Getting started with nfer
In nfer: Event Stream Abstraction using Interval Logic

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)