Package 'emln' reference manual

Title:	Organize, Handle, and Explore Ecological Multilayer Networks
Description:	Data and analysis of ecological multilayer networks, including standardization of data structures and functions to convert between them. Includes an interactive multilayer network visualizer (beta, paper forthcoming), and a collection of 78 empirical ecological multilayer network datasets. This work was supported by research grant ISF (Israel Science Foundation) 1281/20 to Shai Pilosof. Noa Frydman (2023) <doi:10.1111/2041-210X.14225>.
Authors:	Noa Frydman [aut], Shai Pilosof [aut, fnd], Shirly Freilikhman [aut], Geut Galai [cre]
Maintainer:	Geut Galai <[email protected]>
License:	CC BY 4.0
Version:	1.2.0
Built:	2026-05-13 14:50:23 UTC
Source:	https://github.com/ecological-complexity-lab/emln

Creates a monolayer network object.

Description

Automatically identifies if the input is a matrix or an edge list and creates a monolayer object.

Usage

create_monolayer_network(
  x,
  directed = NULL,
  bipartite = NULL,
  group_names = c("set_cols", "set_rows"),
  node_metadata = NULL
)
create_monolayer_network(
  x,
  directed = NULL,
  bipartite = NULL,
  group_names = c("set_cols", "set_rows"),
  node_metadata = NULL
)

Arguments

x

input data in the format of a matrix, edge list or an igraph object.

directed

Is the network directed?

bipartite

Is the network bipartite? Ignored when the input is an igraph object.

group_names

For bipartite networks: name of the groups in the columns and rows, respectively (e.g., parasites and hosts).

node_metadata

Following the igraph method of graph_from_data_frame. First column must be have names matching those in x.

Details

Converts between edge list and matrix formats and creates a monolayer object. It a wrapper function for list_to_matrix, matrix_to_list_unipartite, matrix_to_list_bipartite. Node metadata can only be included with an edge list input.

Value

A monolayer object.

Examples

library(igraph)

# A bipartite network from package bipartte
x <- create_monolayer_network(bipartite::memmott1999, bipartite = TRUE,
directed = FALSE, group_names = c('Animals','Plants'))

# A bipartite network as an igraph object

# Generate a random bipartite network in igraph
g <- igraph::sample_bipartite(10,16,p=0.3, type = 'gnp', directed = TRUE, mode = 'in')
V(g)$name <- letters # name the nodes
V(g)$gender <- sample(c('F','M'), size = 26, replace = TRUE) # Add a node attribute
E(g)$weight=runif(ecount(g)) # Add edge weights
plot(g, layout=layout.bipartite)
create_monolayer_network(g, group_names = c('Parasites','Hosts'))




library(igraph)

# A bipartite network from package bipartte
x <- create_monolayer_network(bipartite::memmott1999, bipartite = TRUE,
directed = FALSE, group_names = c('Animals','Plants'))

# A bipartite network as an igraph object

# Generate a random bipartite network in igraph
g <- igraph::sample_bipartite(10,16,p=0.3, type = 'gnp', directed = TRUE, mode = 'in')
V(g)$name <- letters # name the nodes
V(g)$gender <- sample(c('F','M'), size = 26, replace = TRUE) # Add a node attribute
E(g)$weight=runif(ecount(g)) # Add edge weights
plot(g, layout=layout.bipartite)
create_monolayer_network(g, group_names = c('Parasites','Hosts'))

Create Multilayer Network

Description

This function creates a multilayer network from multiple matrices / link lists.

Usage

create_multilayer_network(
  list_of_layers,
  bipartite,
  directed,
  interlayer_links = NULL,
  layer_attributes = NULL,
  state_node_attributes = NULL,
  physical_node_attributes = NULL
)
create_multilayer_network(
  list_of_layers,
  bipartite,
  directed,
  interlayer_links = NULL,
  layer_attributes = NULL,
  state_node_attributes = NULL,
  physical_node_attributes = NULL
)

Arguments

list_of_layers

List of matrices or list of link lists (format from to weight; see description). These are the intralayer links.

bipartite

Is the network bipartite? Must be provided (no default value).

directed

Is the network directed? Must be provided (no default value).

interlayer_links

Interlayer extended edge list of the format layer_from node_from layer_to node_to weight. Default is NULL, assuming no interlayer links.

layer_attributes

Optional. A data frame with layer attributes. The first column must be called layer_id, and it must have unique values (one row per layer). Layer name column, if exists must be called layer_name, and its values must be unique. The order of the rows and layer_id should be the same as in list_of_layers. No column is allowed to be named name.

state_node_attributes

Optional. Additional information on physical nodes in layers. Must contain columns layer_name and node_name.

physical_node_attributes

Optional. Additional information on physical nodes. Must contain column node_name.

