{ "cells": [ { "cell_type": "markdown", "id": "d5929d1f-9d7f-4532-84cb-d08f03ed58d4", "metadata": {}, "source": [ "Dieses Notebook kann als Vorlage für die Plots von Blatt 1 benutzt werden." ] }, { "cell_type": "code", "execution_count": 1, "id": "555837e8", "metadata": {}, "outputs": [], "source": [ "# was hier passiert, ist nicht so wichtig, sondern soll nur eine drehbare 3D-Ansicht ermöglichen\n", "%matplotlib widget\n", "import matplotlib.pyplot as plt\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "id": "d37d65d6-521f-4cc7-8230-ca98c90897dd", "metadata": {}, "outputs": [], "source": [ "## es ist oft eine gute idee, teile eines programms, die man immer wieder benutzt, in funktionen auszulagern\n", "def curve3D( t ):\n", " \"\"\"A 3D trajectory\n", "\n", " Arguments:\n", " t (array): parameter for the trajectory\n", "\n", " Returns:\n", " A list of three elements, the (x,y,z)-points of the trajectory\n", " \"\"\"\n", " return [t, t, t]\n", "\n", "def curve2D( t ):\n", " \"\"\"A 2D trajectory\n", "\n", " Arguments:\n", " t (array): parameter for the trajectory\n", "\n", " Returns:\n", " A list of two elements, the (x,y)-points of the trajectory\n", " \"\"\"\n", " return [t, t]" ] }, { "cell_type": "code", "execution_count": 3, "id": "bff0d68b-0b71-4231-b149-374e331b939f", "metadata": {}, "outputs": [], "source": [ "## \"linspace\" erzeugt ein array mit 100 einträgen von 0 bis 10 in jeweils gleichem abstand\n", "parameter_range = np.linspace(0, 10, 100)" ] }, { "cell_type": "code", "execution_count": 4, "id": "a87cd20f-3913-4f7a-83ef-d12c40191b43", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5b4c31f488ca465b8d1dd4ae604db14b", "version_major": 2, "version_minor": 0 }, "image/png": 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", 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