661 lines
389 KiB
Plaintext
Vendored
661 lines
389 KiB
Plaintext
Vendored
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "6a739a84",
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"metadata": {},
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"source": [
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"# Tutorial: Two dimensional Wave problem with hard constraint\n",
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"\n",
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"[](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial3/tutorial.ipynb)\n",
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"\n",
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"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",
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"\n",
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"First of all, some useful imports."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "d93daba0",
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"metadata": {},
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"outputs": [],
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"source": [
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"## routine needed to run the notebook on Google Colab\n",
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"try:\n",
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" import google.colab\n",
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" IN_COLAB = True\n",
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"except:\n",
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" IN_COLAB = False\n",
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"if IN_COLAB:\n",
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" !pip install \"pina-mathlab\"\n",
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" \n",
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"import torch\n",
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"\n",
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"import matplotlib.pylab as plt\n",
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"from pina.problem import SpatialProblem, TimeDependentProblem\n",
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"from pina.operator import laplacian, grad\n",
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"from pina.domain import CartesianDomain\n",
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"from pina.solver import PINN\n",
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"from pina.trainer import Trainer\n",
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"from pina.equation import Equation\n",
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"from pina.equation.equation_factory import FixedValue\n",
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"from pina import Condition, LabelTensor"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2316f24e",
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"metadata": {},
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"source": [
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"## The problem definition "
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]
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},
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{
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"cell_type": "markdown",
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"id": "bc2bbf62",
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"metadata": {},
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"source": [
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"The problem is written in the following form:\n",
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"\n",
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"\\begin{equation}\n",
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"\\begin{cases}\n",
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"\\Delta u(x,y,t) = \\frac{\\partial^2}{\\partial t^2} u(x,y,t) \\quad \\text{in } D, \\\\\\\\\n",
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"u(x, y, t=0) = \\sin(\\pi x)\\sin(\\pi y), \\\\\\\\\n",
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"u(x, y, t) = 0 \\quad \\text{on } \\Gamma_1 \\cup \\Gamma_2 \\cup \\Gamma_3 \\cup \\Gamma_4,\n",
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"\\end{cases}\n",
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"\\end{equation}\n",
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"\n",
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"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."
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]
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},
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{
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"cell_type": "markdown",
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"id": "cbc50741",
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"metadata": {},
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"source": [
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"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."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "b60176c4",
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"metadata": {},
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"outputs": [],
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"source": [
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"class Wave(TimeDependentProblem, SpatialProblem):\n",
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" output_variables = ['u']\n",
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" spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]})\n",
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" temporal_domain = CartesianDomain({'t': [0, 1]})\n",
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"\n",
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" def wave_equation(input_, output_):\n",
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" u_t = grad(output_, input_, components=['u'], d=['t'])\n",
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" u_tt = grad(u_t, input_, components=['dudt'], d=['t'])\n",
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" nabla_u = laplacian(output_, input_, components=['u'], d=['x', 'y'])\n",
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" return nabla_u - u_tt\n",
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"\n",
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" def initial_condition(input_, output_):\n",
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" u_expected = (torch.sin(torch.pi*input_.extract(['x'])) *\n",
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" torch.sin(torch.pi*input_.extract(['y'])))\n",
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" return output_.extract(['u']) - u_expected\n",
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"\n",
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" conditions = {\n",
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" 'bound_cond1': Condition(domain=CartesianDomain({'x': [0, 1], 'y': 1, 't': [0, 1]}), equation=FixedValue(0.)),\n",
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" 'bound_cond2': Condition(domain=CartesianDomain({'x': [0, 1], 'y': 0, 't': [0, 1]}), equation=FixedValue(0.)),\n",
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" 'bound_cond3': Condition(domain=CartesianDomain({'x': 1, 'y': [0, 1], 't': [0, 1]}), equation=FixedValue(0.)),\n",
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" 'bound_cond4': Condition(domain=CartesianDomain({'x': 0, 'y': [0, 1], 't': [0, 1]}), equation=FixedValue(0.)),\n",
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" 'time_cond': Condition(domain=CartesianDomain({'x': [0, 1], 'y': [0, 1], 't': 0}), equation=Equation(initial_condition)),\n",
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" 'phys_cond': Condition(domain=CartesianDomain({'x': [0, 1], 'y': [0, 1], 't': [0, 1]}), equation=Equation(wave_equation)),\n",
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" }\n",
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"\n",
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" def wave_sol(self, pts):\n",
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" return (torch.sin(torch.pi*pts.extract(['x'])) *\n",
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" torch.sin(torch.pi*pts.extract(['y'])) *\n",
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" torch.cos(torch.sqrt(torch.tensor(2.))*torch.pi*pts.extract(['t'])))\n",
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"\n",
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" truth_solution = wave_sol\n",
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"\n",
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"problem = Wave()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "03557e0c-1f82-4dad-b611-5d33fddfd0ef",
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"metadata": {},
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"source": [
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"## Hard Constraint Model"
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]
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},
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{
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"cell_type": "markdown",
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"id": "356fe363",
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"metadata": {},
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"source": [
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"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",
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"\n",
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"$$ u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t), $$\n",
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"\n",
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"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."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "9fbbb74f",
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"metadata": {},
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"outputs": [],
