Wave1D_PINO.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))\n",
    "%matplotlib notebook\n",
    "from argparse import ArgumentParser\n",
    "import yaml\n",
    "import os\n",
    "import math\n",
    "import torch\n",
    "# from torch import vmap\n",
    "from functorch import vmap, grad\n",
    "from models import FNN2d\n",
    "from train_utils import Adam\n",
    "# from train_utils.datasets import BurgersLoader\n",
    "# from train_utils.train_2d import train_2d_burger\n",
    "# from train_utils.eval_2d import eval_burgers\n",
    "\n",
    "from solver.WaveEq import WaveEq1D\n",
    "import traceback\n",
    "\n",
    "import scipy.io\n",
    "import torch.nn.functional as F\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "import numpy as np\n",
    "import imageio\n",
    "\n",
    "\n",
    "from tqdm import tqdm\n",
    "from train_utils.utils import save_checkpoint, load_checkpoint, update_config, load_config\n",
    "from train_utils.losses import LpLoss\n",
    "from train_utils.datasets import DataLoader1D\n",
    "\n",
    "from solver.my_random_fields import GRF_Mattern\n",
    "\n",
    "from importlib import reload\n",
    "\n",
    "try:\n",
    "    import wandb\n",
    "except ImportError:\n",
    "    wandb = None\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define Loss Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spectral Derivatives"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def FDM_Wave(u, D=1, c=1.0):\n",
    "    batchsize = u.size(0)\n",
    "    nt = u.size(1)\n",
    "    nx = u.size(2)\n",
    "\n",
    "    u = u.reshape(batchsize, nt, nx)\n",
    "    dt = D / (nt-1)\n",
    "    dx = D / (nx)\n",
    "\n",
    "    u_h = torch.fft.fft(u, dim=2)\n",
    "    # Wavenumbers in y-direction\n",
    "    k_max = nx//2\n",
    "    k_x = torch.cat((torch.arange(start=0, end=k_max, step=1, device=u.device),\n",
    "                     torch.arange(start=-k_max, end=0, step=1, device=u.device)), 0).reshape(1,1,nx)\n",
    "    ux_h = 2j *np.pi*k_x*u_h\n",
    "    uxx_h = 2j *np.pi*k_x*ux_h\n",
    "    ux = torch.fft.irfft(ux_h[:, :, :k_max+1], dim=2, n=nx)\n",
    "    uxx = torch.fft.irfft(uxx_h[:, :, :k_max+1], dim=2, n=nx)\n",
    "    ut = (u[:, 2:, :] - u[:, :-2, :]) / (2 * dt)\n",
    "    utt = (u[:, 2:, :] - 2.0*u[:, 1:-1, :] + u[:, :-2, :]) / (dt**2)\n",
    "    Du = utt - c**2 * uxx[:,1:-1,:]\n",
    "    return Du\n",
    "\n",
    "\n",
    "def PINO_loss_wave(u, u0, c=1.0):\n",
    "    batchsize = u.size(0)\n",
    "    nt = u.size(1)\n",
    "    nx = u.size(2)\n",
    "\n",
    "    u = u.reshape(batchsize, nt, nx)\n",
    "    # lploss = LpLoss(size_average=True)\n",
    "\n",
    "    index_t = torch.zeros(nx,).long()\n",
    "    index_x = torch.tensor(range(nx)).long()\n",
    "    boundary_u = u[:, index_t, index_x]\n",
    "    loss_u = F.mse_loss(boundary_u, u0)\n",
    "\n",
    "    Du = FDM_Wave(u, c=c)[:, :, :]\n",
    "    f = torch.zeros(Du.shape, device=u.device)\n",
    "    loss_f = F.mse_loss(Du, f)\n",
    "\n",
    "    # loss_bc0 = F.mse_loss(u[:, :, 0], u[:, :, -1])\n",
    "    # loss_bc1 = F.mse_loss((u[:, :, 1] - u[:, :, -1]) /\n",
    "    #                       (2/(nx)), (u[:, :, 0] - u[:, :, -2])/(2/(nx)))\n",
    "    return loss_u, loss_f"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define Training Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_wave(model,\n",
    "               train_loader,\n",
    "               optimizer, \n",
    "               scheduler,\n",
    "               config,\n",
    "               rank=0, \n",
    "               log=False,\n",
    "               project='PINO-2d-default',\n",
    "               group='default',\n",
    "               tags=['default'],\n",
    "               use_tqdm=True):\n",
    "    if rank == 0 and wandb and log:\n",
    "        run = wandb.init(project=project,\n",
    "                         entity='shawngr2',\n",
    "                         group=group,\n",
    "                         config=config,\n",
    "                         tags=tags, reinit=True,\n",
    "                         settings=wandb.Settings(start_method=\"fork\"))\n",
    "\n",
    "    data_weight = config['train']['xy_loss']\n",
    "    f_weight = config['train']['f_loss']\n",
    "    ic_weight = config['train']['ic_loss']\n",
    "    c = config['data']['c']\n",
