Description Usage Arguments Details See Also
Prune edges based on given percentage
1 | prune_edges(p, percentage = 0.2, max = -1)
|
p |
process map object created by |
percentage |
how many percentage of the edges should be pruned. |
max |
set max number of edges to keep. If |
Create an event log
> library(dplyr) > library(pmap) > eventlog <- generate_eventlog( size_of_eventlog = 10000, number_of_cases = 2000, categories = c("campaign", "sale"), categories_size = c(10, 4)) > head(eventlog) timestamp case_id activity category 1 2017-01-01 02:14:50 Case 345 Activity 1 (campaign) campaign 2 2017-01-01 02:26:24 Case 1625 Activity 2 (campaign) campaign 3 2017-01-01 03:48:12 Case 1901 Activity 12 (sale) sale 4 2017-01-01 03:57:54 Case 1029 Activity 10 (campaign) campaign 5 2017-01-01 07:46:54 Case 215 Activity 10 (campaign) campaign 6 2017-01-01 09:44:51 Case 1354 Activity 1 (campaign) campaign > str(eventlog) 'data.frame': 10000 obs. of 4 variables: $ timestamp : POSIXct, format: "2017-01-01 02:14:50" "2017-01-01 02:26:24" ... $ case_id: chr "Case 345" "Case 1625" "Case 1901" "Case 1029" ... $ activity : chr "Activity 1 (campaign)" "Activity 2 (campaign)" "Activity 12 (sale)" "Activity 10 (campaign)" ... $ category : chr "campaign" "campaign" "sale" "campaign" ...
Create a process map from the event log and render it directly.
> p <- create_pmap(eventlog, target_categories = c("sale")) > render_pmap(p)
As you can see the activity map is very messy. Let's apply the prune_edges()
to remove 50 percent edges.
> p %>% prune_edges(0.5) %>% render_pmap()
It's cleaner, we can clean it further by remove 50 percent nodes with prune_nodes()
function.
> p %>% prune_nodes(0.5) %>% prune_edges(0.5) %>% render_pmap()
One thing should be noticed, the order of pruning nodes and edges matters.
prune_nodes
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