mirror of
https://github.com/galera951/experiment-automation.git
synced 2024-11-09 15:45:52 +03:00
244 lines
85 KiB
Plaintext
244 lines
85 KiB
Plaintext
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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": 1,
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"id": "aa41c92f-b4cc-46aa-933e-1d2ff85f409e",
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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\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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"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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" 'figure.dpi': 150.0,\n",
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" 'font.size': 12.0,\n",
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"})\n",
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"\n",
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"line = lambda x, k, b: k*x + b\n",
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"deltaPercent = lambda a, b: (1 - min(a, b) / max(a, b)) * 100"
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]
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},
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{
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"cell_type": "markdown",
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"id": "22d07d19-02ec-468b-aa0f-0738cb65931a",
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"metadata": {},
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"source": [
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"## 2 АЧХ ОУ"
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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": "48d80fc6-9c30-4ec2-ac70-ef9bfde85924",
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Крутизна = \t-19.55 дБ/декаду\n",
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"fp0 = \t\t 13.25 Гц\n",
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"fT = \t\t 1.20e+06 Гц\n"
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]
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}
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],
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"source": [
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"data = np.loadtxt(\"data2.txt\", skiprows=1, delimiter=\",\").T\n",
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"f = data[0]\n",
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"Uout = data[1]\n",
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"Ua = data[2]\n",
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"\n",
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"A = 101 * Uout / Ua\n",
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"Adb = 20 * np.log10(A)\n",
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"\n",
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"popt, _ = curve_fit(line, np.log10(f), Adb)\n",
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"print(f\"Крутизна = \\t{popt[0]:.2f} дБ/декаду\")\n",
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"\n",
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"fp0 = 10 ** ((Adb[0] - 3 - popt[1]) / popt[0])\n",
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"print(f\"fp0 = \\t\\t {fp0:.2f} Гц\")\n",
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"\n",
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"fT = 10 ** ((1 - popt[1]) / popt[0])\n",
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"print(f\"fT = \\t\\t {fT:.2e} Гц\")"
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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": 3,
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"id": "1348218c-f9c0-4fc6-97a9-19c8a0a18c44",
