2023-09-15 23:46:38 +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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2023-09-29 12:46:12 +03:00
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"execution_count": 1,
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2023-09-15 23:46:38 +03:00
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"id": "3e9c91d2-a8a3-4cf4-a3bd-682f4979776a",
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"metadata": {},
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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\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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2023-09-29 12:46:12 +03:00
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"plt.style.use([\"bright\"])\n",
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"\n",
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"matplotlib.rcParams.update({\n",
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" 'figure.figsize': [6, 4],\n",
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" 'savefig.facecolor': 'white',\n",
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2023-09-29 13:25:15 +03:00
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" 'figure.dpi': 200.0,\n",
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2023-09-15 23:46:38 +03:00
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" 'font.size': 12.0,\n",
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2023-09-29 13:25:15 +03:00
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"})\n",
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"\n",
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"def line_func(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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2023-09-29 12:46:12 +03:00
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"execution_count": 2,
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2023-09-15 23:46:38 +03:00
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"id": "5e765906-9269-4ba2-81ba-fb2fd3d798f1",
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"metadata": {},
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"outputs": [
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{
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"data": {
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2023-09-29 13:41:43 +03:00
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"image/png": "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2023-09-15 23:46:38 +03:00
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"text/plain": [
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2023-09-29 13:25:15 +03:00
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"<Figure size 1200x800 with 1 Axes>"
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2023-09-15 23:46:38 +03:00
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]
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},
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"metadata": {},
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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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"df = pd.read_csv(\"VAH.csv\")\n",
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"cols = df.columns\n",
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"\n",
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2023-09-29 13:41:43 +03:00
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"plt.plot(df[cols[0]] * 1e-3, df[cols[1]]*1e-1, marker=\".\", lw=.5, color=\"C2\", ls=\"--\")\n",
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2023-09-15 23:46:38 +03:00
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"plt.xlabel(\"Напряжение, кВ\")\n",
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"plt.ylabel(\"Сила тока, мкА\")\n",
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"\n",
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2023-09-29 12:46:12 +03:00
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"plt.savefig(\"hand-VAH.png\")\n",
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2023-09-15 23:46:38 +03:00
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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": "d084ce30-37aa-440c-ab41-591ab094d21f",
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"metadata": {},
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"source": [
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"сопротивление нашей цепи"
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]
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},
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{
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"cell_type": "code",
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2023-09-29 12:46:12 +03:00
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"execution_count": 3,
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2023-09-15 23:46:38 +03:00
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"id": "5b0cd085-4398-4b10-b6cc-3147d4e616f8",
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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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"13991140.642303433"
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]
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},
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2023-09-29 12:46:12 +03:00