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"source": [
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"class HardMLP(torch.nn.Module):\n",
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"\n",
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" def __init__(self, input_dim, output_dim):\n",
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" super().__init__()\n",
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"\n",
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" self.layers = torch.nn.Sequential(torch.nn.Linear(input_dim, 40),\n",
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" torch.nn.ReLU(),\n",
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" torch.nn.Linear(40, 40),\n",
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" torch.nn.ReLU(),\n",
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" torch.nn.Linear(40, output_dim))\n",
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" \n",
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" # here in the foward we implement the hard constraints\n",
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" def forward(self, x):\n",
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" hard = x.extract(['x'])*(1-x.extract(['x']))*x.extract(['y'])*(1-x.extract(['y']))\n",
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" return hard*self.layers(x)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f79fc901-4720-4fac-8b72-84ac5f7d2ec3",
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"metadata": {},
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"source": [
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"## Train and Inference"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b465bebd",
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"metadata": {},
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"source": [
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"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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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "0be8e7f5",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"GPU available: False, used: False\n",
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"TPU available: False, using: 0 TPU cores\n",
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"HPU available: False, using: 0 HPUs\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 0: 100%|██████████| 1/1 [00:00<00:00, 17.47it/s, v_num=18] \n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 10.66it/s, v_num=18, val_loss=0.172, bound_cond1_loss=0.000, bound_cond2_loss=0.000, bound_cond3_loss=0.000, bound_cond4_loss=0.000, time_cond_loss=0.143, phys_cond_loss=0.0252, train_loss=0.169] "
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"`Trainer.fit` stopped: `max_epochs=1000` reached.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 9.53it/s, v_num=18, val_loss=0.172, bound_cond1_loss=0.000, bound_cond2_loss=0.000, bound_cond3_loss=0.000, bound_cond4_loss=0.000, time_cond_loss=0.143, phys_cond_loss=0.0252, train_loss=0.169]\n"
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]
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}
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],
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"source": [
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"# generate the data\n",
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"problem.discretise_domain(1000, 'random', domains=['phys_cond', 'time_cond', 'bound_cond1', 'bound_cond2', 'bound_cond3', 'bound_cond4'])\n",
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"\n",
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"# crete the solver\n",
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"pinn = PINN(problem, HardMLP(len(problem.input_variables), len(problem.output_variables)))\n",
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"\n",
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"# create trainer and train\n",
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"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",
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"trainer.train()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c2a5c405",
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"metadata": {},
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"source": [
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"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**."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "c086c05f",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Plotting at t=0\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Plotting at t=0.5\n",
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"Plotting at t=1\n"
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]
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},
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{
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"data": {
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"image/png": 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|
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"text/plain": [
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"<Figure size 1600x600 with 6 Axes>"
|
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]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
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},
|
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{
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"data": {
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"image/png": 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|
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"text/plain": [
|
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"<Figure size 1600x600 with 6 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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",
|
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"text/plain": [
|
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"<Figure size 1600x600 with 6 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"#plotter = Plotter()\n",
|
|
"\n",
|
|
"# plotting at fixed time t = 0.0\n",
|
|
"print('Plotting at t=0')\n",
|
|
"#plotter.plot(pinn, fixed_variables={'t': 0.0})\n",
|
|
"fixed_variables={'t': 0.0}\n",
|
|
"method='contourf'\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": 17,
|
|
"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": 18,
|
|
"id": "f4bc6be2",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"GPU available: False, used: False\n",
|
|
"TPU available: False, using: 0 TPU cores\n",
|
|
"HPU available: False, using: 0 HPUs\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 7.45it/s, v_num=19, val_loss=9.22e-7, bound_cond1_loss=1.95e-15, bound_cond2_loss=0.000, bound_cond3_loss=2.1e-15, bound_cond4_loss=0.000, time_cond_loss=0.000, phys_cond_loss=8.58e-7, train_loss=8.58e-7] "
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"`Trainer.fit` stopped: `max_epochs=1000` reached.\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 6.91it/s, v_num=19, val_loss=9.22e-7, bound_cond1_loss=1.95e-15, bound_cond2_loss=0.000, bound_cond3_loss=2.1e-15, bound_cond4_loss=0.000, time_cond_loss=0.000, phys_cond_loss=8.58e-7, train_loss=8.58e-7]\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": 19,
|
|
"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": {
|
|
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|
|
"text/plain": [
|
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"<Figure size 1600x600 with 6 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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|
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"text/plain": [
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"<Figure size 1600x600 with 6 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
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",
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"text/plain": [
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"<Figure size 1600x600 with 6 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
|
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"#plotter = Plotter()\n",
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"\n",
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"# plotting at fixed time t = 0.0\n",
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"print('Plotting at t=0')\n",
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"#plotter.plot(pinn, fixed_variables={'t': 0.0})\n",
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"fixed_variables={'t': 0.0}\n",
|
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"method='contourf'\n",
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"pts = pinn.problem.spatial_domain.sample(256, 'grid', variables=['x','y'])\n",
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"grids = [p_.reshape(256, 256) for p_ in pts.extract(['x','y']).T]\n",
|
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"fixed_pts = torch.ones(pts.shape[0], len(fixed_variables))\n",
|
|
"fixed_pts *= torch.tensor(list(fixed_variables.values()))\n",
|
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"fixed_pts = fixed_pts.as_subclass(LabelTensor)\n",
|
|
"fixed_pts.labels = list(fixed_variables.keys())\n",
|
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"pts = pts.append(fixed_pts)\n",
|
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"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",
|
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"cb = getattr(ax[0], method)(*grids, predicted_output)\n",
|
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"fig.colorbar(cb, ax=ax[0])\n",
|
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"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",
|
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"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",
|
|
"id": "61195b1f",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 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..."
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.12.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|