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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": "iVBORw0KGgoAAAANSUhEUgAAAxIAAAIYCAYAAAD5KNoZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAABcSAAAXEgFnn9JSAAB3JklEQVR4nO3de3yT9d3/8XeSJlAjNhQFnUdSnGzOKQ2g2xAFWt3m5jZt4b5v3bzZpNWdd9/YiI6JyyamupP35mw9TDfdBq24k1NpQVHmlNKITh0eeoFnQWlToBSaJvn9wS+R0jZNQtKrSV/Px6OPmev6fq98AtfK9cn38LFEo9GoAAAAACAFVrMDAAAAAJB7SCQAAAAApIxEAgAAAEDKSCQAAAAApIxEAgAAAEDKCswOIB9EIhHt3btXBQUFslgsZocDAAAAHLJoNKre3l6NHTtWVmv/8QcSiQzYu3evnE6n2WEAAAAAGdfV1aXDDjus33ESiQwoKNj/x9jV1SW73S5JCoVCcjqdfY4NJJl2idok+z65wqzPk633PdTrpts/lX7Dda8eyucZicz8LNl470xcM51rpNonU/fraLpXpfz63WrWvZpqP363pief7tVMXHc47tVE7WPHY8+6ByORyICDpzNZrdb4X4Ldbk/qLzCZdonaJPs+ucKsz5Ot9z3U66bbP5V+w3WvphrXSGfmZ8nGe2fimulcI9U+mbpfR9O9KuXX71az7tVU+/G7NT35dK9m4rrDca8e2D4cDisSicSPDzZ1n8XWGeR0OuVwOOTz+WS1WnXdddcNOJ/sQMm0S/Za+cCsz5qt9z3U66bbP5V+3KvpMfOzZuO9M3HNdK6Rap9M3a+j6V6V8ut3q1n3aqr9+N2anny6VzNx3eG4Vwdq7/P55HA4hpy6b4lGo9GUIkM/oVBIDocjPhxktVpls9mG9b17enry5lsI5C/uV+QK7lXkEu5XZFpsRCI2tWmwe4upTRmUT0OKAAAAGJ1sNltSX4rn/xhZnhtNw53IfdyvyBXcq8gl3K8wC1ObMoAhRQAAAOSboZ5xSV0BAAAApIxEAgAAAEDKSCQAAAAApIxEAgAAAEDKSCQAAAAApIxEAgAAAEDKKEiXQaFQSJKGpbL19s5u3bOuTes3b9eu7pDGFdo1a+okXXaOWxOLCrP63gAAAMhfB1a2ToQ6EhkQ22M35rrrrtOyZcuy8l7dPb2qubdV9z2xRaFwpN95u82qS2e7VXuJR2Md2U1mAAAAkH+WLVum66+/Pv56sDoSJBIZEEskurq6ZLfbszYi0d3Tq4tufkzrN28fsu2sqRO1avG5KnQw6AQAAIDkHTgi4XQ6KUg3HOx2u+x2e9amNdXc25pUEiFJ6zdvl/e+QFbiAAAAQP6y2Wzx59pEcmJEorm5WV6vVw0NDXK73YO2MwxDfr9fLpcr/nrJkiUqLS3NSPvBDFU+PBO2Bbv1ke/9ecDpTIOx26za/PMvsGYCAAAAKRvqGXfEznvxer0KBAJyu90yDEOBQOJv1wOBgCorK9XU1BRPNoLBoDwej/x+vyoqKg6pvdl++3hbSkmEJIXCEd2zztBVF56apagAAAAwWo3YqU1+v19NTU2qq6tLaoSgsrJS1dXVfUYsXC6X/H6/Fi1apGAweEjtzZbslKb+/bZlOBIAAABgBCcSqWhubpZhGCorK+t3rqKiQsFgUPX19Wm3Hwl2dSfefivT/QAAAIBE8iKRaGpqkqRB10+4XC6tWLEi7fYjwbjC9NZepNsPAAAASCQvEonm5mZJii+aPpjb7e6zxiLV9iPBrKkT0+w3KcORAAAAAHmSSBiGMWhSkIn2I8FXZpfIbkvtr8tus+qycwbf5QoAAABIV14kEskujI61S7V9skKhUL+fcDic0jUGM8lVqEvOnpxSn0tnu9n6FQAAAEMKh8MDPssmkheJRLLa29uz2t7pdMrhcPT58fl8KV0jkdpLPUlPcTrxSKd+vGBaxt4bAAAA+cvn8/V7jnU6nQn75EUikeo0pWxNa+rq6lJPT0+fn6VLl2bs+oWOAq1afK4Wzpky6DQny///39fe79Knb2iWsW1Xxt4fAAAA+Wnp0qX9nmO7uroS9hmxBelSUVxcnNToQXFxcVrtk5VMKfFDVego0C0LZ+r7F52me9YZWr95m3Z1hzSu0K5ZUyfpK7Mna92L27X4dxv1/q69mjBuTFbjAQAAQO6z2Wyy2Wwp9cmLRMLlcskwjEHPx9Y6xEYiUm0/Ek0sKtRVF546YNXq+Z88SeeeOklv7NijosMckqRoNKrNb3XqI8e5hjlSAAAA5KO8mNo0ffp0SYMvjjYMo0917FTb56KJRYXyuCfEX9/7hKGzrn1I1/7hGXX39JoYGQAAAPJBXiQS1dXVkjTgKEMsWViwYEHa7fPBM1vaFYlGdctD/9Ynrn1I/3hpu9khAQAAIIflRSJRWloqt9s9YDXqlStXyuVyqaqqKu32+eCnl83Qiu/N1jHjC9W2bZc+c0OzrvrdRu3em3hbLwAAAGAgOZFIxEYOEtV1aGhoUH19fZ9RhmAwKL/frzVr1vRb75Bq+3zw2WnHacMNF+gr55QoGpVua3pZZ13zdz3J6AQAAABSZIlGo1GzgxhIfX29Ghoa1N7erkAgIGn/4ufY+oa6ujq53X2rNhuGIa/XK7fbrQkTJqilpUXV1dUqKysb8D1SbT+YUCgkh8Ohnp6erO/alClrn39H37prg97Y0aXV3y/XWScfZXZIAAAAGEGGesYdsYlELsnFREKSdnWHtPb5d/SFGSfEj73+fpdOODJx8REAAADkv6GecXNiahOyY1yhvU8S8co7O+Xx/k1Vdf9U++59JkYGAACAkY5EIoNCoZBCoZDC4bDZoaTliX9v077esP7wjy2aseRB/WXjG2aHBAAAgGEWDofjz7WJkEhkkNPplMPhkM/nMzuUtHx17slqXnqeTvnQEdreuVeX3PKELvvler23c6/ZoQEAAGCY+Hw+ORwOOZ2Jp7uzRiIDYvPHurq6ZLfbZbVaUy4xPpLs7QnL/+fn9bMHX1Q4ElXx4WP0069M18VnnWh2aAAAAMiycDisSCSiUCgkp9PJGonhYLfbZbfbczqJkKSxDpuuqzxdjy07Xx873qX23fvUtm2X2WEBAABgGNhstvhzbSKMSGRAru7alIye3rDueaxN/33uFNkL9ued7+/aqwmHj5HFYjE5OgAAAGQL278Og3xOJA7W0xvW7Ose0TGuQt2ycKaOZ6tYAACAvMT2r8ioVqNdr767U83/ekczr3lQd659RZEIuSgAAMBow4hEBoymEQlJevmdnfrGHU/rqVfekyTN/sgk/d9XZ8o9aZzJkQEAACBTmNo0DEZbIiFJ4UhE9c2vaNnKTdrTE1ahw6brKk7XleedIquVtRMAAAC5jqlNyAqb1aorzztFT91wgWZ/ZJK6e8L6W+BNs8MCAADAMGFEIgNG44jEgSKRqO5+7FWdc+rRKvn/05u6e3plt1lVYCNXBQAAyEVMbRoG+VaQLhOu+t1GPf3K+/r1orN06vEus8MBAABAkihIZwKn0ymHwyGfz2d2KKZq371PK57cqme2tuvsHzys5Q/8Sz29YbPDAgAAQBJ8Pp8cDoeczsTb/DMikQGMSPT3brBb3727RQ/+/3UTHzvepVsvP0vTJhebHBkAAAASSXZEgkQiA0b7GonBRKNRrXr6df3v7zZqx659slkt+u4FH9HVXzhNYx2jO9ECAAAY6di1CaaxWCy6+KwT1bL8AlWcdaLCkajuWvuqgnt6zA4NAAAAh4gRiQxgRCI5f219Q73hqL4084T4sZ7esBwFjE4AAACMNIxIYMT4vOf4PknEg4E3NePqB/XEv7eZGBUAAADSQSIBU0SjUd381xdkbN+tzy5fo+/d3aJd3SGzwwIAAECSSCRgCovFoj/XzNVX50yRJN2x9hWdec2DWvOvd0yODAAAAMlgjUQGsEbi0Dz2wrv61l1Pa+t7XZKkL89264b/LJXL6TA5MgAAgNGLNRIY8c499Wj988ef1ZXnfVgWi/S7xw09/ep7ZocFAACABBi
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"text/plain": [
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"<Figure size 900x600 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": [
