UQWorld

UQLab Release Notes

In this post you can find all the detailed release notes for every UQLab release.

Table of contents

UQLab Modules 1.3.0 (19.09.2019)

UQLabModules V1.2.1 ➜ UQLabModules V1.3.0

Stable release of UQLabModules.

New features

  • Input module:

    • Major update on the module; it now includes new types of copulas (CVine and DVine) and supports independent sets of random variables as well as statistical inference for both marginals and copulas (Developed and documented by Dr. E. Torre from ETH Zurich)
  • Reliability-based design optimization (RBDO) module:​

    • A new module to conduct reliability-based design optimization is now available (Developed and documented by Dr. ​M. Maliki from ETH Zurich)
  • Kriging module:

    • Gaussian process (GP) regression for noisy observations is now available
      (Developed and documented by Dr. D. Wicaksono from ETH Zurich)​
  • Sensitivity analysis module:​​

    • New sample-based estimator for the Kucherenko indices​ (compatible with non-Gaussian copulas)
    • Borgonovo indices can now be computed from pre-existing samples​
  • UQLib:​

    • A collection of standard UQLab plotting and plot formatting functions is now consolidated in uq_graphics inside the lib folder (Developed and documented by P. Wiederkehr, P.-R. Wagner, and Dr. D. Wicaksono from ETH Zurich)​

Enhancements

  • Bayesian inversion module:

    • A sample generated by any MCMC sampler is automatically post-processed using the uq_postProcessInversion function at the end of an inverse analysis
    • Posterior covariance and correlation matrices are now estimated from the MCMC sample by the uq_postProcessInversion function​
  • UQLink​ module:

    • Mathematical expressions with input variables can now be entered in the template file​​​
  • Documentation​:

    • Kriging module:​ Add elaboration on the ​cross-validation estimation
  • Sensitivity module:

    • Chunk-allocation now used for models with high-dimensional inputs to avoid out-of-memory issues​

Changes

  • Added warnings when using sensitivity analysis methods that don’t support dependence for inputs with dependent inputs​

Bug fixes

  • Fixed LRA-based Sobol’ indices not working for multiple-output models
  • Fixed optimization bound issues when using Kriging in certain situations
  • Fixed inconsistent images used in the documentation w.r.t. the actual examples
  • Bugfixes and improvements across the board

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UQLab Modules 1.2.1 (07.03.2019)

UQLabModules V1.2.0 ➜ UQLabModules V1.2.1

Stable release of UQLabModules.

Bug fixes

  • Addressed a number of compatibility issues with versions of MATLAB older than R2016a

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UQLab Modules 1.2.0 (22.02.2019)

UQLabModules V1.1.0 ➜ UQLabModules V1.2.0

Stable release of UQLabModules.

New features

  • Bayesian inversion module:

    • A new module for solving Bayesian inverse problems is now available
      (developed and documented by P.-R. Wagner from ETH Zurich)​
  • Sensitivity analysis module:

    • Kucherenko and ANCOVA indices for global sensitivity analysis with dependent inputs are now available (developed and documented by P. Wiederkehr from ETH Zurich)​
  • Polynomial chaos expansion module:​

    • Added adaptive q-norm truncation for the regression-based PCE​
    • Improved the leave-one-out calculation for the LARS regression method
  • UQLib​​:

    • A collection of general-purpose open-source libraries (including differentiation, optimization, kernel, and input/output processing) is now available and accessible in the lib folder
      (developed and documented by Dr. M. Maliki, C. Lataniotis, P. Wiederkehr, and Dr. D. Wicaksono from ETH Zurich)​

Enhancements

  • Kriging, SVR, and SVC modules:

    • Evaluation of the kernel is now based on the general-purpose kernel evaluation function provided by UQLib (uq_eval_Kernel)​​​
  • Documentation:

    • Sensitivity analysis module:​
      • Added statements on each method whether the method is applicable for dependent input variables​
  • General:​​

    • The uq_gradient function is now vectorized and part of UQLib​​ differentiation library
    • Removed dependence from Optimization and Global Optimization toolboxes by defaulting to optimization algorithms available in UQLib

Changes

  • Documentation:

    • Sensitivity analysis module:​
      • One theory section for all Sobol’ indices​
      • New section on the usage chapter to showcase the sensitivity analysis methods that support dependent inputs (Kucherenko and ANCOVA indices)
  • Kriging:

    • Updated default optimization parameters to provide more accurate results

​​Bug fixes

  • UQLink:
    • UQLink can now handle cases where a command line is given using the full path to the executable that contains white spaces

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UQLab Modules 1.1.0 (05.07.2018)

UQLabModules V1.0.0 ➜ UQLabModules V1.1.0

Stable release of UQLabModules.

