diff --git a/tutorials/tutorial14/tutorial.ipynb b/tutorials/tutorial14/tutorial.ipynb new file mode 100644 index 0000000..d732094 --- /dev/null +++ b/tutorials/tutorial14/tutorial.ipynb @@ -0,0 +1,639 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial: Predicting Lid-driven cavity problem parameters with POD-RBF\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/tutorial14/tutorial.ipynb)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this tutorial we will show how to use the **PINA** library to predict the distributions of velocity and pressure the Lid-driven Cavity problem, a benchmark in Computational Fluid Dynamics. The problem consists of a square cavity with a lid on top moving with tangential velocity (by convention to the right), with the addition of no-slip conditions on the walls of the cavity and null static pressure on the lower left angle. \n", + "\n", + "Our goal is to predict the distributions of velocity and pressure of the fluid inside the cavity as the Reynolds number of the inlet fluid varies. To do so we're using a Reduced Order Model (ROM) based on Proper Orthogonal Decomposition (POD). The parametric solution manifold is approximated here with Radial Basis Function (RBF) Interpolation, a common mesh-free interpolation method that doesn't require trainers or solvers as the found radial basis functions are used to interpolate new points." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's start with the necessary imports. We're particularly interested in the `PODBlock` and `RBFBlock` classes which will allow us to define the POD-RBF model." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "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", + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "plt.style.use('tableau-colorblind10')\n", + "import torch\n", + "import pina\n", + "from pina.model.layers import PODBlock, RBFBlock\n", + "from pina import LabelTensor" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this tutorial we're gonna use the `LidCavity` class from the [Smithers](https://github.com/mathLab/Smithers) library, which contains a set of parametric solutions of the Lid-driven cavity problem in a square domain. The dataset consists of 300 snapshots of the parameter fields, which in this case are the magnitude of velocity and the pressure, and the corresponding parameter values $u$ and $p$. Each snapshot corresponds to a different value of the tangential velocity $\\mu$ of the lid, which has been sampled uniformly between 0.01 m/s and 1 m/s.\n", + "\n", + "Let's start by importing the dataset:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1;31merror\u001b[0m: \u001b[1mexternally-managed-environment\u001b[0m\n", + "\n", + "\u001b[31m×\u001b[0m This environment is externally managed\n", + "\u001b[31m╰─>\u001b[0m To install Python packages system-wide, try apt install\n", + "\u001b[31m \u001b[0m python3-xyz, where xyz is the package you are trying to\n", + "\u001b[31m \u001b[0m install.\n", + "\u001b[31m \u001b[0m \n", + "\u001b[31m \u001b[0m If you wish to install a non-Debian-packaged Python package,\n", + "\u001b[31m \u001b[0m create a virtual environment using python3 -m venv path/to/venv.\n", + "\u001b[31m \u001b[0m Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make\n", + "\u001b[31m \u001b[0m sure you have python3-full installed.\n", + "\u001b[31m \u001b[0m \n", + "\u001b[31m \u001b[0m If you wish to install a non-Debian packaged Python application,\n", + "\u001b[31m \u001b[0m it may be easiest to use pipx install xyz, which will manage a\n", + "\u001b[31m \u001b[0m virtual environment for you. Make sure you have pipx installed.\n", + "\u001b[31m \u001b[0m \n", + "\u001b[31m \u001b[0m See /usr/share/doc/python3.12/README.venv for more information.\n", + "\n", + "\u001b[1;35mnote\u001b[0m: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.\n", + "\u001b[1;36mhint\u001b[0m: See PEP 668 for the detailed specification.\n" + ] + } + ], + "source": [ + "!pip install git+https://github.com/mathLab/Smithers.git #if required --break-system-packages\n", + "import smithers\n", + "from smithers.dataset import LidCavity\n", + "dataset = LidCavity()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's plot two the data points and the corresponding solution for both parameters at different snapshots, in order to better visualise the data we're using:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:4: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:8: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:4: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:8: SyntaxWarning: invalid escape sequence '\\m'\n", + "/tmp/ipykernel_73091/1539980039.py:4: SyntaxWarning: invalid escape sequence '\\m'\n", + " ax.set_title(f'$u$ field for $\\mu$ = {par[0]:.4f}')\n", + "/tmp/ipykernel_73091/1539980039.py:8: SyntaxWarning: invalid escape sequence '\\m'\n", + " ax.set_title(f'$p$ field for $\\mu$ = {par[0]:.4f}')\n" + ] + }, + { + "data": { + "image/png": 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QIEpwxhjt27ePiSKCDh8+rFOnTjFRAHAssj/yyH4ATkf2Rx7ZD7cJq0C0fPly5eTkyOPxKC8vT9u3b2+z7b59+3TzzTcrJydHSUlJWrJkSZe3ic5LSkrSqVOn9MQTT8S6Kwlj8ODBMsbozjvvjHVXgKgi++MH2R95ZD/ciuyPH2R/5JH9cBvLBaK1a9eqpKREpaWlqqys1JgxY1RYWKiampqQ7T/66CMNHjxYTzzxhLKysiKyTQBAdJH9AOA+ZD8AuIvlbzHLy8vTuHHjtGzZMkmS3+/XgAEDNGfOHM2bN6/ddXNycvTAAw/ogQceiNg2AQD2I/sBwH3IfgBwl1QrjZuamrRjxw7Nnz8/sCw5OVkFBQWqqKgIqwPhbLOxsVGNjY2Bf/v9fn344Ye69NJLlZSUFFY/ACAeGWP0j3/8Q9nZ2UpOtudj5ch+AHAWsp/sB+Au0ch9yWKB6MSJE2publZmZmbQ8szMTB04cCCsDoSzzbKyMj3++ONhPR4AJKJjx46pf//+tmyb7AcAZyL7AcBd7Mx9yWKByCnmz5+vkpKSwL99Pp8GDhyo6wbdraQ+vQPLGy/xnP//3ueH2ui1drWhKaMLnQUSzBleDyGdzWi2vE5KRlPI5V7vR4H/z76oTpKU0/PvkqSh3askScPSPpAk1Z/y65YJR3TxxRdbfvx401b2f2ZMiVJT0iVJjb3JfSDW3DJPRDv3h6ad+++ItNP6xym/rrq62tXZP3H0NwLZ33Th3/zec9nf5LV2hb0p8Z9KIKYS4W+rs16/pfb+i8+GXJ52cWOrZZdedG4e6HdRnQb1+Htg+Sc91eeWN72vm/KP2Z77lgpEffr0UUpKiqqrq4OWV1dXt/lBdHZsMz09Xenp6a2WJ/XprdTUcxNEY29PYHCNvVODBno2zdqJQkrrhwJcq9nTcRs3Su5u/UQhuUfoP15TepzfVreeaZKk9Iu6SZKOaICGdf9ARzRAI9KPB9rZeZu907M/NSVdqSkeNfbxBGV9c7fz/yL3gehxyzxhV+5X+y9T/4t9rXL/mM5dMe6Z/oHqm861J/vT1dS7+/m/+Xud/5u/Oc1agYjcB+yVkgBzg99jrUCUfEbyZ7QuEp0961F6RnCRKLXnuVzv1jNN76uvLu95QpJ0TP011FOl46eyJR2z/a21lpIzLS1NY8eOVXl5eWCZ3+9XeXm58vPzw+qAHdts6woyAMSbv/3DK0n6n1N9AssOnO4rSXq7sZ8ONPW1vQ/xkP2NfYL/6rgw+xt68RkVAOJPqNyXpAON9ue+FB/Z39S7e+D/G3tdcNdoL/s+nwMAouFw/fk54GBDeEX5cFhOz5KSEv34xz/Wz372M+3fv19f+9rXVF9fr5kzZ0qSpk+fHvTBc01NTdq1a5d27dqlpqYmHT9+XLt27dJf//rXTm+zsxov8XRYHArnRCHNZ3kVICE1eWPdA3c46esZ9O/2ikTR4ujs7912cQhAdDFPhMdq7h9sis7JgpOzP+htZb3IfQD26+azr/h84h/n5oG/nTo/kV5YJPprQ2ardexgOU2Li4tVW1urhQsXqqqqSrm5udq0aVPgw+aOHj0a9Kna77//vj71qU8F/v3kk0/qySef1KRJk/Taa691apvhiFRxCADs0uxLU4o39OdRnPT1VC9vfeDff/uHV/0v9gVOFgZfdEIHTvdV4+kzUelrPGR/JHM/zceJLoDIay/3P66t3JdE9l/g48Uh7h4CEA8a69Jbvc3sxD96qs/F9YEiUf+LfIEiUbY+iEq/kowxJiqPZKO6ujp5vV6Nve07Su0W+s2NXS0OcaIAt+M10LazXuufQ9GioxOFC4tEktT/4uBbGs/UN+n3N/5YPp9PGRkJ8Ol/FnSU/eQ+EH1uet2Em/1dzX2J7Pd6vRpX9O2Q2d+VAlEifIgu4ESJNDecsfhB1VLozyFq8fEiUYs+F5+fC/pf5NOZ+ib99l+etT33uR+zk7iaDCAWQt1JdKHmj0JPKug6ch+whtdLZLSX+6GKRTiPu4cAxJtQdxJJ5+8mks697exsfXT+5ndFgYi3lgFdwx/99unM2w0+frKA9pH5QPQxT3SelbeZfVxLsYiLA+dRFALgdMl1qe3eRdRekahFr2QKRF3CCQIQGfzR7wwtH2BKoSg0Mh9AIiHzO9bkTbb8VfYdSavjbWZApHEu0TltFYla/P1Uj6j0I6EKRI3eJJ1Ns+8kgbcbwE041qPHytXkj3/TzcXduIrc6E1SSqw7AbgY84V1nc39CzOfYhGAeMP8cF5HdxFJ54pELdorFtkpoQpEACKDMI++cN9y4PNF52qCW3FhAGgfr4/wWc39C4tF/o8oiwNwNuaH1jpTJGrRUiyKdqGIN+0CCEKYx06zLy3WXQCATmO+6DpyHwDiSzdf10ooyXXW7tFprEtXY126mv6R3nHjCOAOIgCS+EPfKS48WQj3Q0wBwE7MF+ek+lLC/qr7C7XkPpkPIFEwT7TPyp1E0UaBCAAh7lCcNMQerw0gGK8J+5D5sccHVANdwxzReS13EjmtUESBCHAxQjw+tPUWBE4iAEQL80X0cCcpgHjkpnmimy9ZZ7z+iGzLaYUiCkQW8YGlSBQcx/Gv2Zcm/+nITE4A0Bbmi9hp6wIB2Q/ASZgnui7UZxPFomhEgcgiDn7EO45hAEBnMWfALXh7GRAe5gn7BBWNGqJTuqFABLgIAQ50Hq8XuBnHP9yE4hAQHuaKxEOBCHABwhuwhtcM3IzjH25BYQgID/NEZD+HyEkoEFnACwHxiOMWsIbXDNyKY9+6SH3VPaKHohDQNcwViY0CUSfxQkA84riNDk4QEgOvF7gZxz/iTdPFUkp6rHsBuAtzReKjQNQBXgSIVxy7cIumjNAnCWm+dtbh9QEE8HoAALSHeSK0RHybGQWiNvAiQDzj+AV4HQAd4TUSGdxFCiCRMVe4S0IViNq6igy4CSEeG5wgAIgnzBUAgI4wV3Qs0e4iSo51BwBEDiEOAOgIc0XkpfpSYt0FAIiYJi9zhVtRIAISBCEee5wgAHA65goAQHuYJ6zr5kucskrijARwMYIcANAR5gp7cZEAQLxjnghfN19yQhSK4n8EgMsR5M6S6kvhJAGA4zBXRAdzAIB4xTwRGfFeJIrv3gMuR5A7FycIAJyCuSL6mAMAxBPmiciK57uJEupbzAA3Icidr+UEwY5vN2vZtr+BkxAAbWOuiB075gCyH0CkMU/Y58IiUbjfdNayjeaG6BScKBABgM0uvJLc2RMFrj4D6Cr+6HcG8hyAUzFPRE+83FFEgQiIQ4R5/OJEAUA0ME8AANrDPIFQ4qOMBSCAMAcAtId5AgDQHuYJtIUCEQAAQILgj34AQHuYJ9AeCkRAHCHQAQAAAISDcwl0hAIRAABAAuAPfwBAW5gj0BkUiIA4QagDANrCHAEAaAtzBDqLAhEQBwh1AEBbmCMAAG1hjoAVFIgAAAAAAEgwFIdgFQUiwOEIdgBAW5gjAABApFAgAgAAiEMUhwAAbWGOQDjCKhAtX75cOTk58ng8ysvL0/bt29ttv27dOg0bNkwej0ejR4/Wxo0bg35/6tQpzZ49W/3791f37t01YsQIrVixIpyuAQBsQvYDgPuQ/UD8oTiEcFkuEK1du1YlJSUqLS1VZWWlxowZo8LCQtXU1IRsv3XrVk2dOlWzZs3Szp07VVRUpKKiIu3duzfQpqSkRJs2bdJ//ud/av/+/XrggQc0e/ZsbdiwIfyRAQmAcIdTkP2AszA/IBrIfiD+MD+gK5KMMcbKCnl5eRo3bpyWLVsmSfL7/RowYIDmzJmjefPmtWpfXFys+vp6vfjii4Fl11xzjXJzcwNXC0aNGqXi4mI9+uijgTZjx47V5z73OX3729/usE91dXXyer0a+uAipaR7rAwHcDQCHh3xNzTocOkC+Xw+ZWRk2PY4ZD/gLMwP7kb2ezV8NtkPhML8kJiaGxr07iL7c9/SHURNTU3asWOHCgoKzm8gOVkFBQWqqKgIuU5FRUVQe0kqLCwMaj9hwgRt2LBBx48flzFGW7Zs0cGDB3XDDTeE3GZjY6Pq6uqCfoBEQ7jDKch+wFmYHxANZD8Qf5gf0FWWCkQnTpxQc3OzMjMzg5ZnZmaqqqoq5DpVVVUdtl+6dKlGjBih/v37Ky0tTTfeeKOWL1+uiRMnhtxmWVmZvF5v4GfAgAFWhgEAsIDsBwD3IfuB+EJxCJHgiG8xW7p0qd58801t2LBBO3bs0OLFi3Xvvffq1VdfDdl+/vz58vl8gZ9jx45FuceAvQh4uAHZD1jH/IB4R/YDgHOlWmncp08fpaSkqLq6Omh5dXW1srKyQq6TlZXVbvvTp09rwYIF+u1vf6vJkydLkq666irt2rVLTz75ZKvbVCUpPT1d6enpVroOAAgT2Q8A7kP2A/GDiweIFEt3EKWlpWns2LEqLy8PLPP7/SovL1d+fn7IdfLz84PaS9LmzZsD7c+cOaMzZ84oOTm4KykpKfL7/Va6BwCwAdkPOAMnAIgmsh+ID8wNiCRLdxBJ576acsaMGbr66qs1fvx4LVmyRPX19Zo5c6Ykafr06erXr5/KysokSffff78mTZqkxYsXa/LkyVqzZo3eeustrVq1SpKUkZGhSZMmae7cuerevbsGDRqk119/XT//+c/11FNPRXCoQHwg5OFEZD8AuA/ZDwDuYrlAVFxcrNraWi1cuFBVVVXKzc3Vpk2bAh9Id/To0aCrAhMmTNDq1av1yCOPaMGCBRoyZIjWr1+vUaNGBdqsWbNG8+fP17/927/pww8/1KBBg/Sd73xH99xzTwSGCADoKrIfiC0uHiAWyH7A2ZgbEGlJxhgT6050VV1dnbxer4Y+uEgp6Z5YdwfoEoIeVvgbGnS4dIF8Pp8yMjJi3Z2oIvvhJswNuBDZ79Xw2WQ/wNzgHs0NDXp3kf2574hvMQNwDiEPAPg45gYAwMcxN8AOFIgAAAAAAIgTFIdgFwpEAAAADsVJAAAAiBYKRIBDcBIAAAAAoD2cM8BOFIgAAAAciJMAAAAQTRSIAAAAAABwOC4cwG4UiAAHIOwBAAAAALFEgQgAAMBhuHAAALgQ8wKigQIRAAAAAACAy1EgAmKMqwEAgAsxLwAALsS8gGihQAQAAAAAAOByFIgAAAAAAHAg7h5CNFEgAgAAcAhOBAAAQKxQIAJiiBMBAAAAAIATUCACAAAAAMBhuJiMaKNABAAA4ACcCAAAgFiiQAQAAAAAgINw0QCxQIEIiBFCHwAAAADgFBSIAAAAYoyLBgCAFswJiBUKRAAAAAAAAC5HgQiIAa4KAAAAAACchAIRAABADHHRAADQgjkBsUSBCAAAAAAAwOUoEAEAAAAAEGPcPYRYo0AEAAAQI5wMAAAAp6BABEQZJwMAAAAAAKehQAQAAAAAQAxxERlOQIEIAAAgBjgZAAAATkKBCAAAAAAAwOUoEAFRxNViAAAAABfiHAFOQYEIAAAgyjgZAAAATkOBCAAAAACAGOCCAZyEAhEAAAAAAIDLUSACooSrAwAAifkAAAA4EwUiAAAAAACijAsGcJqwCkTLly9XTk6OPB6P8vLytH379nbbr1u3TsOGDZPH49Ho0aO1cePGVm3279+vKVOmyOv1qmfPnho3bpyOHj0aTvcAADYg+wHAfch+AHAPywWitWvXqqSkRKWlpaqsrNSYMWNUWFiompqakO23bt2qqVOnatasWdq5c6eKiopUVFSkvXv3Btq8++67uvbaazVs2DC99tpr2r17tx599FF5PJ7wRwYAiBiyHwDch+wHAHdJMsYYKyvk5eVp3LhxWrZsmSTJ7/drwIABmjNnjubNm9eqfXFxserr6/Xiiy8Gll1zzTXKzc3VihUrJEm33367unXrpl/84hdhDaKurk5er1dDH1yklHQmFzgPt4/CLv6GBh0uXSCfz6eMjAzbHofsByKD+QCRQPZ7NXw22Y/4xnwAK5obGvTuIvtz39IdRE1NTdqxY4cKCgrObyA5WQUFBaqoqAi5TkVFRVB7SSosLAy09/v9eumllzR06FAVFhbqE5/4hPLy8rR+/XqLQwEA2IHsBwD3IfsBwH0sFYhOnDih5uZmZWZmBi3PzMxUVVVVyHWqqqrabV9TU6NTp07piSee0I033qhXXnlFN910k774xS/q9ddfD7nNxsZG1dXVBf0AAOxB9gOA+5D9AOA+qbHugN/vlyR94Qtf0De+8Q1JUm5urrZu3aoVK1Zo0qRJrdYpKyvT448/HtV+AgAih+yHG/F2Argd2Q+cw3wAp7J0B1GfPn2UkpKi6urqoOXV1dXKysoKuU5WVla77fv06aPU1FSNGDEiqM3w4cPb/DaD+fPny+fzBX6OHTtmZRhAVDEBIN6R/QDgPmQ/ALiPpQJRWlqaxo4dq/Ly8sAyv9+v8vJy5efnh1wnPz8/qL0kbd68OdA+LS1N48aN0zvvvBPU5uDBgxo0aFDIbaanpysjIyPoBwBgD7IfANyH7AcA97H8FrOSkhLNmDFDV199tcaPH68lS5aovr5eM2fOlCRNnz5d/fr1U1lZmSTp/vvv16RJk7R48WJNnjxZa9as0VtvvaVVq1YFtjl37lwVFxdr4sSJuv7667Vp0yb97ne/02uvvRaZUQIAuoTsBwD3IfuByOPdBXAyywWi4uJi1dbWauHChaqqqlJubq42bdoU+EC6o0ePKjn5/I1JEyZM0OrVq/XII49owYIFGjJkiNavX69Ro0YF2tx0001asWKFysrKdN999+nKK6/U888/r2uvvTYCQwQAdBXZD3QNJwSIR2Q/ALhLkjHGxLoTXVVXVyev16uhDy5SSron1t0BAjghgN38DQ06XLpAPp/Pdbfdk/2IJ8wHiCSy36vhs8l+xCfmA4SjuaFB7y6yP/ctfQYRAAAAAACwjuIQnI4CEQAAgI04IQAAAPGAAhEAAAAAAIDLUSACbMIVYwAAAAAS5waIDxSIAAAAAAAAXI4CEQAAgE24YgwAAOIFBSIAAAAAAGzCxQLECwpEgA2YBAAAAAAA8YQCEQAAgA24WAAAAOIJBSIAAAAAAGzAxQLEEwpEAAAAAAAALkeBCIgwrhIAAAAA4LwA8YYCEQAAQIRxUgAAAOINBSIAAAAAAACXo0AEAAAAAEAEcScp4hEFIiCCmAgAAMwFAAAgHlEgAgAAAAAAcDkKRAAAAAAAAC5HgQgAACBCeHsZAIC5APGKAhEQIUwEAAAAAIB4RYEIAAAAAIAI4KIx4hkFIgAAgAjgpAAAAMQzCkRABHBSAAAAAACIZxSIAAAAAADoIi4aI95RIAIAAOgiTgoAAEC8S6gC0ZmMWPcAABBtZD8AuE8T2Q8AEZca6w5E2sev4KX5YtMPuAdXjYHYu/B1SO4DgDuQ/XASzgmQCBLqDqJQeKECgLs0ecl+RBfHGxB7ZD8AdF3CF4gkJgsAcCOyHwDch+wHgPC5okAkMVnAHhxXgLPxGgUA9yH7EW0cc0gUrikQSbxwAcCNyH7YieMLcCZemwBgnasKRBKTBSKHYwmIH7xeAcB9yH5EA8cZEonrCkQSL2IAcCOyHwDch+wHgM5zZYFIYrIAADci+xFJHE9AfOC1CgCd49oCkcRkgfBx7ADxi9cvALgP2Q87cFwh0YRVIFq+fLlycnLk8XiUl5en7du3t9t+3bp1GjZsmDwej0aPHq2NGze22faee+5RUlKSlixZEk7XLONFDQCdQ/YD53EMwS3IfgBwD8sForVr16qkpESlpaWqrKzUmDFjVFhYqJqampDtt27dqqlTp2rWrFnauXOnioqKVFRUpL1797Zq+9vf/lZvvvmmsrOzrY8EAGAbsh8A3IfsB9pGwRGJyHKB6KmnntJdd92lmTNnasSIEVqxYoV69OihZ555JmT7H/zgB7rxxhs1d+5cDR8+XP/+7/+uT3/601q2bFlQu+PHj2vOnDn65S9/