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Nicolo Grilli Michael Salvini University of Bristol 10 Aprile 2022 Code to optimize x-y data variables obtained from an external solver against experimental data Installation: git clone the repository Usage: Put the simulation files in an arbitrary folder, it must contain a template file from which the input or parameter file will be generated and all other necessary files for your simulation Set properly the parameters in /src/main.py The template file will contain strings like {name_of_my_parameter} that will be substituted by numbers during the optimization iterations. An arbitrary number of these parameters can be specified in the template file and the names must correspond to the ones in the corresponding string in main.py order does not matter Open a terminal in the folder with the simulation files and run: python ~/path/to/src/main.py
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This is a python code similar to Dakota optimization tool
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