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sethi_pls_colab_solution.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
},
"colab": {
"name": "sethi_pls_colab_solution.ipynb",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/gmcn42/5f6e98af7944492c5a4359790a428082/sethi_pls_colab_solution.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "cpTYtYRo85r-",
"colab_type": "text"
},
"source": [
"# Physical Layer Security on Fieldbus Systems - Signal Analysis Workshop\n",
"## (Sample solution - Google Colab version)\n",
"\n",
"Hello everyone!\n",
"\n",
"Sadly, we can't do any hands-on electrical stuff over Zoom, so we will have to make do with a bit of data analysis. We will use Python for this. If you don't have any experience with it, that's no biggie. It is rather intuitive and many helpful libraries exist for our topic. \n",
"\n",
"Essentially, we will first look at some KNX signals I captured and try to understand how that waveform is actually represented by digital data. Afterwards we will try to retrace the signal analysis steps we took for the method we called \"Passive Waveform Fingerprinting\". That would be the one which yielded the nice point cloud pictures. Luckily, I managed to take some measurements from a couple more devices (5 to be exact). So with any luck the picture should look more interesting in the end. ;)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "OjwRVcis85sB",
"colab_type": "text"
},
"source": [
"## What's up with this IPython Notebook thing here?\n",
"\n",
"As you might have noticed, this is an interactive webpage called an IPython notebook running inside Google Colab. The awesome thing about that is: You can write Python programs within it and they will work.\n",
"\n",
"Here let me demonstrate:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "XjiZxvCY85sE",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"outputId": "a0bf309d-8ba1-4d9f-b278-79cafe72e7c6"
},
"source": [
"print(\"Hello, World!\")"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": [
"Hello, World!\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "-URoTDdB85sV",
"colab_type": "text"
},
"source": [
"If you click the cell above and then click \"Run\" in the toolbar on top, Jupyter will execute a timeless classic of computer programming for you. Yay!\n",
"\n",
"Now of course printing single strings is a bit lame, I agree. So lets instead print **multiple** strings **to a file**!"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Rq8UYzBy85sY",
"colab_type": "code",
"colab": {}
},
"source": [
"with open(\"spam.txt\", 'w') as spamfile:\n",
" spamfile.write(100*\"SPAM \" + \"\\n\")"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "0QhEKyhg85si",
"colab_type": "text"
},
"source": [
"So, did that work?? Lets read the file and check:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "yQk_zmbM85sk",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 72
},
"outputId": "d1d5b47c-5909-4c6a-e833-a16706a7b63e"
},
"source": [
"with open(\"spam.txt\") as spamfile:\n",
" print(spamfile.readline())"
],
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"text": [
"SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM SPAM \n",
"\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "y0m3-msa85sr",
"colab_type": "text"
},
"source": [
"\n",
"Seriously though, this example has revealed two peculiarities of Python if you only know other programming languages:\n",
"* Instead of using parentheses for code blocks, Python uses indentation. Some may find this weird but in any case it forces programmers to use clean formatting\n",
"* You can intuitively do addition and multiplication with strings, whoa!\n",
"\n",
"Well, of course you can also do all the other numerical operations on -- well -- numbers:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "3SnuR3_D85su",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 88
},
"outputId": "c7513efa-ee52-434e-e468-6156e1f7cfb7"
},
"source": [
"print(10+5*6) #Addition and Multiplication\n",
"print(2**10) #Exponents\n",
"print(6/5) #Float division\n",
"print(6//5) #Integer division\n",
"# etc. etc. etc...."
],
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": [
"40\n",
"1024\n",
"1.2\n",
"1\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "U0wrjmtt85s2",
"colab_type": "text"
},
"source": [
"Variables work mostly like in other programming languages:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "r26UHg5b85s5",
"colab_type": "code",
"colab": {}
},
"source": [
"a = 10\n",
"b = 20"
],
"execution_count": 5,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "FVt4ww1i85tC",
"colab_type": "text"
},
"source": [
"...and they are persistent in this document. Meaning, if you have run the cell above, the cell below will work too:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "D5IYqaK885tE",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"outputId": "01a51ec9-b554-466d-88ae-4e60abd452b5"
},
"source": [
"import math\n",
"print( math.sqrt(a**2+b**2) )"
],
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"text": [
"22.360679774997898\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "i9h-3Q7x85tK",
"colab_type": "text"
},
"source": [
"Note, that I have just imported the ``math`` module to get the ``sqrt()`` function. Python modules are similar to libraries in C/C++ & friends.\n",
"\n",
"As you can see, Jupyter Notebooks can make for a pretty good persistent calculator sheet with all kinds of functionality. In fact we can even output some graphical stuff in this document.\n",
"Let's plot some functions:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "4Nl_4Cu885tK",
"colab_type": "code",
"colab": {}
},
"source": [
"## We need a couple libraries for this, let's import them\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"## To show plots in this document instead of a window we can't see\n",
"%matplotlib inline "
],
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "--VgvaUi85tT",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 295
},
"outputId": "eb72c938-c0dc-426c-9d3d-ed684d8d3285"
},
"source": [
"x = np.arange(0,4*np.pi,0.1) # make an array with x data points\n",
"y = np.sin(x) # The y-array for sin(x)\n",
"plt.plot(x,y)\n",
"## We can also make the plot look nicer by including axes labels\n",
"plt.xlabel('x values from 0 to 4pi')\n",
"plt.ylabel('sin(x)')\n",
"plt.title('Plot of sin from 0 to 4pi')\n",
"plt.legend(['sin(x)'])\n",
"plt.show()"
],
"execution_count": 8,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "WvdJLA9y85tZ",
"colab_type": "text"
},
"source": [
"Admittedly, this program was a bit longer than what we have seen before but there is nothing crazy about it. We calculate a couple of data points (as matplotlib likes discrete values) and just let it draw lines over them. The arrays x and y together are essentially a sine table with an x-resolution of 0.1 per sample.\n",
"\n",
"Now...... let's do your first **exercise**! Exciting!\n",
"\n",
"Remember my presentation? No? Well no problem... During the first part, I had plotted a somewhat more complex function to show why a high enough sample rate is important for digital measurements.\n",
"\n",
"The function was $f(x)=4\\cdot \\left(\\sin\\left(\\frac{2\\pi x}{23}\\right)+\\sin\\left(\\frac{6\\pi x}{23}-1\\right)\\right) + 0.5 \\cdot \\sin(10x)$ plotted in the range $0\\le x\\le23$\n",
"\n",
"Try to write a program that plots this function in the cell below. A good starting point is to copy the last program. It should be possible to solve this exercise just by modifying that code."
]
},
{
"cell_type": "code",
"metadata": {
"id": "xeeh_pR985ta",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 295
},
"outputId": "020b1c64-aac6-4e9e-858d-73fed86cdf5d"
},
"source": [
"x = np.arange(0,23,0.1) # make an array with x data points\n",
"y = 4*(np.sin(2*np.pi*x/23)+np.sin(6*np.pi*x/23-1)) + 0.5 * np.sin(10*x) # The y-array for my cool function\n",
"plt.plot(x,y)\n",
"## We can also make the plot look nicer by including axes labels\n",
"plt.xlabel('x values from 0 to 23')\n",
"plt.ylabel('f(x)')\n",
"plt.title('The plot from my presentation')\n",
"plt.show()"
],
"execution_count": 9,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "yWNc3SBm85ti",
"colab_type": "text"
},
"source": [
"## Loading the data\n",
"\n",
"Now that we are all experts on plotting stuff, let's see how we can get the data which we'd actually like to look at into this document.\n",
"\n",
"You'll need to import the data into this Colab runtime to do any operations on it. To do that, just run the code cell below which will grab the data from our server and unpack it."
]
},
{
"cell_type": "code",
"metadata": {
"id": "7M7TuUtEPz-n",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 70
},
"outputId": "2feeca62-13e8-4ff1-9859-fbf5b012c29e"
},
"source": [
"!curl -o workshop-physec.zip https://iukwebsrv.informatik.uni-rostock.de/nextcloud/index.php/s/XdSYpRD75yk3nN5/download\n",
"!unzip -qo workshop-physec.zip"
],
"execution_count": 10,
"outputs": [
{
"output_type": "stream",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 46.6M 100 46.6M 0 0 9779k 0 0:00:04 0:00:04 --:--:-- 9779k\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "GoN_0vbFABfl",
"colab_type": "text"
},
"source": [
"The data is stored in CSV-files which now reside in ``workshop-physec/msmts-passive/``. Thankfully the NumPy library has a handy function that will read in a file at a time and generate a 2D-vector from the data."