    "    ckpt_freq = config['train']['ckpt_freq']\n",
    "    model.train()\n",
    "    myloss = LpLoss(size_average=True)\n",
    "    pbar = range(config['train']['epochs'])\n",
    "    if use_tqdm:\n",
    "        pbar = tqdm(pbar, dynamic_ncols=True, smoothing=0.1)\n",
    "\n",
    "    for e in pbar:\n",
    "        model.train()\n",
    "        train_pino = 0.0\n",
    "        data_l2 = 0.0\n",
    "        train_ic = 0.0\n",
    "        train_loss = 0.0\n",
    "\n",
    "        for x, y in train_loader:\n",
    "            x, y = x.to(rank), y.to(rank)\n",
    "#             display(x.shape, y.shape)\n",
    "            out = model(x).reshape(y.shape)\n",
    "            data_loss = myloss(out, y)\n",
    "\n",
    "            loss_ic, loss_f = PINO_loss_wave(out, x[:, 0, :, 0], c=c)\n",
    "            total_loss = loss_ic * ic_weight + loss_f * f_weight + data_loss * data_weight\n",
    "\n",
    "            optimizer.zero_grad()\n",
    "            total_loss.backward()\n",
    "            optimizer.step()\n",
    "\n",
    "            data_l2 += data_loss.item()\n",
    "            train_pino += loss_f.item()\n",
    "            train_loss += total_loss.item()\n",
    "            train_ic += loss_ic.item()\n",
    "        scheduler.step()\n",
    "        data_l2 /= len(train_loader)\n",
    "        train_pino /= len(train_loader)\n",
    "        train_loss /= len(train_loader)\n",
    "        if use_tqdm:\n",
    "            pbar.set_description(\n",
    "                (\n",
    "                    f'Epoch {e}, train loss: {train_loss:.5f} '\n",
    "                    f'train f error: {train_pino:.5f}; '\n",
    "                    f'data l2 error: {data_l2:.5f}; '\n",
    "                    f'train ic error: {train_ic:.5f}'\n",
    "                )\n",
    "            )\n",
    "        if wandb and log:\n",
    "            wandb.log(\n",
    "                {\n",
    "                    'Train f error': train_pino,\n",
    "                    'Train L2 error': data_l2,\n",
    "                    'Train ic error': loss_ic,\n",
    "                    'Train loss': train_loss,\n",
    "                }\n",
    "            )\n",
    "\n",
    "        if e % ckpt_freq == 0:\n",
    "            save_checkpoint(config['train']['save_dir'],\n",
    "                            config['train']['save_name'].replace('.pt', f'_{e}.pt'),\n",
    "                            model, optimizer)\n",
    "    save_checkpoint(config['train']['save_dir'],\n",
    "                    config['train']['save_name'],\n",
    "                    model, optimizer)\n",
    "    print('Done!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def eval_wave(model,\n",
    "              dataloader,\n",
    "              config,\n",
    "              device,\n",
    "              use_tqdm=True):\n",
    "    model.eval()\n",
    "    myloss = LpLoss(size_average=True)\n",
    "    c = config['data']['c']\n",
    "    if use_tqdm:\n",
    "        pbar = tqdm(dataloader, dynamic_ncols=True, smoothing=0.05)\n",
    "    else:\n",
    "        pbar = dataloader\n",
    "\n",
    "    test_err = []\n",
    "    f_err = []\n",
    "\n",
    "    for x, y in pbar:\n",
    "        x, y = x.to(device), y.to(device)\n",
    "        out = model(x).reshape(y.shape)\n",
    "        data_loss = myloss(out, y)\n",
    "\n",
    "        loss_u, f_loss = PINO_loss_wave(out, x[:, 0, :, 0], c=c)\n",
    "        test_err.append(data_loss.item())\n",
    "        f_err.append(f_loss.item())\n",
    "\n",
    "    mean_f_err = np.mean(f_err)\n",
    "    std_f_err = np.std(f_err, ddof=1) / np.sqrt(len(f_err))\n",
    "\n",
    "    mean_err = np.mean(test_err)\n",
    "    std_err = np.std(test_err, ddof=1) / np.sqrt(len(test_err))\n",
    "\n",
    "    print(f'==Averaged relative L2 error mean: {mean_err}, std error: {std_err}==\\n'\n",
    "          f'==Averaged equation error mean: {mean_f_err}, std error: {std_f_err}==')\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load Config File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data': {'name': 'Wave-0000',\n",
       "  'total_num': 1000,\n",
       "  'n_train': 900,\n",
       "  'n_test': 100,\n",
       "  'nx': 4096,\n",
       "  'nt': 100,\n",
       "  'sub': 32,\n",
       "  'sub_t': 1,\n",
       "  'c': 1.0},\n",
