Change Log

All notable changes to this project are documented in this file. Each heading has a format of <version> - <date> where the date format is YYYY-MM-DD.

20.2.0 - 2020-10-07

  • New nodes

    • Neural Network Regressor

  • Add progress bars to nodes

  • Add resource monitor to app

  • Documentation improvements

20.1.1 - 2020-08-19

  • Fix wizard node spacing

  • Fix multiplot and numpy sum nodes

  • Update wavelets example

  • Documentation fixes

  • Change normed keyword in matplotlib hist call to density

  • include this change log in the documentation

20.1.0 - 2020-08-13

  • New nodes

    • Residual Function

    • Generic Model Creator

    • Sample Aggregator

    • Sample Filter

    • Queue Submission

  • Response Surface Node

    • Add preprocessing tools

    • Add more response methods from scikits-learn

      • gradient boosting

    • Expose more model options

    • Add ability to repeated fit models and determine errors with cross validation

    • Add compare plot for plotting error metrics of the various response methods

    • On the 3D plot, allow user to change the values at which the response surface is evaluated at.

  • Optimization Node

    • Expose more optimizer options

    • Add Parallel plot for visualizing optimization attempts

  • Sensitivity Analysis Node

    • Fix SALib imports

    • Add options to plot

  • Overhaul seaborn nodes

  • Code Node

    • Use custom Qt based text editor

    • Address global variable issues

  • Various bug fixes

  • Documentation

19.1.1 - 2019-04-15

  • removed pyearth from dependencies

  • build mfix-plguin doc

  • fix links

  • add video

19.1.0 - 2019-04-11

  • Design of Experiments (DOE)

    • Support geometry parametrization inside MFiX

    • Added genetically optimized latin-hypercube

    • Correctly implemented central composite

    • Include/exclude samples

    • Import/export samples

  • Response Surface Methods (RSM)

    • Supports multiple matrix/response inputs

    • 11 response surface methods available

      • from scikits-learn library:

        • polynomial (with 16 different regressors)

        • Gaussian process model (GPM)

        • multilayer perceptron

        • support vector

        • decision tree

        • random forest

    • from scipy library

      • radial basis function (RBF)

      • nearest

      • cubic

      • linear

    • from pyearth library

      • multivariate adaptive regression splines (MARS)

    • Support fitting multiple models at the same time

    • Assess the quality of the surrogate models constructed through various statistical error metrics calculated and user selectable cross-validation process.

    • Offer the user the selection of which response surface model to be used in the rest of the workflow

  • Optimization

    • Exposed 10 optimization methods in scipy library instead of hard-coding them, including differential evolution

    • “optimize” multiple times with random guesses inside the model space

    • Export results

  • Sensitivity Analysis (SA)

    • Exposed all 5 sensitivity analysis methods implemented in SALib

  • Forward propagation of input uncertainties

    • Handles 7 different type probability density functions (PDF) and user-prescribed distributions for aleatory uncertainties

    • Use any of the DOE methods for epistemic uncertainty

    • Exports the bounds to a file

    • Verified against Ishigami example.

  • Wizard

    • Automatically add and connect nodes for common use cases including

      • Sensitivity analysis

      • Forward propagation of uncertainty

      • Optimization

    • Includes 17 test functions

17.1.1 - 2017-12-14

  • Improve performance with qt 4.8 and python 2.7

  • Remove setTextInteractionFlags flag (only available with Qt 5.1+)

  • Include examples (nc files, code node repo, nodes, and nodewidget usage)

  • Minor documentation fixes

  • Windows menu and desktop icons are now created

  • Fixed issue #45, QtWidgets.QTabBar.RightSide error on Mac

17.1.0 - 2017-12-11

First public release of nodeworks.