LanaR: API for LANA Process Mining

This package provides an R API for LANA Process Mining.

Attention: This package is still in alpha state. Functions and parameters may be renamed and changed at any time.

Setup

In order to use lanar you need to manually install the packages xml2, plyr using install.packages("xml2", "plyr").

Usage

First upload your event logs to your Lana software. Then enter the log name as a parameter to the different functions as they will use the last uploaded log of that name. Look also at the examples.

Download Sample Event Log

downloads an example event log to your working directory

downloadExample()

A list with all your uploaded logs

getLogs()

id	owner	name	date	timezone
546	34	Incident_withImpactAttributes.csv	2018-09-28T13:19:26.175Z	Etc/GMT
547	34	SalesProcess.csv	2018-09-13T13:27:50.414Z	Europe/Berlin

Filter and performance / followers statistics

filter(logName)

Example

discoveredModel("Incident_withImpactAttributes.csv")

Activity Performance Statistics

gives statistics about activities such as minimum/maximum duration, average/median/total duration, standard deviation and frequency.

activityPerformance(logName)

Example

activityPerformance("Incident_withImpactAttributes.csv")

.id	frequency	totalDuration	minDuration	maxDuration	avgDuration	standardDeviation	median
Initial diagnosis	2337	1270500000	0	1320000	543645.7	238600.5	540000
Functional escalation	851	254640000	0	660000	299224.4	118595.1	300000
Incident closure	2000	1582380000	0	2280000	791190.0	361650.6	780000
Incident classification	2000	497580000	0	900000	248790.0	166740.6	240000
Investigation and diagnosis	851	16600800000	0	60240000	19507403.1	12030401.3	19020000
Incident logging	2000	1079040000	0	2040000	539520.0	389029.4	480000
Resolution and recovery	1635	2944380000	0	6240000	1800844.0	1111854.5	1800000

Aggregation

Aggregation with different dimensions such as: time, attribute, frequency, average duration, median duration, total duration.

aggregate(logName, xDimension, yDimension)

Aggregation Dimensions

Time Dimension	what it does
byTime=byMonth	aggregate by month
byTime=dayOfWeek	aggregate by day of week
byTime=byHour	aggregate by day of week

Aggregation Dimension	what it does
frequency	counts the cases given time dimension
avgDuration	outputs the average duration given time dimension
medianDuration	outputs the median duration given time dimension
totalDuration	outputs the total duration given time dimension

Advanced Optional Dimensions

If you are more experienced with Lana, you can insert any kind of filter that you use in Lana into your aggregation or discovered model functions, by simply adding a tracefilter sequence.

TraceFilterSequence:

Variant Filter

[{"max":max variants,"min":min variants,"type":"variantSliderFilter"}]

Attribute Filter

[{"type":"attributeFilter","attributeName":"attribute name","values":["first value","second value"],"inverted":true or false}]

Case Duration Filter

[{"type":"traceDurationFilter","minTraceDuration":min duration in miliseconds,"maxTraceDuration":max duration in miliseconds}]

Timespan Filter

[{"from":start time in miliseconds,"to":ènd time in miliseconds,"startInRange":true,"endInRange":true,"inverted":false,"type":"timeRangeFilter"}]

Activity Filter

[{"type":"activityFilter","activity":"activity1","inverted":true or false},{"type":"activityFilter","activity":"activity 2","inverted":true or false}]

Follower Filter

[{"direct":true or false,"pre":"from","succ":"to","useDuration":true or false,"inverted":true or false,"type":"followerFilter"}]

Endpoint Filter

[{"type":"endpointFilter","activities":["activity1","activity2"],"inverted":true or false}]

Hide Activities Filter

[{"type":"endpointFilter","activities":["activity1","activity2"],"inverted":true or false}]

Examples

aggregate("Incident_withImpactAttributes.csv", xDimension = "byTime=byMonth", yDimension = "frequency")

byTime=byMonth	frequency	Case Count
Jan 2016	2000	2000

aggregate("Incident_withImpactAttributes.csv", xDimension = "byTime=dayOfWeek", yDimension = "avgDuration")

byTime=dayOfWeek	avgDuration	Case Count
Monday	42516060	2000

aggregate("Incident_withImpactAttributes.csv", xDimension = "byTime=byHour", yDimension = "medianDuration")

byTime=byHour	medianDuration	Case Count
09	42516060	2000
10	42516060	2000
11	42516060	2000
12	42516060	2000
13	42516060	2000
14	42516060	2000
15	42516060	2000
16	42516060	2000

aggregate("Incident_withImpactAttributes.csv", xDimension = "byTime=byMonth", yDimension = "totalDuration")

byTime=byMonth	totalDuration	Case Count
Jan 2016	85032120000	2000

aggregate("Incident_withImpactAttributes.csv", xDimension = "byTime=byMonth", yDimension = "totalDuration", traceFilterSequence = [{"max":```max variants```,"min":```min variants```,"type":"variantSliderFilter"}])

aggregate("Incident_withImpactAttributes.csv", xDimension = "byTime=byMonth", yDimension = "totalDuration", traceFilterSequence = [{"max":```max variants```,"min":```min variants```,"type":"variantSliderFilter"}, {"type":"attributeFilter","attributeName":"```attribute name```","values":["```first value```","```second value```"],"inverted":```false or true```}])