Recall the beginning of the chapter, where we provided the equation for the covariance matrix. It read:\n",
      "\n",
      "$$\n",
      "\\Sigma = \\begin{pmatrix}\n",
      "  \\sigma_1^2 & \\sigma_{12} & \\cdots & \\sigma_{1n} \\\\\n",
      "  \\sigma_{21} &\\sigma_2^2 & \\cdots & \\sigma_{2n} \\\\\n",
      "  \\vdots  & \\vdots  & \\ddots & \\vdots  \\\\\n",
      "  \\sigma_{n1} & \\sigma_{n2} & \\cdots & \\sigma_n^2\n",
      " \\end{pmatrix}\n",
      "$$\n",
      "\n",
      "(The Kalman filter literature uses $\\mathbf{P}$ for $\\Sigma$; they both denote the same thing.)\n",
      "\n",
      "The diagonal contains the variance of each of our state variables. So, if our state variables are\n",
      "\n",
      "$$\\textbf{x}=\\begin{bmatrix}x\\\\\\dot{x}\\end{bmatrix}$$\n",
      "\n",
      "and the covariance matrix happens to be\n",
      "$$\\textbf{P}=\\begin{bmatrix}2&0\\\\0&6\\end{bmatrix}$$\n",
      "\n",
      "we know that the variance of $x$ is 2 m, and the variance of $\\dot{x}$ is 6 m/s. The off diagonal elements are all 0, so we also know that $x$ and $\\dot{x}$ are not correlated. Recall the ellipses that we drew of the covariance matrices. Let's look at the ellipse for the matrix."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P = np.array([[2., 0.], \n",
      "              [0., 6.]])\n",
      "stats.plot_covariance_ellipse((0, 0), P,  facecolor='g', alpha=0.2,\n",
      "                              title='|2 0|\\n|0 6|')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxQAAAGxCAYAAAD7zfDlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niIiIaM5YUBARERER0Zz9A8ogxo6h3d6DAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7745a58>"
       ]
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Of course it is unlikely that the position and velocity of an object remain uncorrelated for long. Let's look at a more typical covariance matrix"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "P = np.array([[2.0, 2.4],\n",
      "              [2.4, 6.0]])\n",
      "stats.plot_covariance_ellipse((0, 0), P,  facecolor='g', alpha=0.2, \n",
      "                              title='|2.0  2.4|\\n|2.4  6.0|')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxQAAAGxCAYAAAD7zfDlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAMo1AAAAAAMOy/VRDM8kHtWWgAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7a045f8>"
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here the ellipse is slanted, signifying that $x$ and $\\dot{x}$ are correlated (and, of course, dependent - all correlated variables are dependent). You may or may not have noticed that the off diagonal elements were set to the same value, 2.4. This was not an accident. Let's look at the equation for the covariance for the case where the number of dimensions is two.\n",
      "\n",
      "$$\n",
      "\\mathbf{P} = \\begin{pmatrix}\n",
      "  \\sigma_1^2 & \\sigma_{1,2} \\\\\n",
      "  \\sigma_{2,1} &\\sigma_2^2 \n",
      " \\end{pmatrix}\n",
      "$$\n",
      "\n",
      "Here the notation $\\sigma_{1,2}$ means the covariance of variables 1 and 2 where that is defined as\n",
      "\n",
      "$$\\sigma_{i,j}\n",
      "= \\mathrm{cov}(X_i, X_j) = \\mathrm{E}\\begin{bmatrix}\n",
      "(X_i - \\mu_i)(X_j - \\mu_j)\n",
      "\\end{bmatrix}$$\n",
      "\n",
      "\n",
      "We can rearrange the terms to get\n",
      "\n",
      "$$\\begin{aligned}\n",
      "\\sigma_{i,j} &= \\mathrm{E}\\begin{bmatrix}(X_i - \\mu_i)(X_j - \\mu_j)\\end{bmatrix} \\\\ \n",
      "&= \\mathrm{E}\\begin{bmatrix} (X_j - \\mu_j)(X_i - \\mu_i)\\end{bmatrix} \\\\ \n",
      "&= \\sigma_{j,i}\n",
      "\\end{aligned}$$\n",
      "\n",
      "\n",
      "In general, we can state that $\\sigma_{i,j}=\\sigma_{j,i}$."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's get back to concrete terms. Let's start by revisiting plotting a track. I will hard code the data and noise to avoid being at the mercy of the random number generator, which might generate data that does not illustrate what I want to talk about. I will start with `P=500`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# guarantee the noise is the same each time so I can be sure of\n",
      "# what the graphs look like.\n",
      "zs = [-6.947, 12.467, 6.899, 2.643, 6.980, 5.820, 5.788, 10.614, 5.210, \n",
      "      14.338, 11.401, 19.138, 14.169, 19.572, 25.471, 13.099, 27.090,\n",
      "      12.209, 14.274, 21.302, 14.678, 28.655, 15.914, 28.506, 23.181, \n",
      "      18.981, 28.197, 39.412, 27.640, 31.465, 34.903, 28.420, 33.889, \n",
      "      46.123, 31.355, 30.473, 49.861, 41.310, 42.526, 38.183, 41.383, \n",
      "      41.919, 52.372, 42.048, 48.522, 44.681, 32.989, 37.288, 49.141, \n",
      "      54.235, 62.974, 61.742, 54.863, 52.831, 61.122, 61.187, 58.441, \n",
      "      47.769, 56.855, 53.693, 61.534, 70.665, 60.355, 65.095, 63.386]\n",
      "\n",
      "plot_track(data=zs, R_var=50., Q_var=.2, P=500., count=len(zs), \n",
      "           plot_P=False, title='P=500 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWTHpICIiIiIiWf0fg4aVDmo+WpUAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7bf60b8>"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Looking at the output we see a very large spike in the filter output at the beginning. If you look at the data (dotted red line) you will see a corresponding, smaller spike in the beginning of the data. We set `P=500 m`, which corresponds to $\\text{P}=[\\begin{smallmatrix}500&0\\\\0&500\\end{smallmatrix}]$. We now have enough information to understand what this means, and how the Kalman filter treats it. The 500 in the upper left hand corner corresponds to $\\sigma^2_x$; therefore we are saying the standard deviation of `x` is $\\sqrt{500}$, or roughly 22.36 m. If we recall how standard deviations work, roughly 99% of the samples occur withing $3\\sigma$, therefore `P=500` is telling the Kalman filter that the initial estimate could be up to 67 meters off. That is a pretty large error, so when the measurement spikes the Kalman filter distrusts its own estimate and jumps wildly to try to incorporate the measurement. Then, as the filter evolves $\\mathbf{P}$ quickly converges to a more realistic value.\n",
      "\n",
      "Now let us see the effect of a smaller initial value for `P`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_track(data=zs, R_var=50., Q_var=.2, P=1., count=len(zs), \n",
      "           y_lim=(-20,65), plot_P=False, title='P=1 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7745a90>"
       ]
      }
     ],
     "prompt_number": 53
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This *looks* fantastic at first blush. The plot does not have the spike that the former plot did; the filter starts tracking the measurements and doesn't take any time to settle to the signal. However, if we look at the plots for P you can see that there is an initial spike for the variance in position, and that it never really converges. Poor design leads to a long convergence time, and suboptimal results. \n",
      "\n",
      "So despite the filter tracking very close to the actual signal we cannot conclude that the 'magic' is to just use a small $\\text{P}$. Yes, this will avoid having the Kalman filter take time to accurately track the signal, but if we are truly uncertain about the initial measurements this can cause the filter to generate very bad results. If we are tracking a living object we are probably very uncertain about where it is before we start tracking it. On the other hand, if we are filtering the output of a thermometer, we are just as certain about the first measurement as the 1000th. For your Kalman filter to perform well you must set $\\text{P}$ to a value that truly reflects your knowledge about the data. \n",
      "\n",
      "Let's see the result of a bad initial estimate coupled with a very small $\\text{P}$ We will set our initial estimate at 100m (whereas the dog starts at 0m), but set `P=1 m`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = np.array([100., 0.]).T\n",
      "plot_track(data=zs, R_var=50., Q_var=.2, P=1., initial_x=x,\n",
      "           count=len(zs), plot_P=False, title='P=1 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e79c9eb8>"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can see that the initial estimates are terrible and that it takes the filter a long time to start converging onto the signal . This is because we told the Kalman filter that we strongly believe in our initial estimate of 100m and were incorrect in that belief.\n",
      "\n",
      "Now, let's provide a more reasonable value for P and see the difference."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = np.array([100, 0]).T\n",
      "plot_track(data=zs, R_var=50, Q_var=.02, P=500., initial_x=x,\n",
      "           count=len(zs), plot_P=False, title='P=500')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e79f1358>"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In this case the Kalman filter is very uncertain about the initial state, so it converges onto the signal much faster. It is producing good output after only 5 to 6 evolutions. With the theory we have developed so far this is about as good as we can do. However, this scenario is a bit artificial; if we do not know where the object is when we start tracking we do not initialize the filter to some arbitrary value, such as 0 m or 100 m. Instead, we would normally take the first measurement, use that to initialize the Kalman filter, and proceed from there. But this is an engineering decision. You really need to understand the domain in which you are working and initialize your filter on the best available information. For example, suppose we were trying to track horses in a horse race. The initial measurements might be very bad, and provide you with a position far from the starting gate. We know that the horse must start at the starting gate; initializing the filter to the initial measurement would lead to suboptimal results. In this scenario we would want to always initialize the Kalman filter with the starting gate position. \n",
      "\n",
      "If we have the luxury of not needing to perform the filtering in real time, as the data comes in, we can take advantage of other techniques. We can 'eyeball' the data and see that  the initial measurements are giving us reasonable values for the dog's position because we can see all of the data at once. A *fixed lag smoother* will look N steps ahead before computing the state, and other filters will do things like first run forwards, than backwards over the data. This will be the subject of the Smoothing chapter. It is worthwhile to keep in mind that whenever possible we should prefer this sort of batch processing because it takes advantage of all available information. It does incur cost of additional processing time and increased storage due to the requirement to store some or all of the measurements. And, of course, batch processing does not work if we need real time results, such as when using GPS in our car."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Lets do another Kalman filter for our dog, and this time plot the covariance ellipses on the same plot as the position."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def plot_track_ellipses(noise, count, R, Q=0, P=20., plot_P=True, \n",
      "                        title='Kalman Filter'):\n",
      "    dog = DogSensor(velocity=1, noise_var=noise)\n",
      "    f = dog_tracking_filter(R=R, Q=Q, cov=P)\n",
      "\n",
      "    ps = []\n",
      "    zs = []\n",
      "    cov = []\n",
      "    for t in range (count):\n",
      "        z = dog.sense()\n",
      "        f.update(z)\n",
      "        ps.append(f.x[0])\n",
      "        cov.append(f.P)\n",
      "        zs.append(z)\n",
      "        f.predict()\n",
      "\n",
      "    bp.plot_track([0, count], [0, count])\n",
      "    bp.plot_measurements(range(1,count+1), zs)\n",
      "    plt.plot(range(1,count+1), ps, c='b', label='filter')\n",
      "    plt.legend(loc='best')\n",
      "    plt.title(title)\n",
      "\n",
      "    for i,p in enumerate(cov):\n",
      "        stats.plot_covariance_ellipse(\n",
      "              (i+1, ps[i]), cov=p, axis_equal=False, \n",
      "               facecolor='g', edgecolor=None, alpha=0.6)\n",
      "\n",
      "        if i == len(cov)-1:\n",
      "            s = ('$\\sigma^2_{pos} = %.2f$' % p[0,0])\n",
      "            plt.text (20, 10, s, fontsize=18)\n",
      "            s = ('$\\sigma^2_{vel} = %.2f$' % p[1,1])\n",
      "            plt.text (20, 5, s, fontsize=18)\n",
      "    plt.axis('equal')\n",
      "    plt.show()\n",
      "\n",
      "plot_track_ellipses(noise=5, R=5, Q=.2, count=20, title='R = 5 m')\n",
      "plot_track_ellipses(noise=5, R=.5, Q=.2, count=20, title='R = 0.5 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7ab1da0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAx0AAAGaCAYAAABqsy7aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e78cf630>"
       ]
      }
     ],
     "prompt_number": 64
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If you are viewing this in IPython Notebook or on the web, here is an animation of the filter filtering the data. I've tuned the filter parameters such that it is easy to see a change in $\\mathbf{P}$ as the filter progresses.\n",
