autodl-projects/notebooks/TOT/Time-Curve.ipynb

{
 "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": []
  }
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