New features

  • Metamodelling tools:
    • Support vector machines for classification (SVC) and regression (SVR) now available (developed and documented by Dr. M. Moustapha from ETH Zurich)
  • UQLink:
    • seamless connection of third-party software to UQLab now available by using universal “wrapping” of external codes through templates and a markup system (developed and documented by Dr. M. Moustapha from ETH Zurich)
  • Sensitivity analysis:
    • Borgonovo moment-independent indices are now available (developed and documented by C. Mylonas from ETH Zurich)
  • General:
    • New subsampling, one-hot-encoding and cobweb plot functions now available in the lib/ folder

Enhancements

  • General:
    • Standardized the examples for improved readability
  • Documentation:
    • Added the outputs of uq_print to all manuals
    • Added comments on the default values used in the minimal working examples
    • General readability and consistency improvements
  • Reliability analysis module:
    • AKMCS:
      • Added a convergence criterion on beta
    • IS:
      • One instrumental density function can now be specified for each model output
  • Sensitivity analysis module:
    • Removed the requirement for an input object for SRC / Correlation-based sensitivity analyses when a sample is provided

Changes

  • General:
    • Changes in uq_display for many modules to optimize readability
  • Metamodeling modules:
    • Polynomial chaos expansions:
      • Default degree for Quadrature set equal to 3, for degree-adaptive methods to 1:3
      • Fixed issues that broke the evaluation of a quadrature PCE for multiple outputs models
      • Initialization sets the maximum degree either from the provided degree or custom truncation. If both are provided, the custom truncation will be used.
      • Stability fixes for arbitrary polynomials (fix for integration waypoints)
    • Kriging:
      • Specification ExpDesign.Sampling = 'user' or 'data' is no longer necessary when providing the samples manually
      • Removed ExpDesign.time from results
      • Moved ExpDesign.muX and .sigmaX from Results to Internal

Bug fixes

  • Reliability analysis module:
    • SORM: can now be run on a pre-existing FORM analysis
    • IS: Removed warning in initialization if no instrumental density distribution is provided
  • Sensitivity analysis module:
    • Small stability fixes to sensitivity- and PCE- related calculations
    • Fixed the assembling of the PCE-based Sobol’ indices to avoid problems when using constant variables
    • Fixed LRA-based Sobol’ indices to prevent failing for models with multiple outputs
    • Sobol’ indices can be plotted as a pie-diagram

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UQLab 1.0.0 (28.04.2017)

UQLabBeta V0.92 ➜ UQLabModules V1.0.0 stable

Stable release of UQLabModules.

New features

  • Metamodeling tool:
    • Canonical Low-Rank approximations now available (developed and documented by Dr. K. Konakli and C. Mylonas from ETH Zurich)
    • Polynomial-Chaos-Kriging now available (developed and documented by Dr. R. Schöbi from ETH Zurich)
  • Open source release of the scientific code with extensive command-line help (UQLab Dev Team)

Enhancements

  • General:
    • Constant variables are now supported throughout UQLab modules. Most algorithms are now aware of constant variables and will exclude them to improve computational efficiency (UQLab Dev Team)
  • Input module:
    • Several input marginals added to the existing ones (E. Dodoula and C. Lataniotis)
  • Polynomial Chaos Expansions module:
    • Orthogonal Matching Pursuit added to the regression methods (M. Berchier)
    • Polynomials orthogonal to arbitrary distributions now available (C. Mylonas)
  • Reliability analysis module:
    • Polynomial Chaos-Kriging can now be used as a metamodel in AK-MCS
  • Documentation:
    • Now available in pdf and HTML formats in the Doc/Manuals folder,
      accessible via the uq_doc function

Changes

  • Kriging module:
    • Default correlation family changed to matern-5_2
    • Covariance matrix of the predictor is now available as the third output of uq_evalModel
  • Polynomial Chaos Expansions module:
    • Default quadrature scheme changed to Full when input dimension < 4 (cheaper)
  • Input module:
    • Changed handling of custom distributions

Bug fixes

  • General bug fixes and performance improvements across modules w.r.t. V0.92

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