Parallel data generation: Unexpected behavior of Numpy random generator seed

[BernardoFerreira]

Problem:
When using the 'parallel' option to generate data with f3dasm, i.e.,

experiment_data.evaluate(data_generator=my_generator, mode='parallel')

it seems that the numpy random seed is NOT being randomized in each parallel process as expected (getting the same outcome of numpy random processes in all parallel jobs!).

Potential solution:
Reseed NumPy random generator in DataGenerator class methods with np.random.seed().