      "<img src='animations/multivariate_track1.gif'>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The output on these is a bit messy, but you should be able to see what is happening. In both plots we are drawing the covariance matrix for each point. We start with the covariance $\\mathbf{P}=(\\begin{smallmatrix}50&0\\\\0&50\\end{smallmatrix})$, which signifies a lot of uncertainty about our initial belief. After we receive the first measurement the Kalman filter updates this belief, and so the variance is no longer as large. In the top plot the first ellipse (the one on the far left) should be a slightly squashed ellipse. As the filter continues processing the measurements the covariance ellipse quickly shifts shape until it settles down to being a long, narrow ellipse tilted in the direction of movement.\n",
      "\n",
      "Think about what this means physically. The x-axis of the ellipse denotes our uncertainty in position, and the y-axis our uncertainty in velocity. So, an ellipse that is taller than it is wide signifies that we are more uncertain about the velocity than the position. Conversely, a wide, narrow ellipse shows high uncertainty in position and low uncertainty in velocity. Finally, the amount of tilt shows the amount of correlation between the two variables. \n",
      "\n",
      "The first plot, with `R=5 m`, finishes up with an ellipse that is wider than it is tall. If that is not clear I have printed out the variances for the last ellipse in the lower right hand corner. The variance for position is 3.85 m, and the variance for velocity is 3.0 m. \n",
      "\n",
      "In contrast, the second plot, with `R=0.5 m`, has a final ellipse that is taller than wide. The ellipses in the second plot are all much smaller than the ellipses in the first plot. This stands to reason because a small $\\small\\mathbf{R}$ implies a small amount of noise in our measurements. Small noise means accurate predictions, and thus a strong belief in our position. "
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Question: Explain Ellipse Differences"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Why are the ellipses for $\\mathbf{R}=5 m$ shorter, and more tilted than the ellipses for $\\mathbf{R}=0.5 m$. Hint: think about this in the context of what these ellipses mean physically, not in terms of the math. If you aren't sure about the answer,change $\\mathbf{R}$ to truly large and small numbers such as 100 m and 0.1 m, observe the changes, and think about what this means. "
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Solution"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The $x$ axis is for position, and $y$ is velocity. An ellipse that is vertical, or nearly so, says there is no correlation between position and velocity, and an ellipse that is diagonal says that there is a lot of correlation. Phrased that way, it sounds unlikely - either they are correlated or not. But this is a measure of the *output of the filter*, not a description of the actual, physical world. When $\\mathbf{R}$ is very large we are telling the filter that there is a lot of noise in the measurements. In that case the Kalman gain $\\mathbf{K}$ is set to favor the prediction over the measurement, and the prediction comes from the velocity state variable. So, there is a large correlation between $x$ and $\\dot{x}$. Conversely, if $\\mathbf{R}$ is small, we are telling the filter that the measurement is very trustworthy, and $\\mathbf{K}$ is set to favor the measurement over the prediction. Why would the filter want to use the prediction if the measurement is nearly perfect? If the filter is not using much from the prediction there will be very little correlation reported. \n",
      "\n",
      "**This is a critical point to understand!**. The Kalman filter is just a mathematical model for a real world system. A report of little correlation *does not mean* there is no correlation in the physical system, just that there was no *linear* correlation in the mathematical model. It's just a report of how much measurement vs prediction was incorporated into the model.  \n",
      "\n",
      "Let's bring that point home with a truly large measurement error. We will set $\\mathbf{R}=500 m$. Think about what the plot will look like before scrolling down. To emphasize the issue, I will set the amount of noise injected into the measurements to 0, so the measurement will exactly equal the actual position. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_track_ellipses(noise=0., R=500., Q=.2, count=7, title='R = 500 m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxYAAAGaCAYAAACSU9UtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nk8RCCCGEEEII0W2SWAghhBBCCCG67f8DGlNuLVCcxh0AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7cb3470>"
       ]
      }
     ],
     "prompt_number": 57
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I hope the result was what you were expecting. The ellipse quickly became very wide and not very tall. It did this because the Kalman filter mostly used the prediction vs the measurement to produce the filtered result. We can also see how the filter output is slow to acquire the track. The Kalman filter assumes that the measurements are extremely noisy, and so it is very slow to update its estimate for $\\dot{x}$. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Keep looking at these plots until you grasp how to interpret the covariance matrix $\\mathbf{P}$. When you start dealing with a, say, $9{\\times}9$ matrix it may seem overwhelming - there are 81 numbers to interpret. Just break it down - the diagonal contains the variance for each state variable, and all off diagonal elements are the product of two variances and a scaling factor $p$. You will not be able to plot a $9{\\times}9$ matrix on the screen because it would require living in 10-D space, so you have to develop your intution and understanding in this simple, 2-D case. \n",
      "\n",
      "> **sidebar**: when plotting covariance ellipses, make sure to always use *plt.axis('equal')* in your code. If the axis use different scales the ellipses will be drawn distorted. For example, the ellipse may be drawn as being taller than it is wide, but it may actually be wider than tall."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Batch Processing"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The Kalman filter is designed as a recursive algorithm - as new measurements come in we immediately create a new estimate. But it is very common to have a set of data that have been already collected which we want to filter. Kalman filters can always be run in a *batch* mode, where all of the measurements are filtered at once. We have implemented this in `KalmanFilter.batch_filter()`. Internally, all the function does is loop over the measurements and collect the resulting state and covariance estimates in arrays. It may seem a bit trivial, but you will almost always want to do this if you can for several reasons. First, it will execute a bit quicker than if you implement the loop yourself. Second, the logic in your code will be a bit cleaner, and you will have a reduced chance of bugs. Third, and most importantly, it you batch process your data you can then use an extremely powerful techique to generate far smoother results than you have seen so far. We will present that technique in the next section; here I will show you how to use `KalmanFilter.batch_filter()`.\n",
      "\n",
      "All you have to do is collect your measurements into an array or list. Maybe it is in a CSV file, for example.\n",
      "\n",
      "    zs = read_altitude_from_csv()\n",
      "\n",
      "Or maybe you will generate it using a generator:\n",
      "\n",
      "    zs = [some_func(i) for i in range(1000)]\n",
      "    \n",
      "Just do whatever it takes to get your measurements in an array.\n",
      "\n",
      "Now we will just call the `batch_filter()` method.\n",
      "\n",
      "    Xs, Ps, Xs_pred, Ps_pred = kfilter.batch_filter(zs)\n",
      "    \n",
      "The funtion takes the list/array of measurements, filters it, and returns a list of state estimates (Xs), covariance matrices (Ps), and the predictions for the same (Xs_pred, Ps_pred).\n",
      "\n",
      "Here is a complete example drawing from the code above"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dog = DogSensor(velocity=1, noise_var=10.)\n",
      "f = dog_tracking_filter(R=3., Q=.02, cov=P)\n",
      "count = 50\n",
      "zs = [dog.sense() for t in range(count)]\n",
      "Xs, _, _, _ = f.batch_filter(zs)\n",
      "\n",
      "bp.plot_track([0, count], [0, count])\n",
      "bp.plot_measurements(range(1,count+1), zs)\n",
      "bp.plot_filter(range(1,count+1), Xs[:,0])\n",
      "plt.legend(loc='best')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxoAAAGNCAYAAACWvAeAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nFDRERERERMTh/g/XKR8NXmq8WgAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e794bd68>"
       ]
      }
     ],
     "prompt_number": 58
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Smoothing the Results"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I have an entire chapter on using the Kalman filter to smooth data; I will not repeat the chapter's information here. However, it is so easy to use, and offers such a profoundly improved output that I will tease you will a few examples. The smoothing chapter is not especially difficult; you are sufficiently prepared to read it now.\n",
      "\n",
      "Briefly, the recursive form of Kalman filtering that we have been using up to now use information from the past to generate the current estimate. Recall the last section, where we used batch processing to filter a collection of measurements. This implies that we know now only the past, but the future! This is a key insight.\n",
      "\n",
      "Let's assume that  we are tracking a car. Suppose we get a noisy measurement that implies that the car is starting to turn to the left, but the state function has predicted that the car is moving straight. The Kalman filter has no choice but to move the state estimate somewhat towards the noisy measurement, as it cannot judge whether this is just a particularly noisy measurement or the true start of a turn. \n",
      "\n",
      "However, if we have measurements from the future we can often figure out if a turn was made or not. Suppose the subsequent measurements all continue turning left. We can then be sure that the measurement was not very noisy, but instead a true indication that a turn was initiated. On the other hand, if the subsequent measurements continued on in a straight line we would know that the measurement was noisy and should be mostly ignored.\n",
      "\n",
      "We will not develop the math or algorithm here, I will just show you how to call the algorithm in `filterpy`. The algorithm that we have implemented is called an *RTS smoother*, after the three inventors of the algorithm: Rauch, Tung, and Striebel. The routine is `KalmanFilter.rts_smoother()`. Using it is trivial; we pass in the means and covariances computed from the `batch_filter` step, and receive back the smoothed means, covariances, and Kalman gain."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from numpy.random import seed\n",
      "dog = DogSensor(velocity=1, noise_var=40.)\n",
      "f = dog_tracking_filter(R=3., Q=.2, cov=P)\n",
      "count = 50\n",
      "seed(8923)\n",
      "zs = [dog.sense() for t in range(count)]\n",
      "Xs, Covs, _, _ = f.batch_filter(zs)\n",
      "Ms, Ps, _ = f.rts_smoother(Xs, Covs)\n",
      "\n",
      "bp.plot_measurements(range(1,count+1), zs)\n",
      "bp.plot_filter(range(1,count+1), Xs[:,0])\n",
      "plt.plot(range(1,count+1), Ms[:,0], label='RTS')\n",
