113 lines
54 KiB
Plaintext
113 lines
54 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": "filled-multiple",
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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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"The root path: /Users/xuanyidong/Desktop/AutoDL-Projects\n",
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"The library path: /Users/xuanyidong/Desktop/AutoDL-Projects/lib\n"
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]
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}
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],
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"source": [
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"import os, sys\n",
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"import torch\n",
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"from pathlib import Path\n",
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"import numpy as np\n",
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"import matplotlib\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"\n",
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"__file__ = os.path.dirname(os.path.realpath(\"__file__\"))\n",
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"root_dir = (Path(__file__).parent / \"..\").resolve()\n",
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"lib_dir = (root_dir / \"lib\").resolve()\n",
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"print(\"The root path: {:}\".format(root_dir))\n",
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"print(\"The library path: {:}\".format(lib_dir))\n",
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"assert lib_dir.exists(), \"{:} does not exist\".format(lib_dir)\n",
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"if str(lib_dir) not in sys.path:\n",
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" sys.path.insert(0, str(lib_dir))\n",
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"\n",
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"from datasets import SinGenerator"
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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": "consistent-transition",
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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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"SinGenerator(100/100 elements,\n",
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"amplitude=QuadraticFunc(y = -12.000019073486328 * x^2 + 11.999970436096191 * x + 0.9999865293502808),\n",
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"period_phase_shift=QuarticFunc(y = 7.079958915710449 * x^4 + -13.879528999328613 * x^3 + -17.825382232666016 * x^2 + 53.32909393310547 * x + 53.32909393310547))\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": [
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"<Figure size 1440x576 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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"def visualize_q_func():\n",
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"\n",
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" dpi, width, height = 10, 200, 80\n",
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" figsize = width / float(dpi), height / float(dpi)\n",
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" LabelSize, LegendFontsize, font_gap = 40, 40, 5\n",
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" \n",
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" fig = plt.figure(figsize=figsize)\n",
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" \n",
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" dataset = SinGenerator()\n",
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" print(dataset)\n",
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" xaxis, yaxis = [], []\n",
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" for idx, position, value in dataset:\n",
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" xaxis.append(position)\n",
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" # yaxis.append(dataset._amplitude_scale[position])\n",
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" yaxis.append(value)\n",
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"\n",
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" cur_ax = fig.add_subplot(1, 1, 1)\n",
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" cur_ax.plot(xaxis, yaxis, color=\"k\", linestyle=\"-\", alpha=0.6, label=None)\n",
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"\n",
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"visualize_q_func()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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