Makes sense, so I'd be doing everything at the sample-level For layers, I could have an array that represents "gain automation" for each layer, and then let nu

Makes sense, so I'd be doing everything at the sample-level For layers, I could have an array that represents "gain automation" for each layer, and then let numpy do `track_a * gain_a + track_b * (1-gain_a)` for the whole output in one go. And I'd create silences by inserting 0's (and making sure that I'm inserting them after a zero crossing point to avoid clicks) I'm prone to NIH :-) but I'll also try to see if something like this exists. But at least -- it's clearly do-able/prototype-able! Thank you