{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## **Gaussian Process Emulator**\n", "\n", "This notebook contains basic working examples of fitting and running inference using Gaussian Processes (GPs) as the base estimator model in `twinLab`.\n", "\n", "An in-depth introductory review of GPs can be found at [Rasmussen and Williams (2006)](https://gaussianprocess.org/gpml/).\n", "\n", "This notebook will cover:\n", "\n", "- Basic syntax\n", "- Detrending data\n", "- Specifying a covarance module\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Third-party imports\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "\n", "# twinLab import\n", "import twinlab as tl" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### **Problem Formulation**\n", "\n", "As a start, we will solve a simple regression problem with one input and one output.\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# The true function\n", "def oscillator(x):\n", " return np.cos((x - 5) / 2) ** 2 * x * 2\n", "\n", "\n", "X = np.linspace(-15, 15, 100)[:, np.newaxis]\n", "y = oscillator(X) # Arrange outputs as feature columns\n", "\n", "n_data = 200\n", "X_data = np.random.uniform(-10, 10, size=n_data)\n", "y_data = oscillator(X_data) + np.random.normal(scale=0.2, size=X_data.shape)\n", "\n", "plt.plot(X, y)\n", "plt.scatter(X_data, y_data)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Datasets must be data presented as a `pandas.DataFrame` object, or a filepaths which points to a csv file that can be parsed to a `pandas.DataFrame` object. **Both must be formatted with clearly labelled columns.** Here, we will label the input (predictor) variable `x` and the output variable `y`. In `twinlab`, data is expected to be in column-feature format, meaning each row represents a single data sample, and each column represents a data feature.\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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xy
03.6518874.344898
1-9.052743-9.454922
2-9.649020-4.871539
38.4792350.503219
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" ], "text/plain": [ " x y\n", "0 3.651887 4.344898\n", "1 -9.052743 -9.454922\n", "2 -9.649020 -4.871539\n", "3 8.479235 0.503219\n", "4 -5.774704 -4.326750" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Convert to dataframe\n", "df = pd.DataFrame({\"x\": X_data, \"y\": y_data})\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Define the name of the dataset\n", "dataset_id = \"BasicGP_Data\"\n", "\n", "# Upload the dataset to the cloud\n", "dataset = tl.Dataset(id=dataset_id)\n", "dataset.upload(df)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### **Basic Emulator Workflow**\n", "\n", "By default, a `Emulator` object will try to fit a Gaussian Process with a Constant Mean and a Matern 5/2 covariance kernel to the data. This is done with the basic syntax shown below.\n", "\n", "**Note**: the `train_test_ratio` parameter determines how many data samples in `df` to use for fitting the model. E.g. if `train_test_ratio=0.4`, then 40% of the samples in `df` are used for fitting, and the remaining data is used for testing. The data reserved for testing is used to assess the performance of the model.\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Initialise emulator\n", "emulator_id = \"BasicGP\"\n", "\n", "emulator = tl.Emulator(id=emulator_id)\n", "\n", "# Define the training parameters for your emulator\n", "params = tl.TrainParams(\n", " train_test_ratio=0.75, estimator=\"gaussian_process_regression\"\n", ")\n", "\n", "# Train the mulator using the train method\n", "emulator.train(dataset=dataset, inputs=[\"x\"], outputs=[\"y\"], params=params)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot inference results\n", "df_pred = emulator.predict(pd.DataFrame(X, columns=[\"x\"]))\n", "result_df = pd.concat([df_pred[0], df_pred[1]], axis=1)\n", "df_mean, df_stdev = result_df.iloc[:, 0], result_df.iloc[:, 1]\n", "y_mean, y_stdev = df_mean.values, df_stdev.values\n", "\n", "plt.fill_between(\n", " X.flatten(),\n", " (y_mean - 1.96 * y_stdev).flatten(),\n", " (y_mean + 1.96 * y_stdev).flatten(),\n", " color=\"k\",\n", " alpha=0.1,\n", ")\n", "\n", "plt.scatter(df[\"x\"], df[\"y\"], alpha=0.5, label=\"Training Data\")\n", "plt.xlabel(\"x\")\n", "plt.ylabel(\"y\")\n", "\n", "plt.plot(X, y, c=\"r\", linewidth=2, label=\"True Function\")\n", "plt.plot(X, y_mean, c=\"k\", linewidth=2, linestyle=\"dashed\", label=\"Prediction\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **Detrending Data**\n", "\n", "A standard data processing task before fitting a model to data is (linear) _detrending_: here, the linear non-stationary information about the data is subtracted from the data. This may help with subsequent model fitting.\n", "\n", "In `Emulator`, this is achieved simply with the keyword `detrend` provided to the `estimator_params` argument, inside the `TrainParams`, during initialisation. This results in the following code:\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model DetrendingGP has begun training.