qW7duoU3mjDx4oYVHC9wI7IfANyH7AcAd7FUIGpqatKOHTtUUFBwfgPJySooKFBFRUXIdSoqKoLaS1JhYWFQe7/fr2nTpmnu3LkaOXKklS5FDJMFAIRG9gPBOG7gBmQ/0DaOISSqVCuNT5w4oebmZmVmZgYtz8zM1IEDB0KuU1VVFbJ9VVVV4N/f/e53lZqaqvvuu69T/WhsbFRjY2Pg33V1dZ0dQruavFKaLyKbAoCEQfYDgPuQ/QDgPjH/FrMdO3boBz/4gZ577jklJSV1ap2ysjJ5vd7Az4ABA2zuJXAOVwuAyCD7Ea+YB4Dwkf0A4GyWCkR9+vRRSkqKqqurg5ZXV1crKysr5DpZWVnttn/jjTdUU1OjgQMHKjU1VampqTpy5IgefPBB5eTkhNzm/Pnz5fP5Aj/Hjh2zMox28YcfAAQj+wHAfch+IDSOGyQySwWitLQ0jR07VuXl5YFlfr9f5eXlys/PD7lOfn5+UHtJ2rx5c6D9tGnTtHv3bu3atSvwk52drblz5+rll18Ouc309HRlZGQE/UQSL3qEwnEBtyL7AcB9yH4AcI60yLy7tkOWPoNIkkpKSjRjxgxdffXVGj9+vJYsWaL6+nrNnDlTkjR9+nT169dPZWVlkqT7779fkyZN0uLFizV58mStWbNGb731llatWiVJuvTSS3XppZcGPUa3bt2UlZWlK6+8sqvjAwBEANkPcCIJ9yH7gWDMA4iFNJ/UHKXHslwgKi4uVm1trRYuXKiqqirl5uZq06ZNgQ+kO3r0qJKTz9+YNGHCBK1evVqPPPKIFixYoCFDhmj9+vUaNWpU5EZhAz64DhdiMoDbkf0A4D5kPwDETixyKckYY6L/sJFVV1cnr9eryx9fpGSPJ2LbZaJACwpEcCp/Q4MOly6Qz+eL+G33Tkf2I5qYB+AUaT6pubFBBxe7O/uvWLBIKWQ/ooh5ANF2YS41NzZo/zL7cz/m32LmZIQAJI4DwG14zQNwKooY9iH7AThJrPKeAlEHmCwAwH3IflyI4wFOQHHIfrzW0RaODbgFBSKgHUwGAAAg1igOAYB7xDLzKRB1AkUCAE6U5pO6RekrL92I7IfEcQC4Da95fBzHBNyEAhHQBiYDOBlXkwH7MQ/ACch7AHCPWGc+BaJO4o9EAE4R64nDTch+AHAfsh8tOBbgNhSILCAg3IN9DaeiOBR95IE7sd/hBGR+7JABAKLNCZlPgQgAAAAAgAtQJIQbUSCyiKBIfOxjAB9HLrgL+xuARBa4GfsebkWBCLgAkwEAAHACJ7zVAADgLhSIwkARAUAscLIQW2S/O7CfAVyITHAf9jliwSl/51MgAv4PkwEAuBvzAAC4G/MA3I4CUZgIDwBwH7IfANyH7AfgFhSIADHxA4DbMQ/ASZzyVgOcR0YkPvYxQIGoSwiRxMB+RDzgZME5yIzEwz4FAHdjHgDOoUDURYRJfGP/AQgH2QEA7kP2A0h0FIgAAIBrccIHAO7GPACcR4EoAgiV+MR+A9AVZEj8Yx8CsIrcSCzsTziBkz5KggIRXInJAADcjXkAANyNeQBojQJRhBAw8YN9BSBSyJP4xH4D0BVkSPxjHwKhUSACAAAAAACIAScVLCkQRZCTdixCYx8hXnHsOhf7Jr6wvwBEAlkSv9h3QNsoEME1mAwAwN2YBxAvOFYBe/DaAtpHgSjCCB1nYr8AsBMZ43zsIwCRRq7EF/YX0DEKREh4TAYA4G7MAwDgbswDQOdQILIBAeQc7AsA0ULeOBP7BYCdyBjnYx8BnUeBCAmLyQCJhmMasIbXDOIZxy/QdbyOEC+ccqxSILKJU3awW/H8A4gFssc52BcAooW8cSb2C2AdBSIkHCYDJDKOb6BjvE4AwN2YB4DwUCCyEcEUfTzncAOOc2dj/8QWzz8SCcdz/GBfOQf7AvHKCccuBSIkDCe8oIBoafJyzAMfx2sCiYjjGug8Xi9A11AgshkhFR08z3CrMxmx7gFCIZOij+ccQKyRQ7HF849EEOvjmAIR4l6sX0QAgNhiHkCi465RoH28PpBIYnk8UyCKAgLLPjy3AJyKfIoOnme4Cce787GPoo/nHIgcCkSIW0wGAOBuzANwoyYvby8GWjAPIFHF6timQBQlhFdk8XwCiAdklX14bgE4FfkUHTzPSHSxeHtxWAWi5cuXKycnRx6PR3l5edq+fXu77detW6dhw4bJ4/Fo9OjR2rhxY+B3Z86c0cMPP6zRo0erZ8+eys7O1vTp0/X++++H0zW4AJMBEBtkP5yCeQCIHrIfTsQ8ADdp8kpNUbpz1HKBaO3atSopKVFpaakqKys1ZswYFRYWqqamJmT7rVu3aurUqZo1a5Z27typoqIiFRUVae/evZKkjz76SJWVlXr00UdVWVmp3/zmN3rnnXc0ZcqUro0MCYnJAIgNsh9OwTwARA/ZDydiHgDsk2SMMVZWyMvL07hx47Rs2TJJkt/v14ABAzRnzhzNmzevVfvi4mLV19frxRdfDCy75pprlJubqxUrVoR8jD//+c8aP368jhw5ooEDB3bYp7q6Onm9Xl3++CIlezxWhhN1ab5Y9yB+MRkArfkbGnS4dIF8Pp8yMuy7tED2dw3ZHxnMA8A5ZL9XVyxYpBSy33WYB+BWzQ0NeneR/blv6Q6ipqYm7dixQwUFBec3kJysgoICVVRUhFynoqIiqL0kFRYWttleknw+n5KSktSrV6+Qv29sbFRdXV3QDxIbkwEQO2Q/nIB5AIgush9OwzwA2M9SgejEiRNqbm5WZmZm0PLMzExVVVWFXKeqqspS+4aGBj388MOaOnVqm5WxsrIyeb3ewM+AAQOsDAMAYAHZj1jjpACIPrIfTsI8AESHo77F7MyZM7rttttkjNGPfvSjNtvNnz9fPp8v8HPs2LEo9rJrCDfreM6AxEb2A4D7kP3oLJ5HIHpSrTTu06ePUlJSVF1dHbS8urpaWVlZIdfJysrqVPuWSeLIkSP6wx/+0O776tLT05Wenm6l64hTTAhA7JH9iCXmASA2yH44AXMAEF2W7iBKS0vT2LFjVV5eHljm9/tVXl6u/Pz8kOvk5+cHtZekzZs3B7VvmSQOHTqkV199VZdeeqmVbgEAbET2I1Y4MQBih+wHAPexdAeRJJWUlGjGjBm6+uqrNX78eC1ZskT19fWaOXOmJGn69Onq16+fysrKJEn333+/Jk2apMWLF2vy5Mlas2aN3nrrLa1atUrSuUnilltuUWVlpV588UU1NzcH3qfcu3dvpaWlRWqsiDOcGADOQfYDgPuQ/YglzgWA6LNcICouLlZtba0WLlyoqqoq5ebmatOmTYEPpDt69KiSk8/fmDRhwgStXr1ajzzyiBYsWKAhQ4Zo/fr1GjVqlCTp+PHj2rBhgyQpNzc36LG2bNmi6667LsyhAQAihexHtHFiAMQe2Q8A7pJkjDGx7kRX1dXVyev16vLHFynZ44l1dzqU5ot1D5yPEwOgc/wNDTpcukA+n6/dz3BIRGR/YmMeANpG9nt1xYJFSiH7ExZzABCsuaFB7y6yP/cd9S1mAAAAAAAAiD4KRAAAwFG4cgwAABB9FIgAAAAAAABcjgIRAAAAAACAy1EgijI+qA4A3Ifst4bnC0AiIMsAxBsKRHAkJlQAAAAAAKKHAhEAAAAAAIDLUSCKIu6KsYbnC0AiIMvCw/MGIJ6RYV3D8wfEBgWiKCHkAMB9yH4AcB+yPzJ4HoHoo0AER2NiAAD3Yg4AAACIHgpEUcAfuF3D8wcgHpFdkcHzCCCekFmRxfMJRBcFIpsRapHB8wggnpBZkcXzCSAekFX24HkFoocCkY0Is8ji+QQQD8gqe/C8AnAyMgpAIqBAZBMmCXvwvAJwMjIKANyH7LcfzzEQHRSIbECA2YvnF4ATkU324zkG4DTkUvTwXAP2o0AUYQRXdPA8A3ASMil60nw83wBijyyKDZ5zwF4UiCKESSL6eL4BxBrZHzs87wBihfyJLZ5/wD4UiCKAkIodnnsAsUL+xB77AEC0kTvOwH4A7EGBqIsIp9hjHwCINnLHOdgXAKKFvHEW9gcQeRSIuoBQcg72BYBoIW+ch30CwG7kjDOxX4DIokAUBj5zwpnYJwDsRPY7G/sGgB3Ifudj/wCRQ4HIIgLI2dg/AOxAtsQH9hOASCJT4gf7CogMCkQWEDzxgf0EIJLIlPjC/gIQCWRJ/GGfAV1HgagTuLU0/rC/AHQV2R+/2G8AwkX2xzf2HdA1FIg6QMjEL/YdgHCRH/GPfQjAKnIjMbAfgfBRIGoH4RL/2IcArODKMQC4D9mfeNifQHgoEIXAJJFY2JcAOoOsSDzsUwAdIScA4DwKRB/DJJGY2K8A2kNGJC72LYC2kA+Jjf0LWEeB6P9w11DiY/8C+Diy3x3YxwAuRPa7B/sZsIYCkQgOAHAjsh8A3IfsB4C2ub5AxCThLuxvABJZ4EbscwDkgDux34HOS411B2KFoAAA9yH7AcB9yH6k+aQmb6x7ATifK+8gYpJwN/Y/4E689sExALgPr3sA6LyEuoOoW53U7Gm/DZMEACSWjrKf3AeAxJNG9gNAxCXcHURtTQZ8WwEuxLEAJJb2sh+4EMcEkDjIfljBcQF0LKwC0fLly5WTkyOPx6O8vDxt37693fbr1q3TsGHD5PF4NHr0aG3cuDHo98YYLVy4UH379lX37t1VUFCgQ4cOhdM1Sa1f/IQBAHRdPGU/FwUAIDLIfgBwD8sForVr16qkpESlpaWqrKzUmDFjVFhYqJqampDtt27dqqlTp2rWrFnauXOnioqKVFRUpL179wbafO9739MPf/hDrVixQtu2bVPPnj1VWFiohoaGsAbFB5ABQGTFW/YzDwBA15H9AOAuScYYY2WFvLw8jRs3TsuWLZMk+f1+DRgwQHPmzNG8efNatS8uLlZ9fb1efPHFwLJrrrlGubm5WrFihYwxys7O1oMPPqiHHnpIkuTz+ZSZmannnntOt99+e4d9qqurk9fr1dAHF6n5E22/GZkrCvg4/pBAvPM3NOhw6QL5fD5lZGTY9jhkPxIN+Y94RvZ7NXw22Q/ryH7Eq+aGBr27yP7ct/Qh1U1NTdqxY4fmz58fWJacnKyCggJVVFSEXKeiokIlJSVBywoLC7V+/XpJ0uHDh1VVVaWCgoLA771er/Ly8lRRURFyomhsbFRjY2Pg3z7fuRmgMa1Bye1cfGhIP/dhpkALf3gXqwDH8P/fFVeLtX5LyH4kIvIf8YzslxrS28/+0+nnPsgauFBKjdRk37k1YBt/o/25L1ksEJ04cULNzc3KzMwMWp6ZmakDBw6EXKeqqipk+6qqqsDvW5a11ebjysrK9Pjjj7dafqTsW50bCAAkmL///e/yeu25LEb2A4AzuTn7Dy8m+wG4j525L8Xp19zPnz8/6OrEyZMnNWjQIB09etTWJ8up6urqNGDAAB07dszW282civEzfjeP3+fzaeDAgerdu3esu2I7sj+Y2499xs/43Tx+sp/sd+uxz/gZv1vHH63ct1Qg6tOnj1JSUlRdXR20vLq6WllZWSHXycrKard9y3+rq6vVt2/foDa5ubkht5menq709PRWy71er+sOlAtlZGQwfsYf627EjNvHn5wc1pdSdgrZ72xuP/YZP+N38/jJfvfue7cf+4yf8bt1/HbmvmTxW8zS0tI0duxYlZeXB5b5/X6Vl5crPz8/5Dr5+flB7SVp8+bNgfaXX365srKygtrU1dVp27ZtbW4TABA9ZD8AuA/ZDwDuY/ktZiUlJZoxY4auvvpqjR8/XkuWLFF9fb1mzpwpSZo+fbr69eunsrIySdL999+vSZMmafHixZo8ebLWrFmjt956S6tWrZIkJSUl6YEHHtC3v/1tDRkyRJdffrkeffRRZWdnq6ioKHIjBQCEjewHAPch+wHAXSwXiIqLi1VbW6uFCxeqqqpKubm52rRpU+DD5o4ePRp029OECRO0evVqPfLII1qwYIGGDBmi9evXa9SoUYE23/zmN1VfX6+vfvWrOnnypK699lpt2rRJHk/bX115ofT0dJWWloa8/dQNGD/jZ/yM3+7xk/3Ow/gZP+Nn/GS/+zB+xs/43Tn+aI09ydj9PWkAAAAAAABwNHs/4QgAAAAAAACOR4EIAAAAAADA5SgQAQAAAAAAuBwFIgAAAAAAAJdzbIFo+fLlysnJkcfjUV5enrZv395u+3Xr1mnYsGHyeDwaPXq0Nm7cGPR7Y4wWLlyovn37qnv37iooKNChQ4fsHEKXRHL8Z86c0cMPP6zRo0erZ8+eys7O1vTp0/X+++/bPYywRXr/X+iee+5RUlKSlixZEuFeR4YdY9+/f7+mTJkir9ernj17aty4cTp69KhdQ+iSSI//1KlTmj17tvr376/u3btrxIgRWrFihZ1D6BIr49+3b59uvvlm5eTktHtMW31OY4nsJ/vJfrKf7Cf7yX6yvz1kP9lP9tuY/caB1qxZY9LS0swzzzxj9u3bZ+666y7Tq1cvU11dHbL9n/70J5OSkmK+973vmbfffts88sgjplu3bmbPnj2BNk888YTxer1m/fr15i9/+YuZMmWKufzyy83p06ejNaxOi/T4T548aQoKCszatWvNgQMHTEVFhRk/frwZO3ZsNIfVaXbs/xa/+c1vzJgxY0x2drZ5+umnbR6JdXaM/a9//avp3bu3mTt3rqmsrDR//etfzQsvvNDmNmPJjvHfdddd5oorrjBbtmwxhw8fNitXrjQpKSnmhRdeiNawOs3q+Ldv324eeugh86tf/cpkZWWFPKatbjOWyH6yn+wn+8l+sp/sJ/vJfrI/FLI/OtnvyALR+PHjzb333hv4d3Nzs8nOzjZlZWUh2992221m8uTJQcvy8vLM3XffbYwxxu/3m6ysLPP9738/8PuTJ0+a9PR086tf/cqGEXRNpMcfyvbt240kc+TIkch0OoLsGv/f/vY3069fP7N3714zaNAgR04Udoy9uLjY3HnnnfZ0OMLsGP/IkSPNt771raA2n/70p83/+3//L4I9jwyr479QW8d0V7YZbWQ/2U/2n0P2k/1kP9lP9pP9H0f2k/0t7Mx+x73FrKmpSTt27FBBQUFgWXJysgoKClRRURFynYqKiqD2klRYWBhof/jwYVVVVQW18Xq9ysvLa3ObsWLH+EPx+XxKSkpSr169ItLvSLFr/H6/X9OmTdPcuXM1cuRIezrfRXaM3e/366WXXtLQoUNVWFioT3ziE8rLy9P69ettG0e47Nr3EyZM0IYNG3T8+HEZY7RlyxYdPHhQN9xwgz0DCVM444/FNu1C9pP9ZD/Z34LsJ/vJfrKf7G+N7Cf7o7FNxxWITpw4oebmZmVmZgYtz8zMVFVVVch1qqqq2m3f8l8r24wVO8b/cQ0NDXr44Yc1depUZWRkRKbjEWLX+L/73e8qNTVV9913X+Q7HSF2jL2mpkanTp3SE088oRtvvFGvvPKKbrrpJn3xi1/U66+/bs9AwmTXvl+6dKlGjBih/v37Ky0tTTfeeKOWL1+uiRMnRn4QXRDO+GOxTbuQ/WQ/2U/2X4jsJ/vJfrI/FLKf7G+vPdnf9W2mhvXoiFtnzpzRbbfdJmOMfvSjH8W6O1GxY8cO/eAHP1BlZaWSkpJi3Z2o8vv9kqQvfOEL+sY3viFJys3N1datW7VixQpNmjQplt2LiqVLl+rNN9/Uhg0bNGjQIP3xj3/Uvffeq+zs7FZXIYBERfaT/WQ/2Q/3IfvJfrKf7LfKcXcQ9enTRykpKaqurg5aXl1draysrJDrZGVltdu+5b9Wthkrdoy/RcskceTIEW3evNlxVxEke8b/xhtvqKamRgMHDlRqaqpSU1N15MgRPfjgg8rJybFlHOGwY+x9+vRRamqqRowYEdRm+PDhjvs2AzvGf/r0aS1YsEBPPfWUPv/5z+uqq67S7NmzVVxcrCeffNKegYQpnPHHYpt2IfvJfrKf7L8Q2U/2k/1kfyhkP9nfVnuyPzLbdFyBKC0tTWPHjlV5eXlgmd/vV3l5ufLz80Ouk5+fH9RekjZv3hxof/nllysrKyuoTV1dnbZt29bmNmPFjvFL5yeJQ4cO6dVXX9Wll15qzwC6yI7xT5s2Tbt379auXbsCP9nZ2Zo7d65efvll+wZjkR1jT0tL07hx4/TOO+8EtTl48KAGDRoU4RF0jR3jP3PmjM6cOaPk5OCoS0lJCVxlcYpwxh+LbdqF7Cf7yX6yvwXZT/aT/WQ/2d8a2U/2R2Wbnf446yhas2aNSU9PN88995x5++23zVe/+lXTq1cvU1VVZYwxZtq0aWbevHmB9n/6059MamqqefLJJ83+/ftNaWlpyK+77NWrl3nhhRfM7t27zRe+8AVHf91lJMff1NRkpkyZYvr372927dplPvjgg8BPY2NjTMbYHjv2/8c59dsM7Bj7b37zG9OtWzezatUqc+jQIbN06VKTkpJi3njjjaiPryN2jH/SpElm5MiRZsuWLeZ//ud/zLPPPms8Ho/5j//4j6iPryNWx9/Y2Gh27txpdu7cafr27Wseeughs3PnTnPo0KFOb9NJyH6yn+wn+8l+sp/sJ/vJfrLfGLI/VtnvyAKRMcYsXbrUDBw40KSlpZnx48ebN998M/C7SZMmmRkzZgS1//Wvf22GDh1q0tLSzMiRI81LL70U9Hu/328effRRk5mZadLT081nP/tZ884770RjKGGJ5PgPHz5sJIX82bJlS5RGZE2k9//HOXWiMMaesf/0pz81n/zkJ43H4zFjxowx69evt3sYYYv0+D/44APzpS99yWRnZxuPx2OuvPJKs3jxYuP3+6MxHMusjL+t1/akSZM6vU2nIfvJfrKf7Cf7yX6yn+xvQfbPCGpP9pP9dmd/kjHGWL+BCQAAAAAAAInCcZ9BBAAAAAAAgOiiQAQAAAAAAOByFIgAAAAAAABcjgIRAAAAAACAy1EgAgAAAAAAcDkKRAAAAAAAAC5HgQgAAAAAAMDlKBABAAAAAAC4HAUiAAAAAAAAl6NABAAAAAAA4HIUiAAAAAAAAFyOAhEAAAAAAIDL/X9PH7cYOnE8RQAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(1, 3, figsize=(14, 3))\n", + "for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots['mag(v)'][:3]):\n", + " ax.tricontourf(dataset.triang, u, levels=16)\n", + " ax.set_title(f'$u$ field for $\\mu$ = {par[0]:.4f}')\n", + "fig, axs = plt.subplots(1, 3, figsize=(14, 3))\n", + "for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots['p'][:3]):\n", + " ax.tricontourf(dataset.triang, u, levels=16)\n", + " ax.set_title(f'$p$ field for $\\mu$ = {par[0]:.4f}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To train the model we only need the snapshots for the two parameters. In order to be able to work with the snapshots in **PINA** we first need to assure they're in a compatible format, hence why we start by casting them into `LabelTensor` objects:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "'''velocity magnitude data, 5041 for each snapshot'''\n", + "u=torch.tensor(dataset.snapshots['mag(v)']).float() \n", + "u = LabelTensor(u, labels=[f's{i}' for i in range(u.shape[1])])\n", + "'''pressure data, 5041 for each snapshot'''\n", + "p=torch.tensor(dataset.snapshots['p']).float()\n", + "p = LabelTensor(p, labels=[f's{i}' for i in range(p.shape[1])])\n", + "'''mu corresponding to each snapshot'''\n", + "mu=torch.tensor(dataset.params).float()\n", + "mu = LabelTensor(mu, labels=['mu'])\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The goal of our training is to be able to predict the solution for new test parameters. The first thing we need to do is validate the accuracy of the model, and in order to do so we split the 300 snapshots in training and testing dataset. In the example we set the training `ratio` to 0.9, which means that 90% of the total snapshots is used for training and the remaining 10% for testing." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "'''number of snapshots'''\n", + "n = u.shape[0]\n", + "'''training over total snapshots ratio and number of training snapshots'''\n", + "ratio = 0.9 \n", + "n_train = int(n*ratio)\n", + "'''split u and p data'''\n", + "u_train, u_test = u[:n_train], u[n_train:] #for mag(v)\n", + "p_train, p_test = p[:n_train], p[n_train:] #for p\n", + "'''split snapshots'''\n", + "mu_train, mu_test = mu[:n_train], mu[n_train:]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now proceed by defining the model we intend to use. We inherit from the `torch.nn.Module` class, but in addition we require a `pod_rank` for the POD part and a function `rbf_kernel` in order to perform the RBF part:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "class PODRBF(torch.nn.Module):\n", + " \"\"\"\n", + " Proper orthogonal decomposition with Radial Basis Function interpolation model.\n", + " \"\"\"\n", + " def __init__(self, pod_rank, rbf_kernel):\n", + " \n", + " super().__init__()\n", + " self.pod = PODBlock(pod_rank)\n", + " self.rbf = RBFBlock(kernel=rbf_kernel)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We complete our model by adding two crucial methods. The first is `forward`, and it expands the input POD coefficients. After being expanded the POD layer needs to be fit, hence why we add a `fit` method that gives us the POD basis (current **PINA** default is by performing truncated Singular Value Decomposition). The same method then uses the basis to fit the RBF interpolation. Overall, the completed class looks like this:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "class PODRBF(torch.nn.Module):\n", + " \"\"\"\n", + " Proper orthogonal decomposition with Radial Basis Function interpolation model.\n", + " \"\"\"\n", + " def __init__(self, pod_rank, rbf_kernel):\n", + " \n", + " super().__init__()\n", + " self.pod = PODBlock(pod_rank)\n", + " self.rbf = RBFBlock(kernel=rbf_kernel)\n", + "\n", + " def forward(self, x):\n", + " \"\"\"\n", + " Defines the computation performed at every call.\n", + " :param x: The tensor to apply the forward pass.