A post-fit display transform: in the plane of two dimensions, pushes every node out along its own ray to the length of the longest node there, then recomputes the centroids for the moved nodes. Nothing is refit.
Arguments
- set
An
ena.set, e.g. frommodelorena.make.set.- dimension_name_1
Name of the plane's x dimension (a column of
set$rotation$nodes). Defaults to the first dimension.- dimension_name_2
Name of the plane's y dimension. Defaults to the second dimension.
Details
Nodes of length zero in the plane are left where they are, as are the
nodes' other dimensions. Unit points never change. The centroids, all
dimensions of them, are the model's node weights times the moved nodes:
each unit's line weights split between the codes they connect (half to
each code for unordered networks; for ordered ones, as the fit weights
them) and normalised to sum to 1, the weighting the fit's own centroids
use. So the goodness of fit (ena.correlations) reflects the
moved nodes.
Works for unordered and ordered (accumulate(ordered = TRUE)) sets.
See also
move_nodes_to_unit_circle_with_equal_space, which
also spaces the nodes equally around the circle.
Examples
data(RS.data)
codes <- c("Data", "Technical.Constraints", "Performance.Parameters",
"Client.and.Consultant.Requests", "Design.Reasoning",
"Collaboration")
set <- RS.data |>
accumulate(c("Condition", "UserName"), codes, c("Condition", "GroupName")) |>
model()
circled <- move_nodes_to_unit_circle(set)
circled$rotation$nodes
#> code GMR1 SVD2
#> <ena.metadata> <ena.dimension> <ena.dimension>
#> 1: Data -1.2288590 2.2507655
#> 2: Technical.Constraints 2.5282696 0.4288275
#> 3: Performance.Parameters -1.9625687 1.6505647
#> 4: Client.and.Consultant.Requests 2.3562894 -1.0118994
#> 5: Design.Reasoning -0.7387656 -2.4556599
#> 6: Collaboration 2.3739906 0.9696434
#> SVD3 SVD4 SVD5 SVD6
#> <ena.dimension> <ena.dimension> <ena.dimension> <ena.dimension>
#> 1: 1.2807440 1.1640657 -0.2029861 -1.0705435
#> 2: 0.4206256 -0.2257657 0.5907393 0.8756449
#> 3: -1.9294636 -1.2042659 -0.1085039 0.8685388
#> 4: -1.2335528 2.5802575 -0.4803029 0.0172686
#> 5: 0.6321945 -0.1218005 -0.4144112 -0.2435283
#> 6: -1.2028630 -0.6075374 0.9781716 -2.2400848
#> SVD7 SVD8 SVD9 SVD10
#> <ena.dimension> <ena.dimension> <ena.dimension> <ena.dimension>
#> 1: 0.1646893 0.04657726 -0.3767116 0.01817665
#> 2: -0.5148106 0.05936838 0.4915882 -0.18065112
#> 3: 0.1188862 0.07209038 0.1198674 0.14974249
#> 4: -0.8552341 0.43325316 0.2561674 -0.16171048
#> 5: 0.2518516 -0.16308794 -0.2388267 0.04348831
#> 6: 0.8834779 -0.40519726 -0.3698339 0.10555547
#> SVD11 SVD12 SVD13 SVD14
#> <ena.dimension> <ena.dimension> <ena.dimension> <ena.dimension>
#> 1: 0.20318987 -0.14582546 -0.05718423 -0.17749422
#> 2: -0.20853657 0.10247404 0.06380652 0.25275220
#> 3: -0.04843653 0.10359794 0.02537574 0.03122439
#> 4: 0.10364731 -0.11645697 0.03713176 0.02792928
#> 5: 0.05893082 -0.07362241 -0.03282032 -0.11548123
#> 6: -0.03357836 0.15763841 -0.04942987 -0.06425475
#> SVD15
#> <ena.dimension>
#> 1: 0.002258103
#> 2: 0.024996104
#> 3: -0.008222128
#> 4: 0.039426150
#> 5: -0.031753530
#> 6: 0.023451595
