Calculating the Average of Continuous Channels

By Nex Technologies | November 06, 2017

One of the frequently asked questions is how to calculate the average of multiple continuous channels in NeuroExplorer. Prior to NeuroExplorer version 5.104, we had to use a rather cumbersome function LinearCombinationOfContVars. For example, to calculate the average of channels FP01 and FP02 we would execute this script line:

nex.LinearCombinationOfContVars(doc, "average of FP01 and FP02", doc["FP01"], 0.5, doc["FP02"], 0.5)

Fortunately, Python is a very flexible language. After an update of NeuroExplorer internal Python code (that uses new functions ContAdd, ContMult and ContAddCont), it is now possible to use arithmetic expressions using continuous channels:

import nex
doc = nex.GetActiveDocument()

# average of two channels
doc["average of FP01 and FP02"] = (doc["FP01"]+doc["FP02"])/2.0

# subtract a constant baseline
baseline = 100
doc["FP01 with baseline subtracted"] = doc["FP01"]-baseline

# subtract the reference channel
referenceChannelName = 'FP16'
doc["FP01 with ref. channel subtracted"] = doc["FP01"]-doc[referenceChannelName]

# calculate the average of all continuous channels containing FP in channel name
count = 0
for i in range(nex.GetVarCount(doc, 'continuous')):
 name = nex.GetVarName(doc, i+1, 'continuous')
 if 'FP' in name:
   if count == 0:
     doc['FP average'] = doc[name]
   else:
     doc['FP average'] += doc[name]
   count += 1
 
if count > 0:
 doc['FP average'] = doc['FP average']/float(count)

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