]
},
{
"cell_type": "code",
"metadata": {
"id": "9e516E-Y85tj",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 279
},
"outputId": "cbd24696-56b4-4235-e26f-14c2ba07e6c2"
},
"source": [
"amplitude_signal = np.genfromtxt(\"workshop-physec/msmts-passive/switch-a_1_1_4-1.csv\", delimiter=',', skip_header=1)\n",
"plt.plot(amplitude_signal[:,0],amplitude_signal[:,1])\n",
"plt.xlabel('Time (µs)')\n",
"plt.ylabel('Voltage (V)')\n",
"plt.show()"
],
"execution_count": 11,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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lfwxKGbTBIyRnRyOb6mLZcVct4zdLZ+2NOfQODGG/Q8CyYom/1lMvSiDkshmMbKrDpl32+kuzJDdtXBsA4K4YYuOPFIaaHs4IQ8d6/2JXx/Q8jLMgiWfoCN1SLIgzCWZ1b+CRzbWuTMoY0y31OdTWZERWPXkjCId5Ejfyc5+8dyWFxaweg0PsrOY1zf3O5lps2dMbeSKmqmX8BoxDM8BZSjN3fkeTljjFaVCbO3VMWx02eAxoAnD+sQcBAM48crQa8QGgo6kO2wQRR4czgrLlt75BVy9X/a/hGyLZdRW8d4OhV1KfeVh0Ntd506lvWvsGhvCH+d4JaUa1aOqgpEv8nc11ovdOKPSplyRvlO0dGBKFcQ4SVc/4AQHj1/8SKC8dvrLB/uDKHHVxdEu9KCnHlC7NqnVMq7dONCiYPUL7B+VZoIYbRMzMJ/Z5ZJYiIozW+9xpnJgZr8ruQALjHErE0HRVk8q7cj/g1B6ss1lTiSad8Y9sct/tmGEEwHPqJ3OfxrXwpYwfhXg9boe2gDb4T9QPrtzi2OcZf1u9qENrazJoa8jFMvjzUl+VWfYULDACdJ7TJ/SHjx8PAI6qQzNGNtWiPpfBm9udD1gBTToc06YxFK9dpAQMIJvRxp10B7F1bx827urFgENQPzNDO++YsZjU2eRaHwGoyWYwsqkWmxNq0mnemUkXvU5d4vc6DzGrujYKBMQgkTJ+FLwS/75mi+3vZjXIwSO1wexkBWTe3I9prce2vX3oHbBhABYtwOjWeOyZ8xmGKsBtPgyMCMGHwkjB6CYcFNSHhIPaG/DWDnfGDwBj2hoAyFI7SkDQJVmhqmevvit8w2WRMswTRrfUi/X2DbVZ3DVPnqc4Doxs8lb1GO9qlL6L2yh4/oP0Pl2o+z5Ehapl/Ga+a4SoveOZVz3LGuZnzltzBunD31DduHkm5ncHrTK1UNAoxHmvNolf+9sujCSpAmM8eVrq6H+7XNRN5rHXXFeD5roarA9inHBxVjlvED550iQAhQXADVv39mJv36Aj8zM/1xvbtIVEktc2auQj8zZ5G3UA2kLeUleDxtosNuz0VvWM0U1ev//wK4HQK0XVMn4DRBrTbamrwdlHjbEvZDrcba3PocVj8hnMPL+NE6z840c0Yp3AxT04FLIlAZURGjcMBCnxGwf7Iz10vFZ0ttR5HjAbDlRj2oITEFRj5RiHlpKd6QndHQDgqsIii/Xygf5kOnEBamdhRIQxrfWCeU+oz2kZvt6vG3hEhapn/AYOH9viyMzNdvwAXLfmZnnAOLhb+lZpJi6r3PDia9uxc38/VkbsvWscbFer964REjtIq6Yuw6pDyFDHtNZj/c79IhrGttVj3rptZdFnxkihDwtQMEJYt8VbQDn+YC2zqkToqQSs159j2Vu7HMuY39Wo1jrxsx82ugW9/dHmvk4Zv46xbQ3OjN9kxw8AB7XX420nxm+au+NHaPq7Ay7u6IZa6Pzp2ooftRffiKZa1GYz2JjQw7WwYHRTR1NOC1sgSJwiRYduffPjR1cKKNCY+YH+IdEhc202E0jGNKN1I2SAl1OY5pSo2ee7HS4bwpHhtSuZJwZqInRglMJg5u89fBQAYGDI/d3nzzha6/Gyk+WfRex7c/s+PLJ8Y3mEKqJqGb914I1t17bQbt52xtbU6zDOGPzN+iHfb599zZOek3TvXYn+NAiYF7O+wSE8s9r+YHu4I2/KG8CCa7zTOmHCbWM8jTUObW0YqnUXcNzBI7D7wICnqagEBC1+PDOwV1AfEWGsUNXU1pBDXU3GVeo15sm3LzgKAHDAzggiITB271LBrL4miz29A64xiIz+N4wAbI1AQkLVMn4DefVNWwP6Bodst+fWpWDciAbs2NdvO/nMZY267XTI1oXHcF2XZvoJCsbgW+qyhR2OMB/aAcHlsgW0d3rshHa8Y/JIUflOgcOP0U/j2rVFwkmSVsX/PrMOAPDQEntPY+s4dTNCMC9SRKSdRwjGs7Hb+I1AQIoLBUc7mQWUoeqy6yfrO/3EO7TQFnt7U8YfOYyOnfvyppLfCtKxNvu8Jp95w3rqYV3odrFnzh8Et9QhQ8D6ncFMaBVMHZ2ItAixwEi9udJhW+4XXc21eHLlZscdZJFjlnEYLMiGZahQyrXsMdr/t/cdAaBg3eUEY0yPbat3DepmPrAdP6IBr2/zPg+YOqYFQDLDg+dTtDbWorE2i7c8/C2MF9XaoO32H1zqHLrDeFXHTdQWCUmq1qCQMn4dhunln18qDTtbONzVvhuM39ZiwbKctzbksOxtb2m6JpvBqJZ6vL0jGl27mcqzjhqDDMHRMWc4o75Gs6q46t4lZddl7voV67WFxMlEGCiMJ0Pif25t6aGtddkwFokgzoKICDMndej1yZjOmLZ6vLFtv2isHNTWgA0OgoxZz/3OKZ1ora8RRfOMC0TaQvaG0OTUYOaSc4tODxPxMJAyfh3H6mFnx+kHsmZYD3eNMnaOLIxiqccItWydqNYDHgBoqsviubVbFSkvDwTNgWiIgY0JlLjCgvH+J45sDLxuAqFX1+1KFv3Wek3adgvSZwwpQzV1+d0Ly6LReP7O5joQya1vjDMRp7FvRkdTraunr5klTuho9PRejhvj2htcd+TWXVyGvNM1AprzJhBt7uthz/gdI25ahmlOD1H7pwVv2pTVYYrB05DLYt2WvbZ1mwf0R3smAEA+5r5b2TWb94o8OIOGIWmt3rQn8rbjRlNtFidP7cK0ca2B1ms4ZD3opDs3fVYJx+2lklEBQRv3zMBPHlslumeGLiA5OVuZn+R/nlwLAPj7Gm9hpqmuBo/bqFmThPEjGvH61n2ekXkBIJshjPTIrmWcARrxep5ZHZ3QN6wZ/7/9ZSlO+/cnxOUPH9OCHv1Qxg5Gp2YyhEmdTVi72ZtRvktPXPF/i7yTrLxD33YHlQPWDcVmp5rUK9HHDheYn39yZxNe3by3bFt+893GFv9MJ6dAFMYTAHz2lMnIZclThZKNyeTRYFLGblcinRvWOoM279V6aZ6etSsIa6UwQNDm/K4DA2I129i2erxto76xPnu7vpg/smxD2XRKERrjJ6J6IppHRIuIaBkR3aBfv5OIXiGipUR0BxEFJ8JYMKatHut3HhAfmkwd3SK2Z5/U1YS1DhK/GWfooZZnWSw87HjMxA6NAa/dEp3kTQRM6mxCTYa8D66GIYgIk7uasLdvMLAgeUSayS9Qao7phCmdzegf5JIdn93tRvTHcmCu91MnTUJjbVZE65jWetRkyDaRuvX2U6Zqtu/LbBwYARRtD644/VAA7uFN4sakLs1I41XBvAeACSMa8aaLMGU8fiZD6Dl4BKaMis7IIkyJvxfAacx8LIDpAM4molkA7gRwOICjATQA+ExYBByiv8g1m2UddVB7g6ctv4EpnU14Y9u+Ejtd6+Cvz2UxsqkWbzgMAPN5wIeO06I6OsX4CAvZDGFCRyNe2yp7T8MB5m6a3GmMk+AWXCMGy1qHsWdlspN1puJU3jxQPvNuLWZOuTHcjSondjRgX9+gramidTzXZDPodtntkolOw4FR4hzXc7C22w2yD4KAuZ8m69Z5bgKfeT5PHNmIN7bvE9nnT+psclQdh4HQGD9rMHoxp/9jZn5Q/40BzAMwPiwaDtUZv53u2k64OXhkI/oHGesEDHBSVxOGGHh9W2lZ8+AHNFd3xwltgmEt9NaO8FUuJYyns0lE43DEZEVJzgl2TMJtMTUPk8ld8sVngqGaKyO2k7n7J+ltu6kuzSN61/5+PLJ8o+cOIZPRdlN2dFrvHNsejJlqWCDS5mcuS+JxMqVL28Wtt1jq2Rl2TOpqwqbdvZElZAlVx09EWSJaCGATgDnM/LzptxyAiwE87HDvpUQ0n4jmb9682Vf7EzsakcsSXnx9uwuNhc9GON35r1nK2wxwQ0qUMMvJXU0lE9puyowb0YDamox4hxIEjMfvH2K8snF3JOcLScOYVu2wPsiF7/rzNf323r5BkQqlo6kW7Y25EmnSjkl0d2qMv/wdmtb7EknWDEMlJrFUO7ij0fHsyHzG0T1SVzfGYNwgRU02g4kdjXhVuIszdjyOz2/iPZP0cO9OxgBBI1TGz8yDzDwdmlQ/k4immX7+bwBPMvNTDvfezsw9zNzT1dXlq/2abAYjGmuxShj4zJgAL1oZv46ijuqST5YpXc3YurfPMwpkNkOY3NmER5ZtwGMOVkBhYdEbWjzwV6tF3WOapJkMuaov/KA+l8Wph2nj1u4w0G4pcDMYMEvcRk6IoPpqXHsD6moytm3bMfNvnac5fdlFdLUePU/saMQb29wtYQBt7Hd3NmFNwizLrGRP6mx2lfjNz28EtbNqHOxehaEavPJPi33RqYpIrHqYeQeAuQDOBgAiug5AF4Cvht321NEt4pDDRtLzxwRmZa31OXQ214mYhaFKsJPkyTJVpoxqxrqt+/DpX8+XkOwb1rF3yYkHAwDmBxj5MekoVrXIDuvdYH2nF83UXPGdLGCsTHKyB1Mx0FxXg87mOrwmiJLpBKs56SQPVZ/5XR2me9pKwotM6GjE7t6B0rhFNsyve6Tz7iBuGI8/uasJr27dK9oZdzZru7hVDouZ+Z0ePkYzJz4kogPeMK16uoioXf/cAOAMAC8T0WcAnAXgImYO3VV0dGs9Vm7co6TCkLqOT+5qKpmodhLSFIEO1cChEZ7sA8iP6PceoVkfBZV4POmw9pLTYb0fGBPa0Nvf/NAK0X2Tu5qwcZdMz9s9slF0FuUGvwvfoaM0xr9qU/FO2v7cTD/rsGHo1nj8moHBPs9IoXFiUmcT+gaG8LaNI5eVaiLCoaOaRbuYhtosJnQ04HB9UQ0bYUr8YwHMJaLFAF6ApuO/H8DPAIwG8CwRLSSia0OkAbt0U84FDnp+q8RtB6dhOKXLXkqy1jh+hHYoZJb4nba+Ua34VhwxVpM4fvHU2ljajwPmfprc1ex4WC+FtUsN1aFdLme77p9iHDKbx5TD4OvubLI1qfSLCSMa8eqWvSXRYe3oHN1ah8barG1cfiszN0yUJZL89Ant2N8/aJu/Ii5YH9/II+y0M7M+/7j2Bsxbt60o+qsTPzlsdAteCThmlBPCtOpZzMwzmPkYZp7GzDfq12uYeQozT9f/3RgWDUDBPljVAsIuFZ6VoU/qbMLWvX3Y6RF+tyabQf8g42d/W1P6o6XSqBi/dULX6qGEtweVeLzCYEzoIA7WzY5+08a15i1WvGDsEOz8OKwMpXtkIzbsOiBK6G4Hq+Dxgq7i+9Ec+xwC5vaJCBOF5r8TOrQDztkW5yS7nfF03Ss4KuanAsNSb7IH47di0ZvaInbVvaW6e6vQecioFqzatMd3n6pgWHvuAtq2lEhuAWFIXcsFMVYMyx6VRMleNr2GF21UkOx4hiNKpPOATDqtOKitAU+84mCVZuHmB49sRIZklmI1eoiR2x6XhVqwbd70+ZpztQNbY+fnhYkdjXhmTXEOBztJtrFWs5R7YHGptYp15I1ta0CGgDcTbNnT1VKHplq5BdiMidpiZnbIdtrtj9MFhNfK2HVKMewZf22NFovktsdXi8rf87l3AgCWr/dm/FNHa/q4V026ey/LvZseWOFazkjiAUQbrQ8ALp6lHfAm1W0+aJj9LVrqc+hqkR3WO6O0U43MSkve9FZf1NVkMX5EI541BepzGk7TDtIMEX76hM0u0gcMw4YVlnHv1P7qTXtwoH/IxvzSWZDw8qCvrclgiIHbhHGDooB1nhKRo9e+3Zy+QTfrtY08anlVR4/X4yBtC3/hG/aM3wlOjLe9sRZtDTncv/htz7ITOhowojFXEk7Xui03w5qOzVrUCBYHyLIi+YXdVvsB3Yb4Ly95xxWqdNg9/yFdzaU+HD5g7v8PH6/5J1oTlDsx1Ne37cO8V7eVbPetO7OebueYUn7oNJJ+/+Jp+zDS1va/euZUALKdsYEfmtRIXgJS0g54zU+/csMePLlys63kbn1PLXrkVbtw71YYdv/fFRoDlIOqYPxffq+m57dTs9gx6Z37+20zUlk9cokIRISHBcGV3jlFi9UjGdBRnewDxc//i0t6AAyfBNlesHb9s2u3Yu3mvYE+/xVnaAxykY3E76Zks9TU7+oAACAASURBVD0PMqE+l8W7DulELkuxMMl3TNLG85fveil/zYuZG9m+DLgJSElJymInIPzD8eMAqHkZmy21nF7TSD3kdhQe9FXB+I0TdSM2vhfOmaZFVPQ6tAXkCTEMprpAIFH++0eOFZcNEsdNHIG2hlzgeu5Kw/x1/t67HePLh+EQBsAzkrJIAsZdMP0g9A+yr/6yo/XjegpAid+LQef+fsvOxIaZqyRY+eNnTwQAzLr5MfE9UcD8XBfquzjrbsdukQCAz79nCoDSjH3WV2UWLPtDTopUFYz/tMO1KIG3zn5FVP6jJ2gx9Jet99bLfqSnONSQk9RjHHIZGY8MWHcRAHCkfsAWqhefA52zJnfgpTeiXXDigJt0+nSZieetXVpXk8E9LxbneXA64PvVJ2cCANobc3o553aO0XXCTrkePOm0sJ4Ljj0IQCFEshudRISZ3R2uZQwYyVvMcLrjOP0wVFJvXDCcre6zCbVut/AZodmNvARuj2WYvz6yLFzP/apg/HU57THN20en1RkovHxJiNjO5jrksiVrt0PZWpG5pnkxCHvLa6W05+AOvLFtPzZVgbrHOkmNcMdumbD84F2HaBPf2pd2TGLauDZM6GgolQ5tyhrOfrc89DIO9KuZANqN/2PGtyNDwEK7hd+m/XOP1nbGheeyn1NfOu0Q2+t2FmU1pjOuJKj57Zi0EdPrvkVvi1JQHqsv0KX9X/r8v/mUtvD/fU15wocXqoLxG/bBQKkUYceijQ4xJoeX5CEXTAqted1jJEAv1ztTFcagnvndZG21g4bd6y9dwMuvEwA+8+7JAIAlb8nMfnOZjIjpmTN39frwOLbynYbaLI4Y24pFb8gcqBr1sWJu2+4NnnP0WMzs7sCsyR02vzpDknw+KtgxaaCQWxlwntOGj8zgkHcfdet+Anc+H6zwYUVVMH5DzQJA5O3oNP3tFwk1WkrMwxzK3fyhYwAAv3n2NbUGpHQ4XP/QceNCaS+JcPNhWKzgm+FV77ETNFPJT/1KHn/JEDbcdqZAwRAgKNPfmmwGT6/ekvfgdWtdaehbCrsJU916HuSr71mi0kKkMM5DJGccBgqPLJMUdwkTSPlBVTB+APjtp7UtlNWD0A1SSZ4dPluhskgYuk5JysZyYJVk6nNazBCiaFJAJhUX/vTZwOoyCx5mOA4Hmx+cyt7xzycAAP62Ui1frdPYPlPPGPfb54oFDredsd82nW6f/ZWTAciCJYYNpxlgqK9+8Ij3uaGKIAkA5x0zFoDM98MvqobxG3rWmx96GYA7UzcGpITx20mN7vNBJsmZJ1XUDPiCY8eBOXnZkIKEXd9edc7h+Vy5fT6sKiTjRaqLl/b4Qe1aDofvPviy8I4CbA8i9Xlyy0Py+ozndp1TkD9TXU02/1mSvSoOjGnVLJXMmfWkz+c1Tj53imYFdPndL7kXLAOejJ+IRhHRB4noC0T0KSKaSUQVt2AQEdoacnnzusJ173u9OlRqfeBXVTT5mgcDt3Bwq87wOfjMb8INDR07LO/+gunjsPq75+a/+7WPF42pALvTiChqZ2Xi2L7D9aN1D94LpmsWPl7MXKurUMjp2a3XvR7/mnMPBxBdYhJVEBHed8zYvOOb6RfHe0qjd9qXM7yozc6cQcOxZiI6lYhmA3gAwDnQom0eCeBbAJYQ0Q1EJAvskRAcNrolHzTKDYYUL+koIvlKD6hN+ItmTsh/9iOBSmD3TCfqjD/I6I9Jg9uO69KTtcPY/33G3ovVD75x1mFau6ZmnVQl5qsq48XsTCWB3W41kyFkqJDeMV/WhlaVnbFWUE7bUXpIiq/8YZH8pjDg8nC5bEYkHKiqxAAtbtP6nQfwkkv2wHLgtqScC+BfmPkEZr6Umb/FzF9n5vMBHAvgJWgx9isHJFTfKPSTSpeq9v917z8q//lAX+ipC/IwD9RP/OK5yNqNGk7dYWy1v/OAmuu822KSzSh2vlAfDgArbjxbrW4PEJGnKlIrp/01SrrvDkrrdHsj5pAUcdvzS+etF5l5lZigrgZ9J/HB//67rHFFuDH+f2dmW5siZh5g5r8w8z2hUBUSVNdd6YAzF5Oafkqqrs9l8VXd5f8/5wYbuMprYhu7jWdWb3UtNxxhOE8B9uG5veA2zlhwxqMqITbUFtQN0lj2buOUILNAye+MTXU5WUqpCj11Ndm85czfVvrLuR0FShYzhYN5N6uyB7787vznMM743Bj/QiJ6lIg+bWTSGg5gy19JWVfYbYGdiiofBAOX6dLnz58KTu1Q1L7D9e9+8Oj85yQnwPYN18N9wnlHa5YVH/95MDse2/Mdl/KFBUKGOz/zDgDA+/7j6fKIApAhKlVz2t1ukfi9UCwgeZe/6hxNz//Z3y4oOkSNEoGZs8LsF+Rd1rxDdEoiVQ7cGP84ALcCeBeAV4jor0T0MT2NYkWCbEwLJMw4yJ2mZAttRq0pTPN/zZWFlg4CRJQPKfs7i2nfcIHbovufH58BAFi5cY/cEiegcWK/SLizGeNAHgggzgsBQz4exn0XY8NEPaSeVj2yZe/AEN79/bnK9AQFOYN3Cm/hUK9HxYuvPxMfmH4QRph2oEHBkfEz8yAzz2bmTwKYAOAOABcAeJWI7gyckgignHREskgYRQUTxdzRfnjErbNfKUmN5xeSef0Jfav90yfWBJKLNknwenyzuuWo62Yr1S1z4nGHKt8lInzldE0tOPVbD3nX71aXqYCEjuIDa6c6/XlFf+8fjvYuFCOkDpl+0Fqfw48/NgOHjAo+Wq/IXoiZ+wAsB7ACwC4ARwROSUSQHVrJu698z13vCv502Yn5z6pMyAtu9Jvjplz2uwWBtpsESJnR4BCLUneqOO9J/EhUcerhXfm61wkidjo1kyEqkfjtLdoKBp0S+Dmk/egJE/Ofb52t7qtQLlxJ9jn34z6sBjwYPxFNIKJvENGLAO7Xy5/PzMdFQl3AKJK4BS9fRS0jk3r8oae7OMZJlDlJDdPGx1/ehIeXyr2ekw5J/xvhdAHg5FvnYuOuA8IQyDJbbpm9v3wMGnmDAeA9P3jC/d4AFh5rMa/FTHJu4Ib/mrsmFqYpFQSdSJOY7UYNNzv+vwN4GsAoaGadhzHz9cwsWnaJqJ6I5hHRIiJaRkQ36NcnEdHzRLSaiP5ARKUxW0OExG28oL7R/7rUp7qFLZi+qQ3gdbecl/981o+fxPX3LStrEkjvNOzPgeEn9XvN5yvPPhyP6OEDAOAd330Mp/7gCX9tqY4TH1yypT6Hez5X2B3+5LFV2LHPOV+EH/tyL4TNzC78WXChNIKANAwFoGZYEjbcJP6rAHQz8zeY2c+M7wVwGjMfC2A6gLOJaBaA7wH4ETMfAmA7gE/7qNsXpM5Wjp0n6FT3etWtesy4/0vvyn/+1d/XYZlC2jsXqlx/zWUzWGPyZu2+6gE8lFBvyjAwdXQLjhnfJior2kUawdc8bN794viDO/KL9Y8fXYXpN84RJwuyg8j6TZGTlSOwLHhtO/660DuNYVBwPbAud5mLUeR3Y/wnA3A04ySi04jofU6/swYj2EtO/8cATgPwJ/36rwF8QIniMuBXOnetM++9KDPVKmenOm1cG046pGC98dnfRiOBZzOEB012xZ+788VI2g0TKv1w3xffVfTdy7TQycO75JqrSkhu+mfFF04tjn//8vpSAcGrWslZlGoYBhXp2A4t9Vqwu8vvXoinVkVn2y8l07OrEqDbN+DG+JcAuJ+IHiOiW4noSiK6loh+S0RLALwfwPNulRNRlogWAtgEYA6ANQB2MLNhmvImNLNRu3svJaL5RDR/8+bgOrkQ7taFboUFwo/pnVf7brh4Vnf+81s79uMj/+Nv66sqdR15UHF0ji/d9RKeXrUlEQdVfqHCd+aYVD7v/v5crLBhphL43XGqCoev3lzYpX38F89j8Zs7sK+v2CLMx8bWE4767DLUSmNa6zF1dDMWXntm/trFv5yHHwoiY4YJlcW8+HwxJIIU4GbO+VdmPgnAZQCWAchCs+j5HYCZzPwVZnblyLpJ6HQA4wHMBHC4lDBmvp2Ze5i5p6urS3qbK/zG1ZEdBAvrLFvDV3z/vFe3ofuqB7By425s2q0ek11lPv758+/Mf/6/RW/jH3/5PP5vcWWqfVR74dDRxSZ15/zkKRx17cMlzFTevszD2y+ICC988/T89/P/8xkceW3BIsyPV3pQUK3zuWvei0e+cgqyGcLqm87JX7/t8dXovuqBgKkrRrA+PMUoW1VUBjzNOZl5FTP/iplvZuYf67b9Sq6czLwDwFwAJwJoJyIjQPl4ANEp7IQoeCRKTNrU6w0CRtz0/PcfPYmZNz2Gnz+5FoCWKD5oaXzGxBFFh8yAFhis+6oHcMkd83D/4nBzBwQNVSl03S3n4dsfmJb/vrdvEEdeO7skgqSrR26RWY9S88roaqnDyu+c4/i75CBSpayy74GPF1CTzRTtZgDt3Kn7qgfwmiVbndvBtgrc/TKCdXSLCqHF/SSiLiPUg+7tewY0P4C5AC7Ui10C4K9h0WAHWYz9cOrVCiqWt+DEKZ2Y2NGIL7/3UKz8zjl49KunFP1+04Mr0H3VAzj2xkcw6eoH8cDi9Xhj2z7s2NdXFPOjnKG37pbzcPels4qu/W3lZnzx99oicNlvF2DlxuBMTpe/vQuvbtmLnfv685mmvvfwy7jmz8UZmp54ZVN+4Vu7eU8oTmcXzzoYv9bzohqYv87bpV45aYlSaWfU1mTwxNffo3SPlNYwzsxE7RJh3S3n4Xw9ObyBU259Ir8I/OxvazD9xjl46fXt6BsYwq4D/di06wBOuuVxoUmuN82l5qxuB8F2zyEmI3DYpwYKBmMB/JqIstAWmD8y8/1EtBzA3UT0HWgRPn8ZIg1FKDdjkFudsuBb5dPU1pDDk1eemv9+yKhmzLvmvY45cr/w++KD2J98bDoumF44VvE79mZNHok13z0Xtz+5Ft97uNjC9+FlG/CwQ6az048YhbVb9uLKsw7Dg0s24NgJ7Tj36DH43O9exGfePQnHjGvHpt0HMLmrGUvf2on6XLbkHOM/LpqBnz6xBoAWSfOG/1uGy987Ff/8vy8AAM48ajRO+/e/4aKZE3Hzh47GzQ+uwP88uRbLbzwrnw2rnM3QKVO7sO6W8/Jqhu7ORuU63W3e7Q5S/XOJ7s4mfKRnPJ5aVUjgLZZTAto1mqkPagG47aIZ+PypU3D2j58q+c1IJGMX3dIwyf3qGVOxY18//unEg3HzQyvwrkO7cPGsg0vKK535BeC1HQVCY/zMvBjADJvra6Hp+2OBaFuqGHyq5PaIV/JRrfX46SeOw6zJIzHj23Ncy15+98Iixl8OshnC594zBZ97zxTs7xvEybfOxebd7tEsH12hpdO77HfagnTforfx7fuXAwC++HtZPPkvmeLOGzFcjHoBTfIDgLvmvY675hUCzB557Wy8/O2z88kzyu2m695/JG74v+Ul112ZtNnRr8z2VVFOeAGJ+kpVhRHEPDl8TCtmX3EyxrTV49gbHlG694dzVgIA7tDzLsxethH/9pelAICF156B9kZvFyPpExeNiQQsAJIMXFN1y56l+vdjiOhb4ZMWPLQYJFa9fTDTTz0/b7C9f87RYzGiqRbrbjkv/+/HH52OR796Cn55SU++3BWnHxpG82iozeKFb56Odbech66WOhzUVo9bLzwm2EYCwGI9j2kQelarqsENqqNMJXy3rP0wdruya0qV+sBhY1rQ1pDD/V96F267aEbJOZQfvKx7x6uE1vA0Z1XIRxA2JBL/zwF8A8D/AJokT0S/B/CdMAkLA3JX9LxxvuW6/zqL6o0IH5ihSfaHjGrG6pvOwSHffAhZC8FheG+arUk+3FPIItY7MIi6mix+MPsV9A8N4RtnHoY/LXgTG3f14o/z38BbO/bjocvfjXN+8hRu/tDRuPpeTYd/3xdPwor1u/Dyht1oa8jhx4+uwtIbzsKc5RvwzOqt+OoZUzF72QZ8uGcC9hwY0M4D9vfhst+9iE+dNAkNtRms3rQHs5dtRHOdacgH9OgqEq853LKKOWUQpJrpk6RU1O4JBqrhUvxg2ri2fNpCg/kbGbKsiXAO9A/i9W37UF+Txc79/TjyoFZ854HlGNlUix88srIoKq7Ky5f0aQIEfhHjb2TmeRYGEUyIyBhQlueupH5ly4ZoEeegM5Jof90UBuJjM7UgXJ8/dQoGhxj1uWx+0r7/2IOwfW8fJnQ04pjxBV/CK/QolB+cMR4fnDEeAPDJkyYBAJrrajCmTUuEveyGs9CkM/qHl27A7GUbA7WoUInBom4RFmxPlX2+5Kq9EsQ2UasyMDhlPqvPZTHVYqJ73fuPwpN60pcwzF1LHdjik/kljH8LEU2B3q1EdCGAijTeJphevqDDRItEPguR6VrA5l9BwDrIkmBSZkYum4E1b3VzXU2xhK6IJtO9YeZYUEHQqT990+HlRyCJYmt3rcywJnEjoz+AkdJAJWRDGBFXw4JkVn0BwO0ADieitwC8CuAfQ6UqJNhaS9iV0/9K9Kx+7fiTwngSNh5DR9ECHVid3uEVStpy0/WY6gpygRb3fQjjNGmqDicYGwRzWGrXY4sSXx+B134CXoAn49etcE4noiYAGWaOLiZwCCgnHr9bp/qdoFFJAtXG4K0I4/kd9bllSr3lOgpK61S6P4QwJEmTggGEOlFUnOLChifjJ6KvWr4DwE4AC5h5YUh0hQJ1ywr17a73yX68KCf413BDlDpW+92mmyARPMx1BhqKoGgXlURuXgZUrHpcHbgKhZOgZpV47vZAi9czTv/3WQBnA/g5EV0ZIm2hIArPXcdATebyPtooB37zfqbwhkrIAtUznuAYtN02orx2/WafqwShQ35m569OIPnmnOMBHGeEWCai6wA8AC1s8wIA3w+PvGBBpGp65122ENfHJ03DTUJKKEoOtwPgPuXkl2UXJb8kBLIfmB9Zbs4ZkOduwN7IYSEoL12bihMFicQ/ClpSFQP9AEbrgdrc3TQTB9mEKsTY97o7HMeYMFFJUlcYkEpyQUNVbx+09ZdqPgDJ/QaSlEs2aKg8kdSBKwmvSSLx3wngeSIygqm9H8Dv9cPeUn/1hEPFRFOp3rxlh9vuwKTni7jznW3OEyaKhATVsxgVSFJ0qrSbQEHYAWo7kyTotqUw06pyFqOSbzvRh7vM/G0iehiAEYz9Mmaer3/+RGiUhQBN1SMffL4nqU8TzyhQOVMvHBRP6PIgSbrh1JZnpjbL32Agqy2MuDJhqI/CgNp89DeCkvD0Iu8YZn6BiF4DUA8ARDSRmV/3uC1xKBp8bm/fR38moTNVUGn0lotInKJEOXcLn5WkwzKXqXIlTokt+3AcU0rqK2WTvvhEfkmQtvOJaBU0x62/6X8fCpuwqOA6oIV5dKVlANmBcZSoHLVCsIhczxpCSHBVBF2naorIJOi2xfBp1aOyC4wTksPdbwOYBWAlM08CcDqA50KlKiSIg7QpmD6qWCaUqRUKBhU1+4JHscQdzNtXOwAUSMdFZ0FBWdVY6PCoV5Kb2m/7SR6CSoY6quasxt8EvAAJ4+9n5q0AMkSUYea50Gz7KxJh2fH7jFMVKaKIkJhUlIbQDeD5S+oUF9WvhWQ6KK1Toa0wQhEkTQq2Q1CanrBMdP1CouPfQUTNAJ4EcCcRbQIgz12WIBBISR/pd5EISn0UBqqL3ZfC/PxhzTv3mPSyOkL33A2y3hB2UXFDPk6K36TERDcJc1Ai8V8AYB+ArwB4GMAaAO8Lk6iwIJVkSiNZekMkQSracgeN4TEl/UElkqIqRKE9lNz7g4eqxCnxRlalsxI2meWqbp3rLe/+oCFh/Ncy8xAzDzDzr5n5NgD/GjZhYUFt62ZZzV0mTyUMajMqjNzAYGa4gQc+C1DVEYZ0KFXv+bUAcq/dZu5UgCjiaahToRNJwvjPsLl2TtCERAEiqQOXBl+qHqF9dlwoTQYRDx2RI1IvXbnDj/39wdHiVGdYDGu4DCeJ+kr9wNz4UAZhAcGR8RPR54hoCYDDiGix6d+rABZ7VUxEE4hoLhEtJ6JlRHS5fn06ET1HRAuJaD4RRZZ4XSph+Jl4RTpBQWamOCSF4aJ/DQKRW3NaVU0Rt28HV4/UvLGCzBNdAon6KG6Uu0A6HpjbthXffHQ73P09NHv9mwFcZbq+m5m3CeoeAPA1Zn6RiFoALCCiOdCCut3AzA8R0bn69/f4ot4HJKEV8mUF9ZXfedF2fpLihcQBq/KuHJRqetQcuCT1BnoWUfRZjaFL3pR7uBLZtSQigLP6orJJ8OFxY/xZALugZeAqAhF1eDF/Zl4PPUUjM+8mohXQwjozgFa9WBuAt33Q7Q/CwWdNpxhouN0Y+zwMj9BKgWrIhCDbAnzYfJeo5OL13HVDEa3DZDjJUk/Kd3F+F9Ow4Mb4F6DwLHbHWJOljRBRN4AZAJ4HcAWA2UT0A2iqpnc63HMpgEsBYOLEidKmPFGOjtU1kqeg/qIgbTGtANUq6RsIIzpnOQYDUSJwz13l9o0D6+QOQj+7uKL7Fbx844Qj49e9dMuG7gNwD4ArmHkXEX0HwFeY+R4i+giAX0LzBra2fzu0XL/o6ekJ5JURoCRx+044LW8ixu1ugkZhBAhDn1oa49+lrOW7ex7neGkF/KkE1R3YKgQC6yuVKpKwAIiCtBHR+dASrwDAE8x8v/C+HDSmfycz36tfvgTA5frn/wfgF3Jyy0OxxB0s5Jqe+Hq9kvWswSF80wqp1CfL4RwcnVYmFUYI4eEynPxkIKskz2VJkLZboDHq5fq/y4nou4L7CJo0v4KZf2j66W0Ap+ifTwOwSpXocmDtG3cvW+MeV/FM3HYSVv0ECBuxIEyJU7QzVGgsCuk4UP8AxdqSIPE6oXxmLlnM44dE4j8XwHRmHgIAIvo1gJcAXONx30kALgawhIiMpOzXAPgXAD8hohoAB6Dr8aMAwZ+XpQR+OzXKRb8o4XNyxmCkCDIDmR//LakcH3f/SJLLhOnAliQEYtVjqiTuvgWEqh4A7QAMK542yQ3M/DSc39nxwnYDhXy76kOKzzMUoRNHTKhaBy4bhPXsth7ettcc7g+JSZRWJXNMcitbeq9KncmFiqNn4R61uR+nRZ2E8d8M4CUimgvtWU9GsV1/RUHFicRvBEsVq6BIEXf7MSLMdx9F7Pygw0sEG6tIsXxwTYeA4M1mrdeT8PyOjJ+I/gvA75n5LiJ6AsAJ+k//yswboiAuaNgLMjaSmMIksZpzKtMU02qQhMEXB4L0HvXDTFmgawpNEvSxmKg4ZVWSxKsCV719GeMoqWGZVwL4ARGNBfBHAHcx80vRkBUelMzTBBOlUgavAUngueEIqfolkLaEp7PRRmZVa6zECKJMq55KG2eys0AFc97Yt/vFcLTqYeafMPOJ0CxwtgK4g4heJqLriGhqZBQGCCKSWWDof5XcsQWHYUXlYhC5kzX04oHIUku1zvxf7zpVzX7DGyaqVvf+arItH/dBlwv8ZiorVOBdNgnP72nOycyvMfP3mHkGgIsAfADAitApCwHS4awUk9t2F+DUfgLctmNceOJEGD4MjvlVBddcX39IO0sVU2ane4rv9+cUlr+/QiSRIOhM2rNK7PhriOj9RHQntKBtrwD4UOiUhQQVia9SXPGlSB24kiFtGZD4kATWluJ5hIIg69qO1/Wkws/rl96ThBHodrh7BjQJ/1wA8wDcDeBSZq7ItIsAAJINaKWQC/pf9S18Erq/eqASMsEvgtLxhuXoJ/bcDZlJJ3nkq7omlO6i3By4LGUTerh7NbTQzF9j5u0R0RMq1A+4vA9C/VgAeV0LEyr66OGOwDx3FXQo0jOeoJmE79tDNHuuFEj8LfzWERfcgrSdFiUhSYKfdIrmokk7wTeQiDOGmCH1nJWg7DAMLs5OoexIHD5LYEtrmeqjRCMEXU+chh1WSFIvDhsUjd3AtuWKu4jYPXcTMOrigO1uK9hlL9A3G0E3uY9dn86LSt7AyYNqFFOpb4R9PP74XkpVMX5ArucEzM4+koNgtYkST+rFeNtPAsKRpOW+EZIznqKYSgGtACpmiqrsSN2cU/GGmOGcStWv6jj+F1BVjJ+g+Moli4RFLRRk4oYoEHf7UUHV9DDw9hXMfm3vD4AGP2Eg3BcoeVntd2v7yR18fowwVN4VEO/cqy7Gr6KTLcNTMfgNdHCoNGkraIR6qC3aGQqrCphO5cToQZtzVshpUrnzuTKessoYPyD3sJWWUUGYiWBE7Zs+Vxv/V40rowJRaA+fQkew0TnZ9FnWvqheZV2PYvmEwu97SoLwVVWMnyAL2aCVFdZZdhLsaGWE0qevFBkleAQd8VKCwrmRRzkfahk3+PVXKSe2Venv1rOQ5EJsditNvZgAU24zqovxK7rCq6zQ4i18jKt9knWqkSHE8zWV8AZAZXm52jOuCjZkd0A5DFrqm5EAgb+6GD8gZ7x2Ad3cpCZJcupij8x4ur+wmCVh+EWHKA/X3EMxyN57GL1jbjpOm/vh4jyoNqZSc87YEIaAIg3BW3ZDASBplgVxIEiWo5SpTcXD22zOGRTBChK7evts+t+rlLl9Sd3xQBxt10edSUBVMX5ArmOVllEvm6DeryKUOOaE0IZoTBV9i1ZCKPLcVeRCUq9v58WkMmC/mMuc0qQH5klYAKqM8ZP40Kyoo9xq9GutIb8tUAyXbbZfmPs/qK12qVNgAEw6YO5QbpyqIJEExhcWytkFRonQGD8RTSCiuUS0nIiWEdHlpt++pCd1WUZE3w+LhlKa1MqrOJyo7CSK6lQrXh7KdCKqZKgm2PBTpwrE0mEMC7WqgOLXTDHJY8+v9ZWk1iQIX5Jk634xAC2y54tE1AJgARHNATAawAUAjmXmXiIaFSINNpCac5buDpzKAcWMJMnOKsNZ2lJF0BKXLLSHrP1Q9OFs+1EEqbWLK5kK/MNA6wAAGgxJREFUPjRxQcWqpzSuj6LnrgJdQSM0xs/M6wGs1z/vJqIVAMYB+BcAtzBzr/7bprBosIKgEFpB6rlbQU4cxVZF0befBIQhbYlyPMR8kqlqpujP+suF8dkFKUvy6a5PSN5pEhCJjp+IugHMAPA8gKkA3k1EzxPR34joBId7LiWi+UQ0f/PmzQHRYXPNpbzERLNQ1mf7sTOE4Tf57GB9yiDmoL86jTHlXjoMAYGFIn85I2K4DKdC/3j0kw9v6CQsAKEzfiJqBnAPgCuYeRe0XUYHgFkAvgHgj2TDfZj5dmbuYeaerq6uwOiRvvPwt2YJ6P0qRPHhbjiQChhO7duH8C0P9u0HdLitWK7SfEgc+0mhLBC8N3Y5CJXxE1EOGtO/k5nv1S+/CeBe1jAPwBCAzjDpyNOjOtB9mnMq6W6VCCoPxbGCKmvylQvVnLMqCMOWOy5z05J7XH5TiXhaDT4kYt+MCGjxQphWPQTglwBWMPMPTT/9BcCpepmpAGoBbAmLDitUYmvI1DcF313PsmE45iiikuKlhAHz05cdZ0khaYfSoWEZNEnbD8vZShbqOfnwbdWjNKbim31hWvWcBOBiAEuIaKF+7RoAdwC4g4iWAugDcAlHtPczM3OvFqW7g7K34FF67lYbly9CdA8vSbidBG2HxFpFxdHRczGpAKFD6RBcWYGQgE7XEaZVz9NwfjX/GFa7blDdbhoDVdJh8iBtyej8hJARG0JRpbj8Zu/5KjcBCcQprIx7pUHmKj31ohXSwGteKD7cjX/yVZnnrlw6sUt4LZEGXG15E+G5W4xKnZB+UexvEVSdlgtlVhxGn5Tq42VWRSojVRyALn6+5wmJh7c0jIVdncAwPtxNGlQSHqv2SZHuWOG+KJ29qozHFyEUz13LdxUHLmmawkAPoctQtUh2xl7llCqNCSULpNRI16OjkvakVcX4AZP6RjJJBfUVPHeF7efpkJUPGknKAhQHih47pNko9nJVONwN+ixJbIIZoL1/wTK+sgaf6/qkIMXHadFnRfUxfuuFMg+4yg31HO3hrqKeeRghzKf0k5A7znj4BoLOQe1+xiG7lhx495OKU1bSHCWrivGres+V6uTcrDWMg2AZYkvEokjnsIPwjEeCciV2aQyYoKDkb+DzDYkoT/DgU44/VFLWhUckaLddVYwfQOnWzKEYQTb41S2FZO1HhYQJIqEhDG9YKwI1fQw4kmPpeYRLWUUjBL8275Uw9qT95Adx7gKqivFrydbFhZUgWsXjjstj+pwEk7I4wEGK/Eadgp2har5nyf2qUNnBlrQvjentlIilEri8CcWe+N4GIFHspoJEdTF+2wM2wdZMUKcqH43NnDP+MRcL7HlUwJ67Cv4eqiF8y4YqrT7UEmI1p7zKyFFuaA/3w93kOLBVFeMHzFY97uVUZKHi+j3a999Q2UiCH0E1QGwgLFAJhrlQO6o5VbxXYbV5dylXwvgqaxdgB2n46qRteKqK8YdpWWAe1BLfgNjMOS3fkzYgw4Y4H4NKnZa63ct6H66rMt4w4faelFRV5jorQOrwq7l1fSPp4W58kNoSE5FID17uhIxW6qlekb9ca42y21JsP2jmoHK4K7nfDsoJ3BModPh24PKqN0GLOVBljF8ahsHtuhNUY/Uk4YAHqLxDt3KRGJM61/bD6xMW6mX87GIAqb1/3C9fDUGlyIzbedOMKmP8ahMq3z8KB3GqgzpqvhuGqqMSIA0y5gv5xVxcVG/fzS+k+G+5UHM0FFollSkcJVnkkCTgUlN1Jct5sqoYPyD3nLR2iYqzTVC7iKBh58CW5MkXBoJe7qRmmqUCQvl1+oHUjyBfXrF+RyorZKCpH2zL+EnSUFWMn6DmRKJkyqba8bENFItlRYVMyHIRZgYuv3VGe7qjJnGW6uu9qZWrO2XlkgD1Q3jvd5qEx68qxq9ytklEvj13VRDT0W4iBl/cCCvnrCpDsK1TIZigLwg9d1XrkvjF+G4nQkis9JzK2yE93I0ZpXJMMF55qotEUhjvcLClVkHQh+vFfRqiA1dA3WRuVXQQG5CjWdJyzjqh1PrJnVo1j11ZnVGgqhh/cc5b+STV7nWo0+K5q+7pFy3jTYxVSwIQaWTUuNsv1+w4BGudShE6JMH4gnMIjQZVxfgBlCzRbgexvp04YvbIdELStptxIAyTOpU+9evAFRSkOx4/kiyQPAbnF6qH4AaCOjMMG1XF+DVmLj1g8Wn66dp+iCaFQlStOWfM0rVfB67AzDmF11TKlsQqEp4bJEHV4YSwHO2K8nuokRQKQmP8RDSBiOYS0XIiWkZEl1t+/xoRMRF1hkVDCU2K5SWdWinbVUBmZjjcEbhHrM8VxT2zVfj9FJYFjlrqRbW644Dr85eZ2CjO3XZNiHUPAPgaM79IRC0AFhDRHGZeTkQTAJwJ4PUQ27eFdFuunrRFtpMIOs66XyRY6AoFpa740bVV1K7YgSscCqWHu0pJiBTVl5Uw9orfU8DWXwl4/tAkfmZez8wv6p93A1gBYJz+848AXImIX4Gd3t69U9m7HFlLmi7aFxWUDA8lDKUCpK6wENyE9ja9LPEjcAt+pih0SKCWZtGslpA/kxfKSfYeHfwJCH4Od4d9IhYi6gYwA8DzRHQBgLeYeVEUbRfRoWBQaefsFSTiPtxNgNARE4L1tFS11vF7EBrYIuX30FJcTi70VAqUzkIEXr5JQJiqHgAAETUDuAfAFdDUP9dAU/N43XcpgEsBYOLEiYHRI5U6pPPMKOZ3mxvX4W6+/YqeknJEEZ1TRW+vmqawXNinnnRTNalDPU5VcseeqgOd57MXCV3xLwChSvxElIPG9O9k5nsBTAEwCcAiIloHYDyAF4lojPVeZr6dmXuYuaerqysgetTKSyxgfFs2qJESCIooTZD0ESWiCNXgbgXi7RwSqjmnRC1lLq9golpyc0m55MP23Xv0h/ldyhTHompDRWgSP2kc8ZcAVjDzDwGAmZcAGGUqsw5ADzNvCYsOK6R23FZpyLuTzOcBKhRF7MBlbT25QlegKH3OgDx3pYu5VcfvJfHLai0Lanp/m2uW73JzTnm7cUNq1KOi40/C84cp8Z8E4GIApxHRQv3fuSG25wk7vb1KjkynOmFTr2OdMXZ60myJ44DUqqUcSMItA2768OSY3YYZeK5SZA4vOosttRTqHY7mnMz8NDzeGTN3h9W+LRQYn13SlrKbVwwZEQUqZfKVC1Uduwoku0h1H5KQzDmFh7ulZ2EyE1VZ28kY+3ZQW7hUdcdqxcNEVXnu2qHc/Lj5WD1+24/pcDch606sCOLdq0rnIukwInNORzqF6qtSE1WXsnbvqRKkDumi5vF70nbbVcX4C2oZFh5ame51NOMv0XR61Clz9IoKSbasCAOhmugqGQGoWsD4IikwiK3chslwkjraATL1nVZOvosKG9XF+O2kHkfLCrVOEaUyjcCk0AsSq47hCBXpVBV+TXRVLEDKhbI5ab6cNyWqHqlJHnolC7TY0c7bL6hQ1g9lwaKqGL8BZpmeURSrxy/njtmBK38tejJihWqCDU8oq2XkBgOhw2HwyttX9Q2wSLwVMvjUHO2cf4vbh8eMqmL8yvpYBe7sV4KOS9WSAKEjUpSaHoZpJuk9zjxb9+lh61mtYoUqxcXSsRoJsUCam1sr480pkrbIVRXjN8AQ2N1KD7gsZaL2yFRGgqSOOODX9M61ToVzG0n7ql62EpS72wtDx59Er3Fb/y3H8z01JMmqqaoYfyFbltDZqkhvL+99UcaeGDq/Up1ogkBoNvs+25c7cAUL8bhTIEAc1iBvUVY5gy9MUuNc9qqL8Zs+SyR+pW2uzwES/eGutf3kSV1hgi1/g61c4SAU5ZsSq6C4To+DSOF2V2Uxq7TsbywR+oyyEPCTIh+eMggLCFXF+A1YjarsIGWIqoxTqhIKA5WS8DoKDHGA5ysS9Y3VqsbL7NfqQBUUqb69TIXzQVBsX98gAGAoCRzQAr/hswvX5IfbccpcVcX4C6oeqVWPwgGPQM+bSKkn7vYjQ6kdfSYIox7FQ0uZjr8skpRocCyTH8/yXYxXSeP3a/+6FADw6IpN3oQkAF79wQzPh499nlsQeljmJEEl523Jda9yCltDIL7tnmq42eEG82KeCWE2OjrjKur4123dh+6rHsh/39M7UB5dpvYNSTvrYc5536K38a/3LHGu0/T5N8+uw4LXtuPocW2upf++egtefH0HAODtHfsFlMcDiYe7xHrLtk7/ZAWGqmL8BqQHXJJSyqyjZLcXnSiQyB1HRLA+5xBzYG9eRX3HzPjyXS9h0+5epXd/yKhmX7RZsWN/P87+8ZMAgIVv7HAs98qG3XhwyQZRnfcseBP3L14PAFjy1k7HcsyMj//i+fz3miC2XAHD73z0Y6wR5/laVTL+gUHGT59Y41qGUJjIe3r70Tcw5FqegbyEtuC17Q51Egw2seD17fp90a7/pYe71YU/LXgTy9fvwt/XbA2szrWb9+Dzdy5wZZTGe/7o7c/lry16w55JbtnTW/R9+Y1nobG2vKlqMJmv/3ERdh/Qdg/PrHGOhr5m896i7+PaGxzLGkzfHYwte/qKrvz3J44X3BcvROo7YUh2BtA3MIR/+8vSsukqF1XJ+O9+4Y38YF23Za9tGSIqYuZOMLZ7m3cXJuvy9bs8aTAWnhGNtRKSA0HS3MajhPHsT63agqdWBZf+4UD/kEhXvX1ff8m1i2ZOsC37zGptUbrpg9Nw4fHjUVeTLY9IE55dW1jwnvzGqbZlVm3ak/88/1uno7O5zrZcbU3pEeG6W86zLfvm9lK1TltDzpXWOGFMj/19g6K58sXfvwQA2La3z/Z3g0986KfP5K+1NsTHfquK8R/o16wJvn3/8vy16RPaPctLcMUfFuY/3/v5d9qWyWSAZ9duw8NLC5LhhI5GcRtBYHCIce1fl+KZ1Rrzq7YgbWbc9S+zImurs7mwwH/+PVPwhVMPQVOd/fS7eNbB+O1zr+GiEyYiE5A6ZExbfdF3JwZtRmdzrSPTB4A6C+O/5MSDHcvaMc8EanqKJPZn12zF06udhYReXQuwc19/vlx9zn6R7h8cwpzlG/Pfzz5qTKALuiqqivFb1TuPfOVkTB3dYlv21S178appNzBtXKttuRUW6f6WDx2N4yaOsC1rSHKX/W6BmOYgwZBuy4cfWi3S5VNXnhroonve0WMxY2I7PnqCvRT/jskjMffr78HBHY2ezPzGC47CDecfFRjTB4AZEwsCzm0XzXAtu+jaM/GjR1fiyrMPcy1nXhTqajK46pwjHMve/k/H48hrZwMAjh7XhiVv7Uyk0DE4pK1QT6/a7MmYb3tsFQBg5ncfy1/7wqmH2JZdbdpFAcDPLo5XzVVVjD+XzWBgqCDFOzF9Kx796smY1Gl/uHb2tDG47r5l+e8fm+mcGH5cewPeMlkyfOi4caL2g8JrW/eVXKu32a4PR5hVaqtuOge5bLDP/V+fOM6zzKTOJlFdRBT4ofv4EYVF7n1Hj3Ut29aYw/XnH+VZZ3tjLV75ztmozWY8mXhjbQ3uvnQWmIEjxrZg1aY9yCZQ5Dd2YX9Z+Hb+2t+vOs22bEtdDXabrK1+/k89jvV+67wj8J0HVgAAfvfpdwRBalmgSjDr6+np4fnz55ddz57eAUy7TpM6fvaPx+Hsac4T4Pr7luFXf18HwHtbvHrTbix7exfGj2jA8Qd3OJYbGBzC3t5BHHvjIwCAxdefidb66PSc5vOK048YhUdXbBJt+YcL/vDC6+jp7sCUrmAsZABg464DyGbIVSWSonLAzJh09YNF15zmyL6+gfwuxq1cnCCiBcxcsiJVFeNXQf/gEF5evxtHj3eyS/aPA/2DWLN5D446KPi63XDdX5diy54+kXSaIkW1wiwg/emyE9HT7SzMAcCuA/2oq8nEqrN3Qsr4U6RIkUKAA/2D+NGclfhwz4TA/CfighPjryodf4oUKVJ4oT6XxdXnOh9UDweEdrJHRBOIaC4RLSeiZUR0uX79ViJ6mYgWE9GficjZnjJFihQpUgSOME06BgB8jZmPBDALwBeI6EgAcwBMY+ZjAKwEcHWINKRIkSJFCgtCY/zMvJ6ZX9Q/7wawAsA4Zn6EmQ0bqOcAjA+LhhQpUqRIUYpIjLiJqBvADADPW376FICHHO65lIjmE9H8zZs3h0tgihQpUlQRQmf8RNQM4B4AVzDzLtP1b0JTB91pdx8z387MPczc09XVFTaZKVKkSFE1CNWqh4hy0Jj+ncx8r+n6PwN4H4D3ciXYk6ZIkSLFMEJojJ80H+5fAljBzD80XT8bwJUATmHm0hgCKVKkSJEiVIQp8Z8E4GIAS4jICF15DYDbANQBmKPH93iOmS8LkY4UKVKkSGFCRXjuEtFmAK/5vL0TQHAB2MNFpdBaKXQClUNrpdAJVA6tKZ3AwcxcckhaEYy/HBDRfDuX5SSiUmitFDqByqG1UugEKofWlE5nVEdM3hQpUqRIkUfK+FOkSJGiylANjP/2uAlQQKXQWil0ApVDa6XQCVQOrSmdDhj2Ov4UKVKkSFGMapD4U6RIkSKFCSnjT5EiRYoqw7Bm/ER0NhG9QkSrieiqBNCzjoiWENFCIpqvX+sgojlEtEr/O0K/TkR0m077YiIKNV8iEd1BRJuIaKnpmjJtRHSJXn4VEV0SEZ3XE9Fb+ntdSETnmn67WqfzFSI6y3Q91LHhko8iie/UidZEvVciqieieUS0SKfzBv36JCJ6Xm/zD0RUq1+v07+v1n/v9qI/Alp/RUSvmt7pdP16tP3PzMPyH4AsgDUAJgOoBbAIwJEx07QOQKfl2vcBXKV/vgrA9/TP50KLXErQ8hk8HzJtJwM4DsBSv7QB6ACwVv87Qv88IgI6rwfwdZuyR+r9Xgdgkj4eslGMDQBjARynf26BlnviyIS+UydaE/Ve9XfTrH/OQYv2OwvAHwF8TL/+MwCf0z9/HsDP9M8fA/AHN/oDfqdOtP4KwIU25SPt/+Es8c8EsJqZ1zJzH4C7AVwQM012uADAr/XPvwbwAdP137CG5wC0E9HYsIhg5icBbCuTtrMAzGHmbcy8HVrSnbMjoNMJFwC4m5l7mflVAKuhjYvQxwY75KNAMt+pE61OiOW96u9mj/41p/9jAKcB+JN+3fpOjXf9JwDvJSJyoT8wuNDqhEj7fzgz/nEA3jB9fxPugzkKMIBHiGgBEV2qXxvNzOv1zxsAjNY/J4F+VdripPmL+hb5DkN94kJPpHRScT6KRL9TKs2dkaj3SkRZ0mJ/bYLGBNcA2MGF5E7mNvP06L/vBDAyCjrtaGVm453epL/THxFRnZVWC02h0DqcGX8S8S5mPg7AOdBSUZ5s/pG1vV0i7WuTTBuAnwKYAmA6gPUA/j1ecgogh3wUQPLeqQ2tiXuvzDzIzNOhZe6bCeDwmElyhJVWIpoGLdXs4QBOgKa++dc4aBvOjP8tABNM38fr12IDM7+l/90E4M/QBu5GQ4Wj/92kF08C/aq0xUIzM2/UJ9kQgJ+jsG2PlU6yz0eRyHdqR2tS36tO2w4AcwGcCE0tYkQaNreZp0f/vQ3A1ijptNB6tq5WY2buBfC/iOmdDmfG/wKAQ/UT/1pohzv3xUUMETURUYvxGcCZAJbqNBkn9ZcA+Kv++T4A/6Sf9s8CsNOkIogKqrTNBnAmEY3Q1QJn6tdCheXs44PQ3qtB58d0645JAA4FMA8RjA1dl1ySjwIJfKdOtCbtvRJRFxG1658bAJwB7TxiLoAL9WLWd2q86wsBPK7vspzoDwwOtL5sWvQJ2lmE+Z1G1//lng4n+R+0k/KV0PSA34yZlsnQLAkWAVhm0ANN5/gYgFUAHgXQwQWrgP/SaV8CoCdk+u6Ctp3vh6ZH/LQf2qDlUV6t//tkRHT+VqdjsT6BxprKf1On8xUA50Q1NgC8C5oaZzGAhfq/cxP6Tp1oTdR7BXAMgJd0epYCuNY0t+bp7+f/AajTr9fr31frv0/2oj8CWh/X3+lSAL9DwfIn0v5PQzakSJEiRZVhOKt6UqRIkSKFDVLGnyJFihRVhpTxp0iRIkWVIWX8KVKkSFFlSBl/ihQpUlQZUsafYtiDiEaaoiFuoELEyT1E9N8htXkFEf2Tj/tqiehJk0NSihSBIzXnTFFVIKLrAexh5h+E2EYNgBehRbwc8Cpvc/910IKd3Rk4cSlSIJX4U1QxiOg9RHS//vl6Ivo1ET1FRK8R0YeI6Puk5U94WA9pACI6noj+pgfam032EVNPA/CiwfSJ6Aki6tE/dxLROv3zUaTFbF+oB+06VL//LwA+EfLjp6hipIw/RYoCpkBj2udD86qcy8xHA9gP4Dyd+f8HtHjqxwO4A8BNNvWcBGCBoL3LAPyEtUBePdA8kQHNq/OEch4kRQo3pHrEFCkKeIiZ+4loCbSkIg/r15cA6AZwGIBpAOZooVaQhRY+woqx0GLIeOFZAN8kovEA7mXmVYAW1ZGI+oiohbX4+ClSBIqU8adIUUAvADDzEBH1c+EAbAjaXCEAy5j5RI969kOLE2MG6X9zxgVm/j0RPQ/gPAAPEtFnmflx/ec6AAf8P0qKFM5IVT0pUsjxCoAuIjoR0EIZE9FRNuVWADjEcs1Q3bwH2k4BRDQZwFpmvg1aRMlj9OsjAWxh5v7AnyBFCqSMP0UKMVhLJ3ghgO8R0SJoUSzfaVP0IWi5gc04nYheAHA6gG1E9GUAHwGwlLQsTdMA/EYveyqAB0J4hBQpAKTmnClShAIi+jOAK5l5FRE9AS1p+XzhvfdCS8i+MkwaU1QvUok/RYpwcBW0Q14l6AlM/pIy/RRhIpX4U6RIkaLKkEr8KVKkSFFlSBl/ihQpUlQZUsafIkWKFFWGlPGnSJEiRZUhZfwpUqRIUWX4/7vrrvDGUsaCAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ewNnbR2K85tr",
"colab_type": "text"
},
"source": [
"Ok, awesome! So now a little thing for you to do. Generate a version of the above plot that shows only a single zero-bit. Use the cell below for your code. Use the [matplotlib.pyplot documentation](https://matplotlib.org/api/_as_gen/matplotlib.pyplot.html) to find the relevant parameter to use."
]
},
{
"cell_type": "code",
"metadata": {
"id": "Vaa-Sd8l85tt",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 279
},
"outputId": "296d7fbe-85f3-41a6-d03e-ace1b924e276"
},
"source": [
"plt.plot(amplitude_signal[:,0],amplitude_signal[:,1])\n",
"plt.xlim(160,300) ### This is the important command. It sets the range of the x-axis.\n",
"plt.xlabel('Time (µs)')\n",
"plt.ylabel('Voltage (V)')\n",
"plt.show()"
],
"execution_count": 12,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "I0tPaRh485t3",
"colab_type": "text"
},
"source": [
"Now on to the throwing maths at data part! Fortunately clever people who came before us have already solved the arduous task of writing all that math code, so that we only need to do:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "ATGeotes85t4",
"colab_type": "code",
"colab": {}
},
"source": [
"import scipy.signal\n",
"## The Hilbert transform works best on a signal with filtered out DC component, so let's do that then\n",
"centered_amplitude_signal = amplitude_signal[:,1] - np.mean(amplitude_signal[:,1])\n",
"analytic_signal = scipy.signal.hilbert(centered_amplitude_signal)\n",
"instantaneous_phase = np.unwrap(np.angle(analytic_signal))\n",
"instantaneous_frequency = (np.diff(instantaneous_phase) /(2.0*np.pi) * 2.0)"
],
"execution_count": 13,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "LhOin-kV85t-",
"colab_type": "text"
},
"source": [
"Wow, that was easy! Now that you have something to do as well, your task is to plot the Instantaneous Frequency and Instantaneous Phase over time, similarly to te amplitude plots above. Little help: As the variable ``instantaneous_frequency`` is a sample shorter you will also have to shorten the timebase by a sample, i.e.\\ with the IF use ``amplitude_signal[1:,0]``."
]
},
{
"cell_type": "code",
"metadata": {
"id": "4E2mLzQk85uA",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 544
},
"outputId": "66fe9b7d-8d32-452d-bc43-f059ced322aa"
},
"source": [
"plt.plot(amplitude_signal[:,0],instantaneous_phase)\n",
"plt.xlabel('Time (µs)')\n",
"plt.ylabel('IP (rad)')\n",
"plt.show()\n",
"plt.plot(amplitude_signal[1:,0],instantaneous_frequency)\n",
"plt.xlabel('Time (µs)')\n",
"plt.ylabel('IF (MHz)')\n",
"plt.show()"
],
"execution_count": 14,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "6cfpML1G85uH",
"colab_type": "text"
},
"source": [
"Looks weird, huh? Then it is probably correct as the output of the Hilbert transform for a non-sinewave signal is -- let's say -- *not intuitive*.\n",
"\n",
"Alright, so, looking back at my talk which you may or may not remember, the next thing to do is to calculate mean, skewness, kurtosis and variance for each of the three time-series. This should yield 12 features (values) in total. Now that you are already steeped in Python signal processing, I am confident you will have no problem doing the calculations. Make sure to save the result in an array with 12 elements of the form \n",
"```\n",
"features=([amp_mean, amp_variance, amp_skewness, amp_kurtosis, ip_mean, ip_variance, ip_skewness, ip_kurtosis, if_mean, if_variance, if_skewness, if_kurtosis])\n",
"```\n",
"\n",
"**Hint:** Of course somebody else has already implemented this statistics stuff for us as well. Look at the [documentation for scipy.stats](https://docs.scipy.org/doc/scipy/reference/stats.html)."
