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  {
   "cell_type": "markdown",
   "id": "6a739a84",
   "metadata": {},
   "source": [
    "# Tutorial: Two dimensional Wave problem with hard constraint\n",
    "\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial3/tutorial.ipynb)\n",
    "\n",
    "In this tutorial we present how to solve the wave equation using hard constraint PINNs. For doing so we will build a costum `torch` model and pass it to the `PINN` solver.\n",
    "\n",
    "First of all, some useful imports."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d93daba0",
   "metadata": {},
   "outputs": [],
   "source": [
    "## routine needed to run the notebook on Google Colab\n",
    "try:\n",
    "  import google.colab\n",
    "  IN_COLAB = True\n",
    "except:\n",
    "  IN_COLAB = False\n",
    "if IN_COLAB:\n",
    "  !pip install \"pina-mathlab\"\n",
    "  \n",
    "import torch\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('tableau-colorblind10')\n",
    "\n",
    "from pina.problem import SpatialProblem, TimeDependentProblem\n",
    "from pina.operator import laplacian, grad\n",
    "from pina.domain import CartesianDomain\n",
    "from pina.solver import PINN\n",
    "from pina.trainer import Trainer\n",
    "from pina.equation import Equation\n",
    "from pina.equation.equation_factory import FixedValue\n",
    "from pina import Condition, LabelTensor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2316f24e",
   "metadata": {},
   "source": [
    "## The problem definition "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc2bbf62",
   "metadata": {},
   "source": [
    "The problem is written in the following form:\n",
    "\n",
    "\\begin{equation}\n",
    "\\begin{cases}\n",
    "\\Delta u(x,y,t) = \\frac{\\partial^2}{\\partial t^2} u(x,y,t) \\quad \\text{in } D, \\\\\\\\\n",
    "u(x, y, t=0) = \\sin(\\pi x)\\sin(\\pi y), \\\\\\\\\n",
    "u(x, y, t) = 0 \\quad \\text{on } \\Gamma_1 \\cup \\Gamma_2 \\cup \\Gamma_3 \\cup \\Gamma_4,\n",
    "\\end{cases}\n",
    "\\end{equation}\n",
    "\n",
    "where $D$ is a squared domain $[0,1]^2$, and $\\Gamma_i$, with $i=1,...,4$, are the boundaries of the square, and the velocity in the standard wave equation is fixed to one."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbc50741",
   "metadata": {},
   "source": [
    "Now, the wave problem is written in PINA code as a class, inheriting from `SpatialProblem` and `TimeDependentProblem` since we deal with spatial, and time dependent variables. The equations are written as `conditions` that should be satisfied in the corresponding domains. `truth_solution` is the exact solution which will be compared with the predicted one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b60176c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Wave(TimeDependentProblem, SpatialProblem):\n",
    "    output_variables = ['u']\n",
    "    spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]})\n",
    "    temporal_domain = CartesianDomain({'t': [0, 1]})\n",
    "\n",
    "    def wave_equation(input_, output_):\n",
    "        u_t = grad(output_, input_, components=['u'], d=['t'])\n",
    "        u_tt = grad(u_t, input_, components=['dudt'], d=['t'])\n",
    "        nabla_u = laplacian(output_, input_, components=['u'], d=['x', 'y'])\n",
    "        return nabla_u - u_tt\n",
    "\n",
    "    def initial_condition(input_, output_):\n",
    "        u_expected = (torch.sin(torch.pi*input_.extract(['x'])) *\n",
    "                      torch.sin(torch.pi*input_.extract(['y'])))\n",
    "        return output_.extract(['u']) - u_expected\n",
    "\n",
    "    conditions = {\n",
    "        'bound_cond1': Condition(domain=CartesianDomain({'x': [0, 1], 'y':  1, 't': [0, 1]}), equation=FixedValue(0.)),\n",
    "        'bound_cond2': Condition(domain=CartesianDomain({'x': [0, 1], 'y': 0, 't': [0, 1]}), equation=FixedValue(0.)),\n",
    "        'bound_cond3': Condition(domain=CartesianDomain({'x':  1, 'y': [0, 1], 't': [0, 1]}), equation=FixedValue(0.)),\n",
    "        'bound_cond4': Condition(domain=CartesianDomain({'x': 0, 'y': [0, 1], 't': [0, 1]}), equation=FixedValue(0.)),\n",
    "        'time_cond': Condition(domain=CartesianDomain({'x': [0, 1], 'y': [0, 1], 't': 0}), equation=Equation(initial_condition)),\n",
    "        'phys_cond': Condition(domain=CartesianDomain({'x': [0, 1], 'y': [0, 1], 't': [0, 1]}), equation=Equation(wave_equation)),\n",
    "    }\n",
    "\n",
    "    def wave_sol(self, pts):\n",
    "        return (torch.sin(torch.pi*pts.extract(['x'])) *\n",
    "                torch.sin(torch.pi*pts.extract(['y'])) *\n",
    "                torch.cos(torch.sqrt(torch.tensor(2.))*torch.pi*pts.extract(['t'])))\n",
    "\n",
    "    truth_solution = wave_sol\n",
    "\n",
    "problem = Wave()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03557e0c-1f82-4dad-b611-5d33fddfd0ef",
   "metadata": {},
   "source": [
    "## Hard Constraint Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "356fe363",
   "metadata": {},
   "source": [
    "After the problem, a **torch** model is needed to solve the PINN. Usually, many models are already implemented in **PINA**, but the user has the possibility to build his/her own model in `torch`. The hard constraint we impose is on the boundary of the spatial domain. Specifically, our solution is written as:\n",
    "\n",
    "$$ u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t), $$\n",
    "\n",
    "where $NN$ is the neural net output. This neural network takes as input the coordinates (in this case $x$, $y$ and $t$) and provides the unknown field $u$. By construction, it is zero on the boundaries. The residuals of the equations are evaluated at several sampling points (which the user can manipulate using the method `discretise_domain`) and the loss minimized by the neural network is the sum of the residuals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9fbbb74f",
   "metadata": {},
   "outputs": [],
   "source": [
    "class HardMLP(torch.nn.Module):\n",
    "\n",
    "    def __init__(self, input_dim, output_dim):\n",
    "        super().__init__()\n",
    "\n",
    "        self.layers = torch.nn.Sequential(torch.nn.Linear(input_dim, 40),\n",
    "                                          torch.nn.ReLU(),\n",
    "                                          torch.nn.Linear(40, 40),\n",
    "                                          torch.nn.ReLU(),\n",
    "                                          torch.nn.Linear(40, output_dim))\n",
    "        \n",
    "    # here in the foward we implement the hard constraints\n",
    "    def forward(self, x):\n",
    "        hard = x.extract(['x'])*(1-x.extract(['x']))*x.extract(['y'])*(1-x.extract(['y']))\n",
    "        return hard*self.layers(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f79fc901-4720-4fac-8b72-84ac5f7d2ec3",
   "metadata": {},
   "source": [
    "## Train and Inference"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b465bebd",
   "metadata": {},
   "source": [
    "In this tutorial, the neural network is trained for 1000 epochs with a learning rate of 0.001 (default in `PINN`). Training takes approximately 3 minutes."
   ]
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_epochs=1000` reached.\n"
     ]
    }
   ],
   "source": [
    "# generate the data\n",
    "problem.discretise_domain(1000, 'random', domains=['phys_cond', 'time_cond', 'bound_cond1', 'bound_cond2', 'bound_cond3', 'bound_cond4'])\n",
    "\n",
    "# crete the solver\n",
    "pinn = PINN(problem, HardMLP(len(problem.input_variables), len(problem.output_variables)))\n",
    "\n",
    "# create trainer and train\n",
    "trainer = Trainer(pinn, max_epochs=1000, accelerator='cpu', enable_model_summary=False) # we train on CPU and avoid model summary at beginning of training (optional)\n",
    "trainer.train()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2a5c405",
   "metadata": {},
   "source": [
    "Notice that the loss on the boundaries of the spatial domain is exactly zero, as expected! After the training is completed one can now plot some results using the `Plotter` class of **PINA**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c086c05f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting at t=0\n",
      "Plotting at t=0.5\n",
      "Plotting at t=1\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "method='contourf'\n",
    "# plotting at fixed time t = 0.0\n",
    "print('Plotting at t=0')\n",
    "fixed_variables={'t': 0.0}\n",