Details

Input of list_of_layers is handled by the function create_monolayer_network; see it's description for details on input. If using matrices as input, they should contain row and column names. If link lists are provided as input column names should be from to weight.

When using link lists, it is possible to include link attributes. In that case the headers of all the link lists and, if included, the interlayer links, must be the same (after the weight), even if some attributes are included in only some layers (see detailed example in the code accompanying the package). Missing link attributes can be set to NA.

If interlayer links are provided, then layer_attributes must also be provided. Specify layer and nodes by UNIQUE names (not IDs). Layer names should correspond to those provided in layer_attributes.

Attributes of state nodes can be provided with state_node_attributes. If provided, then columns layer_name and node_name must be included.

For compatibility with function load_emln the output contains description and references. The value of any missing data frames in the multilayer object will be set to NULL.

See multiple example in the code accompanying the package

Value

A multilayer object (see ?multilayer).

Examples

library(tibble)
pond_1 <- matrix(c(0,1,1,0,0,1,0,0,0), byrow = TRUE,
nrow = 3, ncol = 3, dimnames = list(c('pelican','fish','crab'),
c('pelican','fish','crab')))
pond_2 <- matrix(c(0,1,0,0,0,1,0,0,0), byrow = TRUE,
nrow = 3, ncol = 3, dimnames = list(c('pelican','fish','crab'),
c('pelican','fish','crab')))
pond_3 <- matrix(c(0,1,1,0,0,1,0,0,0), byrow = TRUE,
nrow = 3, ncol = 3, dimnames = list(c('pelican','fish','tadpole'),
c('pelican','fish','tadpole')))

layer_attrib <- tibble(layer_id=1:3,
                       layer_name=c('pond_1','pond_2','pond_3'),
                       location=c('valley','mid-elevation','uphill'))

# Create the ELL tibble with interlayer links.
interlayer <- tibble(layer_from=c('pond_1','pond_1','pond_1'),
                     node_from=c('pelican','crab','pelican'),
                     layer_to=c('pond_2','pond_2','pond_3'),
                    node_to=c('pelican','crab','pelican'),
                     weight=1)

# This is a directed network so the links should go both ways,
# even though they are symmetric.
interlayer_2 <- interlayer[,c(3,4,1,2,5)]
names(interlayer_2) <- names(interlayer)
interlayer <- rbind(interlayer, interlayer_2)

multilayer <- create_multilayer_network(list_of_layers =
list(pond_1, pond_2, pond_3), layer_attributes = layer_attrib,
interlayer_links = interlayer, bipartite = FALSE, directed = TRUE)

library(tibble)
pond_1 <- matrix(c(0,1,1,0,0,1,0,0,0), byrow = TRUE,
nrow = 3, ncol = 3, dimnames = list(c('pelican','fish','crab'),
c('pelican','fish','crab')))
pond_2 <- matrix(c(0,1,0,0,0,1,0,0,0), byrow = TRUE,
nrow = 3, ncol = 3, dimnames = list(c('pelican','fish','crab'),
c('pelican','fish','crab')))
pond_3 <- matrix(c(0,1,1,0,0,1,0,0,0), byrow = TRUE,
nrow = 3, ncol = 3, dimnames = list(c('pelican','fish','tadpole'),
c('pelican','fish','tadpole')))

layer_attrib <- tibble(layer_id=1:3,
                       layer_name=c('pond_1','pond_2','pond_3'),
                       location=c('valley','mid-elevation','uphill'))

# Create the ELL tibble with interlayer links.
interlayer <- tibble(layer_from=c('pond_1','pond_1','pond_1'),
                     node_from=c('pelican','crab','pelican'),
                     layer_to=c('pond_2','pond_2','pond_3'),
                    node_to=c('pelican','crab','pelican'),
                     weight=1)