      "plt.legend(loc='best')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxoAAAGKCAYAAACLuTc4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd8TecfwPHPvdlLECJGSCSIPWPvPYsatWdoVdHWKDqs\nlqrWT6tFUbvSUq1Nbar2qFkjEptIQkjIvuf3x2nClXszb3Ijvu/X675unPOc53xvnOr53vM8z1ej\nKIqCEEIIIYQQQpiQ1twBCCGEEEIIIXIfSTSEEEIIIYQQJieJhhBCCCGEEMLkJNEQQgghhBBCmJwk\nGkIIIYQQQgiTk0RDCCGEEEIIYXKSaAghhBBCCCFMLtVEY/LkyWi1Wr1XkSJFkrUpWrQo9vb2NGnS\nhIsXL2ZZwEIIIYQQQoiczzItjXx8fNi3b1/Sny0sLJJ+njlzJrNnz2b58uWULl2aqVOn0qJFCy5f\nvoyjo2NSu8ePH5suaiGEEEIIIUS2cXZ2TvcxaRo6ZWFhgaura9LLxcUFAEVRmDNnDhMmTKBz586U\nL1+e5cuXExERwerVq9MdjBBCCCGEECJ3SFOiERgYSNGiRSlZsiQ9e/YkKCgIgKCgIIKDg2nZsmVS\nW1tbWxo2bMihQ4eyJmIhhBBCCCFEjpfq0KnatWuzfPlyfHx8CA4O5vPPP6du3bpcuHCB+/fvA1Co\nUCG9Y1xdXbl7967RPjPy6EW8Hk6cOAFAjRo1zByJyM3kOhNZTa4xkR3kOssmOh14e8Pt23DsGFSp\nYu6I9ETFPOXq7XNcunmGyzf+IeTxvRTbK4pC6K1Irp0MIeRGhNF2Wq2WU6dOZSq2VBON1q1bJ/1c\noUIF6tSpg6enJ8uXL6dWrVpGj9NoNEb3Jf6HIYQxco2I7CDXmchqco2J7CDXWdZyOnmSMkFBxBQq\nxLmYGDDz71un6AiNuMPd8EDuhQcRGnEHBSXV4xLiddy9HM610yFEhEYbbWdnZ0fz5s1p06ZNpmNN\n02TwF9nb21O+fHkCAgLo1KkTAMHBwRQrViypTXBwMG5ubpkOTgghhBBCCHNy2bQJgLB27eCFBZGy\ni6IoREQ/Skos7j++TlxCTNqPj7Ug+FI0F48F8TQyymi7ggUL0q5dO5o0aYK9vb0pQk9/ohEdHc2/\n//5L06ZN8fT0xM3NjR07dlC9evWk/QcPHuTrr7822oc84hPGyGNgkR3kOhNZTa4xkR3kOssGT57A\n3r0AFJk4kSJeXtl26gRdAqeu/MWuE79zL+xmmo+z0FriWbgMeS2LcvLAv+zctovoaONPMKpUqYKf\nnx+tWrXC0lI/NcjsqrGpJhpjxozhjTfewN3dnQcPHjBt2jSioqLo378/AO+//z7Tp0/Hx8eHUqVK\n8fnnn+Pk5ESvXr0yFZgQQgghhBBmtWYNPHsGDRuClxf88Qfs3AmzZoGDQ5acMiEhnmOX9rHr+LpU\n51skKpS/GD7Fq1DGvTIP7zxjxfKV7N5tfAVYrVZLq1at8PPzo1q1aqYKPZlUE407d+7Qs2dPQkND\nKViwIHXq1OHIkSO4u7sDMG7cOKKiohg+fDiPHj2idu3a7NixA4cs+uULIYQQQohX1JMn0K8fjB0L\n9eqZO5rU+frCkCHQrJn65+nT1TkaHTtCq1YmPVVcfBxHL+5m14l1PIwISbGtg10efNwrU6Z4FcoU\nr4yjrTNbtmxhwtdTOX/+vPHjHBzo3r07AwcOTLqXz0qpJhr+/v6pdjJp0iQmTZpkkoCEEEIIIcQr\nQqeDVavg1i3914MHcPcuaF+qpBAfDxs2wL17cPSoeWJOj8qVYeHC539u1kxNNPbsMVmiERsfw+Hz\nO9l18g8eR4YZbKNN0OEd+JAy+b3x6TuSot5V0Gq0PHnyhNU/r2b58uVJq8EaUrhwYQYMGECPHj3I\nkyePSeJOi3TP0cgOOp2O2NhYc4chzKBEiRIAKY4lfJVYW1ujffkfWSGEECK30Gjg3Xfh6dPk+0JC\n4KUSCNjaqu/HjsG5c1CxYtbHaCKxcTFYNmmMduZM2L070/3FxEZx8Nyf7Dm1nohn4QbbaDUW1DwS\nRItdVykY9gx0f8P3G7n1228s+esv1qxZw7Nnz4yeo2LFivj5+dGmTRusrKwyHXN65bhEQ6fTERMT\ng62tbYpL5IrcyTbxH6BcQFEUoqOjsbGxkWRDCCFE7qTRwNtvq6sxFS8O7u7PXwUKJG9vbw/DhsH8\n+fDTTzBnTvbHnE4Rz8L5Zfc8zgUew8rCikJjGuN2PwK3AyspXKwMbvndccnjilabthWpomKe8deZ\nLew9vZGn0YbrWFhYWFKnXHOa13iT/G8pcPo0FC3KqWHDWPTgATuGDEGn0xk8VqPR0Lx5c/z8/PD1\n9TXr/XSOSzRiY2MlyRC5gkajwdbWNilxFkIIIXKlb75JX3s/PzXRWLkSZs4EG5usicsEAu5cYPm2\nb3j89CEAcQlx3C7mzO1iznB6HZxW21lZWFMofzHc8rvj5uJOYZfiyRKQZ9GR7PtnE/v/2UxUjIEn\nQP/1U7diS5pV70xeRxcA4u3j2aHTsXjSJE7fuWM0VltbW7p27cqgQYPw9PQ04W8h43JcogEpF/sT\n4lUi17IQQgjxkmrVoGpV9Vv6TZuga1dzR5SMLjSEXUH72Xp4NTrF8JODF8UlxHI7JJDbIYF62xMT\nEBfnQly6+Q8xsYbrWFhb2dKgUmuaVO1EHoe8AERGRrJ27VqWLFnC7du3jZ67YMGC9O/fn14lSpCv\nVi0oWDAdnzRr5chEQwghhBBC5EA7d8LgwdC9O6RQMy1VX3yhTiQ38cpNphB55zqrPu/NRZ/M37Ab\nS0AS2Vrb07ByOxpX7YCjnTpJ+969eyxbtgx/f38iIgwPrQLw8fHBz8+P9u3bY/PsGXh7Q0ICfPop\njBgB1taZjj+zJNEQQgghhBBpc+mSuqpUCjfAadKmjWniMbHAu/+y7LfJhBtIMlrU6ELDKu148OgO\n98JucT/sJvcf3uLew1s8jXqSrvPY2zjSqGoHGlVph72NIwAXLlxg0aJFbNmyhfj4eKPHNm7cGD8/\nP+rWrft85MSDB+pSvH/+CWPGwIIFaq2Pjh3VeTRmIomGEEIIIYRIm0uX1PcyZcwbh4npFB17T21g\n098r0aE/VMrB1om+rd6nnEd1AJwd8lOqmP5qWRHPwtWkI5UExMEuD02rdqR+pTbY2dij0+nYs2cP\nixcv5vDhw0bjs7a2pnPnzgwePJhSpUolb+DuDtu3w7Zt8OGH6t9T587wwQcwe3YGfyuZJ4mGEEII\nIYRIm8uX1XcfH/PGYUJPoyNYteNbLgSdSLbPs7APA9qMJp9TysOonOzz4mSf12ACci/sFiHhd3G0\ny4NPiarYWKkLxfj7+7NkyRICAgKM9ptfUeg7ahR9+valgKFVvF7Wpg00bw4//giTJ8Nbbxlud+AA\n5M0Lnp7g5JR6vxkka25mg2XLlqHVatFqtRw8eNBgG29vb7RaLU2aNMnm6MSLDh06xJQpU3j8+LG5\nQxFCCCFynlz2RCPo3mW+Wv2hwSSjWfVOjOzyecpJRlwcKIrR3U72eSntXpF6FVtR2bsOkU+e8u23\n31KvXj0mTpxoNMkomT8/X4SG8nf16rz/wQdpSzISWVnBe+/BzZtQq5bhNt27q8UI8+RRJ4/XrKkm\nJWGGCwZmlCQa2cjOzo7Vq1cn237kyBECAwNlWd8cQBINIYQQwoinT9Vq39bW4OFhun5DQ9XVp7KR\noijsPbWRb3+byKOIEL199lHxDCn7Fh3rD8DCIoXBP337Qr58EBSU6vmuXbvGxIkTqVevHnPmzCHM\nyA197dq1Wbx4MTsLFqRXZCS2HTqk63Ppsbc3vD0hAWrUgLJl1QKKoaFw/DisXQuOjhk/nwEydCob\ntWnThrVr1/Ldd99hafn8V7969Wp8fHywsEhboZec6unTpzg4OJg7DJNQUvh2QgghhHgtOTiok8Bv\n3lQL9JnCkydQogTExsKdO+Dqapp+U/AsOpKfd37HucBjyfaVcCvNwBYfkD+fW+odRUWpydfu3VCy\nZLLdiqJw9OhRFi9ezO4UKolbWFjQvn17Bg8eTMWKFdU+9+1TJ3FnxaR5CwvYvFn9WaeD4GA1Wbp7\n1+Q1TeSJRjbq2bMnDx8+5M8//0zalpCQwJo1a+jdu3ey9oqiMHfuXCpWrIidnR2FChXCz88vWRa8\nceNGOnTogLu7O7a2tnh4eDBu3DhiYmL02gUHB+Pn55fUzs3NjbZt23Lx4sWkNlqtlilTpiSLxcPD\ng4EDByb9OXE42N69exk5ciSFChXC6YUxfsePH6dt27bkzZsXe3t7GjRowL59+/T6nDx5MlqtlkuX\nLtGnTx/y5s1LwYIF+fjjjwG4desWHTt2xNnZGTc3N742sIxeTEwMU6ZMoVSpUtja2lKsWDE+/PBD\noqL016nWarUMGzaM9evXU6FCBWxtbalQoYLe38XkyZMZN24cAJ6enknD3Q4cOADAqVOnaNu2La6u\nrtjZ2eHh4UG/fv2Ijo5OFpcQQgiRKzk4qN+Em0qePNCsGcTHw4oVpuvXiBv3r/KV/4cGk4zGVd9g\nVNcvyJ+/cNpWamraVH3fs0dvc3x8PJs3b6ZTp0707NnTaJLh5OTEkCFDOHDgAHPmzFGTjMT+YmLU\nVaQKFUrX50s3rRYKF4a6dbOknok80chGxYoVo0GDBqxevZp27doBsGvXLh48eEDPnj3x9/fXaz9s\n2DCWLFnCgAEDGDlyJDdv3mTu3LkcO3aM48ePY/Nf1rls2TLs7OwYNWoUzs7OHD58mP/973/cunVL\nr8+uXbty/vx5RowYgaenJw8ePODAgQNcvXqVcuXKJbUzNHxLo9EY3D5ixAjy58/Pp59+mjTcaP/+\n/bRq1Ypq1aoxadIkLC0tWblyJS1btmTnzp00atRIr4+ePXtStmxZZs6cyZYtW5gxYwbOzs4sXryY\n5s2b89VXX7Fq1SrGjRtH9erVk+axKIpC586dOXDgAEOHDqVcuXJcvHiRefPmceHCBb0kAuDw4cNs\n2rSJd999F0dHR7777ju6dOnCzZs3yZ8/P126dOHq1av4+/szZ86cpPGQZcuWJSQkhBYtWuDq6spH\nH31Evnz5uHnzJps2beLZs2dS+VsIIYTIKD8/dejU4sUwenSWLMcaGfWEIxd2seXwahJ0+kvH2lnb\n07vlSCp51U5fp82aqe979oCiEPn0KWvWrGHJkiXcSaGCd9GiRRk4cCDdu3fX+5I2SZ480LYtNG6c\nvnhyIiWbhIeHJ71SEhUVlfZO1ek3yV+mam8iS5cuVTQajXL06FHlxx9/VBwcHJRnz54piqIoffv2\nVerUqaMoiqKUL19eadKkiaIoivL3338rGo1GWbVqlV5fBw8eVDQajbJw4cKkbYl9vWj69OmKVqtV\nbt26pSiKojx69EjRaDTKN998k2KsGo1GmTJlSrLtHh4eysCBA5N9ptq1aysJCQlJ23U6nVKmTBml\nRYsWesfHxsYq5cuXV+rWrZu0bdKkSYpGo1H8/PyStiUkJCju7u6KRqNRpk+fnrQ9PDxcsbe3V/r0\n6ZO07eeff1a0Wq1y4MABvXP9/PPPikajUXbs2KH3uWxsbJRr164lbTt79qyi0WiU77//PmnbrFmz\nFI1Go9y4cUOvz/Xr1ysajUY5efKkgd9aytJ1TYtscfz4ceX48ePmDkPkYnKNieyQa66zuDhFKVxY\nvSc7eNBk3T54dFfZffIPZc6aCcrIbzsrI+Z0TPaatXq0Ehp+P2Mn0OkUpUgR5Z6FhfLl6NFKxYoV\nFQ8PD6OvN954Q9m0aZMSFxdnss+Y1dJ6/26MDJ3KZt26dSMuLo7169cTFRXF+vXrDQ6bWrNmDY6O\njrRs2ZLQ0NCkV5kyZXB1dWXv3r1Jbe3s7ADQ6XQ8fvyY0NBQ6tWrh6IonD59OqmNtbU1e/fu5dGj\nRyb7PEOGDEGrfX4ZnTlzhitXrtCzZ0+9uB8/fkzz5s05evRosqFGfn5+ST9rtVqqV6+ORqNh8ODB\nSdudnZ0pU6YMQS9MuFqzZg2lS5emXLlyeudq2LAhGo1G73cE0KRJE0q+MIayYsWK5MmTR69PY/Lm\nzQvApk2bUiyiI4QQQoh0srSE/v3VnxcvznA3OkVH0L3LbPx7JdNXjmDa8mGs/2sZ1+5eRFF0ydo3\nrNyOUd1m4OKcseFJ/166xOhixWhYrBgL1q0zWsW7efPm/PLLL6xfv5727dvrzdPN7V7tT5reCbs5\nYIJvvnz5aNWqFatWrUKr1RIVFcVbBtY4vnLlCpGRkRQyMjYvJOT5Cgnnz59n3Lhx7N+/P9nchMTh\nTDY2NsycOZMxY8ZQqFAhatWqRdu2benbty/FihXL8Ofx8vJKFjeglyS8SKPREBYWRtGiRZO2FS9e\nXK+Ns7MzVlZWuL40ISxPnjx6n/vKlStcvnyZggWTLzun0Wj02ho6D6h/H2lJvBo1akTXrl2ZMmUK\ns2fPplGjRrzxxhv06tULe2OrOgghhBC5hU4HkZHqsJ6sMHiwOil56NB0HRYbH8PVW+c4F3iU84En\nePIs9f+n21rb07P5e1QtVVfdcPQoDBsG778P/fqleKyiKBw8eJBFixbx119/qRsNDPWytramS5cu\nDB48ONm90uvk1U40XlG9evWiX79+PHnyhBYtWhhcG1mn0+Hi4sKvv/5qsI98+fIBaiLRpEkTnJyc\nmD59Ot7e3tjZ2XH79m0GDBiATvc8gx81ahQdO3Zkw4YN7Ny5k2nTpjF9+nQ2b96cbN7Ey4x9i5/4\nNOXFuAFmzpxJ9erVDR7z8uc1tNqWsWV+lReSRZ1OR/ny5fn2228Nti1SpEiq53m5z5SsWbOG48eP\ns3nzZnbu3MnQoUOZMWMGR44cMZjsCCGEELnGzZtqcbeqVeHUKdP37+0NS5akqWlk1BMuBJ3gXOAx\nLt04TWx8TOoHAUUKeFCxpC91K7Qin9ML9yJLlsDp03DunNFjY2Nj2bRpE4sXL+ZSYi0RA/Lnz0/f\nvn3p06dP+mpf5FKSaJhBx44dsbGx4dChQyxfvtxgGy8vL3bt2kWtWrVSXDJ27969hIWF8fvvv9Og\nQYOk7Tt37jTY3sPDg1GjRjFq1Cju3LlDlSpV+OKLL5ISjXz58hEeHq53TGxsLPfu3UvTZ0vM2h0d\nHWmauBpDFvH29ubkyZMmPU9qdUx8fX3x9fVlypQpbN++nbZt27Jo0SImTpxoshiEEEKIHCexIriz\ns1lO/ygihDMBRzhz7QiBd/81OBTqZVqNFu+i5alQsiYVS9Y0PETq2TP45Rf15xdW10z05MkT/P39\nWbZsGffv3zd6Lg8PD/z8/HjzzTeTfQn7OpNEwwzs7OyYP38+gYGBdOrUyWCbHj16MH/+fKZOncrM\nmTP19iUkJBAREUHevHmTvqV/8cmFTqdj9uzZesckDql68eIvWrQoBQsW1CtO5+Xlxf79+/WOXbhw\noV7/KalRowbe3t7Mnj2bvn374vhS4ZeQkJA0ffuflsKFb731Flu3bmX+/PkMGzZMb19MTAxxcXHJ\nzp+axKTu4cOHekOtwsPDcXZ21ouratWqAFLcTwghRO5nhorgIeH3OBNwmDMBh7kRfDVNx9hY2VLW\noxoVS9aivEd17G1TuQ/44w+1lkfNmvDCCpz3799n6dKl+Pv7G517Aep9z5AhQ2jevLnenNUMWbcO\nNm5Uh5E1bJi5vnIISTTMpE+fPga3Jw7jadCgAcOHD2fWrFmcPXuWli1bYmNjQ0BAAOvWrWPatGn0\n69eP+vXr4+LiQv/+/RkxYgSWlpb89ttvPH36VK/fy5cv07RpU7p37065cuWwsbFh69atXLp0iW++\n+SapnZ+fH++88w5du3alefPmnDlzhh07dlCgQIE0DTHSaDT89NNPtG7dmnLlyjFo0CCKFi3K3bt3\nkxKYPS+tN53S7yGl7X369OG3335j+PDh7N+/P2kC/OXLl1m7di2//fYbDVP5D/Xl8/j6+gIwYcIE\nevbsibW1Nc2aNePnn3/mhx9+4M0336RkyZJERUWxdOlSLC0t6ZoF604LIYQQOUpiouHjk6WnuRd2\nizMBhzgTcJg7odfTdIyzowsVPX2p6FUL76IVsLK0SvsJly5V3/97mnH58mUWLVrExo0biYuLM3iI\nVqulVatWDBkyJOlLR5P49Ve1OneNGpJoiPRJyzf0L9eqmDt3LtWqVWPBggV88sknWFpaUqJECd56\n662k4UL58uVjy5YtjB49mkmTJuHk5ESXLl145513qFSpUlJfxYsXp0+fPuzevZvVq1ej0WgoU6ZM\nUp2OREOGDCEoKIiffvqJ7du307BhQ3bu3EmzZs2SfQZjn6lBgwYcOXKEadOmMW/ePJ48eULhwoXx\n9fXVW2HKWG2OtG7XaDT8/vvvzJkzh+XLl7Nhwwbs7Ozw8vJi+PDhzwvfpODl81SvXp0ZM2Ywb948\nBg0ahKIo7N27l8aNG3PixAnWrFnD/fv3yZMnD9WqVeOHH35ISk6EEEKIXCtx6JSJEw1FUbgTGsSZ\ngMP8E3CY4Ie303ScOt9CHRLl7uqVpvusZKKi4NYtFFtbjnp7s3DQoGQrVr7Izs6Obt26MXjw4OQL\nzNy7B3v3QpcuGauuHRcHifW//qu1lhtolLTOhM2kF4eXOKcwvi86OlqKn4lcRa7pnOfEiROA+shb\niKwg15jIDtl6ndWtC0eOwLVr6qTwTNApOm4GB3Am4BD/BBwm7HFwmo7zKFyGKt51qOxVJ8NL0r4o\nPj6e7du3s+i77zh71fjQLBcXF/r160ffvn2TFuNJpnJlOHtWTTYyUmhv71610njZsnDxYvqPzyJp\nvX83Rp5oCCGEEEKIlB06pD4ByMi39f9RFIWD57az8/hvhEeGpdpeoyh4uVekincdKnnVJq+jS4bP\n/aKoqCjWrl3LTz/9xM2bN4228/DwYMiQIbz55pupf2HYtKmaaOzenbFEY8sW9b19+/Qfm4NJoiGE\nEEIIIVKXidWUFEVh86FV7DyxLsV2Wq0Fpd3KUvn7X6l06iZOZ+dk+glKorCwMFauXMmKFStSrKFV\npUoV3n77bVq0aGF0afxkmjWDOXNgzx6YNi39weXCYVMgiYYQQgghhMhi2478YjTJsLSwwqd4FSp7\n16FiyZrqSlEbb8CBALXGRUZu3F9w69YtFi1axNq1a4mOjjbarlmzZgwdOhRfX9/0z/lo2BAsLODY\nMYiIACen9B1/8CDs2KEOUctFJNEQQgghhBBZZtvRX9l+TL8AsZWlNeU9alDZuw7lPWtga/3S0xI/\nP1i1Sl0VavJk9SY+nS5evMiPP/7Ili1bSEhIMNjG2tqaTp06MWTIELy9vdN9jiR58oCvrzqP5cCB\n9D+ZcHaGbt0yfv4cShINIYQQQgiRJXYcW8u2I/562+ys7Rn+5lSKF0rhxr5hQ/Xb/Tp11KJ6aXxC\noCgKR44cYcGCBRw4cMBoOydra/p068aAkSNxdXVNU9+p6tULqlSBokVN018uIImGEEIIIYQw7swZ\nKF4cjK24ZMTuk3+w+fDPettsre15t/PklJMMAI0G/v47zedKSEhg586dzJ8/n7NnzxptV7hwYQY9\nfUqPc+dwLFUKTJVkAIwYYbq+cglJNIQQQgghhGEJCVCrFsTEqBW00/hkYe+pjWw4uFxvm42VLcM6\nfUYJt9ImCy8mJoY//viDhQsXEhQUZLRdqVKlePvtt+lQujTWlSqBoyNIwd0sJ4mGEEIIIYQw7MYN\nNckoUiTNScb+fzbzx19L9LZZW9nyTsfP8CxsmoJ/ERER/PzzzyxdupQHDx4YbVejRg3efvttmjZt\nilarhfHj1R3du4ODg0liyZSzZ8HbG+ztzR1JlpBEQwghhBBCGJbOiuB/ndnKuv2L9bZZWVrz9huf\n4FW0XKbDCQkJYenSpaxatYqIiAij7Zo2bco777yDr6/v843x8bBihfrzwIGZjiXTdDpo3RoePVKL\n9JloGd+cRBINIYQQQghh2KVL6nsaEo2/z/3J2n0L9bZZWahJRqliFTIVxs2bN1k4fz5rf/+d2NhY\ng20sLS154403GDp0KGXKlDEQ4N9w7x6UKgX16mUqHpM4fVqNp1gx8PAwdzRZQhINIYQQQghhWGKi\nYejG/QWHL+zi1z3z9bZZWlgxpMNESrtXyvDpL1++zPzPP2fzwYMYXqAW7O3t6dGjB4MGDaJoSis+\nNWqkDlUKDlYnm2eV776DTZvUGiDu7sbbJVYDb9cua+MxI625A3jdXb9+Ha1Wy/LlzydMLVu2DK1W\ny82bN80YmRBCCCFeey4u6hyCcsaHPR37dy+/7PpBb5uFhSV+7cfjU6JKhk57+vRphgwZQuvWrdlg\nJMnInz8/H3zwAQcPHuTTTz/VTzJCQkBRkh9UsSI0b56hmNJsxw7YtQv27k253YuJRi4liUY2SEwc\nDL1GjBiBRqNJtQLl6tWr+fbbb7MpYiGEEJlhf/EiBX7/3fCNjhCvkunT4epVozfnxy/t5+cd36Hw\n/Fq30FoyuO1HlPOonq5TKYrCX3/9Ra9evXjzzTfZtWuXwXZFixZl8uTJHDx4kJEjR5Ivcdnd+HjY\nvBk6d1Ynr584ka7zm0yzZur77t3G2wQHq1XEbW2ft8+FZOhUNpoyZQpeXl5628qUKcO6deuwtEz5\nr2L16tVcuHCBUaNGZWWIQgghTKBc//7qDy1aQJMm5g1GiCxy6spBVu34Vi/J0GotGNh2LBVK+qZw\npD6dTseOHTtSrYFRKjaWd/Lnp8PevVhZWT3fce0aLF4My5ercx5ArSR+7JharTu7NW2qvu/Zo37Z\nYOjL5MhItRK4hUWuXXEKJNHIVq1ataJmzZoZPj61px4ZERUVhZ2dncn7FUKI19aLTzGuXJFEQ+RK\np68eYsX22SiKLmmbVqNlQOvRVPKqlaY+4uLi2LhxIwsWLCAgIMBou0qVKjHcz4/m/fqhvXtXXaGp\ncuXnDf74A778Uv25dGkYNAj69YPChTP02TKtYkUoUABu31afBpU2UDfEywvWrMn+2LKZDJ0yM0Nz\nNF7WuHHFoOmSAAAgAElEQVRjtm7dmtQ28ZVIURTmzp1LxYoVsbOzo1ChQvj5+REWFqbXj4eHB23a\ntGH37t3UqlULOzs7vvrqqyz7bEII8Vq6f//5z2XLmi8OIbLI2WtHWL79G3QvJBkajZZ+rT+kSqm6\nqR4fHR3N8uXLady4MWPGjDGaZNStW5dVq1axfv16WnbogLZ3byhZUh129KJ+/WDAADhwQJ28/tFH\n5ksyALTa518wpDZPI5eTJxrZKDw8nNDQUIP7Unpa8cknnzBu3Dhu377NnDlzku0fNmwYS5YsYcCA\nAYwcOZKbN28yd+5cjh07xvHjx7GxsUk6R0BAAN26dWPo0KEMGTKE4sWLm+bDCSGEUF27BsDTcuVw\naNjQzMEIYVr/3jjN0q1fo9M9n56t0Wjp23IU1UrXT/HYiIgIVq1axU8//ZTsy9AXtWzZkmHDhlGl\nyksTyb/8Ul3RSfvS9+SurrB0abo/S5aaMAHGjoWqVc0diVm90onGyG87ZWn/341ab9L+Wrdurfdn\njUaT4ljERM2bN6dIkSKEh4fTq1cvvX2HDh1i4cKFrFy5kt69e+udq0GDBqxYsYIhQ4YA6pOPa9eu\nsXHjRtq3b2+CTySEECKZGjW4sGoV2vh45HmGyEqamBgUa+usO8Hu3epk5apVwd6eu6E3WLL1KxJ0\n8c9jQEPvFiOo4dPIaDePHz9m2bJlLF26lMePHxtsY2FhQYcOHRg2bBilDQ01AnB0zNTHyVaveYKR\n6JVONF41c+fOpexLj9FtbW0z1eeaNWtwdHSkZcuWek9LypQpg6urK3v37k1KNADc3d0lyRBCiKxk\na0tUKjUHhMi0P/+kWrt23Bo1KusmPI8cqc6HOHmSJ2U8+XHj58TERuk16dn8PWqWNTwPKSwsjCVL\nlrBixQoiIyMNtrG2tqZ79+4MHToU95RqTohXkiQa2cjX1zfZZPDr169nqs8rV64QGRlJoUKFDO4P\nCQnR+3PJkiUzdT4hhBBC/Cc8HJYtUytNZ2ctBEWB1q3RAMVnz4ZvvjH9OeLj4b+5E7ElPVi0aTqP\nIvTvKTo3GETt8smXZn3w4AELFy5k9erVREVFJdsP4OjoSJ8+fRg0aBAFCxY0ffw51dWr6rCq7t3V\nVy4nicYrTqfT4eLiwq+//mpwf9La0v+RFaaEEEKITIqIUOcKfP21mmxYW0NgIKRUldqUXp5g/OgR\nvPT/+0y7fh1iY9EVK8aqQ4u5EXxVb3f9iq1pXLWD3rY7d+6wYMEC1qxZQ2xsrMFunZ2dGTRoEP37\n98fZ2dm0Mb8KNm+GdevAxkYSjZzO1HMocjJjk8W9vLzYtWsXtWrVwsHBIZujEkIIYYzjP/+oq+C0\nbQs+PuYOR5jS22+Dv7/6c968arIxaxYYWLAlS4SEQMGCEBLCnaFDKZpgqG52Jl2+DMDWjhX55+oh\nvV0+xavQpfGQpHuT69evM3/+fH7//Xfi4+OTdQXg4uKCn58fvXv3xsnJyfTx5mS3bqmrYFlaqokG\n5Opq4C+S5W1fEQ4ODjx69CjZ9h49eqDT6Zg6dWqyfQkJCYSHh2dHeEIIIV5SYMMGGD1aTTZE7jJ6\nNNSrp06W3rdPLbw2cGD2nf+tt+DGDU7t38+9IUPUmg2mdukSR2u6s6OU/mTzwi7FGdh2LBZaCwIC\nAvjggw9o1qwZa9asMZhkuLq68umnn3LgwAHeeeed1y/JaNsWihdXiwc+eaL+e6DVwksLBOVWr/QT\njdeJr68va9as4f3336dmzZpotVp69OhBgwYNGD58OLNmzeLs2bO0bNkSGxsbAgICWLduHdOmTaNf\nv37mDl8IIV4Pp05B+/Z4VK9OTOIwmqAg88YkMk6nS76UKkD16nDw4PM/m6Pwmp0duiysKH21sB2/\n9Kimt83Jzpmhb3xM0LUbfP/992zfvh3lxQKVLyhSpAjDhg2jW7duScvsv5Y8PdX3PXvUquXx8VC/\nPuTPb964sokkGtkkvVW9X27/7rvvcu7cOVatWsXcuXMB9WkGqKtZVatWjQULFvDJJ59gaWlJiRIl\neOutt2jatGmGYxBCCJFOAQFw7x4WkZHEFCmibgsMNG9MIv1iY9VJ3l99pT61KFHC3BFlqweP7vDT\nk0MkvJBjWVlY06h0dyaM+ZSdO3caPdbDw4N3332XTp06YWVllQ3R5nDNmsG8eWqikbgA0Gu0+qdG\nMZaKmtiL6yanNPknOjo600u+CpGTyDWd85w4cQKAGjVqmDkSkevMmAETJ3K/d28eNWlCWT8/qFED\njh83d2QiLeLjYeVKmDr1+U3hp5+qf86BsuLfsqdRT5j960eEPL6XtC38wTOiA504fuSU0eNKlSrF\n8OHDadeuHZaW8j12krAwdT6NtTXcvQtHjkCFCupwqldAWu/fjZErQQghhDCV/6qCxxQrJkOnXjV/\n/w0DBiQt6YqPD0yZAl27mjWsJNHR6s2qoaFcJhIXH8fizV8mJRnhwc+4cjSY4MAnRo8pV64c7733\nHq1atUKbhbG9slxcoEoVOH1afbVta+6IspUkGkIIIYSpvJBoxLu4wNCh6rAbY2P9Rc7h5qYmhd7e\nMGkS9OwJFhbp7ycgQF2xydSrCs2YAb/9pi6r2+x57QqLyEgYNUq99hJXNMoARVH4dc88rt29qCYY\nR4IJDjKeYFSqVImRI0fStGlTGZqdmmbN1OF4RmqK5GaSaAghhBCm8t98jJhixUCjgR9/NHNAIs28\nvGD/fqhVS12GNCMuXIBKldSaFtevg6OjaWJ7+hS+/x4ePlSfarwgwdZWnU/y5AncvJnhITk7jv/G\njr1buHz0Pg+CIoy2q1y5Mu+//z6NGjWSBCOtvvxSXf74NSRfrwghhBCmcukSXLhAjJubuSMRGVGv\nXsaTDIBy5dREJSwMFiwwXVw//aQmGXXqqCsWvcjSEho1Un9+uZBfGv26cTmffTSNv365ajTJqFKl\nCsuWLeOPP/6gcePGkmSkR0aejOUSkmgIIYQQpmJnp95symTY15NGA598ov789demGSoTFwfffKP+\nPG6ceo6XJa4wuWdPuro+ffo0b/XqxvhRk3lw3XCCUbVqVZYtW8bvv/8uTzFEusm/hEIIIYQQptKm\nDVSrptZUWbwYRozIXH+//qoOifLxgTfeMNzmxURDUQwnIy84ffo03377Lfv37zfapnp0NCNnzKBB\n//6SXIgMk0RDCCGEEK+n774DW1t1ZSlTFVBLfKrx5pswZw4MH565hQCcnKBMGRg7NqkfRVE4fmkf\n+y5uxUJryY1iJcnToTLO98JwPvYnebzL4+yQDzsbB70k4dy5c8yZM4c9KTz5KFPWi0/+Okq9yEg0\n3bunmrQIkRKpoyFEFpNrOueROhoiqyVdY6VLww8/QGQkfPGFmaMSenQ6KFQIQkPh33/VJwam7Hv6\ndOjfH9zdTdOfTgeWliQkxLN230IOnd+R6mFWFtbkcchH7GMNJ/Ze5srZ60bb5i/iQK/+3fmw0Vto\nfHzUSeU3bmQ+dvFKkzoaQgghRE4QHa1+O/4irRYmTlRXCpo2TZa4zUlOn1aTjOLF1ScGpqTVPp+r\nYar+tFqeRj1hydZZXL19Lk2HhQU/5vCRK9wLeGy0Tf6