jasmainak
commented
4 years ago The most straightforward way would be to allow an array of the same length as Dipole.times in this function:
Now what's not super obvious to me is how you would do the sequence of these operations:
I was thinking that you could have run your simulation as is, and then just run dipole.scale(factor) twice: first to undo the scaling that was done and then to apply the scaling you'd like. But the problem now is that there are a bunch of other operations that sandwich the scaling.
I think the best approach would be to add an option postprocess=True/False/None (use what param file says) to simulate_dipole. Then as a user, you would do:
dpls = simulate_dipole(postprocess=False)
dpls = [dpl.scale(fancy_scaling_factor) for dpl in dpls]
I'd like to be able to change the scaling parameter within a simulation.
In my particular example, the ERP I'm looking to simulate might be containing (more or less) separate early and late dynamics, with later parts of the waveform recruiting a much larger neural population. To account for that, I'd like to scale different time intervals of the dipole by different factors.