]
},
{
"cell_type": "code",
"metadata": {
"id": "HjwAXGwm85uJ",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 55
},
"outputId": "3d81e8b2-16b7-4e29-9f1b-0af82178315d"
},
"source": [
"from scipy import stats \n",
"features = ([np.mean(amplitude_signal[:,1]), np.var(amplitude_signal[:,1]),\n",
" stats.skew(amplitude_signal[:,1]), stats.kurtosis(amplitude_signal[:,1]),\n",
" np.mean(instantaneous_phase), np.var(instantaneous_phase),\n",
" stats.skew(instantaneous_phase), stats.kurtosis(instantaneous_phase),\n",
" np.mean(instantaneous_frequency), np.var(instantaneous_frequency),\n",
" stats.skew(instantaneous_frequency), stats.kurtosis(instantaneous_frequency)])\n",
"print(features)"
],
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"text": [
"[29.612129976627568, 13.604418549592038, -0.8937175140675976, -0.17142442971967498, 49.9540365137824, 741.5780665230274, 0.26533510844500857, -1.1234006636642329, 0.0044426483357129605, 0.0001997875544098661, 0.5090316580958151, 40.87426004698325]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "g6HxI-B_85uP",
"colab_type": "text"
},
"source": [
"Ok, now we have all 12 features..... but only for a single data point. Of which we have actually 250 per device or 1250 in total. It would be rather tedious to repeat this manually for all of them. So to let our Computers do the work for us, let's implement a function that we can call in a loop for all the data.\n",
"\n",
"And with \"let's\" I of course mean \"you do it\". :) Below is a prototype for a Python function which should do all the stuff we did before, i.e.\n",
"1. Load a CSV file with np.genfromtxt. The filename is given as a parameter to the function\n",
"2. Center the amplitude signal\n",
"3. Perform the Hilbert-Transform and calculate Instantaneous Phase and Instantaneous Frequency\n",
"4. Calculate the 12D feature vector as in the last exercise\n",
"5. Return the feature vector"
]
},
{
"cell_type": "code",
"metadata": {
"id": "VGvLwRP-85uS",
"colab_type": "code",
"colab": {}
},
"source": [
"def calc_features(fname):\n",
" ### Most of this is copy-paste from above with\n",
" ### the fname variable substituting the explicit filename\n",
" amplitude_signal = np.genfromtxt(fname, delimiter=',', skip_header=1)\n",
"\n",
" centered_amplitude_signal = amplitude_signal[:,1] - np.mean(amplitude_signal[:,1])\n",
" analytic_signal = scipy.signal.hilbert(centered_amplitude_signal)\n",
" instantaneous_phase = np.unwrap(np.angle(analytic_signal))\n",
" instantaneous_frequency = (np.diff(instantaneous_phase) /(2.0*np.pi) * 2.0)\n",
"\n",
" features = ([np.mean(amplitude_signal[:,1]), np.var(amplitude_signal[:,1]),\n",
" stats.skew(amplitude_signal[:,1]), stats.kurtosis(amplitude_signal[:,1]),\n",
" np.mean(instantaneous_phase), np.var(instantaneous_phase),\n",
" stats.skew(instantaneous_phase), stats.kurtosis(instantaneous_phase),\n",
" np.mean(instantaneous_frequency), np.var(instantaneous_frequency),\n",
" stats.skew(instantaneous_frequency), stats.kurtosis(instantaneous_frequency)])\n",
" return features"
],
"execution_count": 16,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "sGHklxq285uX",
"colab_type": "text"
},
"source": [
"Nice, now we can let the Raspberry Pi calculate everything! Below is a codeblock which calls the function you have just implemented for all the data files.\n",
"\n",
"(Text below is from the Raspberry Pi version but I left it in, so you know how we proceed with the workshop. The Colab runtime does the calculations in a couple seconds.)\n",
"\n",
"But.. **oops** while testing this I realized that it takes the Pi Zero **a whopping 20 minutes** (*oof*) to get this done. Apparently Python really isn't quite as fast as C/C++.\n",
"\n",
"So, we have 2 possible ways to go on:\n",
"1. We let the Pis run and make a 25 minute coffee/tea break. :)\n",
"2. You get the prepared results of the below calculations from me and we press on directly\n",
"\n",
"In the second case, I'll send you a CSV file you need to upload to your notebooks folder and you can jump to the cell beginning with \"### Hey hey\". In the first case, you should let the code below run, get a hot beverage, and then skip the \"### Hey hey\" part.\n",
"\n",
"(/End Rasperry Pi specific text)"
]
},
{
"cell_type": "code",
"metadata": {
"id": "dRTNuHYk85uY",
"colab_type": "code",
"colab": {}
},
"source": [
"switchA = np.empty([1,12])\n",
"switchB = np.empty([1,12])\n",
"linecpl = np.empty([1,12])\n",
"knxprog = np.empty([1,12])\n",
"knxstick = np.empty([1,12])\n",
"path = \"workshop-physec/msmts-passive/\"\n",
"for i in range(1, 251):\n",
" switchA = np.vstack([switchA, calc_features(path + \"switch-a_1_1_4-\"+str(i)+\".csv\")])\n",
" switchB = np.vstack([switchB, calc_features(path + \"switch-b_1_1_4-\"+str(i)+\".csv\")])\n",
" linecpl = np.vstack([linecpl, calc_features(path + \"wzierl-lcpl_1_1_0-\"+str(i)+\".csv\")])\n",
" knxprog = np.vstack([knxprog, calc_features(path + \"wzierl-knxprog_1_1_105-\"+str(i)+\".csv\")])\n",
" knxstick = np.vstack([knxstick, calc_features(path + \"wzierl-stick_1_1_3-\"+str(i)+\".csv\")])\n",
"\n",
"switchA = switchA[1:,:]\n",
"switchB = switchB[1:,:]\n",
"linecpl = linecpl[1:,:]\n",
"knxprog = knxprog[1:,:]\n",
"knxstick = knxstick[1:,:]\n",
"all_vectors = np.vstack([switchA, switchB, linecpl, knxprog, knxstick])"
],
"execution_count": 17,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "yrkbBKQC85ud",
"colab_type": "code",
"colab": {}
},
"source": [
"color_switchA = np.full(250, \"xkcd:blue\")\n",
"color_switchB = np.full(250, \"xkcd:orange\")\n",
"color_linecpl = np.full(250, \"xkcd:purple\")\n",
"color_knxprog = np.full(250, \"xkcd:red\")\n",
"color_knxstick = np.full(250, \"xkcd:green\")\n",
"all_colors = np.concatenate((color_switchA, color_switchB, color_linecpl, color_knxprog, color_knxstick))"
],
"execution_count": 18,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "dnU72pX-85ui",
"colab_type": "code",
"colab": {}
},
"source": [
"### Hey hey, this is the program for loading the precalculated results I was talking about,\n",
"### only run this if you have the CSV file you need\n",
"#import csv\n",
"#all_vectors = np.empty([1,12])\n",
"#with open('all_vectors.csv', newline='') as avcsv:\n",
"# csvreader = csv.reader(avcsv, quoting=csv.QUOTE_NONNUMERIC)\n",
"# for row in csvreader:\n",
"# all_vectors = np.vstack([all_vectors, row])\n",
"# \n",
"#all_vectors = all_vectors[1:,:]\n",
"#color_switchA = np.full(250, \"xkcd:blue\")\n",
"#color_switchB = np.full(250, \"xkcd:orange\")\n",
"#color_linecpl = np.full(250, \"xkcd:purple\")\n",
"#color_knxprog = np.full(250, \"xkcd:red\")\n",
"#color_knxstick = np.full(250, \"xkcd:green\")\n",
"#all_colors = np.concatenate((color_switchA, color_switchB, color_linecpl, color_knxprog, color_knxstick))"
],
"execution_count": 19,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "AmS__sg485uo",
"colab_type": "text"
},
"source": [
"Alrighty, now we all should have the ``all_vectors`` and ``all_colors`` arrays at our disposal. Now we want to have a look at our data... but **oh no** it's 12-dimensional. Well, that sucks from a visualization point of view. So let's use a bit of very basic machine learning called Principal Component Analysis (PCA). PCA uses a form of unsupervised learning to try to find the \"best\" projection of a high-dimensional dataset to a lower dimensional space, i.e. one we can plot.\n",
"\n",
"Now that you are basically data-analysis experts, I believe you can do that on your own. There is a perfect explanation on how to implement PCA [on its Wikipedia page](https://en.wikipedia.org/wiki/Principal_component_analysis#Computing_PCA_using_the_covariance_method). I suggest you start reading up on that now, so we can wrap this up before nightfall.\n",
"\n",
"...Haha, kidding. Of course, like always, somebody else has done that for us already. Look at the [documentation of the library Scikit-Learn which includes a PCA implementation](https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html). Down on the page are examples which you should be able to adapt to our data. Write your code below, in addition to performing the PCA transformation, also please make a bar plot of the *Explained Variance Ratio* (EVR) that is a part of PCA's output (see: https://matplotlib.org/3.3.1/api/_as_gen/matplotlib.pyplot.bar.html). The EVR basically serves as an indicator of how much one might reduce the dimensionality without losing too much information (or specifically *Explained Variance*)."
]
},
{
"cell_type": "code",
"metadata": {
"id": "DE_RP_g785up",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 279
},
"outputId": "0044e781-f8fe-458d-aba3-60bd3d01f15b"
},
"source": [
"from sklearn.decomposition import PCA\n",
"\n",
"pca_xfrm = PCA() ### Standard options should be good enough\n",
"### Actually the all_vectors_reduced array still contains\n",
"### 12 dimensions but they are now transformed by PCA to maximize\n",
"### the explained variance in the lower dimensions, so\n",
"### to do the actual reduction we just ignore the\n",
"### higher dimensions during plotting.\n",
"all_vectors_reduced = pca_xfrm.fit_transform(all_vectors)\n",
"plt.bar(range(1,13), pca_xfrm.explained_variance_ratio_)\n",
"plt.xlabel(\"Principal Component\")\n",
"plt.ylabel(\"Explained Variance Ratio\")\n",
"plt.show()"
],
"execution_count": 20,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "c6FxOjH385uu",
"colab_type": "text"
},
"source": [
"You should now have an array with 12 Principal Components. Plot the first two in a 2D scatter plot (see:https://matplotlib.org/3.3.1/api/_as_gen/matplotlib.pyplot.scatter.html)! You should use the ``all_colors`` array as the ``c`` parameter for coloring the dots."
]
},
{
"cell_type": "code",
"metadata": {
"id": "uOcRz_O485uv",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 265
},
"outputId": "c288ca73-b95e-4ddb-e0e6-e8977235ba8a"
},
"source": [
"plt.scatter(all_vectors_reduced[:,0],all_vectors_reduced[:,1], c=all_colors)\n",
"plt.show()"
],
"execution_count": 21,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "AV382zbB85u1",
"colab_type": "text"
},
"source": [
"Ok, this might not actually look too great. :/ How about, we plot in 3D? Try it out using the instructions here: https://matplotlib.org/3.1.1/gallery/mplot3d/scatter3d.html"
]
},
{
"cell_type": "code",
"metadata": {
"id": "lV9gWXFm85u3",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 895
},
"outputId": "3cdceb83-b749-43a1-93c9-9971a81bd670"
},
"source": [
"from mpl_toolkits.mplot3d import Axes3D\n",
"fig = plt.figure(1, figsize=(12, 12))\n",
"pl3d = Axes3D(fig, rect=None)\n",
"pl3d.scatter(all_vectors_reduced[:,0],all_vectors_reduced[:,1], all_vectors_reduced[:,2], c=all_colors)\n",
"plt.show()"
],
"execution_count": 22,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x864 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nbvwmskP85u-",
"colab_type": "text"
},
"source": [
"Congrats, you made it through all the exercises! Actually, depending on the perspective, the 3D plot might also not look that well classifiable **but** I will show you that it's actually not that bad once we're all set. With the 3D plot it helps if it is interactive, unfortunately that doesn't seem to work too well with IPython, so I'll show you a interactive version which can *rotate* (wow) from my Laptop.\n",
"\n",
"Hope you had some fun and maybe learned something new. :)"
]
}
]
}
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