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authorJoshua Baer <joshua.baer@ost.ch>2022-05-15 15:36:08 +0200
committerJoshua Baer <joshua.baer@ost.ch>2022-05-15 15:36:08 +0200
commit2bba3b1d52604c9f671763927ec592a72b09088e (patch)
tree710dfd5f365f1b84b00432336f53cf113d71c578
parentMerge branch 'AndreasFMueller:master' into master (diff)
downloadSeminarSpezielleFunktionen-2bba3b1d52604c9f671763927ec592a72b09088e.tar.gz
SeminarSpezielleFunktionen-2bba3b1d52604c9f671763927ec592a72b09088e.zip
a few animations
-rw-r--r--buch/papers/fm/Python animation/Bessel-FM.ipynb193
-rw-r--r--buch/papers/fm/Python animation/Bessel-FM.py42
-rw-r--r--buch/papers/fm/RS presentation/RS.tex162
3 files changed, 397 insertions, 0 deletions
diff --git a/buch/papers/fm/Python animation/Bessel-FM.ipynb b/buch/papers/fm/Python animation/Bessel-FM.ipynb
new file mode 100644
index 0000000..9d0835a
--- /dev/null
+++ b/buch/papers/fm/Python animation/Bessel-FM.ipynb
@@ -0,0 +1,193 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 74,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ValueError",
+ "evalue": "operands could not be broadcast together with shapes (3,) (600,) ",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
+ "\u001b[1;32m/home/joshua/Documents/SeminarSpezielleFunktionen/buch/papers/fm/Python animation/Bessel-FM.ipynb Cell 1'\u001b[0m in \u001b[0;36m<cell line: 15>\u001b[0;34m()\u001b[0m\n\u001b[1;32m <a href='vscode-notebook-cell:/home/joshua/Documents/SeminarSpezielleFunktionen/buch/papers/fm/Python%20animation/Bessel-FM.ipynb#ch0000000?line=12'>13</a>\u001b[0m x \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mlinspace(\u001b[39m0.01\u001b[39m, N\u001b[39m*\u001b[39mT, N)\n\u001b[1;32m <a href='vscode-notebook-cell:/home/joshua/Documents/SeminarSpezielleFunktionen/buch/papers/fm/Python%20animation/Bessel-FM.ipynb#ch0000000?line=13'>14</a>\u001b[0m beta \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mlinspace(\u001b[39m0.1\u001b[39m,\u001b[39m10\u001b[39m, \u001b[39m3\u001b[39m)\n\u001b[0;32m---> <a href='vscode-notebook-cell:/home/joshua/Documents/SeminarSpezielleFunktionen/buch/papers/fm/Python%20animation/Bessel-FM.ipynb#ch0000000?line=14'>15</a>\u001b[0m y_old \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39msin(\u001b[39m100.0\u001b[39m \u001b[39m*\u001b[39m \u001b[39m2.0\u001b[39m\u001b[39m*\u001b[39mnp\u001b[39m.\u001b[39mpi\u001b[39m*\u001b[39mx\u001b[39m+\u001b[39mbeta\u001b[39m*\u001b[39;49mnp\u001b[39m.\u001b[39;49msin(\u001b[39m50.0\u001b[39;49m \u001b[39m*\u001b[39;49m \u001b[39m2.0\u001b[39;49m\u001b[39m*\u001b[39;49mnp\u001b[39m.\u001b[39;49mpi\u001b[39m*\u001b[39;49mx))\n\u001b[1;32m <a href='vscode-notebook-cell:/home/joshua/Documents/SeminarSpezielleFunktionen/buch/papers/fm/Python%20animation/Bessel-FM.ipynb#ch0000000?line=15'>16</a>\u001b[0m y \u001b[39m=\u001b[39m \u001b[39m0\u001b[39m\u001b[39m*\u001b[39mx;\n\u001b[1;32m <a href='vscode-notebook-cell:/home/joshua/Documents/SeminarSpezielleFunktionen/buch/papers/fm/Python%20animation/Bessel-FM.ipynb#ch0000000?line=16'>17</a>\u001b[0m xf \u001b[39m=\u001b[39m fftfreq(N, \u001b[39m1\u001b[39m \u001b[39m/\u001b[39m \u001b[39m400\u001b[39m)\n",
+ "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (3,) (600,) "
+ ]
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "from scipy import signal\n",
+ "from scipy.fft import fft, ifft, fftfreq\n",
+ "import scipy.special as sc\n",
+ "import scipy.fftpack\n",
+ "import matplotlib.pyplot as plt\n",
+ "from matplotlib.widgets import Slider\n",
+ "\n",
+ "# Number of samplepoints\n",
+ "N = 600\n",
+ "# sample spacing\n",
+ "T = 1.0 / 800.0\n",
+ "x = np.linspace(0.01, N*T, N)\n",
+ "beta = 1.0\n",
+ "y_old = np.sin(100.0 * 2.0*np.pi*x+beta*np.sin(50.0 * 2.0*np.pi*x))\n",
+ "y = 0*x;\n",
+ "xf = fftfreq(N, 1 / 400)\n",
+ "for k in range (-5, 5):\n",
+ " y = sc.jv(k,beta)*np.sin((100.0+k*50) * 2.0*np.pi*x)\n",
+ " yf = fft(y)\n",
+ " plt.plot(xf, np.abs(yf))\n",
+ "\n",
+ "axamp = plt.axes(np.linspace(0.1, 3, 10))\n",
+ "beta_slider = Slider(\n",
+ "ax=axamp,\n",
+ "label=\"Amplitude\",\n",
+ "valmin=0,\n",
+ "valmax=10,\n",
+ "valinit=beta,\n",
+ "orientation=\"vertical\"\n",
+ ")\n",
+ "plt.show()\n",
+ "\n",
+ "yf_old = fft(y_old)\n",
+ "plt.plot(xf, np.abs(yf_old))\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 72,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "# Number of samplepoints\n",
+ "N = 600\n",
+ "# sample spacing\n",
+ "T = 1.0 / 800.0\n",
+ "x = np.linspace(0.0, N*T, N)\n",
+ "y = sc.jv(3,x)#np.sin(50.0 * 2.0*np.pi*x) + 0.5*np.sin(80.0 * 2.0*np.pi*x)\n",
+ "yf = scipy.fftpack.fft(y)\n",
+ "xf = np.linspace(0.0, 1.0/(2.0*T), N//2)\n",
+ "\n",
+ "fig, ax = plt.subplots()\n",
+ "ax.plot(xf, 2.0/N * np.abs(yf[:N//2]))\n",
+ "ax.set(\n",
+ " xlim=(0, 100)\n",
+ ")\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 73,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+XbQn2rwOJxZr4/K7fVTheW/Sp2YfioqL+Pjwx3x+5HM+bv3xXXsBqthYcg4epDDsMkWRkWjy8kCjwdjZGTMvLywbN8aqZQtMqpW+n6GgoPBgoRj88ji1HAqztFUsdcTG3OSGH7/iG7caqeGDAx9wIvEEX7X/6j9jD+DoD3X6wIlfoP0kMLep8Pw3GRQ4iLjcOBacXYC/vT8v1nsRTV4emRs2kv7HSgovhgJgZG2NWY0aGNnaIIRAdf06uQcOkLZ0KZiaYtupI9Weex7rVi0rrYuCgsK9QTH4ZaHRaN053i219eorQCt/J34+EEFekRorM93f5u9CvmNL5BbebPomvfx73T2gzQRtLsDpFdqIIT0Y32g8ERkRzDn2DY33xWOxbAPFaWmYBwXh+s472HTuhFmNGnet/mVREfkXLpC9bTuZGzaQ/c8OrFq0wG3Ke1jUqaOXTgoKClWHQXz4QoieQogwIUS4EKLUEo9CiEFCCCmEKLHB7gPHtT2Qfg1ajK7wpa1v+PFPRunux98auZXF5xfzTOAzvFzv5ZIHeTfXfgEd/gGK9SuhIIRgqvXTfPOzxHT2Uoz8ffFdsZwaa1bjNOIVzP39Swz7FGZmWDVujNt7k6m1aydu779PYXg4154eTNK33yGLivTSS0FBoWrQ2+ALIYyBH4AngbrAMCFE3RLG2QITgaP6yrxnnFwClo5aN0oFaeZbDZMbfnxdiMiI4KODH9HQpSHvtXivzPh62rwOGVFwaWOF9bqJLCoiccZMkl8chauJA18/Y86cl52wbFJ6IldJGJmb4/jCcPw3bcS+Tx9Sf/qJqBdfQpWo9OZVUHjQMIRLpwUQLqWMABBCrAT6ARfvGPcZ8BXwjgFkVj3ZiXBpkzYyx8S8wpdbm5sQ7KWbHz9Plcebe97EwsSCWR1nYWpsWvYFtXuBg4+2iFtFGqbfQJ2cTMwbb5J/8iQOQ4bg+s47dIhaxdcnvmbTtU085f9Uhec0qVaN6l9Ox7p9O+I/+B/Xnh6Ez6JFWNSu/e8YKSUpMTkkXM0k8VoWWan55GYWoVFrEEYCKzsz7JwtcfOzo3qgA85eNhX68lFQUCgbQxh8TyD6lucxwG07eEKIJoC3lHKTEKJUgy+EGA2MBvDx8TGAanpwegVo1ND0pUpP0crfiQX7IsgtVGNtXvpbPeP4DCKzIln4xELcrN3Kn9jIGJq9oq3JnxymrZ+vI/nnzhHz2jiKc3KoPutr7Hv3BuD5Os+zI2oH049Op4V7i0oXXLPv3RvzgACiR40mavgLeP/4I2qfIC7sjyP8ZCJZKdqELys7MxzcrHDztcXEzJjiYg15mUXEX83gyvFE7VwultRu5U79jp5Y2phVSh8FBYX/qPJNWyGEEfAN8FJ5Y6WUC4AFAM2aNatkN3ADoNFAyFLwbQfOAZWeppW/E/P2XOVEVDodA0sutrb7+m7+vvI3IxuMpIVHC90nbzwcdk+D4z9Drxk6XZJz8CAxr0/AxNERv0ULb1t9GxsZ81nbz3h6w9NMOzqN7zp/p7sud2ARGIjfbyu4MOY9Nk3fQ7JzOgiBd51qNH3SD6+gatg6WpS6es9JL+T6xVQuH0vk2IZrhGyNol5HT5r38sPcqpy7HwUFhVIxxKZtLOB9y3OvG8duYgvUB/YIISKBVsD6B3rj9tpebR36ZqVsnOpIM7+y/fgp+Sl8fPhjghyDeK1h2SUb7sLaGer2hzO/Q2FOucOztmwh+tWxmHl74/vbituM/U387P14teGr7Ly+k4OxByumzy3kZhSyf2cWB71fJq1abXzj9zBkhBt9Xm9E3bbVsXOyLNNVY1PNnLptq9P/zcYM+6gltZq6cmZnNCs+OsKlI/FIef/WAgoKDzOGMPjHgQAhRA0hhBkwFFh/86SUMlNK6Syl9JNS+gFHgL5SyhMGkF01nFkJ5vYQVHFf9q1YmZnQ0NuhRD++lJJPDn1CTlEO09tNL99vXxLNR2pzBM6vKnNY5vr1xL41CcuGwfgu+xVT19LdNS/UfQFfO1+mH5tOUXHFom2klFzYH8uKj48QdiyBRl29eW5yAwIz9pM6cQxFMbHlT3IHjh7WdH2pLs9MaY69iyU7l4SybeEFCvOUDGEFhYqit8GXUqqB8cA2IBT4U0p5QQjxqRCir77z33OKciF0g3Yz1NRC7+la+ztxLjaT7ILbDdS6q+vYE7OHN5u+Sa1qtSo3uXcLcGug3bwtZdWbtXUrce9NwaplS3wWLcLYzq7MKc2MzZjSYgpRWVEsvbBUZ1Wy0wrYMOc0e1aE4epry7MftaTt0wHY1PTG5+dFyKIiYsaNQ5ObW6GXeBMXH1sGvt2U1gNqcu10Mn98cZzU2PLvbBQUFP7DIHH4UsrNUspAKWVNKeUXN459KKVcX8LYTg/06j50I6hyoeFQg0zXyt+JYo3kxC3x+Cn5Kcw8PpMmrk14ts6zlZ9cCGj+CiScg9iTd53O3rWb2LffwbJxY7zn/YCRhW5fYG0929LNpxsLzi4gMTex3PHXL6Ty5xfHiY/IouOwQPpNbIy9i9W/581r1sRz1iwKr1whbsr7SI1G99d4C8JI0KSHLwPeaYJGreHvmSe5fsFwZagVFB51lOJpd3J2pTbk0buVQaZr6lsNU2Nxm1tnxvEZ5Kvz+ajNRxgJPf8E9Z8GUyttCYhbyD16jNiJE7GoUwfvn37EyMqqlAlKZlKzSailmvln5pc6RmokxzZEsOH7M1g7mDHk/ebU7+iFMLrbP2/Tvh2ub79N9vbtpP3yS4V0uRP3GvY8/V4z7Jwt2fjDWS4fT9BrPgWFxwXF4N9KdgJE7IHgIWBkmLfG0syYRt4O/zZE2R+zny3XtjAqeBT+9v76C7Cw027env8birTljguvXiXm9dcx9fHBZ+ECjG0qXnPHy9aLobWHsiZ8DREZEXedVxUVs3XheY5viiSopTuDJjfDwa3sLxXHl1/CtkcPkr6bTf7ZsxXW6VZsqlkw8O0meNS0Z8cvFwk7qhh9BYXyUAz+rZz7C6QGgg3jzrlJqxt+/MTsTD478hk17Wsysv5Iwwlo/Lx28zZ0A+qUFKJHj0GYmeH9008YOzhUetpRwaOwNLFkdsjs247nZRWx9ptTRJxOpu3TtejyYh1Mzcrv3yuEwOPTTzBxdSF20tsU5+jngzezMOGp8Q2pHujAjiUXuXKifPeTgsLjjGLwb+XMH+DZFJwruYlaCq38ndBI+OLQd8TnxvNRm48qF5VTGr5twNEfzdGlRL86FnVaGt7z52Pm5anXtI4WjrxS/xV2Re/idNJpANITcvl7xgnSYnN4cnQDGnXzqVA2rLG9PZ5ff40qNpaETz/VSz8AU3Njeo9rqF3pL7lIzCXDdBpTUHgUUQz+TZLDIPGc1p1jYJr4VMPMMpE9Cat5OvBpGrs2NqwAIZDBzxL7x0UKLlzAc9bXWDaob5Cpn6/zPM6Wznx78luSo7NZMysEVWEx/d9qgn/jkpPJysOqSROcx44la/0Gsnft1ltHUzNjeo0NxsHVis0/niMlJlvvORUUHkUUg3+TC2sAofWHGxgLUyOqeW9BSAsmNJ5g8PkBUk9pyIm1xG1QE2y7dCn/Ah2xMrVidPBoYq6m8Pes4xibGDHw7aa41Sg7vLM8nMeMxjwwkISPP6Y4K0tvPS2sTXlqfEPMLU3Y+P1Z8rKUip0KCneiGPybXFgDvm3BVodaNhVkx/Ud5BlfIj/xCYypfNOS0sjZv5/kBUuxq29PtWonQaNfL907aSO60id0PHnG2QyY1KTczVldEGZmeHzxOeqUFJJmfm0ALcHW0YJeY4MpzFWxbeF5iosrF/6poPCoohh8gKRQSL5UqcqT5ZGvzmfm8Zl4WflTlN6CE5GG9TEXxcQQ+/Y7mAcG4vH+m4jsOG2kkYGIDk1j6/cXMbcz4s/aM7msvmCwuS0bNMDx5ZfI+Osvco8cMcicLj62dB4eRNyVDA6uCi9zrEYj2X8lmS82XeSZnw7T5es9dJm1h8E/HuKTDRfYfSkJtfKlofAIoRh8gAtrAQF1DJ8YvPj8YuJz4/mg9fuYGZtyJMJwBl9TUEDMhAmg0eA1ZzZGDfppS0Kc+8sg88eFZ7B53lnsXS0Z+m5rLOxN+OnsTwaZ+yYur7+Oqa8PCZ98arDGKYEt3GnY1Ztzu2NKjNwp1khWHrtOx693M/znYyw9HEWxRlLHw446HnZICb8fu87LS47T5stdLNofQYHKsHdNCgr3A6XFoZRad45fO4O7c2JzYvnl/C886fckbb1a0sjncKX63JaElJKETz6l8GIoXvPnYebrqz1Rrx+cXw29Z4GZdaXnT76ezabvz2DjaEHfiY2xsjPj5fov8/WJrzmddJpGro0M8jqMLCxwnzqV6NFjSPv1V5xGGiZctc3AmiREZLJn+SXc/Oywc7YEIDwpmzf+OM352CwaeTvwbo8gnqjrhoXp7WGlRWoNe8KSWHo4ks83hbLsSBRfD25Icz9Hg+inoHA/UFb4SaGQEgZ1+xl86q+Pf42RMOKtZm8B2vDM87GZZBXoX/gr48+/yFyzBufXxmLbufN/J4KHQFEOhG2p9Nxpcbmsn30aMysT+k5shJWdthb94MDBOFo48uOZH/VV/zZsOnTApksXkufNR5VomFh6I2Mjuo+oB8A/v1xAU6xh3elYnpp7gLiMAuYOa8ya19rQp2H1u4w9gJmJEd3rubNiZCuWj2iJRkqe+ekw3/xzGY3GwNU6NcWQmwL56drS3AoKVYRi8C+uBWFkcHfO4bjD7Li+g1ENRuFu7Q5AK39HNBKOX9PPrZN/9iyJn3+Odfv2OI8bd/tJnzZg5wVn/6jU3JnJ+aybfQojY0G/Nxpj6/hf/R0rUyuG1x3OwbiDhKWF6fMS7sJtynugVpM0Y6bB5rRztqTjc7VJiMjix3mnmLjyNMFeDmyd2J4+DavrnD/QLsCZrRM7MLCxF3N2XuH1laf0c/FICZEHYOOb8H1z+MwFZtaEr/xgWnVY0Al2fgaJhtsvUVCAx93g33TnGDg6R6VR8eWxL/G29eaFei/8e7yJTzXMjI30cuuo09KImTARE1dXPGfOQBjfsTo1MoLgwRC+E3KSKzR3Tnoh6747RbFaQ9+JjXBwvTsa55naz2BlYsWSC0sq/RpKwszbG6eRI8natIm848cNNm9gc3ekrxXFFzJ4uoYLy0a0wNWu4lVQrc1N+HpwMFOeDGLzuXhGLD1OflEFjb6UELYV5rWGJb3h7J9QrQa0exOenAE9pmk7mZlYwoFvYX4bWNoHYh7cWoMKDxePtw8/+RKkXIYWow067e+hvxORGcHcLnMxN/6vH66FqTGNfRwqvXEr1Wpi35pEcXo6fr//VnrZhOAhWoNxYTW0HKPT3PnZRayffYqCXBX932yMk2fJ4aN2ZnYMChzE76G/M7HJxH/vXgyB0+hRZKxeTeKMmfj9sRJhgHpGSw5eY05GKuPMrWiSIDGRle+RK4RgTMeauNiaM+mvM4z69QSLXmxWokvoLrITYN04CN8BjjWh/3xtzodZKSGuualw6lc4PA8WdYVGz0PPaWBhX2n9AQrUBYSmhRKREUFWURYSSTXzatR0qEmQYxBmxkoryUeZx9vgX9qo/a1no5NbSclPYf6Z+bTzbEdHr453nW/l78TcXVfIzFdhb1mx8grJs2eTd+QIHtOmYVG3bukDXeuAewNtIxcdDH5hnor1c06TnVpAnwmNcPUtO6lqeJ3h/Bb6G8suLuOd5obrSW9kYYHLxInET5lC9tat2PXqpdd8Oy4m8vGGi/So70afYF+2zD/HiS2RtOyrX9G6gU28kBLeXnWGSX+eYe6wxhiVUCH0X67ugr9Haovb9fxS27imvNIa1k7alX/zkbBvJhz6HiL3wdOLwatizeKklByMO8hfYX9xOP4w+er8EsdZmljSybsT/Wv2p3X11koD+UeQx9zgb9bWzrHzMNiUs0NmU1BcwOTmk0v8wLTyd2L2ziscv5ZGt7q6u5Gytm8ndeEiHIYOwWHggPIvCB4C2z+AlCtl9uUtKlCz8fszpMXl0uu1YKoHOJQ7tYeNBz38erDq8irGNByDnZl+Wbe3Yt+3D2lLlpD0zbfYdOuGkVnlVpxXk3N484/TNPC0Z/bQxliYGlO7lTshW6Pwb+yCi7etXnoOaupFWm4RX2wOxdvRiveeDCp5YMivsOENcAmCwYsr1HAeAHNbeOJT7aJk1QhY/CQM+BHqD9Lp8iPxR5h5fCaX0y/jbOlM35p9aVu9LQHVAnC00EYcpeSnEJYexuG4w2yP2s6Wa1uo51SPCU0m0KZ6m4rpewfq9HTyz5xBFRdHcVo6wtQUY3t7zGvVxDyoDsY2lY8kU6gEUsoH8qdp06aySsmMlfIjOyn3fW2wKc8knZH1l9SXs07MKnVMfpFaBkzdLD/bcEHneQuuXpWXmjSVEc88I4sLC3W7KDNOyo8dpNz5ealDVEVqufbbEPnDqztl+MlEnfWRUsrQ1FBZf0l9uejsogpdpwvZ+w/Ii7WDZMrixZW7vkAlu3y9Wzb+dLuMSc/793h+TpH85Z39cuXnR2WxulhvPTUajXx/9VnpO3mj/OtE9N0DDs7R/o/9OkDKgiy95cncVCl/7qmd89APZQ7NKsySk/dNlvWX1Jc9V/WUa6+slUXqonJFFKmL5N+X/5Y9VvWQ9ZfUl5P3TZZp+WkVUlOdni5Tl/4qIwYMlBdrB5X+U7+BjHr5FZm+Zo3U6Pp/rVAuwAlZil0V8gFtCN2sWTN54kQVblYdXwSbJsFrR8G1lNVZBdBIDc9teo7EvEQ2DNiAtWnpK5ehCw6TU6hm4+vty523OCeXyCFDKE5Pp8bqvzF1r4DP/Nf+kBYBE89ou2PdOm+xhq0/nSfybApdX6pDUKuK3+WM2j6KqxlX2Tpoq8F9v9dHjCT//Hlqbd+GsX3F/Nbv/X2WP05Es2JkS9rUdL7t3NVTSWz96TztBgfQsKu33nqqizUM//kYp6LTWTuuLUHuN+52bv5/1RsAAxeW78LRFVUBrBkNF9dBj+nQ+rW7hlxMvcikPZOIz41nVPAoRtQfgYVJxTaqC4sLWXRuEYvOLcLJwolZnWbR0KVhmdcU5+SQ9sti0pYsQZOXh0W9etg+0Q2rZs0w8/XF2NERWVxMcWoqhVeukHv0KNk7dqCKuo6xizPOo8dQbegQhGnF3iuNRpJwNZPrF1NJic4hIymPonw1UmprLNk5W+Dqa4dXUDU8ajmU7X57BBBCnJRSluj3e3yjdC5t0m6eVfQWuxTWhq/lfOp53mz6ZpnGHrRunQtxWWSW04hbSkn8Bx9QdO0ant/MqpixB61bJyMKYm6PetFoJDuXhBJ5NoUOQwMrZewBXq73Msn5yWyL3Fap68vC9Z230WRlkfpzxbpj7biYyMrj0YzpUPMuYw/g38gF3/pOHN0QQW5God56mhgbMXtYI2wtTHltRQg5hWo4t0pr7AOfNKyxB22f5UE/a8OIt02BYwtvO70/Zj8vbnkRlUbFkp5LGNdoXIWNPYC5sTnjGo1jRa8VmBiZ8NLWl1gbvrbU8dl79hDR+ylS5s3Dun17aqxZTY2/V+H86qtYNWuGiYsLwtgYIzMzTD08sOnQAbd33qHm1q14L1qEuX9NEr/4goj+A8g7dUonHfOyiji2IYKl7x1kzawQTm27Tk56IS7etvg3dqVmE1ecPG3IzSjk5NYo1n5ziiXvHeTo+ghyM7V/eyklcRn5HApPYfO5eDaejeNQeArRaXk8qIthfTDICl8I0ROYDRgDi6SUX95x/i1gJKAGkoFXpJRRZc1ZpSv8gkyYURNajYXun+k9XVZRFn3W9MHXzpelPZeWu9l1JCKVoQuOsPCFZjxRhh8/9ZfFJM2YgevbkyqXgVqQBTNrQbOX4cmvAO0/+J7fwri4P47WA2rSpIdvxee9gZSS/uv6Y2FiwcreKw2+yRf71iSy9+yh1o5/MHEsP8M1LbeI7t/uxdnGnHXj22JuUnL0TGZyHr9/cgz/Rs50H2mYMtJHIlJ5duERXg/K4s3rE7Ubq8+v1hroqkBdBH++AJe3wtAVENSbDVc38OHBDwmoFsC8bvNwtrz7C68yZBZm8vbetzkSf4SJTSYyov6If//WsqiIhOnTyfh9JeYBAXh8/hmWDcu+EygJKSU5u3eT+PkXqBITcX71VZzHvoowuXubUVVUzKnt1zm1PQp1kQbf+k7UbuWObz0nzCxL3pYsKlATdT6Vy8cSiTyXgjASpHtbsEmVS1xuyV/8LrbmtK3pRP/GnrQPcMH4IbkzKGuFr/emrRDCGPgBeAKIAY4LIdZLKS/eMuwU0ExKmSeEGAvMAAxfeF5XrvwDGhUE9TbIdPNOzyO9IJ0fu/2ok9Fr5O2AmYk2Hr80g5975ChJs2Zh+8QTOI4YUTnFLOwgsLs216DHNKQw4uDf4VzcH0fTnr56GXvQhik+V+c5PjvyGWeSzxis3MJNnMePJ2vrVlIXLsJt8rvljv9iUyiZ+SqWjWhZqrEHsHexoumTvhzbcI06bdPwrqN/uYRW/k5MbutAv+PjyLN2xuqZZVVn7AFMzODpX2DpU/D3SDb3/B9Tz/9Ic/fmzO48Gxszw1VltTe3Z17XeUw9OJXZIbPJKcphYpOJFKekEDPxDfJDQnB85RVc3phY6U12IQS2Xbpg1bw5iZ9/QcoPP5B/KgTP777D2O6/oID48Ax2LLlIVkoBNZu40rJvDaq5l7/xa2ZhQq2mrlw20/BPVhrVY4uoFyl5xswYu/Y1CGrsiqONGQJBak4h11JzOXYtjb2Xk1l7Og5vR0te7xzAwCaemBgbwDGiLtQm38WFaHtx5Kdrj1nYg40beDbRdrIzMIaI0mkBhEspIwCEECuBfsC/Bl9KeWuXiyOA4V9JRbi0CaxdwKu53lNdSb/CyksrGRw4mDpOdXS6xsLUmKY+1UpNwFLFxRH75puY+fnhMX26fivn+oMgdANEHuDYeW/O7IgmuLMXLfsZoJ8u8JT/U3x38jtWhK4wuME396+BfZ8+pP/2G44vvYSpm2upY49GpPJ3SAyvdapJHY/yo4Yad/fh0pEE9q28zNAPWmBsqueHuFjNqMRPKRT5vFT4AfOkDU76zVg+ZlYw9Hf2Lu3G1HPzaOrSkB+6/lApF055mBqb8mX7L7ExteHn8z/jkFZIu692oE5Jofqsr7HvbZjFk7GtLdW/+hKrFi2I//hjIocOw/unHzHx9OL4xmuc3BKJrZMF/d9sjGftajrPG56Uw7urzhByPYPabrZ0eakuLWytOfTHFVJ3JqBSG1NrUC1MzIwBW9rUcua5lr4UqTX8czGRBfuu8u7fZ1m4P4Kvng6miY/usm8j9iQcXaD9TKpytcfsvbX2yMRcu+cWuV/7JfCAGnxPIPqW5zFAyzLGjwBKLPQihBgNjAbw8fExgGoloC7UrvDr9QcjHRJmykBKyfRj07E2teb1xq9X6NpW/k58t/MymXkq7K3+8/FqCgqIeX0CUqXCa+5c/cPWAnqAmQ0h685yIqyYOm09aDc4wGDuFytTKwYGDGR56HISchMMmogF4DzuNTI3bSJ1wQLc//dBiWNUxRr+t+48ng6WvN6l9BDUWzExNabD0EA2zj3DmV3Ret/tsH8WRtFHyOgym1Pb3Ji65jw/Dm+q35w6cK4giUn2pgQW5DE3OR0LIwPuF9yBkTDig1YfYB6TQsCUJeRjQa1fl2IZHGxwWQ6DBmLq7UXs6xO4OvwVwp/6jOvheQS1cqf9kMBSXTd3IqVkyaFIvtxyCSszY74a1ICnm3r/657xfK8ZR9Zd5fSOaJIis3jy1WBsqv2XLGlmYkTvYA96NXBn24VEPt1wgUHzDzGibQ3e7RmEmYmOC4WEc/DPh9qcDDMbaPC01sPg01p7J3670lCUq9u8FeSebtoKIZ4HmgElFkyRUi6QUjaTUjZzcalc+7xyidwPRdkGSbbaFrWN4wnHeb3x6zhYOFTo2lb+jkgJR6/9t8qXNypgFly4QPUZX2HuX0NvHTGz4qzlRA6H1SOgqQudngtCGNgXOTRoKBqp4c+wPw06L4CZjw8OAwaQ8eefqOLiShyz+OA1Lifm8HHfeljq0Ez9Jr71nPALdubElkj9OmRdPwp7v4IGz+DR4SXe6h7I1gsJbLuQUPk5dSA5L5k3dr+Bs5Ur8xu/jU3kQdg9rUplqmPjGDD7FBZGZrw3RM1hh5Qqk2XdogUuPy7mmO/LXL+SQ+su1ej6Ul2djX2BqpgJK0/zyYaLtK3lzLY3OzCkuc9tvnhjUyPaPh1Ar9eCSU/IY9WXx0m+fneLTCEEPeu7s/2tjjzf0pdFB64xZMFhEjILylZClQ/bpsKP7SE2BLp/Dm+FQt85ENjjbmOvFQbmhm+UBIYx+LHArfFtXjeO3YYQohswFegrpdQ/PKKyXNoEptbgf3cWbEXIU+Ux68QsalerzeDAwRW+vqG3A+YmRreVWUj//fcbFTBfM1ibwosH49gf1owa5kfp2i6uSkLSvGy96OTdiVWXV1FYbPg/rfPYVwFImX93lc7UnELm7Ayna5BrmRvgpdF2UC2KizQcXR9ROeUKs2H1SLD3hN7azl0j2tUgyN2Wj9Zd0EbtVAGFxYW8sfsNslXZzO48G8dmI6HJC7D/a7iyo0pkqlNSuD5iBFKlotay37CrU5/39r9HaGpolcjLSS9k89pMCuw8aBy1HJvvxlMUGanTtcnZhQz56TAbz8YxuWcQP7/YDFfb0l1dNYKdGfhOU4SxYO03IcSHZ5Q4zsbchM/612fec024nJDNU3P3czam5LEknIOfOsDh77WBExNPQ5vXSzby9whDGPzjQIAQooYQwgwYCqy/dYAQojHwE1pjn2QAmZVDo9GWDa7VBUwt9Zpq0blFJOQmMKXlFIwr4RqyMDWmyS1+/LyQEBKnTcemY0ecx48r52rduHw8gd3LL+Ed5EAP90UYh/5tkHlL4rk6z5FemM6Wa5Uvy1waptWr4zB4MBlr1lAUc/taYu6ucPJVxUzppdv+yZ04uFnRoJMXoQfjKtf8fNfnkBENAxb8W+fG1NiIaQMbkJhdwDfbL1dKr/KYcWwGZ1PO8kW7L6jteCO0+MkZ4FoX1r2mrcVjQIpzcrk+ejTqpGR8fvoR+9r1mNNlDvbm9ozfNZ6UfMOu9LPTCljzTQi5mYX0mdiYpvM+Aim5PnIU6uSyiwImZRUwdMFhLifm8OPzTRnbqaZOLkxnLxsGvt0UK3tz1s85TfSl0mte9Wrgwdpx2kiwYQuOcCj8jtd/YQ383F27IBi+Bp76Fiwr6fc3IHobfCmlGhgPbANCgT+llBeEEJ8KIW7WHJ4J2AB/CSFOCyHWlzJd1ZJwBrLjobZ+NVrC08NZfH4xfWv2palb5f20rWs6EZqQRUr4NWJen4CpZ3Wqz5xhkKJhl48lsOOXi1Sv5cCTrzXEuF4v7d1NUZ7ec5dEC/cW1HKoxW+hv1VJ/LLT6FEIIUhd+F/ceWRKLsuPRDG0uTe1XCt/C9ystx9mViYc+Cu8YrrHnISjP0HzEeDb+rZTTXyq8WwLH5Ycusb52MxK61YSO6N28uflP3m53ss84fvEfydMLWHgAshLg01van3BBkBqNMRPeY/CsMt4zf4Oy0aNAHCxcuH7Lt+TWZjJ5H2TKTZQL+X8nCLWzz5NQY6KvhMbUb2WA+b+NfD+cT7q1FSujx5DcU5OidfGZ+YzZMER4jMLWPJyc3rUq9iekq2jBf3faoydsyWbfjhL3JX0UscGuNny99g2eFaz5KXFx9l+IUH7nu+bCX+9pK1nNXov1DTM3bohMIgPX0q5WUoZKKWsKaX84saxD6WU62887ialdJNSNrrxY/hegrpweTsgIKB7pafQSA2fHvkUazNrJjWbpJc6rfydsCwqIPa1cUiVCu/5828LQassl47Es2PxRaoHOPDU+IaYmhlD/ae1jVGubNd7/pK4GaIZmhZKSFKIwec3dXfHfuBAMlevRpWg9Y3P3BaGmYkRE7vptlFbGhbWprR4yp/YsHQiz+q4Ui1WwfrXwdYDun5U4pB3ewbhaG3OB2vPG6xpSkJuAh8d/oi6TnVLDhRwbwCd39dm4p41zJ5K6k8/kf3PDtzefQebDh1uO1fbsTYftPqAYwnH+OH0D3rLUhUWs+mHs2SnFtD7tWDca/yXZW3ZsCFes7+j8PJl4ia9jSy+/QsmLbeI5xYeJTm7kGUjWtDSv3JxUtb25lqj72TBph/OlujTv4m7vQV/jmlN3ep2jPvtJNf/eFt71xc8BF7cYPAuevryeGXaXtmmLZZmXfmElDVX1nAq6RSTmk76t/hUZQn2sOb9k8sxiYnCa/Z3mPvrHyoZeiiOnUtD8axdjd7jG2JqfsPd5NcOrF3hfNW5dXr798bOzI7fQn+rkvmdRo1CajSk/vwLZ6Iz2HQuntEd/Mv0zepKvQ7VqeZuxcFV4RSrdeg6dWguJF3Q+u1L8cnaW5ry3pNBnI7OYN2Zu7a1KkyxppipB6ZSVFzEV+2/wrS0DN62E8G7FWx+BzL1k5u9ezfJc+Zi368v1V54ocQx/Wv1Z0CtASw8t5D9MfsrLUujkWxbdJ6kyCy6j6xXYiE/mw4dcJv6Pjl795I8Z+6/x/OLihmx9DixGfksfrk5TX31+2xa2pjRZ0IjzCxN2DD3NBmJpd8ZO1iZsfTl5nxrswKfS4tICHwe+v+oDbN8wHh8DH5OsnaXPLBHpadIyU9h1slZNHVrSv9a/fVWKePrr2macIlV7Z/FunXr8i8oh4sH4ti17BLedRzp/VqwdmV/EyNjbV2Xy9u0GbhVgKWJJQMDBrLz+k4Scw3TqvBWzLw8se/bl4w//2Th+hM4WJkysr1h8gmMjbXRGpnJ+ZzfW46RzIyFvTO0kV7lJO8NbOxJQy97vtoSRl6Rfhu4v136jWMJx5jSYgp+9n6lDzQyhgHzobhIa/Qr6dopiokl7t3JWNSti/snn5TpB3+/5fvUrlab9w+8X2l//pG1V4k6l0qHoYH4Nyo9Sq/asGE4DB5M6k8/kbV5M8Uayeu/n+J0dAazhzY2WN9hW0cL+k5shJSwYe5p8nNKj+SyP/g5TxVu4g+zAXS99BQXEiqxH3QPeHwMfvg/gNTLnTPz+Ezy1fl82PpDvePY05YuJX35cqK69GOJYyMy8vQICwRCtkexe/klfOo60mtsgxsJJHfQ4GkoLoSwzXrJKoshtYdoQzQvGz5EE7S+fI1KheuWvxnV3h8bc8NV+Pap54hXUDVObImkKL8M47zjY5AabYeqcjAyEnzYpy4JWQX8uOdqpXWLzo5m7qm5dPTqqNtiw9EfOk+BsE0QWvEtM6lWE/eO9svCc/Z3GFmUfRdlYWLBjA4zyFfn87+D/6vwPs7l4wmc2n6deh08qd/Rq8yxQgjc//cBlk2aEPf+VH5cvI0doYl80rcePesbNg+kmrs1vV8LJjejiK0/nS/57u/gHDg4G5qPpONr87GzNGPEkhPlh2zeBx4fg39luzZl2b1ySSI7r+9k87XNjGowCn97/VaVmevWkTj9S2yfeAKnSZOQksp3wdJIDq66wuHVV6nVzJVeY4MxKa0Dk1dzsPfRFveqIrxsvejo1ZFVl1dRVKzfl1hJmNeowaWgFvSJPMRzdfTr/nQnQghaD6hJQY6KU/9cL3lQ9HE49ye0GQ/VdEvWaurrSN+G1flpXwQx6RXfNJdS8smhT/5NfNJ5sdFqnNanv/ldyM+okMyU+T+Sf+oU7p98jJlX2Qb4Jv4O/rzV9C0OxB7gjzDdeyonX89m96+X8KhlT/tndNuPEWZmeM3+DpW5JbXmT+eFxq680NpPZ5kVwd3fns7Dg4i7ksG+lZdv/zI7/Rv88z/t3fOTM3B3sOTnF5uTXaBixNLj5FZRWG5leTwMfrEKwndBwBPanq8VJL0gnU8Pf0qQYxCjGozSS5XsPXuIe38qVi1bUv3rmQT7OmJhWrk+t8XFGnb+GsrpHdE06ORF91fqYVxW5p8QUH8gROw2eNjerQwLGkZaQVqVVNE8F5PJd+7tsFAXUfSH4fcKXH3tqNXMldM7rv9bUfFfNBrY+p524dDurQrN+96TQQgBX265VGGd1oSv4WjCUd5q+lbFMpmNTaDPHMhN0t6V6EjeiROkzJ+Pff/+FS6ZMCxoGG2rt2XWiVlcy7xW7vjCfDVbF5zDwsaUnqMblP3/ewdXiy34vNFQvHKSGX1qTYX0rCi1W7rTtKcvFw/EcXZXjPZg1CFYPwFqdIQBP/2buV+3uh3fP9uE0PgsJq48bbANe0PweBj86KNQmKktM1AJPj/yOVlFWXzR7ovSN8p0IC8khNg33sSidm28fvgeI3NzzE2Maepbel2d0ijMU7Hph7OEHUmgRZ8atB8SoFsGbf1BoFFX6jZfV1pVb4WfnR8rL600+Nyzd14h080by65dSV+2nOIsw+9HtOzrj0YtOb4p8vYT51dB7AltVE4FMyGrO1gypkNNNp6NJ+R66aF+d5KSn8LXx7+mmVszng58ukIyAW0RrpZj4eRiiDpc7nBNbi5x703B1MsLtw9KLmVRFkIIPm37KeYm5kzZPwW1pvQVrpSSvSsukZ1WSPcR9bCy073wWk6hmleXnyTCpy5WI0aSvXYNmevWVVjfitCyrz81Gjpz8O9w4k6HwR/DwcEHnll61wZt5yBXPuhdlx2hiczbE16lelWEx8PgX94GRqZQs3OFL916bSvbo7YzrtE4AqsFVlqFvFOniB41GlM3N7wXLsDY5j+D0drfiUsJ2aTn6uYCyUjK4+8ZJ4m9lE7n4UE0711D99t89wbgFFCl0TpGwoihQUM5m3KW8ynnDTbvhbhMdoQmMrJdDdzHvYYmJ4f0FSsMNv9NHFytqNe+OhcPxP0XnaEq0K6SPRpBw2GVmnd0B3+cbcz5cvMlnX3cs0Nmk1+s3TcyEpX8uHZ+X1uga9MkKC7bxZD03WxUsbFUn/ZFpes4uVq58kHLD7iQeoFlF5eVOi70UDxXTiTRok8NPGo5VEjGR+suEJWay/fDGuP35gSsmjUj/pNPKYwo/66isggjQdeX6mLnZMa2RaHkFVnCsJWlJlS93NaPfo2qM+ufy+y7XHay2L3i8TD4V7aDbxttf9AKEJ8Tz2dHPqOBcwNeqvdSpcXnhZwieuQojJ2d8Pl1KSZOt8cHt7oRL3z0Wvl+/NiwdFZ9dYK87CL6vtGIum2rV0wZIbSbt5EHICu+YtdWgH41+2FlYsXvl3432Jw/7Y3AxtyEF9v6YVG3LjYdO5K2ZCmaXMMXmmrWuwYmpkYcWXdjo/XEz5AVq+2fUMnEOGtzEyZ2C+BYZBq7w8pPOD+TfIa14Wt5oe4L1LDXo66SuY12gznpgvZ1lELeyZOkL19Oteeew6pZxRql30kPvx509u7MD6d/ICrr7tYXafG57F95Ga+gahUuXLfudCx/h8QwvksALf2dECYmVJ/1NUZmZsS98w5SVXZjIX0wtzCmZ801FKrN2W40G41T6XsOQgimD2xAbTdbJqw8RXRa1SQ9VoRH3+CnR0HypQqHY6o0Kt7Z9w7Fspgv23+JiVHlokHyQkKIHjkSE2dnfH/9FVO3uxMxgr0csDQ15tDV0sPZpEYSsi2KdbNPY2VrxuD3muEZWMlU7fqDAAkX11bueh2wMbOhb82+bLm2hbSCym1I30pMeh6bzsUzrIU3dhZat5rz2FcpzswkfaXuG4S6YmVnRqMnfLgakkxCWDzsnwX+naBGh3KvLYuhzb2p4WzNV1vCKC7Dt1usKWba0Wm4WroyJniMXjIBqNMH/DvDri+0Icp3oCkoIP79qZh6euL65ht6ixNC8EGrDzAzMuOjQx+hkf9FtxSrNWz/+QKmFsZ0e7luheo7Rafl8cGa8zT1rcaELrX+PW7q5ob7J59QcOFCiTWXDEbIrzhHLqRjyzhirwuObyz7jsLKzIQfn29KsUby2ooQClSGyUauLI++wb+ZWVpB//33p77nTPIZPm79MT52lSvVnL1rN9dfGYGJqys+pRh70JZgbVHDkQN31uO4QUGOik3zz3J4zVX8GzkzaHIz7F2sKqUTAM4B2milKozWARhWZxgqjYq/L+vvPvr5wDUE8HLb/1a6lo0aYdW6FalLFqMpMHwIXKNu3ljamnJ4+VFkbip0+VDvOU2NjXinR23CErNZHRJT6rjV4au5mHqRt5u/jZWpHn/rmwihrbWjyoWdH991OnnuXIqiovD47FOMrPUsyX0DVytX3m7+NicTT7Lq8n//ayc2R5Iak0Pn54Owttc9OalYI3njj9MAfDek0V2NSOx6dMe+X19SfvqJ/LNnDfIabiPxAmx5F/w7UefFl6jTxoMTmyOJvlj2gsbP2ZpvnmnEudhMvtpa8U17Q/J4GPxqNcCpps6X7Inewy/nf2Fw4GB61uhZKbHpf/1FzPjxmNeqhe+K5WU27wBoH+BMRHIucRn5tx2PvZzOH9OOER2aRvshgfQYVR9zHcvDlkn9QdoNyPRI/ecqBX97f1p5tOKPsD/K3Lwrj8w8FX8cj6Zvw+pUd7i96J3zmFcpTk4h42/D70mYWZjQ/AlX4pLtuO76KngZpr79k/XdaejtwDf/XC5xxZdRkMHskNk0c2tGT7/K/f+ViEsgtHoNTi2HmP/ahxZcukTa4iU4DB5skATAWxlQawAtPVryzclvSMhNIDEyi5Nbo6jdyp0aDStWAv3Xw5GcjErn0/718HYs+UvQbepUTFxdiXt3Mpr8/BLHVIrCHG19HAt7bZ9iI2PaDw2kmoc1O5ZeJD+77P23J+q68VIbPxYfjGRnqOGTEnXl0Tb4RXlwbZ/WnaPjpubl9MtM3jeZuk51ebd5+W317kQWF5P0zbck/O9DrNu2xXfpkrt89iXRLkBb7uHAFe0qX1VYzP4/LrP2m1MYGxsx6J2mBHf2Mlzf2PoDtb+rcPMW4NmgZ0nMS2R39O7yB5fC8qNR5BUVM6rD3fkPVi1bYNm4Mak//4wsMnzcf13NcuyM4zmc1Ntg4XVCCN7rGUR8ZgG/Ho686/xPZ38iuyibKS2nGLxPMB3fBRt32Pw2aDTaHgyff46xvT2ub+tXG6okhBB83PpjNFLD5we/YOeSi1jZmekcb3+T2Ix8Zm4Lo1NtF/o38ix1nLGdHdWnfUFRZCRJX8/SV/3/2PIupFzRGnsb7eLN1MyY7iPqUZCrYtey8jfip/QKoq6HHW//dYbErPuTlPVoG/zI/aAu0Dm7Nq0gjQm7JmBtas2cznMq3CquOCOD6DGvkrpgAQ7PPIP3vB90vj2u7WaLi605+8NTiA5N44/Pj3F2dwzBnb0Y8kELXH0NXEPbwQe8W8K5qjX4Hbw64GnjWenN20J1MYsPRtIh0KXE1oVCCJxfHYM6Lp7MDRv0Vfd2suIxPrGAVvUiSU1Uc+WY4RqatK7pRKfaLvyw+yqZef9tMsbmxPJH2B8MqDVAr6iwUjG31W48x52CU8vI2ryZ/BMncXnzDYztDZvIdhMvWy/GNxpP4RE70hPy6Dw8CHMr3cObpZR8uPY8UsJn/eqX+yVo3bo11V4YTvqKFeQcPKiv+toqs6dXQIe37+qj4exlQ5sBtYg8m1JuSQ5zE2PmDGtMgUrDGytPl7mHU1U82gb/8jZtsxO/duUOzVPlMWHXBFLyU5jTZQ5u1hWrcpd/+jTXnh5M3tGjuH/6CR6ffoIw1f2fWghBJ69qmB9NY/3s00ig/5uNaT8k8L8CaIamwWBt5EbihaqZHzA2MmZI7SEcTzjO5fSK14ZfeyqWlJxCRpdRM8e6QwfM69YhZcGCuyoo6sWhOVCsotYzw3DxseXo+msUq3QorKYj7/YIIqtAxby9/8Vp/3DqB4yEEWMbjjWYnLtoMBh82qDZ+glJX32FRd26OAwaVHXygC7mT9EwrgvXqofgFFCxomKbzyWw81ISk7oHlurKuRPXt97CzN+f+KkfUJytR12bvDTY8IY2nLlDyXf8wV288KnnxMG/w0mNLbls801qudrwSd96HI5I5ce9lS+1UVkeXYMvpbZ3rX+ncqvWFRYXMmHXBM6nnOer9l9R37m+7mJUKpJmzyby2eeQmmJ8l/1KtWeeqZCqBbkqDq+5it+xLLwKoEbn6gz7sEWFmjRXirr9QRjDub+qVMyAWgMwNzavcCKWlJKF+69R18OOtrVKd4sJIXAe8yqqqOtkbdmqr7paclPgxGIIfgbh7E/rATXJTivg/D79q17epG51O/o38mTJwUjiM/MJSwtjY8RGnqvzXIUXHBVCCHjyK1JOqlAnJeP2wQcI4ypaVKCNytn/2xUs7I3Z7fUHc0/NLf+iG2Tmqfho/QUaeNrzUhs/na8zsrCg+pfTUSclkTj9y0pofYPN70B+OvSfDyYlJ4YJIej6Yh3MLIzZ/vMF1EVlLzoGN/PiqWAPvvnnMqejMyqvWyV4dA1+8iXIvA6BZbtzCtQFvLXnLY4mHOWztp/R1berziLyTp3i2pAhpM7/Efu+ffFft+7f5hC6UJCr4tjGayybeoiQ7VF4N3DiZ7tCot1NS6+HY0hsXLTNGc6t0pYNqCIcLBzoVaMXGyM2klmoezOQg+GphCflMKJd+Ylltk90w6xmTVJ/+glpiNdy+AetO/BGCQXvOo5416nGic2RFJZVWK2CvPVEIBopmb3jCt+FfIetmS2v1H/FYPOXRlGRPWlhttj75WPlWbVlfE9tv05aXC7dnq/PwLr9+f3S7zon5H25NZT0vCKmD2xwV1ROeVgGB+M0ahSZq1eTvbsSe0gX12mzqztO1q7wy8DKzoyuL9YlLS6XQ2vKXrkLIfhiQAPcbM1584/Td1VR3RO9h30x+yqurw48ugb/8o06LmX47zMLMxnzzxj2x+znf63+R5+afXSaWpWURNzk94ga9izFKal4zplN9S+nY2yrW2JXekIue38LY+mUgxzfeA2vOo4M/aAFfV8Nxt3dutTwzCqhwWDIjNaWn6hChgUNI1+dz7pw3dPflxyKxMnajKcaepQ7VhgZ4TxmNIVXrpCza5c+qmpXdMcWQt1+2siWG7QeUIuCXBWntt+dSFRZvB2teL6VL6su7uFA7AFGNhiJvXnV+NJvJfHLrxDmFri0kLB1ssG6Y91JRmIeJzZHUqupK34NnJnQZALOls58evjTciO3jkSk8vuxaEa2q0F9z8q9J87jXsM8MJD4Dz9Ena57SQtyU2DjW9rM6nZv6HSJb30ngrt4cW53DFHnyy6VYm9pytfPNCQyNZcvNv3XEzgxN5EPDn7AvNPzbstdMBSPrsG/sl37rWxXcibqtcxrvLjlRc6lnGNGxxk8U7t8N4wqPp6Ez7/g6hPdydq8GafRo6m5ZTN23cvfFC7MU3HxQBxrZoXw28dHCT0UT0AzN4Z80IInxzTAyVNbaqFdgDPHrqXduwSNoN5gaqWtAFmF1HGqQ2PXxqwMW6nTP3J0Wh47LyUyrIUP5ia63e3Y9eqFqbc3KT/+pF+bxWMLoShbu0l3Cy4+tgQ0c+XMzui7C6vpwbhONbFw3YoZjgwLqlzZhoqQs28fObt34zxuHKZPfaCNZKuC2kpSSvasuISxqRHtbkTl2JrZMrnFZELTQsvcyC9QFfP+mnN4O1ryRrfKb14bmZlR/asvKU7PIPHzL3RVHDa9BYVZWldOBepntR5QE8fq1uz8NZS8rLKjxtrUdGZkuxqsOHqdXZcS0UgN/zv4PwrVhUxvP73ypTTK4NE0+PnpcP1Iiat7KSUbIzYydONQUgtSmd9tfpmxzlKjIffIEWInvU149x6kr1yJXZ+n8N+0Ede33iwzCic7rYAL+2PZPP8si989yO7ll8jLKqJlX39emNaGLi/Uwdnr9iJc7QOcKVRrOBFZgdWIPpjbaHv8XlgDasOHNd7Ks0HPEp0dzYHYA+WOXX40CiMheLal7klvwsQEp1EjKTh/ntwDlYzOKMyBI/Mg8MkSb+Nb9iulsJoenE47gLCIJjOuM6FxBowdLwFZVETitOmY+fnhOHw4NH0Z3OrDtqkG73d86XA8sZczaDOw5m0JVt19u9POsx3fn/qehNySI5/m7blKRHIuX/RvgGVJvR0qgEWdOji/NpasTZvI2qZDi88Lq7XunE5TwK1uhWSZmGpDNYvy1OxeFlruwuPtHrUJcrfl3VXnWHRmGYfjD/NO83f0K6VRBgYx+EKInkKIMCFEuBDivRLOmwsh/rhx/qgQws8Qckvl6i6QxXdl10ZkRPDqjleZsn8KgdUC+avPX7T0aHnX5VKlIvfIURKnf8nV7j24/tLL5OzfT7UhQ6i1bSvVP/8cM5/bDZHUSNLicgk9FMfuFZf4/dOj/Pr+IfasCCM5Opt67avz9HvNePbjljTr5VdqZcCWNZwwNRb33q2Tn65936qQrr5dcbF04bdLZZc1LlAV88fxaLrXdbsr0ao87Pv3x8TdnZSfKplef+IX7Xtxx+r+3/ldrKjXwfP2wmp6oNaomR0ymxp2/tgXt+KrrboXVqsMacuWURQZidvU9xFmZtoSyk9+pXXrHZpjMDl5WUUcXBWORy37u+o9CSGY2nIqGqnhy2N3b6heTsxm/p5wBjT2pENgxZKzSsN51Cgs6tUj4eOPUaeW4W7JTtQWmfNsCm0mVEqWk6cNrQfUJPJcKhf2x5U51tzEmO+GNiK7