Re-arrange arrays in parallel

## Usage

shift_array(x, along_margin, unit_margin, shift_amount)

## Arguments

x

array, must have at least matrix

along_margin

which index is to be shifted

unit_margin

which dimension decides shift_amount

shift_amount

shift amount along along_margin

## Value

An array with same dimensions as the input x, but with index shifted. The missing elements will be filled with NA.

## Details

A simple use-case for this function is to think of a matrix where each row is a signal and columns stand for time. The objective is to align (time-lock) each signal according to certain events. For each signal, we want to shift the time points by certain amount.

In this case, the shift amount is defined by shift_amount, whose length equals to number of signals. along_margin=2 as we want to shift time points (column, the second dimension) for each signal. unit_margin=1 because the shift amount is depend on the signal number.

## Examples


# Set ncores = 2 to comply to CRAN policy. Please don't run this line

x <- matrix(1:10, nrow = 2, byrow = TRUE)
z <- shift_array(x, 2, 1, c(1,2))

y <- NA * x
y[1,1:4] = x[1,2:5]
y[2,1:3] = x[2,3:5]

# Check if z ang y are the same
z - y
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    0    0    0    0   NA
#> [2,]    0    0    0   NA   NA

# array case
# x is Trial x Frequency x Time
x <- array(1:27, c(3,3,3))

# Shift time for each trial, amount is 1, -1, 0
shift_amount <- c(1,-1,0)
z <- shift_array(x, 3, 1, shift_amount)

if(interactive()){

par(mfrow = c(3, 2), mai = c(0.8, 0.6, 0.4, 0.1))
for( ii in 1:3 ){
image(t(x[ii, ,]), ylab = 'Frequency', xlab = 'Time',
main = paste('Trial', ii))
image(t(z[ii, ,]), ylab = 'Frequency', xlab = 'Time',
main = paste('Shifted amount:', shift_amount[ii]))
}

}