# This is a directed network so the links should go both ways,
# even though they are symmetric.
interlayer_2 <- interlayer[,c(3,4,1,2,5)]
names(interlayer_2) <- names(interlayer)
interlayer <- rbind(interlayer, interlayer_2)

multilayer <- create_multilayer_network(list_of_layers =
list(pond_1, pond_2, pond_3), layer_attributes = layer_attrib,
interlayer_links = interlayer, bipartite = FALSE, directed = TRUE)

View the data sets

Description

@format Data set of multilayer networks

Usage

descriptions
descriptions

Format

An object of class tbl_df (inherits from tbl, data.frame) with 89 rows and 10 columns.

Details

@source create

@examples data(descriptions)

Convert a multilayer class to a a list of igraph objects

Description

This function creates a list of igraph objects from the network layers. Interlayer links are not included.

Usage

get_igraph(multilayer, bipartite, directed)
get_igraph(multilayer, bipartite, directed)

Arguments

multilayer

The multilayer object.

bipartite

Is the network bipartite? Must be provided (no default value).

directed

Is the network directed? Must be provided (no default value).

Details

If link, physical node or state node attributes are included in the multilayer network they are passed to the igraph objects.

Value

A list:

layers_igraph A list of igraph objects, one per layer
nodes A table of physical nodes, as in the multlayer object.
state_nodes_map A table with state nodes to map the nodes to the row and columns of a SAM.

Examples


# See examples in:
# https://emln.ecomplab.com/multilayer.html#To_igraph_objects

# See examples in:
# https://emln.ecomplab.com/multilayer.html#To_igraph_objects

Convert a multilayer class to a supra-adjacency matrix

Description

This function creates a supra-adjacency matrix from a multilayer object.

Usage

get_sam(
  multilayer,
  bipartite,
  directed,
  sparse = FALSE,
  remove_zero_rows_cols = FALSE
)
get_sam(
  multilayer,
  bipartite,
  directed,
  sparse = FALSE,
  remove_zero_rows_cols = FALSE
)

Arguments

multilayer

The multilayer object.

bipartite

Is the network bipartite? Must be provided (no default value).

directed

Is the network directed? Must be provided (no default value).

sparse

Should the returned matrix be a sparse matrix (class Matrix)? Defaults to false.

remove_zero_rows_cols

Should rows and columns that sum to 0 be removed? Defaults to false.

Details

By default, a SAM contains all the nodes in all the layers. However, not all nodes always occur in all layers. This will be reflected in the state_nodes_map: When layer and node ids are NA that means that the node did not occur in the layer.

A node may not have links across all the layers. In that case, its row or column sum will be zero. This can happen in a directed matrix (see toy example for unipartite network), or in diagonally-coupled networks (see toy bipartite example). The user can choose to remove rows and columns that sum to zero by setting remove_zero_rows_cols to TRUE.

Value

A list:

M The SAM. Can also be sparse.
nodes A table of physical nodes, as in the multlayer object.
state_nodes_map A table with state nodes to map the nodes to the row and columns of the SAM.

Examples


# See examples in:
# https://emln.ecomplab.com/multilayer.html#To_supra-adjacency_matrices

# See examples in:
# https://emln.ecomplab.com/multilayer.html#To_supra-adjacency_matrices

Edge list to matrix conversion

Description

Convert an edge list to a matrix. Can handle unipartite and bipartite networks.

Usage

list_to_matrix(
  x,
  directed = FALSE,
  bipartite = TRUE,
  group_names = c("set_cols", "set_rows"),
  node_metadata = NULL
)
list_to_matrix(
  x,
  directed = FALSE,
  bipartite = TRUE,
  group_names = c("set_cols", "set_rows"),
  node_metadata = NULL
)

Arguments

x

An edge list of the format from to weight.

directed

Is the network directed?

bipartite

Is network bipartite?

group_names

For bipartite networks: name of the groups in the columns and rows, respectively (e.g., parasites and hosts).

node_metadata

Following the igraph method of graph_from_data_frame. Must have a column called node_name with names matching those in x.

Details

It is also possible to add node attributes. For this, it uses igraph. The first column in the node_metadata data frame should have the names of the nodes in the edge list.

Value

A monolayer object.

