Post-processing the data from Paramotopy can, of course, be achieved in any computing environment, from Python to Matlab, or even C++. Presented here are methods for using Matlab to gather generated data from Paramotopy, and store or render.
This portion is being actively improved. For now, please download the zip file of the Matlab functions which comprise the Paramotopy post-processing suite.
Note that each system should be post-processed in its own folder.
Any improvements or suggestions gladly welcomed.
Paramotopy Post-Processing Suite <-------- download here!
Note that each system should be post-processed in its own folder.
Any improvements or suggestions gladly welcomed.
Paramotopy Post-Processing Suite <-------- download here!
Rough instructions:
1) Run Paramotopy to obtain a completed data set.
Get some data!
2) gather_data_paramotopy(filename)
Pulls in the data from the bfiles_filename folder. The data saves to .mat files of version 6. Depending on the problem, the files may be quite large.
3) plot_paramotopy_data
Produces finished plots of both the parameter sample as well as the solution set. May struggle for large data sets. Let me know how I can help!
Need to produce a random sample in your parameter space? try make_mc_sample. The configuration is done within the .m file.
1) Run Paramotopy to obtain a completed data set.
Get some data!
2) gather_data_paramotopy(filename)
Pulls in the data from the bfiles_filename folder. The data saves to .mat files of version 6. Depending on the problem, the files may be quite large.
3) plot_paramotopy_data
Produces finished plots of both the parameter sample as well as the solution set. May struggle for large data sets. Let me know how I can help!
Need to produce a random sample in your parameter space? try make_mc_sample. The configuration is done within the .m file.