autodl-projects/notebooks/TOT/synthetic-data.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "filled-multiple",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The root path: /Users/xuanyidong/Desktop/AutoDL-Projects\n",
"The library path: /Users/xuanyidong/Desktop/AutoDL-Projects/lib\n"
]
}
],
"source": [
"import os, sys\n",
"import torch\n",
"from pathlib import Path\n",
"import numpy as np\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"\n",
"\n",
"__file__ = os.path.dirname(os.path.realpath(\"__file__\"))\n",
"root_dir = (Path(__file__).parent / \"..\").resolve()\n",
"lib_dir = (root_dir / \"lib\").resolve()\n",
"print(\"The root path: {:}\".format(root_dir))\n",
"print(\"The library path: {:}\".format(lib_dir))\n",
"assert lib_dir.exists(), \"{:} does not exist\".format(lib_dir)\n",
"if str(lib_dir) not in sys.path:\n",
" sys.path.insert(0, str(lib_dir))\n",
"\n",
"from datasets import SinGenerator"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "consistent-transition",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SinGenerator(100/100 elements,\n",
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"amplitude=QuadraticFunc(y = -12.000055313110352 * x^2 + 11.999917984008789 * x + 0.9999290108680725),\n",
"period_phase_shift=QuarticFunc(y = 7.24642276763916 * x^4 + -14.495288848876953 * x^3 + -17.114450454711914 * x^2 + 53.0693473815918 * x + 53.0693473815918))\n"
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]
},
{
"data": {
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"image/png": "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"text/plain": [
"<Figure size 1440x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def visualize_q_func():\n",
"\n",
" dpi, width, height = 10, 200, 80\n",
" figsize = width / float(dpi), height / float(dpi)\n",
" LabelSize, LegendFontsize, font_gap = 40, 40, 5\n",
" \n",
" fig = plt.figure(figsize=figsize)\n",
" \n",
" dataset = SinGenerator()\n",
" print(dataset)\n",
" xaxis, yaxis = [], []\n",
" for idx, position, value in dataset:\n",
" xaxis.append(position)\n",
" # yaxis.append(dataset._amplitude_scale[position])\n",
" yaxis.append(value)\n",
"\n",
" cur_ax = fig.add_subplot(1, 1, 1)\n",
" cur_ax.plot(xaxis, yaxis, color=\"k\", linestyle=\"-\", alpha=0.6, label=None)\n",
"\n",
"visualize_q_func()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}