SEAVEAtk release July 2023

This is the July 2023 release of EasyVVUQ, as part of the SEAVEAtk, with the following minor updates:

Fixes and updates

• Fixed several tests for newer Python versions.
• Updated integration with QCG-PilotJob

Tutorials

• SSC tutorial: https://github.com/UCL-CCS/EasyVVUQ/blob/dev/tutorials/simplex_stochastic_collocation_tutorial.ipynb
• Hyperparameter tuning tutorial, local sampling: https://github.com/UCL-CCS/EasyVVUQ/blob/dev/tutorials/hyperparameter_tuning_tutorial.ipynb
• Hyperparameter tuning tutorial, remote sampling with FabSim3: https://github.com/UCL-CCS/EasyVVUQ/blob/dev/tutorials/hyperparameter_tuning_tutorial_with_fabsim.ipynb

SEAVEAtk release March 0223

This is the March 2023 release of EasyVVUQ, as part of the SEAVEAtk, with the following updates:

New features

• New Simplex Stochastic Collocation sampler for irregular outputs, e.g. with discontinuities or high gradients in the stochastic input space. Works for scalar QoI only thus far.
• Grid-Search sampler, (e.g. for neural-network hyper parameter tuning).
• HDF5 decoder to allow for reading HDF5 output files, useful when dealing with outputs of different size.

Tutorials

• SSC tutorial: https://github.com/UCL-CCS/EasyVVUQ/blob/dev/tutorials/simplex_stochastic_collocation_tutorial.ipynb
• Hyperparameter tuning tutorial, local sampling: https://github.com/UCL-CCS/EasyVVUQ/blob/dev/tutorials/hyperparameter_tuning_tutorial.ipynb
• Hyperparameter tuning tutorial, remote sampling with FabSim3: https://github.com/UCL-CCS/EasyVVUQ/blob/dev/tutorials/hyperparameter_tuning_tutorial_with_fabsim.ipynb

Usability updates

• Make it more obvious how to import a pandas dataframe containing cases to be considered
• Make it more obvious how to massage the results from the runs before performing the PCE/SC/MC analysis

SEAVEA release

Overhaul of SC sampler / analysis class:

• Made isotropic sparse-grid subroutines more scalable to higher input dimensions. Reused dimension-adaptive subroutines for this purpose, instead of having (slower) separate isotropic routines.
• Rewrote dimension-adaptive SC expansion as a standard PCE expansion with generalized PCE coefficients. See adaptive sparse-grid tutorial.

Documentation:

• Extensive methodological sparse-grid tutorial: https://www.researchgate.net/publication/359296270_Adaptive_sparse-grid_tutorial
• New tutorial on using mathematical expressions involving parameters in template files using the Jinja encoder: https://github.com/UCL-CCS/EasyVVUQ/blob/dev/tutorials/jinja_tutorial.ipynb

M42 release

New features:

• Updated the documentation in a range of places.

Bug fixes:

*Fixed direct integration of EasyVVUQ with QCG-PilotJob. Previously there was an issue with large campaigns where the integration could fail due to an excessively long command-line argument.
*Fixed bug where unsuitable models could be applied with QCG-PilotJob integration.
*Fixed MC sampler for use with 1 parameter: fac0b57

Tutorials:

• Added an example for including noise in an EasyVVUQ campaign ( easyvvuq_Ishigami_with_noise_tutorial.ipynb)

EasyVVUQ v1.1

New features:

• Ability to add external runs via a DataFrame
• Ability to execute EasyVVUQ workflows from R

Tutorials:

• Updates to Dimension Adaptive Fusion tutorial.

EasyVVUQ v1.0

EasyVVUQ v1.0

New Features

• Better support to execute pure Python simulations.
• Added a surrogate method to AnalysisResults classes.
• QCG-PJ support.
• Gaussian Process Surrogate analysis method.
• Reworked Campaign and hand optimised database.
• Re-implemented Actions system for modular execution options.
• DataFrameSampler for uploading new

Updates

• Large scale code refactoring.
• Docstring and documentation updates.
• Additional testing and benchmarking.
• Continuous benchmarking.

EasyVVUQ v0.9.3

A bug-fix release.

EasyVVUQ v0.9.2

Minor release with some updates.

EasyVVUQ v0.9.1

Fixing some bugs introduced in v0.9.

EasyVVUQ v0.9

New features:

• MCMC support for calibration problems.
• Rework of the actions framework to allow a wider range of execution scenarios and to simplify the code base.
• CSV sampler for loading in data created with other software.

Updates:

• New, simplified workflows due to refactoring efforts.
• New tutorials and binder integration.