index_v2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mein erstes Jupyter Notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Browser Kompatibilität\n",
    "\n",
    "Empfohlen werden aktuelle Versionen von\n",
    " * Firefox\n",
    " * Chrome\n",
    " * Safari"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Zellen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ein JN ist in Zellen organisiert,die einzeln durchlaufen werden können. Es gibt unterschiedliche Zelltypen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Markdown**-Zellen:  werden verwendet, um erläuternden Text einzufügen \n",
    "*  oder [Links](https:ki-campus.org) \n",
    "* oder Bilder \n",
    "![edit_mode](https://ki-campus.org/sites/default/files/styles/front_about_icon/public/kic_front/about/KI-Campus__Einsatz_KI.png?itok=g-ZmQYv1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**-Zellen:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hello World'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a='Hello ';\n",
    "b='World';\n",
    "c=a + b;\n",
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zellen werden mit dem Plus-Icon in der Menubar oder ESC + b hinzugefügt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Beispiel: Interaktiven Plot erstellen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wir betrachten die Funktion\n",
    "\n",
    "\\begin{align*}\n",
    " y= \\sin(a*x) + \\cos(x)  &&\\mbox{für } &&x\\in [0;10\\pi)&&&&&&\n",
    "\\end{align*}\n",
    "\n",
    "und wollen den Einfluss des Parameters $a$ beobachten.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zunächst importieren wir einige benötigte Bibliotheken"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Funktionsdefinition\n",
    "\n",
    "Um die unterschiedlichen Ansätze zu veranschaulichen, definieren wir "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def myplot(a): \n",
    "    x = np.linspace(0, 10*np.pi, 10**3);\n",
    "    y = np.sin(a*x) + np.cos(x); \n",
    "    plt.plot(x,y); \n",
    "    plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Standard Plot\n",
    "\n",
    "Wenn wir den Wert von $a$ in der unteren Zelle verändern, abspeichern und die Zelle durchlaufen lassen, verändert sich die Grafik."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "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": [
    "a=1;\n",
    "myplot(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interaktiver Plot\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Schöner ist es allerdings einen Slider zu erzeugen und den Einfluss des Parameters direkt mitverfolgen zu können. Dazu benötigen wir die _interactive_-Funktion aus der ipywidgets-Bibliothek."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import interactive"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Jetzt können wir einen interaktiven Plot erstellen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c091cba564bc410aa0be3dc7587ec33f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=0.0, description='a', max=20.0, min=-20.0), Output()), _dom_classes=('…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interactive_plot=interactive(myplot, a = (-20,20, 0.1));\n",
    "interactive_plot"
   ]
  }
 ],
 "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": "3.8.5"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": false,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}