- Sep 17, 2019
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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
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- May 24, 2019
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added parallel group add parallel_cost_comp_mpi.py draft example updated dockerfile with MPI updated GA driver test to skip if not MPI
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- May 02, 2019
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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
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- Mar 21, 2019
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Mikkel Friis-Møller authored
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
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- Feb 07, 2019
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- Oct 03, 2018
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