OJrvz3xHB88ODA4cXCm5uqB3yqYQwhj4AXgCiAGOCyHWSykv3jJsBJAupawlhBgKfAUM0Vd2qVz5BywdwasZqmIVRxOOsuryKnZd34W1qTVTWkxhSO0hGBsZU5yTQ1FkFEVRkRReCiP/zBnyz59H5uUhTE2xatkSl4kTsOnajaJiY7Kyisi9mEpeZhGZKflkJOaRnpBHZmIe6hshe+ZWJrj62RHUygPf+k5U87DSOYHG2tyExj7VOBCeDARV2Vt0G7W6at+vc39CbQNmdt6BqZEpg2sPZt7peURlReFrV3LRrPVn4sjIU1WqoYWRmRlOr7xC4rRp5B0/jlXz5rpfrMrX9qr17wRepRcPa9bLj9DD8RxZF0HP0bpHdJXE2vC1RGZFMqfzHK671eCj9RfYezmZTrXLzsyuDKrEJFJ+mIdN587YtG//3wm/dlBvIBz4Fho9q83R0JMDf11BVVRMp+eCSizb7WXrxZiGY5gdMps90Xvo5N0J0Pa1nbL6HDbmJnzQu47eetxEmJpS/cvpXBs4iISPP8Fzzuy7P5NSwsY3tXc6/edrvwwrSXBnL6IupHLwryt4BjpQzb10T4C/iwXVA9eQlGdOE+vRhk+2uwVD9IdrAYRLKSMAhBArgX7ArQa/H/DxjcergO+FEEJWwVImOTaaLevcKRYjKR49C5VaBRLq4k5zk1FYGlki/slmbdF8pEqFRl0MQiARYGSMkW1HZLv+aKzt0JhZoiqSqHYXo9py5K5MSyHA1skCBzdrvAKr4eRljbu/PQ6uVrrVpi+FdrWc+XbHZdJyi3C01r1GeKUxNoV6/eH071qXRgVrvVeEwYGDWXB2ASsvrWRyi8l3nZdSsvRQJLXdbGnlX7nepA6Dnyblp59Imf8jPhUx+KeWa5uFdFhc5jArOzMad/Pm+KZIEq9l4Vajcklx+ep85p2eR2PXxnTy7oSquuTnA9f4amsYHQJcKlRUTBeSv5mFVKlwm3LXTbg2GStsC2z/AJ75VS85URdSuXI8keZP1cDRo3RD92K9F9kUsYlpR6fRwr0FVqZWrDh2nZNR6cwa3BAnG8NGD5kHBOAycQJJX88ia+NG7PvcEaRx7i9tS8gnPgOX2nrJEkbaUM2Vnx5j+88XeHpys1Kbu3x/+ntSiq7hJ8cxa0s83QJr4etkmHpGd2IIl44nEH3L85gbx0ocI6VUA5nAXYHVQojRQogTQogTycmVqx+tTo0l37gxRUb10MgAjI3rYmpSF2PT2hQKLzJxItPMnRw7H/JcAyj0qY+qZiM0dZojg1uhqVkfEx8frKs74ehpi1dQNQJbuNOouw/tngmgx6j6DHi7Cc9/1orRczoy/PM29Hm9Ie2eCaBOm+pUc7fWy9iDduNWSjh4T906z4A6X5tVWIU4WzrT3bc7a8PXkqe62yUScj2dC3FZvNDGt9IrHSNLS5xefoncQ4d0L6KlLoID34F3K/BtW+7wRk/4aAurrQ2vtAtmRegKkvOTeaPJGwghMDMxYlL3QELjs1h/pmxXQEXJCzlF5rr1OL7yyl3uSADsvaD9JK3vOmJvpeWoCovZ+1sY1dytaFpO2WNTI1M+bP0h8bnxzD8zn4TMAmZsuUS7Ws4MbFJ6+QR9cHz5ZSwbNSLhs89RJd5SojorXhtz79UCWo8ziCxre3M6Dw8iJTqHo+sjShxzPOE4S84v4enAp1n49IsYGwne/OM06uIqCpOWUur1AzwNLLrl+XDg+zvGnAe8bnl+FXAua96mTZvKSqPRSKlWVf76+4xKXSyDP94m3/7z9L0TWlws5Tf1pVw2sMpFnUo8JesvqS//uPTHXede/y1E1v9oq8wp0O/vp87OkZdatJTXx76m2wUnl0r5kZ2Ul//RWcaZXdfl92N2yqjzKRXWLz0/XbZe0VqO3zH+tuPFxRr55Hf7ZLuvdspCVXGF5y0JjVotIwYMlJc7dJTFOTmlDyzKl/LbBlJ+37LSn5+Df1+R34/ZKWMvp+t8zUcHP5INlzaUzy9dLQOnbpaRKWXoaAAKIiJkaMNGMmr0aKnRaLT2YsUzUn7mKmXyFYPL27U8VH7/6k4ZfSnttuOZhZmy21/dZO/VvWVuUa6UUsq1p2Kk7+SNcs6Oy5WWB5yQpdhVQ6zwYwHvW5573ThW4hghhAlgD1RdU1Uh9PK/3W9MjI3oEOjCnsvJ964fppERNBgEV3eXWC/dkDR0aUgdxzr8fun321bHSVkFbD4Xz+Cm3lib6/f3M7axxnH4cHJ27aIgLKzswcVqrf/ao5F2P0NH6rX3xM7ZgkNrriIr+HdadG4RuepcJjS5fWPQyEjwbs/aRKfl89tRw8T7Z6z6m4KLF3F9952yazuZWmgbpSSHltkopTRSYnI4vSOaOm09qB7goPN1bzZ9EwtjW07mLWRC15pV5s64iXmNGri+9Ra5e/eRuXo1nPkdLm/Vtq50rlX+BBWk3dMBOLhasWPxRQpy/6ubNO3oNJLzkpnebvq/JbD7NfKkT8PqHItMq5LPviEM/nEgQAhRQwhhBgwF7gzqXQ+8eOPx08AueesnXeEuOgW6kJxdyMV4w/dsLZUGz2ijmy5UbUNoIQTP1nmW8Ixwjicc//f478eiUWskw1tXrANSaTg+/xxGVlak/vRT2QMvrIG0CG1kTgXcSMYmRrTs509qTA6Xj+te8jY+J57fL/1O35p9Cah2d9XIjoEutPJ3ZO6ucHIK9cvqLc7MJPnbb7Fq1gy7Xr3KvyCot7ZRyu4vtMlHOiI12ph7C2sT2gysmNE0klaokp7C2DIaW9eqTQC8SbXnn8OqRQsSv5iG6q8p4NMGWr5aJbJMzY154pW65GcVsWdFGFJKNkdsZlPEJsY0HEMDl9vDf78a1IClL7cw+B4OGMDgS61PfjywDQgF/pRSXhBCfCqE6Htj2M+AkxAiHHgLKGHXSOFWOtbWhqPtvlR+KzyD4VZXG5N9xnBtCUujp19PHMwd/g3RVBVrWHE0ik61XajhbJgVnrGDA9Wee5asLVtL73Wq0cD+r8GlDtTuXWEZAU3dcPa24ej6CJ0Lq/1w+gcAxjUq2VcshGByzyBSc4tYtL9k36+uJM/9nuKsLNw+mKrbnsiNOjsU5cKuz3SWc+FAHInXsmg7qBYW1ronKgHM2BpGWlI9Gjq14vvTc4nLMez+RUkIIyM8vvgc1AXEHzRF9plT6daVuuDqa0eLvjW4GpLEsb1hfH7kc4JdghnVYNRdY63MTKrE2IOB4vCllJullIFSyppSyi9uHPtQSrn+xuMCKeVgKWUtKWULeSOiR6F0nG3Maehlr1PvU4PS6FmIC4Gk0PLH6oGFiQWDAgaxO3o38TnxbLuQQFJ2IS9WIhSzLBxffBFhZkbqwoUlDwjbpK271H5SpT7wwkhoC6ulFnB+f/mF1a6kX2H91fU8W+dZ3K3dSx3X2KcaPeu5s3BfBCk5lcvqLQi7TPrvv1Nt6BAsgioQ4utSG1qMgZNLIe50ucNzMws5vOYqnrWrEdiy9NdUEiej0lh+NIqX2tRgRqdPAPj08KdVmotwE7Pk3bgGp5GbYEr6P8fLv0BPGnf3xSPAnqOrorDMs+PLdpVvnVpZHs1M20eETrVdORWdQVpu1WbA3kbwEDAy0db/rmJulrP4I+wPlh6KxMfRio4GSrS5iYmzMw7PPEPmhg0UxdxhkKWEfTPB0R/qDai0DO86jngFaQurFZVTWG1OyBxsTG0Y2WBkufO+3aM2+apivt8VXu7YO5FSkvjFFxjb2OAyoRIJRJ0mg7WztvFHOcb34Kpw1KpiOj1bu0KRVUVqDVNWn6O6vSVvd69NdZvqTGwykYNxB9l0rWqjxciIhq3v49C1CdZt25A082uKrl+vUpFGRoKMNhdRSxVDYt/C07pqIpHK1OGeS1TQmc5BrkgJ+69U7SbqbVg7Q2BPOPMHFKvKH68H1W2q09m7M3+GreJ4VBIvtPatkltZpxGvgBCk/rzo9hPhOyH+DLR7U69NfiG0q/yCHBUhZRRWC0kMYU/MHl5p8IpOBdJqudowpLk3K45GcT21Ylm92Vu3knfsmLaxiYNDha4FtK38un6kLapXRvns6xe1MfdNe/rh4Fax3rs/7b3K5cQcPutf799N+qG1hxLsHMxXx74iraDsXrGVRqOBdeNAahD9f8Djiy8QJibEvf++YSqtlsKF1AvMDf+GtBYXUcWbcGJzZJXJKg3F4D/ABHva42Rtdm/9+KB16+QmQfiOKhc1LGgY2apMrKqdY3BT7/IvqASm7u44DBhA5qq/UcXeWOVLCftmgJ0XBA/VW4arrx0Bzd04vSOarJS76+FIKfn25Le4WrryXJ3ndJ53YtdAjIRg1j/lRBrdgiYvj8QZMzGvUweHwXqk6Td6Dqo3hu3/g8K7m4ioi7Qx9w5u5cfc38nV5Bzm7gqnd7AHXYL+q/1vbGTMJ20+IUeVw4zjMyqve1mc+Bmu7YUeX0A1P0zd3XF7/33yT5wk7Vf9ks5KI0+Vx+R9k3G0cOTtIaOp3dKdE5sjib+qe7lwQ6AY/AcYIyNBx0AX9l5Ovrft0AK6g7XLPXHrBNo1Qha64ehxDDtDNGcvBedXxwCQPG+e9kDkAe3qtd0bpTa2qChtBtZECDi0+u566Lujd3M6+TRjG43F0kT3+kDu9haMbF+DdafjOBmlW0G9lIULUcfH4/7BVP0amxgZwZMzIScB9t/dH/bElkiyUgro+GxtjE11NyUajeT91eewMDXioz53FyerVa0WIxuMZFPEJsPXhU+9qv0Cq9UNmr7072H7/v2w6dyZ5G+/K32DXw+mH5vO9azrfNn+SxwsHOgwNBBbJwu2LzpPfs69c9kqBv8Bp1OQK+l5Ks7EZNw7ocamWl9+2FbIrbp0CYBVJ2MpTGtNpiaSM8lnqkyOafXqOAwbSubaddoP9P6vwdoVGj9vMBk21Sxo0sOXqyFJxF7+zzirNWrmhMzBz86P/rX6V3je1zrVws3OnE82XCg3NrsoOpq0n3/B7qmnsGratMKy7sK7OTR8Fg59D8n/3WWkxeVyavt1ardyx6uCndl+P36do9fSmNq7Dq62JfeNHtVgFAHVAvjw4IekFxiocqymGNa8qv2C7zv3thBcIQQen36CkYUFcVPeQ6oN1+Rm67WtrA1fy8gGI2nuri31YWZpQo9R9cnPVrF9Ufl/V0OhGPwHnA4BzhgJ2BV6H9w6GlWV1skv1kiWHYmiYbUu2Jra8uvFqrmdvonz6NEIc3NSZnwCEXugzXgwrVg1zvJo/IQPNo7m7P/zyr8f4vVX13M18yoTm0ysVFSGtbkJ7z0ZxNmYTFaFxJQ5NvGLaQgTE1zfKbnaZ6V44lNtfaV140FTrI25/+0SphbGtB1UsZj7+Mx8pm++RNtaTjzTrHQXnpmxGdPbTSezKJPPjnxmmKidQ3Mg5hj0mlVinwwTFxfcP/qQgjNnSV1U8cSzkojNieXTw58S7BLM2Ea39yl29bWjw7BAYi6lc6yU0guGRjH4DzgOVmY093NkR6juiT0Gwa2eNvO0Ct06e8KSuJ6Wx8utgxgaNJQdUTu4lmn42+mbmDg74zh8OFl7jlKQ5wTNRhhehpkxbQcFkBqTw8UDceSp8vjh1A80dGlIVx/ds3jvpH8jT5r4ODBjaxjZBSVvpmfv3k3Onj04j3sNUzcD9sS1cYGeX2qN5fFFnN8XS3x4Jm0HBWBpq7s7TErJ1DXnKdZIpg8ILjeip7ZjbcY1Gsc/Uf+wMWKjfq8h8QLsngZ1+kKDp0sdZterF3a9niR57lzyTpzQS6SqWMXkfZORSL5q/xWmRnfnJ9RtW526bT04uTWKiNNVH5yhGPyHgO713LmUkE1Uau69Fdz4eUg4p41kqQKWHIrE3c6C7vXceK7Oc5gZm7H4fNmVKvXFqVczjEw1JEfWqrKqoDWbuFA9wIGj6yJYduo3kvKTeKvpW3qVvRVC8HHfeqTmFjK3hDBNTWGhtrFJzZraxiaGJngI1OpG1tbvObz6Cj51HQlqXbGY+/Vn4th1KYlJ3QPxcdItouflei/TyKUR049OL7VZSrmoCmD1aG3k0VPflptN7f7pp5h5eRHz5puoK1nEEeCbk99wJvkMH7X5CC9br1LHtR8aiIuPLTuXXCQ9oWo/44rBfwjoXle7Wtt+4R6v8hs8DSYWcMLwRvhqcg77r6TwXEsfTI2NcLJ0YmDAQDZEbKj8B1sHjE/Nx6mBmpyz0eSFnKoSGUII2j0TQGGeivNbE+ni3YUmbk30njfYy4HBTb1YfPAaV5NzbjuX+vPPqKKjcf/fB9rGJoZGCGTvb9iTPgLUhXSsYMx9Wm4Rn2y4SENvB15uq3s3J2MjY6a1m4Zaqpmyf0q5fXBLZPsHkHheW+Pe2rl8mTY2eM6ZgyY7h9g