Examples

library(dplyr)
network <- load_emln(17)
nodes <- network$nodes
links<-subset(network$extended_ids %>% filter(layer_from==1), select=c(node_from, node_to, weight))

list_to_matrix(links, directed = TRUE, bipartite = FALSE, node_metadata = nodes)


# See examples in:
# https://emln.ecomplab.com/monolayer.html#Unipartite

library(dplyr)
network <- load_emln(17)
nodes <- network$nodes
links<-subset(network$extended_ids %>% filter(layer_from==1), select=c(node_from, node_to, weight))

list_to_matrix(links, directed = TRUE, bipartite = FALSE, node_metadata = nodes)


# See examples in:
# https://emln.ecomplab.com/monolayer.html#Unipartite

Load networks include din the package

Description

Load a specific network by specifying its ID.

Usage

load_emln(network_id)
load_emln(network_id)

Arguments

network_id

The network ID.

Details

Use the search_emln and view_emln functions to obtain network IDs.

Value

A multilayer object (see ?multilayer).

Examples


load_emln(network_id = 38)


load_emln(network_id = 38)

Incidence matrix to edge list conversion

Description

Convert an incidence matrix to an edge list.

Usage

matrix_to_list_bipartite(x, group_names = c("set_cols", "set_rows"))
matrix_to_list_bipartite(x, group_names = c("set_cols", "set_rows"))

Arguments

x

An incidence matrix.

group_names

Name of the groups in the columns and rows, respectively (e.g., parasites and hosts).

Details

Assigns column and row names if those do not exist. Cannot handle node attributes/metadata. Always assumes an undirected network.

Value

A monolayer object.

Examples


# See examples in: https://emln.ecomplab.com/monolayer.html#Bipartite

matrix_to_list_bipartite(bipartite::memmott1999, group_names = c('Animals', 'Plants'))

# See examples in: https://emln.ecomplab.com/monolayer.html#Bipartite

matrix_to_list_bipartite(bipartite::memmott1999, group_names = c('Animals', 'Plants'))

Adjacency matrix to edge list conversion

Description

Convert an adjacency matrix to an edge list.

Usage

matrix_to_list_unipartite(x, directed)
matrix_to_list_unipartite(x, directed)

Arguments

x

An adjacency or incidence matrix.

directed

Is the network directed? TRUE/FALSE

Details

Assigns column and row names if those do not exist. Cannot handle node attributes/metadata.

Value

A monolayer object

Examples

# See examples in:
# https://emln.ecomplab.com/monolayer.html#Unipartite

# Generate a matrix with random weighted interactions
x <- matrix(rbinom(100,1,0.6),10,10)
x <- x*round(runif(100,1,5),0)
# run
matrix_to_list_unipartite(x, directed = TRUE)

# See examples in:
# https://emln.ecomplab.com/monolayer.html#Unipartite

# Generate a matrix with random weighted interactions
x <- matrix(rbinom(100,1,0.6),10,10)
x <- x*round(runif(100,1,5),0)
# run
matrix_to_list_unipartite(x, directed = TRUE)

An object of class monolayer

Description

A network object of class monolayer contains all the necessary information and R objects to perform future analyses on a monolayer network, and in particular analyses using Infomap.

Value

A list with:

mode: bipartite (B) or unipartite (U)
directed: TRUE/FALSE
nodes: a tibble with information on the nodes (name, id, type, other attributes)
mat: the network in a matrix format
edge_list: the network in an edge list format
igraph_object: the igraph object of the network

An object of class multilayer

Description

A network object of class multilayer contains all the necessary information and R objects that define a multilayer network.

Value

A list with:

nodes Physical nodes. First column is a unique node id. Node attributes are included if provided as input.
layers Information on layers.
extended An extended link list of the format layer_from node_from layer_to node_to weight. All nodes and layers are identified by names.
extended_ids An extended link list of the format layer_from node_from layer_to node_to weight. All nodes and layers are identified by unique IDs automoatically generated.
state_nodes List of state nodes of the format layer_id node_id layer_name node_name. Also includes state node attributes if provided as input.
description For compatibility with load_emln.
references For compatibility with load_emln.

Export a multilayer network to CSV files

Description

Writes an EMLN multilayer object as a set of CSV files consumed by MiRA's CSV importer. Three files are always written; a fourth (<prefix>_state_nodes.csv) is added when per-(layer, node) attributes are present.

