Generate graph layout

Generate a tidy_layout for a SEM graph.

# S3 method for lavaan
get_layout(x, ..., layout_algorithm = "layout_as_tree")

get_layout(x, ...)

# S3 method for default
get_layout(x, ..., rows = NULL)

Arguments

x

An object for which a method exists; currently, methods exist for character, lavaan, and mplus.model objects.

...

Character arguments corresponding to layout elements. Use node names, empty strings (""), or NA values.

layout_algorithm

Optional argument for fit model objects. Character string, indicating which igraph layout algorithm to apply to position the nodes. Defaults to "layout_as_tree"; see details for more options.

rows

Numeric, indicating the number of rows of the graph.

Value

Object of class 'tidy_layout'

Details

There are three ways to generate a layout:

1. Specify the layout in the call to get_layout() by providing node names and the number of rows to create a layout matrix. Empty strings ("") or NA can be used for empty cells. See Example 1.

2. Call get_layout() on a model object or tidy_results object. It will use the function layout_as_tree, or any other layout function from the igraph package, to generate a rudimentary layout. See Example 2.

3. Instead of using get_layout(), just use a matrix or data.frame with your layout. For example, specify the layout in a spreadsheet program, and load it into R (see Example 3). Or, copy the layout to the clipboard from your spreadsheet program, and load it from the clipboard (see Example 4)

The layout algorithms imported from igraph are: c("layout_as_star", "layout_as_tree", "layout_in_circle", "layout_nicely", "layout_on_grid", "layout_randomly", "layout_with_dh", "layout_with_fr", "layout_with_gem", "layout_with_graphopt", "layout_with_kk", "layout_with_lgl", "layout_with_mds"). These can be used by specifying the optional argument layout_algorithm = "".

Examples

# Example 1
get_layout("c", NA,  "d",
           NA,  "e", NA, rows = 2)
#>      [,1] [,2] [,3]
#> [1,] "c"  NA   "d" 
#> [2,] NA   "e"  NA  
#> attr(,"class")
#> [1] "layout_matrix" "matrix"        "array"        

# Example 2
library(lavaan)
fit <- cfa(' visual  =~ x1 + x2 + x3 ',
           data = HolzingerSwineford1939[1:50, ])
#> Warning: lavaan WARNING: some estimated ov variances are negative
get_layout(fit)
#>      [,1] [,2]     [,3]
#> [1,] NA   "visual" NA  
#> [2,] "x1" "x2"     "x3"
#> attr(,"class")
#> [1] "layout_matrix" "matrix"        "array"        

if (FALSE) {
# Example 3
# Here, we first write the layout to .csv, but you could create it in a
# spreadsheet program, and save the spreadsheet to .csv:
write.csv(matrix(c("c", "",  "d", "",  "e", ""), nrow = 2, byrow = TRUE),
          file = file.path(tempdir(), "example3.csv"), row.names = FALSE)
# Now, we load the .csv:
read.csv(file.path(tempdir(), "example3.csv"))

# Example 4
# For this example, make your layout in a spreadsheet program, select it, and
# copy to clipboard. Reading from the clipboard works differently in Windows
# and Mac. For this example, I used Microsoft Excel.
# On Windows, run:
read.table("clipboard", sep = "\t")
# On Mac, run:
read.table(pipe("pbpaste"), sep="\t")
}