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An S3 class and constructors for Reeb graphs

reeb_graph.Rd

This is an S3 class with associated constructors for a data structure to represent Reeb graphs in R.

Usage

reeb_graph(values, edgelist)

# S3 method for class 'reeb_graph'
print(x, ..., n = NULL, minlength = 12L)

# S3 method for class 'reeb_graph'
format(x, ..., n = NULL, minlength = 12L)

read_reeb_graph(file)

Arguments

values

Numeric vector of function values at vertices; may have names, which may be duplicated and/or missing.

edgelist

2-column integer matrix of linked vertex pairs.

x

Object of class reeb_graph.

...

Additional arguments passed to base::format().

n

Integer number of edges to print.

minlength

Minimum name abbreviation length; passed to base::abbreviate().

file

A plain text file containing Reeb graph data formatted as at ReebGraphPairing.

Value

An object of class "reeb_graph", which is a list of two elements:

  • values: Numeric vector of function values at vertices, optionally named.

  • edgelist: 2-column integer matrix of linked vertex pairs.

Details

Vertex indices start at zero, for consistency with examples. The positions of values and the integer values in edgelist will correspond to the same vertices; length(values) must bound max(edgelist).

The S3 class is a list of "values" and "edgelist". The print() method prints one edge per line, with nodes formatted as "index[name] (value)"

References

https://github.com/USFDataVisualization/ReebGraphPairing/

See also

as_reeb_graph()

Examples

x <- reeb_graph(
  values = c(a = 0, b = .4, c = .6, d = 1),
  edgelist = rbind( c(1,2), c(1,3), c(2,4), c(3,4))
)
print(x)
#> Reeb graph with 4 vertices and 4 edges on [0,1]:
#> 1[a] (0.0) -- 2[b] (0.4)
#> 1[a] (0.0) -- 3[c] (0.6)
#> 2[b] (0.4) -- 4[d] (1.0)
#> 3[c] (0.6) -- 4[d] (1.0)
#> 

t10 <- system.file("extdata", "10_tree_iterations.txt", package = "rgph")
( y <- read_reeb_graph(t10) )
#> Reeb graph with 41 vertices and 40 edges on [0,152.2565]:
#>  1 ( 0.000000) --  2 ( 1.386294)
#>  1 ( 0.000000) -- 14 (36.946803)
#>  2 ( 1.386294) --  3 ( 3.295837)
#>  3 ( 3.295837) --  4 ( 5.545177)
#>  3 ( 3.295837) --  5 ( 8.047190)
#>  4 ( 5.545177) --  6 (10.750557)
#>  6 (10.750557) --  7 (13.621371)
#>  7 (13.621371) --  9 (19.775021)
#>  7 (13.621371) --  8 (16.635532)
#>  8 (16.635532) -- 18 (52.026692)
#>  9 (19.775021) -- 10 (23.025851)
#> 10 (23.025851) -- 11 (26.376848)
#> ...

reeb_graph_pairs(x, method = "multi_pass")
#> Reeb graph critical pairing (2 pairs):
#> 1[a] (0) •- ... -• 4[d] (1)
#> 1[a] (0) -< ... >- 4[d] (1)
#> 
reeb_graph_pairs(y, method = "multi_pass")
#> Reeb graph critical pairing (12 pairs):
#>  1 (  0.000000) •- ... -• 41 (152.25645)
#>  1 (  0.000000) -< ... -• 17 ( 48.16463)
#>  3 (  3.295837) -< ... -•  5 (  8.04719)
#>  7 ( 13.621371) -< ... -• 37 (133.60396)
#> 11 ( 26.376848) -< ... -• 12 ( 29.81888)
#> 15 ( 40.620754) -< ... -• 16 ( 44.36142)
#> 19 ( 55.944340) -< ... -• 20 ( 59.91465)
#> 23 ( 72.116364) -< ... -• 25 ( 80.47189)
#> 27 ( 88.987595) -< ... -• 29 ( 97.65158)
#> 31 (106.453606) -< ... -• 33 (115.38475)
#> 35 (124.437180) -< ... -• 36 (129.00668)
#> 39 (142.878906) -< ... -• 40 (147.55518)
#>