       " 'model': {'layers': [16, 24, 24, 32, 32],\n",
       "  'modes1': [15, 12, 9, 9],\n",
       "  'modes2': [15, 12, 9, 9],\n",
       "  'fc_dim': 128,\n",
       "  'activation': 'gelu'},\n",
       " 'train': {'batchsize': 20,\n",
       "  'epochs': 500,\n",
       "  'milestones': [150, 300, 450],\n",
       "  'base_lr': 0.001,\n",
       "  'scheduler_gamma': 0.5,\n",
       "  'ic_loss': 5.0,\n",
       "  'f_loss': 1.0,\n",
       "  'xy_loss': 10.0,\n",
       "  'save_dir': 'Wave',\n",
       "  'save_name': 'Wave-eqn.pt',\n",
       "  'ckpt': 'checkpoints/Wave/Wave-eqn.pt',\n",
       "  'ckpt_freq': 100},\n",
       " 'log': {'project': 'PINO-Wave', 'group': 'Wave-0000'},\n",
       " 'test': {'batchsize': 1, 'ckpt': 'checkpoints/Wave/Wave-eqn.pt'}}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "config_file = 'configs/custom/wave-0000.yaml'\n",
    "config = load_config(config_file)\n",
    "display(config)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nsamples = config['data']['total_num']\n",
    "N = config['data']['nx']\n",
    "Nt0 = config['data']['nt']\n",
    "c = config['data']['c']\n",
    "sub_x = config['data']['sub']\n",
    "sub_t = config['data']['sub_t']\n",
    "Nx = N // sub_x\n",
    "Nt = Nt0 // sub_t + 1\n",
    "dim = 1\n",
    "l = 0.1\n",
    "L = 1.0\n",
    "sigma = 0.2 #2.0\n",
    "Nu = None # 2.0\n",
    "dt = 1.0e-4\n",
    "tend = 1.0\n",
    "save_int = int(tend/dt/Nt)\n",
    "\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Random Fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "grf = GRF_Mattern(dim, N, length=L, nu=Nu, l=l, sigma=sigma, boundary=\"periodic\", device=device)\n",
    "U0 = grf.sample(Nsamples)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "RuntimeError",
     "evalue": "CUDA out of memory. Tried to allocate 32.00 MiB (GPU 0; 15.78 GiB total capacity; 2.17 GiB already allocated; 20.75 MiB free; 2.19 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_58833/3065685695.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mwave_eq\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mWaveEq1D\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mNx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mU\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwave_eq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwave_driver\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0min_dims\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mU0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msave_int\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/.local/lib/python3.8/site-packages/functorch/_src/vmap.py\u001b[0m in \u001b[0;36mwrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    317\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    318\u001b[0m             \u001b[0mbatched_inputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_create_batched_inputs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mflat_in_dims\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflat_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvmap_level\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs_spec\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 319\u001b[0;31m             \u001b[0mbatched_outputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mbatched_inputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    320\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0m_unwrap_batched\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatched_outputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout_dims\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvmap_level\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    321\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/PINO/solver/WaveEq.py\u001b[0m in \u001b[0;36mwave_driver\u001b[0;34m(self, phi0, save_interval, plot_interval)\u001b[0m\n\u001b[1;32m    184\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtend\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    185\u001b[0m \u001b[0;31m#             print(f\"t:\\t{self.t}\")\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 186\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mphi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpsi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwave_rk4\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mphi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpsi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    