knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
To get started with the nfer R interface, one option is to attach the library.
The recommended way to use nfer, though, is to just specify the nfer namespace
whenever you use an nfer function. Throughout this vignette, we'll use the
nfer namespace.
library(nfer)
There are four functions provided by the nfer package:
load
learn
apply
read
To initialize a specification that can be applied to a dataframe of events, use
the load
function. This function takes two parameters: the path to an nfer
specification file and the log level (optional).
ssps <- nfer::load(system.file("extdata", "ssps.nfer", package = "nfer"))
This specification can then be applied to a dataframe containing events. There should be at least two columns, the first of which is a character type containing the event names, and the second of which is either an integer or a character type containing the event timestamps.
The reason for representing timestamps as strings is that integers in R are limited to 32 bits, so if you need larger numbers (say, if you have millisecond granularity Unix timestamps), they must be character type. Technically numeric type timestamp columns are supported but discouraged, because they risk loss of precision during floating-point conversion. Internally, timestamps are represented by nfer as 64-bit integers. Currently the R wrappers will automatically convert factor columns to character columns.
ssps <- nfer::load(system.file("extdata", "ssps.nfer", package = "nfer")) df <- read.table(system.file("extdata", "ssps.events", package = "nfer"), sep="|", header=FALSE, colClasses = "character") intervals <- nfer::apply(ssps, df) summary(intervals)
If the data frame has more than two columns, the 3rd on will be used as data.
Events will be assigned data values with a name equal to the name of the
column whenever the value in the cell corresponding to that event and column
has a value other than NA. The read
function will load event files
formatted for the command-line version of nfer into a dataframe formatted for
the R version.
test <- nfer::load(system.file("extdata", "ops.nfer", package = "nfer")) ops <- nfer::read(system.file("extdata", "ops.events", package = "nfer")) str(ops) intervals <- nfer::apply(test, ops) summary(intervals)
The nfer mining algorithm can also be used from R using the learn
function.
The function takes a single parameter which is a data frame of events.
There should be two columns, the first of which is a character type
containing the event names, and the second of which is an integer, string, or
numeric type containing the event timestamps. learn
also has the same
optional argument as load
which is the log level.
The specification returned from learn
can then be applied to a trace using
apply
just like if it had been loaded from a specification file.
df <- read.table(system.file("extdata", "ssps.events", package = "nfer"), sep="|", header=FALSE) learned <- nfer::learn(df) intervals <- nfer::apply(learned, df) summary(intervals)
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