iDpSpXYjmTVoxoO0YNJu3qDtMmXiJ15Yk\nGkIIIYQpVK6srjZ09OjzbY6O4OoKDx6oVYGLFTNffELfn3+q761avRLDg4If3mbhxi/0KnYbE/Ew\nmitHgrl7Jdxom3xF7ClT240C7o54FC5Dn1aj0Gq04OkJEyao9USEyCRJNIQQQojMSkhQi73FxamF\n3x49er6vZEk10QgMlEQjJ3kx0cjhLt34h6VbvyIq9pnedkebvFR0r4erWwEeP31EUGAguzb+zaXT\n1432ldfNnjJ13ChY3BGNRkN+p4IMaT8Ra0sbtUGFCuqwLyFMIF3PcGfMmIFWq2XESysoTJ48maJF\ni2Jvb0+TJk24ePGiSYMUQgghcrTbt9Uko3BhcHDQ31eypPr+XzE/kQM8eQKHDqn1DV6osp1jhIVB\nTAwAB85sZcGGqcmSjJJFytK28kBKFaqKd4Fq/L3hAvOm+RtNMkqW8mDkxCF88uWHtG7RllLuFale\npiEju35BHoe8Wf2JxGsqzU80jhw5wqJFi6hUqZLeCgYzZ85k9uzZLF++nNKlSzN16lRatGjB5cuX\ncTRVRUwhhBAiJ7t2TX338kq+z9NTfQ8Kyr54RMpsbWHzZrXAYt5suMk+ehRWrlRXuUrLPJ2PPiJh\n6xbWzRjEwfALyXbXKtuU7k2HsXPHTpauW8H+/ftJSEgw2FXZsmX54IMPaN68uSxTK7Jdmp5oPH78\nmD59+rB06VLy5cuXtF1RFObMmcOECRPo3Lkz5cuXZ/ny5URERLB69eosC/pVs2zZMrRabdLLysqK\nYsWK0a9fP27cuMGAAQP09ht7NWnSJKnPbdu20bRpUwoXLoy9vT0eHh506tQJf39/M35SIYR4TaWU\naLRtqxZva98+e2MSxllbq0OmRo3K+nPFx6vL5/7wA2zYkHr7u3d59ps/CzqVTJZkaNDQsX5/mlTo\nyuRJkxk5ciR79uwxmGSUKV2a+fPns3nzZlq0aCFJhjCLND3RGDp0KN26daNRo0a8uBpuUFAQwcHB\ntGzZMmmbra0tDRs25NChQwwdOtT0Eb/CpkyZgpeXF9HR0Rw+fJhly5Zx4MAB/P399X6HFy9eZPr0\n6bz33nvUrl07aXuhQoUAmD17NmPGjKF+/fqMGzcOJycnAgMDOXDgAIsXL6Znz57Z/tmEEOK1Fham\nDsMxlGjUrau+xOvJ0lKt6D1ypLryWKdOKU4+f/D9LBa+W5sHhZz0tltb2fJGzUHs33qUd1eNJzY2\n1uDx3sCoBw9o+8svaGvVMuUnESLdUk00Fi1aRGBgYNITihcz4vv37wPPb4ATubq6cvfuXVPGmSu0\natWKmjVrAjBo0CAKFCjAzJkzCQoKolevXknt9u3bx/Tp06lfvz7du3fX6yM+Pp6pU6fSpEkTdu/e\nnewcISEhWfshhBBCJDd+PIweDUZu/sRrzs9PraNy+jRs3Qrt2hlsduXSEZY4XeGZvX6SYW+ZF+uQ\norzT732ioqIMHuvp6cmoUaNov3kzFosXw759kN5EY8cONb4OHXLm3BXxykkx0bh8+TIff/wxBw8e\nxMLCAlCHS6Wlxl9Kj+gSCxkZUqJEidemuFn9+vWZOXMmt27dSvMxoaGhPHnyhPr16xvcX7BgQVOF\nJ0wkIiKC8+fPmzsMYUBK/xYJYQpyjYlEhXr0wP3bb4kcP55Lrq7JnmpcuX+KYwFb0dlbJW2Lj00g\n+EIsl45f4dkzwwlGoUKF6NatG/Xr18fCwoLrnp54AY/Xr+dqOpOFYqtW4bZyJXeio7mXgeJsIvcp\nVapUpo5PMdE4fPgwoaGhlC9fPmlbQkICf/31Fz/++GPSzVNwcDDFXliyLzg4GDc3t0wFlhaeiRPs\nskhQFk/cu379OkC6fleurq7Y2dmxadMmRo0aRf78+bMoOiGEECL30URHo5jhC82QN9/EbdkybIOC\nsL57l9iiRQHQKTpOBu3i33vH4L/cIyFex/UzoQSdfEjUsxiD/bm4uNC1a1caN26MpeXz27mI6tUB\ncDx9Gk1cHIqVlcHjDbH5rxJ4tIdHBj6hEMmlmGh07tw5aagPqE8zBg4cSOnSpZk4cSKlSpXCzc2N\nHTt2UP2/Czs6OpqDBw/y9ddfG+23Ro0aRvdFR0en9zO8MsLDwwkNDSU6OpqjR48yZcoU3NzcePPN\nN9Pch1ar5aOPPmLy5MkUL16cevXqUb9+fb1hWSJncXJySvGaF9kv8Vtm+XsRWUWusRwqNhYKFoTy\n5WH3brCzy97zb94MFSpQ6b+VrqJinrJ82zf8e+8UALoEHTfPP+TKsWBinsYb7MLFxYXhw4fTq1cv\nzp1TK4Qnu858fbFwdqZ68eLwX0KTJv8Nifdq2xYqVUrnhxO50ePHxqvKp0WKiYazszPOLz06s7e3\nJ1++fJQrVw6A999/n+nTp+Pj40OpUqX4/PPPcXJy0ptzIFStW7fW+3OVKlVYu3YtTk5ORo4w7LPP\nPqNkyZLMmzePPXv2sHPnTiZNmkSpUqVYsWIFtWTylxBC5CxbtsCaNfDGG9Cli7mjeX39/bdaQ+PJ\nk+xPMgD+G/asKApXbp3lt/2LCH54G51O4fa/j7hy5D5REXEGD3V2dubtt9+mf//+2Nvbp3yeo0fT\nX+08Lk6t9aLRQCaHywiRKN2VwTUajd78i3HjxhEVFcXw4cN59OgRtWvXZseOHTi8XLBIMHfuXMqW\nLcvjx49ZunQpmzdv5vDhw3gZWqUkFX369KFPnz48e/aMEydO4O/vz6JFi2jXrh2XLl2iQIECWfAJ\nhBBCJBMWBjodFChg/ObuwgVYsQLy55dEw5xyQDXwq7fPs/WIP9fuXEBRFO5eCefykWCePjI8RMrB\nwYHBgwczePBg8uTJk7aTZGQp22vX1KV4PTzMk4SJXCndicbevXuTbZs0aRKTJk0ySUDpkdVzKEzN\n19c3aXhTx44dadSoEe+99x5t2rTBxcUlQ33a29vTsGFDGjZsiKurK9OmTWPbtm307dvXlKELIYQw\nZu5cmDIFPvlEXb7UkMTq4K/Y/7dyHTMmGtfuXGTbEX+u3D6HoigEBz3h8qH7PAk1PGTc1taWfv36\n8fbbb2fPfMxChWDVKjXZEMJE0p1oCNPQarV8+eWXNGjQgG+++Ybp06dnuk9fX18A7t27l+m+hBBC\npFFisb6UJtAmJhqBgVkejjAiOBj++UetCt6gQbadNujeZbYd8efSzX8ACLsdyb9/3+PRvWcG21tZ\nWdGjRw/ee+89XF1dsy1O8uWD3r2z73zitSCJhhnVq1ePOnXqsGDBAj7++OM0DTeLiori1KlT1KtX\nL9m+rVu3AuDj42PyWIUQQhiRUlXwRImrJAYGgqJkbGiLyJxr16BwYXWSczYMDboZHMDWI/5cvH4S\ngMcPnvHv3/cJuRFhsL2FVkuXrl0ZMWKE3kqeQrzKJNEwszFjxtClSxcWL17MqFGjUm3/9OlTGjRo\ngK+vL23atKF48eJERESwa9cutmzZQu3atWnfvn02RC6EEAJIW6KRLx/kzQvh4RASAtn5TbVQ1a0L\nd+5AJlfRSc3tkEC2HvmF84HHAIh8FMPlQ/e4e9X4eTtER/P+5s2U/G8FT5OIjoZNm9Trc/x40/Ur\nRDpIopFNjBUw7NSpE97e3syZM4cRI0ag1WpTbJ8vXz4WL17Mli1bWLFiBffv30ej0eDt7c2kSZMY\nO3ZsUh9CCCGyWEQEPHgANjapLyM6bx7kyQOOjtkTm0hOo1ETvixwN/QG247+wpmAwwBERcRy5Wgw\nty48xFid46bR0YwOC6PcO++AKZMMgIQE6NVLXahg2DCQAnzCDDRKWsp8m8CL6/C+vGTui6Kjo1+b\nyuDi9SDXdM4jNQ6EyVy/Dm3aqENxTp1K2vxaXmN37sC4cTBxolqn4jVx/+Etth/9ldNX/kZBISYq\nnoDjD7h+JhRdguFbLF9fX8aOHYvvnj3g76/W18jAcKlUr7MGDeDgQdiwQV1aWYh0Suv9uzHyREMI\nIYTIKA8P+PdfjH5l/Trp3h0OHYLTp+HiRXNHky12HFvLliP+KIqO+NgEAk+FcO1UCPGxOoPty5Ur\nx9ixY2nUqJE6csHXFz76KOsCbNpUTTT27Ek50ThxAiZMgNatYfTorItHvHYk0RBCCCEySyZ3q0kG\nqInXa2Dv6Y1sPvwzCfE6bpwN4+rxB8RGGV4a1sPDg9GjR9O2bdvsHd7ctClMnaomGik5cwZ27QI3\nt+yJS7w2JNEQQgghROZcv/78ZzPU1UpRRAQsWaJ+W1+mjEm6PH5pP7/v+4nb/z7icgrVvN3c3Bg5\nciRdu3bFysrKJOdOl9q11eV8z51T5xIZW4Tg0iX1XVatFCYmiYYQQgghMufZM+jYUZ1oPXmyuaPR\nt3cvvP8+1Knz/KlLJlwIOsk3C6Zy8eBdIsIMF9vLmzcvw4YNo1+/fuado2djA59/ri7ra29vvF1i\nomGiREyIRJJoCCGEENlBUaBPHwgIUMfNm+Mb7qxSrhysX2/uKAwzYTXwTX/+wZRpnxF2J9Lgfnt7\newYPHoyfnx958uTJ9PlMIi1zLi5fVt/liYYwMUk0hBBCiIyIi1O/Iff2Tn1pW1DncRw8CDdvqq+U\n6m4I0zFBonHlyhU+nz6Nv/YfNLjf2tqa3r178+6771KgQIEMn8csYmLUQpJarXotC2FCkmgIIYQQ\nGREUBI0bQ4kS+nMUUuLpqSYZgYGSaGSHa9fUV7586gpP6XT37l3mzJnDunXr0OmSrySl0Wjo3Lkz\nH3zwwatbzdvSUl116sYNdT6HECaUIxMNRVGMFqwT4lWSTWVqhBDmkJaK4C8rWRL271cTDZH1Ep9m\nNG8OFhZpPiw8PJx58+axfPlyYmNjDbYpX6UMs6b/j7Jly5oiUvOxsIAqVdSXECaW4xINa2vrpAJn\nkmyIV5miKERHR2NjY2PuUIQQWSGjiQbk3kRDUeCnn9Q6GrNmpevmPks0aKAWEKxdO03No6KiWLZs\nGfPnzyciIsJgm3xu9nTr14Hx78x49e5TFEWWYhbZKsclGlqtFhsbG2JiYswdijCDxH/YnZyczByJ\nadjY2GTvmulCiOyTmGikZ1y7p6f6HhRk+njM4dYtteBc587QrZt6EztlCty+DcOGQalS5o2vYkX1\nlYr4+HjWrl3Lt99+S3BwsME2jvls8KlXmJYtWzCo3UevVpLx8KG6EMH163DhgiQbItvkuEQD1GTD\nrMvBCbM5f/48ADVq1DBzJEIIkYqMPNFo1kwtjJZblhHdtg38/dXlbbt1U7eVL68mGufPmz/RSIWi\nKPz555/MmjWLQCNPmWwdrShduxDu5fJTyr0CA9qMwUJr5ic16ZU3Lxw7BmFh6nUrk75FNpGvWoUQ\nQoiM8PaGypWhdOm0H+PmpiYbr+rE4Zdt366+t2nzfFuFCur7hQvZH086HD9+nK5duzJs2DCDSYaV\njQVl6xem6QAfSlRwwd3Vk6EdJmJlaW2GaDNJq4UmTdSfU6sSLoQJ5cgnGkIIIUSON3u2uSMwr9hY\n9ekM6Cca5cur7zk00QgICOCrr75i586dBvdbWllSolI+vH1dsbZVb5Nc8hTinU6fYWfjkJ2hmlbT\npvDbb2qiMXSouu3BA3USeK1a8Mcf5o1P5EqSaAghhBAi/Q4fhogItVhf8eLPtyc+0fhvKKxZGJj0\nHBwczJw5c1izZo3BpWq1Wi2NmtfFwj0MO6fnTy2c7Jx5t/NknB3yZ3nYWappU/V9z57nv59Ll+De\nPfUlRBaQoVNCCCGESL9t29T31q31t5crB+PHwyefZH9Mifz91W/qly4lIiKCr7/+msaNG/PLL78Y\nTDKaN2/O94u/Jk/5p3pJho21He90+oyCeQtnZ/RZo3RpKFJEnU9z86a67dIl9T23zBkSOY480RBC\nCCFE+n38sbps7MsTvh0cYMYM88SUaPt2Ys+c4ed9+/j+++95+PChwWZVq1Zl/PjxFHTPw/e/f4ZO\neZ6EWFhYMqT9BNxdc0lhRY1GreFSogRYWanbLl9W3318zBeXyNXkiYYQQgiRnTZvhkqVYPRoc0eS\nOU5O0KnT8zkZOYQuPp7Nu3fTomhRph44YDDJ8PDwYN68eaxbtw53r8L8uOFz4uKfF+bToKFfqw8p\n7V4pO0PPet7ez5MMkCcaIsvJEw0hhBAivRInEtesCc7O6T/+3DkonAuG4+Qwhw8f5svPPuOsteGV\noQoUKMCoUaN46623sLKyIjwyjPnrJ/MsJlKvXdcmQ6laqm52hGxeV66o7/JEQ2QRSTSEEEKI9Jow\nAU6ehL//hrrpvCHNbUX7coBLly4xc+ZM9u3bZ3C/vb09Q4cOxc/PDwcHdeWomNgoFm78gvDIML22\nrWu9RYNKbQx1k/ucPQsBATm+3ol4dUmiIYQQQqSHoqg3Z5CxwmeJicb165CQABavWPG3HOTevXvM\nnj2bdevWoShKsv0WFhb07NmTkSNHUrBgwaTtOl0Cy7Z/w+0Q/foZ9Sq2pk2tHlked45hZ5emyulC\nZJQkGkIIIUR6PHwIjx+DoyO8cPOaZvb2auG++/fh7l1wdzd9jFkpLAxsbNTPb4yiwNix6jfmGzeC\nra1JQ3jy5Ak//vgjP/30EzExMQbbtG7RgrHjx1OyZMlk+/74aykXgk7obavg6Uu3xkPQvLQsbq50\n/z5cvPh8yVshsohMBhdCCCHS49o19d3LK1mthjRLvPlN7OtVMns25M8PP/xgvI1GA5s2qXNZElc2\nMoHY2FiWLl1K48aNmTdvnsEkw9fXl99//535CxcaTDL2/7OZ/f9s1ttWzLUk/Vt/iFb7GjxdCg1V\n5wd16KAWXRQiC8kTDSGEECI9EpODjAybSrR0qfpEwM3NNDFlp23bIC4u9XH95curk40vXIDKlTN1\nSkVR2LJlC7NmzeJmYg2Il3h7ezNu3DiaN29u9KnEhaAT/H5gid62vI4uvN3hE2ys7TIV4yujQAG1\n1snFi3DsGNSvb+6IRC4miYYQQgiRHoULQ48embtBK13adPFkp/v34fRpdWx/w4Ypt61QAf74I9MV\nwo8ePcqMGTM4c+aMwf0FCxbkgw8+oFu3blhaGr+tuR0SyNJtX6O8UCvDxsqWt9/4BGfHV7zqd3o1\nbaomGnv2SKIhspQkGkIIIUR6NG6svl5H27er702apD7vIrG+xoULGTrV1atXmTlzJrt37za438HB\nIWklKXt7+xT7Co8M48cNnxMbF520TaPRMqDNGIoW9MxQfK+0Jk3g++9h0iQYNSpjSzQLkQaSaAgh\nhBAibRITjdatU29boYL6ns4nGg8ePOB///sfa9asQafTJdtvbCUpTp9W3ytXBu3zKaiJy9g+fqpf\nuBbFuo4AACAASURBVK9LIz/Ke9ZIV2y5RqNG6ruFBeTJY95YRK4miYYQQggh0sbFRZ0I3iYNdSZK\nl4aVK58nHKmIjIxk4cKFLF68mKioKINtWrduzZgxY/Dy8kq+c8oU2LABliyBgQMB48vYNq7SgYaV\n26YprlzJxQX+/Vd9KvU6rLIlzEYSDSGEEMJcEr+x174ii0D+8AN8913aan9YWUGfPqk2i4uL49df\nf2XOnDmEhYUZbFO9enUmTJhA9erVjXWizjcAaNYsabPBZWxL1qRTgwGpx5/bSTVwkQ0k0RBCCCHM\noXVr2LsXTp16Pp/hVWCiAoOKorBjxw5mzpxJkJEq6R4eHowfP56WLVumXN/i8GGIiFBvnosXB4ws\nY1uwJP1bffB6LGMrRA4giYYQQgiRVmfPqslBnTpQs2bm+4uNhcDAVyvRMIGTJ08yY8YMTp48aXC/\ni4sLo0aNokePHlhZWaXe4Z9/qu+tWgEpLGP7xmu0jK0QOYAkGkIIIURa7doFo0fDe+9lPtFILCYX\nGJhyu1wkMDCQWbNmsT1xUvlL7Ozs8PPzY+jQoTimVHn8ZTt3qu+tWskytkLkIJJoCCGEEGkVEKC+\nG5qMnF6vUaIREhLCd999h7+/PwkJCcn2a7Vaunfvzvvvv0+hQoXS17miQMeO4OhIeLXy/Lhhsixj\nK0QOIYmGEEIIkVaJVcFNkWh4/nfja2R+Qo7yv/+BvT1066auOpVGz549Y3GTJiwMDuapkTkWzZo1\n46OPPqJUapXGjdFo4OOPiRn7IQt/+1iWsRUiB5FEQwghhEirxETD2zvzfSU+0bh/P/N9ZaWEBPji\nCwgLUwsVpiHRiI+PZ+3atfzvf/8jJCTE4BKqlSpVYsKECdSuXTvTIcoytkLkTJJoCCGEEGkRHw83\nbqg3zZ4mGIZToQKEhqbrCYFZnDihJhmenmptjBQoisLu3buZOXMmAYnDzF5SvHhxxo4dS7t27VJe\nSSodZBlbIXImSTSEEEKItIiNhc8+U2+6bW0z35+VlVo4Lafbtk19b9MmxeJu//zzDzNmzODYsWMG\n9+eztmbE+PH07t0ba2trk4R2J+Q6mw+t4sJ1/SRDlrEVImeQREMIIYRIC3t7+PRTc0eR/RJXiGrd\n2uDuGzduMGvWLLZs2WJwv42VFYNDQni7alXy/FexO7NCH99n62F/Tl4+gIKit0+WsRUi55BEQwgh\nhBCGhYbCsWNgbQ1Nm+rtCgsLY+7cufz888/Ex8cnO1Sj0dC1a1c+6NqVwrVqweXLmQ7nydNw/jy2\nhkPnd5CgS35OWcZWiJxFEg0hhBBCGJYnj/pEIyAAHBwAiIqKYsmSJSxYsIDIyEiDhzVu3Jhx48ZR\ntmxZ0OnU6uc+PhkOIyrmKXtOrWfv6U16S9e+qGThsnRrMlSWsRUiB5FEQwghhDCnuDh4/BgKFDB3\nJMlZW0PLltCyJQkJCaxbt47Zs2cTHBxssHl+NycatKtCk8aN0Nk+5VlMJPY2jlC1aoZOHxcfy19n\nt7Lj+DqeRUcYbFPkXgQdBn9BOe9aJptcLoQwDUk0hBBCCHP56y91ydgGDWDfPnNHY5CiKOzdu5eZ\nM2dy5coVg23yuuTB0zcvRcvkRad5wu6T69l9cj0aNBQt6Il30fJ4FyuPV5FyONjlSfWcCboEjv27\nl21H/AmPDDPYJr/WgXbLD1C9QHm0pTK/RK4QwvQk0RBCCCFSoyjw3nvg4QGjR4NWa5p+ixRRhxbl\n0OrgZ86c4csvv+TIkSMG9zs7O9OkXW1i89/FwjL570RB4XZIILdDAtn3zyYACrsUx7toBbyKlsO7\naHnyOOR73l5ROHvtCJsP/Uzwo9sGz+lo50yrmt2oO38DVidvw5fvmeCTCiGygiQaQgghRGru34d5\n/2fvrsOjuL4Gjn/jLiQkwS24S5BQGtxpgEILRX4FCi1FSr2lRoWWCrR9W6RYgSLFrVhxL+7BJVhC\nCEmIEd99/7gEWLIb3WQ34XyeZ59JZu7MnIUQ5uyVM1XVvPjgA+Ndt1w5lbTcuqWWzzXSsq95df36\ndSZOnMi6dev0Hre1tWXw4MHUbVGJTUcXYUX2E6/QiBuERtxgz6kNAHgXK03l0jUp7VWJQ2e3cz3s\nkt7z7GwdaNuwB60aBGJv6wDb3lYHnpqkLoQwH5JoCCGEEFlJrwju62vc69rYqGQjOFgVA6xSxbjX\nz6HIyEgmT57MggULSElJyXDcwsKCnj178u6773L3QTBzN0zUOe7i4MYLz/2Pm3evcPn2GUIjbmR5\nz7tRt7kbddvgcSsra56v24UOjXvj/OSwqx071HCzXM7/EELkP0k0hBBCiKzkV6IBquJ2cLAaPmWi\nRCMhIYE5c+bwxx9/EBurf9J1QEAAH330ETVr1uTSrTP89e8vOjUsbG3seaP755TzqUyzWm0BiEuI\n4crts1y5HcTlrcu47WGH1jJ7E7YtLCxpUqM1nZv2xcPVK2ODsmVh4MCcv1khRIGRREMIIYTIyuXL\napsfiUalSnDmDBh4wM9PqamprFixgl9++cXgSlI1a9bk448/5vnnnwcg5N51Zv3zHWlpj+tYWFpa\nMaTLh5TzqaxzrrODK/UqN6Ne5WbwyZ88OL6Nq4v+4EpxKy7fCuLm3StotJoM96zr25Su/v0p6VnO\niO9WCFHQJNEQQgghspLeo1G5cubtcmP6dJg1y/jXzYRWq2Xbtm38+OOPXLqkf05E6dRU3u/YkcAZ\nM7B8OPk9KjacaWu+JiH5gU7bV9qOpGaFhpnftHZtHPfvp/aNeGr3eAuAxOQEroWe58rtIILvXMTB\nzok2DbtTsWTua24IIcyHJBpCCCFEVoYNg3r1oHlz41/bysr418zE8ePHmTBhAocPH9Z73M3NjRH3\n7vFqSAh2Y8Y8WmHrQWIcf6z5huinlpvt5t+fpjWzMSG7Vi21PXPm0S57WwdqlG9AjfIyz0KIokgS\nDSGEECIrrVurVyF29epVfvrpJzZt2qT3uK2tLYMGDWJEixa4BQRA6dJQuzagCufNXDchw+TuFnU7\n075x7+wFkJ5oBAXl+j0AEBmpKpZbyyOMEObOSAuBCyGEEMIchYeH8/nnn9OhQwe9SYaFhQW9evVi\n+/btjB07FreYGFXfo1MnsLBAo0njr39/4cpt3QShrm8zerccmv1q3LVrg4WFWsY3L0aPBk9PMLD0\nrhDCfMjHAUIIIUQRFBcXx6xZs5g5cyYPHjzQ26ZVq1Z8+OGH1KhR4/HOrl1VXY/4eLRaLSt3z+bk\n5f90zqtUsgb/6/QOlpY5GPbl7Q3x8eDgkJu3o2i1sH07xMSoSfRCCLMmiYYQQghhag8ewLVrariS\nu3ueLpWSksLixYv5v//7PyIiIvS2qVu3Lh9//DH+/v76L2JhAc7ObD2ykt0nN+gc8vEow7DAT7C1\ntstZYBYWeUsyAC5cUMUTfXzgyeRICGGWJNEQQgghTK1fP1izBpYtg97ZnPPwFK1Wy8aNG/npp58I\nDg7W26ZcuXJ88MEHdOnS5dFKUoYcOreDf/b9pbPPzcmDN7uPw8neJVcx5tn27WrburVKXIQQZk0S\nDSGEECIzEyfC2bMwahQ0zGIJ19xKHwZ09WquTv/vv//44YcfOHnypN7jHh4ejB49mn79+mFra5vl\n9c5dP86irZN19tnbOvJmjy/0F88rKDt2qG2bbKxyJYQwuSwng0+ZMoV69erh5uaGm5sbzZs3Z8MG\n3W7UL7/8ktKlS+Po6Ejr1q05e/ZsvgUshBBCFKj162HOHLh3L//ukctE4+zZswwaNIh+/frpTTIc\nHBwYNWoUO3fuZNCgQdlKMm6EXWb2+h/QaNIe7bOysmZot7GUKl4hR/EZnZUV2NsX+hXAhHhWZNmj\nUbZsWX788UeqVKmCRqNh7ty59OjRg8OHD1OvXj1++OEHfv75Z+bNm0fVqlX5+uuvad++PRcuXMDZ\n2bkg3oMQQgiRf9KL9eVHVfB0OUw0bt26xaRJk1izZg1arTbDcUtLS/r06cPbb7+Nt7d39mKIiuLe\notlMtzhOckqizqGBHd6matk62btONu5DUJCqSZLF8K0MFi+GpCTIRsIkhDC9LBONwMBAne/Hjx/P\ntGnTOHToEHXr1uXXX39l7Nix9OzZE4B58+bh7e3NokWLeP311/MnaiGEEKIgJCaqFZisrKBcufy7\nT8WKanvtGrEP7nMn8ialilfIMBciMjKSKVOmsGDBApINLBPbqVMn3n//fXxzmBiF7t7IrJBNxHrr\nfkjYM2AIDau2yNG1MlWzpprQffXq4/edE3Y5nIQuhDCZHM3RSEtLY9myZSQmJhIQEMC1a9cICwuj\nQ4cOj9rY29sTEBDA/v37JdEQQghRuF27ppZULV8ebGzy5RZpaalcs0vg3CtNOVfNi1szBwFgY2VL\n01ptadOwO442rsyePZsZM2YQFxen9zqNGzdm7NixNGiQsyrbIfeus+nQEk4E74enkow2DbvTukGg\ngTNzqXZtlWicOZO7REMIUWhkK9E4ffo0/v7+JCUl4eDgwNKlS6lWrRr79+8HwMfHR6e9t7c3ISEh\nxo9WCCGEKEjpw6YqVzbqZSOiwzh3/Tjnrh/j4q3TJCUnQNMSOm1S0pLZfXwDCxcs5OqRCOJi9NfC\nqFatGh9++CGtW7fOfvE8IOReMJsOLuXE5f16jzeqFkBgi1ez/6ayq1Yt2LpVDZ964QXjX18IYTay\nlWhUr16dU6dOER0dzbJly+jbty870ld+MCCzX3ZHjhzJWZTimSM/I6IgyM+ZyIq1vT1Okyahsbcn\nNhc/L+k/YylpyYRFX+f2/SuERF0lNjEy0/O0Wi2hl6I5vz+U+Pv6h0gVL16cvn370qJFC6ysrDh6\n9Gi2YoqKv8upm3u4HnHOYJsyxapQ3eM5jh09lq1r5kRxJycqABG7d3OtXTujX/9ZJL/LRH6pUqVK\nns7PVqJhY2NDpYcT1Ro0aMDhw4eZMmUKX3zxBQBhYWGUKVPmUfuwsDBKlCih91pCCCFEYZHq7k50\nQECOz9Nqtdx/cJfbUVcJuX+FuzE30WjTsj4RuHczjvP77hB1J17vcRt7K+q3qEKv7i9Tyad2tnsx\nouLDOHlzDzcizhtsUyo0lqqtBlPWs1qOekdyIuHh3BGH9N6ibHA9eBCr2FhiGjcmzc0tX+ISQhhf\nrupopKWlodFoqFixIiVKlGDz5s00atQIgMTERPbu3cvEiRMNnu/n55e7aEWRl/6pjPyMiPwkP2ci\nP4VG3GDKiq+ISdBflVsfF0d33CjF/k2nOXlM/wO4pbUFlRp4UbmRNzb2Vuy7soZLkUdo26gnjau3\nxNpK/xyS2+HX2HRwCSevHDB4/9LuZeh8w4o6tq5YdBqQ7bhzpWpVmDABx4YNs/9v8PPPYdMmWLgQ\n2rbN3/gKEfldJvJbdHR0ns7PMtH4+OOP6datG2XKlCE2NpZFixaxa9cuNm3aBMDbb7/Nd999R/Xq\n1alSpQrjx4/HxcWFfv365SkwIYQQorDRarUs3PJ7lkmGpaUVlUrVoEa5BrhY+bBwzhIWrfvbQFsL\navpVpERdexycdZOJu1G3+XvrZDYc+JvWDV6gee2O2Ns6AHAr/CqbDi7lVCYJRhmvSnRq2oc6lZrk\nWw9GBq6ucOlS9tunpMCePeprqZ8hRKGSZaIRFhbGgAEDuHPnDm5ubtSrV49NmzbRvn17AD788EMS\nEhIYOXIkUVFRNGvWjM2bN+Pk5JTvwQshhBDm5OLNU9wI0/8Q7enmQ43yDalRvgFVytQhNjqO3377\njcWLF5Oamqr3nCeXqr1y+yxbj64k6FrG8fjRcRGs3jOXfw8t47k6nbgbdTvLBKNzs77Urti44BKM\n3Dp8GOLjoVo1KFnS1NEIIXIgy0Rjzpw5WV5k3LhxjBs3zigBCSGEEIXV5sPLdb4v6VmO5+p0okb5\nBni5q4fkmJgYpvw+ldmzZ5OQkKD3Ok2aNOGjjz6iYcOGj/b5lq6Jb+mahNy7zrajqzh6YTcarUbn\nvISkeLYeWWEwvjLelejctJAkGOnSF59p08a0cQghcixXczSEEEKIIm/fPnjvPejWDT77LMvm10LP\nc+nWaZ19r7QbRYUSVQFISkpi/vz5TJ06laioKL3XqJGSwoeRkbScNQsLFxe9bUoVL8/Ajm/T1b8f\nO46v5b8zW0hOTco0trLevnRu2pdaFf0KT4KRLj3RkGFTQhQ6kmgIIYQQ+pw9CwcPQvXq2Wr+dG9G\nCbcKVChRlbS0NFatWsUvv/xisMZU2bJlee+993jhww+xvH0bgoOhTp1M7+fh6k2vlkPp2ORldp9c\nz+6TG3iQGKvTppx3ZTo17VM4E4x0b76pCvu1amXqSIQQOSSJhhBCCKHP5ctq+3A51szcDr+WYe5E\n7dLN2bJlCxMnTuTixYt6z/P09GT06NG88sor2NrawvTpcPEiXL2aZaKRztnBlS7NXqFto54cCNrK\nkQu7cbBzomW9rtSs0CjrBOP77yEkRD3Q16iRrXsaxf79cPo0DB4MtraG2/XqpV5CiEJHEg0hhBBC\nn/Q6D9lINLYcWanzfWqkA1Mn/cmFCxf0tnd2dmbYsGG89tpruounPKxZxbVrOQ7XzsaelvW70bJ+\nt5yduGiReuB/5ZUc3zNPBg5UCdVzz0Ht2gV7byFEgZBEQwghhNAnm4nG3agQjl/aB0BMeALn9ody\n91qs3ra2trYMGDCAESNG4OnpmbGBnx+0b19wqyvFxUFQEFhbQ/36BXPPdLVrq0QjKEgSDSGKKEk0\nhBBCiKdptdkeOrXt6Cri7idw4b8wbp/XP8nbwsKCnj178s4771CmTBnDFxs0SL0KytGjoNGoJMPB\noeDuC1CrFqxdqxINIUSRJImGEEIIoc/x46pXQ1/Pw0OXgy8wc8o8gk/dQ6vR6m3Ttm1b3n//fapn\nc1J5gTp0SG2bNCn4e6f3Ypw5U/D3FkIUCEk0hBBCiKdZWEDlyuqlR2xsLDNnzmT6jD9ITkrR26Za\ntWp88803NG7cOD8jzRtTJhq1aqmtoR6N8ePVEsMffSQrTglRSEmiIYQQQmRTUlISCxYsYMqUKQZr\nYVSrVo2ePXvSsGFD804yAH78EXr2hJYtC/7e1apBjx5qdS2tViV3T1q3Ti0v/NZbBR+bEMIoJNEQ\nQgghspCamsqqVav49ddfDdbCcHKz58vPv6Fnj54cP368gCPMpYoV1csU7O1h1Sr9x2Ji4MgRNUm9\nRYuCjUsIYTSSaAghhBAGaLVatmzZwk8//cTl9MnhT7F1sKZqU29GD3+PDk1fzPtNL15UD9l16mS7\nlkaRs2cPpKWBvz8YqJAuhDB/kmgIIYQQ6YKD1byA3r05cPw4P/zwAydOnNDb1NrWEt+GXlRq6IWb\nqzstG3Q2Tgxz5qgiel988ewmGjt2qG3r1qaNQwiRJ5JoCCGEEOmmTOHMb7/x06+/svvePb1NbGxs\nqFTfm/IN3LFzVP+NtqzfDTtbIy0Pmz6vY8sW+Oor41yzsDlwQG3btDFtHEKIPJFEQwghhACuBAXx\n86JFbChVCvQkGZaWlrz44ov4d6jLzrMrHu23s7EnoF5X4wXSoQPY2amH7bAw8PEx3rXTabXqZWlp\n/Gsbw44davhYQRcRFEIYlZn+hhFCCKEjOhpq1IARI0wdSZETEhLCRx99RMcXXmCDra3eNu3bt2fj\nxo1M+P47Tt7YpXOsRd3OONo7Gy8gZ2do21YlAuvWGe+6T7p0CTw8YMCA/Ll+TsydC2PGqCrl6Wxs\n1PyMgi4iKIQwKkk0hBCiMLCzUyvwTJv2uPaByJOIiAjGjx9P69atWbp0KWnajAX3mjRpwooVK5gx\nYwZVq1bl6IXdRMU97u2wsbKldYPuxg8uMFBt16wx/rVBLRsbHQ3x8flz/ZyYNAl++w3OnTN1JEII\nI5OhU0IIURjY28MLL6gqyp98Alu3mjqiQis2NpbZs2cza9Ys4g08aNeuXZv333+fgIAALB7Wd9Bo\n0thyZKVOu2a12uHq5G78IAMD4fRp6NXL+NcG0xbqe1rt2urnOijo8fwUIUSRIImGEEIUFh98AFOn\nwrZt6tW2rakjKlSSkpKYP38+U6dONVhsr6KnJ+999RWdO3fG8qn5CyevHORu1O1H31taWtG2UY/8\nCbZkSZg8OX+uDeaVaKRXCD9zxrRxCCGMThINIYQoLIoVgw8/hE8/Va82bTJWUxYZpKamsnz5cn77\n7TdCQ0P1tilZsiRjxoyhV69eWFtn/K9Rq9Wy5fBynX1+1QLwcPXOl5jzVVISnDihfnb8/EwdjerR\nANWjceOGmp9RsqRpYxJCGIXM0RBCiMLkrbfA2xvOngUDBeSEotFoWLduHR06dGDs2LF6kwwPDw8+\n++wzduzYQZ8+ffQmGQDnrh/nVvjVR99bYEE7PyMU5zOFK1fUalPVq4Obm6mj0e3R+O47KFVKzUUS\nQhR60qMhhBDmTqt93HPh7AwrVqgVqDw9TRuXmdJqtezcuZNJkyYRFBSkt42zszNDhw5lyJAhuGSj\n8vTTvRl1KzejhEdZo8Rb4GrWhJgYMNC7U+AqVVI9dLVqwbhxal/DhqaNSQhhFNKjIYQQ5u7776Fq\nVZg3T33fokXBJhkhIaon5ebNgrtnLh04cICXXnqJIUOG6E0ybG1tee2119i1axdjxozJVpJx5XYQ\nV0LO6uxr75dPk7QNSUoy7vVsbKBcOeNeM7esrGD8eAgIUMvuurhAo0amjkoIYQTSoyGEEObuyBH1\nAGaq4moODqpHZeRIWLvWNDFk4fjx40yaNIl9+/bpPW5lZUXv3r156623KFWq1OMDixZBly7gbnjl\nqC2HV+h8X718A8r5VDZK3FkKCYE+fVQBwbNni/acnB071DYgQC3lLIQo9ORfshBCmLtjx9TWVMNJ\nUlJg9mxVc2HfPnjuOdPEoce5c+eYNGkS27ZtM9ima9euvPPOO/j6+uoeOHYM+vdXcwKuX9f7cHvz\n7hXOXj+ms69D495GiT1b0ufjREbChQtqXkVRtX272rZubdo4hBBGI0OnhBDCnEVGQnCw6lWoVk1/\nG60WUlPzLwZvb3j3XfX12LHqfiZ25coVRo8eTZcuXQwmGW3atGH9+vVMnjw5Y5IBMGWK2r78ssFP\n0J/uzahUsga+pWrmKfYcsbaGbt3U1/lVvM9clC+vfsYl0RCiyJBEQwghzNnx42pbr57+h+EDB8Df\nH/7v//I3jvfeAw8P2LMHNm3K33tl4tatW3z44Yd06NCBdevW6W3j7+/PihUrmD17NjVrGkgKIiLU\nsClQQ8L0CIu8xcnL/+nsa9+416MCfgXGmFXCL10yn0ngTxs3Ds6fl4ngQhQhkmgIIYQ5u3BBbQ09\nfN2/DwcPwoQJaiUhY3m6oJ2bm+rNAFWZXKMx3r2y4e7du3zxxRe0adOGZcuWodFz/wYNGrBw4UIW\nLVpEw6weVmfPhsRE6NwZKuufb7H1yEq0PO69Ke1VkZoVTDBJuWNHsLNTSWVYWN6u9cEHaqjYsmXG\niU0IITIhiYYQQpizESPUROBPP9V/vGNHeP559Qn9zz8b555LloCvr1pG90kjR6riai+/nL9DtZ4Q\nFRXFhAkTaNmyJfPnzyclJSVDmxo1ajBr1ixWrFhB8+bNs75oWpqqsA4wapTeJpExdzl8YZfOvg6N\nexd8bwaoJY3btoUSJVSPRG5ptSopBahf3zixCSFEJmQyuBBCmLvMlrK1sIBvv1Ur9UyapB6cixfP\n/b1u3YLhw1VPyd27usccHODkyQJZ/SomJobZs2fz559/EhcXp7dNpUqVeOedd+jSpQuWOYnJ0lIN\nm1q8GDp10ttk65GVaDRpj773di9FPd9mOXoPRvXXX6oyfF7+7G/dgjt31HUM9OIIIYQxSaIhhBCF\n3fPPqyFAGzeqmhsTJ+buOhoNDBqkkowuXVTC8bR8TjJiY2OZM2cOs2bNIjY2Vm+b0qVL8/bbb9Oj\nRw+DlbwzZWEBzZur11OSUhJZsWsWB4K26uxv59cLS0urnN/LWIxRN+XQIbVt0qRoL5MrhDAbkmgI\nIURR8O23auJ41aq5v8Zvv8G2bapHZPbsAn0YjY+P56+//mLGjBncv39fbxtvb29GjRpFnz59sLW1\nNXoMt8OvMXfjJMKibunsL+ZcHL/qAUa/X4F7MtEQQogCIImGEEIUBQ0aqFoQuX0Aj4yEzz9XX8+a\npeYDFICEhATmz5/P9OnTiYyM1NumWLFiDB8+nIEDB+Lg4GD0GLRaLXtObWD1nrmkpunOAbGysqZv\nu5FYW9kY/b4FzstLzbHx9zd1JEKIZ4QkGkIIYa6uXVMP/Nl9uM7Lp/weHqo3Y9Mm6N49e+doNLBq\nFbRvD66uObpdUlISixYtYurUqdy7d09vGzc3N4YNG8arr76Ks7Nzjq6fXfEJMSzaOpnTVw9lOOZd\nrDSDOr9HGa9K+XLvAvf+++olhBAFRBINIYQwV4GBcO4cHD2q6mjktyZNcjas5s03YcYMVf/gyy+z\ndUpSUhJLly5lypQphBlYqtXFxYWhQ4cyaNAgXHOYwGTqv//U0q7lywNw+XYQf236mftxERmaNqvZ\nll6thmFnY2+8+xtDcDCsXq2K2hXEz4QQQuSBJBpCCGGOHjyAs2fVPIm8zLvITwMGqERj0iS19K2X\nl8GmKSkpLF++nMmTJxMSEqK3jZOTE4MHD2bo0KG4ubkZN1atFoYMgYsXSduxnX9tQ/j30DK0Wt16\nHHa2DvRt8yaNqpnpnIzffoNfflE9E5JoCCHMnNTREEIIc3T6tBqaVKNG9odOPSk1FTZvNn5cT0pf\n7SouTq12pTeMVJYtW0bbtm355JNP9CYZDg4ODB8+nN27d/Pee+8ZP8kA2L4dzp8nqko5Jt/ZxKaD\nSzIkGeV9qvBRv1/MN8mAx8Pa1qxRyZMQQpgx6dEQQghzdOyY2mZV4VofjUZN+D1yBPbt07uMGpaM\n5gAAIABJREFUK6BWqWrQIPcxglrtauNGmDIF3n4bypYFVIKxevVqJk+ezPXr1/Weamdnx4ABAxg+\nfDjF81L7IzsmT+ZUnRIsGtKQB6HnMhxu26gnXf37mf+k7+eeU/NpLl2C8+dVIiqEEGZKejSEEMIc\n5SXRsLRUFcMBPvlE/yffixera+d1cnCDBtCnDyQlwZQppKamsnz5ctq1a8cHH3ygN8mwtbXl1Vdf\nZffu3Xz22Wf5nmQkX73EUuurzHqtKQ8s0nSOuTi682aPcXRv8ar5JxkA1tbQrZv6es2a7J3z4AH8\n8APs2pV1WyGEMCLp0RBCCHPk6Aje3rlLNEAlEFOmqIfLrVvVylDpbt5UE7kBqlTJe6zffENKy5as\nLlaMyW3bcuPGDb3NbGxs6NOnDyNGjKBkyZJ5v2823Im8ydyVnxHSomKGY9XL1WdAh7dxdXIvkFiM\nJjBQVQpfswY+/jjr9seOqXb16sGJE/kfnxBCPCSJhhBCmKP/+z/49dfcn+/uDh99BGPHql6Ndu3U\nxPInq3936wavv56nMFNSUlh94gSTFy82mGBYW1vTq1cvRo0aRZkyZfJ0v+yKjLnL0Yt72XRwMSk2\nyTrHLC2teKH5AFo37I6lRSHs2O/YUf3dZncZYinUJ4QwEUk0hBDPFo0Guxs3sImMBD8/U0eTubxW\n5h49WiUsR46o+hidO6vkZft2tULUrFm5vkdKSgqrVq1i8uTJ3Lx5U28ba2trevfuzciRI/M9wdBq\ntYRG3ODUlQOcunqQW3ev6m3n6ebDoE7vU76EEXpyTMXZ2eDke70k0RBCmIgkGkKIZ0tSEnV69UJj\nbQ2DB4OVlakjyj9OTmopVK1WfQqenAx//KGOzZoFPj45vmRKSgorV65kypQpmSYYL730EiNGjMjX\nBEOj1RAcelElF1cOcC/6TqbtG1UL4OXWw3Gwc8y3mMySJBpCCBORREMI8WxxcCDFw0P1aISGQgEN\n5TGZvn0ff21rqx46V61S4/xzID3BmDx5Mrdu3dLbxsbGhpdeeok333wT12LOBAUfYdOJBVwJOQuA\nl1tJiruXeLgtibe72jrZu2Q/jtQULt06zakrBzh99RCxD+5neY6ttR0vtX6dJjXaYJHXXqLCJjxc\nVZh3coJatUwdjRDiGSOJhhCi6NNoICoKPD0BSCpVSiUawcFFP9F4mru76snJpuTk5Ec9GFklGC/2\nfYF7ccEsWfkp17XRGdrFJ8QQfOdChv2Ods4Udy+Jl3vJx8mIeym8HiYhSSmJnA0+yqkrBzkbfJTE\n5AdZxm2BBRVLVqdu5aY0qhqAm7NHtt9zkWJpCT/+CLGxRbv3TghhliTREEIUfVOmwNdfw+zZEBhI\ncsmScOaMSjRatDB1dLpSU2HBArXaVN26JgsjKSmJpUuX8scffxis5G1jY0P7zq2p28KXkJiLzNue\ng3kDT3iQFMeNsEvcCLuU4ZiDrSPJacmkpaVmeR0rK2uqlalL3crNqO1aCdeI2LzXCSkMoqPBUJFD\nT0/44IOCjUcIIR6SREMIUbRduaKW9nzwQPVsAEnpS6saKCRnUhcuqB6HihXhqv4JzfkpISGBv//+\nm+nTp3P37l29baysrajXrBo+tWyxcggjKCQs/+LJovfCztaBWhUaUde3GTXKN3w8/+LLL+Grr9SK\nW99+m2/xmVRUFLRpA7dvq2GA0mMhhDAzkmgIIYoujQaGDFFJRr9+0KMHAAm+vsTVqYOzl5eJA9Qj\nL4X68iAuLo4FCxYwa9YsIiIi9LaxtLKkXK1iVG7sjYOLDaCnEOATyt64T+3qz1ErcDDODq6E3w8l\n/H4o96JDn/j6DqlpKTmK1cXBjTq+Tajr24wqZepiY/1Uob3kZJg+XX39ZP2QosbdXQ2JCg+H//4z\nv945IcQzTxINIUTRNXky7N6tVlf67bdHuyO7dCGySxf8zHF52wJONGJiYpg3bx5//vkn9+/rn1ht\naWVBudoeVPbzxsHF1uC1bKxtqVa2HrUrNabWf5dw+3kU+N6CQV+CjQ0ert5UK1dP5xyNVkN0XIT+\nJOT+HVLSVA0MTzcf6vk2o65vMyqUqIqlZSaf3i9fDnfuQO3a0LJljv9MCg0LC1VL4+efVfE+STSE\nEGZGEg0hRNEUFQWffqq+/uOPRxPBzV4BJRr379/nzz//ZO7cucTGxuptY2trQ5na7vg28sLeyUZv\nGzdnT2pX8KN2pcZUKVsHW2s7daB6G5j0u1rtKDQUypXTe76lhSXFXLwo5uJF1bK6c1JUEhIJgLuz\nZ/ZXjEpPKkePznstEnP3ZKLx449F//0KIQoVSTSEEEVTsWKqSN369Y+GTJk9jQaOH1df59Mk5nv3\n7jF79mzmz59PfHy83jaOjo7U9ffF1VeDnWPG/ybKeVemVkWVXJTxqqQ/AbC2hm3boGRJtfJRLqgk\npHjOTjp8GA4eVH///fvn6r6FSvPm4OEBly7B+fNQo8bjYxMnQlAQjBxp/sUphRBFkiQaQoii67nn\n1KuwSEyE119Xk9RzUUwvM3fv3mXGjBksXLiQxMREvW1cXFx4uW9vkjxuEp0UDjxOEKytbOjWvH/O\nlootXdoIkedQxYowfjzY2KjelKLO2hq6dYN9+1TP0ZOJxsqVau7GK6+YLj4hxDNNEg0hhDAXjo7q\nU2gjunXrFtOnT2fp0qUkJyfrbePu7s5rr71G01b1WL5nGglJuis9uToVY2i3sVQoUdWoseWL4sUf\nD5l7VkybBg4OusOmUlIeD8OT3gwhhIlIoiGEeCbZhobCunVQtap6FTGXL19m2rRprFmzhrS0NL1t\nPD09GTZsGP379+fghS0s2P4LWq1Gp015nyoM7Tb22S14Vxg4Ombcd/o0JCVBlSpqaJUQQpiAJBpC\niKLjzh0oUSJbTb2XLIGFC2HCBFVno4g4ffo0U6dO5d9//0Wr1b/8rI+PD2+88QZ9+/bFysaSxdum\ncuT8rgztGldvRd+2I7CxNrzSVI5ERKilZ9PrmIj8c+iQ2jZtato4hBDPNEk0hBBFw6VLUL++qpvx\n669ZFi9LKlVKfREcnP+xFYBDhw4xZcoUdu/ebbBN6dKlGT58OC+99BJ2dnbcj4tg1uoJ3Lh7Waed\nhYUl3Vu8SusGgdlf6SkrGzeqWiYdO8Lixca5pjAsPdFo0sS0cQghnmmSaAghCr+0NFVN+8EDuH8/\nWxWSk9M/VS/EiYZWq2XXrl1MmTKFI0eOGGxXqVIlRowYQWBgIDY2apnaa6EXmL3ue2IeROm0dbB1\nZFCXD6hR3sirXtWqBQkJsGQJvPOO8T9p378fmjXL9QpXRc7338OLL0KdOqaORAjxDJNEQwhR+P3+\nu1p1p0QJ+L//y9YpZpdo7N0La9dC165ZFplLS0vj33//ZerUqQQFBRlsV6tWLUaMGEHHjh2xeiL5\nOnh2G4u3TyMtLVWnvU+xMgx7YSzexfJhtahy5VSC8f338P77qpCisXpLjh5Vq4s1bapWWXpWa0lc\nvAhLl6rCfa1aqdWohBDChCTREEIUbpcuwSefqK9nzMj2xNek9Lkc16+DVmv6h9NNm+Cnn9RypQYS\njZSUFNauXcu0adO4cuWKwUv5+fkxatQoAgICdIY+pWnSWL1nDrtOrMtwTq0Kfvyv0zs42OXjkrAf\nfwyzZqmkas0a49U3+f13tX3uOdP/PZrSihXw+ecwaJBKNIQQwsQk0RBCFG4ff6yG5AwcCC+8kO3T\nNM7O6hNfT09Vv8LBIR+DzIZMKoInJCSwdOlSZs6cye3btw1eomXLlowYMYImesblxyfGMnfDRC7c\nPJnhWDu/XnTz74elZdZDzvLEzQ3GjVMVuz/+GAID8z7U6e5d+PtvlWCMHGmcOAur7t1V0r1unRpO\nmI0hhEIIkZ+yTDQmTJjAypUruXjxInZ2djRr1owJEyZQq1YtnXZffvklM2fOJCoqiqZNmzJlyhRq\n1qyZb4ELIQQAM2eqVYy++Sbn5/7zj/HjyQ2tVg3/AZ1E4/79+/z111/MmzePyMhIvadaWFjQsWNH\nRowYQR0D4/Gv37nIvE0/cy/6js5+Gytb+rUfRaNqAcZ5H9nxxhuqevfo0caZTzFzplrJqls3qFQp\n79crzGrUgMqV4fJlNWfl+edNHZEQ4hmXZaKxa9cuRo0aRePGjdFoNHzxxRe0a9eOs2fPUqxYMQB+\n+OEHfv75Z+bNm0fVqlX5+uuvad++PRcuXMDZ2Tnf34QQ4hnm4QGTJ5s6irwJDVWfzLu5QcWKhISE\nMHv2bBYvXsyDBw/0nmJlZUX37t158803qVy5st42CUkPWLd/AXtPbUSL7lK37s6eDO02lnI++s/N\nNzY2MG+eca6VkqKK1QG89ZZxrlmYWVioXqKff1ZD0yTREEKYWJaJxqZNm3S+nz9/Pm5ubuzfv5+u\nXbui1Wr59ddfGTt2LD179gRg3rx5eHt7s2jRIl5//fX8iVwIIYqK48cBuFS7NtM/+IA1a9aQmpqq\nt6mtrS0vv/wyb7zxBmXKlNHbRqvVcurKAZbvnEl0fMaekIolq/Na149xdXI33nswBa0WvvxSLZ3b\nrp2pozEPnTurRGPSJKNXmRdCiJzK8RyNmJgYNBrNo96Ma9euERYWRocOHR61sbe3JyAggP3790ui\nIYQQWThqbc209u3ZdumSmtCrh4uLCwMGDGDw4MF4eXkZvFZUbDjLds7kzNVDeo83r92BXi2HYWNt\nY5TYTcrWFoYOVS+htGkDn30G1aubOhIhhMh5ojFmzBgaNGiAv78/AHfuqDG/Pj4+Ou28vb0JCQkx\nQohCCFH0aLVaduzYwbRp0zKtgeHl5cWQIUPo168frq6uBttpNGnsOrme9f8tIjklMcNxTzcfXm49\n3Pj1MYR5sbTM3XwlIYTIBzlKNN59913279/P3r17s1Ut1lCbzP5TFQLkZ0RkIjWVSl98QXzt2oT1\n7ZunCcXH9u7Fbe9erOLjude9uxGDNCw1NZV9+/axZs0abt68abBdyZIl6d69OwEBAdjY2HDx4kWD\nbSPiQjlweQMR8aEZjllYWFKrVDPqln2e+PA0joSb178tm/BwSk2fzt2XXiKhWjVTh2N08rtMFAT5\nORP5pUqVKnk6P9uJxjvvvMPSpUvZsWMHFSpUeLS/xMO16MPCwnTGC4eFhT06JoQomuyCg0ktXpy0\nAlz0wfHiRTy2bMHx7FnC+vXL07UsUlLwHTuWNAcH7gUG5msNhoSEBLZv3866deu4d++ewXa+vr70\n6NGDxo0b6xTZ0yclLZmTN3ZxLuRQhsneAF4uZWjm24ViTt55jj+/+CxciNeaNdiFhnJx8uRnuw6G\nEEIUMdlKNMaMGcOyZcvYsWMHVatW1TlWsWJFSpQowebNm2nUqBEAiYmJ7N27l4kGJqL5+fnlMWxR\nVKV/KiM/I4XAf//Byy+rZUXXri24++7eDYB9hw65/jlJ/zlr0Lo1uLlhFR2NX8WKULy40cJMFxYW\nxrx581i4cCExMTEG2z3//PMMHz4cf3//bPUYn7l6mH92ziEqNjzDMXtbR154biDP1emIpYURlpDN\nT//3f7B+Pa6HDuEXEQGdOmV9TlCQWsbVzi7/48sl+V0mCoL8nIn8Fh0dnafzs0w0Ro4cyYIFC1i9\nejVubm6P5mS4uLjg5OSEhYUFb7/9Nt999x3Vq1enSpUqjB8/HhcXF/rl8dNGIYQZ++ILterPP//A\ngwfg6Fgw9921S20NVM/OsQoV4ORJCA42aqJx/vx5Zs2axdq1a0lJSdHbxtLSki5dujB8+PAMtYkM\niY6LZMWuWZy4vF/v8fpVmtOr5VDcnLJXId3kPD3h00/hgw/Uq337zAvNpaaqlZWSklSy+6zXzhBC\nCDOW5Udd06ZNIy4ujrZt21KqVKlHr0mTJj1q8+GHH/LOO+8wcuRIGjduTFhYGJs3b8bJySlfgxdC\nmFBg4OOv9+4tmHtqNLBnj/o6wEhF5sqXV9vr1/N8Ka1Wy549e/jf//5H586dWbFihd4kw9bWlgED\nBrB9+3Z+12io9dFHj5a4NUSj1bDn5Aa+nT9Kb5Lh4eLFG4GfMaTLh4UnyUg3apT6ezhzBubOzbzt\nmjVw8ya4u6skUQghhNnKskdDo9Fk60Ljxo1j3LhxeQ5ICFFIjB6tHvh++gm2b4cnlrjON2fOQFQU\nlC1rvIfM9OsEB+f6EsnJyfzzzz/MmjWL8+fPG2zn7u7OwIEDGThw4OMlav/9F65cge++M3heWloq\ns9f/wJlrhzMcs7SwpFWDF+jc7BXsbOxz/R5Myt4eJkyAgQOzTvh++01tR40yTmVxIYQQ+SbHy9sK\nIcQjPXuq4VNP9m7kp2rVYMcOiIw03qThVq3UMJy6dXN8akxMDIsWLWLu3LmEhYUZbFehQgVee+01\nevXqhYODw+MD9++rJMPODmrU0HuuVqtl+c6ZepOMct6V6dN2BGW9i8DwoT59wM8PMlvh5NQpNUfH\nxQVefbXgYhNCCJErkmgIIXLP31+9CoqdnUoMjKlnT/XKgVu3bjFnzhyWLFlCfHy8wXZ+fn4MHTqU\ndu3a6V9B6sQJta1bF2z0F9DbdWId+878q7PPzsaebs0H8HzdzlhaZr4yVaFhaZl5kgHw++9qO2gQ\nZFJTRAghhHmQREMIIbLp+PHj/Pnnn2zcuJG0tDS9bSwtLenQoQPDhg2jYcOGmV/w2DG1NdAu6NoR\nVu2Zo7PPw8WLt3p/h4er4ergRVbPnnDtGowcaepIhBBCZIMkGiKjxER49101lMFYK/uIoiE8HIoV\nA+tn51dHSkoKmzZt4s8//+REeg+EHg4ODrz00ksMGTKE8ukTzLOSSaJxOzyYuRsnotU+nidnZ+vA\n64GfPZtJBkCXLuolhBCiUHh2nhZE9v32G0ybpl7ajEXAxDNs6FC1FOyiRdC8uamjyVdRUVH8/fff\nzJ8//9Gy3voUL16cQYMG0b9/f9zd3XN2kxkz1KTmpya2x8RHMeOfb0lKSXy0z8LCksGd36dU8Wwm\nMUXB+fNQvbqpoxBCCJFLkmiIjG7cePx1auoz9em1yMSVK6pmho0N+PoW/P0TEuDJidT55OLFi8yZ\nM4dVq1aRlJRksF2VKlUYOnQo3bt3xy63heMcHaFZM51dyalJzFw3IUMhvhcDhlCzQqPc3acwGjoU\nZs9Wk/+NPS9HCCFEgZAnSJFR+uo5P/wgSYZ4bMoU1cP1yivg46N7bP58mDoVxoyBvn2Nf2+tFqpW\nVcO2tm4Fb+9cX+rw+Z2sO/E3TraulK9cGi/3kmi2bWPnkiX8GRbGvlOnMj2/ZcuWDB48mICAgGxV\n8M4JrVbLoi2/c/3ORZ39z9ftQsv63Yx6L7OX3svz/vtw6JAsZSuEEIWQPEWKjM6eVdu2bU0bhzAf\nsbHq02WAt97KePzOHThwAGrWzJ9E4+pVuHVLzR/yyv38hO3HVrN6z1wAouLD+GHB+5TS1uOf6X8R\nnMnqUQ4ODvTq1YtBgwbhm4+9ORsPLubYRd3ih9XL1efFlq/l2z3N1rvvquGbR4+qJHbUKFNHJIQQ\nIock0RAZLV0KQUEG1/UXz6B58yAmBlq00L9CUnpSum2b6n0w8if97Nqlts8/n+trbzmykn/2/QXA\ng+gkrp2M4MaZCFKTM1bZTleqVCn+97//0bdvX9zc3HJ13+w6cn4Xmw4u0dlXwqMsg7t8gFVRWcI2\nJxwdYfx4GDJEFYf09FS9aUIIIQoNSTRERrVqqZcQ6SpWhMaN1dAoferXV8Oarl9Xy49WMnIBufRE\nI5eroP17aCnr9i/k3s04gk/e487VGMhknQM/Pz8GDx5Mhw4dsM6v4YOxsarwHHA15DyLtk7WOezk\n4MrrgZ/iYOeUP/cvDP73P9WbceaMwSWAhRBCmC9JNIQQWevaVb0MrUJmaQmtW8PKlapXw9iJxu7d\napvDREOr1bJyx1zmzp9N8Ml7xEUZntxtYWlBAx9HPp+6gPr16+cl2qwlJqpP6MuXJ+LATmatm0Bq\nWsqjw1ZW1gzt+jHF3UrkbxzmzsoKtm9XFdTLljV1NEIIIXJIEg2RuZQUSEsDe3tTRyLMQWbDltq2\nVYnG4cMwbJjx7nn/vtq6uUGdOtk+7dKlS4z/6XP27TxMWorGYDtbB2vK1/WkQl1P7J1sOHxzAzVr\n1cDWJpcrSWXHmTOQkkKCox0zNv5AXEK0zuF+7UbhW7pm/t2/MHFxedTzI4QQonCRZTyEYZ9+qv6D\nX7jQ1JGIwuDll9XcnunTjXtdd3c1HOvKFfUJdyZSU1PZvHkz/fv3p0OHDuzectBgklG+fHne/mgk\nXd9sSHX/Etg72QBw+uohfl/xGbEP7hv3fTzp2DHSLC2Y92I1QiNu6Bzq2OQlGldvlX/3FkIIIQqI\n9GgIw9zdISlJrfry2jO46o3ImeLF1Su/eHoaPBQREcHSpUtZsGABISEhBttZWVnRuXNnmjRpQvXq\n1WncuDG3w6/xx9rxRMdFPGp3PewSPy/9iOHdv8CnWGmjvg0Ajh1jdfdanHVP09ldv0pzOjeTCc9C\nCCGKBunREI9pNGpsfevWagy5n5/af+SIaeMSpvHgAWSy5Ks5OHXqFO+//z7Nmzfnxx9/NJhk2DvZ\n8OprA9i3bx+///47NWrUeFQDo7RXRd59+QdKFa+gc05EdBi/LP2YK7fPGj3uPbHn2dVSd5nccj5V\nGNB+DJYW8mtZCCFE0SD/o4nHbtxQQ1TOnVNzMtJXeTl1CpKTTRubKHh//AFlysCsWaaOREdSUhIr\nV66kZ8+edO/enRUrVpBs4OezWClH/F+oyrpNa/jys2/webrQYHo7l+KM6f0d1crV09n/IDGWKavG\nZahtkRfngo+zwk93qVx3Z0+GvTA2f+eFCCGEEAVMhk6Jx86dU9v0+hlublClCly6pMbeN2hguthE\nwUpLg99/VxOx81CF25iuXbvGokWLWL58OffvG54/YWllQZnqxahQz5NS5XwY+eJXlPHKehUsBztH\nhgd+zuLt0zh4dtuj/alpKczdOJGo2HDaNOyRp2rgoRE3mbPxJzSWj69ha2PPG4Gf4ebkkevrCiGE\nEOZIEg3x2NOJBkCjRhAeDiEhkmg8S/75B4KD1VC6rl1zdq5WC+fPqzk+JUvmKYyUf/9l6+XLLNy/\nn337DRfWA3B0taVCPU/K1vLA1t4aJwdXRvX8mtJeFbJ9Pysra/q1G4WnqzcbDvytc2zN3nlERIfR\nq9WwLAvoabVaouMjCY24wZ2Im4RGqm1IxHWSUxIftbPAglc7vUtpr4rZjlEIIYQoLCTREI+dfTgW\nveYTy2rOmAHOzsav9CzM22+/qe3o0Vmu9JTBhx/CxInw7bfwySe5uv3t27dZvHgxS6ZMIdxQ7Y6H\nqtSqQLHKFniXd8HiYU+Bi4MbI1/8mlLFy2f/puHh8OuvWACdvv0WD1dvFm2djEbzeML23tObiIq7\nx6DO72NnY49WqyUmPorQiBuERt4gLPImoRE3uRNxg4TkB1nesvvzg6hTqUn2YxRCCCEKEUk0xGMX\nLqjtkz0asn79s+fUKdixQyWYgwfn/PwmDx+ct2/PUaKRlpbG7t27WbhwITt27ECjMVz7ws3Njd69\ne+FULpVrUSd1jrk6FmNUr68p4ZHDAm9pafDdd2p1q2+/pUmN1rg7ezJ73fc6SUPQtSNMWvwBjnbO\nhEbeICEpdxPmm9duT+sGgbk6VwghhCgMJNEQj23dCpcvQ4UKpo5EmJKFBXTrpoZNubll3f5prVur\n7b59avWyLIo9hoeHs2zZMv7++29u3bqVaduGDRvSv39/OnbqyLJdf3Ds4h6d425OHozq9U3ulqT1\n8VGxRkRAXBw4O1O1bF3efvl7/lj9NVFx9x41vRN5M+fXf8jO1oHG1VvRK+C1PM33EEIIIcydJBri\nMTs7qFXL1FHkXmoqTJgAnTpB48amjqbwqlNHzdHIpEchU8WLQ716cPIk7N8PbdpkaKLVajl48CAL\nFy7k33//JSUlxeDlnKyt6dGnD/369aNmzZqkpKYwf/MvnLikO2fD3dmT0b3G4+Wey3khFhZQrhxc\nvAjXrz/6t1DSsxzv9vmR6WvHcyv8arYvZ2djTwmPsurlWY6SnmUpYeFMsdsRWNSrB1by61cIIUTR\nJv/TiaJjwQL44gv48ks1DEbkjWUeVr9u21YlGtu36yQa4eHhrFixgiVLlhAcHJzpJWpYWjLg7l0C\nlyzBuUsXAKJi7/Hn+h+4HnZJp20xFy9G9/qG4m4lch8zqN68ixfVRPgnkm43Zw/e6v0tczf8xNnr\nx3ROsbW2e5hMlKWkZzlKeKitu0vxjDUxFi2C/v2hRw9YtSpvsQohhBBmThINkTWNRg2pio42756C\n//5T2y+/NGkYAujQQQ2dKleOtLQ09u7dy+LFi9m6dSupqakGT7O1taVbt24M6N+f+hs3YrF796Oh\nWJdvBzFn/Y/EJkTrnOPh6s3oXt/g6aq/RkaOpA8b1JME2ds68Hrgp5y8coD7sRF4uZekpGc5irl6\nZb/IXnrxS1nBTQghxDNAEg2Rtb17oWVLVcDv6FFTR2PY3odF1fQM1REFrGNHQurUYfny5SwJCDBY\nsTtdxYoV6d+/P7169cLd3V3tbNgQPv0UrVbL7hPrWLVnjs4KUABe7qUY2fMrPFy9jBP3K6+oJKBV\nK72HLS2taFDludxf/+BBtW3aNPfXEEIIIQoJSTSEEhtreIWpBg3U+PXTpyEpSc3lMDd376rleR0c\nzLvXxZxFRKgVl/IgJSWFHTt2sHjxYnbt2pXpylE2Nja0b9+e/v374+/vr3didHJqEku2TePw+Z0Z\njtWs0Ij/dXoHRzvnPMWso1Urg0lGniUnP07Um8iStkIIIYo+STSEUq0apKSopU2fLrLm4qKOnz+v\nkg0/P9PEmJndu9W2eXOwtTVtLIXRkSPw3HPwxhuPa2jkwPXr11myZAnLly8nPDw807YA7s2HAAAg\nAElEQVS+vr706dOHF198Ec9MEpuImDBmr/tB7wTsTk360KlZn+wPWTIHp06pRL1aNShWzNTRCCGE\nEPlOEg2h5l6EhqreAB8D49wbNVKJxtGj5ploNGoEkyZBmTKmjqRw+u039Yl7DpK0pKQkNm/ezOLF\ni9mfRdVuOzs7unbtSt++ffHz88tyWdcLN04yd+NE4hNjda9j68DADm9T17eQDj164QWoXNnUUQgh\nhBAFQhINAefOqW21aoZXGvLzg4UL1Sffb7xRcLFlV8WK8O67j7+/d0+tQtWlC1Starq4CoM7d2Dx\nYvV3P2pUpk21Wi1nzpxh2bJlrF27lujo6Ezb16xZk759+9K9e3dcXV2zDEWr1bL92BrW7vsLrVZ3\n2JVPsTIMfWFs7mpkmAM/P1i71tRRCCGEEAVGEg2h5jYA1KxpuE3TpuDvr5KRwuDTT2HGDLh1CyZO\nNHU05u2PP9SwuZ49DRZrjIiIYPXq1SxbtowL6RXkDXB2diYwMJA+ffpQJzERi+XLoUQJaN8+0/OS\nUhL5e+tkjl3cm+FYXd9m9G//Fg52jtl+W0IIIYQwLUk0xOMejRo1DLfx91fF1wqLIUNUovHXX6qI\nn42NqSMyT0lJKtEAeOstnUOpqans3LmT5cuXs23btkyXpQVVtbtPnz507doVJycntfP77+Gnn9Tw\nvEwSjfD7ocxe9z0hEdd19ltgQVf/frRr3Kvg5mNMnw6bN8N776k5P0IIIYTIFUk08tPMmVC7tuoN\nyEvxs/wWEwNWVpknGoVNkyaqh+bsWVi3Tn1aLzKKi4Nu3eDMGbWEMXDp0iWWLVvGqlWruHfvXqan\nFytWjB49etCnTx+q6evtattWbbdtM3iNs8FHmbfpZxKS4nX2O9g68mrn96hZoVHO3lNeHT4MK1dC\nu3aSaAghhBB5IIlGfomOhpEjVYXqu3fzvGxovpo+HX7/HbRaU0diPBYW8Npr6lPpP/+URMMQT0+Y\nNYuY6GjW/f03y5Yt48SJE5meYmlpSatWrajvX4M421tYWEWyJWgh/111w9nBFScHV5wdXHF2cMPZ\nxxnnyiVxDr2JU/A1LCtUfHQdjVbDlsMr2PDfIrTo/uyVikzmtXem4eVe8unb57/y5dX2+vXM2wkh\nhBAiU5Jo5JeNG9W495YtzTvJSFdYl4SNiFB1Mzp2hGnTdI8NHAgffQQbNqhVtZ5etvcZl5aWxn//\n/cfy5cvZtGkTSUlJmbb39fWld+/e9OzZk2PBO9l44G+Iz/QUZZSqGWGx5h0c05MQe1dS01K4HnYp\nQ/OGx27xikdz7EyRZECm1cFz7eefwc0NevdWWyGEEOIZIIlGflm9Wm07dYITJ8DRUVY/yg+7d8O1\na2rp3ad5eallW+vXV5ORBQAXLlxg1apVrFmzhjt37mTa1tnZmW7duvHyyy9Tv359tGhZuWs2u0+u\nz/F9tUB8QgzxCTGE6TluYWFJ4Ol42vx1FIuVn+b4+kaTnmgYq0dDo4GvvlJDFDt3lkRDCCHEM0MS\njfyQnKx6NABu31aVtd98E6ZONW1cxrBuHRw6BGPHqrobprZrl9o+nF+QwZtvFlwsZiw8PJy1a9ey\natUqgoKCsmzv7+9P79696dy5Mw4P/57T0lJZuPV3jpzfZfT4nOxdGNT5faq96AmtduVfde7sMHaP\nxvnzKskoWxZKlTLONYUQQohCQBKN/LBzp3qwqF1bFeiaPFlNti0KPv4YgoKga1c1yd3Udu5UW1M+\nmJqpxMREtmzZwsqVK9mzZw9paWmZti9dujS9e/emV69elC1bVudYcmoSczb8RNC1Izr7Heyc6Ndu\nFDbWdsQlRBOXEPPwpb6Of+L7pyd7pyvjVYnXun2Ep+vDYpH9++f+TRtDqVIwZ46qzWIMBw6orTn8\nexFCCCEKkCQa+aFOHTUm291dJRugEg2tVk1SNifnzkHx4mqYUXY0aqQSjaNHTf/gFBkJp06p+SWm\njsVMaDQaDh06xKpVq9iwYQNxcXGZtnd0dKRjx4706tULf39/LPWsjvYgKY6Za7/jSshZnf2ujsV4\ns8c4SntVyFZsaWmpxCXGEPfgcSJia2NHzfINsbIyo19FVlYwaJDxrnfwoNo2a2a8awohhBCFgBn9\n716ElCwJ77yjvtZqoVgxiIpSE5LNbehEr14q2Th+XM1lyIqfn6pNceRI1m3z2/Hj6s+3WTPzGMZl\nQleuXGHlypWsXr2akJCQTNtaAs0TEnixeXM6LliAo6PhIngx8feZtuYrbodf09nv6ebDyJ5fUdwt\n+3NfrKyscXPywM3JI9vnFAnpPRqSaAghhHjGSKKR3ywsVK/Gnj2qV8OcEo2UFLh0ScWY3Ynqfn5q\ne/Ro/sWVXW3bwr17EB6evfbXrqlVqtLfQyF39+5d1q1bx5o1azh16lSW7atVq0bPVq3oPm4cJdLS\n4Jdf1CIFBkTEhDF15ZeER4fq7C/lWZ43e4579hKG3PrqK1XssmFDU0cihBBCFChJNPLRg8Q4zt84\nQYnWTShlZ2d+S8hevgypqWoseiYPnDrq1VPFB4OCICHB9D0Jnp7g6YlWq2X3yfXsObWRNE0qdtb2\n2NraY2djj52NA3bhkdht+Bc7Ty9s04Y93P/wZevw6Gt35+K4OZvvA3R0dDSbNm1i7dq1HDhwAI1G\nk2n74sWL0717d1588UVq1KiBxejRarGCgQMf14vQIzTiBlNXfUl0fKTO/oolq/NG4Gc42jvn7g1o\nNOr+9va6+x88UP8+rIvgr6QePdRLCCGEeMYUwf/VzcODxDgmLf6A8OhQLDwtGTLta+pV9jd1WLrO\nnVPbnFQEd3SETz9Vw8OymFxcUDSaNFbsms2eUxsyb9ji4eTeA39n2qxV/RfoETAYSwvzqOaekJDA\ntm3bWLt2Lbt27SI5OTnT9vb29nTo0IEXX3yR5557Duv0h/e7d2H2bPX1Rx8ZPD/4zkX+WPMNDxJj\ndfbXKN+QIV0/xM7G3sCZWZg+HT7/XBVRfPr+kyfD+PHwzTcwZkzuri+EEEIIsyKJhjElJYGNDVha\n8u+hpY+GnGi1GhZvn4Zv6Vo4O7iaOMgn5CbRAPj6a+PHkkspqcnM//dXTlzeb7Rr7jzxDzEPohjQ\nYQzWVjZGu25OpKSksG/fPtasWcOWLVuIj8+6Mp6/vz89e/akU6dOuLi4ZGxgY6Me8m/ehFq19F7j\n/PUTzFr/PckpiTr7G1Z9ngEd3srbn4erqxrmtn17xkRj926IjTWf4paXL6uEx8MD5s83dTRCCCFE\noSSJhjFNnQo//cS9rz5md+JunUPxCTGs3jOHAR3M6NNaZ2eVZNStq7N786Fl7Dq5HjdnDxpUaYFf\ntecp5pLNVakKUEJSPDPXTeDyLeMvHXzs4l4eJMbxWrePc/8Jfg5pNBqOHDnCP//8w/r164mKisry\nnFq1ahEYGEi3bt0oldX8n2LFVK+BAccv7eevTT+TpknV2d+iTid6txqGpaVVtt6HQW3aqO2ePSop\nt7NT36elqX0AAQF5u4exWFurivLmNKdKCCGEKGQk0TCmNWsgNJR/0i5leFgDOHRuB01qtKZq2bp6\nTjaBMWMyDFM5d/046/5bCEDsg/vcunuVdfvm41u6Jn7VW1K/cvPcj883ouh925l2dTUhkTd09rs5\ne/Jqp3ext3UgKTmRpBT1Sk5JUN//9D3JUfdI6t2DpHJlHh5PICklkdB714l/YrjQ+RsnmLzyC4YH\nfoZTPvVEabVagoKCWLduHf/880+WK0YBVKhQgcDAQAIDA/H19TVKHPvPbGbJ9j/QanXnfHRs8hJd\nmvXDwhjLMvv4qJ6UoCC1ElN6kcWTJ1XdmQoVoFy5vN/HGMqUUcvchobqJkVCCCGEyDZJNIwlIgL2\n7OGab3GOJ9002GzJtml8NOBXbK3N78FFq9Wyfv/CjPvRcvl2EJdvB7Fs5wxqVfDDr1oAtSr6YWNd\n8BPc7964wNTN3xPpoTuB3cejDG92H4eHaya9L+3uwtmz0GoYVKqkcygiJoypq74i/P7jh/3rdy7y\n6/JPGNHjS4q5FDdK/FqtlrNnz7J+/Xo2bNjA9evXszzHx8eHbt26ERgYSJ06dYzz4P/QliMr+Wff\nXxn29wwYQusGgUa7D6BWCgsKUsOn0hON3Q97/wxVdzcFa2soXRr+v717j4uqzv8H/poZGGa4ihdu\ngoJcVbygKIhyv4g3qq0229puu1ttZbdv27e2drPLry23bdu+lV22Wmsru5u3dJCLqKioCAIioiBq\nKiqiyB1mzu+PjwyMchmYgRn19Xw8eMzMmXPOvFnP0nnP5/N5v48eFVPNAgL6f44ffxSVve69V/wQ\nERFdZ5homMvatZB0Oqy6w7BW/nBnN9TWnYEECQBw5sJJaPK+w8IoC3c/7kZRxU4cPX2o13202nbs\nO7wD+w7vgFppjymBUQgPjkWA98QhWTxddeog3v/pBTRclmT4egbjgbTn4aDqZm1CV73c8I1wdsfj\nt76K5T+9hOOnK/Tbq88dx1vfPouHb1oKN9fRA4pbkiSUlpbqk4sjR470eYyzszPmz5+PtLQ0zJw5\nEwqFiVOXLtPa1oK1279A9t7VBtvlMjl+k7wEM8fHm/XzAIhEY/lykZh3OH9eFBmwlmlTHXx9RaJR\nVTWwRCMnR0wJS0oye2hERERXAyYa5vLTTyic7InK4YY3g79JWoKC8m3YWrRBv23Tnh8wLWgOvEb2\nXF50qOl0Wqzb/qXBtjHugZABqKou7/aYptZG7CjZhB0lm+DiOALhwdEID46F10hfs37j3mH/kT34\nZN0ytOpaDLZP9AvHvfP+BKWt6aNETvbDsORXr+Cjta8arP2ovXgG//z2Wfzxhr9ijLtxN50dycX6\n9euxbt06o5ILlUqF5ORkLFq0CDExMbAzdcpOx/qH2Fh9V/qWtmZs3fczMveswsWmCwa72yhsce/8\nP2HSuJmmfW5P5s4VzSsdHDq3LV0K/PnPovStNfH1FcmCEf9u3WJHcCIius4x0TAHSUJ7UyNWpxlW\n8gn1m4Egn0nwcRuHfQe2oq6tHoC4qf86czkeu/VVqymhmn9wK07WdK53kEGGO5KXwHPEGJyuPYHd\nZZux50DOFc3bOlyor0HGnlXI2LMKniPGYHpwDMKDYzDc2c0s8eWVZuHLTe9ApzMsqRs5IRG3JT4E\nhakLlbtQ29njjzf8FSs2vIl9h3fotzc01eH/vn8ef1j0HIJ8JnV7rCRJKCsrw7p167Bu3TpUVlZ2\nu19XSqUSMTExWLBgAZKTk+HQ9SbcVD/8APz618DNN6Ply8+Rs+9nZOavQkNT3RW72inVuH/Rcwj0\nDjXf51/xIXbdr3ewth4zAPCnPwEPPQSEhPT/2NZWID9fPJ85SEkbERGRlWOiYQ4yGba++jDO5nys\n3ySXyZE25y4AgNrOAbdE34dPMt/Wv1958gByizSYMzl1yMMFAGRliW+4p0+H1l6Nn3esNHh7ekgM\nPEeIhblurl6YH3k75kUsxtHqcuwuy0F+SSYutjV2e+qTNUexNve/WJv7X4zzGo8ZIXGYGhjV97Sm\nbkiShMz8Vfhp64or3kuZegMWxNwzKKMntjZK3Dv/T/g6czl2lGzSb29pa8byn17EPan/o++L0pFc\nrF+/HuvXr8fhw4f7PL9SqUR0dDQWLFiAxMREODsPwmJzSQJeew1NdjbYEueHrE/vN1js3pWT/TA8\neMNf4ONmnsXl14RQExKuwkKxiDwkBBg2zHwxERERXUWYaJhBY3M9NuR9Y7AtKjQFHsN99K+nhMYj\n9KOXUezvot+2ettnmDRupmU6UT/3HLB9O5CZiZ2j2g1GKuQyOeZFLL7iEJlMhrEeQRjrEYQbZ9yO\nspmB2B3mhX2R/mhtb7lifwCoOFGKihOl+C77I4z3nYbw4BiEjpth1GJ4naTDqi3/uWINgUwCbi7T\nIuYxMyywPX5cVBjqhkKuwO2JD8NR5YxNe37Qb9dq2/HxumUI907FifJabNy40ahpUba2tvrkIikp\naXCSiy6aNq5Dzoh6ZC2di0ZtOdBNf0U7WxWipyxA4rQbBq2y1nUpL088ctoUERFdx5homIFm13cG\nXZTtlGrMizS8UZfJZLj1hCPKR7ejRSX+Z29ubcT3m/+N+xY8PaTxQpJE5SUAbUEB2LjhRYO3Iycm\nYtQwz15PobB3wARbd0z47x60/OHvKHZXYNeBzThQtRc66cq59lpdO4or8lBckQc7pRpT/CMRHhyL\nIJ9J3fZnaNe24QvN29hzcIvh5ypscNfcJxD2+Oz+/taGmpqAOXNE08KTJwEXl253k8lkSJtzFxzU\nzvgx51Oc+6UBJw+dx6nDdVhTX9Dnx3QkF/Pnz0dycvKgJxcA0NhSj80F65Bd9CWaFnTfjNFOqUbs\nlIWID1vEBGMwPPggEBcnSuQSERFdp5homKjmQjU2F6412JY8/Vdwsr9yuoTr/Juw4MhW/KA6p99W\ncCgXRRV5g7f4tjunTgEXLgCursg9U4ja+rP6txQKG8yd+WvjzjN9OlBQALu9+zD9sccwPTgGFxsv\nYG/5Nuwu24wjJ8u6PayltQl5pVnIK82Cs70rpgXNQXhIrH7aTlt7Cz5Y/QrKjhYaHGenVOMPC//c\n4/qIflGrRafqpibg66+B++/vPtaWFmzbtg2ajduRs6ECF+vq+zy1jY2NfuRiqJILQIysZe9dg80F\na9DU2ggor5xSplLaI3bqQsSFLRrQVDazqasDvvpKVHR69FHAw8NysQwGhaLH7utERETXi6sn0Whp\nEQtGB2E+vinW5P4XWm1nc75hjiMQ11PvgfvuQ4zubuz++n8Nysh+l/UhAr0nQaVUD3a4QmkpAKAl\ndDw0u74zeGvOpFTju4AvWQL89rfAtGn6TU72LoiZMh8xU+bjzPmT2FOWg91lOThd+0u3p6hrrEV2\nwRpkF6yBm+toeDr64/i5ctQ0GC46d7Z3xYM3/gXeo8Z1e54Bue8+IDsb+Phjg0SjoaEBmzdvxsaN\nG5GZmYn6+r6TC4WNAjHR0Zg3bz5SUlLg0sMIial0kg6STgeddOlHp0VLWzO2FW3A5oJ1aG7tft2M\nWmmP2LBFiJu6yCoaLuLtt4G//EU8P3QI+Oab3vcnIiKiq87VkWjs2ye+PX/mGeDlly0djd6RUweR\nf9nUnoVRd/ZaZlUuV2Bx0kN446un9FOMauvPYt32L3Bz7O8HNV69S9OmcqLG4mLjef1mpY0dksNv\nMf48U6b0+vaoYZ5IjbgNc2f+GsdOHxaLyMu2oK6xttv9T9f+0m1CMmqYFx668QWMcHE3PjZj3Hwz\n8MgjQF4eanNzkXnyJDZu3IicnBy0tHS/5qQrha0cbr5O8AxwgZuvM8JCAhAbHYW6lhqcPn4MLa1N\naG5tREtbM5pbG9Hc8bq1Sf+8ua1J/1qra4fuUhIh6bSdyUSX5KK/7O0cERe2CLFTF0JtZ8ZqVqZK\nTOxMNKytf0ZXjz8OrFkDfPqpdcdJRERkha6OROM//wHa24FXXgGefhpwsuCUj0skScKqje8ZbBs9\nyg/hIX13N/YeNQ7x09KQsWeVfltO4XrMCIkzukeDSXx90XTbzcjwasOlPoIAgJipC+HsYP4KOTKZ\nDGPcAzDGPQA3zrkb5ceLsfvAZhQc3o6W1qZejx3jHogH0p6Hk735RwiOnj2L9FmzkF5YiN133gmt\nJPV5jIuLC5KSkjA9cioKqjegqb1ztKO4cheKK3eZPc6BsFc5IT4sDTFTFkBtZ9/3AUMtPLzzeXS0\n5eLoy9mzQEWF+GGiQURE1C9XR6Jx+nTn86++6nE+/VDad3gnKs4fMdh2U/S9RvfFSI1YjL3luThX\nJ343SdLhq4x38dTiN8zaE6JbCxcia+RFNO78Wr9JpbRH4vQbB/dzIUZ0gsdMQfCYKbi1/QEUV+zC\n7rIclB7Jh1bXbrBvyNgw/G7+07DrmFL24ouAj4/oC+HY/+k/kiShuLgYGo0G6enpKCu7tIZEpRIL\n5HswatQozJ07F3PnzkVERARsbW0BAIm1CXhv1VL9v6E1cFA5IX7aDYiZsmDopuINhK0tsHq1aIbX\nx8iYRfn6isf+NO2rrgbc3KxumicREdFQuzoSjU8+Aby8gL//HfjwQ4snGu3aNqy+rK/DRN9wBPlM\nNvocdrYq/Dr+Qbz/00v6bb+cqUT23jWDfsPf0FSHrMtKxiZMu2HIFwcrbewwLWgOpgXNQUNTHQoO\nbUf27vWob6lFZGgiFs66AwrFpUu0vr5z2twtxk/vam1txY4dO5Ceno6MjAycPNl9w8HLeXt7IzU1\nFampqQgLC4NcfmUC6ebqhSdufQ3vrVpq0OxwsMllcsjkcshlnT/OjsMxc3wCYibP60zMrN2iRZaO\noG9jx4pHYxMNrRYIDBTFBg4e7LGaGRER0fXg6kg0lErgpZdER+F77rF0NNhWtNGg74QogXq3cQfv\n2wesXAmEhGDCXXdhelC0QQnXn3d8hakBs8y/HqGLTXt+MJiy5KBy6nkBu7Ha2sS31APkoHbG7Elz\nYdcyAgAQ3nVqDQBs2yZu4mbOFNWielFXV4fNmzcjPT0d2dnZuHix+yZ1lwsODkZycjJSU1MxYcIE\noxoBujgOx2O3vIpvsz5A+S/FsFUoYadUQ6VUQ2WrhsrOHiqlGna2aqiU9pfeE9tUl56L99SwUdhC\nJpNDfimJ6Pq8a3LRo5oa4JvvgdtuM+nfgrroGNGoqjJu/wMHgIsXAVdXJhlERHTd6zPRyMnJwRtv\nvIH8/HycOHECn376Ke6+2/CmeunSpfjoo49QW1uLiIgIvPvuu5gwYYJ5I1WprGIheGNLPTZ0mXIE\nAFETU+A5wqeHIy5z8CDwt78BCxYAd92Fm2J+h/1V+WhqaQAAtLa34JusD/DgDX8ZlI7XFxrOIadw\nvcG2pPCbBz7N5uhRYN488bykxMToerF5s3iM7X4NzC+//IKMjAxs2rQJO3bsQFtbW5+nlMvlmDFj\nBlJSUpCUlIQxY8YMKDR7lSPunvc/AzrWrN55B1i6FEhPB1Zc2UmdBqC/Ixo7d4rHiIhBCYeIiOhq\n0mei0dDQgMmTJ+Puu+/GXXfddcXN7+uvv44333wTK1asQFBQEF566SUkJyejrKwMjgOYR2/t0nd9\nj4auzfnktlc05+tVaKh4LC4GADg7DMONc+7BVxnv6ncprcpH/sGtmB5s/kWymrzv0Nbeqn/t7OCK\n6CnzBn5CDw9RnrStTfRGGKyeEdnZ4jEuDgCg0+lQVFSETZs2ISMjA6WXSvb2Ra1WIyYmBsnJyUhI\nSICrq+vgxDvUGhpEyVhAlO0l8/DzAwoKOhOOvuzYIR7ZEZyIiKjvRGPevHmYd+kb63sum7YkSRLe\neustPPvss7jpppsAACtWrICbmxu+/PJL3G8Fi7bNqaauGpsLDJvzJUXcCmeHftysBgSIqWBVVWKK\nhZMTIicmIe9ANg7/0jki8MPmfyNk7FSzrps4V3caufs2GGybO+NWKG16LsfbJ6USmDwZ2L0b2Lu3\nxxEHkzQ0ALt2oVmhwDatFpuefRYZGRk4c+aMUYePGDECSUlJSE5OxuzZs6FSqcwfo6X9+9/AuXPi\nBpfVkczH1rZ/i9U7Eg2OaBAREcG4Ekk9qKysRHV1NVJSUvTbVCoVYmJikJuba3JwAMS35FZibe4X\naNd2TslxcRiO+LAb+ncSGxtg/Hjx/FI/C5lMhsUJf+xc+AzgYtMFrN76mckxd7Vh59fQorMXw3Cn\nUZgVmmz6iadPF4+7d5t+rsucOXMGK3/8EX9ITUWYnx9+/+ijWLlyZZ9Jhp+fHx544AF899132Llz\nJ1577TUkJib2nmS88QYwYcKg/B79ptOJks7GaG0F/vEP8fyZZ1jtyFLa2wF7e/HTpYklERHR9cqk\nxeCnTp0CALi7Gy5cdnNzw4kTJ0w5dafAQHHjtG+fKBkJiFKku3YBw4YBQUHm+Zw+VJ0qx56yHINt\nC6Pu6LU5X49CQ4HCQjF96tI3n+7DvZESfgt+3rlSv9v2knTMGB+HgNETTYodEM3w8kqzDLalRiyG\njcIMi4bDw4EPPgD27DH5VJIk4ejRo9i+fTsyMjJQWFho1HFyuRzTpk1DYmIikpOT4e/v3/8Pr6gQ\nXdPXrDHs82AJJSVipMjVFRg1qvNn8mRR5rerH38