Usage

multilayer_to_csv(
  multilayer,
  dir,
  prefix = "network",
  bipartite = FALSE,
  setA_type = NULL,
  directed = NULL
)
multilayer_to_csv(
  multilayer,
  dir,
  prefix = "network",
  bipartite = FALSE,
  setA_type = NULL,
  directed = NULL
)

Arguments

multilayer

A multilayer object (created by create_multilayer_network or load_emln).

dir

Directory to write the CSV files to. Created if it does not already exist.

prefix

Character. File name prefix. Defaults to "network". Three files are always written: <prefix>_edges.csv, <prefix>_layers.csv, <prefix>_nodes.csv. A fourth file <prefix>_state_nodes.csv is written when the multilayer object contains per-(layer, node) attributes beyond layer_name and node_name (e.g. abundance, module).

bipartite

Logical. Whether the network is bipartite. Defaults to FALSE. When TRUE, the nodes table must contain a node_type (or legacy node_group) column with exactly two distinct values across the network, and a bipartite column is written to the layers CSV.

setA_type

Optional character. The node_type value to render as Set A (top row) in MiRA's bipartite layout. By ecological convention this is the higher trophic level (e.g. "pollinator", "parasite", "disperser"). Only used when bipartite = TRUE; written as a setA_type column in the layers CSV. If NULL (default), MiRA falls back to alphabetical ordering of the two types.

directed

Logical or NULL. Whether the network is directed. If NULL (default), auto-detected by checking intralayer edge symmetry.

Details

The CSV files follow the schema accepted by MiRA's CSV importer:

edges: layer_from, node_from, layer_to, node_to, weight (+ any extra link attributes).
layers: layer_id, layer_name (+ latitude, longitude, bipartite and any extra layer attributes).
nodes: node_name (+ node_type and any extra physical node attributes, same across all layers). node_group is renamed to node_type.
state_nodes (written only when extra per-(layer, node) attributes exist): layer_name, node_name + extra columns. Use this when the same node has different attribute values in different layers (e.g. abundance, module membership).

The directed flag is not written to the CSV files; it is a property you specify in MiRA's CSV import dialog at load time.

Value

Invisibly returns a named character vector of file paths written (edges, layers, nodes, and optionally state_nodes).

Note

MiRA (Multilayer Interactive Rendering Application) is a browser-based interactive visualization tool for multilayer networks, available at https://mira.ecomplab.com/.

If you use MiRA in published research, please cite:

Nehoray SM, Bloch Y, Pilosof S (2026). Interactively visualizing biological multilayer networks using MiRA. arXiv:2605.09597 [cs.SI]. doi:10.48550/arXiv.2605.09597

Feedback and bug reports: https://github.com/Ecological-Complexity-Lab/MiRA/issues.

Examples


net <- load_emln(14)
multilayer_to_csv(net, dir = "tests/out/", prefix = "kefi", bipartite = TRUE)

net <- load_emln(14)
multilayer_to_csv(net, dir = "tests/out/", prefix = "kefi", bipartite = TRUE)

Export a multilayer network to JSON

Description

Converts an EMLN multilayer object to JSON format compatible with MiRA, the multilayer interactive R-network app.

Usage

multilayer_to_json(
  multilayer,
  file = NULL,
  bipartite = FALSE,
  setA_type = NULL,
  directed = NULL,
  directed_interlayer = NULL
)
multilayer_to_json(
  multilayer,
  file = NULL,
  bipartite = FALSE,
  setA_type = NULL,
  directed = NULL,
  directed_interlayer = NULL
)

Arguments

multilayer

A multilayer object (created by create_multilayer_network or load_emln).

file

Optional file path to write the JSON to. If NULL, returns the JSON string.

bipartite

Logical. Whether the network is bipartite. Defaults to FALSE. MiRA does not auto-detect bipartite structure — you must set this to TRUE explicitly. When TRUE, the nodes table must contain a node_type (or legacy node_group) column with exactly two distinct values across the network. Any node_group column is renamed to node_type in the output regardless of the bipartite flag (MiRA's canonical name).

setA_type

Optional character. The node_type value to render as Set A (top row) in MiRA's bipartite layout. By ecological convention this is the higher trophic level (e.g. "pollinator", "parasite", "disperser"). Only used when bipartite = TRUE. If NULL (default), MiRA falls back to alphabetical ordering of the two types.

directed

Logical or NULL. Whether intralayer links are directed. If NULL (default), auto-detected by checking intralayer edge symmetry.

directed_interlayer

Logical or NULL. Whether interlayer links are directed. If NULL (default), inherits from directed (matching MiRA's parser behavior). Set explicitly when intra- and interlayer directionality differ.

