2022-10-07 13:23:12 +03:00
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{
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"cells": [
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{
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"cell_type": "code",
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2022-10-17 00:13:23 +03:00
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"execution_count": 102,
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2022-10-07 13:23:12 +03:00
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"id": "1dd847b1-0ad5-4f0f-b22b-8c68142dcbe3",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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2022-10-17 00:13:23 +03:00
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"import matplotlib.pyplot as plt\n",
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"from scipy.optimize import curve_fit"
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2022-10-07 13:23:12 +03:00
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]
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},
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{
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"cell_type": "code",
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2022-10-17 00:13:23 +03:00
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"execution_count": 103,
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2022-10-07 13:23:12 +03:00
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"id": "657cc2c7-920b-46e0-a7a8-ef65146ddf4e",
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"metadata": {},
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"outputs": [],
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2022-10-17 00:13:23 +03:00
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"source": [
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"I_names = np.array([13, 24, 35, 46, 57, 68, 79, 90, 101])\n",
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"I_values = I_names * 1.5 / 155# ток в мА"
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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": 124,
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"id": "61022dfd-06b7-43cb-ac1f-2128f46ff7ee",
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"metadata": {},
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"outputs": [],
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"source": [
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"colors = ['tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan']"
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]
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},
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{
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"cell_type": "markdown",
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"id": "cab0ae39-aeb0-425a-a38a-8491552135fe",
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"metadata": {
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"tags": []
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},
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"source": [
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"### График зависимости индукции от силы тока в обмотках магнита $B = f(I_\\text{М})$"
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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": 105,
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"id": "4c853de8-c61e-4ce0-b796-ffaa6e697b12",
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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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"df = pd.read_csv(rf'data/induction_on_amperage.csv')\n",
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"\n",
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"B = np.array(df['Ind[mT]'])\n",
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"I_m = np.array(df['I[mA]'])"
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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": 131,
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"id": "576974ec-5d4d-42c1-9280-7a7f9b74a6be",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 1800x1200 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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"plt.figure(figsize=(6, 4), dpi=300)\n",
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"\n",
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"# plt.minorticks_on()\n",
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"# plt.grid(which='minor', linestyle=':', color='0.9')\n",
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"plt.grid(which='major', linestyle='-', color='0.8', lw=0.3)\n",
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"\n",
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"plt.errorbar(I_m, B, xerr=5+0.003*I_m, yerr=0.5+0.003*B, lw=1, ls='', marker='.', markersize=8, label=r\"$B = f(I_М)$\", ds='default')\n",
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" \n",
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"plt.xlabel(r\"$I_М$, мА\")\n",
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"plt.ylabel(r\"$B$, мТл\")\n",
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"\n",
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"plt.legend()\n",
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"plt.savefig(rf\"images/BonI.png\", facecolor=\"white\")\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c9e18b07-8656-49b4-bf8e-1c2371bee3e5",
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"metadata": {},
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"source": [
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"### Семейство характеристик $\\varepsilon_\\text{х} = f(B)$"
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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": 108,
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"id": "fadcfd44-216a-4449-9e75-398c8d3c740c",
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"metadata": {},
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"outputs": [],
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"source": [
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"def B_approx(x):\n",
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" for i, xi in enumerate(I_m):\n",
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" if xi >= x:\n",
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" x1 = I_m[i - 1]\n",
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" x2 = I_m[i]\n",
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" y1 = B[i - 1]\n",
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" y2 = B[i]\n",
