diff --git a/mkdocs.yml b/mkdocs.yml index 40fe713b..1e636f1a 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -176,9 +176,9 @@ nav: - Learning Operators: - Introduction: operators/index.md - Examples: - - Intro: examples/intro.ipynb - - Sine: examples/sine.ipynb + - Basics: examples/basics.ipynb - Physics-informed: examples/physicsinformed.ipynb + - Self-supervised: examples/selfsupervised.ipynb - Code: - API: api/continuity/ - Changelog: CHANGELOG.md diff --git a/notebooks/basics.ipynb b/notebooks/basics.ipynb new file mode 100644 index 00000000..97b7080e --- /dev/null +++ b/notebooks/basics.ipynb @@ -0,0 +1,318 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Basics\n", + "\n", + "This example demonstrates the basics of neural operators in Continuity,\n", + "including how to train it on a given operator." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "import matplotlib.pyplot as plt\n", + "from continuity.operators import DeepONet" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "hide" + ] + }, + "outputs": [], + "source": [ + "torch.manual_seed(0)\n", + "plt.rcParams[\"axes.facecolor\"] = (1, 1, 1, 0)\n", + "plt.rcParams[\"figure.facecolor\"] = (1, 1, 1, 0)\n", + "plt.rcParams[\"legend.framealpha\"] = 0.0\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Problem\n", + "\n", + "Let's assume we want to learn the derivative operator $G: u \\mapsto \\partial_x u$.\n", + "We choose (as an example) the function $u$ that maps to its derivative $v$\n", + "$$\n", + "u(x) = \\sin(x) \\to \\cos(y) = v(y)\n", + "$$\n", + "on the interval $[-\\pi, \\pi]$.\n", + "\n", + "Let's start with defining and plotting input and target function!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "invertible-output" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Input function (some example)\n", + "u = lambda x: torch.sin(x)\n", + "\n", + "# Target function (the derivative of u)\n", + "v = lambda y: torch.cos(y)\n", + "\n", + "# Plot input and target function\n", + "L = torch.pi\n", + "x = torch.linspace(-L, L, 1000)\n", + "plt.plot(x, u(x), \"g-\", label=\"Input $u$\")\n", + "plt.plot(x, v(x), \"k-\", label=\"Target $v$\")\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Operator\n", + "\n", + "In order to approximate the operator $G$ from above with a neural network,\n", + "we set up a neural operator.\n", + "A neural operator takes an input function $u$ evaluated at sensor positions $x$\n", + "and maps it to a function $v$ evaluated at (different) evaluation positions $y$:\n", + "$$\n", + "v(y) = \\operatorname{Operator}\\left(x, u(x)\\right)(y).\n", + "$$\n", + "In this example, we choose the DeepONet architecture with 32 sensors." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "invertible-output" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "num_sensors = 32\n", + "\n", + "# Define operator\n", + "operator = DeepONet(num_sensors)\n", + "\n", + "# Some sensor positions\n", + "x = torch.linspace(-L, L, num_sensors)\n", + "\n", + "# Plot sensors\n", + "plt.plot(x, u(x), \"go\", label=\"Sensors\")\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plotting\n", + "\n", + "Before we train the neural operator, let us show how to evaluate the (untrained)\n", + "neural operator and plot the result." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "invertible-output" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Some (different) evaluation positions\n", + "y = torch.linspace(-L, L, 42)\n", + "\n", + "# Call operator\n", + "v_pred = operator(x, u(x), y)\n", + "\n", + "# Plot the predicted function\n", + "v_pred = v_pred.reshape(y.shape).detach()\n", + "plt.plot(y, v(y), \"k-\", label=\"Target $v$\")\n", + "plt.plot(y, v_pred, \"r--\", label=\"Predicted $v$ (untrained)\")\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Training\n", + "\n", + "Now, let's train the neural operator!\n", + "\n", + "We define a corresponding data set, i.e., a list-like of input-output samples." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Dataset containing single sample\n", + "dataset = [(x, u(x), y, v(y))]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using Adam we train the neural operator for 1000 epochs. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model parameters: 7984\n", + "Epoch 1000: loss = 1.5345e-04 (924.06 it/s)\n" + ] + } + ], + "source": [ + "optimizer = torch.optim.Adam(operator.parameters(), lr=1e-3)\n", + "operator.compile(optimizer)\n", + "operator.fit(dataset, epochs=1000)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluating\n", + "\n", + "The trained operator can be evaluated at arbitrary positions, so let's plot a\n", + "fine resolution of the mapping along with the target function." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "invertible-output" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Use a fine equidistant grid\n", + "y = torch.linspace(-L, L, 1000)\n", + "\n", + "# Call operator with more points\n", + "v_pred = operator(x, u(x), y)\n", + "\n", + "# Plot output and target function\n", + "v_pred = v_pred.reshape(y.shape).detach()\n", + "plt.plot(y, v(y), \"k-\", label=\"Target $v$\")\n", + "plt.plot(y, v_pred, \"r--\", label=\"Predicted $v$\")\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "That's the basics!" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv", + "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": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/intro.ipynb b/notebooks/intro.ipynb deleted file mode 100644 index 3c4dc04c..00000000 --- a/notebooks/intro.ipynb +++ /dev/null @@ -1,297 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Intro: Operator Learning\n", - "\n", - "This example demonstrates the basics of neural operators in Continuity,\n", - "including how to train it on a given operator." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import torch\n", - "import matplotlib.pyplot as plt\n", - "from continuity.operators import DeepONet" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "tags": [ - "hide" - ] - }, - "outputs": [], - "source": [ - "plt.rcParams[\"axes.facecolor\"] = (1, 1, 1, 0)\n", - "plt.rcParams[\"figure.facecolor\"] = (1, 1, 1, 0)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Problem Statement\n", - "\n", - "Let's assume we want to learn the derivative operator $G: u \\mapsto \\partial_x u$.\n", - "We choose (as an example) the function $u$ that maps to its derivative $v$\n", - "$$\n", - "u(x) = \\sin(x) \\to \\cos(y) = v(y)\n", - "$$\n", - "on the interval $[-\\pi, \\pi]$.\n", - "\n", - "Let's start with defining and plotting input and target function!" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Input function (some example)\n", - "u = lambda x: torch.sin(x)\n", - "\n", - "# Target function (the derivative of u)\n", - "v = lambda y: torch.cos(y)\n", - "\n", - "# Plot input and target function\n", - "L = torch.pi\n", - "x = torch.linspace(-L, L, 1000)\n", - "plt.plot(x, u(x), \"g-\", label=\"Input $u$\")\n", - "plt.plot(x, v(x), \"k-\", label=\"Target $v$\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Neural Operator\n", - "\n", - "In order to approximate the operator $G$ from above with a neural network,\n", - "we set up a neural operator.\n", - "A neural operator takes an input function $u$ evaluated at sensor positions $x$\n", - "and maps it to a function $v$ evaluated at (different) evaluation positions $y$:\n", - "$$\n", - "v(y) = \\operatorname{Operator}\\left(x, u(x)\\right)(y).\n", - "$$\n", - "In this example, we choose the DeepONet architecture with 32 sensors." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "num_sensors = 32\n", - "\n", - "# Define operator\n", - "operator = DeepONet(num_sensors)\n", - "\n", - "# Some sensor positions\n", - "x = torch.linspace(-L, L, num_sensors)\n", - "\n", - "# Plot sensors\n", - "plt.plot(x, u(x), \"go\", label=\"Sensors\")\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Evaluating a Neural Operator\n", - "\n", - "Before we train the neural operator, let us show how to evaluate the (untrained)\n", - "neural operator and plot the result." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Some (different) evaluation positions\n", - "y = torch.linspace(-L, L, 42)\n", - "\n", - "# Call operator\n", - "v_pred = operator(x, u(x), y)\n", - "\n", - "# Plot the predicted function\n", - "v_pred = v_pred.reshape(y.shape).detach()\n", - "plt.plot(y, v_pred, \".\")\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Training\n", - "\n", - "Now, let's train the neural operator!\n", - "\n", - "We define a corresponding data set, i.e., a list-like of input-output samples." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# Dataset containing single sample\n", - "dataset = [(x, u(x), y, v(y))]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Using Adam we train the neural operator for 1000 epochs. " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model parameters: 7984\n", - "Epoch 1000: loss = 1.5171e-04 (1194.96 it/s)\n" - ] - } - ], - "source": [ - "optimizer = torch.optim.Adam(operator.parameters(), lr=1e-3)\n", - "operator.compile(optimizer)\n", - "operator.fit(dataset, epochs=1000)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Evaluating the trained operator\n", - "\n", - "The trained operator can be evaluated at arbitrary positions, so let's plot a\n", - "fine resolution of the mapping along with the target function." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Use a fine equidistant grid\n", - "y = torch.linspace(-L, L, 1000)\n", - "\n", - "# Call operator with more points\n", - "v_pred = operator(x, u(x), y)\n", - "\n", - "# Plot output and target function\n", - "v_pred = v_pred.reshape(y.shape).detach()\n", - "plt.plot(y, v(y), \"k-\", label=\"Target $v$\")\n", - "plt.plot(y, v_pred, \"r--\", label=\"Predicted $v$\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "That's the basics!" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "venv", - "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": "3.11.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/physicsinformed.ipynb b/notebooks/physicsinformed.ipynb index c4d9e4e0..9fc8e0cd 100644 --- a/notebooks/physicsinformed.ipynb +++ b/notebooks/physicsinformed.ipynb @@ -33,7 +33,8 @@ "source": [ "torch.manual_seed(0)\n", "plt.rcParams[\"axes.facecolor\"] = (1, 1, 1, 0)\n", - "plt.rcParams[\"figure.facecolor\"] = (1, 1, 1, 0)\n" + "plt.rcParams[\"figure.facecolor\"] = (1, 1, 1, 0)\n", + "plt.rcParams[\"legend.framealpha\"] = 0.0\n" ] }, { @@ -49,11 +50,15 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "tags": [ + "invertible-output" + ] + }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -87,7 +92,8 @@ "x = torch.linspace(-1, 1, 100)\n", "for i in range(num_functions):\n", " u = polynomial(a[i])\n", - " plt.plot(x, u(x))\n", + " plt.plot(x, u(x), label=f\"Polynomial {i+1}\")\n", + "plt.legend()\n", "plt.show()" ] }, @@ -186,7 +192,7 @@ "output_type": "stream", "text": [ "Model parameters: 7984\n", - "Epoch 1000: loss = 2.8581e-05 (815.91 it/s)\n" + "Epoch 1000: loss = 2.8581e-05 (766.69 it/s)\n" ] } ], @@ -210,11 +216,15 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "tags": [ + "invertible-output" + ] + }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] diff --git a/notebooks/selfsupervised.ipynb b/notebooks/selfsupervised.ipynb new file mode 100644 index 00000000..c765cb44 --- /dev/null +++ b/notebooks/selfsupervised.ipynb @@ -0,0 +1,279 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Self-supervised\n", + "\n", + "This example shows how to train a neural operator on sine functions\n", + "in a self-supervised manner." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup\n", + "\n", + "Import modules." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "import matplotlib.pyplot as plt\n", + "from continuity.data.datasets import Sine\n", + "from continuity.operators import ContinuousConvolution\n", + "from continuity.operators.common import NeuralNetworkKernel\n", + "from continuity.plotting import plot_evaluation, plot_observation" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [ + "hide" + ] + }, + "outputs": [], + "source": [ + "torch.manual_seed(0)\n", + "plt.rcParams[\"axes.facecolor\"] = (1, 1, 1, 0)\n", + "plt.rcParams[\"figure.facecolor\"] = (1, 1, 1, 0)\n", + "plt.rcParams[\"legend.framealpha\"] = 0.0\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dataset\n", + "\n", + "Create a data set of sine waves: The `Sine` dataset generates $N$ sine waves\n", + "$$\n", + "f(x) = \\sin(w_k x), \\quad w_k = 1 + \\frac{k}{N-1}, \\quad k = 0, \\dots, N-1.\n", + "$$\n", + "As a `SelfSupervisedDataset` it exports batches of samples for self-supervised\n", + "training, namely\n", + "$$\n", + "\\left(\\mathbf{x}, f(\\mathbf{x}), x_j, f(x_j)\\right), \\quad \\text{for } j = 1, \\dots, M,\n", + "$$\n", + "where $\\mathbf{x} = (x_i)_{i=1 \\dots M}$ are the $M$ equidistantly\n", + "distributed sensor positions. " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "tags": [ + "invertible-output" + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Dataset contains 32 batches.