Ejh0TSdLVUMnpWmVjI0Y0WlvFSB8REdF1btCq\nTvW2kHm3kd8Y29TUYOrp02h3cEBBVZVYeAzA/fPP4fP22zi7aBGO/PWvZom3N5IkQVP8ucE2Vwd3\nyBqcjP5dunKaNQt2Y8eibsQItHY5frjcFy7qEbjQVKPf9p91b2LR1D9AITftnyqn7AeDztLOquGQ\nNw4s/sup1WpMBHDxwAGUDeB8ra2tKCkpwZ49e5Cfn2/0lCiVSoUpU6ZgxowZCAsLg/Ol9SG1tbUD\n+r2cQ0IQBKBx5Urst/ANu2N+PoJlMshqa4HaWlFEAMDFykqUXR6bry9cX3sNOpUKF/LzLRDt1csc\n1z9Rb3iN0VDgdUaDJTAw0KTjTbp79fDwAABUV1fD29tbv726ulr/ninsDx0CADR1jGpccj4mBj5v\nvw1XjQbHnngC2kHuFH7s3EFU1xn2SZjum2h0c77LXYyIQHcFVxVyG0T6L8DG4s4pU3VNNdhWvhrT\nfRPhYDewcpm1DdU4cna/wbYpY2IHHP/lmvz9UbBhA9pHjDA+ptpa5OfnY8+ePdi3bx9aWlqMOm7E\niBEIDw9HeHg4Jk6cqG+eZw4Xw8OhtbeH/cGDUJ46hVYzXMN90ung/8wzqJ86FadvuQXSpW/C66dN\nw57t22FTVweb2lrY1NbCtrYWWnU31cEUCtQmJg5+rNc7nQ7opp8KERERdc+kRMPPzw8eHh7QaDSY\nfmmefnNzM7Zu3Yo33nijx+Ou6JHQk0uVhpyiogyPCQ8HEhKgyMxEWEkJ8MgjAy99d28AAB+TSURB\nVP0V+qTVtmPDfz8x2Dah/BzS3HVA0mBMrwnHRZxEbnG6fsuRs/txrPYgZk1MRnL4r+DqNKpfZ/xo\nzasGr73qgZtTf2u2RMMYkiShpKQEmZmZyMjIwL59+4w+dvLkyUhMTERSUhLGjx8/KGV/9VJTgR9+\nwOSqKmDhwsH7nA67dgFZWXA9eBA+//gH11cMkY5v/4z6W7RjB3DzzWJqWnp63/sToZ/XGNEA8Tqj\nwXbhwgWTjjeqvG15eTkAUVK0qqoKBQUFGDFiBHx8fPD444/j1VdfRUhICAIDA/HKK6/AyckJv/nN\nb0wKDIBYlwGIeemXe+ABIDNTrA14+OFBu0HbVqzB6fOd601kOglp3xcAvxlYzwVjpM2+G0UVu3Cx\n8bx+m1bbjq37fsb2kvRLCcfNcHUa2ee5qk4dRFFFnsG2BT4xQ5JkNDU1Ydu2bcjIyEBWVhaqq6uN\nOs7W1hbR0dFITExEYkIC3IdiZKFDWhrwww+ipOlQWLVKPN54I5MMazVsGHDihOj2TUREREbrM9HY\ntWsXEhISAIh1Fy+88AJeeOEF3HPPPfjkk0/w9NNPo6mpCQ8//DBqa2sRGRkJjUYDBwcH06NraAAU\niu4TjRtvFIvDi4uB7duBqCjTP+8yp2t/MVicDQCzdlTBS6ce1PKV9ipHPHjDX/Hxutdwru60wXtd\nE46oiSlICv9VrwnH2u1fGLwe6x6I0NueGJS4AeDEiRPIyspCRkYGcnNzjZ4S5eHhgYSEBIwZMwah\noaGYPXu2eCMpCWhuFuVbQ0IGLW69m24C5swBBrKYfCC6JhpknTp6aBw92vP0qaIi4JdfxN+Fa6U3\nCxERkYn6TDTi4uKg0+l63acj+TC7778XN5k23YSpVALPPScqvAQHm+0jdZIOZUcLsblgLfYfMayi\npJTkmLfhAHDrnSIBGkQ+buPw/F3vIq80G5q8b3DuouECaa22HVv2rUduiabHhKP8eDHKjhpWbVoY\ndadZpx5ptVoUFhYiIyMDmZmZOHDggNHHTpkyBQkJCUhMTMSECRMgk8kMF7Q1NQFbtohmgJdVNhs0\nzs6D13TwcgcPihLHw4YNTv8RMg+1Wnypcfo0cPIkMHr0lft88gnw1lvASy8Bf/nL0MdIRERkhQat\n6pTZ9Nb34NFHzfYxza1NyCvNQk7hOpyu/aXbfRILa+FS12Keb5+3bQOWLRP19ntI0mwUtogKTcbM\n8XH9TjgkScK6XMPRjADvUAT5dDM61E91dXXIyclBZmYmNm/ejHPnzhl1nL29PaKjo5GQkID4+HiM\nGtXHWpOOUqFTp16b3xKvXy8eFy4UjeHIevn6ikTjyJHuEw12BCciIrqC9Scag+zM+ZPYUrgeO/Zn\noLm1scf9gkZPQqJmt7jhNUeFn8ZGYPVqUbq0j9Egw4QjC5q8b3tNOGaHpmD0qHGoOFlqsM/CWXcM\naDRDkiRUVFQgMzMTmZmZ2L17N9qNbCbn7e2tH7WIiIiAnV0/+o5cKgaAuLh+x3xVePRRMdXGHNMM\naXCNHQvk5Ym1GpdraQE6ygrPmDG0cREREVmx6zLRkCRJTI8qXIv9lXsgQepx3zHugYidugBhgbNh\nc4utuKnoz81yT0JDxWNxsWhAaEQCIBKOFMwcH99rwpFTuP6KYyeMnYZxXuONDq+1tRV5eXnIzMxE\nVlYWjhw5YtRxcknCNE9PJNx1FxITExEYGDjwqVqbN4vHa3VakVwOzJpl6SjIGMuXAytWdL8gvLBQ\njLyNHy+mwRERERGA6yzRaGltQt6BbOQUrkP1ueM97ieXKxAWOBuxUxfC1+OyzuPmSDIAwMMDGD4c\nOHdOzPv28jL60MsTjo1536L2Yu9N7hacdwUeegi44w6gY6H1Zc6ePYvs7GxkZGRg69atqK+vNyoe\nZ2dnxMbGIsHGBrH/+hdcZ84E/vhHo3+fbmm1wOHDIgGLiTHtXAOh04lO5zU1ouQtXd966xHDaVNE\nRETdst5EY8sWUbfe2CZwWq0YHZgyRb9JkiQ0tzah9uIZ7NyfgR0lm9DUy/QoJ7ULZk9KxexJc+Hi\nONzU36B3MpkY1cjJEXH3I9Ho0DXh2Lk/E5pd33WbcEwJmAWf/+YCK1eKqR2XEg1JklBaWqpfyF1Y\nWAhJ6nl0p6uAgAAkJCQgISEB06dPh42Njai8889/iht0UykUQFUVcOiQSMiGWm4uEB0NBASIRdss\nPUs9CQkRCTwTUiIiIgPWmWicOSO+xXZwAOrqALkcOp0WjS0NaGi+iIami2horrv0eBENF8+h4YtP\n0YA2NCTEoFHbjPqmOjQ210Or63stgY+bP2KnLkRY4BzY2gzhotyJEzsTjZSUAZ/GRmGL2ZPmImJC\nwhUJh9JWhYWz7gCe+woA0DRuHHIvJRaZmZk4deqUUZ+hVCoRERGB+Ph4JCQkYGxHyc+uxo8XU0sq\nKsRIjakJglwOBAX1vd9giIwUSe6hQ0BZ2dCU1qWrU0qKSf//JSIiulZZZ6JRVCQeJ00C5HKs3/4V\nsvb+hJa25p6PCb008nH6oFEfIZcrMDUgCrFTF8DXI3hwu0335JFHgDvv7FyvYaKuCcfe8m04WXMM\nYYFR0DZI+OLoUWS6uWHbAw8Y3dti5MiR+lGL2bNnw9HRsY8AbMRC+dZWscjdEiMR5mJjAyxYAHz2\nmVi0b85E4+BBMQWvu2SNiIiI6BphnYlGR0fwKVNQcaIUG/K+NtupHdUumD0pBbMnpWKYoxHTslpa\nRHWg+fNF12hzJiQTJpjvXF3IIIdNkwsObt+N9//fEpSWlgIuLuLNPpKMSZMm6ZOL0NBQyLtrTtab\nNWsGGLUVSkvrTDSeftp8533hBTGN7dNPgXvuMd95afDV1YlRO5YjJiIi6pN1JhqFl5rMTZ6M4opd\nJp1KaWMHB5UTRg7zxMzx8ZgWNAe2NkrjT5CdDXz4oeg+fsMNJsUymOrr67FlyxZ9laiamhqjjlOr\n1Zg9ezYSExMRHx8P96FqjHc1SEkRjSFzc8V0vr76fhijpQVYt048j442/Xw0dBISgKwscT2wWhgR\nEVGfrDPR6BjRmDwZ5b+sNnjLxXEEXByGw1HlBHu1ExxUTnBUO8Ne5QSHNRvguOJLOEQnwOFf78FB\n5dS/pOJyFy8Cr78unlthknHs2DFkZGQgIyMDO3fuRFtbm1HHeXl56XtbREZGQtVbU0QLUJeViRGY\ngADLLsJ2cgIee0wkGObqBJ+dLa6rSZMAf3/znJOGRsdUwKoqJhpERERGsM5EY+JEoL4ezSEBOJZ/\nyOCtpxb/HS4OPcz9dw0F1u0C4hcBxkyL6s3x46Jjc2GhuMG47z7TzmcGWq0We/fu1VeJOnjQuPUo\nMpkM06ZN00+JCg4ewjUpv/2t6KgcHS1+Zs7svhdBFz5vvQXs3g38+KN5urCbYtky855v1SrxaOnf\ni/rP11c8dvSU0WqBe+8FwsJEQtrfaYZERETXOOtMND77DABwuHI3dJJOv9nd1bvnJAMAfHzEtAZT\nSRJw220iyQgMFFNd/PxMP29fn9nNzX9dXR1ycnKQmZmJ7Oxs1NbWGnU6JycnREdHIzExEXFxcRhu\niYXZkgSsXy8qUGk0YptSCYSHA19+2e1iaFlrKxw6igFERQ1hsENApwN++kk8v+kmy8ZC/ddxvVZV\nicfSUuDzz0XluCeesFxcREREVso6E41Lyo8XG7wO9DZPdaY+yWTABx8Af/6zWLBrbC+Pgdi0CXjw\nQTEV4/PPAQBHjx41mBLV3t53iV4A8PX1RWJiIhISEhAeHg6l0oRpY+Ygk4kKYlu3ir4oOTni9e7d\nQA9rQZy3b4eipUWMarm5DXHAg6ypSfRb2LMHmDrV0tFQf10+orFzp3iMiLBENERERFbPyhONIoPX\ngT6Thu7DQ0NFtaHB5uwM7eHD2Gtnh4zXX0dGRgbKy8uNOlShUCA8PFyfXIwbN84yZXp74+UF/PrX\n4gcAzp8HSkqA7taF1NQg8KmnxPO4uCELccg4OAB//7ulo6CBGjtWrNXpSPzZEZyIiKhXVptoNLbU\n4/iZSoNtAaMnWiga86uvr0dOTg4yNm5Eto8PzjU2Au+/3+dxLi4uiIuLQ0JCAmJjY+HSUbb2ajFs\nmL4z+RXKyqBVq6FoagJuvXVo4zJGR9d0a0vmaGiEhgLNzaLHCsARDSIioj5YbaJx+Jf9kLqsz/Ac\nMQZO9sP6d5KmJrFgs7dGc3V1wDffAL///QAjNd7x48cNpkS1traKN/qoaOTv768ftZg+fTpsbPrx\nz/af/4jpX/ffL6btWLOoKOzNzISisRFhsbGWjsbQyy8D//438P33Yo0JXX/k8s4F3xcvAsXFop9G\nWJhl4yIiIrJS1pVoXLgg1ilMm4by9gMGb/V7fcannwL/8z+i0dozz3S/z9GjorJUUZFYqHv//QMM\nvHs6nQ6FhYXYtGkTMjIyUFZWZtRxCoUCM2fORGJiIhITE+HbMTd8IPLyxNqIq6XKkY0NtM7Olo7i\nSidPiutlzRomGiQ6u2s0QGVln1XUiIiIrlfWlWgUFABLlgAzZqD8ccPpNYHe/Vyf4eEB1NaKZntP\nP31l6cldu4BFi4DqaiAkBEhKMjF4obm5Gdu2bUN6ejoyMjJw9uxZo45z1moRHxKCxCVLEBsbC2dz\n3Wzv3y8eB6kL+XUjLQ1Yvlys23nxRUtHQ5amVJrtbwYREdG1yroSjUuN+hqmTcKJM0f0m2WQ9X99\nRkqKWLxZWQmkpwNz53a+98MPwJ13iqlVCQnAd98Brq4DDvvs2bPIyspCeno6tmzZgubmZqOO66gS\nlTRjBqZPmwZbc3SevlxpqXgcP978576exMeLKXgFBWJkY8wY4489cUI0fFy8WIyyEREREV0HrDLR\nODTBC5JUo9/sNXIsHNT9/IZfoQD+8Afg+edFqdqORKOtDXjuOZFk3Hef+JZ6AGVgDx8+rB+12LNn\nD6SOhcK9kMvl+ipRiYmJ8B/sztA1NaJZnqOj6DFCA2dnJ66h778X06ceftj4Y1evFiV9R49monG1\nkyTg7Fnx96M/ySYREdF1yCoTjfIRCqDLjKN+T5vqcN99wNKl4kbvxAlRatXWVtworl4tmmwZWUFI\nq9UiPz8f6enp2LRpEyorK/s+CICjoyNiYmKQlJSEuLg4uJowctJvHaMZISGslGQOaWki0TCyI7se\nu4FfO1avFv+OCxYAa9daOhoiIiKrZj2JhlYrFmUDKG8/Y/BWwEAb9Xl6ig7MjY2iupSX16UTBgBP\nPtnn4U1NTdiyZQvS09ORmZmJc+fOGfWxXl5eSExMRHJyMiIiIizXOC8iQvSsaGiwzOdfa371KyA5\nWVxXxrpwAcjMFGuEFi4cvNhoaHR0B+9o2kdEREQ9sp5Eo6UFePppXDx5FCfP/6LfPKD1GV199VWf\n5WO7qqmpQWZmJjQaDbZs2YKWlhajjps4cSKSk5ORlJSECRMmWEfjPFtbLgI3J0fH3ksld+fnn8V0\nvdhYYOTIwYmLhk5HBbiSEmD9emD+fIuGQ0REZM2sJ9GwtweWLsWh8lxg/TL95tFufrBX9fPmrisj\nkoyjR48iPT0dGo0Gu3fvhk6n6/MYW1tbREZGIikpCUlJSfDqGC0xRWOj6JxtjnORddiyRTxy2tS1\nYViXXj6NjZaLg4iI6CpgPYnGJeXHiwxeBw10fUYvJElCSUkJNBoNNBqN0f0tnJ2dER8fj6SkJMTE\nxJivBC0gvh1duFB8Q8q539eOd94BHnigf9OtyLo9/LDoT8PRDCIiol5ZfaIx4IXgl2lra0NeXh40\nGg02bdqEEydOGHXc6NGjkZycjOTkZMyYMQO2trZmiecK48aJijbFxYNzfrIMmQyYPNnSUZA5vfOO\npSMgIiK6KlhVolHXUIvqc8f1r+UyOcZ5DXyNQWNjIzZv3gyNRoPMzEzU1dUZddz48eORkpKClJQU\njB8/fmjWWwQEiDK7VVVi4bqpoyU63ZVNCsk82tuBbdvEQu+0NEtHQ0RERGSVrCrRKD9u+G2+j5s/\n1Hb2/TrH+fPnkZGRgY0bNyInJ8eoxdxyuRwzZ85ESkoKkpOT4e3t3a/PNAsbG9FUr7BQdPOOjDTt\nfF98Icr3PvQQ8NJL5omRhB07gLg4wN9fdJe3hoX/RERERFbGOhKNffuA999H+XTDRd/GlrU9efKk\nfr3Fzp07odVq+zxGpVIhJiYGKSkpiI+Px/DhwwcUulmFhopEo7jY9ESjpEQ07ONNsPnNmgWMGAEc\nPgwcOMCu60RERETdsI5EY9s2YPlylL9+E2DXubm39RmHDx+GRqPBxo0bUVhYaNTHuLq6IikpCcnJ\nyZgzZw7UarWpkZtXaKjoHt3WZtp5KiuB998Xz2fMMD0uMqRQiIZtn30mGrh1l2hkZQEeHmyWSERE\nRNct60g0Cgtx3kWFM3adZWXlcgX8vTpv4CRJQlFRETZu3AiNRoNDhw4ZdWovLy/MnTsXKSkpCA8P\nh42NdfzK3Xr6aeCZZ0w7R2srcNttYv3ADTeIG2Iyv7S0zkTjf//X8D1JEpWmystFEh0VZZkYiYiI\niCzIOu669+1DeYBhM7Mx7gGwUSixY8cOfXJhbKWooKAgpKSkYO7cuZg4caJ1NM8zhjkWb//978Cu\nXaKD8aef8tv0wZKSIhbvb98OnD4NuLl1vldaKpKMESOAmTMtFyMRERGRBVk+0dDpgKIilC8IAABo\n23U4e6weZwsOI2JZBGpqaow6TVhYmD658PPzG8yIrdujjwIHD4pF4K6ulo7m2uXkJEagPD0BOzvD\n91atEo+LFolF/kRERETXIcvfBR05gsaGBmxS2+PghipUV9ShvVUHoLLXw2xsbBAZGYm5c+ciOTkZ\n7u7uQxOvtXNyAlassHQU14eXX+5+e0eiwW7gREREdB2zWKJRV1cnytCuXYvsAH+0ZPc9LUqtViM2\nNhYpKSlISEiAi4vLEERK1A/Hj4upa2o1kJxs6WiIiIiILMYiicbdd9+N3NxctLe397mvk5MTkpKS\nkJqaiujoaOurFGVuLS2ij0ZrKxARYeloqL9sbYEXXgAaGgD7/vWAISIiIrqWWCTRyMnJ6fV9J2cH\nLFyQhtTUVERGRkKpVA5RZFYgJ0csNJ4zB9iype/98/NFedVrPQG7Wri7A0uXWjoKIiIiIouz/BqN\nS9ROtvAIcIFngAuef+gNjPedaumQLCP0UpPC4mJRJrW3qlFHjwJJSaL3RmYmMGrU0MRIV9JqRdUw\nVvkiIiIiAmDhRMPPzw9x8TE41JQLFzc1ZDIZbBS2CPCeYMmwLMvDAxg+HDh3DjhxQiQR3WlrAxYv\nBmprOztVk2U8+yzw8cfA+vVAeLiloyEiIiKyCmZo3NB/Tz75JDQaDTIyMpD8qzkY5m6v73Xh6xkM\nW5vraKrU5WQyw1GNnjz/vOjh4O0tqkyZowcHDcyFC8CZM6J5HxEREREBsFCisWTJEgQGBkL2xRco\n/+RNg/cCvSdZIiTr0pFolJR0//66dcCyZYBCAaxcCYwc2f1+NDTS0sQjEw0iIiIiPYt+DS5tz0W5\ns9ZgW5B3qIWisSJRUWJBuJdX9+///LN4fOUVYPbsoYuLuhcfLx4LC8U0KiIiIiKy7BqNM4eLcSFo\nuP61rUKJMe5BFozIStxxh/jpyf/9H5CaCsyfP3QxUc/s7IBJk4CiIuD8eUtHQ0RERGQVLJdoSBLK\nW08D6Ew0/LxCYGtja7GQrhoyGbBwoaWjoK7WrAE+/RR46ilLR0JERERkFSyXaFRVodzH0WAT12fQ\nVWvsWPbPICIiIurCYms0pMJCHPI3XMTMRIOIiIiI6NpgsUTjdNRU1Lmo9K+VtiqMdQ+wVDjWq70d\nePBB4MABS0dCRERERGQ0iyUaB0/uN3g9zms8FAqraVRueWfOAJ9/DgQHAx98IEqoarV9H0dERERE\nZAUsdmdffrzI4DWnTV2mshK46y7xXC4HPvxQ9M0gIiIiIroKWGREQ5IkHDpu2IwukP0zDE2Y0Pl8\n6VIgLs5SkRARERER9ZtFRjRO1hxFfdMF/Ws7pRo+bv6WCMV6OToCL78M1NQAf/6zpaMhIiIiIuoX\niyQa5VUFBq/9vSZAIee0oCs8/7ylIyAiIiIiGhCLTJ0q37DS4DXXZxARERERXVsskmgcUjYYvOb6\nDCIiIiKia4tFEo1GZefHqu0c4D3KzxJhEBERERHRILFYH40O/qMnQs71GURERERE1xSLJxqBozlt\nioiIiIjoWmP5RMOHiQYRERER0bXGoomGvcoJXiN9LRkCERERERENAosmGgGjJ0Ius/igChERERER\nmZnZ7vLfe+89+Pn5Qa1WIzw8HFu3bu3zGJa1JSIiIiK6Npkl0fj666/x+OOP4/nnn0dBQQGioqIw\nb948HDt2rNfj2KiPiIiIiOjaZJZE480338S9996L3/3udwgODsbbb78NT09PLF++vMdjHNTO8Bjh\nY46PJyIiIiIiK2NyotHa2or8/HykpKQYbE9JSUFubm6PxwWODuX6DCIiIiKia5SNqSc4e/YstFot\n3N3dDba7ubnh1KlTPR6n1Dlj9+7dpn48XaN4bdBQ4HVGg43XGA0FXmc0WAIDA0063mJDCh4uvpb6\naCIiIiIiGmQmj2iMHDkSCoUC1dXVBturq6vh6enZ7THO9q5IjJ4LmUxm6sfTNabjW5nw8HALR0LX\nMl5nNNh4jdFQ4HVGg+3ChQsmHW/yiIZSqcT06dOh0WgMtqenpyMqKqrbYwK8Q5lkEBERERFdw0we\n0QCAJ598Er/97W8xc+ZMREVF4f3338epU6fw4IMPdrs/+2cQEREREV3bZJIkSeY40fLly7Fs2TKc\nPHkSkyZNwj//+U/MmTNH/76pQy9ERERERGQZLi4u/T7GbIlGX5hoEBERERFdnQaSaLCRBRERERER\nmd2QjWgQEREREdH1gyMaRERERERkdkw0iIiIiIjI7JhokEXk5OQgLS0N3t7ekMvlWLFixRX7LF26\nFKNHj4a9vT3i4+Oxf/9+C0RKV6u//e1vmDFjBlxcXODm5oa0tDSUlJRcsR+vMxqod999F1OmTIGL\niwtcXFwQFRWF9evXG+zD64vM7W9/+xvkcjmWLFlisJ3XGg3U0qVLIZfLDX68vLyu2Gcg1xcTDbKI\nhoYGTJ48Gf/617+gVquvaOD4+uuv480338Q777yDXbt2wc3NDcnJyaivr7dQxHS12bx5Mx555BFs\n374dmZmZsLGxQVJSEmpra/X78DojU/j4+GDZsmXYu3cv9uzZg4SEBNx4440oLCwEwOuLzG/Hjh34\n6KOPMHnyZIP/bvJaI1OFhITg1KlT+p+ioiL9eyZdXxKRhTk6OkorVqzQv9bpdJKHh4f06quv6rc1\nNTVJTk5O0gcffGCJEOkaUF9fLykUCmnt2rWSJPE6o8ExfPhw6cMPP+T1RWZ3/vx5yd/fX8rOzpbi\n4uKkJUuWSJLEv2VkuhdeeEEKDQ3t9j1Try+OaJDVqaysRHV1NVJSUvTbVCoVYmJikJuba8HI6GpW\nV1cHnU4HV1dXALzOyLy0Wi1WrlyJ5uZmxMTE8Pois7v//vtx6623IjY2FlKXgqG81sgcKioqMHr0\naIwbNw633347KisrAZh+fdkMWsREA3Tq1CkAgLu7u8F2Nzc3nDhxwhIh0TXgscceQ1hYGGbNmgWA\n1xmZR1FREWbNmoWWlhao1Wp88803CA4O1v8HmNcXmcNHH32EiooKfPnllwBgMG2Kf8vIVJGRkVix\nYgVCQkJQXV2NV155BVFRUSgpKTH5+mKiQVeVy9dyEBnjySefRG5uLrZu3WrUNcTrjIwVEhKCffv2\n4cKFC/j222+xePFiZGVl9XoMry/qj7KyMjz33HPYunUrFAoFAECSJINRjZ7wWiNjpKam6p+HhoZi\n1qxZ8PPzw4oVKxAREdHjccZcX5w6RVbHw8MDAFBdXW2wvbq6Wv8ekbGeeOIJfP3118jMzISvr69+\nO68zMgdbW1uMGzcOYWFhePXVVxEZGYl3330Xnp6eAHh9kem2b9+Os2fPYuLEibC1tYWtrS1ycnLw\n3nvvQalUYuTIkQB4rZH52NvbY+LEiTh06JDJf8uYaJDV8fPzg4eHBzQajX5bc3Mztm7diqioKAtG\nRlebxx57TJ9kBAUFGbzH64wGg1arhU6n4/VFZnPTTTehuLgYhYWFKCwsREFBAcLDw3H77bejoKAA\ngYGBvNbIrJqbm1FaWgpPT0+T/5Ypli5dunQQYyXqVkNDA/bv349Tp07h448/xqRJk+Di4oK2tja4\nuLhAq9XitddeQ3BwMLRaLZ588klUV1fjww8/hFKptHT4dBV4+OGH8dlnn+Hbb7+Ft7c36uvrUV9f\nD5lMBqVSCZlMxuuMTPLMM89ApVJBp9Ph2LFjeOutt/Dll19i2bJl8Pf35/VFZqFSqTBq1Cj9j5ub\nG7744guMHTsWd999N/+Wkcmeeuop/d+ygwcP4pFHHkFFRQU++OAD0+/JzFMYi6h/srKyJJlMJslk\nMkkul+uf33vvvfp9li5dKnl6ekoqlUqKi4uTSkpKLBgxXW0uv7Y6fl588UWD/Xid0UDdc8890tix\nYyU7OzvJzc1NSk5OljQajcE+vL5oMHQtb9uB1xoN1OLFiyUvLy9JqVRKo0ePlm655RaptLTUYJ+B\nXl8ySTJiNREREREREVE/cI0GERERERGZHRMNIiIiIiIyOyYaRERERERkdkw0iIiIiIjI7JhoEBER\nERGR2THRICIiIiIis2OiQUREREREZsdEg4iIiIiIzI6JBhERERERmd3/Bw4PT5PAGW09AAAAAElF\nTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e794bef0>"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This output is fantastic!. Two things are very apparent to me in this chart. First, the RTS output is much, much smoother than the KF output. Second, it is almost always more accurate than the KF output (we will examine this claim in detail in the **Smoothing** chapter).\n",
      "\n",
      "While you can usually find isolated sections where the KF produces a more accurate estimate than the RTS smoother, the RTS almost always significantly outperforms the KF. If you are able to batch process your data, there is no reason to not use the RTS algorithm.\n",
      "\n",
      "We cannot always wait to collect all of our data before we filter it. If so, that means that we cannot use the RTS filter, but we may still have options. The **Smoothing** chapter discusses various strategies that you can use, and it is a mandatory (and easy) chapter if you want to achieve the best possible results from your filtering.\n",
      "\n",
      "Let's wrap this up by looking at the velocity estimates of the two filters."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dog = DogSensor(velocity=1, noise_var=40.)\n",
      "f = dog_tracking_filter(R=3., Q=.2, cov=P)\n",
      "count = 50\n",
      "seed(8923)\n",
      "zs = [dog.sense() for t in range(count)]\n",
      "Xs, Covs, _, _ = f.batch_filter(zs)\n",
      "Ms, Ps, _ = f.rts_smoother(Xs, Covs)\n",
      "bp.plot_filter(Xs[:,1])\n",
      "plt.plot(Ms[:,1], label='RTS')\n",