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" return y1 + (y2-y1)/(x2-x1)*(x-x1)"
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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": 113,
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"id": "e6741806-03fb-487f-8366-bbb6c825c49b",
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"metadata": {},
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"outputs": [],
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"source": [
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"def line(x, arg1, arg2):\n",
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" return x * arg1 + arg2"
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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": 176,
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"id": "08c7f31f-1c40-4904-b619-91c227f7a6b3",
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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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
|
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"text/plain": [
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"<Figure size 1800x1200 with 1 Axes>"
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|
]
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|
},
|
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"metadata": {
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|
|
"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
|
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"source": [
|
|
|
|
|
|
"plt.figure(figsize=(6, 4), dpi=300)\n",
|
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|
|
|
|
"plt.grid(which='major', linestyle='-', color='0.8', lw=0.3)\n",
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"\n",
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"dE_dB = []\n",
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"\n",
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|
|
|
"for i, I_name in enumerate(I_names):\n",
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|
" df = pd.read_csv(rf\"data/VoA_{I_name}.csv\")\n",
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" \n",
|
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|
|
|
" U_ = df[\"U_34[mV]\"]\n",
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|
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" U0 = U_[0]\n",
|
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" U = 1000*(U0 - U_)\n",
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" \n",
|
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|
|
|
" I_ = df[\"I_m[mA]\"]\n",
|
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|
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" B_ = np.array([B_approx(x) for x in I_], dtype=np.float64)\n",
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" \n",
|
|
|
|
|
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" popt, pcov = curve_fit(line, B_, U)\n",
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" \n",
|
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|
|
" # print(f\"k = {popt[0]:.4f} \\t \")\n",
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|
|
" dE_dB.append(popt[0]/1000)\n",
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" \n",
|
|
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|
|
|
" plt.errorbar(B_, U, xerr=1+0.003*B_, yerr=1+0.003*U, ls='', marker='.', markersize=4, label=r\"$I_{||} = $\"+rf\"${I_values[i]:.2f}\\pm{1.5/155:.2f}$ мА\", ds='default', color=colors[i])\n",
|
|
|
|
|
|
" plt.plot(B_, line(B_, popt[0], popt[1]), color=colors[i], lw=1)\n",
|
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|
"\n",
|
|
|
|
|
|
"dE_dB = np.array(dE_dB) * 1000\n",
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|
|
" \n",
|
|
|
|
|
|
"plt.xlabel(r\"$B$, мТл\")\n",
|
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|
|
"plt.ylabel(r\"$\\varepsilon_x$, мкВ\")\n",
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"\n",
|
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|
|
|
"plt.legend()\n",
|
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|
|
"plt.savefig(rf\"images/UonB.png\", facecolor=\"white\")\n",
|
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|
|
"plt.show()"
|
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]
|
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|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
|
"id": "ed4c8024-e86f-4672-bd64-1d5d8e596592",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"### Зависимость $k = f(I)$"
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|
]
|
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|
},
|
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|
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|
{
|
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": 179,
|
|
|
|
|
|
"id": "0d76d070-47ce-4f4f-9342-566a1107abab",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
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|
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|
|
"data": {
|
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|
|
"image/png": "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
|
|
|
|
|
|
"text/plain": [
|
|
|
|
|
|
"<Figure size 1800x1200 with 1 Axes>"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
"metadata": {
|
|
|
|
|
|
"needs_background": "light"
|
|
|
|
|
|
},
|
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"plt.figure(figsize=(6, 4), dpi=300)\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.grid(which='major', linestyle='-', color='0.8', lw=0.3)\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"popt, pcov = curve_fit(line, I_values, dE_dB)\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"k = popt[0]\n",
|
|
|
|
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|
"\n",
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"plt.errorbar(I_values, dE_dB, xerr=0.01, yerr=3.15e-03, color=colors[0], lw=1, ls='', marker='.', markersize=4, label=r\"$\\dfrac{d\\varepsilon_x}{dB} = f(I_{||})$\", ds='default')\n",
|
|
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"plt.plot(I_values, line(I_values, popt[0], popt[1]), color=colors[0], lw=1)\n",
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"\n",
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"plt.xlabel(r\"$I_М$, мА\")\n",
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"plt.ylabel(r\"$d\\varepsilon_x/dB$, мВ/Тл\")\n",
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"\n",
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"plt.legend()\n",
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"plt.savefig(rf\"images/KonI.png\", facecolor=\"white\")\n",
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"plt.show()"
