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6.11.1-band-gap-width-of-semiconductor/logSigmaOnRevT.png
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6.11.1-band-gap-width-of-semiconductor/sigmaOnT.png
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6.11.5-tunnel-diode/vah-osc.jpg
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6.11.5-tunnel-diode/vah.png
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6.6.1-messbauer-effect/description.pdf
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solid-magnetic-gisteresis/data/Kazikov.csv
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solid-magnetic-gisteresis/data/Lugovcov-12V.csv
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solid-magnetic-gisteresis/data/Lugovcov.csv
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solid-magnetic-gisteresis/data/Smirnov.csv
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solid-magnetic-gisteresis/data/Zakharov.csv
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solid-magnetic-gisteresis/output/Kazikov.png
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solid-magnetic-gisteresis/output/Smirnov.png
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solid-magnetic-gisteresis/output/Zakharov.png
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solid-magnetic-gisteresis/output/pic4.png
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solid-magnetic-gisteresis/plots.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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||||
"id": "280f1e1b-c050-4f4a-b45b-b4d488b55d99",
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||||
"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# %load /home/glebi/git/experiment-automation/processing_tools.py\n",
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"import numpy as np\n",
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"from scipy.optimize import curve_fit\n",
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"import pandas as pd\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib as mpl\n",
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"import scienceplots\n",
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"\n",
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"plt.style.use(['science', 'russian-font'])\n",
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"\n",
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"mpl.rcParams.update({\n",
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" 'figure.figsize': [6, 4],\n",
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" 'savefig.facecolor': 'white',\n",
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" 'figure.dpi': 150.0,\n",
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" 'font.size': 12.0,\n",
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"})"
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]
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},
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{
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"cell_type": "markdown",
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||||
"id": "bb054603-67f5-4418-8c09-e8e3210ffb17",
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"metadata": {},
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"source": [
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"U_1 = 12V -- первые данные Lugovcov\n",
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"\n",
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"U = 25V -- остальные данные\n",
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"\n",
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"Формат:\n",
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"t[us], U[V], U[V]"
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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": 15,
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||||
"id": "01617d5c-6498-42db-bbe0-b24c0bf40ea8",
|
||||
"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"from random import random, randint, choice\n",
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"def plot_data(filename):\n",
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" t, x, y = np.loadtxt(f\"data//{filename}\", skiprows=1, delimiter=\",\").T\n",
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" r = 1 / (2**.5)\n",
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" a = 150 # Э/А\n",
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" B = -x / r * a\n",
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" H = y / r * a\n",
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" with mpl.rc_context({\n",
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" 'figure.figsize': [7, randint(3,5)],\n",
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" 'font.size': randint(10, 16), \n",
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" 'axes.grid' : random() > .5,\n",
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" 'axes.facecolor': f\"'{1-random()*.07}'\",\n",
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" 'axes.grid.axis': choice(['both']),\n",
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" 'axes.grid.which': choice(['both', 'minor', 'major'])\n",
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" }):\n",
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" fig, ax = plt.subplots()\n",
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" ax.plot(B, H, lw=random()*.3, color=f\"C{randint(0, 7)}\", linestyle=choice(['-', '--', ':']))\n",
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" ax.set_xlabel(\"Величина поля B, Э\")\n",
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" ax.set_ylabel(\"Величина поля H, Э\")\n",
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" fig.savefig(f\"output//{filename.split('.')[0]}.png\")"
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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": 16,
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||||
"id": "2c5c0796-12f5-4433-a202-35ce633d9dfe",
|
||||
"metadata": {
|
||||
"tags": []
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||||
},
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||||
"outputs": [],
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||||
"source": [
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"filenames = [\"Lugovcov.csv\", \"Kazikov.csv\", \"Smirnov.csv\", \"Zakharov.csv\"]\n",
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"\n",
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"for f in filenames:\n",
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" plot_data(f)"
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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": null,
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||||
"id": "fa22ed90-4ccd-4957-b3a6-a9c983141716",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
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||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
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"language": "python",
|
||||
"name": "python3"
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||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
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||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.12"
|
||||
}
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||||
},
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||||
"nbformat": 4,
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||||
"nbformat_minor": 5
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}
|