getLoops: Extract, Plot and Manipulate Labels for Feedback Loops in a...

In jarrod-dalton/causalloop:

Extract, Plot and Manipulate Labels for Feedback Loops in a Causal Loop Diagram

Usage

getLoops(x, S = 100, nsteps = 6)

setLoopLabel(FBL, loopIx, label)

## S3 method for class 'feedbackLoops'
plot(FBL, ...)

Arguments

x	a CLD object
S	number of loop traversals (random walks on directed graph) to be simulated, originating from each variable in the CLD.
nsteps	number of steps for each loop traversal. Setting this to larger values (e.g., 10 or 15) tends to yield a larger number of identified loops, many of which involve large numbers of variables. The default value of 6 tends to yield simpler loop structures (which contain up to a maximum of 6 variables).
FBL	A feedbackLoops object (i.e., object outputted from getLoops())
loopIx	Loop index. When getLoops() is run, each loop is assigned an index. The function setLoopLabel will take a loopIx as input. The loop indices are always displayed in the plot method.
label	Label to assign to a feedback loop in setLoopLabel().

Details

This function applies a particle-based approach to identifying loops (cycles) within a causal loop diagram. Random walks are generated, initiated at each variable, and any cycles that are identified are retained and numbered.

Value

a list of 2-element lists, each with element [[1]] containing a feedback loop and element [[2]] containing the loop's type (i.e., either "balancing" or "reinforcing"). Balancing loops have an odd number of links with negative polarity, and reinforcing loops have an even number of links with negative polarity.

Examples

edges <- tibble::tribble(
~from, ~to, ~polarity,
1,2,1,
1,5,1,
1,8,1,
2,3,-1,
2,7,1,
2,9,1,
3,1,1,
3,2,1,
3,4,1,
3,6,-1,
4,5,1,
5,2,1,
6,4,1,
8,9,-1,
9,8,1
)
txtedges <- edges %>% dplyr::mutate(from = letters[from], to = letters[to])
z <- CLD(txtedges$from, txtedges$to, polarity = txtedges$polarity)
loops <- getLoops(z)
loops <- setLoopLabel(loops, loopIx = 5, label = "BCFdE!")

jarrod-dalton/causalloop documentation built on May 10, 2022, 8:08 a.m.