From 4a2a61d36d4f0392b6104f428b738e17e7660414 Mon Sep 17 00:00:00 2001
From: Eirik Lorgen Tanberg <eirik@tanberg.org>
Date: Wed, 30 Aug 2023 22:07:31 +0100
Subject: [PATCH] =?UTF-8?q?Legg=20til=20LF=20for=20=C3=98F1?=
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Øvingsforelesning 1 - TDT4110"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Læremål**:\n",
+    "\n",
+    "* Bli introdusert til hva programmering er\n",
+    "\n",
+    "* Grunnleggende syntaks\n",
+    "\n",
+    "* Utføre enkle utregninger i Python\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Hva tilsvarer 85 grader celsius i Fahrenheit?**\n",
+    "\n",
+    "$F = \\frac{9}{5} \\cdot Celsius + 32$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "185.0"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(9/5) * 85 + 32"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Oppgave 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Regn ut følgende i Python ved hjelp av kode**\n",
+    "\n",
+    "$4 \\cdot -2-2\\left(2+-5\\right)$\n",
+    "\n",
+    "$-2--2-2$\n",
+    "\n",
+    "$5-2^{-1\\cdot-1}$\n",
+    "\n",
+    "$-(1 \\cdot 1 \\cdot 2 \\cdot 3 \\cdot 5 \\cdot -8)$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-2"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "4 * -2 - 2 * (2 + -5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-2"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(-2) - (-2) - 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "5 - 2 ** (-1 * -1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "240"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "-(1 * 1 * 2 * 3 * 5 * -8)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Er 1000 000 000 større enn $2^{31}$?**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-1147483648"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Dersom dette gir et negativt tall, er 1 mrd mindre enn 2 ** 31\n",
+    "1000000000 - 2 ** 31"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 4\n",
+    "\n",
+    "Hva blir resten når $2^7$ deles på $42$ "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2 ** 7 % 42"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 5: Input\n",
+    "\n",
+    "**Lag et program som gjør følgende:**\n",
+    "1. Tar inn to tall fra bruker\n",
+    "2. Multipliserer dem \n",
+    "3. Skriver ut `(tall 1) * (tall 2) = (resultat)`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10 * 12 = 120\n"
+     ]
+    }
+   ],
+   "source": [
+    "tall1 = int(input(\"Skriv inn et tall: \"))\n",
+    "tall2 = int(input(\"Skriv inn et tall: \"))\n",
+    "\n",
+    "resultat = tall1 * tall2\n",
+    "\n",
+    "print(f\"{tall1} * {tall2} = {resultat}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 6: Innebygde funksjoner \n",
+    "\n",
+    "Skriv et program som spør brukeren om to tall og printer absoluttverdien av differansen\n",
+    "<br>\n",
+    "\n",
+    "Hint: Bruk den innebygde funksjonen **abs()**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tall1 = int(input(\"Skriv inn et tall: \"))\n",
+    "tall2 = int(input(\"Skriv inn et tall: \"))\n",
+    "\n",
+    "resultat = abs(tall1 - tall2)\n",
+    "\n",
+    "print(resultat)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 7: Feilretting og variabeltyper\n",
+    "\n",
+    "Følgende program skal regne ut og printe summen av prisen på tre varer. Prisene er lagret som forskjellige variabeltyper. Undersøk feilmeldingene og rett koden slik at den skriver ut riktig totalsum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Totalsummen for varene er 49.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "banan_pris = 10.50\n",
+    "melk_pris = 23.50 # Ta vekk fnuttene for å gjøre dette om fra string til float\n",
+    "havregryn_pris = 15\n",
+    "\n",
+    "total_sum = banan_pris + melk_pris + havregryn_pris\n",
+    "\n",
+    "print('Totalsummen for varene er ' + str(total_sum)) # Gjør om til str slik at vi kan sette sammen"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 8: Bruk av variabler\n",
+    "\n",
+    "Regn ut volumet av en kjegle med radius 3 og høyde 7.\n",
+    "\n",
+    "$V = \\frac{\\pi r^2 h}{3}$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "65.97344572538566\n"
+     ]
+    }
+   ],
+   "source": [
+    "import math\n",
+    "\n",
+    "radius = 3\n",
+    "height = 7\n",
+    "\n",
+    "volume = math.pi * radius ** 2 * height / 3\n",
+    "\n",
+    "print(volume)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 9: Variabler og input \n",
+    "\n",
+    "1. Endre kjegleprogrammet fra oppgave 6 til å ta inn radius og høyde fra brukeren\n",
+    "2. Verdiene skal være av desimaltall (float) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "radius = float(input(\"Skriv inn radius: \"))\n",
+    "height = float(input(\"Skriv inn height: \"))\n",
+    "\n",
+    "volume = math.pi * radius ** 2 * height / 3\n",
+    "\n",
+    "print(volume)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 10: Sammenligning\n",
+    "\n",
+    "Ta inn to tall fra brukeren og skriv ut True om det første tallet er større enn det andre, False dersom ikke"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tall1 = float(input(\"Skriv inn et tall: \")) # Kan velge mellom float og int her\n",
+    "tall2 = float(input(\"Skriv inn et tall: \")) \n",
+    "\n",
+    "is_1_larger_than_2 = tall1 > tall2\n",
+    "\n",
+    "print(is_1_larger_than_2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 11 (Ekstraoppgave): Lag en funksjon\n",
+    "\n",
+    "Lag en funksjon som kan regne om fra Celsius til Fahrenheit\n",
+    "\n",
+    "$F = \\frac{9}{5} \\cdot Celsius + 32$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_celsius_to_fahrenheit(celsius):\n",
+    "    return 9/5 * celsius + 32"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Oppgave 12 (Ekstraoppgave): Plotting\n",
+    "\n",
+    "Plot Celsius på x-aksen og Fahrenheit på y-aksen, fra -100 til 100 Celsius (hint: np.linspace). \n",
+    "\n",
+    "Bonus: Legg til labels på aksene og en \"Legend\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "from matplotlib import pyplot as plt\n",
+    "\n",
+    "x_axis = np.linspace(-100, 100)\n",
+    "\n",
+    "plt.plot(x_axis, convert_celsius_to_fahrenheit(x_axis), label=\"Fra vår funksjon\")\n",
+    "plt.ylabel(\"Fahrenheit\")\n",
+    "plt.xlabel(\"Celsius\")\n",
+    "plt.legend()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Fritt kodefelt (Du kan bruke  dette for å teste egen kode)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Skriv koden din her"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.6 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": "3.11.5"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
-- 
GitLab