Acces to Telegraphed Gain

[Asrilioss]

Hi,

I didn't find a way to acces to the Telegraphed Gain of the Digitizer channel. I dont know if is possible to do so, I have acces to it if I double click on "Vm_scaled" in Clampfit for exemple it show Signal : Name, Units, V/mV, @ 0 V and telegraphed gain. But accessing it by coding would be perfect.

I ask that to code something how check if the gain didn't change between two folders.

Thanks you,

[Scott W Harden]

Hi @Asrilioss, this may be possible! It's a lot of info, but if you inspect the ABF header like this you may find the variable name you're looking for:

https://swharden.com/pyabf/tutorial/#inspect-the-abf-header

It will generate a report like: https://github.com/swharden/pyABF/blob/main/data/headers/2020_07_29_0062.md#adcsection

[Scott W Harden]

Maybe something like

print(myAbf._adcSection.fTelegraphAdditGain[0])

The 0 is the ADC channel, and you may need to try several numbers to get it right

[Asrilioss]

Yeah I just found that I need to look at header I was looking headerV2 but your faster, thanks you for your answers and a fast one, this work perfectly, do you know if is a value I can change ?
Ty

[Scott W Harden]

this work perfectly

Great to hear! 🚀

do you know if is a value I can change?

Interesting question! I don't think so... that is read when the ABF is first loaded, and all the data is loaded and scaled by that value when the class is initialized, so changing it later probably won't have an effect

pyABF/src/pyabf/abf.py

Lines 466 to 484 in 06247e0

 def _loadAndScaleData(self, fb: BufferedReader): 
     """Load data from the ABF file and scale it by its scaleFactor.""" 
  
     # read the data from the ABF file 
     fb.seek(self.dataByteStart) 
     raw = np.fromfile(fb, dtype=self._dtype, count=self.dataPointCount) 
     nRows = self.channelCount 
     nCols = int(self.dataPointCount/self.channelCount) 
     raw = np.reshape(raw, (nCols, nRows)) 
     raw = np.transpose(raw) 
  
     # if data is int, scale it to float32 so we can scale it 
     self.data = raw.astype(np.float32) 
  
     # if the data was originally an int, it must be scaled 
     if self._dtype == np.int16: 
         for i in range(self.channelCount): 
             self.data[i] = np.multiply(self.data[i], self._dataGain[i]) 
             self.data[i] = np.add(self.data[i], self._dataOffset[i]) 

However you could probably reach in and modify what's in abf.data[channel] based on your needs, then SetSweep() calls later would returned that modified data.

Good luck!