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"plt.plot(f, Adb, \"o\")\n",
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"plt.plot(f, line(np.log10(f), *popt), \"--\", color=\"C0\")\n",
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"plt.xscale(\"log\")\n",
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"\n",
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"plt.xlabel(\"Frequency, Hz\")\n",
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"plt.ylabel(\"Gain factor, dB\")\n",
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"\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": "570b3241-2223-4e98-956b-5b75b608fdd7",
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"metadata": {},
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"source": [
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"## 3 Неинвертирующий усилитель"
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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": 11,
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"id": "949340bc-88c9-48c0-8c91-3dce05307861",
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Входное напряжение сдвига Uos \t1.49e-04 В\n"
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]
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}
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],
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"source": [
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"R1 = 1e3 # Ohm\n",
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"R2 = 1e5 # Ohm\n",
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"\n",
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"Uout_dc = 0.015 # V\n",
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"Uos = Uout_dc / (1 + R2 / R1)\n",
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"print(f\"Входное напряжение сдвига Uos \\t{Uos:.2e} В\")"
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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": 5,
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"id": "247fe705-0dc7-4bf4-ac2a-154d3db03f1b",
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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": [
|
|||
|
|
"<Figure size 900x600 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"data = np.loadtxt(\"data3.txt\", skiprows=1, delimiter=\",\").T\n",
|
|||
|
|
"f = data[0]\n",
|
|||
|
|
"Uin = data[1]\n",
|
|||
|
|
"Uout = data[2]\n",
|
|||
|
|
"\n",
|
|||
|
|
"A = Uout / Uin\n",
|
|||
|
|
"Adb = 20 * np.log10(A)\n",
|
|||
|
|
"\n",
|
|||
|
|
"plt.plot(f, Adb, \"--o\")\n",
|
|||
|
|
"plt.xscale(\"log\")\n",
|
|||
|
|
"\n",
|
|||
|
|
"plt.xlabel(\"Frequency, Hz\")\n",
|
|||
|
|
"plt.ylabel(\"Gain factor, dB\")\n",
|
|||
|
|
"\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 6,
|
|||
|
|
"id": "57a10d24-1c60-4f58-add1-009eafa97da2",
|
|||
|
|
"metadata": {
|
|||
|
|
"tags": []
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"Граничная частота Fp \t\t\t1.46e+04 Гц\n",
|
|||
|
|
"Расхождение между A(f_низк) и K0 \t1.64 %\n",
|
|||
|
|
"Расхождение между beta*fT и Fp \t\t18.47 %\n"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"Fp = None\n",
|
|||
|
|
"for i in range(len(f) - 1):\n",
|
|||
|
|
" if ((Adb[0] - 3) < Adb[i]) and ((Adb[0] - 3) >= Adb[i+1]):\n",
|
|||
|
|
" k = (Adb[i] - Adb[i+1]) / (f[i] - f[i+1])\n",
|
|||
|
|
" b = Adb[i] - k*f[i]\n",
|
|||
|
|
" Fp = ((Adb[0] - 3) - b) / k\n",
|
|||
|
|
" break\n",
|
|||
|
|
"print(f\"Граничная частота Fp \\t\\t\\t{Fp:.2e} Гц\")\n",
|
|||
|
|
" \n",
|
|||
|
|
"beta = R1 / (R1 + R2)\n",
|
|||
|
|
"K0 = 1 / beta\n",
|
|||
|
|
"print(f\"Расхождение между A(f_низк) и K0 \\t{deltaPercent(A[0], K0):.2f} %\")\n",
|
|||
|
|
"print(f\"Расхождение между beta*fT и Fp \\t\\t{deltaPercent(Fp, beta*fT):.2f} %\")"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"id": "2a97fea6-18cf-442a-949e-4871688d3c0e",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": []
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"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
|
|||
|
|
}
|