187\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    188\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mit\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/PINO/solver/WaveEq.py\u001b[0m in \u001b[0;36mwave_rk4\u001b[0;34m(self, phi, psi, t)\u001b[0m\n\u001b[1;32m    138\u001b[0m         \u001b[0mpsi3\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate_field\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpsi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpsi_RHS3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep_frac\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1.0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    139\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 140\u001b[0;31m         \u001b[0mphi_RHS4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpsi_RHS4\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwave_calc_RHS\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mphi3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpsi3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    141\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    142\u001b[0m         \u001b[0mt_new\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/PINO/solver/WaveEq.py\u001b[0m in \u001b[0;36mwave_calc_RHS\u001b[0;34m(self, phi, psi)\u001b[0m\n\u001b[1;32m    104\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    105\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mwave_calc_RHS\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mphi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpsi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 106\u001b[0;31m         \u001b[0mphi_xx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDxx\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mphi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    107\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m         \u001b[0mpsi_RHS\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mphi_xx\u001b[0m \u001b[0;31m# it is usually c^2, but c is consistent with simflowny code\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/PINO/solver/WaveEq.py\u001b[0m in \u001b[0;36mDxx\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m     98\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     99\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mDxx\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 100\u001b[0;31m         \u001b[0mdata_dxx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCD_ii\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    101\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mdata_dxx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    102\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/PINO/solver/WaveEq.py\u001b[0m in \u001b[0;36mCD_ii\u001b[0;34m(self, data, axis, dx)\u001b[0m\n\u001b[1;32m     90\u001b[0m         \u001b[0mdata_p1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mroll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mshifts\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdims\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m         \u001b[0mdata_p2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mroll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mshifts\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdims\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 92\u001b[0;31m         \u001b[0mdata_diff_ii\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mdata_m2\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m16.0\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mdata_m1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m30.0\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m16.0\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mdata_p1\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0mdata_p2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m12.0\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mdx\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     93\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mdata_diff_ii\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     94\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mRuntimeError\u001b[0m: CUDA out of memory. Tried to allocate 32.00 MiB (GPU 0; 15.78 GiB total capacity; 2.17 GiB already allocated; 20.75 MiB free; 2.19 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF"
