Description Methods Author(s) Examples
PipelineData
is a virtual class representing a dataset with an
attached pipeline that describes the series of steps that produced the
object. The storage of the data is up to the implementation. The
methods described here apply equally to PipelineData
and any
other object that has pipeline
as a slot/attribute.
pipeline(object, ancestry = TRUE, local = TRUE)
:
Gets the pipeline that produced the object. If ancestry
is
TRUE
, the returned pipeline includes the protocols that
produced predecessors of a different type. If local
is TRUE
, the pipeline includes protocols after the last
protocol that output an object of a different type, i.e., all
local protocols have this type as both their input and output.
explore(object)
:
Produces an interactive, exploratory visualization of this data,
in the context of the last applied protocol.
Michael Lawrence
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | ## A non-PipelineData data example
setStage("average", intype = "numeric")
setProtocol("mean", fun = mean, parent = "average")
setProtocol("quantile", representation = list(probs = "numeric"),
fun = quantile, parent = "average")
setProtocol("range", representation = list(low = "numeric", high = "numeric"),
fun = function(x, low = 0, high = Inf) x[x >= low & x <= high],
parent = setStage("trim", intype = "numeric"))
d <- c(1, 2, 4)
p <- Pipeline("trim", "average")
d2 <- perform(p, d)
attr(d2, 'pipeline')
pipeline(d2)
## Not run:
## this will give an error, no slot called pipelinem, just numeric value.
d2@pipeline
## End(Not run)
setClass("ProcessNumeric", contains = c("numeric", "PipelineData"))
d <- new("ProcessNumeric", c(1, 2, 4))
d@pipeline
setStage("average", intype = "ProcessNumeric")
setProtocol("mean", fun = function(x) new("ProcessNumeric", mean(x)), parent = "average")
setProtocol("quantile", representation = list(probs = "numeric"),
fun = function(x) new("ProcessNumeric", quantile(x)), parent = "average")
setProtocol("range", representation = list(low = "numeric", high = "numeric"),
fun = function(x, low = 0, high = Inf) new("ProcessNumeric",
x[x >= low & x <= high]),
parent = setStage("trim", intype = "ProcessNumeric"))
p <- Pipeline("trim", "average")
d2 <- perform(p, d)
attr(d2, 'pipeline')
pipeline(d2)
class(d2)
d2@pipeline
|
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