    "pts = pinn.problem.spatial_domain.sample(256, 'grid', variables=['x','y'])\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fixed_pts = torch.ones(pts.shape[0], len(fixed_variables))\n",
    "fixed_pts *= torch.tensor(list(fixed_variables.values()))\n",
    "fixed_pts = fixed_pts.as_subclass(LabelTensor)\n",
    "fixed_pts.labels = list(fixed_variables.keys())\n",
    "pts = pts.append(fixed_pts)\n",
    "pts = pts.to(device=pinn.device)\n",
    "predicted_output = pinn.forward(pts).extract('u').as_subclass(torch.Tensor).cpu().detach().reshape(256,256)\n",
    "true_output = pinn.problem.truth_solution(pts).cpu().detach().reshape(256,256)\n",
    "pts = pts.cpu()\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(16, 6))\n",
    "cb = getattr(ax[0], method)(*grids, predicted_output)\n",
    "fig.colorbar(cb, ax=ax[0])\n",
    "ax[0].title.set_text('Neural Network prediction')\n",
    "cb = getattr(ax[1], method)(*grids, true_output)\n",
    "fig.colorbar(cb, ax=ax[1])\n",
    "ax[1].title.set_text('True solution')\n",
    "cb = getattr(ax[2],method)(*grids,(true_output - predicted_output))\n",
    "fig.colorbar(cb, ax=ax[2])\n",
    "ax[2].title.set_text('Residual')\n",
    "# plotting at fixed time t = 0.5\n",
    "print('Plotting at t=0.5')\n",
    "#plotter.plot(pinn, fixed_variables={'t': 0.5})\n",
    "fixed_variables={'t': 0.5}\n",
    "pts = pinn.problem.spatial_domain.sample(256, 'grid', variables=['x','y'])\n",
    "fixed_pts = torch.ones(pts.shape[0], len(fixed_variables))\n",
    "fixed_pts *= torch.tensor(list(fixed_variables.values()))\n",
    "fixed_pts = fixed_pts.as_subclass(LabelTensor)\n",
    "fixed_pts.labels = list(fixed_variables.keys())\n",
    "pts = pts.append(fixed_pts)\n",
    "pts = pts.to(device=pinn.device)\n",
    "predicted_output = pinn.forward(pts).extract('u').as_subclass(torch.Tensor).cpu().detach().reshape(256,256)\n",
    "true_output = pinn.problem.truth_solution(pts).cpu().detach().reshape(256,256)\n",
    "pts = pts.cpu()\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(16, 6))\n",
    "cb = getattr(ax[0], method)(*grids, predicted_output)\n",
    "fig.colorbar(cb, ax=ax[0])\n",
    "ax[0].title.set_text('Neural Network prediction')\n",
    "cb = getattr(ax[1], method)(*grids, true_output)\n",
    "fig.colorbar(cb, ax=ax[1])\n",
    "ax[1].title.set_text('True solution')\n",
    "cb = getattr(ax[2],method)(*grids,(true_output - predicted_output))\n",
    "fig.colorbar(cb, ax=ax[2])\n",
    "ax[2].title.set_text('Residual')\n",
    "# plotting at fixed time t = 1.\n",
    "print('Plotting at t=1')\n",
    "#plotter.plot(pinn, fixed_variables={'t': 1.0})\n",
    "fixed_variables={'t': 1.0}\n",
    "pts = pinn.problem.spatial_domain.sample(256, 'grid', variables=['x','y'])\n",
    "fixed_pts = torch.ones(pts.shape[0], len(fixed_variables))\n",
    "fixed_pts *= torch.tensor(list(fixed_variables.values()))\n",
    "fixed_pts = fixed_pts.as_subclass(LabelTensor)\n",
    "fixed_pts.labels = list(fixed_variables.keys())\n",
    "pts = pts.append(fixed_pts)\n",
    "pts = pts.to(device=pinn.device)\n",
    "predicted_output = pinn.forward(pts).extract('u').as_subclass(torch.Tensor).cpu().detach().reshape(256,256)\n",
    "true_output = pinn.problem.truth_solution(pts).cpu().detach().reshape(256,256)\n",
    "pts = pts.cpu()\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(16, 6))\n",
    "cb = getattr(ax[0], method)(*grids, predicted_output)\n",
    "fig.colorbar(cb, ax=ax[0])\n",
    "ax[0].title.set_text('Neural Network prediction')\n",
    "cb = getattr(ax[1], method)(*grids, true_output)\n",
    "fig.colorbar(cb, ax=ax[1])\n",
    "ax[1].title.set_text('True solution')\n",
    "cb = getattr(ax[2],method)(*grids,(true_output - predicted_output))\n",
    "fig.colorbar(cb, ax=ax[2])\n",
    "ax[2].title.set_text('Residual')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35e51649",
   "metadata": {},
   "source": [
    "The results are not so great, and we can clearly see that as time progress the solution gets worse.... Can we do better?\n",
    "\n",
    "A valid option is to impose the initial condition as hard constraint as well. Specifically, our solution is written as:\n",
    "\n",
    "$$ u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t)\\cdot t + \\cos(\\sqrt{2}\\pi t)\\sin(\\pi x)\\sin(\\pi y), $$\n",
    "\n",
