384 lines
115 KiB
Plaintext
384 lines
115 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "1a44722c-9586-4418-ad7f-8a3c964a9db8",
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"metadata": {},
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"source": [
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"# Grafiken"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "d29042ce-7023-45f2-a389-e73d4ddfd7e8",
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"metadata": {
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"tags": [
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"hide-input"
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]
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},
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"outputs": [],
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"source": [
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"import random\n",
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"def rand_numbers(n, start, end, digits=2):\n",
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" \"\"\" Erzeugt einen Array mit Zufallszahlen mit 2 Nachkommastellen\n",
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" n\n",
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" Anzahl der erzeugten Zufallszahlen\n",
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" \n",
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" start\n",
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" Kleinste mögliche Zahl (inklusiv)\n",
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" \n",
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" end\n",
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" Größte mögliche Zahl (exklusiv)\n",
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" \n",
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" digits\n",
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" Anzahl Nachkommastellen, Default: 2\n",
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" \"\"\"\n",
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" factor = 10 ** digits\n",
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" result = []\n",
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" for i in range(n):\n",
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" result.append(random.randint(start * factor, end * factor) / factor)\n",
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" \n",
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" return result "
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]
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},
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{
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"cell_type": "markdown",
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"id": "ab90ad44-8536-4445-8674-a451a9a4971f",
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"metadata": {},
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"source": [
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"## Matplotlib\n",
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"\n",
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"Bisher haben wir nur mit Zahlen ein Texten gearbeitet.\n",
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"Dafür haben wir die Packages `math` und `random` verwendet.\n",
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"\n",
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"Jetzt möchten wir Grafiken erzeugen. Dazu benötigen wir ein weiteres Package: `mathplotlib`,\n",
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"genauer gesagt, davon erst einmal nur den Teil `pyplot`.\n",
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"\n",
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"Um uns Tipparbeit zu sparen sagen wir beim `import`, dass wir im Folgenden dieses Package `plt` nennen möchten."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "89b767d1-4305-492b-984f-960b322e89a6",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"numbers = rand_numbers(50, -100, 100)\n",
|
|
"plt.plot(numbers);\n",
|
|
"plt.show() # bei manchen Jupyter-Versionen nicht nötig, einfach mal ohne testen"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "fa5231c5-7b2a-4d02-a0e3-69a8ee78d930",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Aufgabe\n",
|
|
"Erklärt,\n",
|
|
"1. was das Programm tut\n",
|
|
"2. was auf der Grafik zu sehen ist\n",
|
|
"3. wozu das Semikolon in der vorletzten Zeile dient"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "486f4398-0d21-411d-8f91-e57fc925d2b8",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Lösung\n",
|
|
"1. Was tut Programm?\n",
|
|
" - es importiert die Bibliothek `mathplotlib.pyplot`. Diese enthält Funktionen zum Zeichnen von Grafiken\n",
|
|
" - diese Bibliothek nennen wir `plt` weil das schneller zu schreibenist als `mathplotlib.pyplot`\n",
|
|
" - 50 Zufallszahlen zwischen -100 und 100 erzeugt und diese im Array mit dem Namen `numbers` speichern\n",
|
|
" - die Zufallszahlen in `numbers` zeichnen\n",
|
|
"1. Was ist auf Grafik zu sehen?\n",
|
|
" - Der Wert der Zufallszahlen ist auf der y-Achse\n",
|
|
" - Die 0te Zufallszahl ist auf der x-Achse bei x=0, die 1te Zufallszahl bei x=1 usw.\n",
