Package 'network.tools'

Drop empty columns

Description

Remove columns from an interaction matrix where all values are zero.

Usage

drop_empty_cols(mat = NULL, na.rm = TRUE)

Arguments

mat	A matrix containing interaction data.
na.rm	Logical. If TRUE, NA values will be ignored for deciding if a column should be removed. If FALSE, columns having NA values will never be removed.

Value

A matrix

Examples

mat <- matrix(c(0,0,0, 1,1,0, 0,0,NA), ncol = 3, byrow = TRUE)
mat
drop_empty_cols(mat)
drop_empty_cols(mat, na.rm = FALSE)

---

Drop empty rows

Description

Remove rows from an interaction matrix where all values are zero.

Usage

drop_empty_rows(mat = NULL, na.rm = TRUE)

Arguments

mat	A matrix containing interaction data.
na.rm	Logical. If TRUE, NA values will be ignored for deciding if a row should be removed. If FALSE, rows having NA values will never be removed.

Value

A matrix

Examples

mat <- matrix(c(0,0,0, 1,1,0, 0,0,NA), ncol = 3, byrow = TRUE)
mat
drop_empty_rows(mat)
drop_empty_rows(mat, na.rm = FALSE)

---

Expand interaction dataset to include zeroes (unobserved interactions)

Description

Expand interaction dataset to include zeroes (unobserved interactions)

Usage

expand_unobs(
  df = NULL,
  plant.var = "Plant",
  animal.var = "Animal",
  int.var = "Visits",
  fill.value = 0
)

Arguments

df	A data frame with interaction presence or frequency data
plant.var	character. Name of the column representing plants.
animal.var	character. Name of the column representing animals.
int.var	character. Name of the column representing interaction presence or frequency.
fill.value	Value to use in int.var for unobserved interactions.

Value

A data frame

Examples

data(web)
df <- web[sample(1:nrow(web), size = 30), ]
df.expand <- expand_unobs(df)

---

Niche width and individual specialisation indices

Description

Calculate indices of niche width and individual specialisation, following Bolnick et al. 2002 (doi:10.1890/0012-9658(2002)083[2936:MILRS]2.0.CO;2).

TNW calculates the Total Niche Width of the population, using Shannon diversity.

WIC calculates the Within-Individual Component of niche width as a weighted average of individuals' Shannon diversity (i.e. the Shannon diversity value of each individual plant is weighted by the proportion of visits or interactions received by that plant). WIC can also return the individual Shannon diversity values, if indiv = TRUE.

indiv_spec returns a data.frame with the following columns:

• WIC (Within-Individual Component)

• TNW (Total Niche Width)

• IndSpec (Individual Specialisation index, calculated as the ratio WIC / TNW).

Usage

indiv_spec(net)

TNW(net)

WIC(net, indiv = FALSE)

Arguments

net	A matrix or data.frame containing interaction data. Plants in rows, Animals in columns. Numbers need not be integers (i.e. counts), can be relative abundances or interaction frequencies.
indiv	Logical. If TRUE, return individual Shannon diversity values. If FALSE, return the weighted average of individual Shannon diversity, weighted by the proportion of interactions represented by each plant (i.e. the WIC).

Value

A numeric value or vector for WIC and TNW, a data.frame in the case of indiv_spec

Note

Ideally net should not contain missing data (NA). If present, they will be ignored.

References

Bolnick DI, LH Yang, JA Fordyce, JM Davis, and Svanback R. 2002. Measuring individual-level resource specialization. Ecology 83: 2936-2941.

See Also

RInSp::WTdMC()

Examples

data(web)
net <- long2wide(web)

indiv_spec(net)
WIC(net)
WIC(net, indiv = TRUE)
TNW(net)

---

Transform interaction data from long to wide format

Description

Transform interaction data from long to wide format

Usage

long2wide(
  df = NULL,
  plant.var = "Plant",
  animal.var = "Animal",
  int.var = "Visits",
  exclude.noint = TRUE,
  fill.value = NA,
  sort = TRUE
)

Arguments

df	A data frame with interaction presence or frequency data
plant.var	character. Name of the column representing plants.
animal.var	character. Name of the column representing animals.
int.var	character. Name of the column representing interaction presence or frequency.
exclude.noint	Logical. Exclude plants/animals with no interactions? Default is TRUE.
fill.value	Value to fill empty cells in the matrix. Default is NA.
sort	Sort matrix rows and columns by frequency?

Value

A matrix with plants and animals as row and column names, respectively.

Examples

data(web)
long2wide(web)

---

Plot bipartite interaction web as a heatmap

Description

Plot bipartite interaction web as a heatmap

Usage

plot_web_heatmap(
  df,
  plant.var = "Plant",
  animal.var = "Animal",
  int.var = "Visits",
  binarize = FALSE,
  sort = TRUE,
  zero.na = TRUE,
  na.colour = "white"
)

Arguments

df	A data frame with interaction presence or frequency data
plant.var	character. Name of the column representing plants.
animal.var	character. Name of the column representing animals.
int.var	character. Name of the column representing interaction presence or frequency.
binarize	Logical. Discretize int.var into two categories? (Default is FALSE).
sort	Logical. If TRUE, sort rows and columns by prevalence to show nestedness.
zero.na	Logical. Show zeros as NA?
na.colour	Colour to be used for NA.

Value

A ggplot object.

Examples

data(web)
plot_web_heatmap(web)
plot_web_heatmap(web, zero.na = FALSE)
plot_web_heatmap(web, sort = FALSE)
plot_web_heatmap(web, binarize = TRUE)

---

Bipartite network

Description

Example data frame containing data for a bipartite web of number of visits from 8 animals to 4 plants.

Usage

web

Format

web

A data frame with 32 rows and 3 columns:

Plant

Plant ID

Animal

Animal ID

Visits

Number of visits

Source

dataset simulated

---

Transform interaction data from wide to long format

Description

Transform interaction data from wide to long format

Usage

wide2long(mat = NULL, int.name = "Visits")

Arguments

mat	A matrix containing interaction data. Plants in rows, Animals in columns.
int.name	character. Column name for the interaction values.

Value

A data frame with three columns: "Plant", "Animal", and interaction values.

Examples

data(web)
mat <- long2wide(web)
mat
df <- wide2long(mat)
df

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