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"execution_count": 3,
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2023-09-15 23:46:38 +03:00
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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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"1263.4 / (903e-7)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "cd1ec375-3bdd-4bcb-88a0-fa6dcf173ec4",
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"metadata": {},
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"source": [
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"максимальное напряжение на резисторе, который снимает ток"
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]
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},
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{
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"cell_type": "code",
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2023-09-29 12:46:12 +03:00
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"execution_count": 4,
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2023-09-15 23:46:38 +03:00
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"id": "cfe69bd0-e5c9-45af-826b-22e759bc6eca",
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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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"8.32"
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]
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},
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2023-09-29 12:46:12 +03:00
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"execution_count": 4,
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2023-09-15 23:46:38 +03:00
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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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"1600e-7 * 52e3"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6a53d766-e438-4378-b7b0-db3c46578f2c",
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"metadata": {},
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"source": [
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"аналитическая функция вах"
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]
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},
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{
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"cell_type": "code",
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2023-09-29 12:46:12 +03:00
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"execution_count": 5,
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2023-09-15 23:46:38 +03:00
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"id": "8a4273c4-db67-40b9-b887-926d8e6866e1",
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"metadata": {},
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"outputs": [],
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"source": [
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|
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"# def vah_func(u):\n",
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"# return S_e * (1.537e10 / )"
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]
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},
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2023-09-29 13:25:15 +03:00
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{
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"cell_type": "markdown",
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"id": "59f5605a-6a22-49de-98a2-bc83e9d8d49b",
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"metadata": {},
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"source": [
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"обработка данных"
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]
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},
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2023-09-15 23:46:38 +03:00
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{
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"cell_type": "code",
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2023-09-29 12:46:12 +03:00
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"execution_count": 6,
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2023-09-29 13:25:15 +03:00
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"id": "87f15973-cb08-477e-a81d-2a81e1536105",
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"metadata": {},
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"outputs": [],
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"source": [
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"U_min = 900\n",
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"R = 26.99e3 # Ом\n",
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"\n",
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"column_names = [\"Voltage\", \"Current\"]\n",
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"\n",
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"experiment_names = [\"Первая серия измерений\", \"Вторая серия измерений\"]\n",
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"file_idxs = [[1, 2, 3], [4, 5]]\n",
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"\n",
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"dots_result = [None, None]\n",
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"ex_result = [None, None]\n",