\n", + " :type x: torch.Tensor\n", + " :return: the output computed by the model.\n", + " :rtype: torch.Tensor\n", + " \"\"\"\n", + " coefficients = self.rbf(x)\n", + " return self.pod.expand(coefficients)\n", + " def fit(self, p, x):\n", + " \"\"\"\n", + " Call the :meth:`pina.model.layers.PODBlock.fit` method of the\n", + " :attr:`pina.model.layers.PODBlock` attribute to perform the POD,\n", + " and the :meth:`pina.model.layers.RBFBlock.fit` method of the\n", + " :attr:`pina.model.layers.RBFBlock` attribute to fit the interpolation.\n", + " \"\"\"\n", + " self.pod.fit(x)\n", + " self.rbf.fit(p, self.pod.reduce(x))\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that we've built our class, we can fit the model and ask it to predict the parameters for the remaining snapshots. We remember that we don't need to train the model, as it doesn't involve any learnable parameter. The only things we have to set are the rank of the decomposition and the radial basis function (here we use thin plate). Here we focus on predicting the magnitude of velocity:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'PODBlock' object has no attribute 'scaler'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 5\u001b[0m\n\u001b[1;32m 2\u001b[0m pod_rbfu \u001b[38;5;241m=\u001b[39m PODRBF(pod_rank\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m, rbf_kernel\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mthin_plate_spline\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 4\u001b[0m \u001b[38;5;124;03m'''fit the model to velocity training data'''\u001b[39;00m\n\u001b[0;32m----> 5\u001b[0m \u001b[43mpod_rbfu\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmu_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mu_train\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;124;03m'''predict the parameter using the fitted model'''\u001b[39;00m\n\u001b[1;32m 8\u001b[0m u_train_rbf \u001b[38;5;241m=\u001b[39m pod_rbfu(mu_train)\n", + "Cell \u001b[0;32mIn[7], line 29\u001b[0m, in \u001b[0;36mPODRBF.fit\u001b[0;34m(self, p, x)\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 23\u001b[0m \u001b[38;5;124;03mCall the :meth:`pina.model.layers.PODBlock.fit` method of the\u001b[39;00m\n\u001b[1;32m 24\u001b[0m \u001b[38;5;124;03m:attr:`pina.model.layers.PODBlock` attribute to perform the POD,\u001b[39;00m\n\u001b[1;32m 25\u001b[0m \u001b[38;5;124;03mand the :meth:`pina.model.layers.RBFBlock.fit` method of the\u001b[39;00m\n\u001b[1;32m 26\u001b[0m \u001b[38;5;124;03m:attr:`pina.model.layers.RBFBlock` attribute to fit the interpolation.\u001b[39;00m\n\u001b[1;32m 27\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 28\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpod\u001b[38;5;241m.\u001b[39mfit(x)\n\u001b[0;32m---> 29\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrbf\u001b[38;5;241m.\u001b[39mfit(p, \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpod\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreduce\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m)\n", + "File \u001b[0;32m~/PINA/pina/model/layers/pod.py:158\u001b[0m, in \u001b[0;36mPODBlock.reduce\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m 156\u001b[0m coeff \u001b[38;5;241m=\u001b[39m coeff\u001b[38;5;241m.\u001b[39mT\n\u001b[1;32m 157\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__scale_coefficients:\n\u001b[0;32m--> 158\u001b[0m coeff \u001b[38;5;241m=\u001b[39m (coeff \u001b[38;5;241m-\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscaler\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmean\u001b[39m\u001b[38;5;124m\"\u001b[39m]) \u001b[38;5;241m/\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mscaler[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstd\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 160\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m coeff\n", + "File \u001b[0;32m~/.local/lib/python3.12/site-packages/torch/nn/modules/module.py:1931\u001b[0m, in \u001b[0;36mModule.__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 1929\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m modules:\n\u001b[1;32m 1930\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m modules[name]\n\u001b[0;32m-> 1931\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\n\u001b[1;32m 1932\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m object has no attribute \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1933\u001b[0m )\n", + "\u001b[0;31mAttributeError\u001b[0m: 'PODBlock' object has no attribute 'scaler'" + ] + } + ], + "source": [ + "'''create the model'''\n", + "pod_rbfu = PODRBF(pod_rank=20, rbf_kernel='thin_plate_spline')\n", + "\n", + "'''fit the model to velocity training data'''\n", + "pod_rbfu.fit(mu_train, u_train)\n", + "\n", + "'''predict the parameter using the fitted model'''\n", + "u_train_rbf = pod_rbfu(mu_train)\n", + "u_test_rbf = pod_rbfu(mu_test)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally we can calculate the relative error for our model:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Error summary for POD-RBF model:\n", + " Train: 5.046389e-04\n", + " Test: 5.203592e-02\n" + ] + } + ], + "source": [ + "relative_u_error_train = torch.norm(u_train_rbf - u_train)/torch.norm(u_train)\n", + "relative_u_error_test = torch.norm(u_test_rbf - u_test)/torch.norm(u_test)\n", + "\n", + "print('Error summary for POD-RBF model:')\n", + "print(f' Train: {relative_u_error_train.item():e}')\n", + "print(f' Test: {relative_u_error_test.item():e}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The results are promising! Now let's visualise them, comparing four random predicted snapshots to the true ones:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:14: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:15: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:16: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:14: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:15: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:16: SyntaxWarning: invalid escape sequence '\\m'\n", + "/tmp/ipykernel_72919/1955650770.py:14: SyntaxWarning: invalid escape sequence '\\m'\n", + " axs[0, i].set_title('Prediction for ' f'$\\mu$ = {mu_test[idx_].item():.4f}')\n", + "/tmp/ipykernel_72919/1955650770.py:15: SyntaxWarning: invalid escape sequence '\\m'\n", + " axs[1, i].set_title('True snapshot for ' f'$\\mu$ = {mu_test[idx_].item():.4f}')\n", + "/tmp/ipykernel_72919/1955650770.py:16: SyntaxWarning: invalid escape sequence '\\m'\n", + " axs[2, i].set_title('Error for ' f'$\\mu$ = {mu_test[idx_].item():.4f}')\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "\n", + "idx = torch.randint(0, len(u_test), (4,))\n", + "u_idx_rbf = pod_rbfu(mu_test[idx])\n", + "fig, axs = plt.subplots(3, 4, figsize=(14, 10))\n", + "\n", + "relative_u_error_rbf = np.abs(u_test[idx] - u_idx_rbf.detach())\n", + "relative_u_error_rbf = np.where(u_test[idx] < 1e-7, 1e-7, relative_u_error_rbf/u_test[idx])\n", + " \n", + "for i, (idx_, rbf_, rbf_err_) in enumerate(\n", + " zip(idx, u_idx_rbf, relative_u_error_rbf)):\n", + " axs[0, i].set_title('Prediction for ' f'$\\mu$ = {mu_test[idx_].item():.4f}')\n", + " axs[1, i].set_title('True snapshot for ' f'$\\mu$ = {mu_test[idx_].item():.4f}')\n", + " axs[2, i].set_title('Error for ' f'$\\mu$ = {mu_test[idx_].item():.4f}')\n", + "\n", + " cm = axs[0, i].tricontourf(dataset.triang, rbf_.detach()) # POD-RBF prediction\n", + " plt.colorbar(cm, ax=axs[0, i])\n", + " \n", + " cm = axs[1, i].tricontourf(dataset.triang, u_test[idx_].flatten()) # Truth\n", + " plt.colorbar(cm, ax=axs[1, i])\n", + "\n", + " cm = axs[2, i].tripcolor(dataset.triang, rbf_err_, norm=matplotlib.colors.LogNorm()) # Error for POD-RBF\n", + " plt.colorbar(cm, ax=axs[2, i])\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Overall we have reached a good level of approximation while avoiding time-consuming training procedures. Let's try doing the same to predict the pressure snapshots:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Error summary for POD-RBF model:\n", + " Train: 5.159679e-02\n", + " Test: 2.299810e+06\n" + ] + } + ], + "source": [ + "'''create the model'''\n", + "pod_rbfp = PODRBF(pod_rank=20, rbf_kernel='thin_plate_spline')\n", + "\n", + "'''fit the model to pressure training data'''\n", + "pod_rbfp.fit(mu_train, p_train)\n", + "\n", + "'''predict the parameter using the fitted model'''\n", + "p_train_rbf = pod_rbfp(mu_train)\n", + "p_test_rbf = pod_rbfp(mu_test)\n", + "\n", + "relative_p_error_train = torch.norm(p_train_rbf - p_train)/torch.norm(p_train)\n", + "relative_p_error_test = torch.norm(p_test_rbf - p_test)/torch.norm(p_test)\n", + "\n", + "print('Error summary for POD-RBF model:')\n", + "print(f' Train: {relative_p_error_train.item():e}')\n", + "print(f' Test: {relative_p_error_test.item():e}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Unfortunately here we obtain a very high relative test error, although this is likely due to the nature of the available data. Looking at the plots we can see that the pressure field is subject to high variations between subsequent snapshots, especially here: " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:5: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:5: SyntaxWarning: invalid escape sequence '\\m'\n", + "/tmp/ipykernel_72919/772579621.py:5: SyntaxWarning: invalid escape sequence '\\m'\n", + " ax.set_title(f'$p$ field for $\\mu$ = {par[0]:.4f}')\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(2, 3, figsize=(14, 6))\n", + "for ax, par, u in zip(axs.ravel(), dataset.params[66:72], dataset.snapshots['p'][66:72]):\n", + " cm = ax.tricontourf(dataset.triang, u, levels=16)\n", + " plt.colorbar(cm, ax=ax)\n", + " ax.set_title(f'$p$ field for $\\mu$ = {par[0]:.4f}')\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Or here:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:5: SyntaxWarning: invalid escape sequence '\\m'\n", + "<>:5: SyntaxWarning: invalid escape sequence '\\m'\n", + "/tmp/ipykernel_72919/651675647.py:5: SyntaxWarning: invalid escape sequence '\\m'\n", + " ax.set_title(f'$p$ field for $\\mu$ = {par[0]:.4f}')\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(2, 3, figsize=(14, 6))\n", + "for ax, par, u in zip(axs.ravel(), dataset.params[98:104], dataset.snapshots['p'][98:104]):\n", + " cm = ax.tricontourf(dataset.triang, u, levels=16)\n", + " plt.colorbar(cm, ax=ax)\n", + " ax.set_title(f'$p$ field for $\\mu$ = {par[0]:.4f}')\n", + "plt.tight_layout() \n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Scrolling through the velocity snapshots we can observe a more regular behaviour, with no such variations in subsequent snapshots. Moreover, if we decide not to consider the abovementioned \"problematic\" snapshots, we can already observe a huge improvement:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Error summary for POD-RBF model:\n", + " Train: 3.610590e-02\n", + " Test: 1.616627e-01\n" + ] + } + ], + "source": [ + "'''excluding problematic snapshots'''\n", + "data = list(range(300))\n", + "data_to_consider = data[:67] + data[71:100] + data[102:]\n", + "'''proceed as before'''\n", + "newp=torch.tensor(dataset.snapshots['p'][data_to_consider]).float()\n", + "newp = LabelTensor(newp, labels=[f's{i}' for i in range(newp.shape[1])])\n", + "\n", + "newmu=torch.tensor(dataset.params[data_to_consider]).float()\n", + "newmu = LabelTensor(newmu, labels=['mu'])\n", + "\n", + "newn = newp.shape[0]\n", + "ratio = 0.9 \n", + "new_train = int(newn*ratio)\n", + "\n", + "new_p_train, new_p_test = newp[:new_train], newp[new_train:] \n", + "\n", + "new_mu_train, new_mu_test = newmu[:new_train], newmu[new_train:]\n", + "\n", + "new_pod_rbfp = PODRBF(pod_rank=20, rbf_kernel='thin_plate_spline')\n", + "\n", + "new_pod_rbfp.fit(new_mu_train, new_p_train)\n", + "\n", + "new_p_train_rbf = new_pod_rbfp(new_mu_train)\n", + "new_p_test_rbf = new_pod_rbfp(new_mu_test)\n", + "\n", + "new_relative_p_error_train = torch.norm(new_p_train_rbf - new_p_train)/torch.norm(new_p_train)\n", + "new_relative_p_error_test = torch.norm(new_p_test_rbf - new_p_test)/torch.norm(new_p_test)\n", + "\n", + "print('Error summary for POD-RBF model:')\n", + "print(f' Train: {new_relative_p_error_train.item():e}')\n", + "print(f' Test: {new_relative_p_error_test.item():e}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## What's next?\n", + "\n", + "Congratulations on completing the **PINA** tutorial on building and using a custom POD class! Now you can try:\n", + "\n", + "1. Varying the inputs of the model (for a list of the supported RB functions look at the `rbf_layer.py` file in `pina.layers`)\n", + "\n", + "2. Changing the POD model, for example using Artificial Neural Networks. For a more in depth overview of POD-NN and a comparison with the POD-RBF model already shown, look at [Tutorial: Reduced order model (POD-RBF or POD-NN) for parametric problems](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb)\n", + "\n", + "3. Building your own classes or adapt the one shown to other datasets/problems" + ] + } + ], + "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": 2 +} diff --git a/tutorials/tutorial14/tutorial.py b/tutorials/tutorial14/tutorial.py new file mode 100644 index 0000000..81847f6 --- /dev/null +++ b/tutorials/tutorial14/tutorial.py @@ -0,0 +1,311 @@ +#!