336qUP3/rta0sD13O83WeL7OjHmi7ZPUcUx8jEyM2/XCWgpyqC4dWDP5DgLejFXU87Nh+seoMYYlYVoP6g+Dsn1Bg2Jo+yw5HYWZsxLBbWhi+VO8lkLD0wlKDyvqXxAtwaSOOL7yAsbMzSTNnVllGp4u3LYVBCdSOa8mLroar0fJOjyAsTI35YM35f3Uviokl9acF2D7ZE+tWrQwm604uhZoRXRBMa+sl2F1fVaFrP1p/gewCFTMGBWNcwVwLbztvpracyonEE8w7Pa9C1xK6EY4vhNbjIeAJnS+zqB2Ix6efkHfiBEnfflshkREZEXx46EMauzbmrWZv6XSNnZMlvcYGk5NeyOYfz+pcpqOiKAb/IaF7XTdORKVXOs2+0jQbAapcOPuHwabMKVSz6mQMvYM9cL6lyUV1m+r08u/F31f+Nlxkxq3s+xrMbDDq8DouE14n/9QpsrdtM7wc4HrWdX63nYO0VHFlXTYaA9U3d7E1Z8qTdTgckcpfJ7QbuIlfTgdjY9wm391QxlDkZhZycNUVPGrZU79uDmx9TxviqAPrTsey4UwcE7oEUNvdtlLy+9Xqx4BaA1h4bqFOPZEByIzRJlh5NISuH1ZYpn3fvjgMG0raz7+QuWGDTtfkFOXwxp43sDSxZGaHmSX67UvDo6Y9XV4MIj48k90rqqbVpWLwHxK613NDSth5rzdvPZtoPzAnfik3xV5XVofEkFOo5sU2fnede6X+K+Sr8/n9koELuCVf1lbFbD4SrBxxGDQI88BAkr6ehabQ8F+is0Nmg7mG9kMDSYnO4ezusqNrKsLQ5t608HPki82hxG7dQc6OnTiPfRVT94r51HVFSsne38JQqzR0GV4HMfBHMDLW+sXLycaOz8znf2vP09jHgbGdauqlx5SWUwioFsCU/VPKd/sVq+HvUaBRw9OLwaRy3bPcp0zBqnlz4t+fWu4mrlqj5p1973A96zozO8zEzbriG+eBzd1p0acGVrZmUAU3n4rBf0io62GHp4PlvffjC6Fd5Sdd1CYq6Ym80cKwoZc9jbwd7jpf06EmXby7sDx0OVlFBnQjHfhGux/RejwAwtgYt/cmo4qJIX35csPJAc4mn2V71HZeqvcSDVv44xfszNH1EWSl3p2BWxmMjATTBjZA5uUR+9HHmNWsidOLL5Z/YSUJPRTPtTMptOzjry2fYO8FT30HsSe0tYhKQaORvP3XGVTFkm+faYSJsX7mxtLEklkdZ1FUXMSkPZMoUBeUPvifD+H6Iej9DThV/otGmJnhNXcOpp6exIwbT1FkZKljZ52YxYHYA0xtNZUWHi0qLbNZLz/aDKqld+e8klAM/kOCEILu9dzYH55Crp410itMg6fB3A6O6x+bfDA8lavJuSWu7m8yttFYsouyWXZxmd7yAEi7pt2HaPaKNsTwBtZt2mDTsSMp839EnWqYBDON1PDV8a9wsnDixXovIoSgw9BAEIJ9Ky8b7Da9lqsNM7MOY5uZSswrb1TNRi2QmZzH/j+v4FnbgUbdbombrz9Qm5C1byZc21/itUsORXIwPJX/PVUXPwOVvK5hX4Np7aZxNuUsHx78sOT38+xfcOQHbX37hkP0lmns4ID3gp9ACK6PHoMq6e6cmD8u/cHy0OUMrzucwYF6lLOAKm1irhj8h4ge9dwpUmvufclkM2toOBQurq1QU4ySWHIoEidrM3oHe5Q6JsgxiCd8n2DZxWVkFGToJQ/QZtUamUDbu6tGuk5+F01+PsnfzdZfDrApYhNnk88ysclErE21Rs7W0YJWff2JOpfKpcPxBpGTf+YMPns2cKBeRyaFyirZ29EUa/jnl4sYGQm6vlj37hVnrxngVAv+egkyb69EeiY6g+lbQuka5MqwFoatkdTVtytvNHmDLZFbmHfmjk3c+LOw/nVtX+LunxtMppmPD94/zkedksL1V15BnfZfYbd/ov5h2rFpdPDqwKSmkwwmsypQDP5DRHM/R1xszdl4xjBGo0I0GwHFRXCy8iGa0Wl57LyUyLAWPpiblF3jZVyjceSp8lh8Qc+Q0JRwOP27dnVve7eP29zfH8fhw8n46y/yTukXppmryuWbk99Q36k+/Wr1u+1ccGcvPAMd2P/nlRKLq1UEqVIR/78PMXF1pf2Mj8gqUDN51VmDb/Kd3BpF4rUsOj1bG1vHEkogmNvCkBWgLoA/XwC19ksnM0/FuN9CcLW14OvBDatkxfpK/VfoX6s/P575kbXha7UHs+Jh5bNg5QiDl2hLhBgQy0aN8J4/H1V0DNdHjKQ4I4NDsYd4d9+7BDsHM7PDTIyN9KhddA9QDP5DhLGRoHcDD3aFJZWabVlluAZBza5wbOG/H+yKsvxIFEZC8Fwrn3LH1nSoSS//Xvx+6XdS8vW4q9gzTbth17708Djn8eMxcXcn4eNP9KqhsuDsAlLyU5jScgpG4vaPljASdHmhDgC7fg2tcA/cW0n9+WcKL1/G/aMPCarpwXs9g9h5KYkVRw1Xzz3+aibHN0US2MKNgOZlbD66BEL/eVp//sa3kBoNk/46TWJWAd8/25hq1lXjahJC8GGrD2nl0YqPDn3E1strYMVgyE+HYb+DjWuVyLVu2QKv77+n6OpVLg0ZxKfrJuBv78/3Xb//ty/tg4xi8B8yngr2oEitufelFkBbeyYnscz66KWRX1TMHyei6VHPDQ973erXjG04lqLiIhaeLaVbVXkknIfzf2t9uWUYAGMba9ymvk9hWBhpyyq3gRuVFcWvF3+lb82+BLsElzjGztmSdoMDiL2cwZld0ZWSUxAaSvIP87Dt2RPbLl0AeKmNH+0DnPls40XOx+pfbjcvq4htC85h62RBh2G1y7+gbj/o8C6cXs7xpZPZEZrE+73q0NinYkXVKoqpsSmzO8+mkXMwUw5/yO6cCHjmV21UWRVi074dGdMnUJAQx0dLC/nB/z2d+hs8CCgG/yGjiU81qttb3B+3jn9nbc/bwz9UOERzVUgMGXmqCmVZ+tr5MjBgIH+G/Vm5Gju7p4G5fYm++zux7dYNm06dSJ47F1VcxXqqSimZcXwGZkZmvNHkjTLH1mnjQY2Gzhxec5WEaxUzzprCQuLefRcTBwfcP/ovrtzISPDtkEY4Wpvx6vKTpOvRIU2jkfzzywUK8tQ8OaY+5rqWrO78PjG+A2gRtYDpfiG8VMamvCGxEib8kKmiTkEhb7m6sNHIMJFQZfFP1D+MTfuexa/VxNHUnswXx5K1fXuVyzUEehl8IYSjEOIfIcSVG7/v+koXQjQSQhwWQlwQQpwVQui/bf4YY2Qk6B3swb4ryWTm3WO3jhDQepw2RPPqTp0v02gkvxy4RkNvB5r5VmzVN67ROCxMLJh14u567GUSc1Lbr7bNeG3GcDkIIXD74AMA4j/4X4X84f9E/cO+mH2MbTgWF6uyWzQKoXXtWDuYs23h+Qql0Sd/N5vCK+F4TPsCk2q3vyZnG3PmP9+UpKxCJqw8Ven+Ccc3XiPmUjodhwXi7KV7ktTZ2Ex6RgwixKwpQxO/QZytuiqr/6IuglUvYxO2hZ+CJ9DEvRlT9k9h8fnFVZK0JKVkwdkFvLXnLeo51WPay7/h/+efmNWsSeyEiSRMm4Ymv+q/cPRB3xX+e8BOKWUAsPPG8zvJA16QUtYDegLfCSEc9JT7WPNUcHVUxZJtF+5xqQWA+k+Djbu2PrqO7AhN5FpKLiPb1ajwBp6TpROjgkexN2Yvh+MO637hrs/AyglajS1/7A3MvDxxe/cdcg8dImPlSp2uySrKYvqx6dRxrMPzdXWrrW9hbUrP0fXJyypix5KLOvnzc48cIW3JEhyGDcWmffsSxzTyduCz/vXYfyWFj9dfqLDRu3IikRObI6nTxoM6be4uH1wa11JyeWXJCRxsrPF5dRXCty2sGQOnqrCBTmEO/PEcXNoIvb7GtvV45nebTw+/Hnxz8hve3fcuuSrDFSLLLMxk0t5JzD01l6f8n2JR90XYmdlhWr06vsuXUe3ZZ0n/dRkRffuRc/CgXrJUiYnkn6mi3hBSykr/AGGAx43HHkCYDtecAQLKG9e0aVOpUDIajUa2/2qXfHbh4fujwL5ZUn5kJ2VsiE7DB88/JNtM3ylV6uJKiStUF8oeq3rIAesGSHWxuvwLLv+j1e/g3ArL0mg0MuqVETK0UWNZGBVV7vhPDn0ig5cGy/Mp5yss6+zuaPn9mJ3yyLqrZY5TJSXJsLbtZHjPJ2Vxbm65807bdFH6Tt4oZ++4rLMu8REZcv743fLvmSekukj3v1N0Wq5sPW2HbPzpdnklMUt7sDBXyqX9tH+DvTOl1Gh0nk8nMuOknN9Oyo8dpDz+y22nijXFcuHZhTJ4abDsvbq3PJlwUm9x+2P2yy5/dJGNljaSi88tlppSXk/OkaMyvHsPebF2kIx6+WWZe+xYqWNLojA6RsZ/8qkMbRAsw3v1rtC1twKckKXZ39JO6PIDZNzyWNz6vJTxLYBQwKiU86OBE8AJHx+fSr3Yx4Vv/wmTfu9tlDHpefdeeH6GlNN9pPxtaLlDT19Pl76TN8qF+8o2auWx7do2WX9Jfbn84vKyB6pVUn7fUsrvGkqpKqiUrKL4eHmpWXN57ZkhUlNYWOq4kwknZf0l9eXMYzMrJUej0cidv16U34/ZKUMPxZU8RqWSkcNfkKENG8n8sDCd533rj9PSd/JG+cuBiHLHZybnyZ/f3id/nXpQ5mWX/nrv5HpqruwwY5ds8NFWeT424/aTRflSrhqhNfqrRmi/BAxB+C4pZwZI+bmHlGHbSh12PP64fOKvJ2T9JfXl/w78T8Zll/z+lkVERoR8fefrsv6S+rLfmn7yQsqFcq8pzs+XKb8slmGt28iLtYNkeM8nZdLsOTL32DGpzs6+baymsFDmh4bK1F+XycjhL8iLQXXkxfoNZOzUqbIwOrrC+t6kLIMvZDm3fUKIHUBJRTqmAkullA63jE2XUpboMBVCeAB7gBellEfKu/No1qyZPKFnA4JHmei0PNrP2M2kJwJ5vWvAvVdg70zY/TmM3gvVG5U6bPxvIewNS+bQlC7YWlQ+LlpKydgdYzmVdIp1/dfhbl1K3ZgTi2HjG9pojbr9Sh6jA1lbtxL7xps4vvgCblOm3HU+T5XH0xueRiM1rO67utIhecXFGjbOPUPclQz6TGh0V7vApG++JXXBAjy+nI5D//46z6sq1jD+txC2XUjk7e6BjOtcq0R3Wm5GIau/PklhnpqB7zTF0UO3jNjQ+Cxe/OUYhWoNS15uXnJEjpTakhY7PwXHmjDgR/CuZMmBwhzY+6XWlegcCIMXa5v0lEGeKo/5Z+azPFQbedWrRi/61exHM/dmd4XN3qRAXcDR+KOsuryKvTF7sTK1YmSDkQyvOxxzY93r8Wjy8sjauo2M1X+TH3IKNNrieUb29hiZmyOLiylOS/s3+MHM1xe7vn1wGDgQU4/SkxJ1QQhxUkrZrMRz5Rn8ciYOAzpJKeNvGnQp5V1xXEIIO7TGfpqUUqe6qorBL59hC44Ql5nPnrc7VWk6dokUZMJ3weDbRhv3XAIx6Xl0nLmHV9r6MbX33c2qK0pMdgwD1g2glUcr5nSZc/drLsiCuU202Z8vbym30UV5JHwxjfRly/D87jvseva47dzHhz5m9ZXVLO65mKZu+vWOLcxT8feMk+RkFNJ3YiPca2hD/DI3bCDunXdxGDwYj88+rfC86mIN7646y+pTsbzY2pcPnqqL6S31bPKzi1gzK4Sc9EL6vvGf3PLYdSmRiStPY21mwq8jWhDoVs7m7rV9sPY1bfXKhsOg8/vgoGP2rboIzq+CnZ9Bdpy28XiP6WCm+xdsfE48P5//mQ1XN5CnzsPWzJaGLg3xsfXBwcKBYk0xGYUZhGeEczH1IvnqfBwtHHmm9jMMrT0UJ0snnWWVRHFWFnknTlIUcRVVXByaoiKEMMLEzQ0zXx+smjTB1NNTLxm3UpUGfyaQKqX8UgjxHuAopXz3jjFmwBZgg5TyO13nVgx++awOieGtP8/w55jWtKjheO8VKGeV//H6Cyw/EsXedzvj6WCY3rFLzi9h1slZfN3xa3r43W6E2fExHPgWRu0CT/0beMuiIiKHD6co/Cp+K3/HPEB7J7X7+m4m7J7AK/Vf4c2mb+otByAnvYA1s0IoyFXT741G2CRf5vrLr2DZqBE+Py+qdK0cjUYybXMoiw5co4WfI3OGNcbd3oLczEI2zDlNRlI+fV5viGdg+ZFMhepivttxhfl7rlKvuh0LXmim+9+1IEtbd+foTyCLofaTEDwU/NqBpcMdShdrO61d2qjd+M2O08bWPzkTfFpW/E24Qb46n73RezkSf4SzKWdJyEkgW5WNQGBjZoO/vT91nerSyasTzdybYWZcNUljVU1VGnwn4E/AB4