Jan Kwakkel

if it says running sequentially, you are not using multiprocessing. Can you try one of the pure python examples that come with the workbench (e.g., the lake problem)?

you really need to provide much more context. For example, are you using notebooks, a normal script, can you show the exact code? Also why not try to make it...

please show the full code, not snippets. My hunch is that you miss ```python if __name__ == '__main__': # model definition and run code needs to go here ```

I now have a working prototype in the branch [output_space_exploration](https://github.com/quaquel/EMAworkbench/tree/output_space_exploration). There is still some work to be done including some more testing of the algorithm itself, documenting the code, and...

No, Rhodium is actually a python port of openMORDM, an R package (https://doi.org/10.1016/j.envsoft.2015.07.014 https://github.com/OpenMORDM/OpenMORDM). The workbench started already in 2010 and has a much longer history. I have had a...

If you have any further questions, just post them here or contact me by e-mail. I will include a discussion on Rhodium in the documentation as soon as possible.

can't this be achieved by simply setting the numpy random seed globally? I agree it would be a useful features

So, I quickly checked the code. Sampling relies entirely on scipy.stats or numpy.random. Scipy.stats uses the global numpy random state, so setting the global numpy random state should be sufficient...

I completely agree with the use case. Thread safety is no concern for sampling: it only happens in the main thread. Farming out to other processes / threads happens after...

So I ran a quick test using the inter temporal version of the lake problem and setting the global numpy random state. This works: it produces the exact same results....