     ]
    }
   ],
   "source": [
    "wave_eq = WaveEq1D(Nx=N, c=c, dt=dt, device=device)\n",
    "U = vmap(wave_eq.wave_driver, in_dims=(0, None))(U0, save_int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = U0.cpu().float()\n",
    "u = U.cpu().float()\n",
    "\n",
    "display(u.shape,a.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = DataLoader(a, u, config['data']['nx'], config['data']['nt'], config['data']['sub'], config['data']['sub_t'])\n",
    "train_loader = dataset.make_loader(config['data']['n_train'], config['train']['batchsize'], start=0, train=True)\n",
    "test_loader = dataset.make_loader(config['data']['n_test'], config['test']['batchsize'], start=config['data']['n_train'], train=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "log = False\n",
    "model = FNN2d(modes1=config['model']['modes1'],\n",
    "                  modes2=config['model']['modes2'],\n",
    "                  fc_dim=config['model']['fc_dim'],\n",
    "                  layers=config['model']['layers'],\n",
    "                  activation=config['model']['activation']).to(device)\n",
    "\n",
    "optimizer = Adam(model.parameters(), betas=(0.9, 0.999),lr=config['train']['base_lr'])\n",
    "scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer,\n",
    "                                                 milestones=config['train']['milestones'],\n",
    "                                                 gamma=config['train']['scheduler_gamma'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load from checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weights loaded from checkpoints/Wave/Wave-eqn.pt\n"
     ]
    }
   ],
   "source": [
    "load_checkpoint(model, ckpt_path=config['train']['ckpt'], optimizer=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 0, train loss: 11.09598 train f error: 0.19722; data l2 error: 1.08572; train ic error: 0.37393:   0%|          | 1/500 [00:01<09:34,  1.15s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checkpoint is saved at checkpoints/Wave/Wave-eqn_0.pt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 100, train loss: 0.15661 train f error: 0.05580; data l2 error: 0.01008; train ic error: 0.00003:  20%|██        | 101/500 [01:52<07:24,  1.11s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checkpoint is saved at checkpoints/Wave/Wave-eqn_100.pt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 200, train loss: 0.12669 train f error: 0.06106; data l2 error: 0.00656; train ic error: 0.00002:  40%|████      | 201/500 [03:43<05:35,  1.12s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checkpoint is saved at checkpoints/Wave/Wave-eqn_200.pt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 300, train loss: 0.09267 train f error: 0.06581; data l2 error: 0.00269; train ic error: 0.00001:  60%|██████    | 301/500 [05:35<03:42,  1.12s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checkpoint is saved at checkpoints/Wave/Wave-eqn_300.pt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 400, train loss: 0.09134 train f error: 0.06733; data l2 error: 0.00240; train ic error: 0.00000:  80%|████████  | 401/500 [07:26<01:50,  1.12s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checkpoint is saved at checkpoints/Wave/Wave-eqn_400.pt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 499, train loss: 0.08624 train f error: 0.07007; data l2 error: 0.00162; train ic error: 0.00000: 100%|██████████| 500/500 [09:17<00:00,  1.12s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checkpoint is saved at checkpoints/Wave/Wave-eqn.pt\n",
      "Done!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "train_wave(model,\n",
    "           train_loader,\n",
    "           optimizer,\n",
    "           scheduler,\n",
    "           config,\n",
    "           rank=0,\n",
    "           log=log,\n",
    "           project=config['log']['project'],\n",
    "           group=config['log']['group'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluate on Test Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [00:00<00:00, 236.71it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==Averaged relative L2 error mean: 0.0012154258752707391, std error: 2.8122548682792986e-05==\n",