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"\n",
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"for num, (ex_name, f_idxs) in enumerate(zip(experiment_names, file_idxs)):\n",
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" result = pd.DataFrame(columns=column_names)\n",
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"\n",
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" for i in f_idxs:\n",
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" df = pd.read_csv(f\"RISING-{i}.csv\", header = None)\n",
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" df = df.loc[lambda x : x[4] > U_min]\n",
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"\n",
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" U = df[4] # В\n",
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|
|
" U_cur = df[10]\n",
|
|
|
|
|
|
" I = U_cur / R # А\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
" result = pd.concat([result, pd.concat(dict(zip(column_names, [U, I])), axis=1)], ignore_index=True)\n",
|
|
|
|
|
|
" \n",
|
|
|
|
|
|
" result[\"Current\"] -= min(result[\"Current\"])\n",
|
|
|
|
|
|
" ex_result[num] = result.groupby(\"Voltage\").mean().reset_index()\n",
|
|
|
|
|
|
" dots_result[num] = result"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
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|
|
|
"cell_type": "code",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"execution_count": 7,
|
2023-09-15 23:46:38 +03:00
|
|
|
|
"id": "24817123-a6cd-47a5-a153-7d4e6ab68135",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
|
|
|
"data": {
|
2023-09-29 12:46:12 +03:00
|
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|
"image/png": "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
|
2023-09-15 23:46:38 +03:00
|
|
|
|
"text/plain": [
|
2023-09-29 13:25:15 +03:00
|
|
|
|
"<Figure size 1200x800 with 1 Axes>"
|
2023-09-15 23:46:38 +03:00
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
2023-09-29 13:25:15 +03:00
|
|
|
|
"for num, (ex_name, dots, line) in enumerate(zip(experiment_names, dots_result, ex_result)):\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
" plt.plot(dots[\"Voltage\"]*1e-3, dots[\"Current\"]*1e6, alpha=0.01, ls=\"\", marker=\".\", markersize=2, color=f\"C{num}\")\n",
|
|
|
|
|
|
" plt.plot(line[\"Voltage\"]*1e-3, line[\"Current\"]*1e6, lw=1.5, alpha=1, color=f\"C{num}\", label=ex_name)\n",
|
|
|
|
|
|
"else:\n",
|
|
|
|
|
|
" df = pd.read_csv(\"VAH.csv\")\n",
|
|
|
|
|
|
" cols = df.columns\n",
|
|
|
|
|
|
" plt.plot(df[cols[0]]*1e-3, df[cols[1]]*1e-1, marker=\".\", lw=1, markersize=3, ls=\"--\", color=\"C2\", label=\"Ручные измерения\")\n",
|
|
|
|
|
|
" \n",
|
|
|
|
|
|
"plt.xlabel(fr\"Напряжение, кВ\")\n",
|
|
|
|
|
|
"plt.ylabel(fr\"Сила тока, мкА\")\n",
|
2023-09-29 13:25:15 +03:00
|
|
|
|
"# plt.yscale(\"log\")\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.legend()\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"plt.savefig(\"all-VAH.png\")\n",
|
2023-09-29 13:25:15 +03:00
|
|
|
|
"plt.show()"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
2023-09-29 12:46:12 +03:00
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
|
"id": "8c61ec35-5368-4a1c-8708-9f5b08d969f7",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"### Прямые с осциллографа"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
2023-09-29 13:25:15 +03:00
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"execution_count": 8,
|
2023-09-29 13:25:15 +03:00
|
|
|
|
"id": "f964e34e-f019-49d3-9815-86764aad6a64",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
|
|
|
"name": "stdout",
|
|
|
|
|
|
"output_type": "stream",
|
|
|
|
|
|
"text": [
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"0: k= -10.50\tb= -15.26\n",
|
|
|
|
|
|
"1: k= -7.50\tb= -17.57\n"
|
2023-09-29 13:25:15 +03:00
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"data": {
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"image/png": "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
|
2023-09-29 13:25:15 +03:00
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|
"text/plain": [
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"<Figure size 1200x800 with 1 Axes>"
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|
]
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|
|
},
|
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"metadata": {},
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"output_type": "display_data"
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}
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],
|
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"source": [
|
|
|
|
|
|
"opt_arr = []\n",
|
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|
|
|
"for num, (ex_name, line) in enumerate(zip(experiment_names, ex_result)):\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
" x = 1e3 / line[\"Voltage\"]\n",
|
2023-09-29 13:25:15 +03:00
|
|
|
|
" y = np.log(line[\"Current\"]) - 2 * np.log(line[\"Voltage\"])\n",
|
2023-09-15 23:46:38 +03:00
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|
" \n",
|
2023-09-29 13:25:15 +03:00
|
|
|
|
" popt, pcov = curve_fit(line_func, x, y)\n",
|
|
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|
|
|
" print(f\"{num}: k= {popt[0]:.2f}\\tb= {popt[1]:.2f}\")\n",
|
|
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|
|
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" opt_arr.append(popt)\n",
|
2023-09-15 23:46:38 +03:00
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|
" \n",
|
