I have temporarily abandoned vectfit and aaa since I've been pretty unsuccessful with them and I don't need poles/zeroes to find the unity gain frequency. Instead I'm just fitting the transfer function linearly (on a log-log scale). I've found the UGF at about 5.5 kHz right now, using old data - next step is to get the Red Pitaya working so I can take data with that. Also need to move this code from matlab to python. Uncertainty's propagated using the 95% confidence bounds given by the fit, using curvefit - so just from the standard error, and all points are weighted equally. Ideally would like to propagate uncertainty accounting for the coherence data too, but haven't figured out how to do that correctly yet.

[UPDATE 7/22/2022: added raw data files]

# SR785 Measurement - Timestamp: Jun 29 2022 - 11:40:42
# Parameter File: TFSR785template.yml
#---------- Measurement Setup ------------
# Start frequency (Hz) = 100000.000000
# Stop frequency (Hz) = 100.000000
# Number of frequency points = 30
# Excitation amplitude (mV) = 10.000000
# Settling cycles = 5
# Integration cycles = 100
#---------- Measurement Parameters ----------

# SR785 Measurement - Timestamp: Jun 29 2022 - 11:56:50
# Parameter File: TFSR785template.yml
#---------- Measurement Setup ------------
# Start frequency (Hz) = 100000.000000
# Stop frequency (Hz) = 2000.000000
# Number of frequency points = 300
# Excitation amplitude (mV) = 5.000000
# Settling cycles = 5
# Integration cycles = 200
#---------- Measurement Parameters ----------