in CleeseBPF.py: createBPF, eq format is t,nbband, and all (f,g) pairs as a single row, while other transforms store bpfs as (t,gain) pairs in different rows. This is justified because eq transformations are 2-dimensional, with times and frequencies, but it creates difficulties in subsequent experimental code and cannot be loaded as a simple pandas Dataframe. Perhaps better stored as t,f,gain triplets on successive rows ?
update: the criteria for whether that or the alternative is the best format is ease of integration with palin kernel methods, which should be able to process experiments like smileEQ
jjau
commented
5 months ago
in CleeseBPF.py: createBPF, eq format is t,nbband, and all (f,g) pairs as a single row, while other transforms store bpfs as (t,gain) pairs in different rows. This is justified because eq transformations are 2-dimensional, with times and frequencies, but it creates difficulties in subsequent experimental code and cannot be loaded as a simple pandas Dataframe. Perhaps better stored as t,f,gain triplets on successive rows ?