      "==Averaged equation error mean: 0.0747406174428761, std error: 0.003449729510826108==\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "eval_wave(model, test_loader, config, device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [00:00<00:00, 284.21it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==Averaged relative L2 error mean: 0.03709864497184753, std error: 0.0009186125951561321==\n",
      "==Averaged equation error mean: 0.012226411206647754, std error: 0.00044778704791337395==\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "eval_wave(model, test_loader, config, device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nx = config['data']['nx'] // config['data']['sub']\n",
    "Nt = config['data']['nt'] // config['data']['sub_t'] + 1\n",
    "Ntest = config['data']['n_test']\n",
    "model.eval()\n",
    "test_x = np.zeros((Ntest,Nt,Nx,3))\n",
    "preds_y = np.zeros((Ntest,Nt,Nx))\n",
    "test_y = np.zeros((Ntest,Nt,Nx))\n",
    "with torch.no_grad():\n",
    "    for i, data in enumerate(test_loader):\n",
    "        data_x, data_y = data\n",
    "        data_x, data_y = data_x.to(device), data_y.to(device)\n",
    "        pred_y = model(data_x).reshape(data_y.shape)\n",
    "        test_x[i] = data_x.cpu().numpy()\n",
    "        test_y[i] = data_y.cpu().numpy()\n",
    "        preds_y[i] = pred_y.cpu().numpy()\n",
    "#     data_loss = myloss(out, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "key = 1\n",
    "pred = preds_y[key]\n",
    "true = test_y[key]\n",
    "\n",
    "\n",
    "a = test_x[key]\n",
    "Nt, Nx, _ = a.shape\n",
    "u0 = a[0,:,0]\n",
    "T = a[:,:,2]\n",
    "X = a[:,:,1]\n",
    "x = X[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({'font.size': 11})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\" width=\"2158.888946079915\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0, 0.0, 1.0)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(24,5))\n",
    "plt.subplot(1,4,1)\n",
    "\n",
    "plt.plot(x, u0)\n",
    "plt.xlabel('$x$')\n",
    "plt.ylabel('$u$')\n",
    "plt.title('Intial Condition $u(x)$')\n",
    "plt.xlim([0,1])\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.subplot(1,4,2)\n",
    "# plt.pcolor(XX,TT, S_test, cmap='jet')\n",
    "plt.pcolormesh(X, T, true, cmap='jet', shading='gouraud')\n",
    "plt.colorbar()\n",
    "plt.xlabel('$x$')\n",
    "plt.ylabel('$t$')\n",
    "plt.title(f'Exact $u(x,t)$')\n",
    "plt.tight_layout()\n",
    "plt.axis('square')\n",
    "\n",
    "plt.subplot(1,4,3)\n",
    "# plt.pcolor(XX,TT, S_pred, cmap='jet')\n",
    "plt.pcolormesh(X, T, pred, cmap='jet', shading='gouraud')\n",
    "plt.colorbar()\n",
    "plt.xlabel('$x$')\n",
    "plt.ylabel('$t$')\n",
    "plt.title(f'Predict $u(x,t)$')\n",
    "plt.axis('square')\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.subplot(1,4,4)\n",
    "# plt.pcolor(XX,TT, S_pred - S_test, cmap='jet')\n",
    "plt.pcolormesh(X, T, pred - true, cmap='jet', shading='gouraud')\n",
    "plt.colorbar()\n",
    "plt.xlabel('$x$')\n",
    "plt.ylabel('$t$')\n",
    "plt.title('Absolute error')\n",
    "plt.tight_layout()\n",
    "plt.axis('square')\n",
    "\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\" width=\"538.8889031645696\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig = plt.figure(figsize=(6,5))\n",
    "ax = fig.add_subplot(111)\n",
    "plt.ion()\n",
    "\n",
    "fig.show()\n",
    "fig.canvas.draw()\n",
    "ax.plot(x, true[0], 'b-', label='Exact')\n",
    "ax.plot(x, pred[0], 'r--', label='PINO Prediction')\n",
    "ylim = plt.ylim()\n",
    "xlim = [0, 1]\n",
    "plt.tight_layout()\n",
    "\n",
    "\n",
    "\n",
    "for i in range(Nt):\n",
    "    ax.clear()\n",
    "    ax.plot(x, true[i], 'b-', label='Exact')\n",
    "    ax.plot(x, pred[i], 'r--', label='PINO Prediction')\n",
    "    plt.ylim(ylim)\n",
    "    plt.xlim(xlim)\n",
    "    plt.xlabel(f'$x$')\n",
    "    plt.ylabel(f'$u$')\n",
    "    plt.title(f'Wave Equation')\n",
    "    plt.legend(loc='lower right')\n",
    "    plt.tight_layout()\n",
    "    fig.canvas.draw()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save and Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_data(data_path, test_x, test_y, preds_y):\n",
    "    data_dir, data_filename = os.path.split(data_path)\n",
    "    os.makedirs(data_dir, exist_ok=True)\n",
    "    np.savez(data_path, test_x=test_x, test_y=test_y, preds_y=preds_y)\n",