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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": 180,
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"id": "2d140d8b-b9fb-48b7-88fd-ccd862fc794f",
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"metadata": {},
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"outputs": [],
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"source": [
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"h = 2.2e-3"
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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": 189,
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"id": "deb90002-f303-4b6b-ad90-e3c83d3ab41b",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"0.0004318927697950297"
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]
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},
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"execution_count": 189,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"R_h = k*h\n",
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"R_h"
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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": 190,
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"id": "8731ed11-0b5c-4304-9ab3-eb563dbe33e3",
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"metadata": {},
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"outputs": [],
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"source": [
|
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"q = 1.6e-19"
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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": 191,
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"id": "048587bd-6a59-449c-a65c-86f810f3ce4c",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1.44711846020626e+22"
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]
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},
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"execution_count": 191,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
|
|
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"n = 1 / (R_h * q)\n",
|
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"n"
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]
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},
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{
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"cell_type": "code",
|
2022-10-18 11:37:28 +03:00
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"execution_count": 204,
|
2022-10-17 00:13:23 +03:00
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"id": "8f61c6e8-356b-4a4c-b797-dd5e8d0331eb",
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"metadata": {},
|
2022-10-18 11:37:28 +03:00
|
|
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"outputs": [],
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|
"source": [
|
|
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|
"a = 2.2e-3\n",
|
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|
|
"L35 = 3e-3\n",
|
|
|
|
|
|
"l = 2.5e-3"
|
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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": 207,
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"id": "1f153f00-d44c-41e5-8bab-ad09bd8e5896",
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"metadata": {},
|
2022-10-17 00:13:23 +03:00
|
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"outputs": [
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{
|
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"data": {
|
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"text/plain": [
|
2022-10-18 11:37:28 +03:00
|
|
|
|
"274.0977615349475"
|
2022-10-17 00:13:23 +03:00
|
|
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]
|
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},
|
2022-10-18 11:37:28 +03:00
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"execution_count": 207,
|
2022-10-17 00:13:23 +03:00
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"metadata": {},
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"output_type": "execute_result"
|
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}
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|
],
|
|
|
|
|
|
"source": [
|
2022-10-18 11:37:28 +03:00
|
|
|
|
"sigma = 1 * L35/(1.99 * a * l)\n",
|
2022-10-17 00:13:23 +03:00
|
|
|
|
"sigma"
|
|
|
|
|
|
]
|
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|
|
},
|
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|
{
|
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|
"cell_type": "code",
|
2022-10-18 11:37:28 +03:00
|
|
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|
"execution_count": 208,
|
2022-10-17 00:13:23 +03:00
|
|
|
|
"id": "cf5b7366-16f9-434f-969f-74b61fed23ca",
|
|
|
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|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
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|
|
|
{
|
|
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|
|
"data": {
|
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|
"text/plain": [
|
2022-10-18 11:37:28 +03:00
|
|
|
|
"1183.8084142394603"
|
2022-10-17 00:13:23 +03:00
|
|
|
|
]
|
|
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|
|
|
},
|
2022-10-18 11:37:28 +03:00
|
|
|
|
"execution_count": 208,
|
2022-10-17 00:13:23 +03:00
|
|
|
|
"metadata": {},
|
|
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|
|
"output_type": "execute_result"
|
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|
|
}
|
|
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|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"b = sigma * R_h\n",
|
|
|
|
|
|
"b*10000"
|
|
|
|
|
|
]
|
2022-10-07 13:23:12 +03:00
|
|
|
|
}
|
|
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|
|
|
],
|
|
|
|
|
|
"metadata": {
|
|
|
|
|
|
"kernelspec": {
|
|
|
|
|
|
"display_name": "Python 3 (ipykernel)",
|
|
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|
|
"language": "python",
|
|
|
|
|
|
"name": "python3"
|
|
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|
|
},
|
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|
|
"language_info": {
|
|
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|
|
"codemirror_mode": {
|
|
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|
|
"name": "ipython",
|
|
|
|
|
|
"version": 3
|
|
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|
|
},
|
|
|
|
|
|
"file_extension": ".py",
|
|
|
|
|
|
"mimetype": "text/x-python",
|
|
|
|
|
|
"name": "python",
|
|
|
|
|
|
"nbconvert_exporter": "python",
|
|
|
|
|
|
"pygments_lexer": "ipython3",
|
|
|
|
|
|
"version": "3.10.2"
|
|
|
|
|
|
}
|
|
|
|
|
|
},
|
|
|
|
|
|
"nbformat": 4,
|
|
|
|
|
|
"nbformat_minor": 5
|
|
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|
|
|
}
|