    "Let us build the network first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "33e43412",
   "metadata": {},
   "outputs": [],
   "source": [
    "class HardMLPtime(torch.nn.Module):\n",
    "\n",
    "    def __init__(self, input_dim, output_dim):\n",
    "        super().__init__()\n",
    "\n",
    "        self.layers = torch.nn.Sequential(torch.nn.Linear(input_dim, 40),\n",
    "                                          torch.nn.ReLU(),\n",
    "                                          torch.nn.Linear(40, 40),\n",
    "                                          torch.nn.ReLU(),\n",
    "                                          torch.nn.Linear(40, output_dim))\n",
    "        \n",
    "    # here in the foward we implement the hard constraints\n",
    "    def forward(self, x):\n",
    "        hard_space = x.extract(['x'])*(1-x.extract(['x']))*x.extract(['y'])*(1-x.extract(['y']))\n",
    "        hard_t = torch.sin(torch.pi*x.extract(['x'])) * torch.sin(torch.pi*x.extract(['y'])) * torch.cos(torch.sqrt(torch.tensor(2.))*torch.pi*x.extract(['t']))\n",
    "        return hard_space * self.layers(x) * x.extract(['t']) + hard_t"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d3dc67b",
   "metadata": {},
   "source": [
    "Now let's train with the same configuration as thre previous test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f4bc6be2",
   "metadata": {},
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      "GPU available: False, used: False\n",
      "TPU available: False, using: 0 TPU cores\n",
      "HPU available: False, using: 0 HPUs\n"
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       "Sanity Checking: |          | 0/? [00:00<?, ?it/s]"
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       "version_minor": 0
      },
      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      },
      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f491b0b81ec24da58ea476ae5e8a868a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a61a512e051e44a49fb3db77601c96ad",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dc3f7de2ce194f908e64a22464d2027a",
       "version_major": 2,
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      },
      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d7645ffea3c94107b4373b5dfd319128",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "738c97edacce442f9d5e1cca0ec8bb95",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: |          | 0/? [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_epochs=1000` reached.\n"
     ]
    }
   ],
   "source": [
    "# generate the data\n",
    "problem.discretise_domain(1000, 'random', domains=['phys_cond', 'time_cond', 'bound_cond1', 'bound_cond2', 'bound_cond3', 'bound_cond4'])\n",
    "\n",
    "# crete the solver\n",
    "pinn = PINN(problem, HardMLPtime(len(problem.input_variables), len(problem.output_variables)))\n",
    "\n",
    "# create trainer and train\n",
    "trainer = Trainer(pinn, max_epochs=1000, accelerator='cpu', enable_model_summary=False) # we train on CPU and avoid model summary at beginning of training (optional)\n",
    "trainer.train()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0f80cb8",
   "metadata": {},
   "source": [
    "We can clearly see that the loss is way lower now. Let's plot the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "019767e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting at t=0\n",
      "Plotting at t=0.5\n",
      "Plotting at t=1\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting at fixed time t = 0.0\n",
    "print('Plotting at t=0')\n",
    "fixed_variables={'t': 0.0}\n",
    "pts = pinn.problem.spatial_domain.sample(256, 'grid', variables=['x','y'])\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fixed_pts = torch.ones(pts.shape[0], len(fixed_variables))\n",
    "fixed_pts *= torch.tensor(list(fixed_variables.values()))\n",
    "fixed_pts = fixed_pts.as_subclass(LabelTensor)\n",
    "fixed_pts.labels = list(fixed_variables.keys())\n",
    "pts = pts.append(fixed_pts)\n",
    "pts = pts.to(device=pinn.device)\n",
    "predicted_output = pinn.forward(pts).extract('u').as_subclass(torch.Tensor).cpu().detach().reshape(256,256)\n",
    "true_output = pinn.problem.truth_solution(pts).cpu().detach().reshape(256,256)\n",
