{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "afraid-minutes",
"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\n",
"import re\n",
"import sys\n",
"import torch\n",
"import pprint\n",
"import numpy as np\n",
"import pandas as pd\n",
"from pathlib import Path\n",
"from scipy.interpolate import make_interp_spline\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",
"from utils.qlib_utils import QResult"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "continental-drain",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"TSF-2x24-drop0_0s2013-01-01\n",
"TSF-2x24-drop0_0s2012-01-01\n",
"TSF-2x24-drop0_0s2008-01-01\n",
"TSF-2x24-drop0_0s2009-01-01\n",
"TSF-2x24-drop0_0s2010-01-01\n",
"TSF-2x24-drop0_0s2011-01-01\n",
"TSF-2x24-drop0_0s2008-07-01\n",
"TSF-2x24-drop0_0s2009-07-01\n",
"There are 3011 dates\n",
"Dates: 2008-01-02 2008-01-03\n"
]
}
],
"source": [
"qresults = torch.load(os.path.join(root_dir, 'notebooks', 'TOT', 'temp-time-x.pth'))\n",
"for qresult in qresults:\n",
" print(qresult.name)\n",
"all_dates = set()\n",
"for qresult in qresults:\n",
" dates = qresult.find_all_dates()\n",
" for date in dates:\n",
" all_dates.add(date)\n",
"all_dates = sorted(list(all_dates))\n",
"print('There are {:} dates'.format(len(all_dates)))\n",
"print('Dates: {:} {:}'.format(all_dates[0], all_dates[1]))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "intimate-approval",
"metadata": {},
"outputs": [],
"source": [
"import matplotlib\n",
"from matplotlib import cm\n",
"matplotlib.use(\"agg\")\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.ticker as ticker"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "supreme-basis",
"metadata": {},
"outputs": [],
"source": [
"def vis_time_curve(qresults, dates, use_original, save_path):\n",
" save_dir = (save_path / '..').resolve()\n",
" save_dir.mkdir(parents=True, exist_ok=True)\n",
" print('There are {:} qlib-results'.format(len(qresults)))\n",
" \n",
" dpi, width, height = 200, 5000, 2000\n",
" figsize = width / float(dpi), height / float(dpi)\n",
" LabelSize, LegendFontsize = 22, 12\n",
" font_gap = 5\n",
" linestyles = ['-', '--']\n",
" colors = ['k', 'r']\n",
" \n",
" fig = plt.figure(figsize=figsize)\n",
" cur_ax = fig.add_subplot(1, 1, 1)\n",
" for idx, qresult in enumerate(qresults):\n",
" print('Visualize [{:}] -- {:}'.format(idx, qresult.name))\n",
" x_axis, y_axis = [], []\n",
" for idate, date in enumerate(dates):\n",
" if date in qresult._date2ICs[-1]:\n",
" mean, std = qresult.get_IC_by_date(date, 100)\n",
" if not np.isnan(mean):\n",
" x_axis.append(idate)\n",
" y_axis.append(mean)\n",
" x_axis, y_axis = np.array(x_axis), np.array(y_axis)\n",
" if use_original:\n",
" cur_ax.plot(x_axis, y_axis, linewidth=1, color=colors[idx], linestyle=linestyles[idx])\n",
" else:\n",
" xnew = np.linspace(x_axis.min(), x_axis.max(), 200)\n",
" spl = make_interp_spline(x_axis, y_axis, k=5)\n",
" ynew = spl(xnew)\n",
" cur_ax.plot(xnew, ynew, linewidth=2, color=colors[idx], linestyle=linestyles[idx])\n",
" \n",
" for tick in cur_ax.xaxis.get_major_ticks():\n",
" tick.label.set_fontsize(LabelSize - font_gap)\n",
" for tick in cur_ax.yaxis.get_major_ticks():\n",
" tick.label.set_fontsize(LabelSize - font_gap)\n",
" cur_ax.set_ylabel(\"IC (%)\", fontsize=LabelSize)\n",
" fig.savefig(save_path, dpi=dpi, bbox_inches=\"tight\", format=\"pdf\")\n",
" plt.close(\"all\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "shared-envelope",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The Desktop is at: /Users/xuanyidong/Desktop\n",
"There are 2 qlib-results\n",
"Visualize [0] -- TSF-2x24-drop0_0s2008-01-01\n",
"Visualize [1] -- TSF-2x24-drop0_0s2009-07-01\n",
"There are 2 qlib-results\n",
"Visualize [0] -- TSF-2x24-drop0_0s2008-01-01\n",
"Visualize [1] -- TSF-2x24-drop0_0s2009-07-01\n"
]
}
],
"source": [
"# Visualization\n",
"home_dir = Path.home()\n",
"desktop_dir = home_dir / 'Desktop'\n",
"print('The Desktop is at: {:}'.format(desktop_dir))\n",
"\n",
"vis_time_curve(\n",
" (qresults[2], qresults[-1]),\n",
" all_dates,\n",
" True,\n",
" desktop_dir / 'es_csi300_time_curve.pdf')\n",
"\n",
"vis_time_curve(\n",
" (qresults[2], qresults[-1]),\n",
" all_dates,\n",
" False,\n",
" desktop_dir / 'es_csi300_time_curve-inter.pdf')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "exempt-stable",
"metadata": {},
"outputs": [],
"source": []
}
],
"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"
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"nbformat": 4,
"nbformat_minor": 5
}