2023-09-29 13:25:15 +03:00
|
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|
" plt.plot(x, y, ls=\"\", marker=\".\", markersize=5, color=f\"C{num}\", label=ex_name)\n",
|
|
|
|
|
|
" plt.plot(x, line_func(x, *popt), lw=0.5, alpha=.5, color=f\"C{num}\")\n",
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|
"\n",
|
2023-09-29 13:41:43 +03:00
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|
"plt.xlabel(r\"$\\dfrac {10^3} U$, у.е.\")\n",
|
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|
|
"plt.ylabel(r\"$\\log \\dfrac I {U^2}$, у.е.\")\n",
|
2023-09-15 23:46:38 +03:00
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|
"\n",
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"plt.legend()\n",
|
2023-09-29 12:46:12 +03:00
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|
|
"plt.savefig(\"osc-NORDGAME-FAULER.png\")\n",
|
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|
"plt.show()"
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]
|
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|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
|
"id": "bb204b4f-dc40-4da5-bb0f-465162d6460f",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"### Прямая ручная"
|
|
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|
|
]
|
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|
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|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"execution_count": 9,
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"id": "6b0c2a09-1033-43c5-baa4-02616c6bdb91",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
|
|
|
"name": "stdout",
|
|
|
|
|
|
"output_type": "stream",
|
|
|
|
|
|
"text": [
|
|
|
|
|
|
"1: k= -11.41\tb= -14.52\n"
|
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|
|
|
]
|
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|
},
|
|
|
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|
|
{
|
|
|
|
|
|
"data": {
|
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|
|
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAABEkAAAL2CAYAAAC9qcjXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAB7CAAAewgFu0HU+AACi3ElEQVR4nOz9e3CUdb73/X6uJJAAIemEcGgSkHSHQEQO6QZlVFBMRxxnxEHSMkpm1666l8m6y73/uJ01ybCcvdV6rMcJa/lUPU/V3Gt1nKq99210hI7iMM6MmI4IgieSDuAhAkknHIMQQoN4QEh6/+FKD4EcoZMr3Xm/qqhq+7quX3/SHZXr29/f72eEQqGQAAAAAAAAxrg4swMAAAAAAACMBhRJAAAAAAAARJEEAAAAAABAEkUSAAAAAAAASRRJAAAAAAAAJFEkAQAAAAAAkESRBAAAAAAAQBJFEgAAAAAAAElSgtkBMLa0t7dr+/btmjNnjiZMmGB2HAAAAABAjPvuu+/U2tqq1atXKyMjo99zKZJgRG3fvl3FxcVmxwAAAAAAjDFVVVXasGFDv+dQJIlR5eXlqq6uViAQkM1mk8Ph0LJly1RWVjbgtcFgUC+88IL8fr8kqaOjQ5Lkcrm0ceNGWSyWG841Z84cST/+cubl5fV7bmNjo4qLiwd17lAw7vCPzbiMy7gjOzbjMi7jjty4wzk24zIu447cuMM5NuOOvnG7r+m+H+0PRZIYEwgE5Ha7VVpaqvr6elksFvn9fr3wwgsqLy+Xx+OR1+uVw+Ho9Xqfz6fy8nJt3LhRFRUV4ef9fr8KCgq0adMmeTwelZSU3FC+7ik2eXl5fWa41lDOHQrGHf6xGZdxGXdkx2ZcxmXckRt3OMdmXMZl3JEbdzjHZtzRN+5glnxg4dYYEgwGVVhYKK/Xq5KSknDHh8PhkNfrVVlZmQKBgJxOpwKBwHXXBwIBlZeXq76+XkVFRT2OdY8hSaWlpfL5fMP+8wAAAAAAMJIoksSQ8vJyVVRUyGaz9Xq8oqIiXDhxu93XHfd4PPL7/SosLOz1epfL1WOsaGW1WvXMM8/IarWO6XGHe+zhEG3vcbSNO1yi7X3g37l/iLb3ONrGHS7R9j5E27jDKdrei2gbd7hE2/sQbeMOp2h7L6Jt3OEy7HlDiBkWi2XAcyoqKkKSQpJCNTU1PY65XK7wsebm5l6vt9lsIUmDeq3e1NfXhySF6uvrI3ouRhc+u+jE5xa9+OyiE59b9OKzi058btGJzy16jabPbihZ6CSJEX6/X8FgUIZh9DsV5uo5WzU1NT2OlZaWymKxyOVy9dmN0r2Ia1/HAQAAAACIVhRJYsTVa4x4PJ4+z0tPTw8/DgaDPY4VFRXp3Llz1xVPrj6/+5qrp94AAAAAABALKJLECJfLJYfDIYvFotLS0j7P6+4EkSS73T6k19iyZYskyWKxaOPGjTcWdAiibW4c/oHPLjrxuUUvPrvoxOcWvfjsohOfW3Tic4te0frZGaFQKGR2CIycTZs2qby8XNKP020G2xESDAaVnZ2tYDA4pOuu5ff75XQ6VV9fP2xbeAEAAAAA0G0o96EJI5QJo0T3VByHwzGoQkcwGFRdXZ1KS0tls9n00ksvRaS40djY2Ocxq9UaddVGAAAAAIB52tra1NbW1uux/u4/r0WRZAzx+XzhtUteeumlfs+trq6Wx+NRR0eH/H6/HA6HKioqItb9UVxc3OexZ555Rs8++2xEXgcAAAAAEPs8Ho+ee+65mx6H6TZjiN1uVyAQUEVFhcrKyoZ0rd/vl9vtVkdHh7xe701Pt6mqqlJeXl6v59BJAgAAAAAYioE6SYqLi5lug38oLS294QKJ9OP0nPr6eqWlpamwsPCGx+mWl5fHmiQAAAAAgIiI1Jft7G4zAoLBoAzDiNgfp9M5pNevrKxUZWXlTRc2LBaLSkpKJEnl5eXy+/03PBYAAAAAAKMNnSQjwGKxqKamRsFgMCLj2Wy2QZ/r8/lUWloqj8cTLnDcjMLCQlVWVkr6cc5X90KwAAAAAABEO4okI+RG1/C4Gd3riHi9XhUVFQ3qXIvFIq/X22chxmKxhB/X1dVFMi4AAAAAAKZiuk2MCgQCKigo6LNAEgwG5fP5wv/s8XgUCATk9/vpDgEAAAAAjEkUSWJQMBhUYWGhamtr++xgqaur67GmyNUdIsuWLetz7O4thCVzumMAAAAAABguFEliTDAYDHeQ9Ld7TE1NTY/j69evl8ViUXNzc79Tc7xeb/hxaWlpZEIDAAAAADAKsCZJjCkoKJDL5VIgEOjR9XG1QCCgysrKHkUOh8OhkpISVVRU9Dndxufzhafo9LduCQAAAAAA0YgiSQwpLCyU3+8f9Na81xY5KioqVF5eLqfTqY0bN8rlcoWn4VRXV+uJJ56QxWJRRUXFgAvBAgAAAAAQbSiSxIjq6uoeC7EOpK+pOBUVFQoEAqqoqNALL7ygYDCojo4Opaenq6SkRBs3buyxfgkAAAAAALGCIkmMKCoqUigUishYNpttTO9w09nVqb3HG3T6YrumJWdoWVa+4uPizY4FAAAAABhmFEmAq2w/tEPP176okxdOhZ/LTLHq6YKntDp3lYnJAAAAAADDjd1tgP+y/dAOPbm1rEeBRJJOXGjTk1vLtP3QDpOSAQAAAABGAkUSQD9OsXm+9kWF1PuUpZBCer72RXV2dY5wMgAAAADASKFIAkjae7zhug6Sa528cEp7jzeMUCIAAAAAwEijSAJIOn2xPaLnAQAAAACiD0USQNK05IyIngcAAAAAiD4USQBJy7LyNTNlRr/nZKZYtSwrf4QSAQAAAABGGkUSQFJ8XLx+V/BrGTJ6PW7I0NMFTyk+Lv66Y51dnfroaJ22ffG2Pjpax+KuAAAgJpSWlsowjEH/sdvtKiwsVGVlpdnRAeCGUSQB/svq3FX6w9pN13WUZKZY9Ye1m7Q6d9V112w/tEP3eh7Whj/9s/7HX36nDX/6Z63y/ILtggEAQNTzeDwKhUJqbm6Ww+G47vlr/3i9XjkcDpWXlystLU2bNm0yMT0A3BgjFAr1vucpMAz8fr+cTqfq6+t7/M92NOns6tTe4w06fbFd05IztCwrv9cOku2HdujJrWW9bhtsyOizsAIAABBtNm3apPLycklSc3OzbDZbn+cGg0FlZ2crGAyqpKREHo9npGICQK+Gch9KJwlwjfi4eC2fvVRrbn1Ay2cv7XOKzfO1L/ZaIJGkkEJ6vvZFpt4AAICYk56e3u9xi8Wil156SZJUWVkZLq4AQDSgSAJTNDY2yu/3y+/3q62tzew4Q7b3eINOXjjV7zknL5zS3uMNI5QIAABg9CgqKgo/ZtoNADO0tbWF7zkbGxsHfR1FEpiiuLhYTqdTTqczKlswT19sj+h5AAAAscZisYQf+/1+84IAGJM8Hk/4nrO4uHjQ1yUMYyagT1VVVcrLy5MkWa1Wk9MM3bTkjIieBwAARq/BrleGntLT0xUMBs2OAWCMKi0t1Zo1ayT9OJNhsIUSiiQwRV5e3qhduHUwlmXla2bKjH6n3GSmWLUsK38EUwEAgEjbfmiHnq99scf/8zNTrHq64CkWaB9AIBAIP+5voVcAGA5Wq/WGvpBnug3Qix86L+vTU43qCnX1ejw+Ll6/K/i1DBm9Hjdk6OmCp/iWCQCAKNa9k921X4qcuNCmJ7eWafuhHSYlG/18Pl/4cUlJSY+pNwAwmlEkAXpx9Nxxvdu0S9UHtunst+d6PWd17ir9Ye0mzUyZ0eP5zBQr2/8CABDl2Mnu5nTvaONyuXqsP+fz+VRYWCjDMHr8KSws7NF50j3G1efY7XZVV1crGAzK7XbL6XT2OO50OuV2u8PX93dOMBgc8XF6s2nTpuvej7S0NLndblVXV193fjAYVGlpaXjswsJCFRYW9nruUETyvXA6nQoEAqqsrFRhYaHcbnc4a/e5veXt/rmufh8GM13L5/MpLS2tx+9SZWVlnz/nYN+/7p/VbrcrLS0t/DtdXV0dvq57vYvBLk482Ncfbb/j1/L7/SotLQ3n7/6M3W53j89ioM9j1AoBI6i