    "\n",
    "def load_data(data_path):\n",
    "    data = np.load(data_path)\n",
    "    test_x = data['test_x']\n",
    "    test_y = data['test_y']\n",
    "    preds_y = data['preds_y']\n",
    "    return test_x, test_y, preds_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = 'data/Wave1D'\n",
    "data_filename = 'data.npz'\n",
    "data_path = os.path.join(data_dir, data_filename)\n",
    "# os.makedirs(data_dir, exist_ok=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_data(data_path, test_x, test_y, preds_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_x, test_y, preds_y = load_data(data_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_predictions(key, test_x, test_y, preds_y, print_index=False, save_path=None, font_size=None):\n",
    "    if font_size is not None:\n",
    "        plt.rcParams.update({'font.size': font_size})\n",
    "    pred = preds_y[key]\n",
    "    true = test_y[key]\n",
    "\n",
    "\n",
    "    a = test_x[key]\n",
    "    Nt, Nx, _ = a.shape\n",
    "    u0 = a[0,:,0]\n",
    "    T = a[:,:,2]\n",
    "    X = a[:,:,1]\n",
    "    x = X[0]\n",
    "\n",
    "    # Plot\n",
    "    fig = plt.figure(figsize=(23,5))\n",
    "    plt.subplot(1,4,1)\n",
    "\n",
    "    plt.plot(x, u0)\n",
    "    plt.xlabel('$x$')\n",
    "    plt.ylabel('$u$')\n",
    "    plt.title('Intial Condition $u(x)$')\n",
    "    plt.xlim([0,1])\n",
    "    plt.tight_layout()\n",
    "\n",
    "    plt.subplot(1,4,2)\n",
    "    # plt.pcolor(XX,TT, S_test, cmap='jet')\n",
    "    plt.pcolormesh(X, T, true, cmap='jet', shading='gouraud')\n",
    "    plt.colorbar()\n",
    "    plt.xlabel('$x$')\n",
    "    plt.ylabel('$t$')\n",
    "    plt.title(f'Exact $u(x,t)$')\n",
    "    plt.tight_layout()\n",
    "    plt.axis('square')\n",
    "\n",
    "    plt.subplot(1,4,3)\n",
    "    # plt.pcolor(XX,TT, S_pred, cmap='jet')\n",
    "    plt.pcolormesh(X, T, pred, cmap='jet', shading='gouraud')\n",
    "    plt.colorbar()\n",
    "    plt.xlabel('$x$')\n",
    "    plt.ylabel('$t$')\n",
    "    plt.title(f'Predict $u(x,t)$')\n",
    "    plt.axis('square')\n",
    "\n",
    "    plt.tight_layout()\n",
    "\n",
    "    plt.subplot(1,4,4)\n",
    "    # plt.pcolor(XX,TT, S_pred - S_test, cmap='jet')\n",
    "    plt.pcolormesh(X, T, pred - true, cmap='jet', shading='gouraud')\n",
    "    plt.colorbar()\n",
    "    plt.xlabel('$x$')\n",
    "    plt.ylabel('$t$')\n",
    "    plt.title('Absolute Error')\n",
    "    plt.tight_layout()\n",
    "    plt.axis('square')\n",
    "\n",
    "    if save_path is not None:\n",
    "        plt.savefig(f'{save_path}.png', bbox_inches='tight')\n",
    "    plt.show()\n",
    "\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Movies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_movie_1D(key, test_x, test_y, preds_y, plot_title='', movie_dir='', movie_name='movie.gif', frame_basename='movie', frame_ext='jpg', remove_frames=True, font_size=None):\n",
    "    frame_files = []\n",
    "    os.makedirs(movie_dir, exist_ok=True)\n",
    "\n",
    "    if font_size is not None:\n",
    "        plt.rcParams.update({'font.size': font_size})\n",
    "    \n",
    "    pred = preds_y[key]\n",
    "    true = test_y[key]\n",
    "\n",
    "    \n",
    "    a = test_x[key]\n",
    "    Nt, Nx, _ = a.shape\n",
    "    u0 = a[0,:,0]\n",
    "    T = a[:,:,2]\n",
    "    X = a[:,:,1]\n",
    "    x = X[0]\n",
    "    t = T[:,0]\n",
    "\n",
    "    fig = plt.figure(figsize=(6,5))\n",
    "    ax = fig.add_subplot(111)\n",
    "    plt.ion()\n",
    "\n",
    "    fig.show()\n",
    "    fig.canvas.draw()\n",
    "    a = test_x[key]\n",
    "    Nt, Nx, _ = a.shape\n",
    "    u0 = a[0,:,0]\n",
    "    T = a[:,:,2]\n",
    "    X = a[:,:,1]\n",
    "    x = X[0]\n",
    "    ax.plot(x, true[0], 'b-', label='Exact')\n",
    "    ax.plot(x, pred[0], 'r--', label='PINO Prediction')\n",
    "    ylim = plt.ylim()\n",
    "    xlim = [0, 1]\n",
    "#     plt.xlim(xlim)\n",
    "#     plt.xlabel(f'$x$')\n",
    "#     plt.ylabel(f'$u$')\n",
    "#     plt.title(f'{plot_title} $t={t[0]:.2f}$')\n",
    "#     plt.legend(loc='lower right')\n",
    "    plt.tight_layout()\n",
    "    \n",
    "    \n",
    "    \n",
    "    for i in range(Nt):\n",
    "        ax.clear()\n",
    "        ax.plot(x, true[i], 'b-', label='Exact')\n",
