chunk.blocks: Organize Data in Chunks
In haberdashPI/wright.lab.util: A set of utilitiy functions used in our lab.

TODO

1	chunk.blocks(data, chunk.size, condition = "condition", day = "day", block = "block", day.chunk = "day.block", chunk = "chunk")

`data`
`chunk.size`
`condition`
`day`
`block`
`day.chunk`
`chunk`

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (data, chunk.size, condition = "condition", day = "day", 
    block = "block", day.chunk = "day.block", chunk = "chunk") 
{
    maximums = droplevels(aggregate(data[, block], by = list(condition = data[, 
        condition], day = data[, day]), max))
    conditions = as.character(unique(maximums$condition))
    num.days = length(unique(maximums$day))
    block.max = array(dim = c(length(conditions), num.days))
    index = 0
    for (cond in conditions) {
        index = index + 1
        days = rep(0, num.days)
        d = subset(maximums, condition == cond)
        days[d$day + 1] = ceiling(d$x/chunk.size)
        block.max[index, ] = c(0, cumsum(days)[1:(num.days - 
            1)])
    }
    rownames(block.max) = conditions
    new.data = data
    new.data[, day.chunk] = floor(new.data[, block]/chunk.size) + 
        diag(block.max[as.character(new.data[, condition]), new.data[, 
            day] + 1])
    new.data[, chunk] = floor(new.data[, block]/chunk.size)
    list(data = new.data, block.max = block.max)
  }