|
|
|
|
|
|
"text/plain": [
|
|
|
|
|
|
"<Figure size 1200x800 with 1 Axes>"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"df = pd.read_csv(\"VAH.csv\")\n",
|
|
|
|
|
|
"cols = df.columns\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"volt_h = df[cols[0]]\n",
|
|
|
|
|
|
"curr_h = df[cols[1]]*1e-7\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"x = 1e3 / volt_h\n",
|
|
|
|
|
|
"y = np.log(curr_h) - 2 * np.log(volt_h)\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"popt, pcov = curve_fit(line_func, x, y)\n",
|
|
|
|
|
|
"print(f\"{num}: k= {popt[0]:.2f}\\tb= {popt[1]:.2f}\")\n",
|
|
|
|
|
|
"opt_arr.append(popt)\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.plot(x, y, ls=\"\", marker=\".\", markersize=5, color=f\"C2\", label=\"Ручные измерения\")\n",
|
|
|
|
|
|
"plt.plot(x, line_func(x, *popt), lw=0.5, alpha=.5, color=f\"C2\")\n",
|
|
|
|
|
|
"\n",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"plt.xlabel(r\"$\\dfrac {10^3} U$, у.е.\")\n",
|
|
|
|
|
|
"plt.ylabel(r\"$\\log \\dfrac I {U^2}$, у.е.\")\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.legend()\n",
|
|
|
|
|
|
"plt.savefig(\"hand-NORDGAME-FAULER.png\")\n",
|
|
|
|
|
|
"plt.show()"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
|
"id": "a212083d-2d53-4522-860d-8eba58766461",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"### Все вместе"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"execution_count": 10,
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"id": "d668aa7a-0a40-475b-9876-698f4bc62c0a",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
|
|
|
"data": {
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"image/png": "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
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"text/plain": [
|
|
|
|
|
|
"<Figure size 1200x800 with 1 Axes>"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"for num, (ex_name, line) in enumerate(zip(experiment_names, ex_result)):\n",
|
|
|
|
|
|
" x = 1e3 / line[\"Voltage\"]\n",
|
|
|
|
|
|
" y = np.log(line[\"Current\"]) - 2 * np.log(line[\"Voltage\"])\n",
|
|
|
|
|
|
" \n",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
" plt.plot(x, y, ls=\"\", marker=\".\", markersize=4, color=f\"C{num}\", label=ex_name)\n",
|
|
|
|
|
|
" plt.plot(x, line_func(x, *(opt_arr[num])), lw=1, color=f\"C{num}\")\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"else:\n",
|
|
|
|
|
|
" x = 1e3 / volt_h\n",
|
|
|
|
|
|
" y = np.log(curr_h) - 2 * np.log(volt_h)\n",
|
|
|
|
|
|
"\n",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
" plt.plot(x, y, ls=\"\", marker=\".\", markersize=4, color=f\"C2\", label=\"Ручные измерения\")\n",
|
|
|
|
|
|
" plt.plot(x, line_func(x, *(opt_arr[-1])), lw=1, color=f\"C2\")\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
" \n",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"plt.xlabel(r\"$\\dfrac {10^3} U$, у.е.\")\n",
|
|
|
|
|
|
"plt.ylabel(r\"$\\log \\dfrac I {U^2}$, у.е.\")\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.legend()\n",
|
|
|
|
|
|
"plt.savefig(\"osc-NORDGAME-FAULER.png\")\n",
|
2023-09-15 23:46:38 +03:00
|
|
|
|
"plt.show()"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
2023-09-29 13:25:15 +03:00
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
|
"id": "31fee377-ff25-4382-8f41-228790745a73",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"Угол наклона полученной прямой получается по формуле\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"$\\tan \\alpha = -0.683 \\cdot \\dfrac {\\phi^\\frac 3 2} \\beta$\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"зная $\\phi = 4.5$ эВ -- работу выхода, находим $\\beta$ -- форм-фактор острия:"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
2023-09-15 23:46:38 +03:00
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"execution_count": 11,
|
2023-09-29 13:25:15 +03:00
|
|
|
|
"id": "21ac3719-9a57-4f80-9858-fc3c018fb1ad",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
|
|
|
"name": "stdout",
|
|
|
|
|
|
"output_type": "stream",
|
|
|
|
|
|
"text": [
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"beta:\t6.21e-01\n",
|
|
|
|
|
|
"beta:\t8.69e-01\n",
|
|
|
|
|
|
"beta:\t5.71e-01\n"
|
2023-09-29 13:25:15 +03:00
|
|
|
|
]
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"for opt in opt_arr:\n",
|
|
|
|
|
|
" tan_a = opt[0]\n",
|
|
|
|
|
|
" beta = -0.683 * (4.5**(3/2)) / tan_a\n",
|
2023-09-29 12:46:12 +03:00
|
|
|
|
" print(f\"beta:\\t{beta:.2e}\")"
|
2023-09-29 13:25:15 +03:00
|
|
|
|
]
|
|
|
|
|
|
},
|
2023-09-29 13:41:43 +03:00
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
|
"id": "d030c573-6440-4bcc-bab6-2887bd67624d",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"# тоже самое, но для каждого файла в отдельности"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": 12,
|
|
|
|
|
|
"id": "9e61c01d-77b7-4984-b906-68f55031aed4",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
|
|
|
"data": {
|
|
|
|
|
|
"text/plain": [
|
|
|
|
|
|