|
|
"1. Die Funktion plot() zeichnet die Grafik und liefert zusätzlich noch ein Ergebnis zurück. Das Semikolon sorgt dafür, dass das Ergebnis nicht angezeigt wird."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5feb449e-76c4-4ea9-b0e2-4912f100cc39",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Aufgabe\n",
|
|
"Wie kann man erkennen, wie gleichmäßig die Zufallszahlen verteilt sind?"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "7d02f67c-6395-42be-988d-e29d182d0bd5",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Lösung\n",
|
|
"Die Zufallszahlen der Größe nach sortieren.\n",
|
|
"Je gleichmäßiger sie verteilt sind desto gerader ist die Linie im Graphen."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "c3cd108d-ec9f-4570-b604-b18c07887f95",
|
|
"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": [
|
|
"numbers.sort()\n",
|
|
"plt.plot(numbers);\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4866c521-8484-413b-80af-7bb129a5c2c5",
|
|
"metadata": {},
|
|
"source": [
|
|
"Das sieht schon nicht schlecht aus. Abweichungen von der Gerade sind aber deutlich zu sehen."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "2f2ddb2c-d63e-4ee7-b5c1-1c148eea8787",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Aufgabe\n",
|
|
"Welche Stelle im Programm muss geändert werden damit der erzeugte Graph viel näher an einer Gerade ist?"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "7cc38c4b-8ff6-4549-9a26-df42bad9e42f",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Lösung\n",
|
|
"Nach dem Gesetz der großen Zahlen müsste die Abweichung von der Gerade kleiner werden wenn man mehr Zufallszahlen zieht."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "aee05f91-0bbd-4c9e-a972-ff305167c974",
|
|
"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": [
|
|
"numbers = rand_numbers(10000, -100, 100)\n",
|
|
"numbers.sort()\n",
|
|
"plt.plot(numbers);\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "fcdd2a03-14b2-4424-a0a0-5bc1e73017ae",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Matplotlib Dokumentation\n",
|
|
"\n",
|
|
"Dokumentation zu Matplotlib und anderen Python Packages findet man im unteren Teil des Hilfe-Menüs.\n",
|
|
"\n",
|
|
"![jupyter_help.png](jupyter_help.png)\n",
|
|
"\n",
|
|
"Falls diese fehlen:\n",
|
|
"* matplotlib: https://matplotlib.org/stable/api/index.html\n",
|
|
"* pandas: https://pandas.pydata.org/docs/reference/index.html"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "95389da8-8526-4904-bc04-01a2104f1d1d",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Aufgabe\n",
|
|
"Erzeuge einen Graph mit Sinus und Cosinus-Funktion."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "34fcc9ed-61b0-483a-ae79-fb5faa25ac9b",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Lösung"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "0c429b71-11b0-4a30-8710-61298f161185",
|
|
"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": [
|
|
"import math\n",
|
|
"\n",
|
|
"sins = []\n",
|
|
"coss = []\n",
|
|
"\n",
|
|
"for i in range(360):\n",
|
|
" sins.append(math.sin(math.radians(i)))\n",
|
|
" coss.append(math.cos(math.radians(i))) \n",
|
|
" \n",
|
|
"plt.plot(sins)\n",
|
|
"plt.plot(coss);\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6dda6efa-5540-4659-8f66-afd18b697f5c",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Aufgabe\n",
|
|
"* Lest die Dokumentation zu `plt.plot` und verändert\n",
|
|
" * Farbe der Linie\n",
|
|
" * Dicke der Linie\n",
|
|
" * Beschriftung der x-Achse (Werte in Bogen- statt Gradmaß)\n",
|
|
"* Lest die Dokumentation zu `plot` und versucht den Graphen zu beschriften"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ba58416c-8104-468b-8a0b-88cf86e85879",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Lösung"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "9e65731d-e81f-491a-ace5-46eaa6e208e6",
|
|
"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": [
|
|
"import math\n",
|
|
"\n",
|
|
"sins = []\n",
|
|
"coss = []\n",
|
|
"rads = []\n",
|
|
"\n",
|
|
"for i in range(360):\n",
|
|
" r = math.radians(i)\n",
|
|
" rads.append(r)\n",
|
|
" sins.append(math.sin(r))\n",
|
|
" coss.append(math.cos(r))\n",
|
|
"\n",
|
|
"plt.plot(rads, sins, color='violet', linewidth=2)\n",
|
|
"plt.plot(rads, coss, color='darkblue', linewidth=2)\n",
|
|
"\n",
|
|
"plt.title('sin(x) und cos(x)')\n",
|
|
"plt.xlabel('x von 0 bis 2π')\n",
|
|
"plt.ylabel('y')\n",
|
|
"plt.legend(['sin(x)', 'cos(x)']);\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "470cd36c-2758-4f6f-b359-3a6adfb127dc",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Grafiken speichern/exportieren\n",
|
|
"\n",
|
|
"Bilder können nicht nur angezeigt sondern auch gespeichert werden. Dies muss *vor* dem Aufruf von `plt.show()` geschehen:\n",
|
|
"\n",
|
|
"```\n",
|
|
"plt.savefig('sin_cos.png');\n",
|
|
"plt.savefig('sin_cos.pdf');\n",
|
|
"plt.savefig('sin_cos.svg');\n",
|
|
"plt.savefig('sin_cos.png', dpi=300, transparent=True, bbox_inches='tight')\n",
|
|
"\n",
|
|
"plt.show()\n",
|
|
"```"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"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": "3.9.7"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|