\n", "Training complete!\n", "\n" ] } ], "source": [ "# Initialise emulator\n", "emulator_id = \"DetrendingGP\"\n", "\n", "detrending_emulator = tl.Emulator(id=emulator_id)\n", "\n", "# Define the estimator params and allow detrending of data\n", "estimator_params = tl.EstimatorParams(detrend=True)\n", "\n", "# Define the training parameters for your emulator\n", "params = tl.TrainParams(\n", " train_test_ratio=0.75,\n", " estimator=\"gaussian_process_regression\",\n", " estimator_params=estimator_params,\n", ")\n", "\n", "# Train the emulator using the defined parameters\n", "detrending_emulator.train(\n", " dataset=dataset, inputs=[\"x\"], outputs=[\"y\"], params=params, verbose=True\n", ")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot inference results\n", "df_pred = emulator.predict(pd.DataFrame(X, columns=[\"x\"]))\n", "result_df = pd.concat([df_pred[0], df_pred[1]], axis=1)\n", "df_mean, df_stdev = result_df.iloc[:, 0], result_df.iloc[:, 1]\n", "y_mean, y_stdev = df_mean.values, df_stdev.values\n", "\n", "plt.fill_between(\n", " X.flatten(),\n", " (y_mean - 1.96 * y_stdev).flatten(),\n", " (y_mean + 1.96 * y_stdev).flatten(),\n", " color=\"k\",\n", " alpha=0.1,\n", ")\n", "\n", "plt.scatter(df[\"x\"], df[\"y\"], alpha=0.5, label=\"Training Data\")\n", "plt.xlabel(\"x\")\n", "plt.ylabel(\"y\")\n", "\n", "plt.plot(X, y, c=\"r\", linewidth=2, label=\"True Function\")\n", "plt.plot(X, y_mean, c=\"k\", linewidth=2, linestyle=\"dashed\", label=\"Prediction\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note the difference in the mean prediction of the detrended model compared to the standard model without detrending (from the previous section). The prediction is automatically re-trended during inference, so no need for any other operations.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **Specifying a Covariance Kernel**\n", "\n", "In some cases, it may be desirable to specify a covariance module for the GP. The user may have some belief that the process is linear in nature, or may contain a combination of periodic signals at different length-scales, or may want to specifically account for short-time noise in the data.\n", "\n", "`Emulator` allows the user to do this, via the `covar_module` keyword provided to the `estimator_params` dictionary. Currently, the kernels are provided as 3-character uppercase strings. The list of possible kernels are:\n", "\n", "- `\"LIN\"`: Linear kernel\n", "- `\"M12\"`: Matern 1/2 kernel\n", "- `\"M32\"`: Matern 3/2 kernel\n", "- `\"M52\"`: Matern 5/2 kernel\n", "- `\"PER\"`: Periodic kernel\n", "- `\"RBF\"`: Radial Basis Function kernel\n", "- `\"RQF\"`: Rational Quadratic Kernel\n", "\n", "Additionally, the kernels can be [composed](https://www.cs.toronto.edu/~duvenaud/cookbook/) using brackets and `+` or `*` string operators. For example:\n", "\n", "- `\"LIN+PER\"`\n", "- `\"(M52*PER)+RQF`\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# Initialise emulator\n", "emulator_id = \"LinearGP\"\n", "\n", "linear_emulator = tl.Emulator(id=emulator_id)\n", "\n", "# Define the estimator params with a covariance function\n", "estimator_params = tl.EstimatorParams(covar_module=\"LIN\")\n", "\n", "# Define the training parameters for your emulator\n", "params = tl.TrainParams(\n", " train_test_ratio=0.75,\n", " estimator=\"gaussian_process_regression\",\n", " estimator_params=estimator_params,\n", ")\n", "\n", "# Train the emulator using the defined parameters\n", "linear_emulator.train(dataset=dataset, inputs=[\"x\"], outputs=[\"y\"], params=params)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot inference results\n", "df_pred = linear_emulator.predict(pd.DataFrame(X, columns=[\"x\"]))\n", "result_df = pd.concat([df_pred[0], df_pred[1]], axis=1)\n", "df_mean, df_stdev = result_df.iloc[:, 0], result_df.iloc[:, 1]\n", "y_mean, y_stdev = df_mean.values, df_stdev.values\n", "\n", "plt.fill_between(\n", " X.flatten(),\n", " (y_mean - 1.96 * y_stdev).flatten(),\n", " (y_mean + 1.96 * y_stdev).flatten(),\n", " color=\"k\",\n", " alpha=0.1,\n", ")\n", "\n", "plt.scatter(df[\"x\"], df[\"y\"], alpha=0.5, label=\"Training Data\")\n", "plt.xlabel(\"x\")\n", "plt.ylabel(\"y\")\n", "\n", "plt.plot(X, y, c=\"r\", linewidth=2, label=\"True Function\")\n", "plt.plot(X, y_mean, c=\"k\", linewidth=2, linestyle=\"dashed\", label=\"Prediction\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# Delete campaigns and dataset\n", "tl.delete_campaign(\"BasicGP\")\n", "tl.delete_campaign(\"DetrendingGP\")\n", "tl.delete_campaign(\"LinearGP\")\n", "\n", "tl.delete_dataset(dataset_id)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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" }, "vscode": { "interpreter": { "hash": "a73b81f77433a07a5451f1269b58376229ced6e8222af986634b7460575721ae" } } }, "nbformat": 4, "nbformat_minor": 2 }