    "pts = pts.cpu()\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(16, 6))\n",
    "cb = getattr(ax[0], method)(*grids, predicted_output)\n",
    "fig.colorbar(cb, ax=ax[0])\n",
    "ax[0].title.set_text('Neural Network prediction')\n",
    "cb = getattr(ax[1], method)(*grids, true_output)\n",
    "fig.colorbar(cb, ax=ax[1])\n",
    "ax[1].title.set_text('True solution')\n",
    "cb = getattr(ax[2],method)(*grids,(true_output - predicted_output))\n",
    "fig.colorbar(cb, ax=ax[2])\n",
    "ax[2].title.set_text('Residual')\n",
    "# plotting at fixed time t = 0.5\n",
    "print('Plotting at t=0.5')\n",
    "#plotter.plot(pinn, fixed_variables={'t': 0.5})\n",
    "fixed_variables={'t': 0.5}\n",
    "pts = pinn.problem.spatial_domain.sample(256, 'grid', variables=['x','y'])\n",
    "fixed_pts = torch.ones(pts.shape[0], len(fixed_variables))\n",
    "fixed_pts *= torch.tensor(list(fixed_variables.values()))\n",
    "fixed_pts = fixed_pts.as_subclass(LabelTensor)\n",
    "fixed_pts.labels = list(fixed_variables.keys())\n",
    "pts = pts.append(fixed_pts)\n",
    "pts = pts.to(device=pinn.device)\n",
    "predicted_output = pinn.forward(pts).extract('u').as_subclass(torch.Tensor).cpu().detach().reshape(256,256)\n",
    "true_output = pinn.problem.truth_solution(pts).cpu().detach().reshape(256,256)\n",
    "pts = pts.cpu()\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(16, 6))\n",
    "cb = getattr(ax[0], method)(*grids, predicted_output)\n",
    "fig.colorbar(cb, ax=ax[0])\n",
    "ax[0].title.set_text('Neural Network prediction')\n",
    "cb = getattr(ax[1], method)(*grids, true_output)\n",
    "fig.colorbar(cb, ax=ax[1])\n",
    "ax[1].title.set_text('True solution')\n",
    "cb = getattr(ax[2],method)(*grids,(true_output - predicted_output))\n",
    "fig.colorbar(cb, ax=ax[2])\n",
    "ax[2].title.set_text('Residual')\n",
    "# plotting at fixed time t = 1.\n",
    "print('Plotting at t=1')\n",
    "#plotter.plot(pinn, fixed_variables={'t': 1.0})\n",
    "fixed_variables={'t': 1.0}\n",
    "pts = pinn.problem.spatial_domain.sample(256, 'grid', variables=['x','y'])\n",
    "fixed_pts = torch.ones(pts.shape[0], len(fixed_variables))\n",
    "fixed_pts *= torch.tensor(list(fixed_variables.values()))\n",
    "fixed_pts = fixed_pts.as_subclass(LabelTensor)\n",
    "fixed_pts.labels = list(fixed_variables.keys())\n",
    "pts = pts.append(fixed_pts)\n",
    "pts = pts.to(device=pinn.device)\n",
    "predicted_output = pinn.forward(pts).extract('u').as_subclass(torch.Tensor).cpu().detach().reshape(256,256)\n",
    "true_output = pinn.problem.truth_solution(pts).cpu().detach().reshape(256,256)\n",
    "pts = pts.cpu()\n",
    "grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(16, 6))\n",
    "cb = getattr(ax[0], method)(*grids, predicted_output)\n",
    "fig.colorbar(cb, ax=ax[0])\n",
    "ax[0].title.set_text('Neural Network prediction')\n",
    "cb = getattr(ax[1], method)(*grids, true_output)\n",
    "fig.colorbar(cb, ax=ax[1])\n",
    "ax[1].title.set_text('True solution')\n",
    "cb = getattr(ax[2],method)(*grids,(true_output - predicted_output))\n",
    "fig.colorbar(cb, ax=ax[2])\n",
    "ax[2].title.set_text('Residual')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7338109",
   "metadata": {},
   "source": [
    "We can see now that the results are way better! This is due to the fact that previously the network was  not learning correctly the initial conditon, leading to a poor solution when time evolved. By imposing the initial condition the network is able to correctly solve the problem."
   ]
  },
  {
   "cell_type": "markdown",
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    "## What's next?\n",
    "\n",
    "Congratulations on completing the two dimensional Wave tutorial of **PINA**! There are multiple directions you can go now:\n",
    "\n",
    "1. Train the network for longer or with different layer sizes and assert the finaly accuracy\n",
    "\n",
    "2. Propose new types of hard constraints in time, e.g. $$ u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t)(1-\\exp(-t)) + \\cos(\\sqrt{2}\\pi t)sin(\\pi x)\\sin(\\pi y), $$\n",
    "\n",
    "3. Exploit extrafeature training for model 1 and 2\n",
    "\n",
    "4. Many more..."
   ]
  }
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