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##' Average by session
##'
##' Calculates the average estimate per session or block of trials
##'
##' @param estimate Series of estimates in event time
##' @param sessionBoundaries Vector of the starting indices for each session
##' (which means to include the end, the last value should be length(estimate) + 1)
##' @return Vector of average estimate for each session
##' @export
##' @author Chloe Bracis
##' @examples
##' # Create vector of values (i.e. estimates, respones, etc.)
##' values = runif(100)
##' # Specify sessions, here a group of 10 trials
##' sessionBoundaries = seq(1, 101, 10)
##' valuesBySession = averageBySession(values, sessionBoundaries)
averageBySession = function( estimate, sessionBoundaries )
{
# can pass in NA to skip averaging by session, but still called in model fitting
if ( all( is.na( sessionBoundaries ) ) )
{
avg = estimate
} else
{
avg = sapply( 1:( length( sessionBoundaries ) - 1 ),
function( x ) if ( !is.na( sessionBoundaries[x] )
&& !is.na( sessionBoundaries[x + 1] ) )
mean( estimate[sessionBoundaries[x]:( sessionBoundaries[x + 1] - 1 )] ) )
}
return( unlist( avg ) )
}
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