Details

The JSON output contains four arrays matching MiRA's expected format:

nodes: Physical nodes with node_id, node_name, and any extra attributes. For bipartite networks, node_group is mapped to node_type.
layers: Layer metadata with layer_id, layer_name, and extra attributes. For bipartite networks, a bipartite: true flag is added; if setA_type is given it is also written per layer.
extended: The extended edge list with layer_from, node_from, layer_to, node_to, weight, and any link attributes.
state_nodes: State node map with layer_id, node_id, layer_name, node_name, plus any extra per-(layer, node) attributes (e.g. abundance, module).

Top-level flags directed and (when set) directed_interlayer indicate edge directionality globally; they are not repeated per link.

Value

If file is NULL, returns the JSON string invisibly. If file is specified, writes JSON to disk and returns the file path invisibly.

Note

MiRA (Multilayer Interactive Rendering Application) is a browser-based interactive visualization tool for multilayer networks, available at https://mira.ecomplab.com/.

If you use MiRA in published research, please cite:

Nehoray SM, Bloch Y, Pilosof S (2026). Interactively visualizing biological multilayer networks using MiRA. arXiv:2605.09597 [cs.SI]. doi:10.48550/arXiv.2605.09597

Feedback and bug reports: https://github.com/Ecological-Complexity-Lab/MiRA/issues.

Examples


# Export to file
net <- load_emln(14)
multilayer_to_json(net, file = "tests/my_network.json", bipartite = TRUE)

# Bipartite with explicit Set A ordering
multilayer_to_json(net, bipartite = TRUE, setA_type = "pollinator")

# Get JSON string
json_str <- multilayer_to_json(net)

# Export to file
net <- load_emln(14)
multilayer_to_json(net, file = "tests/my_network.json", bipartite = TRUE)

# Bipartite with explicit Set A ordering
multilayer_to_json(net, bipartite = TRUE, setA_type = "pollinator")

# Get JSON string
json_str <- multilayer_to_json(net)

Plot a multilayer network in the browser

Description

Converts an EMLN multilayer object to JSON and opens MiRA, the multilayer interactive R-network app, in the default web browser.

Usage

plot_multilayer(
  multilayer,
  bipartite = FALSE,
  setA_type = NULL,
  directed = NULL,
  directed_interlayer = NULL,
  port = 8080,
  mira_path = NULL,
  browser = getOption("browser")
)
plot_multilayer(
  multilayer,
  bipartite = FALSE,
  setA_type = NULL,
  directed = NULL,
  directed_interlayer = NULL,
  port = 8080,
  mira_path = NULL,
  browser = getOption("browser")
)

Arguments

multilayer

A multilayer object (created by create_multilayer_network or load_emln).

bipartite

Logical. Whether the network is bipartite. Defaults to FALSE. Bipartite is not auto-detected. When TRUE, the nodes table must contain a node_type (or legacy node_group) column with exactly two distinct values across the network.

setA_type

directed

Logical or NULL. Whether intralayer links are directed. If NULL (default), auto-detected by checking intralayer edge symmetry.

directed_interlayer

Logical or NULL. Whether interlayer links are directed. If NULL (default), inherits from directed.

port

Integer. Port for the local HTTP server. Default is 8080.

mira_path

Character. Path to the MiRA web-app directory. If NULL (default), uses the copy bundled with the package (system.file("MiRA", package = "emln")).

browser

Choose the specific browser to open MiRA in. Defaults to the system default via getOption("browser"). Can be a browser name (e.g. "chrome", "firefox") or a command (e.g. "open -a 'Google Chrome'").

Details

The function:

Converts the multilayer object to JSON via multilayer_to_json
Starts a local HTTP server (using httpuv) that serves the MiRA app and the network JSON
Opens the browser with auto-load enabled

The server runs in the background. Call httpuv::stopServer(handle) or close R to stop it. The JSON data is kept in memory and never written to disk.

