JetGP Module Examples#
This section provides examples for using JetGP classes, including DEGP, WDEGP, DDEGP, GDDEGP, and WDDEGP.
Tutorials
- Derivative-Enhanced Gaussian Process (DEGP)
- Overview
- Example 1: 1D First-Order Derivatives Only
- Example 2: 1D First- and Second-Order Derivatives
- Example 3: 2D First-Order Derivatives
- Example 4: 2D Second-Order (Main) Derivatives
- Example 5: 1D Heterogeneous Derivative Coverage
- Example 6: Predicting Untrained Partial Derivatives
- Example 7: 2D Function-Only Training with Derivative Predictions
- 1D DEGP Kernel Comparison
- Overview
- Step 1: Import packages and define training data
- Step 2: Squared Exponential (SE) kernel
- Step 3: Matern kernel
- Step 4: Rational Quadratic (RQ) kernel
- Step 5: Sine-Exponential (SineExp) kernel
- Step 6: Visual comparison – function predictions
- Step 7: Visual comparison – derivative predictions
- Step 8: RMSE summary
- Summary
- 2D DEGP Kernel Comparison: Isotropic vs Anisotropic
- Directional Derivative-Enhanced Gaussian Process (DDEGP)
- Directional Derivative-Enhanced Gaussian Process (DDEGP) - Selective Coverage
- Generalized Directional Derivative-Enhanced Gaussian Process (GDDEGP)
- Example 2: GDDEGP with Multiple Directional Derivatives Per Point Using Global Perturbations
- GDDEGP Tutorial: Mixed Derivative Coverage
- Overview
- Data Structure Correspondence
- Step 1: Import required packages
- Step 2: Set configuration parameters
- Step 3: Define the Branin function
- Step 4: Generate training data with MIXED derivative coverage
- Step 5: Initialize and train the GDDEGP model
- Step 6: Evaluate model on a test grid
- Step 7: Verify interpolation at training points
- Step 8: Visualize results with mixed coverage
- Summary
- Key Takeaways
- Example 3: More Direction Types Than Spatial Dimensions
- Example 4: 2D Function-Only Training with Derivative Predictions
- Weighted Derivative-Enhanced Gaussian Process (WDEGP)
- Weighted Individual Submodel Framework
- Key Data Structures:
submodel_indicesandderivative_specs - Derivative Predictions
- Example 1: 1D Weighted DEGP with Individual Submodels
- Example 2: 1D Sparse Weighted DEGP with Selective Derivative Observations
- Example 3: 1D Weighted DEGP with Multiple Submodels
- Example 4: Heterogeneous Derivative Indices Within Submodels
- Example 5: WDEGP with Different Derivative Specifications per Submodel
- Example 6: WDEGP with DDEGP Submodels (Global Directional Derivatives)
- Example 7: WDEGP with GDDEGP Submodels (Point-Wise Directional Derivatives)
- Example: Predicting Derivatives Not Common to All Submodels
- Example 8: 2D Function-Only WDEGP with Derivative Predictions