Make nice visualization

notebooks/TOT/synthetic-visualize-env.ipynb

@@ -0,0 +1,152 @@
+{
+ "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",
+    "from matplotlib import cm\n",
+    "matplotlib.use(\"agg\")\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.ticker as ticker\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 ConstantGenerator, SinGenerator, SyntheticDEnv\n",
+    "from datasets import DynamicQuadraticFunc\n",
+    "from datasets.synthetic_example import create_example_v1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "detected-second",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def draw_fig(save_dir, timestamp, xaxis, yaxis):\n",
+    "    save_path = save_dir / '{:04d}'.format(timestamp)\n",
+    "    # print('Plot the figure at timestamp-{:} into {:}'.format(timestamp, save_path))\n",
+    "    dpi, width, height = 40, 1500, 1500\n",
+    "    figsize = width / float(dpi), height / float(dpi)\n",
+    "    LabelSize, LegendFontsize, font_gap = 80, 80, 5\n",
+    "\n",
+    "    fig = plt.figure(figsize=figsize)\n",
+    "    \n",
+    "    cur_ax = fig.add_subplot(1, 1, 1)\n",
+    "    cur_ax.scatter(xaxis, yaxis, color=\"k\", s=10, alpha=0.9, label=\"Timestamp={:02d}\".format(timestamp))\n",
+    "    cur_ax.set_xlabel(\"X\", fontsize=LabelSize)\n",
+    "    cur_ax.set_ylabel(\"f(X)\", rotation=0, fontsize=LabelSize)\n",
+    "    cur_ax.set_xlim(-6, 6)\n",
+    "    cur_ax.set_ylim(-40, 40)\n",
+    "    for tick in cur_ax.xaxis.get_major_ticks():\n",
+    "        tick.label.set_fontsize(LabelSize - font_gap)\n",
+    "        tick.label.set_rotation(10)\n",
+    "    for tick in cur_ax.yaxis.get_major_ticks():\n",
+    "        tick.label.set_fontsize(LabelSize - font_gap)\n",
+    "        \n",
+    "    plt.legend(loc=1, fontsize=LegendFontsize)\n",
+    "    fig.savefig(str(save_path) + '.pdf', dpi=dpi, bbox_inches=\"tight\", format=\"pdf\")\n",
+    "    fig.savefig(str(save_path) + '.png', dpi=dpi, bbox_inches=\"tight\", format=\"png\")\n",
+    "    plt.close(\"all\")\n",
+    "\n",
+    "\n",
+    "def visualize_env(save_dir):\n",
+    "    save_dir.mkdir(parents=True, exist_ok=True)\n",
+    "    dynamic_env, function = create_example_v1(100, num_per_task=500)\n",
+    "    \n",
+    "    additional_xaxis = np.arange(-6, 6, 0.1)\n",
+    "    for timestamp, dataset in dynamic_env:\n",
+    "        num = dataset.shape[0]\n",
+    "        # timeaxis = (torch.zeros(num) + timestamp).numpy()\n",
+    "        xaxis = dataset[:,0].numpy()\n",
+    "        xaxis = np.concatenate((additional_xaxis, xaxis))\n",
+    "        # compute the ground truth\n",
+    "        function.set_timestamp(timestamp)\n",
+    "        yaxis = function(xaxis)\n",
+    "        draw_fig(save_dir, timestamp, xaxis, yaxis)\n",
+    "\n",
+    "home_dir = Path.home()\n",
+    "desktop_dir = home_dir / 'Desktop'\n",
+    "vis_save_dir = desktop_dir / 'vis-synthetic'\n",
+    "visualize_env(vis_save_dir)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "rapid-uruguay",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ffmpeg -y -i /Users/xuanyidong/Desktop/vis-synthetic/%04d.png -pix_fmt yuv420p -vf fps=2 -vf scale=1000:1000 -vb 5000k /Users/xuanyidong/Desktop/vis-synthetic/vis.mp4\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Plot the data\n",
+    "cmd = 'ffmpeg -y -i {:}/%04d.png -pix_fmt yuv420p -vf fps=2 -vf scale=1000:1000 -vb 5000k {:}/vis.mp4'.format(vis_save_dir, vis_save_dir)\n",
+    "print(cmd)\n",
+    "os.system(cmd)"
+   ]
+  }
+ ],
+ "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
+}