/usr/bin/env python +# coding: utf-8 + +# # Tutorial: Predicting Lid-driven cavity problem parameters with POD-RBF +# +# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial14/tutorial.ipynb) + +# In this tutorial we will show how to use the **PINA** library to predict the distributions of velocity and pressure the Lid-driven Cavity problem, a benchmark in Computational Fluid Dynamics. The problem consists of a square cavity with a lid on top moving with tangential velocity (by convention to the right), with the addition of no-slip conditions on the walls of the cavity and null static pressure on the lower left angle. +# +# Our goal is to predict the distributions of velocity and pressure of the fluid inside the cavity as the Reynolds number of the inlet fluid varies. To do so we're using a Reduced Order Model (ROM) based on Proper Orthogonal Decomposition (POD). The parametric solution manifold is approximated here with Radial Basis Function (RBF) Interpolation, a common mesh-free interpolation method that doesn't require trainers or solvers as the found radial basis functions are used to interpolate new points. + +# Let's start with the necessary imports. We're particularly interested in the `PODBlock` and `RBFBlock` classes which will allow us to define the POD-RBF model. + +# In[1]: + + +## routine needed to run the notebook on Google Colab +try: + import google.colab + IN_COLAB = True +except: + IN_COLAB = False +if IN_COLAB: + get_ipython().system('pip install "pina-mathlab"') + +get_ipython().run_line_magic('matplotlib', 'inline') + +import matplotlib.pyplot as plt +plt.style.use('tableau-colorblind10') +import torch +import pina +from pina.model.layers import PODBlock, RBFBlock +from pina import LabelTensor + + +# In this tutorial we're gonna use the `LidCavity` class from the [Smithers](https://github.com/mathLab/Smithers) library, which contains a set of parametric solutions of the Lid-driven cavity problem in a square domain. The dataset consists of 300 snapshots of the parameter fields, which in this case are the magnitude of velocity and the pressure, and the corresponding parameter values $u$ and $p$. Each snapshot corresponds to a different value of the tangential velocity $\mu$ of the lid, which has been sampled uniformly between 0.01 m/s and 1 m/s. +# +# Let's start by importing the dataset: + +# In[2]: + + +get_ipython().system('pip install git+https://github.com/mathLab/Smithers.git #if required --break-system-packages') +import smithers +from smithers.dataset import LidCavity +dataset = LidCavity() + + +# Let's plot two the data points and the corresponding solution for both parameters at different snapshots, in order to better visualise the data we're using: + +# In[3]: + + +fig, axs = plt.subplots(1, 3, figsize=(14, 3)) +for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots['mag(v)'][:3]): + ax.tricontourf(dataset.triang, u, levels=16) + ax.set_title(f'$u$ field for $\mu$ = {par[0]:.4f}') +fig, axs = plt.subplots(1, 3, figsize=(14, 3)) +for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots['p'][:3]): + ax.tricontourf(dataset.triang, u, levels=16) + ax.set_title(f'$p$ field for $\mu$ = {par[0]:.4f}') + + +# To train the model we only need the snapshots for the two parameters. In order to be able to work with the snapshots in **PINA** we first need to assure they're in a compatible format, hence why we start by casting them into `LabelTensor` objects: + +# In[4]: + + +'''velocity magnitude data, 5041 for each snapshot''' +u=torch.tensor(dataset.snapshots['mag(v)']).float() +u = LabelTensor(u, labels=[f's{i}' for i in range(u.shape[1])]) +'''pressure data, 5041 for each snapshot''' +p=torch.tensor(dataset.snapshots['p']).float() +p = LabelTensor(p, labels=[f's{i}' for i in range(p.shape[1])]) +'''mu corresponding to each snapshot''' +mu=torch.tensor(dataset.params).float() +mu = LabelTensor(mu, labels=['mu']) + + +# The goal of our training is to be able to predict the solution for new test parameters. The first thing we need to do is validate the accuracy of the model, and in order to do so we split the 300 snapshots in training and testing dataset. In the example we set the training `ratio` to 0.9, which means that 90% of the total snapshots is used for training and the remaining 10% for testing. + +# In[5]: + + +'''number of snapshots''' +n = u.shape[0] +'''training over total snapshots ratio and number of training snapshots''' +ratio = 0.9 +n_train = int(n*ratio) +'''split u and p data''' +u_train, u_test = u[:n_train], u[n_train:] #for mag(v) +p_train, p_test = p[:n_train], p[n_train:] #for p +'''split snapshots''' +mu_train, mu_test = mu[:n_train], mu[n_train:] + + +# We now proceed by defining the model we intend to use. We inherit from the `torch.nn.Module` class, but in addition we require a `pod_rank` for the POD part and a function `rbf_kernel` in order to perform the RBF part: + +# In[6]: + + +class PODRBF(torch.nn.Module): + """ + Proper orthogonal decomposition with Radial Basis Function interpolation model. + """ + def __init__(self, pod_rank, rbf_kernel): + + super().__init__() + self.pod = PODBlock(pod_rank) + self.rbf = RBFBlock(kernel=rbf_kernel) + + +# We complete our model by adding two crucial methods. The first is `forward`, and it expands the input POD coefficients. After being expanded the POD layer needs to be fit, hence why we add a `fit` method that gives us the POD basis (current **PINA** default is by performing truncated Singular Value Decomposition). The same method then uses the basis to fit the RBF interpolation. Overall, the completed class looks like this: + +# In[7]: + + +class PODRBF(torch.nn.Module): + """ + Proper orthogonal decomposition with Radial Basis Function interpolation model. + """ + def __init__(self, pod_rank, rbf_kernel): + + super().