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "size = 4\n", + "dataset = Sine(\n", + " num_sensors=32,\n", + " size=size,\n", + " batch_size=4,\n", + ")\n", + "print(f\"Dataset contains {len(dataset)} batches.\")\n", + "\n", + "# Plot first sample\n", + "first_batch = dataset[0]\n", + "x, u, y, v = [a[0] for a in first_batch]\n", + "plt.plot(y, v, 'ro', label='Label')\n", + "plt.plot(x, u, 'k.', label='Sensors')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Operator\n", + "\n", + "We use a `ContinuousConvolution` neural operator with a slightly overparameterized\n", + "`NeuralNetworkKernel` as kernel function." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "kernel = NeuralNetworkKernel(kernel_width=128, kernel_depth=10)\n", + "model = ContinuousConvolution(kernel)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Training\n", + "\n", + "Train the neural operator." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model parameters: 165505\n", + "Epoch 100: loss = 3.9808e-03 (232.73 it/s)\n" + ] + } + ], + "source": [ + "optimizer = torch.optim.Adam(model.parameters(), lr=1e-4)\n", + "model.compile(optimizer)\n", + "model.fit(dataset, epochs=100)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plotting\n", + "\n", + "Plot model predictions for training data." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "tags": [ + "invertible-output" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(1, 4, figsize=(16, 3))\n", + "for i in range(size):\n", + " obs = dataset.get_observation(i)\n", + " plot_evaluation(model, obs, ax=axs[i])\n", + " plot_observation(obs, ax=axs[i])\n", + " axs[i].set_title(f\"$k = {i}$\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Generalization\n", + "\n", + "Plot prediction on a test sample which was not part of the training set." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "tags": [ + "invertible-output" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, '$k = 1.5$')" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1, 1, figsize=(4, 3))\n", + "i_test = (size-1) / 2\n", + "obs = dataset.generate_observation(i_test)\n", + "plot_evaluation(model, obs, ax=ax)\n", + "plot_observation(obs, ax=ax)\n", + "ax.set_title(f\"$k = {i_test}$\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv", + "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": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/sine.ipynb b/notebooks/sine.ipynb deleted file mode 100644 index 0e1cd9fd..00000000 --- a/notebooks/sine.ipynb +++ /dev/null @@ -1,224 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Sine\n", - "\n", - "This example trains a neural operator on the sine function in a self-supervised \n", - "manner." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setup\n", - "\n", - "Import modules." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import torch\n", - "import matplotlib.pyplot as plt\n", - "from continuity.data.datasets import Sine\n", - "from continuity.operators import NeuralOperator\n", - "from continuity.plotting import plot_evaluation, plot_observation" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "tags": [ - "hide" - ] - }, - "outputs": [], - "source": [ - "plt.rcParams[\"axes.facecolor\"] = (1, 1, 1, 0)\n", - "plt.rcParams[\"figure.facecolor\"] = (1, 1, 1, 0)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data set\n", - "\n", - "Create a data set of sine waves with 32 sensors." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "size = 4\n", - "dataset = Sine(\n", - " num_sensors=16,\n", - " size=size,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Neural operator\n", - "\n", - "Create a neural operator." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "model = NeuralOperator(\n", - " coordinate_dim=dataset.coordinate_dim,\n", - " num_channels=dataset.num_channels,\n", - " depth=1,\n", - " kernel_width=32,\n", - " kernel_depth=3,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Training\n", - "\n", - "Train the neural operator in a self-supervised manner." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model parameters: 9795\n", - "Epoch 1000: loss = 4.7573e-03 (96.85 it/s)\n" - ] - } - ], - "source": [ - "optimizer = torch.optim.Adam(model.parameters(), lr=1e-3)\n", - "criterion = torch.nn.MSELoss()\n", - "\n", - "model.compile(optimizer, criterion)\n", - "model.fit(dataset, epochs=1000)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plotting\n", - "\n", - "Plot training data and predictions." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "tags": [ - "invertible-output" - ] - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(1, 4, figsize=(16, 3))\n", - "for i in range(size):\n", - " obs = dataset.get_observation(i)\n", - " plot_evaluation(model, obs, ax=axs[i])\n", - " plot_observation(obs, ax=axs[i])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot test observations and predictions." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "tags": [ - "invertible-output" - ] - }, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(1, 1, figsize=(4, 3))\n", - "i_test = (size-1) / 2\n", - "obs = dataset.generate_observation(i_test)\n", - "plot_evaluation(model, obs, ax=ax)\n", - "plot_observation(obs, ax=ax)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "venv", - "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": "3.11.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/continuity/data/datasets.py b/src/continuity/data/datasets.py index dd4c4652..1026175d 100644 --- a/src/continuity/data/datasets.py +++ b/src/continuity/data/datasets.py @@ -140,6 +140,18 @@ class Sine(SelfSupervisedDataSet): sine waves is evenly distributed between $\pi$ for the first observation and $2\pi$ for the last observation, respectively. + The `Sine` dataset generates $N$ sine waves + $$ + f(x) = \sin(w_k x), \quad w_k = 1 + \frac{k}{N-1}, \quad k = 0, \dots, N-1. + $$ + As a `SelfSupervisedDataset` it exports batches of samples for self-supervised + training, namely + $$ + \left(\mathbf{x}, f(\mathbf{x}), x_j, f(x_j)\right), \quad \text{for } j = 1, \dots, M, + $$ + where $\mathbf{x} = (x_i)_{i=1 \dots M}$ are the $M$ equidistantly + distributed sensor positions. + - coordinate_dim: 1 - num_channels: 1 @@ -172,7 +184,7 @@ def generate_observation(self, i: float): if self.size == 1: w = 1 else: - w = i / self.size + 1 + w = 1 + i / (self.size - 1) u = np.sin(w * np.pi * x) diff --git a/src/continuity/operators/neuraloperator.py b/src/continuity/operators/neuraloperator.py index fca4c77e..a06d6795 100644 --- a/src/continuity/operators/neuraloperator.py +++ b/src/continuity/operators/neuraloperator.py @@ -21,22 +21,22 @@ class ContinuousConvolution(Operator): where $(x_i, u_i)$ are the $N$ sensors of the mapped observation. Args: + kernel: Kernel function $\kappa$ or network (if $d$ is the coordinate dimension, $\kappa: \R^d \times \R^d \to \R$) coordinate_dim: Dimension of coordinate space num_channels: Number of channels - kernel: Kernel function $\kappa$ or network (if $d$ is the coordinate dimension, $\kappa: \R^d \times \R^d \to \R$) """ def __init__( self, - coordinate_dim: int, - num_channels: int, kernel: Union[Callable[[Tensor], Tensor], torch.nn.Module], + coordinate_dim: int = 1, + num_channels: int = 1, ): super().__init__() + self.kernel = kernel self.coordinate_dim = coordinate_dim self.num_channels = num_channels - self.kernel = kernel def forward(self, x: Tensor, u: Tensor, y: Tensor) -> Tensor: """Forward pass through the operator. @@ -123,26 +123,26 @@ def __init__( self.num_channels = num_channels self.lifting = ContinuousConvolution( + NeuralNetworkKernel(kernel_width, kernel_depth), coordinate_dim, num_channels, - NeuralNetworkKernel(kernel_width, kernel_depth), ) self.hidden_layers = torch.nn.ModuleList( [ ContinuousConvolution( + NeuralNetworkKernel(kernel_width, kernel_depth), coordinate_dim, num_channels, - NeuralNetworkKernel(kernel_width, kernel_depth), ) for _ in range(depth) ] ) self.projection = ContinuousConvolution( + NeuralNetworkKernel(kernel_width, kernel_depth), coordinate_dim, num_channels, - NeuralNetworkKernel(kernel_width, kernel_depth), ) def forward(self, x: Tensor, u: Tensor, y: Tensor) -> Tensor: diff --git a/tests/test_convolution.py b/tests/test_convolution.py index cc96c584..6f03ca11 100644 --- a/tests/test_convolution.py +++ b/tests/test_convolution.py @@ -24,9 +24,9 @@ def dirac(x, y): # Operator operator = ContinuousConvolution( + kernel=dirac, coordinate_dim=dataset.coordinate_dim, num_channels=dataset.num_channels, - kernel=dirac, ) # Create tensors