Gaussian Process Subspace Regression Prediction, Eigen-Decomposition Version
Project description
This is a prototypical implementation of GPS in the Python programming language. For the original research article documenting the method, see the Citation section.
Citation
- Ruda Zhang, Simon Mak, and David Dunson. Gaussian Process Subspace Prediction for Model Reduction. SIAM Journal on Scientific Computing, 2022. https://epubs.siam.org/doi/10.1137/21M1432739
Installation
Install the package via pip using the following command:
- python3 -m pip install GPyS
Example Use
After installing the package you can load it via:
For GPS Preprocessor:
- from GPyS_preprocessor import Preprocessor
- Note that only Preprocessor.setup(X) takes in argument X and this must be called first before any other functions
- The remaining functions merely returns preprocessing quantities of interests
For GPS Prediction:
- from GPyS_prediction import Prediction
- All the functions can be independently called here.
- Also, user can directly call Prediction.GPS_Prediction() to immediately obtain prediction results
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