{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Sascha Spors](https://orcid.org/0000-0001-7225-9992),\n",
    "Professorship Signal Theory and Digital Signal Processing,\n",
    "[Institute of Communications Engineering (INT)](https://www.int.uni-rostock.de/),\n",
    "Faculty of Computer Science and Electrical Engineering (IEF),\n",
    "[University of Rostock, Germany](https://www.uni-rostock.de/en/)\n",
    "\n",
    "# Tutorial Signals and Systems (Signal- und Systemtheorie)\n",
    "\n",
    "Summer Semester 2022 (Bachelor Course #24015)\n",
    "\n",
    "- lecture: https://github.com/spatialaudio/signals-and-systems-lecture\n",
    "- tutorial: https://github.com/spatialaudio/signals-and-systems-exercises\n",
    "\n",
    "Feel free to contact lecturer [frank.schultz@uni-rostock.de](https://orcid.org/0000-0002-3010-0294)\n",
    "\n",
    "## Übung / Exercise 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sine Integral"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-17T15:08:11.695597Z",
     "iopub.status.busy": "2022-07-17T15:08:11.695372Z",
     "iopub.status.idle": "2022-07-17T15:08:12.457314Z",
     "shell.execute_reply": "2022-07-17T15:08:12.456115Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.special import sici"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-17T15:08:12.460459Z",
     "iopub.status.busy": "2022-07-17T15:08:12.460238Z",
     "iopub.status.idle": "2022-07-17T15:08:13.003225Z",
     "shell.execute_reply": "2022-07-17T15:08:13.002459Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "N = 7\n",
    "x = np.linspace(0, N*2*np.pi, 2**10)\n",
    "si, _ = sici(x)\n",
    "\n",
    "plt.figure(figsize=(6, 4))\n",
    "plt.plot(x, si, lw=2)\n",
    "plt.xticks(np.arange(0, N+1)*2*np.pi, ['0', r'$2\\pi$', r'$4\\pi$',\n",
    "           r'$6\\pi$', r'$8\\pi$', r'$10\\pi$', r'$12\\pi$', r'$14\\pi$'])\n",
    "plt.yticks(np.arange(0, 4)*np.pi/4, ['0', r'$\\pi/4$', r'$\\pi/2$', r'$3\\pi/4$'])\n",
    "plt.xlim(0, 14*np.pi)\n",
    "plt.ylim(0, 3/4*np.pi)\n",
    "plt.xlabel(r'$\\omega$')\n",
    "plt.ylabel(\n",
    "    r'$\\mathrm{Si}(\\omega) = \\int_0^\\omega\\,\\,\\,\\frac{\\sin \\nu}{\\nu}\\,\\,\\,\\mathrm{d}\\nu$')\n",
    "#plt.title('Sine Integral Si(x)')\n",
    "plt.grid(True)\n",
    "plt.savefig('sine_intergral_0A13DD5E57.pdf')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Copyright\n",
    "\n",
    "This tutorial is provided as Open Educational Resource (OER), to be found at\n",
    "https://github.com/spatialaudio/signals-and-systems-exercises\n",
    "accompanying the OER lecture\n",
    "https://github.com/spatialaudio/signals-and-systems-lecture.\n",
    "Both are licensed under a) the Creative Commons Attribution 4.0 International\n",
    "License for text and graphics and b) the MIT License for source code.\n",
    "Please attribute material from the tutorial as *Frank Schultz,\n",
    "Continuous- and Discrete-Time Signals and Systems - A Tutorial Featuring\n",
    "Computational Examples, University of Rostock* with\n",
    "``github URL, commit number and/or version tag, year, (file name and/or content)``."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mydsp",
   "language": "python",
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