"['RISING-1.csv',\n",
|
|
|
|
|
|
" 'RISING-2.csv',\n",
|
|
|
|
|
|
" 'RISING-3.csv',\n",
|
|
|
|
|
|
" 'RISING-4.csv',\n",
|
|
|
|
|
|
" 'RISING-5.csv',\n",
|
|
|
|
|
|
" 'BOTH-1.csv',\n",
|
|
|
|
|
|
" 'BOTH-2.csv',\n",
|
|
|
|
|
|
" 'BOTH-3.csv']"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
"execution_count": 12,
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"file_names = [f\"RISING-{i}.csv\" for i in range(1, 6)] + [f\"BOTH-{i}.csv\" for i in range(1, 4)]\n",
|
|
|
|
|
|
"file_names"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": 13,
|
|
|
|
|
|
"id": "cef56c78-13e9-435f-b84e-9549f195e647",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"U_min = 900\n",
|
|
|
|
|
|
"R = 26.99e3 # Ом\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"column_names = [\"Voltage\", \"Current\"]\n",
|
|
|
|
|
|
"dots_result = []\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"for num, f_name in enumerate(file_names):\n",
|
|
|
|
|
|
" result = pd.DataFrame(columns=column_names)\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
" df = pd.read_csv(f_name, header = None)\n",
|
|
|
|
|
|
" df = df.loc[lambda x : x[4] > U_min]\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
" U = df[4] # В\n",
|
|
|
|
|
|
" U_cur = df[10]\n",
|
|
|
|
|
|
" I = U_cur / R # А\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
" result = pd.concat([result, pd.concat(dict(zip(column_names, [U, I])), axis=1)], ignore_index=True)\n",
|
|
|
|
|
|
" \n",
|
|
|
|
|
|
" result[\"Current\"] -= min(result[\"Current\"])\n",
|
|
|
|
|
|
" dots_result.append(result.groupby(\"Voltage\").mean().reset_index())"
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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": 14,
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|
"id": "ec61c33d-578b-45e4-9146-049724620a32",
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|
|
"metadata": {},
|
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|
|
|
|
"outputs": [
|
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|
|
{
|
|
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|
"name": "stdout",
|
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|
"output_type": "stream",
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"text": [
|
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|
|
|
|
"0: k= -15.31\tb= -11.32\n",
|
|
|
|
|
|
"1: k= -10.81\tb= -14.96\n",
|
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"2: k= -15.25\tb= -11.58\n",
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"3: k= -10.82\tb= -15.03\n",
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"4: k= -7.69\tb= -17.53\n",
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"5: k= -7.45\tb= -17.89\n",
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"6: k= -7.95\tb= -17.49\n",
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"7: k= -7.96\tb= -17.50\n"
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]
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},
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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": [
|
|
|
|
|
|
"<Figure size 1200x800 with 1 Axes>"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"opt_arr = []\n",
|
|
|
|
|
|
"for num, (f_name, line) in enumerate(zip(file_names, dots_result)):\n",
|
|
|
|
|
|
" x = 1e3 / line[\"Voltage\"]\n",
|
|
|
|
|
|
" y = np.log(line[\"Current\"]) - 2 * np.log(line[\"Voltage\"])\n",
|
|
|
|
|
|
" \n",
|
|
|
|
|
|
" popt, pcov = curve_fit(line_func, x, y)\n",
|
|
|
|
|
|
" print(f\"{num}: k= {popt[0]:.2f}\\tb= {popt[1]:.2f}\")\n",
|
|
|
|
|
|
" opt_arr.append(popt)\n",
|
|
|
|
|
|
" \n",
|
|
|
|
|
|
" plt.plot(x, y, ls=\"\", marker=\".\", markersize=5, color=f\"C{num}\", label=f_name)\n",
|
|
|
|
|
|
" plt.plot(x, line_func(x, *popt), lw=0.5, alpha=.5, color=f\"C{num}\")\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.xlabel(r\"$\\dfrac {10^3} U$, у.е.\")\n",
|
|
|
|
|
|
"plt.ylabel(r\"$\\log \\dfrac I {U^2}$, у.е.\")\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.legend()\n",
|
|
|
|
|
|
"plt.savefig(\"separ-NORDGAME-FAULER.png\")\n",
|
|
|
|
|
|
"plt.show()"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
2023-09-29 13:25:15 +03:00
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"execution_count": 26,
|
|
|
|
|
|
"id": "285e6509-6d8b-4235-8fc8-1134142e685d",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"opt_arr = np.array(opt_arr)\n",
|
|
|
|
|
|
"k_arr = opt_arr.T[0]\n",
|
|
|
|
|
|
"b_arr = opt_arr.T[1]"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
|
"id": "4b8623ef-91d3-455d-9093-8c2a60201356",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"### Первый случай (b от ln -k)"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": 34,
|
|
|
|
|
|
"id": "5af98fb6-4675-493e-aad6-19a8810a096a",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
|
|
|
"name": "stdout",
|
|
|
|
|
|
"output_type": "stream",
|
|
|
|
|
|
"text": [
|
|
|
|
|
|
"k= 8.97\tb= -36.05\n"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"data": {
|
|
|
|
|
|
"image/png": "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
|
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|
|
"text/plain": [
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|
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"<Figure size 1200x800 with 1 Axes>"
|
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|
]
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|
|
},
|
|
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|