Value

Invisibly returns the server handle. Use httpuv::stopServer(handle) to stop the server when done.

Note

MiRA (Multilayer Interactive Rendering Application) is a browser-based interactive visualization tool for multilayer networks, available at https://mira.ecomplab.com/.

If you use MiRA in published research, please cite:

Nehoray SM, Bloch Y, Pilosof S (2026). Interactively visualizing biological multilayer networks using MiRA. arXiv:2605.09597 [cs.SI]. doi:10.48550/arXiv.2605.09597

Feedback and bug reports: https://github.com/Ecological-Complexity-Lab/MiRA/issues.

Examples

if (interactive()){
net <- load_emln(60)
srv <- plot_multilayer(net, bipartite = TRUE, setA_type = "pollinator")

# When done:
httpuv::stopServer(srv)
}
if (interactive()){
net <- load_emln(60)
srv <- plot_multilayer(net, bipartite = TRUE, setA_type = "pollinator")

# When done:
httpuv::stopServer(srv)
}

Search networks

Description

Search the database for networks depending on search parameters specified below.

Usage

search_emln(
  ecological_network_type = NULL,
  multilayer_network_type = NULL,
  state_nodes = NULL,
  node_number_minimum = NULL,
  layer_number_minimum = NULL,
  weighted = NULL,
  interlayer = NULL,
  directed = NULL
)
search_emln(
  ecological_network_type = NULL,
  multilayer_network_type = NULL,
  state_nodes = NULL,
  node_number_minimum = NULL,
  layer_number_minimum = NULL,
  weighted = NULL,
  interlayer = NULL,
  directed = NULL
)

Arguments

ecological_network_type

One of: Seed-Dispersal, Pollination, Food-Web, Host-Parasite, Multiple, Plant-Herbivore, Anemone-Fish, Plant-Ant

multilayer_network_type

Environment, Temporal, Multiplex, Perturbation, Spatial

state_nodes

TRUE/FALSE

node_number_minimum

The minimum number of layers wanted in the network

layer_number_minimum

The minimum number of layers wanted in the network

weighted

TRUE/FALSE

interlayer

TRUE/FALSE

directed

TRUE/FALSE

Value

A tibble containing the network id, and all the search arguments for each of the networks that are compatible with the search.

Examples

# See examples in:
# https://emln.ecomplab.com/data.html#Browsing_the_data

# Generates a tibble of all the networks in the package that are pollination networks
search_emln(ecological_network_type = 'Plant-Ant')

# Generates a tibble of all the networks in the package that have state nodes and are temporal
search_emln(multilayer_network_type = 'Temporal', state_node = TRUE)

# See examples in:
# https://emln.ecomplab.com/data.html#Browsing_the_data

# Generates a tibble of all the networks in the package that are pollination networks
search_emln(ecological_network_type = 'Plant-Ant')

# Generates a tibble of all the networks in the package that have state nodes and are temporal
search_emln(multilayer_network_type = 'Temporal', state_node = TRUE)

View networks

Description

View the database interactively.

Usage

view_emln()
view_emln()

Value

An interactive GUI for browinsg through networks.

Package 'emln'

Help Index

Creates a monolayer network object.

Description

Usage

Arguments

Details

Value

See Also

Examples

Create Multilayer Network

Description

Usage

Arguments

Details

Value

See Also

Examples

View the data sets

Description

Usage

Format

Details

Convert a multilayer class to a a list of igraph objects

Description

Usage

Arguments

Details

Value

Examples

Convert a multilayer class to a supra-adjacency matrix

Description

Usage

Arguments

Details

Value

Examples

Edge list to matrix conversion

Description

Usage

Arguments

Details

Value

See Also

Examples

Load networks include din the package

Description

Usage

Arguments

Details

Value

See Also

Examples

Incidence matrix to edge list conversion

Description

Usage

Arguments

Details

Value

See Also

Examples

Adjacency matrix to edge list conversion

Description

Usage

Arguments

Details

Value

See Also

Examples

An object of class monolayer

Description

Value

See Also

An object of class multilayer

Description

Value

See Also

Export a multilayer network to CSV files

Description

Usage