Hi,
I am currently trying to learn how to do spot pattern indexing using the kinematic diffraction from diffsims.
However, depending how finely I want to discretize the reduced fundamental orientation sector, the computation time for running
diffsims.generators.simulation_generator.SimulationGenerator().calculate_diffraction2d()
can take up a lot of memories and time (especially when the laptop is poor). Hence, I would like to run this simulation process on a cluster instead and then load the simulated results into the Jupyter notebook for indexing. Is such a thing possible to do? If so, how should I save the output object which seems to be
diffsims.simulations.simulation2d.Simulation2D
and how should I load it again?
Hi,
I am currently trying to learn how to do spot pattern indexing using the kinematic diffraction from
diffsims.However, depending how finely I want to discretize the reduced fundamental orientation sector, the computation time for running
can take up a lot of memories and time (especially when the laptop is poor). Hence, I would like to run this simulation process on a cluster instead and then load the simulated results into the Jupyter notebook for indexing. Is such a thing possible to do? If so, how should I save the output object which seems to be
and how should I load it again?