      "plt.legend(loc='best')\n",
      "plt.gca().axhline(1, c='k')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAxsAAAGNCAYAAAB5fmy+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAD4BGEDAAAAgE8QNgAAAAD4xP8HzaL7AzjGRtoAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e7749ac8>"
       ]
      }
     ],
     "prompt_number": 60
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The improvement in the velocity, which is an unobserved variable, is even more dramatic. \n",
      "\n",
      "Since we are plotting velocies let's look at what the the 'raw' velocity is, which we can compute by subtracting subsequent measurements. We see below that the noise swamps the signal, causing the computed values to be essentially worthless. I show this to reiterate the importance of using Kalman filters to compute velocities, accelerations, and even higher order values. I use a Kalman filter even when my measurements are so accurate that I am willing to use them unfiltered if I am also interested in the velocities and/or accelerations. Even a very small error in a measurement gets magnified when computing velocities. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dx = np.diff(zs, axis=0)\n",
      "plt.plot(Xs[:,1], label='Filter')\n",
      "plt.plot(Ms[:,1], label='RTS')\n",
      "plt.plot(range(1,count), dx, c='r',ls='--', lw=2, label='Raw velocity')\n",
      "plt.legend(loc='best')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAGNCAYAAADghrULAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niOzmfzOCSgEjdPpvAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f85e794bf28>"
       ]
      }
     ],
     "prompt_number": 61
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Walking Through the KalmanFilter Code (Optional)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "** author's note: this code is somewhat old. This section needs to be edited; I would not pay a lot of attention to it right now. **\n",
      "\n",
      "The kalman filter code that we are using is implemented in my Python library `FilterPy`. If you are interested in the full implementation of the filter you should look in `filterpy\\kalman\\kalman_filter.py`. In the following I will present a simplified implementation of the same code. The code in the library handles issues that are beyond the scope of this chapter, such as numerical stability and support for the extended Kalman filter, subject of a later chapter. \n",
      "\n",
      "The code is implemented as the class `KalmanFilter`. Some Python programmers are not a fan of object oriented (OO) Python, and eschew classes. I do not intend to enter into that battle other than to say that I have often seen OO abused. Here I use the class to encapsulate the data that is pertinent to the filter so that you do not have to store and pass around a half dozen variables everywhere.\n",
      "\n",
      "The method `__init__()` is used by Python to create the object. Here is the method \n",
      "\n",
      "    def __init__(self, dim_x, dim_z):\n",
      "        \"\"\" Create a Kalman filter. You are responsible for setting the \n",
      "        various state variables to reasonable values; the defaults below will\n",
      "        not give you a functional filter.\n",
      "        \n",
      "        Parameters\n",
      "        ----------\n",
      "        dim_x : int\n",
      "            Number of state variables for the Kalman filter. For example, if\n",
      "            you are tracking the position and velocity of an object in two\n",
      "            dimensions, dim_x would be 4.\n",
      "            \n",
      "            This is used to set the default size of P, Q, and u\n",
      "           \n",
      "        dim_z : int\n",
      "            Number of of measurement inputs. For example, if the sensor\n",
      "            provides you with position in (x,y), dim_z would be 2.            \n",
      "        \"\"\"\n",
      "        \n",
      "        self.dim_x = dim_x\n",
      "        self.dim_z = dim_z\n",
      "\n",
      "        self.x = np.zeros((dim_x,1)) # state\n",
      "        self.P = np.eye(dim_x)       # uncertainty covariance\n",
      "        self.Q = np.eye(dim_x)       # process uncertainty\n",
      "        self.u = 0                   # control input vector\n",
      "        self.B = np.zeros((dim_x,1))\n",
      "        self.F = 0                   # state transition matrix\n",
      "        self.H = 0                   # Measurement function\n",
      "        self.R = np.eye(dim_z)       # state uncertainty\n",
      "\n",
      "        # identity matrix. Do not alter this.\n",
      "        self._I = np.eye(dim_x)\n",
      "\n",
      "More than anything this method exists to document for you what the variable names are in the filter. To do anything useful with this filter you will have to modify most of these values. Some are set to useful values. For example, `R` is set to an identity matrix; if you want the diagonals of `R` to be 10. you may write (as we did earlier in this chapter) `my_filter.R += 10.`.\n",
      "\n",
      "The names used for each variable matches the math symbology used in this chapter. Thus, `self.P` is the covariance matrix, `self.x` is the state, and so on.\n",
      "\n",
      "The predict function implements the predict step of the Kalman equations, which are \n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{x}^- &= \\mathbf{F x} + \\mathbf{B u} \\\\\n",
      "\\mathbf{P}^- &= \\mathbf{FP{F}}^\\mathsf{T} + \\mathbf{Q} \n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "The corresponding code is\n",
      "\n",
      "    def predict(self):        \n",
      "        self.x = self.F.dot(self.x) + self.B.dot(self.u)\n",
      "        self.P = self.F.dot(self.P).dot(self.F.T) + self.Q\n",
      "\n",
      "I haven't discussed the use of numpy much until now, but this method illustrates the power of that package. We use numpy's `array` class to store our data and perform the linear algebra for our filters. `array` implements matrix multiplication using the `.dot()` method; if you use `*` you will get element-wise multiplication. As a heavy user of linear algebra this design is somewhat distressing as I use matrix multiplication far more often than element-wise multiplication. However, this design is due to historical developments in the library and we must live with it. The Python community has recognized this problem, and in Python 3.5 we will have the `@` operator to implement matrix multiplication. \n",
      "\n",
      "With that in mind, the Python code `self.F.dot(self.x)` implements the math expression $\\mathbf{F x}$.\n",
      "\n",
      "Numpy's `array` implements matrix transposition by using the `.T` property. Therefore, `F.T` is the python implementation of $\\mathbf{F}^\\mathsf{T}$.\n",
      "\n",
      "The `update()` method implements the update equations of the Kalman filter, which are\n",
      "\n",
      "$$\n",
      "\\begin{aligned}\n",
      "\\mathbf{y} &= \\mathbf{z} - \\mathbf{H}\\mathbf{x^-} \\\\\n",
      "\\mathbf{K} &= \\mathbf{P} \\mathbf{H}^\\mathsf{T} (\\mathbf{H} \\mathbf{P^-} \\mathbf{H}^\\mathsf{T} +\\mathbf{R})^{-1} \\\\\n",
      "\\mathbf{x} &= \\mathbf{x}^- + \\mathbf{K} \\mathbf{y} \\\\\n",
      "\\mathbf{P} &= (\\mathbf{I} - \\mathbf{K} \\mathbf{H})\\mathbf{P^-}\n",
      "\\end{aligned}\n",
      "$$\n",
      "\n",
      "The corresponding code is:\n",
      "\n",
      "    def update(self, Z, R=None):\n",
      "        \"\"\"\n",
      "        Add a new measurement (Z) to the kalman filter. If Z is None, nothing\n",
      "        is changed.\n",
      "\n",
      "        Optionally provide R to override the measurement noise for this\n",
      "        one call, otherwise  self.R will be used.\n",
      "\n",
      "        self.residual, self.S, and self.K are stored in case you want to\n",
      "        inspect these variables. Strictly speaking they are not part of the\n",
      "        output of the Kalman filter, however, it is often useful to know\n",
      "        what these values are in various scenarios.\n",
      "        \"\"\"\n",
      "\n",
      "        if Z is None:\n",
      "            return\n",
      "\n",
      "        if R is None:\n",
      "            R = self.R\n",
      "        elif np.isscalar(R):\n",
      "            R = np.eye(self.dim_z) * R\n",
      "\n",
      "        # error (residual) between measurement and prediction\n",
      "        self.residual = Z - self.H.dot(self.x)\n",
      "\n",
      "        # project system uncertainty into measurement space\n",
      "        self.S = self.H.dot(self.P).dot(self.H.T) + R\n",
      "\n",
      "        # map system uncertainty into kalman gain\n",
      "        self.K = self.P.dot(self.H.T).dot(linalg.inv(self.S))\n",
      "\n",
      "        # predict new x with residual scaled by the kalman gain\n",
      "        self.x += self.K.dot(self.residual)\n",
      "\n",
      "        KH = self.K.dot(self.H)\n",
      "        I_KH = self._I - KH\n",
      "        self.P = (I_KH.dot(self.P.dot(I_KH.T)) +\n",
      "                 self.K.dot(self.R.dot(self.K.T)))\n",
      "\n",
      "There are a few more complications in this piece of code compared to `predict()` but it should still be quite clear. \n",
      "\n",
      "The first complication are the lines:\n",
      "\n",
      "        if Z is None:\n",
      "            return\n",
      "            \n",
      "This just lets you deal with missing data in a natural way. It is typical to use `None` to indicate the absence of data. If there is no data for an update we skip the update equations. This bit of code means you can write something like:\n",
      "\n",
      "    z = read_sensor()    # may return None if no data\n",
      "    my_kf.update(z)\n",
      "    \n",
      "instead of:\n",
      "    z = read_sensor()\n",
      "    if z is not None:\n",
      "        my_kf.update(z)\n",
      "        \n",
      "Reasonable people will argue whether my choice is cleaner, or obscures the fact that we do not update if the measurement is `None`. Having written a lot of avionics code my proclivity is always to do the safe thing. If we pass 'None' into the function I do not want an exception to occur; instead, I want the reasonable thing to happen, which is to just return without doing anything. If you feel that my choice obscures that fact, go ahead and write the explicit `if` statement prior to calling `update()` and get the best of both worlds.\n",
      "\n",
      "The next bit of code lets you optionally pass in a value to override `R`. It is common for the sensor noise to vary over time; if it does you can pass in the value as the optional parameter `R`.\n",
      "\n",
      "        if R is None:\n",
      "            R = self.R\n",
      "        elif np.isscalar(R):\n",
      "            R = np.eye(self.dim_z) * R\n",
      "            \n",
      "This code will use self.R if you do not provide a value for `R`. If you did provide a value, it will check if you provided a scalar (number); if so it constructs a matrix of the correct dimension for you. Otherwise it assumes that you passed in a matrix of the correct dimension.\n",
      "\n",
      "The rest of the code implements the Kalman filter equations, with one exception. Instead of implementing \n",
      "\n",
      "$$\\mathbf{P} = (\\mathbf{I} - \\mathbf{KH})\\mathbf{P}^-$$\n",
      "\n",
      "it implements the somewhat more complicated form \n",
      "\n",
      "$$\\mathbf{P} = (\\mathbf{I} - \\mathbf{KH})\\mathbf{P}^-(\\mathbf{I} - \\mathbf{KRK})^\\mathsf{T} + \\mathbf{KRK}^\\mathsf{T}$$.\n",
      "\n",
      "The reason for this altered equation is that it is more numerically stable than the former equation, at the cost of being a bit more expensive to compute. It is not always possible to find the optimal value for $\\text{K}$, in which case the former equation will not produce good results because it assumes optimality. The longer reformulation used in the code is derived from more general math that does not assume optimality, and hence provides good results for non-optimal filters (such as when we can not correctly model our measurement error).\n",
      "\n",
      "Various texts differ as to whether this form of the equation should always be used, or only used when you know you need it. I choose to expend a bit more processing power to ensure stability; if your hardware is very constrained and you are able to prove that the simpler equation is correct for your problem then you might choose to use it instead. Personally, I find that a risky approach and do not recommend it to non-experts. Brown's *Introduction to Random Signals and Applied Kalman Filtering* [3] discusses this issue in some detail, if you are interested."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "References"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "- [1] http://docs.scipy.org/doc/scipy/reference/tutorial/stats.htmly\n",
      "\n",
      "- [2] https://en.wikipedia.org/wiki/Kalman_filter\n",
      "\n",
      "- [3] Brown, Robert Grover. *Introduction to Random Signals and Applied Kalman Filtering* John Wiley & Sons, Inc. 2012\n",
      "\n",
      "- [4] `FilterPy` library. Roger Labbe.\n",
      "https://github.com/rlabbe/filterpy"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}