causal_net | R Documentation |
Creates a Causal net, also known as Heuristics net. This is similar to a processmapR process map.
However, the causal map deals with parallelism by trying to identifying causal dependencies
between activities by using different heuristics as documented in dependency_matrix
.
causal_net(
eventlog = NULL,
dependencies = dependency_matrix(eventlog = eventlog, threshold = threshold,
threshold_frequency = threshold_frequency, ...),
bindings = causal_bindings(eventlog, dependencies),
threshold = 0.9,
threshold_frequency = 0,
type = causal_frequency("absolute"),
sec = NULL,
type_nodes = type,
type_edges = type,
sec_nodes = sec,
sec_edges = sec,
...
)
eventlog |
The event log for which a causal map should be computed.
Can be left NULL for more control if parameters |
dependencies |
A dependency matrix created for the event log, for example, by |
bindings |
Causal bindings created by |
threshold |
The dependency threshold to be used when using the default dependency matrix computation. |
threshold_frequency |
The frequency threshold to be used when using the default dependency matrix computation. |
type |
A causal map type. For example, |
sec |
A causal process map type. Values are shown between brackets. |
type_nodes |
A causal map type to be used for nodes only. |
type_edges |
A causal map type to be used for edges only. |
sec_nodes |
A secondary causal map type for nodes only. |
sec_edges |
A secondary causal map type for edges only. |
... |
Further parameters forwarded to the default |
Warning: Projected frequencies are heuristically determined and counts may not add up.
A DiagrammeR graph of the causal map.
# Causal map with default parameters
causal_net(L_heur_1)
# Causal map with lower dependency treshold
causal_net(L_heur_1, threshold = .8)
# For even more control omit the `eventlog` parameter
# and provide `dependencies` and `bindings` directly.
d <- dependency_matrix(L_heur_1, threshold = .8)
causal_net(dependencies = d,
bindings = causal_bindings(L_heur_1, d, "nearest"))
# The returned DiagrammeR object can be further augmented with
# panning and zooming before rendering:
library(magrittr)
causal_net(L_heur_1) %>%
render_causal_net(render = TRUE) %>%
DiagrammeRsvg::export_svg() %>%
svgPanZoom::svgPanZoom()
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