diffnet-arithmetic: 'diffnet' Arithmetic and Logical Operators

In srdyal/diffusiontest: Analysis of Diffusion and Contagion Processes on Networks

diffnet Arithmetic and Logical Operators

Description

Addition, subtraction, network power of diffnet and logical operators such as & and | as objects

Usage

## S3 method for class 'diffnet'
x ^ y

graph_power(x, y, valued = getOption("diffnet.valued", FALSE))

## S3 method for class 'diffnet'
y / x

## S3 method for class 'diffnet'
x - y

## S3 method for class 'diffnet'
x * y

## S3 method for class 'diffnet'
x & y

## S3 method for class 'diffnet'
x | y

Arguments

x	A diffnet class object.
y	Integer scalar. Power of the network
valued	Logical scalar. When FALSE all non-zero entries of the adjacency matrices are set to one.

Details

Using binary operators, ease data management process with diffnet.

By default the binary operator ^ assumes that the graph is valued, hence the power is computed using a weighted edges. Otherwise, if more control is needed, the user can use graph_power instead.

Value

A diffnet class object

See Also

Other diffnet methods: %*%(), as.array.diffnet(), c.diffnet(), diffnet-class, diffnet_index, plot.diffnet(), summary.diffnet()

Examples

# Computing two-steps away threshold with the Brazilian farmers data --------
data(brfarmersDiffNet)

expo1 <- threshold(brfarmersDiffNet)
expo2 <- threshold(brfarmersDiffNet^2)

# Computing correlation
cor(expo1,expo2)

# Drawing a qqplot
qqplot(expo1, expo2)

# Working with inverse ------------------------------------------------------
brf2_step <- brfarmersDiffNet^2
brf2_step <- 1/brf2_step

# Removing the first 3 vertex of medInnovationsDiffnet ----------------------
data(medInnovationsDiffNet)

# Using a diffnet object
first3Diffnet <- medInnovationsDiffNet[1:3,,]
medInnovationsDiffNet - first3Diffnet

# Using indexes
medInnovationsDiffNet - 1:3

# Using ids
medInnovationsDiffNet - as.character(1001:1003)

srdyal/diffusiontest documentation built on Dec. 9, 2024, 1:14 a.m.