    "        ax.plot(x, pred[i], 'r--', label='PINO Prediction')\n",
    "        \n",
    "        plt.xlabel(f'$x$')\n",
    "        plt.ylabel(f'$u$')\n",
    "        plt.title(f'{plot_title} $t={t[i]:.2f}$')\n",
    "        plt.legend(loc='lower right')\n",
    "        plt.ylim(ylim)\n",
    "        plt.xlim(xlim)\n",
    "        plt.tight_layout()\n",
    "        fig.canvas.draw()\n",
    "#         plt.show()\n",
    "        if movie_dir:\n",
    "            frame_path = os.path.join(movie_dir,f'{frame_basename}-{i:03}.{frame_ext}')\n",
    "            frame_files.append(frame_path)\n",
    "            plt.savefig(frame_path)\n",
    "    \n",
    "    if movie_dir:\n",
    "        movie_path = os.path.join(movie_dir, movie_name)\n",
    "        with imageio.get_writer(movie_path, mode='I') as writer:\n",
    "            for frame in frame_files:\n",
    "                image = imageio.imread(frame)\n",
    "                writer.append_data(image)\n",
    "                \n",
    "    if movie_dir and remove_frames:\n",
    "        for frame in frame_files:\n",
    "            try:\n",
    "                os.remove(frame)\n",
    "            except:\n",
    "                pass\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Movie Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = 'data/Wave1D'\n",
    "data_filename = 'data.npz'\n",
    "data_path = os.path.join(data_dir, data_filename)\n",
    "# os.makedirs(data_dir, exist_ok=True)\n",
    "test_x, test_y, preds_y = load_data(data_path)\n",
    "\n",
    "movie_dir = 'Wave1D/movie/'\n",
    "os.makedirs(movie_dir, exist_ok=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "key = 0\n",
    "movie_name = f'Wave1D_{key}.gif'\n",
    "frame_basename = f'Wave1D_{key}_frame'\n",
    "frame_ext = 'jpg'\n",
    "plot_title = \"Wave Equation\"\n",
    "font_size = 12\n",
    "remove_frames = True\n",
    "\n",
    "generate_movie_1D(key, test_x, test_y, preds_y, plot_title=plot_title, movie_dir=movie_dir, movie_name=movie_name, frame_basename=frame_basename, frame_ext=frame_ext, remove_frames=remove_frames, font_size=font_size)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "key = 1\n",
    "movie_name = f'Wave1D_{key}.gif'\n",
    "frame_basename = f'Wave1D_{key}_frame'\n",
    "frame_ext = 'jpg'\n",
    "plot_title = \"Wave Equation\"\n",
    "font_size = 12\n",
    "remove_frames = True\n",
    "\n",
    "generate_movie_1D(key, test_x, test_y, preds_y, plot_title=plot_title, movie_dir=movie_dir, movie_name=movie_name, frame_basename=frame_basename, frame_ext=frame_ext, remove_frames=remove_frames, font_size=font_size)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "key = 2\n",
    "movie_name = f'Wave1D_{key}.gif'\n",
    "frame_basename = f'Wave1D_{key}_frame'\n",
    "frame_ext = 'jpg'\n",
    "plot_title = \"Wave Equation\"\n",
    "font_size = 12\n",
    "remove_frames = True\n",
    "\n",
    "generate_movie_1D(key, test_x, test_y, preds_y, plot_title=plot_title, movie_dir=movie_dir, movie_name=movie_name, frame_basename=frame_basename, frame_ext=frame_ext, remove_frames=remove_frames, font_size=font_size)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"387.77778805038105\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig = plt.figure(figsize=(6,5))\n",
    "ax = fig.add_subplot(111)\n",
    "plt.ion()\n",
    "\n",
    "\n",
    "fig.show()\n",
    "fig.canvas.draw()\n",
    "diff = pred - true\n",
    "ax.plot(x, pred[0] - true[0], 'b-', label='Difference')\n",
    "# ax.plot(x, pred[0], 'r--', label='PINO Prediction')\n",
    "ylim = [diff.min(), diff.max()]\n",
    "xlim = [0, 1]\n",
    "plt.xlim(xlim)\n",
    "plt.ylim(ylim)\n",
    "plt.tight_layout()\n",
    "\n",
    "\n",
    "\n",
    "for i in range(Nt):\n",
    "    ax.clear()\n",
    "#     ax.plot(x, true[i], 'b-', label='Exact')\n",
    "#     ax.plot(x, pred[i], 'r--', label='PINO Prediction')\n",
    "    ax.plot(x, diff[i], 'b-', label='Difference')\n",
    "    plt.ylim(ylim)\n",
    "    plt.xlim(xlim)\n",
    "    plt.xlabel(f'$x$')\n",
    "    plt.ylabel(f'$u$')\n",
    "    plt.title(f'Wave Equation')\n",
    "    plt.legend(loc='lower right')\n",
    "    plt.tight_layout()\n",
    "    fig.canvas.draw()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "myenv",
   "language": "python",
   "name": "myenv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}