gCnpFSpgkhmgGvSilHCiGeBxYDF2659CUp5emy5lYMfvnkFalp8cVOnqzvzszBVZtsUiI3V/meTWD4mttOJWUX0P6r3fRrVJ0ZTxtON7VGzbObniUhN4G/+/79Xxhk0iX4sZ220NuAHw0mTxUfT+QzQ8DEBL+VK0mzkTyz8RlcrVz5rddvmBowfT87TWv0C3OKaHBhAS4m6fit/B1jBwe95153OpbJf5/F1MiIt9vWROxNIj9HRa9XG+Bdp/zFwpGIVD5Ye57wpByGNPPmk371sDCtRBmBjGg49hOc/g3yUkEYgb032Hlq78gKs7TlMNT52nM1OmgrnNbqpvcdW0moNCpMhMm9v0OuQqrM4FclisHXjcmrzrLhbBzHp3bD2lzHJBlDcngebJsCz/0NAd3+PTx9cygL90ewc1InahioUuJNrmZcZejGoTR2bcyPT/yIEQKW9NZ2tBp/4raKmIag4OJFIp8fjqmPD9NesORcfjgre6/E38HfoHIA0s5dZf2s4+SZOdKxX3Xq9a5vsLkjU3KZ8etpalwpwFgIXHt70bdrDexK2VspUmvYfyWZRfuvcTgiFU8HSz4fUJ/OtQ1QtkBdBDHHte6e1HDIjgeE1lXjVAvcg7UdqnRoSahwO4rBf4QJuZ7OwHmH+Lx/fZ5v5XvvFVAXwbyWYGwOrx4AYxPSc4to+9UuutVxY86wxlUi9s+wP/nsyGdMajqJl9RmsHYs9Jmt9fFWATn79xP16hjC3SQWc6bRo/4Ag8soiokh6oUXKCrQENbrc+JjiqjfwZO2T9fCxEy/olwajeTU9iiOrovApJoZO6ppOJaajZmxES1qOFKvuh0utuYYGwnScou4lJDNsWtpZOarcLU1Z0zHmjzbwgdLPfVQqHrKMvj3YUmoYEgaezvQwNOeXw9H8lxLn3t/a2piBk98Cn88DyFLofkIFh+KJK+omHGda1WZ2MGBgzkcd5jvQr6lTmouLb1aQOMXqkzeNrckNvUXTForsPr4N4oXdTaIq+Um+ecvED32VWRhEf6LfyGodh2OrIvg9D/XiQvPoNOztfGoVTl5KTE57F5+iaTILAKaudLp+SBGmRsTcj2DLefiORyRyuKDkRTdaMMoBNRwtuaJum70auBOu1oumJkoVVgeBZQV/iPAXyeieWfVWX4b1ZI2Ne/DLbCUsLQPJJwje9Qh2s49T+uaTvw0vMRFhsHIKczm+T86k6zO57dOc/D171olcvbF7GPCrgm0qt6KL42eJmHiW5hU98B73jzMa+rXtg8ge+dOYt95F2MHe3x++unfzWGA6xdS2b38EjnphdRq6kqTnr64eOtW8iA9IZeTW6K4fCwBc2tT2g8JIKCZW4mLgmKNJLdITXGxxM7StMKNxhUeHBSXziNOgaqY1tN30rKGEz8O1z86pVIkX4Yf23LJoSM9Y19m4+vtqO9ZxRUEz/xB9IaxPOvrj4ONB0t6LtE7hO5OTiedZvQ/o/Gz82NJzyVYmVqRFxJCzOsTkIWFuH/4P+z69KnUnZWmsJCkr2eRvmwZFvXq4TV/Hqaud/vHVYXFhGyL4szOaFSFxbj721GjkQueAdWo5mGFmYX2Rr2oQE1mUj6xl9OJOJ1MfHgmxqZGNOjkRdMevljYGLY+vMKDiWLwHwO+2nqJn/ZeZf/kLgYLgawoudunYX3oK36sPo1XR4+rWmEZ12F+O3Ctw8len/PqztfwtvPml+6/4GDhYBARJxNP8tqO13C2dGbpk0txtvzv7kkVF0fspLfJP3UKmy5dcH3nbcxr6FYJVEpJzu7dJE7/ElV0NNVeGI7r229jVE7oZWGeiosH4rl8PIGU6Jx/jxubGCGMQF2k+fdYNXcrglp7ULuVO9b2lWvgrfBwohj8x4DYjHw6ztjN8618+bhv2RmIVcVna08zJOQ5/G1UmIw7VHURFupC+KUHpF6FMXvB0Z/DcYcZv3M8fvZ+/ND1h9IzcXVk1/VdvLf/Pdyt3VnUfRGuVnevvGVxMWm/LiN5zhxkYSF2vXvjMHAAVi1aIIzv3twszswke8dO0pYvpzA0FLNaNXGfOhXr1q0rrF92WgHJUdmkJeRSlK9Go5FY2Zph62SBR017bKqV0KFK4bFAMfiPCW//dYaNZ+M4MLkLzjb3dlUXnZZHl1l7eL1uARMiXtXGTz/7JxhVwWbfhje0rRaH/gZBvf89fDjuMG/ueRMrEyvmdJlDfeeKhzQWa4pZdG4R35/+ngbODZjTZc5tK/uSUKemkrpgARmr/kaTm4uRrS2WDepj4u6BMDdDk51DYcRVCsMuQ3ExZrVq4vjiizj0748wVdwsCoZFMfiPCVeTc+j2zV7GdqzJuz2D7qnsiStPsfV8Anvf6Yx72DLY/DZ0+xjaGSYT9V9O/AIb34S2b8ATn9x1+kr6FcbvHE9SXhKjgkcxqsEonZOjrmVe48ODH3I6+TS9avTikzafYGGi+0pZU1BAzu7d5B4+QsGFC6iTk5EqFUbW1pj5+WFRvx62nTph0bBq+rwqKIBi8B8rxv0Wwr6wZA681wV7y3uzejwemcbgHw8zoUst3upeWxu1s+pluLD2RhGzvoYRFLoR/hyuzboc+jsYlxxVnFmYyfRj09kUsQkvGy9GB4+mh1+PUgucXUm/worQFawNX4u1qTXvtXiPp/yfUoyywkOJYvAfIy7EZdJ7zoH/jG8VU6yR9Jl7gIy8InZO6vRfYo4q/0ao5nl4YS34tNJP0JUd2oYXbvXhxfVgVn727v6Y/cw9NZfQtFCsTKxo7t6c2o61cTB3oLC4kLicOE4lnSI8IxxTI1MGBw5mVPCocl04CgoPMkri1WNEver2PBXswcL913iulS9udlW7eff7setcjM9i7rDGt2dhmlpqV+G/9IBlA7UVNf07Vk7IhbXw90hwDdLuC+hg7AHae7WnrWdbQhJD2HxtMycTT7IvZh8S7SLH1tSWBi4NGBQwiF7+vXC0uA8F6BQU7iHKCv8R5HpqHl2/2cOgJl58OSi4yuQkZBbwxLd7qVfdjt9HtSrZBZKdAL/2h7QIbemDRsN0F6DRwN6vtD/eLbTG/s7KihWkWFNMjioHUyPTStewV1B4kClrha/kSz+C+DhZMbyVH3+eiOZiXFaVyJBS8v6ac6iKNXw5MLh0f7etO7y8WWuw174Kq8dATlL5ApJCYUkvbdOL4CEwfK3exh7A2MgYe3N7xdgrPJYoBv8RZULXWjhamzFl9VmKdWiSXVFWh8Sy61IS7/QIwq+8aphWjlqD3eFdOP83zG0KW9+H+DPa2uc3URVA+A748wWY3waSw6D/fG254wo0vFBQUCgZxaXzCLP+TBwTfj/F/56qy4h2umWB6kJkSi595h6gtrstf4xpXbG6KynhsPsLCF0PGjWY2YCNq/ZxVpz2t7k9NHsZ2kwAa8OWSlBQeNRRNm0fU/oEe7D2VCxfbwujY6ALtVxt9J6zQFXM2BUhGBkJvhvaqOJFtpxrafuR5iTB1V0QGwL5aYAAey9ty0S/dtpNXwUFBYOirPAfcRIyC+g1Zz8uNuasHddWr3rmUkom/XmG1adi+eWlZnQJcjOgpgoKCoZA2bR9jHG3t+DbIY24nJTN5L/PotHDnz9jWxirT8Xy1hOBirFXUHgIUQz+Y0DHQBfe7RHE+jNxfLE5lIre1Ukp+WF3OPP3XOXZlj683qXqGpsoKChUHXr58IUQjsAfgB8QibaJeXopY+2Ai8BaKeV4feQqVJxXO/qTmFXAzweuUaTW8HHfejr539XFGr7ccolFB67Rt2F1PutXXyk5oKDwkKLvCv89YKeUMgDYeeN5aXwG7NNTnkIlEULw4VN1GdPBn2VHonhp8THiMvLLvCY6LY9nFx5l0YFrvNTGj++GVGKTVkFB4YFB3yidfkCnG4+XAnuAyXcOEkI0BdyArUDV9r1TKBUjI8GUXnXwc7bms40X6f7tPl5o7cvTTb3wd9FG8Gg0ktCELP48Hs1vx65jZmzEt0MaMqCx133WXkFBQV/0NfhuUsr4G48T0Br12xBCGAGzgOeBbnrKUzAAw1r40KamE19tvcT8vVeZt+cqDlam2FmYkpZbRE6hGhMjwdNNvXijWyDu9kozDQWFR4FyDb4QYgdQUvugqbc+kVJKIURJu4GvAZullDHl+X6FEKOB0QA+Pj7lqaagB75O1sx7rimxGfnsDE0kLCGbnEI1Dpam1PO0p1sdNxyty265p6Cg8HChVxy+ECIM6CSljBdCeAB7pJS17xizAmgPaAAbwAyYJ6Usy9+vxOErKCgoVIKqzLRdD7wIfHnj97o7B0gpn7tFkZeAZuUZewUFBQUFw6NvlM6XwBNCiCto/fNfAgghmgkhFumrnIKCgoKC4VBKKygoKCg8QiilFRQUFBQUFIOvoKCg8LigGHwFBQWFxwTF4CsoKCg8JigGX0FBQeEx4YGN0hFCJANRekzhDKQYSJ2q4EHXDx58HR90/UDR0RA86PrBg6Wjr5TSpaQTD6zB1xchxInSQpMeBB50/eDB1/FB1w8UHQ3Bg64fPBw6guLSUVBQUHhsUAy+goKCwmPCo2zwF9xvBcrhQdcPHnwdH3T9QNHREDzo+sHDoeOj68NXUFBQULidR3mFr6CgoKBwC4rBV1BQUHhMeOQMvhCipxAiTAgRLoR44OruCyG8hRC7hRAXhRAXhBAT77dOJSGEMBZCnBJCbLzfupSEEMJBCLFKCHFJCBEqhGh9v3W6FSHEmzf+vueFEL8LIe57n0ghxC9CiCQhxPlbjjkKIf4RQly58bvaA6jjzBt/57NCiDVCCIf7qGKJOt5ybpIQQgohnO+HbuXxSBl8IYQx8APwJFAXGCaEqHt/tboLNTBJSlkXaAWMewB1BJgIhN5vJcpgNrBVShkENOQB0lUI4QlMQNvspz5gDAy9v1oBsAToecex94CdUsoAYOeN5/eTJdyt4z9AfSllMHAZmHKvlbqDJdytI0IIb6A7cP1eK6Qrj5TBB1oA4VLKCCllEbAS6HefdboNKWW8lDLkxuNstIbK8/5qdTtCCC+gN/BANrERQtgDHYCfAaSURVLKjPuq1N2YAJZCCBPACoi7z/ogpdwHpN1xuB+w9MbjpUD/e6nTnZSko5Ryu5RSfePpEcDrnit2uz4lvY8A3wLvAg9sJMyjZvA9gehbnsfwgBnTWxFC+AGNgaP3WZU7+Q7tP67mPutRGjWAZGDxDbfTIiGE9f1W6iZSyljga7QrvXggU0q5/f5qVSpuUsr4G48TALf7qYwOvAJsud9K3IkQoh8QK6U8c791KYtHzeA/NAghbIC/gTeklFn3W5+bCCGeApKklCfvty5lYAI0AeZLKRsDudx/V8S/3PCD90P7xVQdsBZCPH9/tSofqY3RfmBXp0KIqWhdoivuty63IoSwAt4HPrzfupTHo2bwYwHvW5573Tj2QCGEMEVr7FdIKVffb33uoC3QVwgRidYl1kUIsfz+qnQXMUCMlPLmndEqtF8ADwrdgGtSymQppQpYDbS5zzqVRqIQwgPgxu+k+6xPiQghXgKeAp6TD17yUE20X+5nbnxuvIAQIYT7fdWqBB41g38cCBBC1BBCmKHdKFt/n3W6DSGEQOt7DpVSfnO/9bkTKeUUKaWXlNIP7fu3S0r5QK1OpZQJQLQQovaNQ12Bi/dRpTu5DrQSQljd+Ht35QHaVL6D9cCLNx6/CKy7j7qUiBCiJ1oXY18pZd791udOpJTnpJSuUkq/G5+bGKDJjf/TB4pHyuDf2NgZD2xD+wH7U0p54f5qdRdtgeFoV86nb/z0ut9KPYS8DqwQQpwFGgHT7q86/3HjzmMVEAKcQ/s5u++p90KI34HDQG0hRIwQYgTwJfCEEOIK2juTLx9AHb8HbIF/bnxefnwAdXwoUEorKCgoKDwmPFIrfAUFBQWF0lEMvoKCgsJjgmLwFRQUFB4TFIOvoKCg8JigGHwFBQWFxwTF4CsoKCg8JigGX0FBQeEx4f9laWvwPHZrIgAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "for n in range (5):\n",
+ " x = np.linspace(0,15,1000)\n",
+ " y = sc.jv(n,x)\n",
+ " plt.plot(x, y, '-')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from scipy import special\n",
+ "\n",
+ "def drumhead_height(n, k, distance, angle, t):\n",
+ " kth_zero = special.jn_zeros(n, k)[-1]\n",
+ " return np.cos(t) * np.cos(n*angle) * special.jn(n, distance*kth_zero)\n",