__init__() + self.pod = PODBlock(pod_rank) + self.rbf = RBFBlock(kernel=rbf_kernel) + + def forward(self, x): + """ + Defines the computation performed at every call. + :param x: The tensor to apply the forward pass. + :type x: torch.Tensor + :return: the output computed by the model. + :rtype: torch.Tensor + """ + coefficients = self.rbf(x) + return self.pod.expand(coefficients) + def fit(self, p, x): + """ + Call the :meth:`pina.model.layers.PODBlock.fit` method of the + :attr:`pina.model.layers.PODBlock` attribute to perform the POD, + and the :meth:`pina.model.layers.RBFBlock.fit` method of the + :attr:`pina.model.layers.RBFBlock` attribute to fit the interpolation. + """ + self.pod.fit(x) + self.rbf.fit(p, self.pod.reduce(x)) + + + +# Now that we've built our class, we can fit the model and ask it to predict the parameters for the remaining snapshots. We remember that we don't need to train the model, as it doesn't involve any learnable parameter. The only things we have to set are the rank of the decomposition and the radial basis function (here we use thin plate). Here we focus on predicting the magnitude of velocity: + +# In[8]: + + +'''create the model''' +pod_rbfu = PODRBF(pod_rank=20, rbf_kernel='thin_plate_spline') + +'''fit the model to velocity training data''' +pod_rbfu.fit(mu_train, u_train) + +'''predict the parameter using the fitted model''' +u_train_rbf = pod_rbfu(mu_train) +u_test_rbf = pod_rbfu(mu_test) + + +# Finally we can calculate the relative error for our model: + +# In[ ]: + + +relative_u_error_train = torch.norm(u_train_rbf - u_train)/torch.norm(u_train) +relative_u_error_test = torch.norm(u_test_rbf - u_test)/torch.norm(u_test) + +print('Error summary for POD-RBF model:') +print(f' Train: {relative_u_error_train.item():e}') +print(f' Test: {relative_u_error_test.item():e}') + + +# The results are promising! Now let's visualise them, comparing four random predicted snapshots to the true ones: + +# In[ ]: + + +import numpy as np +import matplotlib +import matplotlib.pyplot as plt + +idx = torch.randint(0, len(u_test), (4,)) +u_idx_rbf = pod_rbfu(mu_test[idx]) +fig, axs = plt.subplots(3, 4, figsize=(14, 10)) + +relative_u_error_rbf = np.abs(u_test[idx] - u_idx_rbf.detach()) +relative_u_error_rbf = np.where(u_test[idx] < 1e-7, 1e-7, relative_u_error_rbf/u_test[idx]) + +for i, (idx_, rbf_, rbf_err_) in enumerate( + zip(idx, u_idx_rbf, relative_u_error_rbf)): + axs[0, i].set_title('Prediction for ' f'$\mu$ = {mu_test[idx_].item():.4f}') + axs[1, i].set_title('True snapshot for ' f'$\mu$ = {mu_test[idx_].item():.4f}') + axs[2, i].set_title('Error for ' f'$\mu$ = {mu_test[idx_].item():.4f}') + + cm = axs[0, i].tricontourf(dataset.triang, rbf_.detach()) # POD-RBF prediction + plt.colorbar(cm, ax=axs[0, i]) + + cm = axs[1, i].tricontourf(dataset.triang, u_test[idx_].flatten()) # Truth + plt.colorbar(cm, ax=axs[1, i]) + + cm = axs[2, i].tripcolor(dataset.triang, rbf_err_, norm=matplotlib.colors.LogNorm()) # Error for POD-RBF + plt.colorbar(cm, ax=axs[2, i]) + +plt.show() + + +# Overall we have reached a good level of approximation while avoiding time-consuming training procedures. Let's try doing the same to predict the pressure snapshots: + +# In[ ]: + + +'''create the model''' +pod_rbfp = PODRBF(pod_rank=20, rbf_kernel='thin_plate_spline') + +'''fit the model to pressure training data''' +pod_rbfp.fit(mu_train, p_train) + +'''predict the parameter using the fitted model''' +p_train_rbf = pod_rbfp(mu_train) +p_test_rbf = pod_rbfp(mu_test) + +relative_p_error_train = torch.norm(p_train_rbf - p_train)/torch.norm(p_train) +relative_p_error_test = torch.norm(p_test_rbf - p_test)/torch.norm(p_test) + +print('Error summary for POD-RBF model:') +print(f' Train: {relative_p_error_train.item():e}') +print(f' Test: {relative_p_error_test.item():e}') + + +# Unfortunately here we obtain a very high relative test error, although this is likely due to the nature of the available data. Looking at the plots we can see that the pressure field is subject to high variations between subsequent snapshots, especially here: + +# In[ ]: + + +fig, axs = plt.subplots(2, 3, figsize=(14, 6)) +for ax, par, u in zip(axs.ravel(), dataset.params[66:72], dataset.snapshots['p'][66:72]): + cm = ax.tricontourf(dataset.triang, u, levels=16) + plt.colorbar(cm, ax=ax) + ax.set_title(f'$p$ field for $\mu$ = {par[0]:.4f}') +plt.tight_layout() +plt.show() + + + +# Or here: + +# In[ ]: + + +fig, axs = plt.subplots(2, 3, figsize=(14, 6)) +for ax, par, u in zip(axs.ravel(), dataset.params[98:104], dataset.snapshots['p'][98:104]): + cm = ax.tricontourf(dataset.triang, u, levels=16) + plt.colorbar(cm, ax=ax) + ax.set_title(f'$p$ field for $\mu$ = {par[0]:.4f}') +plt.tight_layout() +plt.show() + + +# Scrolling through the velocity snapshots we can observe a more regular behaviour, with no such variations in subsequent snapshots. Moreover, if we decide not to consider the abovementioned "problematic" snapshots, we can already observe a huge improvement: + +# In[ ]: + + +'''excluding problematic snapshots''' +data = list(range(300)) +data_to_consider = data[:67] + data[71:100] + data[102:] +'''proceed as before''' +newp=torch.tensor(dataset.snapshots['p'][data_to_consider]).float() +newp = LabelTensor(newp, labels=[f's{i}' for i in range(newp.shape[1])]) + +newmu=torch.tensor(dataset.params[data_to_consider]).float() +newmu = LabelTensor(newmu, labels=['mu']) + +newn = newp.shape[0] +ratio = 0.9 +new_train = int(newn*ratio) + +new_p_train, new_p_test = newp[:new_train], newp[new_train:] + +new_mu_train, new_mu_test = newmu[:new_train], newmu[new_train:] + +new_pod_rbfp = PODRBF(pod_rank=20, rbf_kernel='thin_plate_spline') + +new_pod_rbfp.fit(new_mu_train, new_p_train) + +new_p_train_rbf = new_pod_rbfp(new_mu_train) +new_p_test_rbf = new_pod_rbfp(new_mu_test) + +new_relative_p_error_train = torch.norm(new_p_train_rbf - new_p_train)/torch.norm(new_p_train) +new_relative_p_error_test = torch.norm(new_p_test_rbf - new_p_test)/torch.norm(new_p_test) + +print('Error summary for POD-RBF model:') +print(f' Train: {new_relative_p_error_train.item():e}') +print(f' Test: {new_relative_p_error_test.item():e}') + + +# ## What's next? +# +# Congratulations on completing the **PINA** tutorial on building and using a custom POD class! Now you can try: +# +# 1. Varying the inputs of the model (for a list of the supported RB functions look at the `rbf_layer.py` file in `pina.layers`) +# +# 2. Changing the POD model, for example using Artificial Neural Networks. For a more in depth overview of POD-NN and a comparison with the POD-RBF model already shown, look at [Tutorial: Reduced order model (POD-RBF or POD-NN) for parametric problems](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb) +# +# 3. Building your own classes or adapt the one shown to other datasets/problems