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.
23.1.0 - 2023-12-15¶
Fix deprecated numpy objects np.int, np.float
Cast variables to ints for Qt calls
22.1.0 - 2022-06-08¶
New nodes
Parallel coordinates plot (matplotlib)
Add Node creator to help create new nodes
Include/exclude points from histogram in NN regressor and response surface Nodes
Fix NN regressor option in wizard
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.