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Hi! Thank you for taking the time to port this to Python :)
I am however a bit confused, since I thought Ledalab implemented an algorithm that constrained the phasic driver to be non-negative (since negative sudomotor nerver activations make no sense). The current output, that I can get with leda2.analysis.phasicDriverRaw is not non-negative and very dense, I assume because it perfectly reconstructs the data when summed with the tonic component
You can see what I mean with the green curve here.
Any pointers on how to better specify what analysis I want from Ledapy ?
The text was updated successfully, but these errors were encountered:
Hi! Thank you for taking the time to port this to Python :)
I am however a bit confused, since I thought Ledalab implemented an algorithm that constrained the phasic driver to be non-negative (since negative sudomotor nerver activations make no sense). The current output, that I can get with
leda2.analysis.phasicDriverRaw
is not non-negative and very dense, I assume because it perfectly reconstructs the data when summed with the tonic componentYou can see what I mean with the green curve here.
Any pointers on how to better specify what analysis I want from Ledapy ?
The text was updated successfully, but these errors were encountered: