Mikkel Friis-Møller authored 5 years ago and Riccardo Riva committed 5 years ago

Added initial implementation of the predict functions

Fixed pep8

WIP on implementing the evaluation of a surrogate based on a dictionary

Added option for evaluating a surrogate model with a dictionary

Added option for using MinMaxScaler and not only StandardScaler. Improved documentation

Added one more surrogate type, fixed output type and PEP8

Initial implementation of predict_gradient for OpenTURNS metamodels. Improved documentation and clarified names

Bugfix to predict functions and refractoring

Bugfix and improved exceptions

Added documentation for finite differences (to be implemented)

Added implementation for the step size parameters

Added implementation for finite differences

Added step size and output scaling.

Fixed TypeError: 'staticmethod' object is not callable
thanks to https://stackoverflow.com/a/41921291/3676517

Removed class SurrogateEvaluation and placed all of its content in the load module

new structure to allow for load constraints

finished new structure and updated tests

included aggregated_cost.py

Added function to compute the relative and absolute errors

removed try except from load constraints and added setup requirement: openturns vers. >= 1.13

working on ex 8

Added SurrogateModel class

passing input vals to load component to get the shapes right

Added  warning for extrapolation

Added first test for load module

Added test and fixed a bug

Added another test

Added test for SurrogateModel class

Added first test for predict_gradient() and fixed a bug

Added test for PCE

Fixed test_PCE()

Added test for MLPRegressor

Improved test

Added test for wrong input type

Added test for input domain boundary

Added test for unknown model type

Improved test for PCE and neural network

Added test for input and output scaler

Fixed predict_gradient() if there is an input_scaler. Remove code for finite differences, since they will be computed with OpenMDAO

Fixed ouput_scaler in predict_gradient()

added test of load constraint

Added more test

Improved test

coverage up + pep8

added docstrings

pep8

fixed loose connection of post constraint in some cases

Fixed behavior of scikit-learn neural network in case of 1D output

PEP8

Mikkel Friis-Møller authored 5 years ago and Mads M. Pedersen committed 5 years ago

added parallel group
add parallel_cost_comp_mpi.py draft example
updated dockerfile with MPI
updated GA driver test to skip if not MPI

Mikkel Friis-Møller authored 5 years ago and Mads M. Pedersen committed 5 years ago

Added possibility to specify units
Created examples/docs/example_5_floris.py where floris and pywake are compared

added Plant Energy and Floris to CI-image

moved example data files

resat topfarmkeys after example 6 ran

updated no_print statement

added plantenergy to ci-file to catch changes
added search for topfarm.plugins to the init-file

fix pep8

figs

extended possible design variable input types:
[value]
[(value,'unit')
[(value, lower, upper)]
[(value, lower, upper, unit)]

updated example 6 accordingly

established TopFarmGroup class for integrated optimization
created example_4_integrated_optimization_aep_and_irr.py

fixed pep8 and iir-example

Introduced Penalty Component
Various updates to facilitate the modular approach

fixed penalty function

fixed failing tests

fixed more failing tests

updated fuga/recorder tests to account for the new structure and increased number of elements in the recorder.

upd. the input keys

improved coverage