+ "\n",
+ "theta = np.r_[0:2*np.pi:50j]\n",
+ "radius = np.r_[0:1:50j]\n",
+ "x = np.array([r * np.cos(theta) for r in radius])\n",
+ "y = np.array([r * np.sin(theta) for r in radius])\n",
+ "z = np.array([drumhead_height(1, 1, r, theta, 0.5) for r in radius])\n",
+ "\n",
+ "import matplotlib.pyplot as plt\n",
+ "fig = plt.figure()\n",
+ "ax = fig.add_axes(rect=(0, 0.05, 0.95, 0.95), projection='3d')\n",
+ "ax.plot_surface(x, y, z, rstride=1, cstride=1, cmap='RdBu_r', vmin=-0.5, vmax=0.5)\n",
+ "ax.set_xlabel('X')\n",
+ "ax.set_ylabel('Y')\n",
+ "ax.set_xticks(np.arange(-1, 1.1, 0.5))\n",
+ "ax.set_yticks(np.arange(-1, 1.1, 0.5))\n",
+ "ax.set_zlabel('Z')\n",
+ "\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "interpreter": {
+ "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
+ },
+ "kernelspec": {
+ "display_name": "Python 3.8.10 64-bit",
+ "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": "3.8.10"
+ },
+ "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/buch/papers/fm/Python animation/Bessel-FM.py b/buch/papers/fm/Python animation/Bessel-FM.py
new file mode 100644
index 0000000..cf30e16
--- /dev/null
+++ b/buch/papers/fm/Python animation/Bessel-FM.py
@@ -0,0 +1,42 @@
+import numpy as np
+from scipy import signal
+from scipy.fft import fft, ifft, fftfreq
+import scipy.special as sc
+import scipy.fftpack
+import matplotlib.pyplot as plt
+from matplotlib.widgets import Slider
+
+# Number of samplepoints
+N = 600
+# sample spacing
+T = 1.0 / 800.0
+x = np.linspace(0.01, N*T, N)
+beta = 1.0
+y_old = np.sin(100.0 * 2.0*np.pi*x+beta*np.sin(50.0 * 2.0*np.pi*x))
+y = 0*x;
+xf = fftfreq(N, 1 / 400)
+for k in range (-5, 5):
+ y = sc.jv(k,beta)*np.sin((100.0+k*50) * 2.0*np.pi*x)
+ yf = fft(y)
+ plt.plot(xf, np.abs(yf))
+
+axbeta =plt.axes([0.25, 0.1, 0.65, 0.03])
+beta_slider = Slider(
+ax=axbeta,
+label="Beta",
+valmin=0.1,
+valmax=3,
+valinit=beta,
+)
+
+def update(val):
+ line.set_ydata(fm(beta_slider.val))
+ fig.canvas.draw_idle()
+
+
+beta_slider.on_changed(update)
+plt.show()
+
+yf_old = fft(y_old)
+plt.plot(xf, np.abs(yf_old))
+plt.show() \ No newline at end of file
diff --git a/buch/papers/fm/RS presentation/RS.tex b/buch/papers/fm/RS presentation/RS.tex
new file mode 100644
index 0000000..8e3de17
--- /dev/null
+++ b/buch/papers/fm/RS presentation/RS.tex
@@ -0,0 +1,162 @@
+\documentclass[11pt,aspectratio=169]{beamer}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage{lmodern}
+\usepackage[ngerman]{babel}
+\usepackage{tikz}
+\usetheme{Hannover}
+
+\begin{document}
+ \author{Joshua Bär}
+ \title{FM - Bessel}
+ \subtitle{}
+ \logo{}
+ \institute{OST Ostschweizer Fachhochschule}
+ \date{16.5.2022}
+ \subject{Mathematisches Seminar}
+ %\setbeamercovered{transparent}
+ \setbeamercovered{invisible}
+ \setbeamertemplate{navigation symbols}{}
+ \begin{frame}[plain]
+ \maketitle
+ \end{frame}
+%-------------------------------------------------------------------------------
+\section{Einführung}
+ \begin{frame}
+ \frametitle{Frequenzmodulation}
+ \begin{itemize}
+ \visible<1->{\item Für Übertragung von Daten}
+ \visible<2->{\item Amplituden unabhängig}
+ \end{itemize}
+ \end{frame}
+%-------------------------------------------------------------------------------
+ \begin{frame}
+ \frametitle{Parameter}
+ \begin{center}
+ \begin{tabular}{ c c c }
+ \hline
+ Nutzlas & Fehler & Versenden \\
+ \hline
+ 3 & 2 & 7 Werte eines Polynoms vom Grad 2 \\
+ 4 & 2 & 8 Werte eines Polynoms vom Grad 3 \\
+\visible<1->{3}&
+\visible<1->{3}&
+\visible<1->{9 Werte eines Polynoms vom Grad 2} \\
+ &&\\
+\visible<1->{$k$} &
+\visible<1->{$t$} &
+\visible<1->{$k+2t$ Werte eines Polynoms vom Grad $k-1$} \\
+ \hline
+ &&\\
+ &&\\
+ \multicolumn{3}{l} {
+ \visible<1>{Ausserdem können bis zu $2t$ Fehler erkannt werden!}
+ }
+ \end{tabular}
+ \end{center}
+ \end{frame}
+
+%-------------------------------------------------------------------------------
+
+\section{Diskrete Fourier Transformation}
+ \begin{frame}
+ \frametitle{Idee}
+ \begin{itemize}
+ \item Fourier-transformieren
+ \item Übertragung
+ \item Rücktransformieren
+ \end{itemize}
+ \end{frame}
+%-------------------------------------------------------------------------------
+ \begin{frame}
+ \begin{figure}
+ \only<1>{
+ \includegraphics[width=0.9\linewidth]{images/fig1.pdf}
+ }
+ \only<2>{
+ \includegraphics[width=0.9\linewidth]{images/fig2.pdf}
+ }
+ \only<3>{
+ \includegraphics[width=0.9\linewidth]{images/fig3.pdf}
+ }
+ \only<4>{
+ \includegraphics[width=0.9\linewidth]{images/fig4.pdf}
+ }
+ \only<5>{
+ \includegraphics[width=0.9\linewidth]{images/fig5.pdf}
+ }
+ \only<6>{
+ \includegraphics[width=0.9\linewidth]{images/fig6.pdf}
+ }
+ \only<7>{
+ \includegraphics[width=0.9\linewidth]{images/fig7.pdf}
+ }
+ \end{figure}
+ \end{frame}
+%-------------------------------------------------------------------------------
+ \begin{frame}
+ \frametitle{Diskrete Fourier Transformation}
+ \begin{itemize}
+ \item Diskrete Fourier-Transformation gegeben durch:
+ \visible<1->{
+ \[
+ \label{ft_discrete}
+ \hat{c}_{k}
+ = \frac{1}{N} \sum_{n=0}^{N-1}
+ {f}_n \cdot e^{-\frac{2\pi j}{N} \cdot kn}
+ \]}
+ \visible<2->{
+ \item Ersetzte
+ \[
+ w = e^{-\frac{2\pi j}{N} k}
+ \]}
+ \visible<3->{
+ \item Wenn $N$ konstant:
+ \[
+ \hat{c}_{k}=\frac{1}{N}( {f}_0 w^0 + {f}_1 w^1 + {f}_2 w^2 + \dots + {f}_{N-1} w^N)
+ \]}
+ \end{itemize}
+ \end{frame}
+
+%-------------------------------------------------------------------------------
+
+%-------------------------------------------------------------------------------
+ \begin{frame}
+ \frametitle{Ein Beispiel}
+
+ \begin{itemize}
+
+ \onslide<1->{\item endlicher Körper $q = 11$}
+
+ \onslide<2->{ist eine Primzahl}
+
+ \onslide<3->{beinhaltet die Zahlen $\mathbb{F}_{11} = \{0,1,2,3,4,5,6,7,8,9,10\}$}
+
+ \vspace{10pt}
+
+ \onslide<4->{\item Nachrichtenblock $=$ Nutzlast $+$ Fehlerkorrekturstellen}
+
+ \onslide<5->{$n = q - 1 = 10$ Zahlen}
+
+ \vspace{10pt}
+
+ \onslide<6->{\item Max.~Fehler $t = 2$}
+
+ \onslide<7->{maximale Anzahl von Fehler, die wir noch korrigieren können}
+
+ \vspace{10pt}
+
+ \onslide<8->{\item Nutzlast $k = n -2t = 6$ Zahlen}
+
+ \onslide<9->{Fehlerkorrkturstellen $2t = 4$ Zahlen}
+
+ \onslide<10->{Nachricht $m = [0,0,0,0,4,7,2,5,8,1]$}
+
+ \onslide<11->{als Polynom $m(X) = 4X^5 + 7X^4 + 2X^3 + 5X^2 + 8X + 1$}
+
+ \end{itemize}
+
+ \end{frame}
+
+
+\end{document}