"metadata": {},
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|
"output_type": "display_data"
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}
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|
],
|
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|
|
|
|
"source": [
|
|
|
|
|
|
"x = np.log(-k_arr)\n",
|
|
|
|
|
|
"y = b_arr\n",
|
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"\n",
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|
|
|
"popt, pcov = curve_fit(line_func, x, y)\n",
|
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|
|
"print(f\"k= {popt[0]:.2f}\\tb= {popt[1]:.2f}\")\n",
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"\n",
|
|
|
|
|
|
"plt.plot(x, y, ls=\"\", marker=\".\", markersize=5, color=f\"C0\", label=\"Коэффициенты прямой\")\n",
|
|
|
|
|
|
"plt.plot(x, line_func(x, *popt), lw=0.5, alpha=.5, color=f\"C0\")\n",
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"\n",
|
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|
|
|
"plt.xlabel(r\"$b$, у.е.\")\n",
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|
"plt.ylabel(r\"$\\log -k$, у.е.\")\n",
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"\n",
|
|
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|
|
"plt.legend()\n",
|
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|
|
"plt.savefig(\"separ-1-KOEF.png\")\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": "9591a07f-d002-4b3c-b329-cfc1823e5080",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"source": [
|
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|
|
"### Третий случай (b + 2 * log(-k) от exp(-b / 2))"
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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": 36,
|
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|
|
"id": "0202a50a-02d6-40dd-8d79-854d179273e4",
|
|
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|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
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|
|
"name": "stdout",
|
|
|
|
|
|
"output_type": "stream",
|
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|
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|
|
"text": [
|
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|
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|
|
"k= -0.00\tb= -6.90\n"
|
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|
]
|
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},
|
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{
|
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|
"data": {
|
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|
|
|
"image/png": "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
|
|
|
|
|
|
"text/plain": [
|
|
|
|
|
|
"<Figure size 1200x800 with 1 Axes>"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"source": [
|
|
|
|
|
|
"x = np.exp(-b_arr / 2)\n",
|
|
|
|
|
|
"y = b_arr + 2 * np.log(-k_arr)\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"popt, pcov = curve_fit(line_func, x, y)\n",
|
|
|
|
|
|
"print(f\"k= {popt[0]:.2f}\\tb= {popt[1]:.2f}\")\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.plot(x, y, ls=\"\", marker=\".\", markersize=5, color=f\"C0\", label=\"Коэффициенты прямой\")\n",
|
|
|
|
|
|
"plt.plot(x, line_func(x, *popt), lw=0.5, alpha=.5, color=f\"C0\")\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.xlabel(r\"$\\exp{-b / 2}$, у.е.\")\n",
|
|
|
|
|
|
"plt.ylabel(r\"$b + 2\\log{-k}$, у.е.\")\n",
|
|
|
|
|
|
"\n",
|
|
|
|
|
|
"plt.legend()\n",
|
|
|
|
|
|
"plt.savefig(\"separ-3-KOEF.png\")\n",
|
|
|
|
|
|
"plt.show()"
|
|
|
|
|
|
]
|
|
|
|
|
|
},
|
|
|
|
|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": 20,
|
2023-09-15 23:46:38 +03:00
|
|
|
|
"id": "8dfd4820-1065-4364-abe3-498825506a74",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [
|
|
|
|
|
|
{
|
|
|
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|
|
"data": {
|
2023-09-29 12:46:12 +03:00
|
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"image/png": "iVBORw0KGgoAAAANSUhEUgAABBgAAALWCAYAAADs0yCXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAB7CAAAewgFu0HU+AAEAAElEQVR4nOz9e3jc533feb9/pzkDGAxASiApiQfJEhTJsUDJthzHji3CTuKE2zZElLb8Y5snJuJ2/ex2W5NmepCUtpGppNvd9aYRKK+zz3XxShoBsbdynMQibceOHckiAcuWIko2CepEgiKBwRCY8+/0/DEABBAHzoAgQYKf13XBmpnf/Z3vbwD6j/s79/29jTAMQ0RERERERERELoO52jcgIiIiIiIiItc/FRhERERERERE5LKpwCAiIiIiIiIil00FBhERERERERG5bCowiIiIiIiIiMhlU4FBRERERERERC6bCgwiIiIiIiIictlUYBARERERERGRy6YCg4iIiIiIiIhcNhUYREREREREROSy2at9A1dCLpfj8ccfZ2hoCIBsNgvAjh072L9/P+l0etHY3t5estksDz/8MF1dXWzdunXmPYeHh/mzP/szBgYGOHz48My1hQwMDNDX1zfnte7ubvbu3XuZn05ERERERETk2mOEYRiu9k2spCNHjrBv3z7279/Prl27Zl4fGhrioYceIpfL0dfXx549exaM7+npYWBgYMkc/f39c977Yt3d3WSzWfr7++cUKD796U8zNDR0yeKEiIiIiIiIyPVmTRUYhoeH6enpYXBwcMHrR44cobu7G4DDhw+zY8eOeWOWKjDs2rWLAwcOLFkc6Onp4ciRI5w6dWrBlRLbt28nl8tx8uTJOj6RiIiIiIiIyPVhTW2R6OvrY2hoiO7ubg4fPjzv+uyCwoEDBxYsMEBthUI6nZ7ZYtHV1cX999+/5NYKqBUwBgYG2Lt376Jj9+/fT09PD/v27ePAgQP1fTARERERERGRa9yaWsHQ3d3NkSNHADh58uSCKw22bdvG8PAw6XSa8fHxedd7enrYv38/XV1dDeefXv2w2OqIaYZhLJpfRERERERE5Hq0pk6R6O3tJZ1Os2PHjkW3MUw3fLwSPRCmt1Zc6r3T6TS5XG6mGCIiIiIiIiJyvVtTBYZdu3YxPj6+4PYIqDVazOVyAEuuMFiO2cWCSxUYpq9Pb8EQERERERERud6tqQLDpTz99NNAbQXB/v37V/S9p4sFl+rTAJDJZAA4evToit6DiIiIiIiIyGpZU00el5LL5di3bx/wbhPHpQwPD8+Mz+VyZLNZduzYwf79+xeMHRsbW9Y9iYiIiIiIiKwFa77AkMvlOHbsGL29vWzdupWnnnrqkg0cH3/8cXK53LxCRE9PD9u3b+fw4cPztkE0UiyYfs/pfhCNGB0d5b/9t/9GIpEgGo0uOKa9vZ1169Y1/N4iIiIiIiJyYzp//jyjo6MLXqtUKhSLRX7jN36D9vb2Rd9jzRYYBgYG6OvrI5vNMjQ0RFdXFwcOHKj7dIiF+jj09/ezbds2tm3bxvj4+Jziw3KKBctZwfCNb3yDz372sw3HiYiIiIiIiFyO1tZW/uk//aeLXl+zBYZdu3axa9eumedDQ0P09PSQzWbp7+9ftMnjgQMHlmzSuGvXLp544gn27dtHX1/fzOvTfRWutM2bNwPwH/7Df2DLli0LjrnUCobjx4+ze/duDh06RGdn55W4TeVQjuvu/ZVDOfTvVjmU4+rlWAufQTluvBxr4TMoh3IslWOpFQynTp3i3/27fzczH13Mmi0wXKyrq4vBwUFaW1vp7u7mwIED7N27d964S50A0d3dzRNPPMHBgwc5cODAzCqGepo7roR4PA7AL//yL9e9GmMxnZ2dl/0eyqEcVzvHWvgMynHj5VgLn0E5lON6fH/lUI7r8f2VQzmuxRxDQ0P8u3/372bmo4u5oU6RSKfT7NmzB4B9+/Yt65jI2QWIY8eOzTxua2ur+z2mt0ZcraKEiIiIiIiIyJV2QxUYoLYCYdrsLQ71mr0VYnaBYrpYUE9fhel+DZdaLXE96+jo4JFHHqGjo0M5roEcV8OV/hxr5W+hv/eNlUN/b+W4Xq2F/2+slRxXw1r5Xa2Ff7dXw1r4W6ylHFfDVf0c4RoxODgYbt26Nezq6gpPnjy56LjDhw+HQAiEXV1dM6+Pj4+HXV1d4datW5eMHx8fn4nfs2fPgu87Pj6+5L1u3bo1BMK9e/fW/wGnDA4OhkA4ODjYcOxKvodcX/Q3v7Ho731j0d/7xqO/+Y1Ff+8bi/7eN57r5W9e732umRUMfX19DA8PMzQ0tKyVCUeOHGFoaIjh4WEGBgYWHTf7tIht27bNPL7//vsXHLOQ4eFhYO5qChEREREREZHr2ZopMMzuZ/DAAw8sOm56cg/MOUliutlFV1fXnNMn6o1Pp9Mz7zF7zMVm919Y7CQLERERERERkevNmikwPPzww6TTaU6ePLlkgaC/v3/mcW9v78zjrVu3zpw0sVRvhMOHDwO14yov7sC5f//+eTku9vTTTwPMNJtcDWtlL5HUT3/zG4v+3jcW/b1vPPqb31j0976x6O9941lrf3MjDMNwtW9ipezbt49cLrfoFokjR47MbEvo7++fV4g4cuQI/f39i8YPDQ2xfft20uk0p06dWvAUiJ6eHgYGBjh58uSChYpt27aRzWYZHx9v8NPNvYfBwcErfoyJiIiIiIiISL3z0DWzggHgwIEDpNNptm/fzsDAwJwTHQYGBujp6SGdTtPX17fgKocdO3awbds2uru7OXLkyMzruVyOgwcPsn37dnbs2MHg4OCiR0w+9dRT7Nixg+7u7jlbJXK53ExxY3BwcGU+sIiIiIiIiMg1Yk2tYJg2PDzMgQMHOHbsGLlcjmw2SyaTYdeuXezfv3/R4sBC8cPDw2QyGbq6unj44YeX3H4x28DAAH19fXOOr+zu7mbv3r2X9dm0gkFERERERESupnrnoWuywLCWqcAgIiIiIiIiV9MNuUVCRERERERERFaHCgwiIiIiIiIictlUYBARERERERGRy2av9g3I8hw/fnzmcUdHx5o5N1VERERERERW38jICCMjI8Dc+edSVGC4Tu3evXvm8SOPPMKjjz66ejcjIiIiIiIia0pfXx+PPfZYQzEqMFynDh06RGdnJ4BWL4iIiIiIiMiK6u3tZefOnUBtBcPsL7kXowLDdaqzs1PHVIqIiIiIiMgVsZyt+GryKCIiIiIiIiKXTSsYRERERERERGa5kK9yNjtJxfeJWhY3Z5poSUWuuxxXmwoMIiIiIiIiIsBINs9Lp0Y5N14EwA98LNMC3mF9a4J7t7TTkUld8zlWiwoMIiIiIiIicsMbHsnx3CtnyJerjOZK5EoVCAAT0vEohUqV87kiD969ga0d6Ws2x2pSgUFERERERERuaCPZPM+9cobzuSKns3ks06Q9FScasahUfcYLFXJnKmzMpHjulTPEo3bDqwyuRo7VpgKDiIiIiIiI3NBeOjVKvlzldDZPcyLCreuaprYt1NycSfDm+UlOZ/PEYzYvnRptePJ/NXKsNp0iISIiIiIiIjesC/kq58aLjOZKWKY5b+IPYJnW1Osmo7kS58aLXMhXr6kc1wIVGEREREREROSGdTY7CUCuVKE1GZ038Z9mmRatyWitb8KsuGslx7VABQYRERERERG5YVV8Hz/wIYBoZOGJ/7RoxIKgdvJDxfevqRzXAhUYRERERERE5IYVtazaigITKtWlJ/SVqg9mbaVB1Fq6UHC1c1wLVGAQERERERGRG9bNmSagdkzkeKFSW2mwAD+onfSQjkfnxF0rOa4FKjCIiIiIiIjIDaslFWF9a4L2dBw/CHjz/OS8AoAf+FOvB7Sn46xvTdCSilxTOa4FOqbyOnX8+PGZxx0dHXR0dKzi3YiIiIiIiFy/7t3SzvlckY2ZFKezeY6/NU5rMko0YlGp+lOrDgI2ZlKkYhHu3dJ+TeZYSSMjI4yMjABz559LUYHhOrV79+6Zx4888giPPvro6t2MiIiIiIjIVVItVylOFAj8ANM
|
2023-09-15 23:46:38 +03:00
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"text/plain": [
|
2023-09-29 13:25:15 +03:00
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"<Figure size 1200x800 with 1 Axes>"
|
2023-09-15 23:46:38 +03:00
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
|
2023-09-29 13:25:15 +03:00
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"idx = 900\n",
|
2023-09-15 23:46:38 +03:00
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"U_min = 800\n",
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"\n",
|
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|
|
"for i in range(1, 4):\n",
|
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|
|
" df = pd.read_csv(f\"BOTH-{i}.csv\", header = None)\n",
|
2023-09-29 13:25:15 +03:00
|
|
|
|
" data = [None, None]\n",
|
2023-09-15 23:46:38 +03:00
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|
|
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" df = df.loc[lambda x : x[4] > U_min]\n",
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" \n",
|
2023-09-29 13:25:15 +03:00
|
|
|
|
" data[0] = df.loc[lambda x : x.index < idx]\n",
|
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|
|
" data[1] = df.loc[lambda x : x.index >= idx]\n",
|
2023-09-15 23:46:38 +03:00
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" \n",
|
2023-09-29 13:25:15 +03:00
|
|
|
|
" for (i, d) in enumerate(data):\n",
|
|
|
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|
|
" U = d[4] * 1e-3 # кВ\n",
|
|
|
|
|
|
" U_res = d[10]\n",
|
|
|
|
|
|
" R = 26.99e3 # Ом\n",
|
|
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|
|
" I = U_res / R * 1e6 # мкА\n",
|
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"\n",
|
|
|
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|
|
" plt.plot(U, I, lw=5, alpha=0.2, ls=\"\", marker=\"o\", markersize=4, color=f\"C{i}\")\n",
|
2023-09-15 23:46:38 +03:00
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" \n",
|
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" \n",
|
|
|
|
|
|
"plt.xlabel(fr\"Напряжение, кВ\")\n",
|
|
|
|
|
|
"plt.ylabel(fr\"Сила тока, мкА\")\n",
|
|
|
|
|
|
"# plt.yscale(\"log\")\n",
|
|
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|
|
"\n",
|
2023-09-29 13:41:43 +03:00
|
|
|
|
"plt.savefig(\"all-VAH-BOTH.png\")\n",
|
2023-09-15 23:46:38 +03:00
|
|
|
|
"plt.show()"
|
|
|
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|
|
]
|
2023-09-29 13:41:43 +03:00
|
|
|
|
},
|
|
|
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|
|
{
|
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
|
"id": "8418865a-0381-4a73-986c-b13d75f23d64",
|
|
|
|
|
|
"metadata": {},
|
|
|
|
|
|
"outputs": [],
|
|
|
|
|
|
"source": []
|
2023-09-15 23:46:38 +03:00
|
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|
|
}
|
|
|
|
|
|
],
|
|
|
|
|
|
"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": "3.10.12"
|
|
|
|
|
|
}
|
|
|
|
|
|
},
|
|
|
|
|
|
"nbformat": 4,
|
|
|
|
|
|
"nbformat_minor": 5
|
|
|
|
|
|
}
|
