Description Usage Arguments Details See Also
Create the process map by analyzing the given eventlog
and extract the nodes by generate_nodes()
and edges by generate_edges()
.
1 2 3 4 5 6 7 8 9 10 |
eventlog |
Event log |
distinct_case |
Whether should count distinct case only. Default is |
distinct_repeated_activities |
Whether should distinct repeat activities. Default is |
target_categories |
A vector contains the target activity categories |
edge_label |
Specify which attribute is used for the edge label. |
edge_width |
Specify which attribute is used for the edge width. |
> eventlog <- data.frame( timestamp = c( as.POSIXct("2017-10-01"), as.POSIXct("2017-10-02"), as.POSIXct("2017-10-03"), as.POSIXct("2017-10-04"), as.POSIXct("2017-10-05"), as.POSIXct("2017-10-06"), as.POSIXct("2017-10-07"), as.POSIXct("2017-10-08"), as.POSIXct("2017-10-09"), as.POSIXct("2017-10-10") ), case_id = c("c1", "c1", "c1", "c1", "c1", "c1", "c1", "c1", "c1", "c1"), activity = c("a", "b", "d", "a", "c", "a", "b", "c", "a", "d"), category = c("campaign", "campaign", "sale", "campaign", "sale", "campaign", "campaign", "sale", "campaign", "sale"), stringsAsFactors = FALSE ) > eventlog timestamp case_id activity category 1 2017-10-01 c1 a campaign 2 2017-10-02 c1 b campaign 3 2017-10-03 c1 d sale 4 2017-10-04 c1 a campaign 5 2017-10-05 c1 c sale 6 2017-10-06 c1 a campaign 7 2017-10-07 c1 b campaign 8 2017-10-08 c1 c sale 9 2017-10-09 c1 a campaign 10 2017-10-10 c1 d sale > p <- create_pmap(eventlog, target_categories = c("sale")) > render_pmap(p)
Or for more complex event log:
> eventlog <- generate_eventlog( size_of_eventlog = 10000, number_of_cases = 2000, categories = c("campaign", "sale"), categories_size = c(8, 2)) > head(eventlog) timestamp case_id activity category 1 2017-01-01 02:40:20 Case 1204 Activity 7 (campaign) campaign 2 2017-01-01 03:10:31 Case 1554 Activity 5 (campaign) campaign 3 2017-01-01 04:01:51 Case 546 Activity 4 (campaign) campaign 4 2017-01-01 05:04:09 Case 1119 Activity 9 (sale) sale 5 2017-01-01 06:43:11 Case 1368 Activity 2 (campaign) campaign 6 2017-01-01 07:43:06 Case 986 Activity 8 (campaign) campaign > str(eventlog) 'data.frame': 10000 obs. of 4 variables: $ timestamp : POSIXct, format: "2017-01-01 02:40:20" "2017-01-01 03:10:31" ... $ case_id: chr "Case 1204" "Case 1554" "Case 546" "Case 1119" ... $ activity : chr "Activity 7 (campaign)" "Activity 5 (campaign)" "Activity 4 (campaign)" "Activity 9 (sale)" ... $ category : chr "campaign" "campaign" "campaign" "sale" ... > p <- create_pmap(eventlog, target_categories = c("sale")) > render_pmap(p)
prune_edges
create_pmap_graph
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