edgel: Read edge list files

edgelR Documentation

Read edge list files

Description

A function to read edge list files with send, receive, and ties format for a multivariate network with the possibility to transform it into an three dimenasional array.

Usage

edgel(file, header = TRUE, sep = "\t", toarray = TRUE, dichot = FALSE, 
      attr = FALSE, rownames = FALSE, add = NULL)

Arguments

file

path to the file

header

(logical) does the file has a header?

sep

the separator among the columns (default is horizontal tab)

toarray

(logical) should the data frame be transformed to arrays?

dichot

(logical) should the data be dichotomized?

attr

(logical) whether or not the file corresponds to attribute-based data

rownames

(logical) are rownames the labels of the nodes?

add

(optional) isolates to be added to the network

Details

edgel is a function to read files with send, receive, and ties format, which is a data frame with at least 2 columns for the sender, receiver and for multiplex networks also the ties, one column for each type of relation. However, the attr option correspond to a actor and self-ties data frame file with the option to transform it into a diagonal matrix. When toarray is set to FALSE, options attr and rownames allow placing the first column of the data frame as the name of the table, which is the format of two-mode data, and compute for instance Galois transformations among the partite sets. If more than one isolate is added, then the data must be included as a vector.

It is also possible to treat the input data as data frame object and manipulate it via e.g. the subset function with the toarray option. Valued networks are now supported as well.

Value

By default an array; usually with three dimensions of stacked matrices where the multiple relations are placed. If toarray = FALSE, then the data frame is given.

Note

For compatibility reasons, alias for edgel is read.srt.

Author(s)

Antonio Rivero Ostoic

See Also

write.edgel, read.gml, read.dl, galois


multiplex documentation built on Nov. 16, 2023, 5:08 p.m.