reviewNeuronsInteractive: Manually classify the identified neurons from SCALPEL.
In scalpel: Processes Calcium Imaging Data

Description Usage Arguments Value See Also Examples

We interactively review the set of identified neurons that result from either Step 2 or 3 of SCALPEL in order to manually classify them according to whether they appear to be real neurons or not. To do this, the frame from which the dictionary element was derived is plotted. The user can manually classify the neuron as real or not, or indicate that additional frames are needed to make the classification, in which case the reviewNeuronsMoreFrames function can subsequently be used. A similar manual classification can be done non-interactively using reviewNeurons.

1	reviewNeuronsInteractive(scalpelOutput, neuronSet)

`scalpelOutput`	An object returned by one of the SCALPEL functions: `scalpel`, `scalpelStep2`, or `scalpelStep3`.
`neuronSet`	The set of neurons that should be reviewed: use `"A"` for those resulting from `scalpelStep2` and saved as `scalpelOutput$A`, or use `"Afilter"` for those resulting from `scalpelStep3` and saved as `scalpelOutput$Afilter`. This argument is ignored if the class of `scalpelOutput` is `scalpelStep2`.

None

For other functions useful in the classification process, see reviewNeuronsMoreFrames, reviewOverlappingNeurons, and updateNeuronsInteractive. Once classification is finished, the argument neuronsToOutline="kept" can be used with plotBrightest and plotVideoVariance, and the argument neuronsToDisplay="kept" can be used with plotResults, plotResultsAllLambda, plotTemporal, and plotSpatial. Finally, the argument excludeReps="discarded" allows the discarded dictionary elements to be excluded from the sparse group lasso model when running scalpelStep3.

## Not run: 
### many of the functions in this package are interconnected so the
### easiest way to learn to use the package is by working through the vignette,
### which is available at ajpete.com/software

#assumes you have run the example for the "scalpel" function

#we review the set of spatial components from Step 2,
#which are contained in scalpelOutput$A
reviewNeuronsInteractive(scalpelOutput = scalpelOutput, neuronSet = "A")
#enter "Y" for the first neuron and then "Q"
#entering "Q" allows us to finish manually classifying later using the same command
#this time there are fewer left to review
reviewNeuronsInteractive(scalpelOutput = scalpelOutput, neuronSet = "A")
#enter "N" for the first and "?" for the second this time
#note that once a neuron is classified as "N", it disappears from the plot

## End(Not run)